UTDallas Offline Computing System for B Physics with the Babar Experiment at SLAC

NASA Astrophysics Data System (ADS)

Benninger, Tracy L.

1998-10-01

The University of Texas at Dallas High Energy Physics group is building a high performance, large storage computing system for B physics research with the BaBar experiment (``factory'') at the Stanford Linear Accelerator Center. The goal of this system is to analyze one terabyte of complex Event Store data from BaBar in one to two days. The foundation of the computing system is a Sun E6000 Enterprise multiprocessor system, with additions of a Sun StorEdge L1800 Tape Library, a Sun Workstation for processing batch jobs, staging disks and interface cards. The design considerations, current status, projects underway, and possible upgrade paths will be discussed.

A Java Program for the Viewing of Ambient Data

DOE Office of Scientific and Technical Information (OSTI.GOV)

Fisher, A.

2004-09-03

The BaBar detector system has a large number of sensors and data feeds, called ambient feeds. These feeds are vital to the operation and monitoring of the Pep rings and the BaBar system. In order to more easily monitor these systems a simple web interface to display graphical representations of the data is needed. Towards this end it was decided that using a Java Web Servlet (Sun Microsystems) would be an effective and simple way to achieve this effect. By combining Web Servlets with the Corba Technology (OMG) this provides a way for many people to access data from anywheremore » in the world. Using this type of program in conjunction with the HEP AIDA systems for graphing makes a powerful tool for the monitoring of the BaBar system. An overview of the BaBar system, and how the Ambient data is given. The uses and limitations of this method for viewing the data as well as examples of other ways to access the data and potential other uses for the servlet are also discussed.« less

The BABAR detector: Upgrades, operation and performance

NASA Astrophysics Data System (ADS)

Aubert, B.; Barate, R.; Boutigny, D.; Couderc, F.; del Amo Sanchez, P.; Gaillard, J.-M.; Hicheur, A.; Karyotakis, Y.; Lees, J. P.; Poireau, V.; Prudent, X.; Robbe, P.; Tisserand, V.; Zghiche, A.; Grauges, E.; Garra Tico, J.; Lopez, L.; Martinelli, M.; Palano, A.; Pappagallo, M.; Pompili, A.; Chen, G. P.; Chen, J. C.; Qi, N. D.; Rong, G.; Wang, P.; Zhu, Y. S.; Eigen, G.; Stugu, B.; Sun, L.; Abrams, G. S.; Battaglia, M.; Borgland, A. W.; Breon, A. B.; Brown, D. N.; Button-Shafer, J.; Cahn, R. N.; Charles, E.; Clark, A. R.; Day, C. T.; Furman, M.; Gill, M. S.; Groysman, Y.; Jacobsen, R. G.; Kadel, R. W.; Kadyk, J. A.; Kerth, L. T.; Kolomensky, Yu. G.; Kral, J. F.; Kukartsev, G.; LeClerc, C.; Levi, M. E.; Lynch, G.; Merchant, A. M.; Mir, L. M.; Oddone, P. J.; Orimoto, T. J.; Osipenkov, I. L.; Pripstein, M.; Roe, N. A.; Romosan, A.; Ronan, M. T.; Shelkov, V. G.; Suzuki, A.; Tackmann, K.; Tanabe, T.; Wenzel, W. A.; Zisman, M.; Barrett, M.; Bright-Thomas, P. G.; Ford, K. E.; Harrison, T. J.; Hart, A. J.; Hawkes, C. M.; Knowles, D. J.; Morgan, S. E.; O'Neale, S. W.; Penny, R. C.; Smith, D.; Soni, N.; Watson, A. T.; Watson, N. K.; Goetzen, K.; Held, T.; Koch, H.; Kunze, M.; Lewandowski, B.; Pelizaeus, M.; Peters, K.; Schmuecker, H.; Schroeder, T.; Steinke, M.; Fella, A.; Antonioli, E.; Boyd, J. T.; Chevalier, N.; Cottingham, W. N.; Foster, B.; Mackay, C.; Walker, D.; Abe, K.; Asgeirsson, D. J.; Cuhadar-Donszelmann, T.; Fulsom, B. G.; Hearty, C.; Knecht, N. S.; Mattison, T. S.; McKenna, J. A.; Thiessen, D.; Khan, A.; Kyberd, P.; McKemey, A. K.; Randle-Conde, A.; Saleem, M.; Sherwood, D. J.; Teodorescu, L.; Blinov, V. E.; Bukin, A. D.; Buzykaev, A. R.; Druzhinin, V. P.; Golubev, V. B.; Korol, A. A.; Kravchenko, E. A.; Onuchin, A. P.; Serednyakov, S. I.; Skovpen, Yu. I.; Solodov, E. P.; Telnov, V. I.; Todyshev, K. Yu.; Yushkov, A. N.; Best, D. S.; Bondioli, M.; Bruinsma, M.; Chao, M.; Curry, S.; Eschrich, I.; Kirkby, D.; Lankford, A. J.; Mandelkern, M.; Martin, E. C.; McMahon, S.; Mommsen, R. K.; Stoker, D. P.; Abachi, S.; Buchanan, C.; Hartfiel, B. L.; Weinstein, A. J. R.; Atmacan, H.; Foulkes, S. D.; Gary, J. W.; Layter, J.; Liu, F.; Long, O.; Shen, B. C.; Vitug, G. M.; Wang, K.; Yasin, Z.; Zhang, L.; Hadavand, H. K.; Hill, E. J.; Paar, H. P.; Rahatlou, S.; Schwanke, U.; Sharma, V.; Berryhill, J. W.; Campagnari, C.; Cunha, A.; Dahmes, B.; Hong, T. M.; Kovalskyi, D.; Kuznetsova, N.; Levy, S. L.; Lu, A.; Mazur, M. A.; Richman, J. D.; Verkerke, W.; Beck, T. W.; Beringer, J.; Eisner, A. M.; Flacco, C. J.; Grillo, A. A.; Grothe, M.; Heusch, C. A.; Kroseberg, J.; Lockman, W. S.; Martinez, A. J.; Nesom, G.; Schalk, T.; Schmitz, R. E.; Schumm, B. A.; Seiden, A.; Spencer, E.; Spradlin, P.; Turri, M.; Walkowiak, W.; Wang, L.; Wilder, M.; Williams, D. C.; Wilson, M. G.; Winstrom, L. O.; Chen, E.; Cheng, C. H.; Doll, D. A.; Dorsten, M. P.; Dvoretskii, A.; Echenard, B.; Erwin, R. J.; Fang, F.; Flood, K.; Hitlin, D. G.; Metzler, S.; Narsky, I.; Oyang, J.; Piatenko, T.; Porter, F. C.; Ryd, A.; Samuel, A.; Yang, S.; Zhu, R. Y.; Andreassen, R.; Devmal, S.; Geld, T. L.; Jayatilleke, S.; Mancinelli, G.; Meadows, B. T.; Mishra, K.; Sokoloff, M. D.; Abe, T.; Antillon, E. A.; Barillari, T.; Becker, J.; Blanc, F.; Bloom, P. C.; Chen, S.; Clifton, Z. C.; Derrington, I. M.; Destree, J.; Dima, M. O.; Ford, W. T.; Gaz, A.; Gilman, J. D.; Hachtel, J.; Hirschauer, J. F.; Johnson, D. R.; Kreisel, A.; Nagel, M.; Nauenberg, U.; Olivas, A.; Rankin, P.; Roy, J.; Ruddick, W. O.; Smith, J. G.; Ulmer, K. A.; van Hoek, W. C.; Wagner, S. R.; West, C. G.; Zhang, J.; Ayad, R.; Blouw, J.; Chen, A.; Eckhart, E. A.; Harton, J. L.; Hu, T.; Toki, W. H.; Wilson, R. J.; Winklmeier, F.; Zeng, Q. L.; Altenburg, D.; Feltresi, E.; Hauke, A.; Jasper, H.; Karbach, M.; Merkel, J.; Petzold, A.; Spaan, B.; Wacker, K.; Brandt, T.; Brose, J.; Colberg, T.; Dahlinger, G.; Dickopp, M.; Eckstein, P.; Futterschneider, H.; Kaiser, S.; Kobel, M. J.; Krause, R.; Müller-Pfefferkorn, R.; Mader, W. F.; Maly, E.; Nogowski, R.; Otto, S.; Schubert, J.; Schubert, K. R.; Schwierz, R.; Sundermann, J. E.; Volk, A.; Wilden, L.; Bernard, D.; Brochard, F.; Cohen-Tanugi, J.; Dohou, F.; Ferrag, S.; Latour, E.; Mathieu, A.; Renard, C.; Schrenk, S.; T'Jampens, S.; Thiebaux, Ch.; Vasileiadis, G.; Verderi, M.; Anjomshoaa, A.; Bernet, R.; Clark, P. J.; Lavin, D. R.; Muheim, F.; Playfer, S.; Robertson, A. I.; Swain, J. E.; Watson, J. E.; Xie, Y.; Andreotti, D.; Andreotti, M.; Bettoni, D.; Bozzi, C.; Calabrese, R.; Carassiti, V.; Cecchi, A.; Cibinetto, G.; Cotta Ramusino, A.; Evangelisti, F.; Fioravanti, E.; Franchini, P.; Garzia, I.; Landi, L.; Luppi, E.; Malaguti, R.; Negrini, M.; Padoan, C.; Petrella, A.; Piemontese, L.; Santoro, V.; Sarti, A.; Anulli, F.; Baldini-Ferroli, R.; Calcaterra, A.; Finocchiaro, G.; Pacetti, S.; Patteri, P.; Peruzzi, I. M.; Piccolo, M.; Rama, M.; de Sangro, R.; Santoni, M.; Zallo, A.; Bagnasco, S.; Buzzo, A.; Capra, R.; Contri, R.; Crosetti, G.; Lo Vetere, M.; Macri, M. M.; Minutoli, S.; Monge, M. R.; Musico, P.; Passaggio, S.; Pastore, F. C.; Patrignani, C.; Pia, M. G.; Robutti, E.; Santroni, A.; Tosi, S.; Bhuyan, B.; Prasad, V.; Bailey, S.; Brandenburg, G.; Chaisanguanthum, K. S.; Lee, C. L.; Morii, M.; Won, E.; Wu, J.; Adametz, A.; Dubitzky, R. S.; Marks, J.; Schenk, S.; Uwer, U.; Klose, V.; Lacker, H. M.; Aspinwall, M. L.; Bhimji, W.; Bowerman, D. A.; Dauncey, P. D.; Egede, U.; Flack, R. L.; Gaillard, J. R.; Gunawardane, N. J. W.; Morton, G. W.; Nash, J. A.; Nikolich, M. B.; Panduro Vazquez, W.; Sanders, P.; Smith, D.; Taylor, G. P.; Tibbetts, M.; Behera, P. K.; Chai, X.; Charles, M. J.; Grenier, G. J.; Hamilton, R.; Lee, S.-J.; Mallik, U.; Meyer, N. T.; Chen, C.; Cochran, J.; Crawley, H. B.; Dong, L.; Eyges, V.; Fischer, P.-A.; Lamsa, J.; Meyer, W. T.; Prell, S.; Rosenberg, E. I.; Rubin, A. E.; Gao, Y. Y.; Gritsan, A. V.; Guo, Z. J.; Lae, C. K.; Schott, G.; Albert, J. N.; Arnaud, N.; Beigbeder, C.; Breton, D.; Davier, M.; Derkach, D.; Dû, S.; Firmino da Costa, J.; Grosdidier, G.; Höcker, A.; Laplace, S.; Le Diberder, F.; Lepeltier, V.; Lutz, A. M.; Malaescu, B.; Nief, J. Y.; Petersen, T. C.; Plaszczynski, S.; Pruvot, S.; Roudeau, P.; Schune, M. H.; Serrano, J.; Sordini, V.; Stocchi, A.; Tocut, V.; Trincaz-Duvoid, S.; Wang, L. L.; Wormser, G.; Bionta, R. M.; Brigljević, V.; Lange, D. J.; Simani, M. C.; Wright, D. M.; Bingham, I.; Burke, J. P.; Chavez, C. A.; Coleman, J. P.; Forster, I. J.; Fry, J. R.; Gabathuler, E.; Gamet, R.; George, M.; Hutchcroft, D. E.; Kay, M.; Parry, R. J.; Payne, D. J.; Schofield, K. C.; Sloane, R. J.; Touramanis, C.; Azzopardi, D. E.; Bellodi, G.; Bevan, A. J.; Clarke, C. K.; Cormack, C. M.; Di Lodovico, F.; Dixon, P.; George, K. A.; Menges, W.; Potter, R. J. L.; Sacco, R.; Shorthouse, H. W.; Sigamani, M.; Strother, P.; Vidal, P. B.; Brown, C. L.; Cowan, G.; Flaecher, H. U.; George, S.; Green, M. G.; Hopkins, D. A.; Jackson, P. S.; Kurup, A.; Marker, C. E.; McGrath, P.; McMahon, T. R.; Paramesvaran, S.; Salvatore, F.; Vaitsas, G.; Winter, M. A.; Wren, A. C.; Brown, D. N.; Davis, C. L.; Denig, A. G.; Fritsch, M.; Gradl, W.; Griessinger, K.; Hafner, A.; Prencipe, E.; Allison, J.; Alwyn, K. E.; Bailey, D. S.; Barlow, N. R.; Barlow, R. J.; Chia, Y. M.; Edgar, C. L.; Forti, A. C.; Fullwood, J.; Hart, P. A.; Hodgkinson, M. C.; Jackson, F.; Jackson, G.; Kelly, M. P.; Kolya, S. D.; Lafferty, G. D.; Lyon, A. J.; Naisbit, M. T.; Savvas, N.; Weatherall, J. H.; West, T. J.; Williams, J. C.; Yi, J. I.; Anderson, J.; Farbin, A.; Hulsbergen, W. D.; Jawahery, A.; Lillard, V.; Roberts, D. A.; Schieck, J. R.; Simi, G.; Tuggle, J. M.; Blaylock, G.; Dallapiccola, C.; Hertzbach, S. S.; Kofler, R.; Koptchev, V. B.; Li, X.; Moore, T. B.; Salvati, E.; Saremi, S.; Staengle, H.; Willocq, S. Y.; Cowan, R.; Dujmic, D.; Fisher, P. H.; Henderson, S. W.; Koeneke, K.; Lang, M. I.; Sciolla, G.; Spitznagel, M.; Taylor, F.; Yamamoto, R. K.; Yi, M.; Zhao, M.; Zheng, Y.; Klemetti, M.; Lindemann, D.; Mangeol, D. J. J.; Mclachlin, S. E.; Milek, M.; Patel, P. M.; Robertson, S. H.; Biassoni, P.; Cerizza, G.; Lazzaro, A.; Lombardo, V.; Neri, N.; Palombo, F.; Pellegrini, R.; Stracka, S.; Bauer, J. M.; Cremaldi, L.; Eschenburg, V.; Kroeger, R.; Reidy, J.; Sanders, D. A.; Summers, D. J.; Zhao, H. W.; Godang, R.; Brunet, S.; Cote, D.; Nguyen, X.; Simard, M.; Taras, P.; Viaud, B.; Nicholson, H.; Cavallo, N.; De Nardo, G.; Fabozzi, F.; Gatto, C.; Lista, L.; Monorchio, D.; Onorato, G.; Paolucci, P.; Piccolo, D.; Sciacca, C.; Baak, M. A.; Raven, G.; Snoek, H. L.; Jessop, C. P.; Knoepfel, K. J.; LoSecco, J. M.; Wang, W. F.; Allmendinger, T.; Benelli, G.; Brau, B.; Corwin, L. A.; Gan, K. K.; Honscheid, K.; Hufnagel, D.; Kagan, H.; Kass, R.; Morris, J. P.; Rahimi, A. M.; Regensburger, J. J.; Smith, D. S.; Ter-Antonyan, R.; Wong, Q. K.; Blount, N. L.; Brau, J.; Frey, R.; Igonkina, O.; Iwasaki, M.; Kolb, J. A.; Lu, M.; Potter, C. T.; Rahmat, R.; Sinev, N. B.; Strom, D.; Strube, J.; Torrence, E.; Borsato, E.; Castelli, G.; Colecchia, F.; Crescente, A.; Dal Corso, F.; Dorigo, A.; Fanin, C.; Furano, F.; Gagliardi, N.; Galeazzi, F.; Margoni, M.; Marzolla, M.; Michelon, G.; Morandin, M.; Posocco, M.; Rotondo, M.; Simonetto, F.; Solagna, P.; Stevanato, E.; Stroili, R.; Tiozzo, G.; Voci, C.; Akar, S.; Bailly, P.; Ben-Haim, E.; Bonneaud, G.; Briand, H.; Chauveau, J.; Hamon, O.; John, M. J. J.; Lebbolo, H.; Leruste, Ph.; Malclès, J.; Marchiori, G.; Martin, L.; Ocariz, J.; Perez, A.; Pivk, M.; Prendki, J.; Roos, L.; Sitt, S.; Stark, J.; Thérin, G.; Vallereau, A.; Biasini, M.; Covarelli, R.; Manoni, E.; Pennazzi, S.; Pioppi, M.; Angelini, C.; Batignani, G.; Bettarini, S.; Bosi, F.; Bucci, F.; Calderini, G.; Carpinelli, M.; Cenci, R.; Cervelli, A.; Forti, F.; Giorgi, M. A.; Lusiani, A.; Marchiori, G.; Morganti, M.; Morsani, F.; Paoloni, E.; Raffaelli, F.; Rizzo, G.; Sandrelli, F.; Triggiani, G.; Walsh, J. J.; Haire, M.; Judd, D.; Biesiada, J.; Danielson, N.; Elmer, P.; Fernholz, R. E.; Lau, Y. P.; Lu, C.; Miftakov, V.; Olsen, J.; Lopes Pegna, D.; Sands, W. R.; Smith, A. J. S.; Telnov, A. V.; Tumanov, A.; Varnes, E. W.; Baracchini, E.; Bellini, F.; Bulfon, C.; Buccheri, E.; Cavoto, G.; D'Orazio, A.; Di Marco, E.; Faccini, R.; Ferrarotto, F.; Ferroni, F.; Gaspero, M.; Jackson, P. D.; Lamanna, E.; Leonardi, E.; Li Gioi, L.; Lunadei, R.; Mazzoni, M. A.; Morganti, S.; Piredda, G.; Polci, F.; del Re, D.; Renga, F.; Safai Tehrani, F.; Serra, M.; Voena, C.; Bünger, C.; Christ, S.; Hartmann, T.; Leddig, T.; Schröder, H.; Wagner, G.; Waldi, R.; Adye, T.; Bly, M.; Brew, C.; Condurache, C.; De Groot, N.; Franek, B.; Geddes, N. I.; Gopal, G. P.; Olaiya, E. O.; Ricciardi, S.; Roethel, W.; Wilson, F. F.; Xella, S. M.; Aleksan, R.; Bourgeois, P.; Emery, S.; Escalier, M.; Esteve, L.; Gaidot, A.; Ganzhur, S. F.; Giraud, P.-F.; Georgette, Z.; Graziani, G.; Hamel de Monchenault, G.; Kozanecki, W.; Langer, M.; Legendre, M.; London, G. W.; Mayer, B.; Micout, P.; Serfass, B.; Vasseur, G.; Yèche, Ch.; Zito, M.; Allen, M. T.; Akre, R.; Aston, D.; Azemoon, T.; Bard, D. J.; Bartelt, J.; Bartoldus, R.; Bechtle, P.; Becla, J.; Benitez, J. F.; Berger, N.; Bertsche, K.; Boeheim, C. T.; Bouldin, K.; Boyarski, A. M.; Boyce, R. F.; Browne, M.; Buchmueller, O. L.; Burgess, W.; Cai, Y.; Cartaro, C.; Ceseracciu, A.; Claus, R.; Convery, M. R.; Coupal, D. P.; Craddock, W. W.; Crane, G.; Cristinziani, M.; DeBarger, S.; Decker, F. J.; Dingfelder, J. C.; Donald, M.; Dorfan, J.; Dubois-Felsmann, G. P.; Dunwoodie, W.; Ebert, M.; Ecklund, S.; Erickson, R.; Fan, S.; Field, R. C.; Fisher, A.; Fox, J.; Franco Sevilla, M.; Fulsom, B. G.; Gabareen, A. M.; Gaponenko, I.; Glanzman, T.; Gowdy, S. J.; Graham, M. T.; Grenier, P.; Hadig, T.; Halyo, V.; Haller, G.; Hamilton, J.; Hanushevsky, A.; Hasan, A.; Hast, C.; Hee, C.; Himel, T.; Hryn'ova, T.; Huffer, M. E.; Hung, T.; Innes, W. R.; Iverson, R.; Kaminski, J.; Kelsey, M. H.; Kim, H.; Kim, P.; Kharakh, D.; Kocian, M. L.; Krasnykh, A.; Krebs, J.; Kroeger, W.; Kulikov, A.; Kurita, N.; Langenegger, U.; Leith, D. W. G. S.; Lewis, P.; Li, S.; Libby, J.; Lindquist, B.; Luitz, S.; Lüth, V.; Lynch, H. L.; MacFarlane, D. B.; Marsiske, H.; McCulloch, M.; McDonald, J.; Melen, R.; Menke, S.; Metcalfe, S.; Messner, R.; Moss, L. J.; Mount, R.; Muller, D. R.; Neal, H.; Nelson, D.; Nelson, S.; Nordby, M.; Nosochkov, Y.; Novokhatski, A.; O'Grady, C. P.; O'Neill, F. G.; Ofte, I.; Ozcan, V. E.; Perazzo, A.; Perl, M.; Petrak, S.; Piemontese, M.; Pierson, S.; Pulliam, T.; Ratcliff, B. N.; Ratkovsky, S.; Reif, R.; Rivetta, C.; Rodriguez, R.; Roodman, A.; Salnikov, A. A.; Schietinger, T.; Schindler, R. H.; Schwarz, H.; Schwiening, J.; Seeman, J.; Smith, D.; Snyder, A.; Soha, A.; Stanek, M.; Stelzer, J.; Su, D.; Sullivan, M. K.; Suzuki, K.; Swain, S. K.; Tanaka, H. A.; Teytelman, D.; Thompson, J. M.; Tinslay, J. S.; Trunov, A.; Turner, J.; van Bakel, N.; van Winkle, D.; Va'vra, J.; Wagner, A. P.; Weaver, M.; Weinstein, A. J. R.; Weber, T.; West, C. A.; Wienands, U.; Wisniewski, W. J.; Wittgen, M.; Wittmer, W.; Wright, D. H.; Wulsin, H. W.; Yan, Y.; Yarritu, A. K.; Yi, K.; Yocky, G.; Young, C. C.; Ziegler, V.; Chen, X. R.; Liu, H.; Park, W.; Purohit, M. V.; Singh, H.; Weidemann, A. W.; White, R. M.; Wilson, J. R.; Yumiceva, F. X.; Sekula, S. J.; Bellis, M.; Burchat, P. R.; Edwards, A. J.; Majewski, S. A.; Meyer, T. I.; Miyashita, T. S.; Petersen, B. A.; Roat, C.; Ahmed, M.; Ahmed, S.; Alam, M. S.; Bula, R.; Ernst, J. A.; Jain, V.; Liu, J.; Pan, B.; Saeed, M. A.; Wappler, F. R.; Zain, S. B.; Gorodeisky, R.; Guttman, N.; Peimer, D.; Soffer, A.; De Silva, A.; Lund, P.; Krishnamurthy, M.; Ragghianti, G.; Spanier, S. M.; Wogsland, B. J.; Eckmann, R.; Ritchie, J. L.; Ruland, A. M.; Satpathy, A.; Schilling, C. J.; Schwitters, R. F.; Wray, B. C.; Drummond, B. W.; Izen, J. M.; Kitayama, I.; Lou, X. C.; Ye, S.; Bianchi, F.; Bona, M.; Gallo, F.; Gamba, D.; Pelliccioni, M.; Bomben, M.; Borean, C.; Bosisio, L.; Cossutti, F.; Della Ricca, G.; Dittongo, S.; Grancagnolo, S.; Lanceri, L.; Poropat, P.; Rashevskaya, I.; Vitale, L.; Vuagnin, G.; Manfredi, P. F.; Re, V.; Speziali, V.; Frank, E. D.; Gladney, L.; Guo, Q. H.; Panetta, J.; Azzolini, V.; Lopez-March, N.; Martinez-Vidal, F.; Milanes, D. A.; Oyanguren, A.; Agarwal, A.; Albert, J.; Banerjee, Sw.; Bernlochner, F. U.; Brown, C. M.; Choi, H. H. F.; Fortin, D.; Fransham, K. B.; Hamano, K.; Kowalewski, R.; Lewczuk, M. J.; Nugent, I. M.; Roney, J. M.; Sobie, R. J.; Back, J. J.; Gershon, T. J.; Harrison, P. F.; Ilic, J.; Latham, T. E.; Mohanty, G. B.; Puccio, E.; Band, H. R.; Chen, X.; Cheng, B.; Dasu, S.; Datta, M.; Eichenbaum, A. M.; Hollar, J. J.; Hu, H.; Johnson, J. R.; Kutter, P. E.; Li, H.; Liu, R.; Mellado, B.; Mihalyi, A.; Mohapatra, A. K.; Pan, Y.; Pierini, M.; Prepost, R.; Scott, I. J.; Tan, P.; Vuosalo, C. O.; von Wimmersperg-Toeller, J. H.; Wu, S. L.; Yu, Z.; Greene, M. G.; Kordich, T. M. B.

2013-11-01

The BABAR detector operated successfully at the PEP-II asymmetric e+e- collider at the SLAC National Accelerator Laboratory from 1999 to 2008. This report covers upgrades, operation, and performance of the collider and the detector systems, as well as the trigger, online and offline computing, and aspects of event reconstruction since the beginning of data taking.

The BaBar detector: Upgrades, operation and performance

DOE Office of Scientific and Technical Information (OSTI.GOV)

Aubert, B.; Barate, R.; Boutigny, D.

2013-11-01

The BaBar detector operated successfully at the PEP-II asymmetric e+e- collider at the SLAC National Accelerator Laboratory from 1999 to 2008. This report covers upgrades, operation, and performance of the collider and the detector systems, as well as the trigger, online and offline computing, and aspects of event reconstruction since the beginning of data taking.

Performances of RPCs in the BaBar experiment

NASA Astrophysics Data System (ADS)

Anulli, F.; Baldini, R.; Band, H.; Bionta, R.; Brau, J.; Brigljevic, V.; Buzzo, A.; Calcaterra, A.; Carpinelli, M.; Cartaro, T.; Cavallo, N.; Crosetti, G.; De Nardo, G.; De Sangro, R.; Eichenbaum, A.; Falciai, D.; Fabozzi, F.; Ferroni, F.; Finocchiaro, G.; Forti, F.; Frey, R.; Johnson, J.; Gatto, C.; Grauges-Pous, E.; Iwasaki, M.; Lange, D.; Lista, L.; Lo Vetere, M.; Lu, C.; Neal, H.; Neri, N.; Macri, M.; Messener, B.; Monge, M. R.; Moore, T.; Morganti, S.; Palano, A.; Paoloni, E.; Paolucci, P.; Passaggio, S.; Pastore, F.; Patrignani, C.; Patteri, P.; Peruzzi, I.; Piccolo, D.; Piccolo, M.; Piredda, G.; Pompili, A.; Robutti, E.; Roodman, A.; Santroni, A.; Sciacca, C.; Sinev, N.; Soha, A.; Storm, D.; Tosi, S.; Va'vra, J.; Xie, Y.; Wright, D.; Wisniewski, W.

2003-12-01

The BaBar experiment uses a big system based on RPC detectors to discriminate muons from pions and to identify neutral hadrons. About 2000 m2 of RPC chambers have been working at SLAC since the end of 1998. We report on the performances of the RPC chambers focusing on new problems discovered in the RPC behaviour. These problems started very soon after the installation of the chambers on the detector when the high-ambient temperature triggered an increase of dark currents inside the chambers and a reduction of the efficiency. Careful analysis of the BaBar data and dedicated R&D efforts in the laboratory have helped to identify the main source of the trouble in the linseed oil varnish on the bakelite electrodes.

New results on low energy exclusive hadronic final states from BABAR

NASA Astrophysics Data System (ADS)

Gary, J. William

2018-01-01

The 3.6 standard deviation discrepancy between the standard model (SM) prediction for the muon anomalous magnetic moment gμ - 2 and the corresponding experimental measurement is one of the most persistent and intriguing potential signals in particle physics for physics beyond the SM. The largest uncertainty in the SM prediction for gμ - 2 arises from the uncertainty in the measured low energy inclusive e+e- → hadrons cross section. New results from the BABAR experiment at SLAC for the e+e- → π+ π- π0 π0 and e+e- → KK ππ cross sections are presented that significantly reduce this uncertainty. New BABAR results for other low energy exclusive hadronic processes are also discussed.

Dalitz Plot Analyses of B- to D+ Pi- Pi-, B+ to Pi+ Pi- Pi+ and D(S)+ to Pi+ Pi- Pi+ at BaBar

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dong, Liaoyuan; /Iowa State U.

We report on the Dalitz plot analyses of B{sup -} {yields} D{sup +}{pi}{sup -}{pi}{sup -}, B{sup +} {yields} {pi}{sup +}{pi}{sup -}{pi}{sup +} and D{sub s}{sup +} {yields} {pi}{sup +}{pi}{sup -}{sup +}. The Dalitz plot method and the most recent BABAR results are discussed.

Penguin and rare decays in BaBar

DOE Office of Scientific and Technical Information (OSTI.GOV)

Akar, Simon

2015-04-29

We present recent results from the BABAR Collaboration on radiative decays. These include searches for new physics via measurements of several observables such as the time- dependent CP asymmetry in B 0 → K 0 Sπ – π +γ exclusive decays, as well as direct CP asymmetries and branching fractions in B → X sγ and B → X sℓ +ℓ – inclusive decays.

Distributing File-Based Data to Remote Sites Within the BABAR Collaboration

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gowdy, Stephen J.

BABAR [1] uses two formats for its data: Objectivity database and root [2] files. This poster concerns the distribution of the latter--for Objectivity data see [3]. The BABAR analysis data is stored in root files--one per physics run and analysis selection channel--maintained in a large directory tree. Currently BABAR has more than 4.5 TBytes in 200,000 root files. This data is (mostly) produced at SLAC, but is required for analysis at universities and research centers throughout the us and Europe. Two basic problems confront us when we seek to import bulk data from slac to an institute's local storage viamore » the network. We must determine which files must be imported (depending on the local site requirements and which files have already been imported), and we must make the optimum use of the network when transferring the data. Basic ftp-like tools (ftp, scp, etc) do not attempt to solve the first problem. More sophisticated tools like rsync [4], the widely-used mirror/synchronization program, compare local and remote file systems, checking for changes (based on file date, size and, if desired, an elaborate checksum) in order to only copy new or modified files. However rsync allows for only limited file selection. Also when, as in BABAR, an extremely large directory structure must be scanned, rsync can take several hours just to determine which files need to be copied. Although rsync (and scp) provides on-the-fly compression, it does not allow us to optimize the network transfer by using multiple streams, adjusting the tcp window size, or separating encrypted authentication from unencrypted data channels.« less

Search for Rare B Meson Decays at the BABAR Experiment

NASA Astrophysics Data System (ADS)

Cheaib, R.; BABAR Collaboration

2016-11-01

b → s transitions are flavour-changing neutral current (FCNC) processes that play an important role in the search for physics beyond the Standard Model (SM). Contributions from virtual particles in the loop are predicted to deviate observables, such as the branching fraction, from their SM expectations. Using data from the BaBar experiment, we present the first search for the rare decay B + → K+ τ+τ-. The BABAR results on the measurement of the angular asymmetries of B → K* l + l -, where l = e or μ, are also reported. In addition, using a time-dependent analysis of B → K s 0π+π-γ, the mixing induced CP-asymmetry for the radiative FCNC decay, B → K s 0ργ, is measured, along with an amplitude analysis of the mKπ and mKππ spectrum.

Modeling Lost-Particle Backgrounds in PEP-II Using LPTURTLE

DOE Office of Scientific and Technical Information (OSTI.GOV)

Fieguth, T.; /SLAC; Barlow, R.

2005-05-17

Background studies during the design, construction, commissioning, operation and improvement of BaBar and PEP-II have been greatly influenced by results from a program referred to as LPTURTLE (Lost Particle TURTLE) which was originally conceived for the purpose of studying gas background for SLC. This venerable program is still in use today. We describe its use, capabilities and improvements and refer to current results now being applied to BaBar.

Applying object-oriented software engineering at the BaBar collaboration

NASA Astrophysics Data System (ADS)

Jacobsen, Bob; BaBar Collaboration Reconstruction Software Group

1997-02-01

The BaBar experiment at SLAC will start taking data in 1999. We are attempting to build its reconstruction software using good software engineering practices, including the use of object-oriented technology. We summarize our experience to date with analysis and design activities, training, CASE and documentation tools, C++ programming practice and similar topics. The emphasis is on the practical issues of simultaneously introducing new techniques to a large collaboration while under a deadline for system delivery.

Analysis of BaBar data for three meson tau decay modes using the Tauola generator

DOE PAGES

Shekhovtsova, Olga

2014-11-24

The hadronic current for the τ⁻ → π⁻π⁺π⁻ν τ decay calculated in the framework of the Resonance Chiral Theory with an additional modification to include the σ meson is described. In addition, implementation into the Monte Carlo generator Tauola and fitting strategy to get the model parameters using the one-dimensional distributions are discussed. The results of the fit to one-dimensional mass invariant spectrum of the BaBar data are presented.

Searches for New Physics in CP Violation from BABAR

DOE Office of Scientific and Technical Information (OSTI.GOV)

Palombo, Fernando

Results of recent searches for new physics in CP violation in charm decays from the BABAR experiment are presented. These results include a measurement of D 0 - anti D 0 mixing and searches for CP violation in two-body D 0 decays, a search for CP violation in the charm decays D ± → K S 0K ± and D s ± → K S 0K ± , K S 0π ± , and a search for direct CP violation in the singly-Cabibbo suppressed D ± → K +K -π ±decays. These studies are based on the final datasetmore » collected by BABAR at the PEP-II B factory at SLAC in the period 1999-2008. No evidence of CP violation is found in these charm decays. The measured mixing parameter y CP = [0.72 ± 0.18(stat) ± 0.12(syst)]% excludes the no-mixing null hypothesis with a significance of 3.3σ .« less

PHENIX: Beyond 15 years of discovery

DOE PAGES

Morrison, David; Nagle, James L.

2015-01-12

The PHENIX experiment at BNL’s Relativistic Heavy Ion Collider (RHIC) was designed to uncover properties of the quark–gluon plasma (QGP) via rare penetrating probes. Over the past 15 years, the collaboration has delivered on its promised measurements, often with exciting results beyond those originally foreseen. That the QGP behaves as a nearly perfect fluid and that non-photonic electrons are substantially suppressed has led to the use of heavy quarks as probes of the medium. The PHENIX silicon vertex detectors are opening a new arena for QGP studies, and the MPC-EX, a novel forward calorimeter with silicon readout, accesses low-x physicsmore » via direct photons with unprecedented precision. PHENIX has proposed sPHENIX, a major upgrade using the recently acquired BaBar solenoid and full calorimetric coverage and high rate capabilities. sPHENIX will reconstruct jets and extend observables to higher transverse momentum, where comparisons to results from the Large Hadron Collider (LHC) heavy-ion program will provide the most insightful. Following the RHIC program, the nuclear physics community has identified an electron ion collider (EIC) as crucial to the next generation of QCD investigations. The BaBar magnet and sPHENIX calorimetry will be an excellent foundation for a new collaborative pursuit of discovery.« less

Precise discussion of time-reversal asymmetries in B-meson decays

DOE PAGES

Morozumi, Takuya; Okane, Hideaki; Umeeda, Hiroyuki

2015-02-26

BaBar collaboration announced that they observed time reversal (T) asymmetry through B meson system. In the experiment, time dependencies of two distinctive processes, B_ →B¯ 0 and B¯ 0 → B_ (– expresses CP value) are compared with each other. In our study, we examine event number difference of these two processes. In contrast to the BaBar asymmetry, the asymmetry of events number includes the overall normalization difference for rates. Time dependence of the asymmetry is more general and it includes terms absent in one used by BaBar collaboration. Both of the BaBar asymmetry and ours are naively thought tomore » be T-odd since two processes compared are related with flipping time direction. We investigate the time reversal transformation property of our asymmetry. Using our notation, one can see that the asymmetry is not precisely a T-odd quantity, taking into account indirect CP and CPT violation of K meson systems. The effect of ϵK is extracted and gives rise to O(10 –3) contribution. The introduced parameters are invariant under rephasing of quarks so that the coefficients of our asymmetry are expressed as phase convention independent quantities. Some combinations of the asymmetry enable us to extract parameters for wrong sign decays of B d meson, CPT violation, etc. As a result, we also study the reason why the T-even terms are allowed to contribute to the asymmetry, and find that several conditions are needed for the asymmetry to be a T-odd quantity.« less

Measurement of the D - s Decay Constant f Ds and Observation of New Charm Resonances Decaying to D*π

DOE Office of Scientific and Technical Information (OSTI.GOV)

Benitez, Jose

2012-03-01

The absolute branching fractions for the decays D - s → ℓ-more » $$\\bar{v}$$ -(ℓ = e, μ, or τ) are measured using a data sample corresponding to an integrated luminosity of 521 fb -1 collected at center of mass energies near 10.58 GeV with the BABAR detector at the PEPII e +e - collider at SLAC. The number of D s - mesons is determined by reconstructing the recoiling system DKXγ in events of the type e +e - → DKXD* s -, where D* s - → D s - γ and X represents additional pions from fragmentation. The D s - → ℓ -v ℓ events are detected by full or partial reconstruction of the recoiling system DKX{gamma}ℓ. The following results are obtained: β(D s - → μ -v) = (6.02 ± 0.38 ± 0.34) x 10 -3, {Beta}(D s -→ τ -v) = (5.00 ± 0.35 ± 0.49) x 10 -2, and B(D s - → e -ν) < 2.8 x 10 -4 at 90% C.L., where the first uncertainty is statistical and the second is systematic. The branching fraction measurements are combined to determine the D s - decay constant f Ds = (258.6 ± 6.4 ± 7.5) MeV. In addition, a study has been performed of the D +π} -, D 0π} +, and D* +π - systems in inclusive e +e - → c c interactions in a search for excited D meson states. The dataset used consists of {approx}454 fb -1. The mass spectra for these systems show, for the first time, candidates for the radial excitations of the D 0, D* 0, and D* +, as well as the L = 2 excited states of the D 0 and D -, where L is the orbital angular momentum of the quarks. Finally, a prototype of a next generation Detector of Internally Reflected Cherenkov radiation (Focusing DIRC) has been tested using a 10 GeV electron beam at SLAC. The Focusing DIRC is based on the DIRC which was used in the BABAR detector, but has new pixel photon detectors which improve the resolution on the single photon time of propagation by about an order of magnitude allowing, for the first time, to correct the chromatic smearing in the Cherenkov angle. The Focusing DIRC may be used in a future Super-B factory.« less

Selected Topics on Hadronic B Decays From BaBar

DOE Office of Scientific and Technical Information (OSTI.GOV)

Suzuki, K.; /SLAC

Recent measurements of branching fractions and decay-rate asymmetries in charmless hadronic B decays at the BaBar experiment are presented. The selected topics include Dalitz plot analyses of B {yields} K{sup +} {pi}{sup -}{pi} and signal searches in B {yields} PP and PV, where isoscalar mesons are involved, and in B {yields} b{sub 1}P, P and V denote a pseudoscalar and vector meson, respectively. Several measurements in charmless hadronic B decays have indicated possible deviations from the theoretical predictions within the Standard Model. The measurements presented would contribute to searching for and resolving such puzzles.

Mechanisms Affecting Performance of the BaBar Resistive Plate Chambers and Searches for Remediation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lu, Changguo

2003-09-19

The BaBar experiment at PEPII relies on the Instrumentation of the Flux Return (IFR) for both muon identification and KL detection. The active detector is composed of Resistive Plate Chambers (RPC's) operated in streamer mode. Since the start of operation the RPC's have suffered persistent efficiency deterioration and dark current increase problems. The ''autopsy'' of bad BaBar RPC's revealed that in many cases uncured Linseed oil droplets had formed on the inner surface of the Bakelite plates, leading to current paths from oil ''stalagmites'' bridging the 2 mm gap. In this paper a possible model of this ''stalagmite'' formation andmore » its effect on the dark current and efficiency of RPC chambers is presented. Laboratory test results strongly support this model. Based upon this model we are searching for solutions to eliminate the unfavorable effect of the oil stalagmites. The lab tests show that the stalagmite resistivity increases dramatically if exposed to the air, an observation that points to a possible way to remedy the damage and increase the efficiency. We have seen that flowing an oxygen gas mixture into the chamber helps to polymerize the uncured linseed oil. Consequently the resistivity of the bridged oil stalagmites increases, as does that of the oil coating on the frame edges and spacers, significantly reducing the RPC dark currents and low-efficiency regions. We have tested this idea on two chambers removed from BaBar because of their low efficiency and high dark current. These test results are reported in the paper, and two other remediation methods also mentioned. We continue to study this problem, and try to find new treatments with permanent improvement.« less

A binary link tracker for the BaBar level 1 trigger system

DOE Office of Scientific and Technical Information (OSTI.GOV)

Berenyi, A.; Chen, H.K.; Dao, K.

1999-08-01

The BaBar detector at PEP-II will operate in a high-luminosity e{sup +}e{sup {minus}} collider environment near the {Upsilon}(4S) resonance with the primary goal of studying CP violation in the B meson system. In this environment, typical physics events of interest involve multiple charged particles. These events are identified by counting these tracks in a fast first level (Level 1) trigger system, by reconstructing the tracks in real time. For this purpose, a Binary Link Tracker Module (BLTM) was designed and fabricated for the BaBar Level 1 Drift Chamber trigger system. The BLTM is responsible for linking track segments, constructed bymore » the Track Segment Finder Modules (TSFM), into complete tracks. A single BLTM module processes a 360 MBytes/s stream of segment hit data, corresponding to information from the entire Drift Chamber, and implements a fast and robust algorithm that tolerates high hit occupancies as well as local inefficiencies of the Drift Chamber. The algorithms and the necessary control logic of the BLTM were implemented in Field Programmable Gate Arrays (FPGAs), using the VHDL hardware description language. The finished 9U x 400 mm Euro-format board contains roughly 75,000 gates of programmable logic or about 10,000 lines of VHDL code synthesized into five FPGAs.« less

Measurement of branching fraction ratios and CP asymmetries in B →D0 CPK decays with the BABAR detector

DOE Office of Scientific and Technical Information (OSTI.GOV)

Marchiori, Giovanni

2005-06-23

The primary goals of the BABAR experiment are the detection of CP violation (CPV) in the B meson system, the precise measurement of some of the elements of the CKM matrix and the measurement of the rates of rare B meson decays. At present, BABAR has achieved major successes: (1) the discovery, in neutral B decays, of direct and mixing-induced CP violation; (2) accurate measurements of the magnitudes of the CKM matrix elements |V cb| and |V ub|; (3) a precise measurement of the CKM parameter β {triple_bond} arg[- V cdV* cb/V tdV* tb]; (4) a first measurement of themore » CKM parameters α (triple bond) arg[- V tdV* tb/V udV* ub], γ (triple bond) arg[- V udV* ub/V cdV* cb]; and (5) the observation of several rare B decays and the discovery of new particles (in the charmed and charmonium mesons spectroscopy). However, the physics program of BABAR is not yet complete. Two of the key elements of this program that still need to be achieved are: (1) the observation of direct CP violation in charged B decays, which would constitute the first evidence of direct CPV in a charged meson decay; and (2) the precise measurement of α and γ, which are necessary ingredients for a stringent test of the Standard Model predictions in the quark electroweak sector. A possibility for the discovery of direct CP violation in charged B decays would be the observation of a non-vanishing rate asymmetry in the Cabibbo-suppressed decay B - → D 0 K -, with the D 0 decaying to either a CP-even or a CP-odd eigenstate. This class of decays can also provide theoretically-clean information on γ.« less

NEWS: TRUMP resources

NASA Astrophysics Data System (ADS)

Swinbank, Elizabeth

2000-05-01

Support for astronomy in A-level physics aslogo Help is at hand for teachers and students choosing astronomy as part of A-level physics. The Teaching Resources Unit for Modern Physics (TRUMP) has produced a resource package covering all the astronomical options in the Edexcel, OCR and AQA (NEAB) syllabuses. The forerunner to TRUMP was the project that produced the highly successful Particle Physics Pack, sponsored by the Institute of Physics, which was instrumental in introducing particle physics into A-level syllabuses. The TRUMP Astrophysics Resource Package fills a gap between the colourful stimulus of popular materials on the one hand, and professional texts on the other. But this is not just another A-level textbook; the six-part resource pack has a similar structure and purpose to the Particle Physics Pack. It provides over 400 pages of comprehensive information for teachers, building on their existing subject knowledge and bringing them up to date as well as giving suggestions for teaching and notes on syllabus coverage. The package includes nearly 40 photocopiable sheets for students. The emphasis is on the physics that underpins the astronomy. There are details of student activities requiring no specialist equipment beyond that normally found in A-level labs, exercises using authentic data, and plenty of questions (all with worked solutions). The development of the TRUMP Astrophysics Package was funded by the Nuffield Foundation, the Particle Physics and Astronomy Research Council, the Institute of Physics and York University. The package is available by mail order, price £48 (inc. UK p&p) from the TRUMP Project, Science Education Group, University of York, Heslington, York YO10 5DD. Some parts may be purchased separately; for details contact the project's director, Elizabeth Swinbank (tel: 01904 434537, fax: 01904 434078, e-mail: es14@york.ac.uk) or consult the web page www.york.ac.uk/org/seg/trump. The BaBar experiment balogo In the spring of 1999, scientists began to collect data from the BaBar experiment - an international collaboration involving the UK, several other European countries and the USA. The experiment is designed to throw light on the puzzling question of why there is so little antimatter in the universe and so much matter. The TRUMP BaBar resource package brings the mystery of antimatter into schools. There are notes and colourful posters on the physics of BaBar, and photocopiable sheets supporting student activities. These include explorations of symmetry, templates for making a scale model of the BaBar detector, and a web-based research project. The pack is designed mainly for A-level physics (particularly those courses that include some particle physics) but parts also relate to GCSE science, Scottish Higher physics and Standard physics. The BaBar resource package is available free from the Particle Physics and Astronomy Research Council, which fully funded its development and production. Contact the Publicity Team, PPARC, Polaris House, North Star Avenue, Swindon, Wiltshire SN2 1SZ (tel: 01973 442123, e-mail: pr_pus@pparc.ac.uk).

First Observation of CP Violation in B[over ¯]^{0}→D_{CP}^{(*)}h^{0} Decays by a Combined Time-Dependent Analysis of BABAR and Belle Data.

PubMed

Abdesselam, A; Adachi, I; Adametz, A; Adye, T; Ahmed, H; Aihara, H; Akar, S; Alam, M S; Albert, J; Al Said, S; Andreassen, R; Angelini, C; Anulli, F; Arinstein, K; Arnaud, N; Asner, D M; Aston, D; Aulchenko, V; Aushev, T; Ayad, R; Babu, V; Badhrees, I; Bahinipati, S; Bakich, A M; Band, H R; Banerjee, Sw; Barberio, E; Bard, D J; Barlow, R J; Batignani, G; Beaulieu, A; Bellis, M; Ben-Haim, E; Bernard, D; Bernlochner, F U; Bettarini, S; Bettoni, D; Bevan, A J; Bhardwaj, V; Bhuyan, B; Bianchi, F; Biasini, M; Biswal, J; Blinov, V E; Bloom, P C; Bobrov, A; Bomben, M; Bondar, A; Bonneaud, G R; Bonvicini, G; Bozek, A; Bozzi, C; Bračko, M; Briand, H; Browder, T E; Brown, D N; Brown, D N; Bünger, C; Burchat, P R; Buzykaev, A R; Calabrese, R; Calcaterra, A; Calderini, G; Carpinelli, M; Cartaro, C; Casarosa, G; Cenci, R; Červenkov, D; Chang, P; Chao, D S; Chauveau, J; Cheaib, R; Chekelian, V; Chen, A; Chen, C; Cheng, C H; Cheon, B G; Chilikin, K; Chistov, R; Cho, K; Chobanova, V; Choi, H H F; Choi, S-K; Chrzaszcz, M; Cibinetto, G; Cinabro, D; Cochran, J; Coleman, J P; Contri, R; Convery, M R; Cowan, G; Cowan, R; Cremaldi, L; Dalseno, J; Dasu, S; Davier, M; Davis, C L; De Mori, F; De Nardo, G; Denig, A G; Derkach, D; de Sangro, R; Dey, B; Di Lodovico, F; Dingfelder, J; Dittrich, S; Doležal, Z; Dorfan, J; Drásal, Z; Drutskoy, A; Druzhinin, V P; Dubois-Felsmann, G P; Dunwoodie, W; Dutta, D; Ebert, M; Echenard, B; Eidelman, S; Eigen, G; Eisner, A M; Emery, S; Ernst, J A; Faccini, R; Farhat, H; Fast, J E; Feindt, M; Ferber, T; Ferrarotto, F; Ferroni, F; Field, R C; Filippi, A; Finocchiaro, G; Fioravanti, E; Flood, K T; Ford, W T; Forti, F; Franco Sevilla, M; Fritsch, M; Fry, J R; Fulsom, B G; Gabathuler, E; Gabyshev, N; Gamba, D; Garmash, A; Gary, J W; Garzia, I; Gaspero, M; Gaur, V; Gaz, A; Gershon, T J; Getzkow, D; Gillard, R; Li Gioi, L; Giorgi, M A; Glattauer, R; Godang, R; Goh, Y M; Goldenzweig, P; Golob, B; Golubev, V B; Gorodeisky, R; Gradl, W; Graham, M T; Grauges, E; Griessinger, K; Gritsan, A V; Grosdidier, G; Grünberg, O; Guttman, N; Haba, J; Hafner, A; Hamilton, B; Hara, T; Harrison, P F; Hast, C; Hayasaka, K; Hayashii, H; Hearty, C; He, X H; Hess, M; Hitlin, D G; Hong, T M; Honscheid, K; Hou, W-S; Hsiung, Y B; Huard, Z; Hutchcroft, D E; Iijima, T; Inguglia, G; Innes, W R; Ishikawa, A; Itoh, R; Iwasaki, Y; Izen, J M; Jaegle, I; Jawahery, A; Jessop, C P; Joffe, D; Joo, K K; Julius, T; Kang, K H; Kass, R; Kawasaki, T; Kerth, L T; Khan, A; Kiesling, C; Kim, D Y; Kim, J B; Kim, J H; Kim, K T; Kim, P; Kim, S H; Kim, Y J; King, G J; Kinoshita, K; Ko, B R; Koch, H; Kodyš, P; Kolomensky, Yu G; Korpar, S; Kovalskyi, D; Kowalewski, R; Kravchenko, E A; Križan, P; Krokovny, P; Kuhr, T; Kumar, R; Kuzmin, A; Kwon, Y-J; Lacker, H M; Lafferty, G D; Lanceri, L; Lange, D J; Lankford, A J; Latham, T E; Leddig, T; Le Diberder, F; Lee, D H; Lee, I S; Lee, M J; Lees, J P; Leith, D W G S; Leruste, Ph; Lewczuk, M J; Lewis, P; Libby, J; Lockman, W S; Long, O; Lopes Pegna, D; LoSecco, J M; Lou, X C; Lueck, T; Luitz, S; Lukin, P; Luppi, E; Lusiani, A; Luth, V; Lutz, A M; Lynch, G; MacFarlane, D B; Malaescu, B; Mallik, U; Manoni, E; Marchiori, G; Margoni, M; Martellotti, S; Martinez-Vidal, F; Masuda, M; Mattison, T S; Matvienko, D; McKenna, J A; Meadows, B T; Miyabayashi, K; Miyashita, T S; Miyata, H; Mizuk, R; Mohanty, G B; Moll, A; Monge, M R; Moon, H K; Morandin, M; Muller, D R; Mussa, R; Nakano, E; Nakazawa, H; Nakao, M; Nanut, T; Nayak, M; Neal, H; Neri, N; Nisar, N K; Nishida, S; Nugent, I M; Oberhof, B; Ocariz, J; Ogawa, S; Okuno, S; Olaiya, E O; Olsen, J; Ongmongkolkul, P; Onorato, G; Onuchin, A P; Onuki, Y; Ostrowicz, W; Oyanguren, A; Pakhlova, G; Pakhlov, P; Palano, A; Pal, B; Palombo, F; Pan, Y; Panduro Vazquez, W; Paoloni, E; Park, C W; Park, H; Passaggio, S; Patel, P M; Patrignani, C; Patteri, P; Payne, D J; Pedlar, T K; Peimer, D R; Peruzzi, I M; Pesántez, L; Pestotnik, R; Petrič, M; Piccolo, M; Piemontese, L; Piilonen, L E; Pilloni, A; Piredda, G; Playfer, S; 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Sumisawa, K; Sumiyoshi, T; Summers, D J; Sun, L; Tamponi, U; Taras, P; Tasneem, N; Teramoto, Y; Tisserand, V; Todyshev, K Yu; Toki, W H; Touramanis, C; Trabelsi, K; Tsuboyama, T; Uchida, M; Uglov, T; Unno, Y; Uno, S; Usov, Y; Uwer, U; Vahsen, S E; Van Hulse, C; Vanhoefer, P; Varner, G; Vasseur, G; Va'vra, J; Verderi, M; Vinokurova, A; Vitale, L; Vorobyev, V; Voß, C; Wagner, M N; Wagner, S R; Waldi, R; Walsh, J J; Wang, C H; Wang, M-Z; Wang, P; Watanabe, Y; West, C A; Williams, K M; Wilson, F F; Wilson, J R; Wisniewski, W J; Won, E; Wormser, G; Wright, D M; Wu, S L; Wulsin, H W; Yamamoto, H; Yamaoka, J; Yashchenko, S; Yuan, C Z; Yusa, Y; Zallo, A; Zhang, C C; Zhang, Z P; Zhilich, V; Zhulanov, V; Zupanc, A

2015-09-18

We report a measurement of the time-dependent CP asymmetry of B[over ¯]^{0}→D_{CP}^{(*)}h^{0} decays, where the light neutral hadron h^{0} is a π^{0}, η, or ω meson, and the neutral D meson is reconstructed in the CP eigenstates K^{+}K^{-}, K_{S}^{0}π^{0}, or K_{S}^{0}ω. The measurement is performed combining the final data samples collected at the ϒ(4S) resonance by the BABAR and Belle experiments at the asymmetric-energy B factories PEP-II at SLAC and KEKB at KEK, respectively. The data samples contain (471±3)×10^{6} BB[over ¯] pairs recorded by the BABAR detector and (772±11)×10^{6} BB[over ¯] pairs recorded by the Belle detector. We measure the CP asymmetry parameters -η_{f}S=+0.66±0.10(stat)±0.06(syst) and C=-0.02±0.07(stat)±0.03(syst). These results correspond to the first observation of CP violation in B[over ¯]^{0}→D_{CP}^{(*)}h^{0} decays. The hypothesis of no mixing-induced CP violation is excluded in these decays at the level of 5.4 standard deviations.

BaBar superconducting coil: design, construction and test

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bell, R A; Berndt, M; Burgess, W

2001-01-26

The BABAR Detector, located in the PEP-II B-Factory at the Stanford Linear Accelerator Center, includes a large 1.5 Tesla superconducting solenoid, 2.8 m bore and length 3.7 m. The two layer solenoid is wound with an aluminum stabilized conductor which is graded axially to produce a {+-} 3% field uniformity in the tracking region. This paper summarizes the 3 year design, fabrication and testing program of the superconducting solenoid. The work was carried out by an international collaboration between INFN, LLNL and SLAC. The coil was constructed by Ansaldo Energia. Critical current measurements of the superconducting strand, cable and conductor,more » cool-down, operation with the thermo-siphon cooling, fast and slow discharges, and magnetic forces are discussed in detail.« less

Recent BaBar Results on Hadron Spectroscopy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Robutti, E.; /INFN, Genoa

2005-08-29

Recent results from on hadronic spectroscopy are presented, based on data collected by the BaBar experiment between 1999 and 2004. The properties of the recently discovered D*{sub sJ}(2317){sup +} and D{sub sJ}(2460){sup +} states are studied: resonance parameters and ratios of decay rates are measured from continuum e{sup +}e{sup -} production, and production rates are measured from B decays. A search for the D*{sub sJ}(2632){sup +} state whose observation has been recently reported by the SELEX Collaboration, and a search for a charged partner of the charmonium-like X(3872) state, are performed, yielding negative results. Finally, extensive searches for several pentaquarkmore » candidates, both fully inclusive and in B decays, result in no positive evidence.« less

FastSim: A Fast Simulation for the SuperB Detector

NASA Astrophysics Data System (ADS)

Andreassen, R.; Arnaud, N.; Brown, D. N.; Burmistrov, L.; Carlson, J.; Cheng, C.-h.; Di Simone, A.; Gaponenko, I.; Manoni, E.; Perez, A.; Rama, M.; Roberts, D.; Rotondo, M.; Simi, G.; Sokoloff, M.; Suzuki, A.; Walsh, J.

2011-12-01

We have developed a parameterized (fast) simulation for detector optimization and physics reach studies of the proposed SuperB Flavor Factory in Italy. Detector components are modeled as thin sections of planes, cylinders, disks or cones. Particle-material interactions are modeled using simplified cross-sections and formulas. Active detectors are modeled using parameterized response functions. Geometry and response parameters are configured using xml files with a custom-designed schema. Reconstruction algorithms adapted from BaBar are used to build tracks and clusters. Multiple sources of background signals can be merged with primary signals. Pattern recognition errors are modeled statistically by randomly misassigning nearby tracking hits. Standard BaBar analysis tuples are used as an event output. Hadronic B meson pair events can be simulated at roughly 10Hz.

Measurement of the branching fractions of B-->D**(l) nu(l) decays in events tagged by a fully reconstructed B meson.

PubMed

Aubert, B; Bona, M; Karyotakis, Y; Lees, J P; Poireau, V; Prencipe, E; Prudent, X; Tisserand, V; Garra Tico, J; Grauges, E; Lopez, L; Palano, A; Pappagallo, M; Eigen, G; Stugu, B; Sun, L; Abrams, G S; Battaglia, M; Brown, D N; Cahn, R N; Jacobsen, R G; Kerth, L T; Kolomensky, Yu G; Lynch, G; Osipenkov, I L; Ronan, M T; Tackmann, K; Tanabe, T; Hawkes, C M; Soni, N; Watson, A T; Koch, H; Schroeder, T; Walker, D; Asgeirsson, D J; Fulsom, B G; Hearty, C; Mattison, T S; Mckenna, J A; Barrett, M; Khan, A; Blinov, V E; Bukin, A D; Buzykaev, A R; Druzhinin, V P; Golubev, V B; Onuchin, A P; Serednyakov, S I; Skovpen, Yu I; Solodov, E P; Todyshev, K Yu; Bondioli, M; Curry, S; Eschrich, I; Kirkby, D; Lankford, A J; Lund, P; Mandelkern, M; Martin, E C; Stoker, D P; Abachi, S; Buchanan, C; Gary, J W; Liu, F; Long, O; Shen, B C; Vitug, G M; Yasin, Z; Zhang, L; Sharma, V; Campagnari, C; Hong, T M; Kovalskyi, D; Mazur, M A; Richman, J D; Beck, T W; Eisner, A M; Flacco, C J; Heusch, C A; Kroseberg, J; Lockman, W S; Schalk, T; Schumm, B A; Seiden, A; Wang, L; Wilson, M G; Winstrom, L O; Cheng, C H; Doll, D A; Echenard, B; Fang, F; Hitlin, D G; Narsky, I; Piatenko, T; Porter, F C; Andreassen, R; Mancinelli, G; Meadows, B T; Mishra, K; Sokoloff, M D; Bloom, P C; Ford, W T; Gaz, A; Hirschauer, J F; Nagel, M; Nauenberg, U; Smith, J G; Ulmer, K A; Wagner, S R; Ayad, R; Soffer, A; Toki, W H; Wilson, R J; Altenburg, D D; Feltresi, E; Hauke, A; Jasper, H; Karbach, M; Merkel, J; Petzold, A; Spaan, B; Wacker, K; Kobel, M J; Mader, W F; Nogowski, R; Schubert, K R; Schwierz, R; Sundermann, J E; Volk, A; Bernard, D; Bonneaud, G R; Latour, E; Thiebaux, Ch; Verderi, M; Clark, P J; Gradl, W; Playfer, S; Watson, J E; Andreotti, M; Bettoni, D; Bozzi, C; Calabrese, R; Cecchi, A; Cibinetto, G; Franchini, P; Luppi, E; Negrini, M; Petrella, A; Piemontese, L; Santoro, V; Baldini-Ferroli, R; Calcaterra, A; de Sangro, R; Finocchiaro, G; Pacetti, S; Patteri, P; Peruzzi, I M; Piccolo, M; Rama, M; Zallo, A; Buzzo, A; Contri, R; Lo Vetere, M; Macri, M M; Monge, M R; Passaggio, S; Patrignani, C; Robutti, E; Santroni, A; Tosi, S; Chaisanguanthum, K S; Morii, M; Marks, J; Schenk, S; Uwer, U; Klose, V; Lacker, H M; Bard, D J; Dauncey, P D; Nash, J A; Panduro Vazquez, W; Tibbetts, M; Behera, P K; Chai, X; Charles, M J; Mallik, U; Cochran, J; Crawley, H B; Dong, L; Meyer, W T; Prell, S; Rosenberg, E I; Rubin, A E; Gao, Y Y; Gritsan, A V; Guo, Z J; Lae, C K; Denig, A G; Fritsch, M; Schott, G; Arnaud, N; Béquilleux, J; D'Orazio, A; Davier, M; Firmino da Costa, J; Grosdidier, G; Höcker, A; Lepeltier, V; Le Diberder, F; Lutz, A M; Pruvot, S; Roudeau, P; Schune, M H; Serrano, J; Sordini, V; Stocchi, A; Wormser, G; Lange, D J; Wright, D M; Bingham, I; Burke, J P; Chavez, C A; Fry, J R; Gabathuler, E; Gamet, R; Hutchcroft, D E; Payne, D J; Touramanis, C; Bevan, A J; Clarke, C K; George, K A; Di Lodovico, F; Sacco, R; Sigamani, M; Cowan, G; Flaecher, H U; Hopkins, D A; Paramesvaran, S; Salvatore, F; Wren, A C; Brown, D N; Davis, C L; Alwyn, K E; Bailey, D; Barlow, R J; Chia, Y M; Edgar, C L; Jackson, G; Lafferty, G D; West, T J; Yi, J I; Anderson, J; Chen, C; Jawahery, A; Roberts, D A; Simi, G; Tuggle, J M; Dallapiccola, C; Li, X; Salvati, E; Saremi, S; Cowan, R; Dujmic, D; Fisher, P H; Koeneke, K; Sciolla, G; Spitznagel, M; Taylor, F; Yamamoto, R K; Zhao, M; Patel, P M; Robertson, S H; Lazzaro, A; Lombardo, V; Palombo, E; Bauer, J M; Cremaldi, L; Eschenburg, V; Godang, R; Kroeger, R; Sanders, D A; Summers, D J; Zhao, H W; Simard, M; Taras, P; Viaud, F B; Nicholson, H; De Nardo, G; Lista, L; Monorchio, D; Onorato, G; Sciacca, C; Raven, G; Snoek, H L; Jessop, C P; Knoepfel, K J; Lo Secco, J M; Wang, W F; Benelli, G; Corwin, L A; Honscheid, K; Kagan, H; Kass, R; Morris, J P; Rahimi, A M; Regensburger, J J; Sekula, S J; Wong, Q K; Blount, N L; Brau, J; Frey, R; Igonkina, O; Kolb, J A; Lu, M; Rahmat, R; Sinev, N B; Strom, D; Strube, J; Torrence, E; Castelli, G; Gagliardi, N; Margoni, M; Morandin, M; Posocco, M; Rotondo, M; Simonetto, F; Stroili, R; Voci, C; del Amo Sanchez, P; Ben-Haim, E; Briand, H; Calderini, G; Chauveau, J; David, P; Del Buono, L; Hamon, O; Leruste, Ph; Ocariz, J; Perez, A; Prendki, J; Sitt, S; Gladney, L; Biasini, M; Covarelli, R; Manoni, E; Angelini, C; Batignani, G; Bettarini, S; Carpinelli, M; Cervelli, A; Forti, E; Giorgi, M A; Lusiani, A; Marchiori, G; Morganti, M; Neri, N; Paoloni, E; Rizzo, G; Walsh, J J; Lopes Pegna, D; Lu, C; Olsen, J; Smith, A J S; Telnov, A V; Anulli, F; Baracchini, E; Cavoto, G; del Re, D; Di Marco, E; Faccini, R; Ferrarotto, F; Ferroni, F; Gaspero, M; Jackson, P D; Li Gioi, L; Mazzoni, M A; Morganti, S; Piredda, G; Polci, F; Renga, F; Voena, C; Ebert, M; Hartmann, T; Schröder, H; Waldi, R; Adye, T; Franek, B; Olaiya, E O; Wilson, F F; Emery, S; Escalier, M; Esteve, L; Ganzhur, S F; Hamel de Monchenault, G; Kozanecki, W; Vasseur, G; Yèche, Ch; Zito, M; Chen, X R; Liu, H; Park, W; Purohit, M V; White, R M; Wilson, J R; Allen, M T; Aston, D; Bartoldus, R; Bechtle, P; Benitez, J F; Cenci, R; Coleman, J P; Convery, M R; Dingfelder, J C; Dorfan, J; Dubois-Felsmann, G P; Dunwoodie, W; Field, R C; Gabareen, A M; Gowdy, S J; Graham, M T; Grenier, P; Hast, C; Innes, W R; Kaminski, J; Kelsey, M H; Kim, H; Kim, P; Kocian, M L; Leith, D W G S; Li, S; Lindquist, B; Luitz, S; Luth, V; Lynch, H L; MacFarlane, D B; Marsiske, H; Messner, R; Muller, D R; Neal, H; Nelson, S; O'Grady, C P; Ofte, I; Perazzo, A; Perl, M; Ratcliff, B N; Roodman, A; Salnikov, A A; Schindler, R H; Schwiening, J; Snyder, A; Su, D; sullivan, M K; Suzuki, K; Swain, S K; Thompson, J M; Va'vra, J; Wagner, A P; Weaver, M; West, C A; Wisniewski, W J; Wittgen, M; Wright, D H; Wulsin, H W; Yarritu, A K; Yi, K; Young, C C; Ziegler, V; Burchat, P R; Edwards, A J; Majewski, S A; Miyashita, T S; Petersen, B A; Wilden, L; Ahmed, S; Alam, M S; Ernst, J A; Pan, B; Saeed, M A; Zain, S B; Spanier, S M; Wogsland, B J; Eckmann, R; Ritchie, J L; Ruland, A M; Schilling, C J; Schwitters, R F; Drummond, B W; Izen, J M; Lou, X C; Bianchi, F; Gamba, D; Pelliccioni, M; Bomben, M; Bosisio, L; Cartaro, C; Della Ricca, G; Lanceri, L; Vitale, L; Azzolini, V; Lopez-March, N; Martinez-Vidal, F; Milanes, D A; Oyanguren, A; Albert, J; Banerjee, Sw; Bhuyan, B; Choi, H H F; Hamano, K; Kowalewski, R; Lewczuk, M J; Nugent, I M; Roney, J M; Sobie, R J; Gershon, T J; Harrison, P F; Ilic, J; Latham, T E; Mohanty, G B; Band, H R; Chen, X; Dasu, S; Flood, K T; Pan, Y; Pierini, M; Prepost, R; Vuosalo, C O; Wu, S L

2008-12-31

We report a measurement of the branching fractions of B-->D**(l) nu(l), decays based on 417 fb(-1) of data collected at the Y(4S) resonance with the BABAR detector at the PEP-II e+e- storage rings. Events are selected by full reconstructing one of the B mesons in a hadronic decay mode. A fit to the invariant mass differences m(D(*) pi)- m(D(*)) is performed to extract the signal yields of the different D** states. We observe the B-->D**l(-1)nu(l) decay modes corresponding to the four D states predicted by heavy quark symmetry with a significance greater than 5 standard deviations including systematic uncertainties.

The GlueX DIRC detector

NASA Astrophysics Data System (ADS)

Barbosa, F.; Bessuille, J.; Chudakov, E.; Dzhygadlo, R.; Fanelli, C.; Frye, J.; Hardin, J.; Kelsey, J.; Patsyuk, M.; Schwarz, C.; Schwiening, J.; Stevens, J.; Shepherd, M.; Whitlatch, T.; Williams, M.

2017-12-01

The GlueX DIRC (Detection of Internally Reflected Cherenkov light) detector is being developed to upgrade the particle identification capabilities in the forward region of the GlueX experiment at Jefferson Lab. The GlueX DIRC will utilize four existing decommissioned BaBar DIRC bar boxes, which will be oriented to form a plane roughly 4 m away from the fixed target of the experiment. A new photon camera has been designed that is based on the SuperB FDIRC prototype. The full GlueX DIRC system will consist of two such cameras, with the first planned to be built and installed in 2017. We present the current status of the design and R&D, along with the future plans of the GlueX DIRC detector.

Measurement of angular asymmetries in the decays B → K * ℓ + ℓ -

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lees, J. P.; Poireau, V.; Tisserand, V.

2016-03-28

We study the lepton forward-backward asymmetry A FB and the longitudinal K* polarization F L, as well as an observable P 2 derived from them, in the rare decays B→ K * ℓ + ℓ - , where + is either e+e- or μ+μ-, using the full sample of 471 million BB-events collected at the (4S) resonance with the BABAR, detector at the PEP-II e+e- collider. We separately fit and report results for the K*0(892)+ and K*+(892)+ final states, as well as theirmore » combination K * ℓ + ℓ - , in five disjoint dilepton mass-squared bins. An angular analysis of B+→ K * ℓ + ℓ - decays is presented here for the first time.« less

Study of B → Kππγ decays at the BaBar experiment

NASA Astrophysics Data System (ADS)

Graugés, Eugeni; BaBar Collaboration

2016-04-01

The preliminary results obtained from the analysis of the B meson radiative decays to Kππγ, recorded at the BaBar experiment, are presented. A preliminary measurement of the time-dependent CP asymmetry related to the hadronic CP eigenstate ρ0 KS0 is extracted from the radiative-penguin decay B0 → KS0 π+π- γ. The decay B+ →K+π+π- γ is used to measure the intermediate resonant amplitudes of different resonances decaying to Kππ through the intermediate states ρ0K+, K*0π+ and (Kπ) S -waveπ+. Assuming (isospin symmetry) that the resonant amplitudes are the same for B0 → KS0 π+π- γ, the time-dependent CP asymmetry of the B0 → KS0 ργ decay is obtained.

Measurement of the Branching Fractions and CP Asymmetries of B{sup -} --> D{sup 0}{sub (CP)}K{sup -} Decays with the BABAR Detector

DOE Office of Scientific and Technical Information (OSTI.GOV)

Aubert, B

The authors have reconstructed B{sup -} --> D{sup 0}K{sup -} decays with D{sup 0} mesons decaying to non-CP (K{sup -}{pi}{sup +}), CD-even (K{sup -}K{sup +}, {pi}{sup -}{pi}{sup +}) and CP-odd (K{sup 0}{sub s}{pi}{sup 0}) eigenstates. They have measured the CP asymmetries A{sub CP{sup +}} = 0.40 {+-} 0.15(stat) {+-} 0.08(syst), A{sup CP{sup -}} = 0.21 {+-} 0.17(stat) {+-} 0.07(syst), and the double ratio of branching fractions R{sub +} = 0.87 {+-} 0.14(stat) {+-} 0.06(syst), R{sub -} = 0.80 {+-} 0.14(stat) {+-} 0.08(syst). These results improve the previous existing measurements from BABAR. All results presented in this document are preliminary.

Proton Form Factors Measurements in the Time-Like Region

DOE Office of Scientific and Technical Information (OSTI.GOV)

Anulli, F.; /Frascati

2007-10-22

I present an overview of the measurement of the proton form factors in the time-like region. BABAR has recently measured with great accuracy the e{sup +}e{sup -} {yields} p{bar p} reaction from production threshold up to an energy of {approx} 4.5 GeV, finding evidence for a ratio of the electric to magnetic form factor greater than unity, contrary to expectation. In agreement with previous measurements, BABAR confirmed the steep rise of the magnetic form factor close to the p{bar p} mass threshold, suggesting the possible presence of an under-threshold N{bar N} vector state. These and other open questions related tomore » the nucleon form factors both in the time-like and space-like region, wait for more data with different experimental techniques to be possibly solved.« less

Continuation of support for the Intercampus Institute for Research at Particle Accelerators. Final technical report

DOE Office of Scientific and Technical Information (OSTI.GOV)

Caldwell, D.; Eisner, A.

1997-10-01

During the budget period beginning May 16, 1995, the UCSD group of the U.C. Intercampus Institute for Research at Particle Accelerators devoted approximately 75% of its effort to the PEP-II B Factory and the associated BABAR detector at SLAC, and 25% of its effort to the LSND collaboration at LAMPF. Michael Sullivan spent all of his time on PEP-II, while Alan Eisner split his time between BABAR and LSND. Sullivan remained a critical member of the group designing the PEP-II interaction region and the machine-detector interface; and, in fact, toward the end of the period he left IIRPA to becomemore » a SLAC employee, in order to ensure his continued participation in those efforts. That work has focused on developing an interaction region in which the accelerator can achieve the required high specific luminosity while, at the same time, maintaining low enough beam background to allow a detector to operate. Both requirements are essential to achieving the primary physics goal of not only detecting but doing detailed measurements of CP violation. Eisner`s work on the BABAR detector concentrated on the electromagnetic (CsI crystal) calorimeter. With the calorimeter geometry largely established, he turned his attention more fully to the areas of calorimeter data acquisition and calibration. The data acquisition focus, was on understaning the performance of the proposed system via calculations and simulations, a joint project with Yao-xin Wang of the UCSB IIRPA group.« less

Measurement of the B0 ---> Psi (2S) Lambda0 Branching Fraction on BaBar at the Stanford Linear Accelerator Center (Abstract Only)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Olivas, Alexander Raymond, Jr.; /Colorado U.

2005-11-16

The decays of B{sup 0} mesons to hadronic final states remains a rich area of physics on BaBar. Not only do the c{bar c}-K final states (e.g. B{sup 0} {yields} {psi}(2S)K{sup 0}) allow for the measurement of CP Violation, but the branching fractions provide a sensitive test of the theoretical methods used to account for low energy non-perturbative QCD effects. They present the measurement of the branching fraction for the decay B{sup 0} {yields} {psi}(2S)K{sub s}. The data set consists of 88.8 {+-} 1.0 x 10{sup 6} B{bar b} pairs collected on the e{sup +}e{sup -} {yields} {Upsilon}(4S) resonance onmore » BaBar/PEP-II at the Stanford Linear Accelerator Center (SLAC). This analysis features a modification of present cuts, with respect to those published so far on BaBar, on the K{sub S} {yields} {pi}{sup +}{pi}{sup -} and {psi}(2S) {yields} J/{psi}{pi}{sup +}{pi}{sup -} which aim at reducing the background while keeping the signal intact. Various data selection criteria are studied for the lepton modes (e{sup +}e{sup -} and {mu}{sup +}{mu}{sup -}) of the J/{psi} and {psi}(2S) to improve signal purity as well as study the stability of the resultant branching fractions.« less

Simulation of PEP-II Accelerator Backgrounds Using TURTLE

DOE Office of Scientific and Technical Information (OSTI.GOV)

Barlow, R.J.; Fieguth, T.; /SLAC

2006-02-15

We present studies of accelerator-induced backgrounds in the BaBar detector at the SLAC B-Factory, carried out using LPTURTLE, a modified version of the DECAY TURTLE simulation package. Lost-particle backgrounds in PEP-II are dominated by a combination of beam-gas bremstrahlung, beam-gas Coulomb scattering, radiative-Bhabha events and beam-beam blow-up. The radiation damage and detector occupancy caused by the associated electromagnetic shower debris can limit the usable luminosity. In order to understand and mitigate such backgrounds, we have performed a full program of beam-gas and luminosity-background simulations, that include the effects of the detector solenoidal field, detailed modeling of limiting apertures in bothmore » collider rings, and optimization of the betatron collimation scheme in the presence of large transverse tails.« less

Evidence for an Excess of B̄→D (*)τ⁻ν̄ τ Decays

DOE PAGES

Lees, J. P.; Poireau, V.; Tisserand, V.; ...

2012-09-06

Based on the full BABAR data sample, we report improved measurements of the ratios R(D (*))=B(B̄→D (*)τ⁻ν¯ τ)/B(B̄→D (*)l l¯ν¯ l), where l is either e or μ. These ratios are sensitive to new physics contributions in the form of a charged Higgs boson. We measure R(D)=0.440±0.058±0.042 and R(D*)=0.332±0.024±0.018, which exceed the standard model expectations by 2.0σ and 2.7σ, respectively. Taken together, our results disagree with these expectations at the 3.4σ level. This excess cannot be explained by a charged Higgs boson in the type II two-Higgs-doublet model.

The GlueX DIRC detector

DOE PAGES

Barbosa, F.; Bessuille, J.; Chudakov, E.; ...

2017-02-03

We present the GlueX DIRC (Detection of Internally Reflected Cherenkov light) detector that is being developed to upgrade the particle identification capabilities in the forward region of the GlueX experiment at Jefferson Lab. The GlueX DIRC will utilize four existing decommissioned BaBar DIRC bar boxes, which will be oriented to form a plane roughly 4 m away from the fixed target of the experiment. A new photon camera has been designed that is based on the SuperB FDIRC prototype. The full GlueX DIRC system will consist of two such cameras, with the first planned to be built and installed inmore » 2017. In addition, we present the current status of the design and R&D, along with the future plans of the GlueX DIRC detector.« less

Measurement of the branching fractions and CP asymmetry of B--->D(0)((CP))K- decays with the BABAR detector.

PubMed

Aubert, B; Barate, R; Boutigny, D; Gaillard, J-M; Hicheur, A; Karyotakis, Y; Lees, J P; Robbe, P; Tisserand, V; Zghiche, A; Palano, A; Pompili, A; Chen, J C; Qi, N D; Rong, G; Wang, P; Zhu, Y S; Eigen, G; Ofte, I; Stugu, B; Abrams, G S; Borgland, A W; Breon, A B; Brown, D N; Button-Shafer, J; Cahn, R N; Charles, E; Day, C T; Gill, M S; Gritsan, A V; Groysman, Y; Jacobsen, R G; Kadel, R W; Kadyk, J; Kerth, L T; Kolomensky, Yu G; Kukartsev, G; LeClerc, C; Levi, M E; Lynch, G; Mir, L M; Oddone, P J; Orimoto, T J; Pripstein, M; Roe, N A; Romosan, A; Ronan, M T; Shelkov, V G; Telnov, A V; Wenzel, W A; Ford, K; Harrison, T J; Hawkes, C M; Knowles, D J; Morgan, S E; Penny, R C; Watson, A T; Watson, N K; Goetzen, K; Koch, H; Lewandowski, B; Pelizaeus, M; Peters, K; Schmuecker, H; Steinke, M; Boyd, J T; Chevalier, N; Cottingham, W N; Kelly, M P; Latham, T E; Mackay, C; Wilson, F F; Abe, K; Cuhadar-Donszelmann, T; Hearty, C; Mattison, T S; McKenna, J A; Thiessen, D; Kyberd, P; McKemey, A K; Teodorescu, L; Blinov, V E; Bukin, A D; Golubev, V B; Ivanchenko, V N; Kravchenko, E A; Onuchin, A P; Serednyakov, S I; Skovpen, Yu I; Solodov, E P; Yushkov, A N; Best, D; Bruinsma, M; Chao, M; Eschrich, I; Kirkby, D; Lankford, A J; Mandelkern, M; Mommsen, R K; Roethel, W; Stoker, D P; Buchanan, C; Hartfiel, B L; Gary, J W; Shen, B C; Wang, K; Del Re, D; Hadavand, H K; Hill, E J; MacFarlane, D B; Paar, H P; Rahatlou, Sh; Sharma, V; Berryhill, J W; Campagnari, C; Dahmes, B; Kuznetsova, N; Levy, S L; Long, O; Lu, A; Mazur, M A; Richman, J D; Verkerke, W; Beck, T W; Beringer, J; Eisner, A M; Heusch, C A; Lockman, W S; Schalk, T; Schmitz, R E; Schumm, B A; Seiden, A; Turri, M; Walkowiak, W; Williams, D C; Wilson, M G; Albert, J; Chen, E; Dubois-Felsmann, G P; Dvoretskii, A; Hitlin, D G; Narsky, I; Piatenko, T; Porter, F C; Ryd, A; Samuel, A; Yang, S; Jayatilleke, S; Mancinelli, G; Meadows, B T; Sokoloff, M D; Abe, T; Blanc, F; Bloom, P; Chen, S; Clark, P J; Ford, W T; Nauenberg, U; Olivas, A; Rankin, P; Roy, J; Smith, J G; Van Hoek, W C; Zhang, L; Harton, J L; Hu, T; Soffer, A; Toki, W H; Wilson, R J; Zhang, J; Aleksan, R; Emery, S; Gaidot, A; Ganzhur, S F; Giraud, P-F; Hamel De Monchenault, G; Kozanecki, W; Langer, M; Legendre, M; London, G W; Mayer, B; Schott, G; Vasseur, G; Yeche, Ch; Zito, M; Altenburg, D; Brandt, T; Brose, J; Colberg, T; Dickopp, M; Hauke, A; Lacker, H M; Maly, E; Müller-Pfefferkorn, R; Nogowski, R; Otto, S; Schubert, J; Schubert, K R; Schwierz, R; Spaan, B; Bernard, D; Bonneaud, G R; Brochard, F; Cohen-Tanugi, J; Grenier, P; Thiebaux, Ch; Vasileiadis, G; Verderi, M; Khan, A; Lavin, D; Muheim, F; Playfer, S; Swain, J E; Andreotti, M; Azzolini, V; Bettoni, D; Bozzi, C; Calabrese, R; Cibinetto, G; Luppi, E; Negrini, M; Piemontese, L; Sarti, A; Treadwell, E; Anulli, F; Baldini-Ferroli, R; Calcaterra, A; De Sangro, R; Falciai, D; Finocchiaro, G; Patteri, P; Peruzzi, I M; Piccolo, M; Zallo, A; Buzzo, A; Capra, R; Contri, R; Crosetti, G; Lo Vetere, M; Macri, M; Monge, M R; Passaggio, S; Patrignani, C; Robutti, E; Santroni, A; Tosi, S; Bailey, S; Morii, M; Won, E; Dubitzky, R S; Langenegger, U; Bhimji, W; Bowerman, D A; Dauncey, P D; Egede, U; Gaillard, J R; Morton, G W; Nash, J A; Sanders, P; Taylor, G P; Grenier, G J; Lee, S-J; Mallik, U; Cochran, J; Crawley, H B; Lamsa, J; Meyer, W T; Prell, S; Rosenberg, E I; Yi, J; Biasini, M; Pioppi, M; Davier, M; Grosdidier, G; Höcker, A; Laplace, S; Le Diberder, F; Lepeltier, V; Lutz, A M; Petersen, T C; Plaszczynski, S; Schune, M H; Tantot, L; Wormser, G; Brigljević, V; Cheng, C H; Lange, D J; Wright, D M; Bevan, A J; Fry, J R; Gabathuler, E; Gamet, R; Kay, M; Payne, D J; Sloane, R J; Touramanis, C; Back, J J; Cormack, C M; Harrison, P F; Shorthouse, H W; Vidal, P B; Brown, C L; Cowan, G; Flack, R L; Flaecher, H U; George, S; Green, M G; Kurup, A; Marker, C E; McMahon, T R; Ricciardi, S; Salvatore, F; Vaitsas, G; Winter, M A; Brown, D; Davis, C L; Allison, J; Barlow, N R; Barlow, R J; Hart, P A; Hodgkinson, M C; Jackson, F; Lafferty, G D; Lyon, A J; Weatherall, J H; Williams, J C; Farbin, A; Jawahery, A; Kovalskyi, D; Lae, C K; Lillard, V; Roberts, D A; Blaylock, G; Dallapiccola, C; Flood, K T; Hertzbach, S S; Kofler, R; Koptchev, V B; Moore, T B; Saremi, S; Staengle, H; Willocq, S; Cowan, R; Sciolla, G; Taylor, F; Yamamoto, R K; Mangeol, D J J; Patel, P M; Robertson, S H; Lazzaro, A; Palombo, F; Bauer, J M; Cremaldi, L; Eschenburg, V; Godang, R; Kroeger, R; Reidy, J; Sanders, D A; Summers, D J; Zhao, H W; Brunet, S; Cote-Ahern, D; Taras, P; Nicholson, H; Raven, G; Wilden, L; Cartaro, C; Cavallo, N; De Nardo, G; Fabozzi, F; Gatto, C; Lista, L; Paolucci, P; Piccolo, D; Sciacca, C; Jessop, C P; LoSecco, J M; Gabriel, T A; Brau, B; Gan, K K; Honscheid, K; Hufnagel, D; Kagan, H; Kass, R; Pulliam, T; Wong, Q K; Brau, J; Frey, R; Potter, C T; Sinev, N B; Strom, D; Torrence, E; Colecchia, F; Dorigo, A; Galeazzi, F; Margoni, M; Morandin, M; Posocco, M; Rotondo, M; Simonetto, F; Stroili, R; Tiozzo, G; Voci, C; Benayoun, M; Briand, H; Chauveau, J; David, P; De la Vaissière, Ch; Del Buono, L; Hamon, O; John, M J J; Leruste, Ph; Ocariz, J; Pivk, M; Roos, L; Stark, J; T'Jampens, S; Therin, G; Manfredi, P F; Re, V; Behera, P K; Gladney, L; Guo, Q H; Panetta, J; Angelini, C; Batignani, G; Bettarini, S; Bondioli, M; Bucci, F; Calderini, G; Carpinelli, M; Del Gamba, V; Forti, F; Giorgi, M A; Lusiani, A; Marchiori, G; Martinez-Vidal, F; Morganti, M; Neri, N; Paoloni, E; Rama, M; Rizzo, G; Sandrelli, F; Walsh, J; Haire, M; Judd, D; Paick, K; Wagoner, D E; Cavoto, G; Danielson, N; Elmer, P; Lu, C; Miftakov, V; Olsen, J; Smith, A J S; Tanaka, H A; Bellini, F; Faccini, R; Ferrarotto, F; Ferroni, F; Gaspero, M; Mazzoni, M A; Morganti, S; Pierini, M; Piredda, G; Safai Tehrani, F; Voena, C; Christ, S; Wagner, G; Waldi, R; Adye, T; De Groot, N; Franek, B; Geddes, N I; Gopal, G P; Olaiya, E O; Xella, S M; Purohit, M V; Weidemann, A W; Yumiceva, F X; Aston, D; Bartoldus, R; Berger, N; Boyarski, A M; Buchmueller, O L; Convery, M R; Coupal, D P; Dong, D; Dorfan, J; Dujmic, D; Dunwoodie, W; Field, R C; Glanzman, T; Gowdy, S J; Grauges-Pous, E; Hadig, T; Halyo, V; Hryn'ova, T; Innes, W R; Kelsey, M H; Kim, P; Kocian, M L; Leith, D W G S; Libby, J; Luitz, S; Luth, V; Lynch, H L; Marsiske, H; Messner, R; Muller, D R; O'Grady, C P; Ozcan, V E; Perazzo, A; Perl, M; Petrak, S; Ratcliff, B N; Roodman, A; Salnikov, A A; Schindler, R H; Schwiening, J; Simi, G; Snyder, A; Soha, A; Stelzer, J; Su, D; Sullivan, M K; Va'vra, J; Wagner, S R; Weaver, M; Weinstein, A J R; Wisniewski, W J; Wright, D H; Young, C C; Burchat, P R; Edwards, A J; Meyer, T I; Petersen, B A; Roat, C; Ahmed, M; Ahmed, S; Alam, M S; Ernst, J A; Saeed, M A; Saleem, M; Wappler, F R; Bugg, W; Krishnamurthy, M; Spanier, S M; Eckmann, R; Kim, H; Ritchie, J L; Schwitters, R F; Izen, J M; Kitayama, I; Lou, X C; Ye, S; Bianchi, F; Bona, M; Gallo, F; Gamba, D; Borean, C; Bosisio, L; Della Ricca, G; Dittongo, S; Grancagnolo, S; Lanceri, L; Poropat, P; Vitale, L; Vuagnin, G; Panvini, R S; Banerjee, Sw; Brown, C M; Fortin, D; Jackson, P D; Kowalewski, R; Roney, J M; Band, H R; Dasu, S; Datta, M; Eichenbaum, A M; Johnson, J R; Kutter, P E; Li, H; Liu, R; Di Lodovico, F; Mihalyi, A; Mohapatra, A K; Pan, Y; Prepost, R; Sekula, S J; von Wimmersperg-Toeller, J H; Wu, J; Wu, S L; Yu, Z; Neal, H

2004-05-21

We present a study of B--->D(0)(CP)K- decays, where D(0)(CP) is reconstructed in CP-even channels, based on a sample of 88.8 x 10(6) Upsilon(4S)-->BB decays collected with the BABAR detector at the PEP-II e(+)e(-) storage ring. We measure the ratio of Cabibbo-suppressed to Cabibbo-favored branching fractions B(B--->D(0)(CP)K-)/B(B--->D(0)(CP)pi(-))=[8.8+/-1.6(stat)+/-0.5(syst)]x10(-2) and the CP asymmetry A(CP)=0.07+/-0.17(stat)+/-0.06(syst). We also measure B(B--->D0K-)/B(B--->D0pi(-))=[8.31+/-0.35(stat)+/-0.20(syst)]x10(-2) using a sample of 61.0 x 10(6) BB pairs.

Measurement of the D^{*}(2010)^{+}-D^{+} Mass Difference.

PubMed

Lees, J P; Poireau, V; Tisserand, V; Grauges, E; Palano, A; Eigen, G; Brown, D N; Kolomensky, Yu G; Fritsch, M; Koch, H; Schroeder, T; Hearty, C; Mattison, T S; McKenna, J A; So, R Y; Blinov, V E; Buzykaev, A R; Druzhinin, V P; Golubev, V B; Kravchenko, E A; Onuchin, A P; Serednyakov, S I; Skovpen, Yu I; Solodov, E P; Todyshev, K Yu; Lankford, A J; Gary, J W; Long, O; Eisner, A M; Lockman, W S; Panduro Vazquez, W; Chao, D S; Cheng, C H; Echenard, B; Flood, K T; Hitlin, D G; Kim, J; Miyashita, T S; Ongmongkolkul, P; Porter, F C; Röhrken, M; Huard, Z; Meadows, B T; Pushpawela, B G; Sokoloff, M D; Smith, J G; Wagner, S R; Bernard, D; Verderi, M; Bettoni, D; Bozzi, C; Calabrese, R; Cibinetto, G; Fioravanti, E; Garzia, I; Luppi, E; Santoro, V; Calcaterra, A; de Sangro, R; Finocchiaro, G; Martellotti, S; Patteri, P; Peruzzi, I M; Piccolo, M; Rotondo, M; Zallo, A; Passaggio, S; Patrignani, C; Lacker, H M; Bhuyan, B; Mallik, U; Chen, C; Cochran, J; Prell, S; Ahmed, H; Gritsan, A V; Arnaud, N; Davier, M; Le Diberder, F; Lutz, A M; Wormser, G; Lange, D J; Wright, D M; Coleman, J P; Gabathuler, E; Hutchcroft, D E; Payne, D J; Touramanis, C; Bevan, A J; Di Lodovico, F; Sacco, R; Cowan, G; Banerjee, Sw; Brown, D N; Davis, C L; Denig, A G; Gradl, W; Griessinger, K; Hafner, A; Schubert, K R; Barlow, R J; Lafferty, G D; Cenci, R; Jawahery, A; Roberts, D A; Cowan, R; Robertson, S H; Dey, B; Neri, N; Palombo, F; Cheaib, R; Cremaldi, L; Godang, R; Summers, D J; Taras, P; De Nardo, G; Sciacca, C; Raven, G; Jessop, C P; LoSecco, J M; Honscheid, K; Kass, R; Gaz, A; Margoni, M; Posocco, M; Simi, G; Simonetto, F; Stroili, R; Akar, S; Ben-Haim, E; Bomben, M; Bonneaud, G R; Calderini, G; Chauveau, J; Marchiori, G; Ocariz, J; Biasini, M; Manoni, E; Rossi, A; Batignani, G; Bettarini, S; Carpinelli, M; Casarosa, G; Chrzaszcz, M; Forti, F; Giorgi, M A; Lusiani, A; Oberhof, B; Paoloni, E; Rama, M; Rizzo, G; Walsh, J J; Smith, A J S; Anulli, F; Faccini, R; Ferrarotto, F; Ferroni, F; Pilloni, A; Piredda, G; Bünger, C; Dittrich, S; Grünberg, O; Heß, M; Leddig, T; Voß, C; Waldi, R; Adye, T; Wilson, F F; Emery, S; Vasseur, G; Aston, D; Cartaro, C; Convery, M R; Dorfan, J; Dunwoodie, W; Ebert, M; Field, R C; Fulsom, B G; Graham, M T; Hast, C; Innes, W R; Kim, P; Leith, D W G S; Luitz, S; MacFarlane, D B; Muller, D R; Neal, H; Ratcliff, B N; Roodman, A; Sullivan, M K; Va'vra, J; Wisniewski, W J; Purohit, M V; Wilson, J R; Randle-Conde, A; Sekula, S J; Bellis, M; Burchat, P R; Puccio, E M T; Alam, M S; Ernst, J A; Gorodeisky, R; Guttman, N; Peimer, D R; Soffer, A; Spanier, S M; Ritchie, J L; Schwitters, R F; Izen, J M; Lou, X C; Bianchi, F; De Mori, F; Filippi, A; Gamba, D; Lanceri, L; Vitale, L; Martinez-Vidal, F; Oyanguren, A; Albert, J; Beaulieu, A; Bernlochner, F U; King, G J; Kowalewski, R; Lueck, T; Nugent, I M; Roney, J M; Sobie, R J; Tasneem, N; Gershon, T J; Harrison, P F; Latham, T E; Prepost, R; Wu, S L; Sun, L

2017-11-17

We measure the mass difference, Δm_{+}, between the D^{*}(2010)^{+} and the D^{+} using the decay chain D^{*}(2010)^{+}→D^{+}π^{0} with D^{+}→K^{-}π^{+}π^{+}. The data were recorded with the BABAR detector at center-of-mass energies at and near the ϒ(4S) resonance, and correspond to an integrated luminosity of approximately 468  fb^{-1}. We measure Δm_{+}=(140 601.0±6.8[stat]±12.9[syst])  keV. We combine this result with a previous BABAR measurement of Δm_{0}≡m(D^{*}(2010)^{+})-m(D^{0}) to obtain Δm_{D}=m(D^{+})-m(D^{0})=(4824.9±6.8[stat]±12.9[syst])  keV. These results are compatible with and approximately five times more precise than the Particle Data Group averages.

Search for a dark photon in e(+)e(-) collisions at BABAR.

PubMed

Lees, J P; Poireau, V; Tisserand, V; Grauges, E; Palano, A; Eigen, G; Stugu, B; Brown, D N; Feng, M; Kerth, L T; Kolomensky, Yu G; Lee, M J; Lynch, G; Koch, H; Schroeder, T; Hearty, C; Mattison, T S; McKenna, J A; So, R Y; Khan, A; Blinov, V E; Buzykaev, A R; Druzhinin, V P; Golubev, V B; Kravchenko, E A; Onuchin, A P; Serednyakov, S I; Skovpen, Yu I; Solodov, E P; Todyshev, K Yu; Lankford, A J; Mandelkern, M; Dey, B; Gary, J W; Long, O; Campagnari, C; Franco Sevilla, M; Hong, T M; Kovalskyi, D; Richman, J D; West, C A; Eisner, A M; Lockman, W S; Panduro Vazquez, W; Schumm, B A; Seiden, A; Chao, D S; Cheng, C H; Echenard, B; Flood, K T; Hitlin, D G; Miyashita, T S; Ongmongkolkul, P; Porter, F C; Andreassen, R; Huard, Z; Meadows, B T; Pushpawela, B G; Sokoloff, M D; Sun, L; Bloom, P C; Ford, W T; Gaz, A; Smith, J G; Wagner, S R; Ayad, R; Toki, W H; Spaan, B; Bernard, D; Verderi, M; Playfer, S; Bettoni, D; Bozzi, C; Calabrese, R; Cibinetto, G; Fioravanti, E; Garzia, I; Luppi, E; Piemontese, L; Santoro, V; Calcaterra, A; de Sangro, R; Finocchiaro, G; Martellotti, S; Patteri, P; Peruzzi, I M; Piccolo, M; Rama, M; Zallo, A; Contri, R; Lo Vetere, M; Monge, M R; Passaggio, S; Patrignani, C; Robutti, E; Bhuyan, B; Prasad, V; Adametz, A; Uwer, U; Lacker, H M; Dauncey, P D; Mallik, U; Chen, C; Cochran, J; Prell, S; Ahmed, H; Gritsan, A V; Arnaud, N; Davier, M; Derkach, D; Grosdidier, G; Le Diberder, F; Lutz, A M; Malaescu, B; Roudeau, P; Stocchi, A; Wormser, G; Lange, D J; Wright, D M; Coleman, J P; Fry, J R; Gabathuler, E; Hutchcroft, D E; Payne, D J; Touramanis, C; Bevan, A J; Di Lodovico, F; Sacco, R; Cowan, G; Bougher, J; Brown, D N; Davis, C L; Denig, A G; Fritsch, M; Gradl, W; Griessinger, K; Hafner, A; Schubert, K R; Barlow, R J; Lafferty, G D; Cenci, R; Hamilton, B; Jawahery, A; Roberts, D A; Cowan, R; Sciolla, G; Cheaib, R; Patel, P M; Robertson, S H; Neri, N; Palombo, F; Cremaldi, L; Godang, R; Sonnek, P; Summers, D J; Simard, M; Taras, P; De Nardo, G; Onorato, G; Sciacca, C; Martinelli, M; Raven, G; Jessop, C P; LoSecco, J M; Honscheid, K; Kass, R; Feltresi, E; Margoni, M; Morandin, M; Posocco, M; Rotondo, M; Simi, G; Simonetto, F; Stroili, R; Akar, S; Ben-Haim, E; Bomben, M; Bonneaud, G R; Briand, H; Calderini, G; Chauveau, J; Leruste, Ph; Marchiori, G; Ocariz, J; Biasini, M; Manoni, E; Pacetti, S; Rossi, A; Angelini, C; Batignani, G; Bettarini, S; Carpinelli, M; Casarosa, G; Cervelli, A; Chrzaszcz, M; Forti, F; Giorgi, M A; Lusiani, A; Oberhof, B; Paoloni, E; Perez, A; Rizzo, G; Walsh, J J; Lopes Pegna, D; Olsen, J; Smith, A J S; Faccini, R; Ferrarotto, F; Ferroni, F; Gaspero, M; Li Gioi, L; Pilloni, A; Piredda, G; Bünger, C; Dittrich, S; Grünberg, O; Hartmann, T; Hess, M; Leddig, T; Voß, C; Waldi, R; Adye, T; Olaiya, E O; Wilson, F F; Emery, S; Vasseur, G; Anulli, F; Aston, D; Bard, D J; Cartaro, C; Convery, M R; Dorfan, J; Dubois-Felsmann, G P; Dunwoodie, W; Ebert, M; Field, R C; Fulsom, B G; Graham, M T; Hast, C; Innes, W R; Kim, P; Leith, D W G S; Lewis, P; Lindemann, D; Luitz, S; Luth, V; Lynch, H L; MacFarlane, D B; Muller, D R; Neal, H; Perl, M; Pulliam, T; Ratcliff, B N; Roodman, A; Salnikov, A A; Schindler, R H; Snyder, A; Su, D; Sullivan, M K; Va'vra, J; Wisniewski, W J; Wulsin, H W; Purohit, M V; White, R M; Wilson, J R; Randle-Conde, A; Sekula, S J; Bellis, M; Burchat, P R; Puccio, E M T; Alam, M S; Ernst, J A; Gorodeisky, R; Guttman, N; Peimer, D R; Soffer, A; Spanier, S M; Ritchie, J L; Ruland, A M; Schwitters, R F; Wray, B C; Izen, J M; Lou, X C; Bianchi, F; De Mori, F; Filippi, A; Gamba, D; Lanceri, L; Vitale, L; Martinez-Vidal, F; Oyanguren, A; Villanueva-Perez, P; Albert, J; Banerjee, Sw; Beaulieu, A; Bernlochner, F U; Choi, H H F; King, G J; Kowalewski, R; Lewczuk, M J; Lueck, T; Nugent, I M; Roney, J M; Sobie, R J; Tasneem, N; Gershon, T J; Harrison, P F; Latham, T E; Band, H R; Dasu, S; Pan, Y; Prepost, R; Wu, S L

2014-11-14

Dark sectors charged under a new Abelian interaction have recently received much attention in the context of dark matter models. These models introduce a light new mediator, the so-called dark photon (A^{'}), connecting the dark sector to the standard model. We present a search for a dark photon in the reaction e^{+}e^{-}→γA^{'}, A^{'}→e^{+}e^{-}, μ^{+}μ^{-} using 514  fb^{-1} of data collected with the BABAR detector. We observe no statistically significant deviations from the standard model predictions, and we set 90% confidence level upper limits on the mixing strength between the photon and dark photon at the level of 10^{-4}-10^{-3} for dark photon masses in the range 0.02-10.2  GeV. We further constrain the range of the parameter space favored by interpretations of the discrepancy between the calculated and measured anomalous magnetic moment of the muon.

Rare B Meson Decays With Omega Mesons

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhang, Lei; /Colorado U.

2006-04-24

Rare charmless hadronic B decays are particularly interesting because of their importance in understanding the CP violation, which is essential to explain the matter-antimatter asymmetry in our universe, and of their roles in testing the ''effective'' theory of B physics. The study has been done with the BABAR experiment, which is mainly designed for the study of CP violation in the decays of neutral B mesons, and secondarily for rare processes that become accessible with the high luminosity of the PEP-II B Factory. In a sample of 89 million produced B{bar B} pairs on the BABAR experiment, we observed themore » decays B{sup 0} {yields} {omega}K{sup 0} and B{sup +} {yields} {omega}{rho}{sup +} for the first time, made more precise measurements for B{sup +} {yields} {omega}h{sup +} and reported tighter upper limits for B {yields} {omega}K* and B{sup 0} {yields} {omega}{rho}{sup 0}.« less

Measurement of the D * ( 2010 ) + - D + Mass Difference

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lees, J. P.; Poireau, V.; Tisserand, V.

Here, we measure the mass difference, Δm +, between the D* (2010) + and the D + using the decay chain D* (2010) + → D + π 0 with D + → K - π + π +. The data were recorded with the BABAR detector at center-of-mass energies at and near the Υ(4S) resonance, and correspond to an integrated luminosity of approximately 468 fb -1. We measure Δm + = (140 601.0 ± 6.8 [stat] ± 12.9 [syst] ) keV . We combine this result with a previous BABAR measurement of Δm 0 ≡ m(D* (2010) +) -more » m (D 0) to obtain Δm D = m (D +) - m (D 0) = ( 4824.9 ± 6.8 [stat] ± 12.9 [syst]) keV . These results are compatible with and approximately five times more precise than the Particle Data Group averages.« less

Measurement of the D * ( 2010 ) + - D + Mass Difference

DOE PAGES

Lees, J. P.; Poireau, V.; Tisserand, V.; ...

2017-11-14

Here, we measure the mass difference, Δm +, between the D* (2010) + and the D + using the decay chain D* (2010) + → D + π 0 with D + → K - π + π +. The data were recorded with the BABAR detector at center-of-mass energies at and near the Υ(4S) resonance, and correspond to an integrated luminosity of approximately 468 fb -1. We measure Δm + = (140 601.0 ± 6.8 [stat] ± 12.9 [syst] ) keV . We combine this result with a previous BABAR measurement of Δm 0 ≡ m(D* (2010) +) -more » m (D 0) to obtain Δm D = m (D +) - m (D 0) = ( 4824.9 ± 6.8 [stat] ± 12.9 [syst]) keV . These results are compatible with and approximately five times more precise than the Particle Data Group averages.« less

Measurements of Time-Dependent CP Asymmetries in b->s Penguin Dominated Hadronic B Decays at BABAR

DOE Office of Scientific and Technical Information (OSTI.GOV)

Biassoni, Pietro

2010-02-10

We report measurements of Time-Dependent CP asymmetries in several b->s penguin dominated hadronic B decays, where New Physics contributions may appear. We find no significant discrepancies with respect to the Standard Model expectations.

Measurements of CP Asymmetries in the Decay B --> {phi}K

DOE Office of Scientific and Technical Information (OSTI.GOV)

Aubert, B

The authors present a preliminary measurement of the time-dependent CP asymmetry for the neutral B-meson decay B{sup 0} --> {phi}K{sup 0}. They use a sample of approximately 227 million B-meson pairs recorded at the {Upsilon}(4S) resonance with the BABAR detector at the PEP-II B-meson Factory at SLAC. They reconstruct the CP eigenstates {phi}K{sub s}{sup 0} and {phi}K{sub L}{sup 0} where {phi} --> K{sup +}K{sup -}, K{sub s}{sup 0} --> {pi}{sup +}{pi}{sup -}, and K{sub L}{sup 0} is observed via its hadronic interactions. The other B meson in the event is tagged as either a B{sup 0} or {bar B}{sup 0}more » from its decay products. The values of the CP-violation parameters deived from the combined {phi}K{sup 0} dataset are S{sub {phi}K} = +0.50 {+-} 0.25(stat.){sub -0.04}{sup +0.07}(syst.) and C{sub {phi}K} = 0.00 {+-} 0.23(stat.) {+-}0.05(syst.). In addition, the authors measure the CP-violating charge asymmetry A{sub CP}(B{sup +} --> {phi}K{sup +}) = 0.054 {+-} 0.056(stat.) {+-} 0.012(syst.). All results are preliminary.« less

Search for Invisible Decays of a Dark Photon Produced in e^{+}e^{-} Collisions at BaBar.

PubMed

Lees, J P; Poireau, V; Tisserand, V; Grauges, E; Palano, A; Eigen, G; Brown, D N; Derdzinski, M; Giuffrida, A; Kolomensky, Yu G; Fritsch, M; Koch, H; Schroeder, T; Hearty, C; Mattison, T S; McKenna, J A; So, R Y; Blinov, V E; Buzykaev, A R; Druzhinin, V P; Golubev, V B; Kravchenko, E A; Onuchin, A P; Serednyakov, S I; Skovpen, Yu I; Solodov, E P; Todyshev, K Yu; Lankford, A J; Gary, J W; Long, O; Eisner, A M; Lockman, W S; Panduro Vazquez, W; Chao, D S; Cheng, C H; Echenard, B; Flood, K T; Hitlin, D G; Kim, J; Miyashita, T S; Ongmongkolkul, P; Porter, F C; Röhrken, M; Huard, Z; Meadows, B T; Pushpawela, B G; Sokoloff, M D; Sun, L; Smith, J G; Wagner, S R; Bernard, D; Verderi, M; Bettoni, D; Bozzi, C; Calabrese, R; Cibinetto, G; Fioravanti, E; Garzia, I; Luppi, E; Santoro, V; Calcaterra, A; de Sangro, R; Finocchiaro, G; Martellotti, S; Patteri, P; Peruzzi, I M; Piccolo, M; Rotondo, M; Zallo, A; Passaggio, S; Patrignani, C; Lacker, H M; Bhuyan, B; Mallik, U; Chen, C; Cochran, J; Prell, S; Ahmed, H; Gritsan, A V; Arnaud, N; Davier, M; Le Diberder, F; Lutz, A M; Wormser, G; Lange, D J; Wright, D M; Coleman, J P; Gabathuler, E; Hutchcroft, D E; Payne, D J; Touramanis, C; Bevan, A J; Di Lodovico, F; Sacco, R; Cowan, G; Banerjee, Sw; Brown, D N; Davis, C L; Denig, A G; Gradl, W; Griessinger, K; Hafner, A; Schubert, K R; Barlow, R J; Lafferty, G D; Cenci, R; Jawahery, A; Roberts, D A; Cowan, R; Robertson, S H; Dey, B; Neri, N; Palombo, F; Cheaib, R; Cremaldi, L; Godang, R; Summers, D J; Taras, P; De Nardo, G; Sciacca, C; Raven, G; Jessop, C P; LoSecco, J M; Honscheid, K; Kass, R; Gaz, A; Margoni, M; Posocco, M; Simi, G; Simonetto, F; Stroili, R; Akar, S; Ben-Haim, E; Bomben, M; Bonneaud, G R; Calderini, G; Chauveau, J; Marchiori, G; Ocariz, J; Biasini, M; Manoni, E; Rossi, A; Batignani, G; Bettarini, S; Carpinelli, M; Casarosa, G; Chrzaszcz, M; Forti, F; Giorgi, M A; Lusiani, A; Oberhof, B; Paoloni, E; Rama, M; Rizzo, G; Walsh, J J; Smith, A J S; Anulli, F; Faccini, R; Ferrarotto, F; Ferroni, F; Pilloni, A; Piredda, G; Bünger, C; Dittrich, S; Grünberg, O; Heß, M; Leddig, T; Voß, C; Waldi, R; Adye, T; Wilson, F F; Emery, S; Vasseur, G; Aston, D; Cartaro, C; Convery, M R; Dorfan, J; Dunwoodie, W; Ebert, M; Field, R C; Fulsom, B G; Graham, M T; Hast, C; Innes, W R; Kim, P; Leith, D W G S; Luitz, S; MacFarlane, D B; Muller, D R; Neal, H; Ratcliff, B N; Roodman, A; Sullivan, M K; Va'vra, J; Wisniewski, W J; Purohit, M V; Wilson, J R; Randle-Conde, A; Sekula, S J; Bellis, M; Burchat, P R; Puccio, E M T; Alam, M S; Ernst, J A; Gorodeisky, R; Guttman, N; Peimer, D R; Soffer, A; Spanier, S M; Ritchie, J L; Schwitters, R F; Izen, J M; Lou, X C; Bianchi, F; De Mori, F; Filippi, A; Gamba, D; Lanceri, L; Vitale, L; Martinez-Vidal, F; Oyanguren, A; Albert, J; Beaulieu, A; Bernlochner, F U; King, G J; Kowalewski, R; Lueck, T; Nugent, I M; Roney, J M; Sobie, R J; Tasneem, N; Gershon, T J; Harrison, P F; Latham, T E; Prepost, R; Wu, S L

2017-09-29

We search for single-photon events in 53  fb^{-1} of e^{+}e^{-} collision data collected with the BABAR detector at the PEP-II B-Factory. We look for events with a single high-energy photon and a large missing momentum and energy, consistent with production of a spin-1 particle A^{'} through the process e^{+}e^{-}→γA^{'}; A^{'}→invisible. Such particles, referred to as "dark photons," are motivated by theories applying a U(1) gauge symmetry to dark matter. We find no evidence for such processes and set 90% confidence level upper limits on the coupling strength of A^{'} to e^{+}e^{-} in the mass range m_{A^{'}}≤8  GeV. In particular, our limits exclude the values of the A^{'} coupling suggested by the dark-photon interpretation of the muon (g-2)_{μ} anomaly, as well as a broad range of parameters for the dark-sector models.

Search for B^{+}→K^{+}τ^{+}τ^{-} at the BaBar Experiment.

PubMed

Lees, J P; Poireau, V; Tisserand, V; Grauges, E; Palano, A; Eigen, G; Brown, D N; Kolomensky, Yu G; Koch, H; Schroeder, T; Hearty, C; Mattison, T S; McKenna, J A; So, R Y; Blinov, V E; Buzykaev, A R; Druzhinin, V P; Golubev, V B; Kravchenko, E A; Onuchin, A P; Serednyakov, S I; Skovpen, Yu I; Solodov, E P; Todyshev, K Yu; Lankford, A J; Gary, J W; Long, O; Eisner, A M; Lockman, W S; Panduro Vazquez, W; Chao, D S; Cheng, C H; Echenard, B; Flood, K T; Hitlin, D G; Kim, J; Miyashita, T S; Ongmongkolkul, P; Porter, F C; Röhrken, M; Huard, Z; Meadows, B T; Pushpawela, B G; Sokoloff, M D; Sun, L; Smith, J G; Wagner, S R; Bernard, D; Verderi, M; Bettoni, D; Bozzi, C; Calabrese, R; Cibinetto, G; Fioravanti, E; Garzia, I; Luppi, E; Santoro, V; Calcaterra, A; de Sangro, R; Finocchiaro, G; Martellotti, S; Patteri, P; Peruzzi, I M; Piccolo, M; Zallo, A; Passaggio, S; Patrignani, C; Bhuyan, B; Mallik, U; Chen, C; Cochran, J; Prell, S; Ahmed, H; Gritsan, A V; Arnaud, N; Davier, M; Le Diberder, F; Lutz, A M; Wormser, G; Lange, D J; Wright, D M; Coleman, J P; Gabathuler, E; Hutchcroft, D E; Payne, D J; Touramanis, C; Bevan, A J; Di Lodovico, F; Sacco, R; Cowan, G; Banerjee, Sw; Brown, D N; Davis, C L; Denig, A G; Fritsch, M; Gradl, W; Griessinger, K; Hafner, A; Schubert, K R; Barlow, R J; Lafferty, G D; Cenci, R; Jawahery, A; Roberts, D A; Cowan, R; Cheaib, R; Robertson, S H; Dey, B; Neri, N; Palombo, F; Cremaldi, L; Godang, R; Summers, D J; Taras, P; De Nardo, G; Sciacca, C; Raven, G; Jessop, C P; LoSecco, J M; Honscheid, K; Kass, R; Gaz, A; Margoni, M; Posocco, M; Rotondo, M; Simi, G; Simonetto, F; Stroili, R; Akar, S; Ben-Haim, E; Bomben, M; Bonneaud, G R; Calderini, G; Chauveau, J; Marchiori, G; Ocariz, J; Biasini, M; Manoni, E; Rossi, A; Batignani, G; Bettarini, S; Carpinelli, M; Casarosa, G; Chrzaszcz, M; Forti, F; Giorgi, M A; Lusiani, A; Oberhof, B; Paoloni, E; Rama, M; Rizzo, G; Walsh, J J; Smith, A J S; Anulli, F; Faccini, R; Ferrarotto, F; Ferroni, F; Pilloni, A; Piredda, G; Bünger, C; Dittrich, S; Grünberg, O; Heß, M; Leddig, T; Voß, C; Waldi, R; Adye, T; Wilson, F F; Emery, S; Vasseur, G; Aston, D; Cartaro, C; Convery, M R; Dorfan, J; Dunwoodie, W; Ebert, M; Field, R C; Fulsom, B G; Graham, M T; Hast, C; Innes, W R; Kim, P; Leith, D W G S; Luitz, S; Luth, V; MacFarlane, D B; Muller, D R; Neal, H; Ratcliff, B N; Roodman, A; Sullivan, M K; Va'vra, J; Wisniewski, W J; Purohit, M V; Wilson, J R; Randle-Conde, A; Sekula, S J; Bellis, M; Burchat, P R; Puccio, E M T; Alam, M S; Ernst, J A; Gorodeisky, R; Guttman, N; Peimer, D R; Soffer, A; Spanier, S M; Ritchie, J L; Schwitters, R F; Izen, J M; Lou, X C; Bianchi, F; De Mori, F; Filippi, A; Gamba, D; Lanceri, L; Vitale, L; Martinez-Vidal, F; Oyanguren, A; Albert, J; Beaulieu, A; Bernlochner, F U; King, G J; Kowalewski, R; Lueck, T; Nugent, I M; Roney, J M; Tasneem, N; Gershon, T J; Harrison, P F; Latham, T E; Prepost, R; Wu, S L

2017-01-20

We search for the rare flavor-changing neutral current process B^{+}→K^{+}τ^{+}τ^{-} using data from the BABAR experiment. The data sample, collected at the center-of-mass energy of the ϒ(4S) resonance, corresponds to a total integrated luminosity of 424  fb^{-1} and to 471×10^{6}  BB[over ¯] pairs. We reconstruct one B meson, produced in the ϒ(4S)→B^{+}B^{-} decay, in one of many hadronic decay modes and search for activity compatible with a B^{+}→K^{+}τ^{+}τ^{-} decay in the rest of the event. Each τ lepton is required to decay leptonically into an electron or muon and neutrinos. Comparing the expected number of background events with the data sample after applying the selection criteria, we do not find evidence for a signal. The resulting upper limit, at the 90% confidence level, is B(B^{+}→K^{+}τ^{+}τ^{-})<2.25×10^{-3}.

Measuring B to S Gamma, B to D Gamma and |V(Td)/V(Ts)| at BaBar

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bard, Deborah; /SLAC

2012-06-01

Using a sample of 471 million B{bar B} events collected with the BaBar detector, we study the sum of seven exclusive final states b {yields} X{sub s(d)}{gamma}, where X{sub s(d)} is a strange (non-strange) hadronic system with a mass of up to 2.0 Gev/c{sup 2}. After correcting for unobserved decay modes, we obtain a branching fraction for b {yields} d{gamma} of (9.2 {+-} 2.0(stat.) {+-} 2.3(syst.)) x 10{sup -6} in this mass range, and a branching fraction for b {yields} s{gamma} of (23.0 {+-} 0.8(stat.) {+-} 3.0(syst.)) x 10{sup -5} in the same mass range. We find BF(b {yields} d{gamma})/BF(bmore » {yields} s{gamma}) = 0.040 {+-} 0.009(stat.) {+-} 0.010(syst.), from which we determine |V{sub td}/V{sub ts}| = 0.199 {+-} 0.022(stat.) {+-} 0.024(syst.) {+-} 0.002(th.).« less

Failure Scenarios and Mitigations for the BABAR Superconducting Solenoid

NASA Astrophysics Data System (ADS)

Thompson, EunJoo; Candia, A.; Craddock, W. W.; Racine, M.; Weisend, J. G.

2006-04-01

The cryogenic department at the Stanford Linear Accelerator Center is responsible for the operation, troubleshooting, and upgrade of the 1.5 Tesla superconducting solenoid detector for the BABAR B-factory experiment. Events that disable the detector are rare but significantly impact the availability of the detector for physics research. As a result, a number of systems and procedures have been developed over time to minimize the downtime of the detector, for example improved control systems, improved and automatic backup systems, and spares for all major components. Together they can prevent or mitigate many of the failures experienced by the utilities, mechanical systems, controls and instrumentation. In this paper we describe various failure scenarios, their effect on the detector, and the modifications made to mitigate the effects of the failure. As a result of these modifications the reliability of the detector has increased significantly with only 3 shutdowns of the detector due to cryogenics systems over the last 2 years.

Observation of CP violation in neutral B meson going to positive kaon-antipion and neutral B meson going to pion-antipion decays with the BABAR detector

NASA Astrophysics Data System (ADS)

Li, Xuanzhong

This dissertation describes the measurement of asymmetries in neutral B meson decays to two-body final states of charged pions and kaons. The results are obtained from a data sample of 383 million Upsilon(4 S) → BB¯ decays collected between 1999 and 2006 with the BABAR detector at the PEP-II asymmetric-energy B factory located at the Stanford Linear Accelerator Center, California. The maximum likelihood fit that incorporates kinematical, event-shape, and particle identification information is used to measure the CP asymmetries in B0 → pi +pi- and K+/- pi∓ decays. The direct CP-violating asymmetry between decays to K-pi + is AKpi = -0.107 +/- 0.018+0.007-0.004 . The time-dependent CP-violating parameters in B0 → pi+pi- decays are Spipi = -0.60 +/- 0.11 +/- 0.03, Cpipi = -0.21 +/- 0.09 +/- 0.02. For all the measurements above, the first error is statistical and the second is systematic.

Search for a Dark Photon in e + e - Collisions at BaBar

DOE PAGES

Lees, J. P.; Poireau, V.; Tisserand, V.; ...

2014-11-10

Dark sectors charged under a new Abelian interaction have recently received much attention in the context of dark matter models. These models introduce a light new mediator, the so-called dark photon (A'), connecting the dark sector to the standard model. We present a search for a dark photon in the reaction e +e -→γA', A'→e +e -, μ +μ - using 514 fb -1 of data collected with the BABAR detector. We observe no statistically significant deviations from the standard model predictions, and we set 90% confidence level upper limits on the mixing strength between the photon and dark photonmore » at the level of10 -4-10 -3 for dark photon masses in the range 0.02–10.2 GeV We further constrain the range of the parameter space favored by interpretations of the discrepancy between the calculated and measured anomalous magnetic moment of the muon.« less

Search for B + → K + τ + τ - at the BaBar Experiment

DOE PAGES

Lees, J. P.; Poireau, V.; Tisserand, V.; ...

2017-01-20

We search for the rare flavor-changing neutral current process B + → K + τ + τ - using data from the BABAR experiment. The data sample, collected at the center-of-mass energy of the Υ ( 4 S ) resonance, corresponds to a total integrated luminosity of 424 fb - 1 and to 471 × 1 0 6 Bmore » $$\\bar{B}$$ pairs. We reconstruct one B meson, produced in the Υ ( 4 S ) → B + B - decay, in one of many hadronic decay modes and search for activity compatible with a B + → K + τ + τ - decay in the rest of the event. Each τ lepton is required to decay leptonically into an electron or muon and neutrinos. Comparing the expected number of background events with the data sample after applying the selection criteria, we do not find evidence for a signal. The resulting upper limit, at the 90% confidence level, is B ( B + → K + τ + τ - ) < 2.25 × 10 - 3 .« less

Universal behavior of the γ⁎γ→(π0,η,η′) transition form factors

PubMed Central

Melikhov, Dmitri; Stech, Berthold

2012-01-01

The photon transition form factors of π, η and η′ are discussed in view of recent measurements. It is shown that the exact axial anomaly sum rule allows a precise comparison of all three form factors at high-Q2 independent of the different structures and distribution amplitudes of the participating pseudoscalar mesons. We conclude: (i) The πγ form factor reported by Belle is in excellent agreement with the nonstrange I=0 component of the η and η′ form factors obtained from the BaBar measurements. (ii) Within errors, the πγ form factor from Belle is compatible with the asymptotic pQCD behavior, similar to the η and η′ form factors from BaBar. Still, the best fits to the data sets of πγ, ηγ, and η′γ form factors favor a universal small logarithmic rise Q2FPγ(Q2)∼log(Q2). PMID:23226917

Search for B + → K + τ + τ - at the BaBar Experiment

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lees, J. P.; Poireau, V.; Tisserand, V.

We search for the rare flavor-changing neutral current process B + → K + τ + τ - using data from the BABAR experiment. The data sample, collected at the center-of-mass energy of the Υ ( 4 S ) resonance, corresponds to a total integrated luminosity of 424 fb - 1 and to 471 × 1 0 6 Bmore » $$\\bar{B}$$ pairs. We reconstruct one B meson, produced in the Υ ( 4 S ) → B + B - decay, in one of many hadronic decay modes and search for activity compatible with a B + → K + τ + τ - decay in the rest of the event. Each τ lepton is required to decay leptonically into an electron or muon and neutrinos. Comparing the expected number of background events with the data sample after applying the selection criteria, we do not find evidence for a signal. The resulting upper limit, at the 90% confidence level, is B ( B + → K + τ + τ - ) < 2.25 × 10 - 3 .« less

Semileptonic Λb→Λcℓν¯ℓ transition in full QCD

NASA Astrophysics Data System (ADS)

Azizi, K.; Süngü, J. Y.

2018-04-01

The tree-level b →c ℓν¯ ℓ based hadronic transitions have been the focus of much attention since recording significant deviations of the experimental data, on the ratios of the branching fractions in τ and e -μ channels of the semileptonic B →D transition, from the SM predictions by the BABAR Collaboration in 2012. It can be of great importance to look whether similar discrepancies take place in the semileptonic baryonic Λb→Λcℓν¯ ℓ decay channel or not. In this accordance we estimate the decay width as well as the ratios of the branching fractions in τ and e -μ channels of this baryonic transition by calculating the form factors, entering the amplitude of this transition as the main inputs, in the framework of QCD sum rules in full theory. We compare the obtained results with the predictions of other theoretical studies. Our results may be compared with the corresponding future experimental data to look for possible deviations of data from the SM predictions.

Measurements of Time-Dependent CP Asymmetries in b\\to s Penguin Dominated Hadronic B Decays at BaBar

DOE Office of Scientific and Technical Information (OSTI.GOV)

Biassoni, Pietro; /Milan U. /INFN, Milan

2009-12-09

We report measurements of Time-Dependent CP asymmetries in several b {yields} s penguin dominated hadronic B decays, where New Physics contributions may appear. We find no significant discrepancies with respect to the Standard Model expectations.

Fabrication of DIRC radiator bars and plates at InSync, Inc.

NASA Astrophysics Data System (ADS)

Tonnessen, T. W.

2017-12-01

Fabrication of quality radiator bars and plates is paramount to a successful DIRC project. This write up discusses the trials and tribulations of the manufacture of ~600 bars for the BaBar DIRC project and discusses the history and current capabilities of InSync, Inc.

Observation of the {chi}{sub c2}(2P) meson in the reaction {gamma}{gamma}{yields}DD at BABAR

DOE Office of Scientific and Technical Information (OSTI.GOV)

Aubert, B.; Karyotakis, Y.; Lees, J. P.

2010-05-01

A search for the Z(3930) resonance in {gamma}{gamma} production of the DD system has been performed using a data sample corresponding to an integrated luminosity of 384 fb{sup -1} recorded by the BABAR experiment at the PEP-II asymmetric-energy electron-positron collider. The DD invariant mass distribution shows clear evidence of the Z(3930) state with a significance of 5.8{sigma}. We determine mass and width values of (3926.7{+-}2.7{+-}1.1) MeV/c{sup 2} and (21.3{+-}6.8{+-}3.6) MeV, respectively. A decay angular analysis provides evidence that the Z(3930) is a tensor state with positive parity and C parity (J{sup PC}=2{sup ++}); therefore we identify the Z(3930) state asmore » the {chi}{sub c2}(2P) meson. The value of the partial width {Gamma}{sub {gamma}{gamma}x}B(Z(3930){yields}DD) is found to be (0.24{+-}0.05{+-}0.04) keV.« less

Spin-1 Particles and Perturbative QCD

NASA Astrophysics Data System (ADS)

de Melo, J. P. B. C.; Frederico, T.; Ji, Chueng-Ryong

2018-07-01

Due to the angular condition in the light-front dynamics (LFD), the extraction of the electromagnetic form factors for spin-1 particles can be uniquely determined taking into account implicitly non-valence and/or the zero-mode contributions to the matrix elements of the electromagnetic current. No matter which matrix elements of the electromagnetic current is used to extract the electromagnetic form factors, the same unique result is obtained. As physical observables, the electromagnetic form factors obtained from matrix elements of the current in LFD must be equal to those obtained in the instant form calculations. Recently, the Babar collaboration (Phys Rev D 78:071103, 2008) has analyzed the reaction e^+ + e^-→ ρ ^+ + ρ ^- at √{s}=10.58 GeV to measure the cross section as well as the ratios of the helicity amplitudes F_{λ 'λ }. We present our recent analysis of the Babar data for the rho meson considering the angular condition in LFD to put a stringent test on the onset of asymptotic perturbative QCD and predict the energy regime where the subleading contributions are still considerable.

Measurement of Branching Fractions for Two-Body Charmless B Decays to Charged Pions and Kaons at BaBar

DOE Office of Scientific and Technical Information (OSTI.GOV)

Barrera, Barbara

The authors present preliminary results of a search for charmless two-body B decays to charged pions and kaons using data collected by the BaBar detector at the Stanford Linear Accelerator Center's PEP-II Storage ring. In a sample of 8.8 million produced B anti-B pairs the authors measure the branching fractions beta(B{sup 0} --> pi{sup +}pi{sup {minus}}) = (9.3{sub {minus}2.3{minus}1.4}{sup +2.6+1.2}) x 10{sup {minus}6} and beta(B{sup 0} --> K{sup +}pi{sup {minus}}) = (12.5{sub {minus}2.6{minus}1.7}{sup +3.0+1.3}) x 10{sup {minus}6}, where the first uncertainty is statistical and the second is systematic. For the decay B{sup 0} --> K{sup +}K{sup {minus}} they find nomore » significant signal and set an upper limit of beta(B{sup 0} --> K{sup +}K{sup {minus}}) < 6.6 x 10{sup {minus}6} at the 90% confidence level.« less

A BABAR sensitivity study on the search for the invisible decay of J/psi in B+/- mesons going to K*+/- J/psi

NASA Astrophysics Data System (ADS)

Cheaib, Racha

We present a sensitivity study on the search for J/psi → nu nu in B+/- → K*+/- J/psi using data from the BABAR experiment at the SLAC National Accelerator Laboratory. The decay is highly suppressed in the Standard Model and thus is a possible window for new physics such as supersymmetry and dark matter. Hadronic tag reconstruction is employed for the analysis, where one B is fully reconstructed using hadronic decay modes. The remaining tracks and clusters are attributed to the signal B on which the B+/- → K*+/- J/psi cut-based signal selection is applied. The associated K* is allowed to decay via two modes, Mode 1: K* +/- → K0S pi+/- and Mode 2: K* +/- → K+/- pi 0. The approach is to reconstruct a K*+/- candidate, the only signature in a signal event, and calculate the recoiling mass. The data is left blinded in the signal region and only a range of the branching fraction limits is calculated to determine the sensitivity. The result for Mode 1 is an upper limit, at the 90% confidence level, on B (J/psi → nunu) of 9.13 x 10-2 using the Barlow method and 11.10 x 10-2 using the Feldmann-Cousins method. The upper limit for Mode 2, also at the 90% CL, is estimated to be 2.49 x 10-2 and 2.98 x 10-2 using Barlow and Feldmann-Cousins respectively. The branching fractions thus yield a sensitivity of order 10-2. Although the result is not an improvement on the current J/psi → nu nu limits, this method can be extended to other cc¯ quarkonium modes and could further yield a much better result with data from the newly approved SuperB experiment, the extension of BABAR to higher luminosities.

Search for neutral D meson mixing using semileptonic decays

NASA Astrophysics Data System (ADS)

Flood, Kevin T.

Based on a 87 fb-1 dataset, a search for D0-D¯0 mixing is made using the semileptonic decay modes D*+ → pi +D0, D0 → [K/K*]enu (+c.c.) at the B-Factory facility at the Stanford Linear Accelerator Center. These modes offer unambiguous initial and final-state charm flavor tags, and allow the combined use of the D0 lifetime and D*+- D0 mass difference (DeltaM) in a global likelihood fit. The high-statistics sample of reconstructed unmixed semileptonic D0 decays is used to model both the DeltaM distribution and the time-dependence of mixed events directly from the data. Neural networks are used both to select events and to fully reconstruct the D0. A result consistent with no charm mixing has been obtained, Rmix = 0.0023 +/- 0.0012(stat) +/- 0.0004(sys ). This corresponds to an upper limit of Rmix < 0.0047 (95% C.L.) and Rmix < 0.0043 (90% C.L.). The lowest current published limit on semileptonic charm mixing is 0.005 (90% C.L.) (E791, E.M. Aitala et al., Phys.Rev.Lett. 77 2384 (1996)). The current best published limit using any analysis technique on the total rate of charm mixing is 0.0016 (95% C.L.) (Babar Kpi mixing, B. Aubert et al., Phys.Rev.Lett. 91 171801 (2003)).

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bevan, A. J.; Golob, B.; Mannel, Th.

This work is on the Physics of the B Factories. Part A of this book contains a brief description of the SLAC and KEK B Factories as well as their detectors, BaBar and Belle, and data taking related issues. Part B discusses tools and methods used by the experiments in order to obtain results. The results themselves can be found in Part C.

The Physics of the B Factories

DOE PAGES

Bevan, A. J.; Golob, B.; Mannel, Th.; ...

2014-11-19

This work is on the Physics of the B Factories. Part A of this book contains a brief description of the SLAC and KEK B Factories as well as their detectors, BaBar and Belle, and data taking related issues. Part B discusses tools and methods used by the experiments in order to obtain results. The results themselves can be found in Part C.

A review of event processing frameworks used in HEP

DOE PAGES

Sexton-Kennedy, E.

2015-12-23

Today there are many different experimental event processing frameworks in use by running or about to be running experiments. This talk will discuss the different components of these frameworks. In the past there have been attempts at shared framework projects for example the collaborations on the BaBar framework (between BaBar, CDF, and CLEO), on the Gaudi framework (between LHCb and ATLAS), on AliROOT/FairROOT (between Alice and GSI/Fair), and in some ways on art (Fermilab based experiments) and CMS’ framework. However, for reasons that will be discussed, these collaborations did not result in common frameworks shared among the intended experiments. Thoughmore » importantly, two of the resulting projects have succeeded in providing frameworks that are shared among many customer experiments: Fermilab's art framework and GSI/Fair's FairROOT. Interestingly, several projects are considering remerging their frameworks after many years apart. I'll report on an investigation and analysis of these realities. In addition, with the advent of the need for multi-threaded frameworks and the scarce available manpower, it is important to collaborate in the future, however it is also important to understand why previous attempts at multi-experiment frameworks either worked or didn't work.« less

The sPHENIX Experiment

NASA Astrophysics Data System (ADS)

Pérez Lara, Carlos E.

2018-02-01

Our understanding of QCD under extreme conditions has advanced tremendously in the last 20 years with the discovery of the Quark Gluon Plasma and its characterisation in heavy ion collisions at RHIC and LHC. The sPHENIX detector planned at RHIC is designed to further study the microscopic nature of the QGP through precision measurements of jet, upsilon and open heavy flavor probes over a broad pT range. The multi-year sPHENIX physics program will commence in early 2023, using state-of-the art detector technologies to fully exploit the highest RHIC luminosities. The experiment incorporates the 1.4 T former BaBar solenoid magnet, and will feature high precision tracking and vertexing capabilities, provided by a compact TPC, Si-strip intermediate tracker and MAPS vertex detector. This is complemented by highly granular electromagnetic and hadronic calorimetry with full azimuthal coverage. In this document I describe the sPHENIX detector design and physics program, with particular emphasis on the comprehensive open heavy flavour program enabled by the experiment's large coverage, high rate capability and precision vertexing.

Increasing value and reducing waste: addressing inaccessible research.

PubMed

Chan, An-Wen; Song, Fujian; Vickers, Andrew; Jefferson, Tom; Dickersin, Kay; Gøtzsche, Peter C; Krumholz, Harlan M; Ghersi, Davina; van der Worp, H Bart

2014-01-18

The methods and results of health research are documented in study protocols, full study reports (detailing all analyses), journal reports, and participant-level datasets. However, protocols, full study reports, and participant-level datasets are rarely available, and journal reports are available for only half of all studies and are plagued by selective reporting of methods and results. Furthermore, information provided in study protocols and reports varies in quality and is often incomplete. When full information about studies is inaccessible, billions of dollars in investment are wasted, bias is introduced, and research and care of patients are detrimentally affected. To help to improve this situation at a systemic level, three main actions are warranted. First, academic institutions and funders should reward investigators who fully disseminate their research protocols, reports, and participant-level datasets. Second, standards for the content of protocols and full study reports and for data sharing practices should be rigorously developed and adopted for all types of health research. Finally, journals, funders, sponsors, research ethics committees, regulators, and legislators should endorse and enforce policies supporting study registration and wide availability of journal reports, full study reports, and participant-level datasets. Copyright © 2014 Elsevier Ltd. All rights reserved.

Increasing value and reducing waste: addressing inaccessible research

PubMed Central

Chan, An-Wen; Song, Fujian; Vickers, Andrew; Jefferson, Tom; Dickersin, Kay; Gøtzsche, Peter C.; Krumholz, Harlan M.; Ghersi, Davina; van der Worp, H. Bart

2015-01-01

The study protocol, publications, full study report detailing all analyses, and participant-level dataset constitute the main documentation of methods and results for health research. However, journal publications are available for only half of all studies and are plagued by selective reporting of methods and results. The protocol, full study report, and participant-level dataset are rarely available. The quality of information provided in study protocols and reports is variable and often incomplete. Inaccessibility of full information for the vast majority of studies wastes billions of dollars, introduces bias, and has a detrimental impact on patient care and research. To help improve this situation at a systemic level, three main actions are warranted. Firstly, it is important that academic institutions and funders reward investigators who fully disseminate their research protocols, reports, and participant-level datasets. Secondly, standards for the content of protocols, full study reports, and data sharing practices should be rigorously developed and adopted for all types of health research. Finally, journals, funders, sponsors, research ethics committees, regulators, and legislators should implement and enforce policies supporting study registration and availability of journal publications, full study reports, and participant-level datasets. PMID:24411650

Relative Humidity in Limited Streamer Tubes for Stanford Linear Accelerator Center's BaBar Detector

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lang, M.I.; /MIT; Convery, M.

2005-12-15

The BABAR Detector at the Stanford Linear Accelerator Center studies the decay of B mesons created in e{sup +}e{sup -} collisions. The outermost layer of the detector, used to detect muons and neutral hadrons created during this process, is being upgraded from Resistive Plate Chambers (RPCs) to Limited Streamer Tubes (LSTs). The standard-size LST tube consists of eight cells, where a silver-plated wire runs down the center of each. A large potential difference is placed between the wires and ground. Gas flows through a series of modules connected with tubing, typically four. LSTs must be carefully tested before installation, asmore » it will be extremely difficult to repair any damage once installed in the detector. In the testing process, the count rate in most modules showed was stable and consistent with cosmic ray rate over an approximately 500 V operating range between 5400 to 5900 V. The count in some modules, however, was shown to unexpectedly spike near the operation point. In general, the modules through which the gas first flows did not show this problem, but those further along the gas chain were much more likely to do so. The suggestion was that this spike was due to higher humidity in the modules furthest from the fresh, dry inflowing gas, and that the water molecules in more humid modules were adversely affecting the modules' performance. This project studied the effect of humidity in the modules, using a small capacitive humidity sensor (Honeywell). The sensor provided a humidity-dependent output voltage, as well as a temperature measurement from a thermistor. A full-size hygrometer (Panametrics) was used for testing and calibrating the Honeywell sensors. First the relative humidity of the air was measured. For the full calibration, a special gas-mixing setup was used, where relative humidity of the LST gas mixture could be varied from almost dry to almost fully saturated. With the sensor calibrated, a set of sensors was used to measure humidity vs. time in the LSTs. The sensors were placed in two sets of LST modules, one gas line flowing through each set. These modules were tested for count rate v. voltage while simultaneously measuring relative humidity in each module. One set produced expected readings, while the other showed the spike in count rate. The relative humidity in the two sets of modules looked very similar, but it rose significantly for modules further along the gas chain.« less

Full Life Cycle of Data Analysis with Climate Model Diagnostic Analyzer (CMDA)

NASA Astrophysics Data System (ADS)

Lee, S.; Zhai, C.; Pan, L.; Tang, B.; Zhang, J.; Bao, Q.; Malarout, N.

2017-12-01

We have developed a system that supports the full life cycle of a data analysis process, from data discovery, to data customization, to analysis, to reanalysis, to publication, and to reproduction. The system called Climate Model Diagnostic Analyzer (CMDA) is designed to demonstrate that the full life cycle of data analysis can be supported within one integrated system for climate model diagnostic evaluation with global observational and reanalysis datasets. CMDA has four subsystems that are highly integrated to support the analysis life cycle. Data System manages datasets used by CMDA analysis tools, Analysis System manages CMDA analysis tools which are all web services, Provenance System manages the meta data of CMDA datasets and the provenance of CMDA analysis history, and Recommendation System extracts knowledge from CMDA usage history and recommends datasets/analysis tools to users. These four subsystems are not only highly integrated but also easily expandable. New datasets can be easily added to Data System and scanned to be visible to the other subsystems. New analysis tools can be easily registered to be available in the Analysis System and Provenance System. With CMDA, a user can start a data analysis process by discovering datasets of relevance to their research topic using the Recommendation System. Next, the user can customize the discovered datasets for their scientific use (e.g. anomaly calculation, regridding, etc) with tools in the Analysis System. Next, the user can do their analysis with the tools (e.g. conditional sampling, time averaging, spatial averaging) in the Analysis System. Next, the user can reanalyze the datasets based on the previously stored analysis provenance in the Provenance System. Further, they can publish their analysis process and result to the Provenance System to share with other users. Finally, any user can reproduce the published analysis process and results. By supporting the full life cycle of climate data analysis, CMDA improves the research productivity and collaboration level of its user.

An Assessment of Health Care Information and Management Systems Society and Leapfrog Data on Computerized Provider Order Entry

PubMed Central

Diana, Mark L; Kazley, Abby Swanson; Menachemi, Nir

2011-01-01

Objective To assess the internal consistency and agreement between the Health Care Information and Management Systems Society (HIMSS) and the Leapfrog computerized provider order entry (CPOE) data. Data Sources Secondary hospital data collected by HIMSS Analytics, the Leapfrog Group, and the American Hospital Association from 2005 to 2007. Study Design Dichotomous measures of full CPOE status were created for the HIMSS and Leapfrog datasets in each year. We assessed internal consistency by calculating the percent of full adopters in a given year that report full CPOE status in subsequent years. We assessed the level of agreement between the two datasets by calculating the κ statistic and McNemar's test. We examined responsiveness by assessing the change in full CPOE status rates, over time, reported by HIMSS and Leapfrog data, respectively. Principal Findings Findings indicate minimal agreement between the two datasets regarding positive hospital CPOE status, but adequate agreement within a given dataset from year to year. Relative to each other, the HIMSS data tend to overestimate increases in full CPOE status over time, while the Leapfrog data may underestimate year over year increases in national CPOE status. Conclusions Both Leapfrog and HIMSS data have strengths and weaknesses. Those interested in studying outcomes associated with CPOE use or adoption should be aware of the strengths and limitations of the Leapfrog and HIMSS datasets. Future development of a standard definition of CPOE status in hospitals will allow for a more comprehensive validation of these data. PMID:21449956

Leptonic Decays of the Charged B Meson

DOE Office of Scientific and Technical Information (OSTI.GOV)

Corwin, Luke A.

2008-01-01

We present a search for the decay B + → ℓ +ν ( = τ, μ, or e) in (458.9±5.1)×10 6 Υ(4S) decays recorded with the BABAR detector at the SLAC PEP-II B-Factory. A sample of events with one reconstructed exclusive semi-leptonic B decay (B - → D 0ℓ -more » $$\\bar{v}$$X) is selected, and in the recoil a search for B + →ℓ +ν ℓ signal is performed. The τ is identified in the following channels: τ + → e +ν e$$\\bar{v}$$ τ , τ + → μ +ν μ$$\\bar{v}$$ τ , τ + → π +$$\\bar{v}$$ τ , and τ + → π +π 0$$\\bar{v}$$ τ . The analysis strategy and the statistical procedure is set up for branching fraction extraction or upper limit determination. We determine from the dataset a preliminary measurement of B(B + → τ +ν τ) = (1.8 ± 0.8 ± 0.1) × 10 -4, which excludes zero at 2.4σ, and f B = 255 ± 58 MeV. Combination with the hadronically tagged measurement yields B(B + → τ +ν τ) = (1.8 ± 0.6) × 10 -4. We also set preliminary limits on the branching fractions at B(B + → e +ν e) < 7.7 × 10 -6 (90% C.L.), B(B + → μ +ν μ) < 11 × 10 -6 (90% C.L.), and B(B + → τ +ν τ ) < 3.2 × 10 -4(90% C.L.).« less

Searches for dark photons at e{sup +}e{sup −} colliders

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bossi, Fabio

2013-11-07

Searches for new, light, neutral vector particles are being pursued by several different experiments in the world, using e{sup +}e{sup −} collsion data at center-of-mass energies ranging between ∼1 and ∼10 GeV. In this paper I will review the most recent results from KLOE, BESIII, BaBar and Belle and briefly discuss open issues and future perspectives in the field.

Study of the Rare Decay B Mesons Decaying to X Mesons Positive And Negative Leptons at BABAR

DOE Office of Scientific and Technical Information (OSTI.GOV)

Koptchev, Ventzislav B.; /Massachusetts U., Amherst

2005-08-30

Flavor-changing neutral current transitions are forbidden at tree level in the Standard Model and can only occur via higher order diagrams. Since the amplitudes for such loops are dominated by the heaviest known particles, and non-SM effects are expected to contribute at the same order as the SM, such processes are an ideal place to look for new physics. We present a measurement of the inclusive branching fraction for the flavor-changing neutral current process B {yields} X{sub s}{ell}{sup +}{ell}{sup -} with a sample of 81.9 fb{sup -1}, collected with the BABAR detector at the Stanford Linear Accelerator Center. The finalmore » state is reconstructed from e{sup +}e{sup -} or {mu}{sup +}{mu}{sup -} pairs and a hadronic system consisting of one K{sup {+-}} or K{sub s} and up to two pions, with at most one {pi}{sup 0}. They observe a signal of 40 {+-} 10(stat) {+-} 2(syst) events and extract a branching fraction {Beta}(B {yields} X{sub s}{ell}{sup +}{ell}{sup -}) = (5.6 {+-} 1.5(stat) {+-} 0.6(exp. syst) {+-} 1.1(model syst)) x 10{sup -6} for m{sub ll} > 0.2 GeV.« less

First observation of CP violation in B¯ 0 → D (*) CP h 0 decays by a combined time-dependent analysis of BaBar And Belle Data

DOE Office of Scientific and Technical Information (OSTI.GOV)

Abdesselam, A.

We report a measurement of the time-dependent CP asymmetry of B¯ 0 → D (*) CPh 0 decays, where the light neutral hadron h 0 is a π 0, η, or ω meson, and the neutral D meson is reconstructed in the CP eigenstates K +K –, K 0 Sπ 0, or K 0 Sω. The measurement is performed combining the final data samples collected at the Υ(4S) resonance by the BABAR and Belle experiments at the asymmetric-energy B factories PEP-II at SLAC and KEKB at KEK, respectively. The data samples contain (471±3)×10 6 BB¯ pairs recorded by the BABARmore » detector and (772±11)×10 6 BB¯ pairs recorded by the Belle detector. We measure the CP asymmetry parameters –ηfS=+0.66±0.10(stat)±0.06(syst) and C=–0.02±0.07(stat)±0.03(syst). These results correspond to the first observation of CP violation in B¯ 0 → D (*) CPh 0 decays. As a result, the hypothesis of no mixing-induced CP violation is excluded in these decays at the level of 5.4 standard deviations.« less

Production and Decay of {xi}{sub c}{sup 0} at BABAR

DOE Office of Scientific and Technical Information (OSTI.GOV)

Aubert, B.; Barate, R.; Boutigny, D.

Using 116.1 fb{sup -1} of data collected by the BABAR detector, we present an analysis of {xi}{sub c}{sup 0} production in B decays and from the cc continuum, with the {xi}{sub c}{sup 0} decaying into {omega}{sup -}K{sup +} and {xi}{sup -}{pi}{sup +} final states. We measure the ratio of branching fractions B({xi}{sub c}{sup 0}{yields}{omega}{sup -}K{sup +})/B({xi}{sub c}{sup 0}{yields}{xi}{sup -}{pi}{sup +}) to be 0.294{+-}0.018{+-}0.016, where the first uncertainty is statistical and the second is systematic. The {xi}{sub c}{sup 0} momentum spectrum is measured on and 40 MeV below the {upsilon}(4S) resonance. From these spectra the branching fraction product B(B{yields}{xi}{sub c}{sup 0}X)xB({xi}{submore » c}{sup 0}{yields}{xi}{sup -}{pi}{sup +}) is measured to be (2.11{+-}0.19{+-}0.25)x10{sup -4}, and the cross-section product {sigma}(e{sup +}e{sup -}{yields}{xi}{sub c}{sup 0}X)xB({xi}{sub c}{sup 0}{yields}{xi}{sup -}{pi}{sup +}) from the continuum is measured to be (388{+-}39{+-}41) fb at a center-of-mass energy of 10.58 GeV.« less

A measurement of B0 meson properties using partially reconstructed B0 to D*- pi+ and B0 tp D*- lepton+ nu-lepton decays with the BABAR detector

DOE Office of Scientific and Technical Information (OSTI.GOV)

Barrera, Barbara

The two B{sup 0} decay processes B{sup 0} {yields} D*{sup -} {pi}{sup +} and B{sup 0} {yields} D*{sup -} {ell}{sup +} {nu}{sub {ell}} have been studied by means of a partial reconstruction technique using a data sample collected with the BABAR detector at the PEP-II storage ring. To increase statistics, only the soft {pi}{sup -} from the decay D*{sup -} {yields} {pi}{sup -} D{sup 0} was used in association with either an oppositely-charged high-momentum pion or lepton. Events were then identified by exploiting the constraints from the simple kinematics of {Upsilon}(4S) decays. A clear signature is obtained in each case.more » The position of the B{sup 0} decay point was obtained from the reconstructed {pi}{sup +} ({ell}{sup +}){pi}{sup -} vertex. The position of the other {bar B}{sup 0} in the event was also determined. Taking advantage of the boost given to the {Upsilon}(4S) system by the asymmetric beam energies of PEP-II, the lifetime of the B{sup 0} meson has been measured from the separation distance between the two vertices along the beam direction.« less

Dalitz plot analysis of three-body charmonium decays at BABAR

NASA Astrophysics Data System (ADS)

Palano, Antimo

2016-05-01

We present preliminary results on the measurement of the I=1/2 Kπ S-wave through a model independent partial wave analysis of ηc decays to KS0 K+π- and K+ K-π0 produced in two-photon interactions. We also perform a Dalitz plot analysis of the J/ψ decays to π+π-π0 and K+ K-π0 produced in the initial state radiation process.

Measurement of the γγ*→η and γγ*→η' transition form factors

DOE PAGES

del Amo Sanchez, P.; Lees, J. P.; Poireau, V.; ...

2011-09-06

We study the reactions e⁺e⁻→e⁺e⁻η (') in the single-tag mode and measure the γγ*→η (') transition form factors in the momentum-transfer range from 4 to 40 GeV². The analysis is based on 469 fb⁻¹ of integrated luminosity collected at PEP-II with the BABAR detector at e⁺e⁻ center-of-mass energies near 10.6 GeV.

Measurement of the γγ*→η and γγ*→η' transition form factors

NASA Astrophysics Data System (ADS)

Del Amo Sanchez, P.; Lees, J. P.; Poireau, V.; Prencipe, E.; Tisserand, V.; Garra Tico, J.; Grauges, E.; Martinelli, M.; Milanes, D. A.; Palano, A.; Pappagallo, M.; Eigen, G.; Stugu, B.; Sun, L.; Brown, D. N.; Kerth, L. T.; Kolomensky, Yu. G.; Lynch, G.; Osipenkov, I. L.; Koch, H.; Schroeder, T.; Asgeirsson, D. J.; Hearty, C.; Mattison, T. S.; McKenna, J. A.; Khan, A.; Blinov, V. E.; Botov, A. A.; Buzykaev, A. R.; Druzhinin, V. P.; Golubev, V. B.; Kravchenko, E. A.; Onuchin, A. P.; Serednyakov, S. I.; Skovpen, Yu. I.; Solodov, E. P.; Todyshev, K. Yu.; Yushkov, A. N.; Bondioli, M.; Curry, S.; Kirkby, D.; Lankford, A. J.; Mandelkern, M.; Martin, E. C.; Stoker, D. P.; Atmacan, H.; Gary, J. W.; Liu, F.; Long, O.; Vitug, G. M.; Campagnari, C.; Hong, T. M.; Kovalskyi, D.; Richman, J. D.; West, C. A.; Eisner, A. M.; Heusch, C. A.; Kroseberg, J.; Lockman, W. S.; Martinez, A. J.; Schalk, T.; Schumm, B. A.; Seiden, A.; Winstrom, L. O.; Cheng, C. H.; Doll, D. A.; Echenard, B.; Hitlin, D. G.; Ongmongkolkul, P.; Porter, F. C.; Rakitin, A. Y.; Andreassen, R.; Dubrovin, M. S.; Meadows, B. T.; Sokoloff, M. D.; Bloom, P. C.; Ford, W. T.; Gaz, A.; Nagel, M.; Nauenberg, U.; Smith, J. G.; Wagner, S. R.; Ayad, R.; Toki, W. H.; Jasper, H.; Petzold, A.; Spaan, B.; Kobel, M. J.; Schubert, K. R.; Schwierz, R.; Bernard, D.; Verderi, M.; Clark, P. J.; Playfer, S.; Watson, J. E.; Andreotti, M.; Bettoni, D.; Bozzi, C.; Calabrese, R.; Cecchi, A.; Cibinetto, G.; Fioravanti, E.; Franchini, P.; Garzia, I.; Luppi, E.; Munerato, M.; Negrini, M.; Petrella, A.; Piemontese, L.; Baldini-Ferroli, R.; Calcaterra, A.; de Sangro, R.; Finocchiaro, G.; Nicolaci, M.; Pacetti, S.; Patteri, P.; Peruzzi, I. M.; Piccolo, M.; Rama, M.; Zallo, A.; Contri, R.; Guido, E.; Lo Vetere, M.; Monge, M. R.; Passaggio, S.; Patrignani, C.; Robutti, E.; Bhuyan, B.; Prasad, V.; Lee, C. L.; Morii, M.; Edwards, A. J.; Adametz, A.; Marks, J.; Uwer, U.; Bernlochner, F. U.; Ebert, M.; Lacker, H. M.; Lueck, T.; Volk, A.; Dauncey, P. D.; Tibbetts, M.; Behera, P. K.; Mallik, U.; Chen, C.; Cochran, J.; Crawley, H. B.; Meyer, W. T.; Prell, S.; Rosenberg, E. I.; Rubin, A. E.; Gritsan, A. V.; Guo, Z. J.; Arnaud, N.; Davier, M.; Derkach, D.; Firmino da Costa, J.; Grosdidier, G.; Le Diberder, F.; Lutz, A. M.; Malaescu, B.; Perez, A.; Roudeau, P.; Schune, M. H.; Serrano, J.; Sordini, V.; Stocchi, A.; Wang, L.; Wormser, G.; Lange, D. J.; Wright, D. M.; Bingham, I.; Chavez, C. A.; Coleman, J. P.; Fry, J. R.; Gabathuler, E.; Hutchcroft, D. E.; Payne, D. J.; Touramanis, C.; Bevan, A. J.; di Lodovico, F.; Sacco, R.; Sigamani, M.; Cowan, G.; Paramesvaran, S.; Wren, A. C.; Brown, D. N.; Davis, C. L.; Denig, A. G.; Fritsch, M.; Gradl, W.; Hafner, A.; Alwyn, K. E.; Bailey, D.; Barlow, R. J.; Jackson, G.; Lafferty, G. D.; Anderson, J.; Cenci, R.; Jawahery, A.; Roberts, D. A.; Simi, G.; Tuggle, J. M.; Dallapiccola, C.; Salvati, E.; Cowan, R.; Dujmic, D.; Sciolla, G.; Zhao, M.; Lindemann, D.; Patel, P. M.; Robertson, S. H.; Schram, M.; Biassoni, P.; Lazzaro, A.; Lombardo, V.; Palombo, F.; Stracka, S.; Cremaldi, L.; Godang, R.; Kroeger, R.; Sonnek, P.; Summers, D. J.; Nguyen, X.; Simard, M.; Taras, P.; de Nardo, G.; Monorchio, D.; Onorato, G.; Sciacca, C.; Raven, G.; Snoek, H. L.; Jessop, C. P.; Knoepfel, K. J.; Losecco, J. M.; Wang, W. F.; Corwin, L. A.; Honscheid, K.; Kass, R.; Blount, N. L.; Brau, J.; Frey, R.; Igonkina, O.; Kolb, J. A.; Rahmat, R.; Sinev, N. B.; Strom, D.; Strube, J.; Torrence, E.; Castelli, G.; Feltresi, E.; Gagliardi, N.; Margoni, M.; Morandin, M.; Posocco, M.; Rotondo, M.; Simonetto, F.; Stroili, R.; Ben-Haim, E.; Bomben, M.; Bonneaud, G. R.; Briand, H.; Calderini, G.; Chauveau, J.; Hamon, O.; Leruste, Ph.; Marchiori, G.; Ocariz, J.; Prendki, J.; Sitt, S.; Biasini, M.; Manoni, E.; Rossi, A.; Angelini, C.; Batignani, G.; Bettarini, S.; Carpinelli, M.; Casarosa, G.; Cervelli, A.; Forti, F.; Giorgi, M. A.; Lusiani, A.; Neri, N.; Paoloni, E.; Rizzo, G.; Walsh, J. J.; Lopes Pegna, D.; Lu, C.; Olsen, J.; Smith, A. J. S.; Telnov, A. V.; Anulli, F.; Baracchini, E.; Cavoto, G.; Faccini, R.; Ferrarotto, F.; Ferroni, F.; Gaspero, M.; Li Gioi, L.; Mazzoni, M. A.; Piredda, G.; Renga, F.; Buenger, C.; Hartmann, T.; Leddig, T.; Schröder, H.; Waldi, R.; Adye, T.; Olaiya, E. O.; Wilson, F. F.; Emery, S.; Hamel de Monchenault, G.; Vasseur, G.; Yèche, Ch.; Allen, M. T.; Aston, D.; Bard, D. J.; Bartoldus, R.; Benitez, J. F.; Cartaro, C.; Convery, M. R.; Dorfan, J.; Dubois-Felsmann, G. P.; Dunwoodie, W.; Field, R. C.; Franco Sevilla, M.; Fulsom, B. G.; Gabareen, A. M.; Graham, M. T.; Grenier, P.; Hast, C.; Innes, W. R.; Kelsey, M. H.; Kim, H.; Kim, P.; Kocian, M. L.; Leith, D. W. G. S.; Lewis, P.; Li, S.; Lindquist, B.; Luitz, S.; Luth, V.; Lynch, H. L.; Macfarlane, D. B.; Muller, D. R.; Neal, H.; Nelson, S.; O'Grady, C. P.; Ofte, I.; Perl, M.; Pulliam, T.; Ratcliff, B. N.; Roodman, A.; Salnikov, A. A.; Santoro, V.; Schindler, R. H.; Schwiening, J.; Snyder, A.; Su, D.; Sullivan, M. K.; Sun, S.; Suzuki, K.; Thompson, J. M.; Va'Vra, J.; Wagner, A. P.; Weaver, M.; Wisniewski, W. J.; Wittgen, M.; Wright, D. H.; Wulsin, H. W.; Yarritu, A. K.; Young, C. C.; Ziegler, V.; Chen, X. R.; Park, W.; Purohit, M. V.; White, R. M.; Wilson, J. R.; Randle-Conde, A.; Sekula, S. J.; Bellis, M.; Burchat, P. R.; Miyashita, T. S.; Ahmed, S.; Alam, M. S.; Ernst, J. A.; Pan, B.; Saeed, M. A.; Zain, S. B.; Guttman, N.; Soffer, A.; Lund, P.; Spanier, S. M.; Eckmann, R.; Ritchie, J. L.; Ruland, A. M.; Schilling, C. J.; Schwitters, R. F.; Wray, B. C.; Izen, J. M.; Lou, X. C.; Bianchi, F.; Gamba, D.; Pelliccioni, M.; Lanceri, L.; Vitale, L.; Lopez-March, N.; Martinez-Vidal, F.; Oyanguren, A.; Ahmed, H.; Albert, J.; Banerjee, Sw.; Choi, H. H. F.; Hamano, K.; King, G. J.; Kowalewski, R.; Lewczuk, M. J.; Lindsay, C.; Nugent, I. M.; Roney, J. M.; Sobie, R. J.; Gershon, T. J.; Harrison, P. F.; Latham, T. E.; Puccio, E. M. T.; Band, H. R.; Dasu, S.; Flood, K. T.; Pan, Y.; Prepost, R.; Vuosalo, C. O.; Wu, S. L.

2011-09-01

We study the reactions e+e-→e+e-η(') in the single-tag mode and measure the γγ*→η(') transition form factors in the momentum-transfer range from 4 to 40GeV2. The analysis is based on 469fb-1 of integrated luminosity collected at PEP-II with the BABAR detector at e+e- center-of-mass energies near 10.6 GeV.

A Search for the Decay B+ --> K+ nu nubar

DOE Office of Scientific and Technical Information (OSTI.GOV)

Aubert, B

In this work the authors report the results of a search for the exclusive decay mode B{sup +} --> K{sup +}{nu}{bar {nu}}. By modifying the particle identification (PID) criteria used in the search, they additionally obtain a limit on the related decay B{sup +} --> {pi}{sup +}{nu}{bar {nu}}. The data used in this analysis were collected with the BABAR detector at the PEP-II asymmetric-energy e{sup +}e{sup -} storage ring.

Deep learning in breast cancer risk assessment: evaluation of convolutional neural networks on a clinical dataset of full-field digital mammograms.

PubMed

Li, Hui; Giger, Maryellen L; Huynh, Benjamin Q; Antropova, Natalia O

2017-10-01

To evaluate deep learning in the assessment of breast cancer risk in which convolutional neural networks (CNNs) with transfer learning are used to extract parenchymal characteristics directly from full-field digital mammographic (FFDM) images instead of using computerized radiographic texture analysis (RTA), 456 clinical FFDM cases were included: a "high-risk" BRCA1/2 gene-mutation carriers dataset (53 cases), a "high-risk" unilateral cancer patients dataset (75 cases), and a "low-risk dataset" (328 cases). Deep learning was compared to the use of features from RTA, as well as to a combination of both in the task of distinguishing between high- and low-risk subjects. Similar classification performances were obtained using CNN [area under the curve [Formula: see text]; standard error [Formula: see text

Full-motion video analysis for improved gender classification

NASA Astrophysics Data System (ADS)

Flora, Jeffrey B.; Lochtefeld, Darrell F.; Iftekharuddin, Khan M.

2014-06-01

The ability of computer systems to perform gender classification using the dynamic motion of the human subject has important applications in medicine, human factors, and human-computer interface systems. Previous works in motion analysis have used data from sensors (including gyroscopes, accelerometers, and force plates), radar signatures, and video. However, full-motion video, motion capture, range data provides a higher resolution time and spatial dataset for the analysis of dynamic motion. Works using motion capture data have been limited by small datasets in a controlled environment. In this paper, we explore machine learning techniques to a new dataset that has a larger number of subjects. Additionally, these subjects move unrestricted through a capture volume, representing a more realistic, less controlled environment. We conclude that existing linear classification methods are insufficient for the gender classification for larger dataset captured in relatively uncontrolled environment. A method based on a nonlinear support vector machine classifier is proposed to obtain gender classification for the larger dataset. In experimental testing with a dataset consisting of 98 trials (49 subjects, 2 trials per subject), classification rates using leave-one-out cross-validation are improved from 73% using linear discriminant analysis to 88% using the nonlinear support vector machine classifier.

Search for the rare leptonic decay B+-->mu(+)nu(mu).

PubMed

Aubert, B; Barate, R; Boutigny, D; Couderc, F; Gaillard, J-M; Hicheur, A; Karyotakis, Y; Lees, J P; Tisserand, V; Zghiche, A; Palano, A; Pompili, A; Chen, J C; Qi, N D; Rong, G; Wang, P; Zhu, Y S; Eigen, G; Ofte, I; Stugu, B; Abrams, G S; Borgland, A W; Breon, A B; Brown, D N; Button-Shafer, J; Cahn, R N; Charles, E; Day, C T; Gill, M S; Gritsan, A V; Groysman, Y; Jacobsen, R G; Kadel, R W; Kadyk, J; Kerth, L T; Kolomensky, Yu G; Kukartsev, G; LeClerc, C; Levi, M E; Lynch, G; Mir, L M; Oddone, P J; Orimoto, T J; Pripstein, M; Roe, N A; Ronan, M T; Shelkov, V G; Telnov, A V; Wenzel, W A; Ford, K; Harrison, T J; Hawkes, C M; Morgan, S E; Watson, A T; Watson, N K; Fritsch, M; Goetzen, K; Held, T; Koch, H; Lewandowski, B; Pelizaeus, M; Peters, K; Schmuecker, H; Steinke, M; Boyd, J T; Chevalier, N; Cottingham, W N; Kelly, M P; Latham, T E; Mackay, C; Wilson, F F; Abe, K; Cuhadar-Donszelmann, T; Hearty, C; Mattison, T S; McKenna, J A; Thiessen, D; Kyberd, P; McKemey, A K; Teodorescu, L; Blinov, V E; Bukin, A D; Golubev, V B; Ivanchenko, V N; Kravchenko, E A; Onuchin, A P; Serednyakov, S I; Skovpen, Yu I; Solodov, E P; Yushkov, A N; Best, D; Bruinsma, M; Chao, M; Eschrich, I; Kirkby, D; Lankford, A J; Mandelkern, M; Mommsen, R K; Roethel, W; Stoker, D P; Buchanan, C; Hartfiel, B L; Gary, J W; Layter, J; Shen, B C; Wang, K; del Re, D; Hadavand, H K; Hill, E J; MacFarlane, D B; Paar, H P; Rahatlou, Sh; Sharma, V; Berryhill, J W; Campagnari, C; Dahmes, B; Levy, S L; Long, O; Lu, A; Mazur, M A; Richman, J D; Verkerke, W; Beck, T W; Beringer, J; Eisner, A M; Heusch, C A; Lockman, W S; Schalk, T; Schmitz, R E; Schumm, B A; Seiden, A; Spradlin, P; Walkowiak, W; Williams, D C; Wilson, M G; Albert, J; Chen, E; Dubois-Felsmann, G P; Dvoretskii, A; Erwin, R J; Hitlin, D G; Narsky, I; Piatenko, T; Porter, F C; Ryd, A; Samuel, A; Yang, S; Jayatilleke, S; Mancinelli, G; Meadows, B T; Sokoloff, M D; Abe, T; Blanc, F; Bloom, P; Chen, S; Clark, P J; Ford, W T; Nauenberg, U; Olivas, A; Rankin, P; Roy, J; Smith, J G; van Hoek, W C; Zhang, L; Harton, J L; Hu, T; Soffer, A; Toki, W H; Wilson, R J; Zhang, J; Altenburg, D; Brandt, T; Brose, J; Colberg, T; Dickopp, M; Feltresi, E; Hauke, A; Lacker, H M; Maly, E; Müller-Pfefferkorn, R; Nogowski, R; Otto, S; Schubert, J; Schubert, K R; Schwierz, R; Spaan, B; Bernard, D; Bonneaud, G R; Brochard, F; Grenier, P; Thiebaux, Ch; Vasileiadis, G; Verderi, M; Bard, D J; Khan, A; Lavin, D; Muheim, F; Playfer, S; Andreotti, M; Azzolini, V; Bettoni, D; Bozzi, C; Calabrese, R; Cibinetto, G; Luppi, E; Negrini, M; Piemontese, L; Sarti, A; Treadwell, E; Baldini-Ferroli, R; Calcaterra, A; de Sangro, R; Finocchiaro, G; Patteri, P; Piccolo, M; Zallo, A; Buzzo, A; Capra, R; Contri, R; Crosetti, G; Lo Vetere, M; Macri, M; Monge, M R; Passaggio, S; Patrignani, C; Robutti, E; Santroni, A; Tosi, S; Bailey, S; Morii, M; Won, E; Dubitzky, R S; Langenegger, U; Bhimji, W; Bowerman, D A; Dauncey, P D; Egede, U; Gaillard, J R; Morton, G W; Nash, J A; Taylor, G P; Grenier, G J; Lee, S-J; Mallik, U; Cochran, J; Crawley, H B; Lamsa, J; Meyer, W T; Prell, S; Rosenberg, E I; Yi, J; Davier, M; Grosdidier, G; Höcker, A; Laplace, S; Le Diberder, F; Lepeltier, V; Lutz, A M; Petersen, T C; Plaszczynski, S; Schune, M H; Tantot, L; Wormser, G; Brigljević, V; Cheng, C H; Lange, D J; Simani, M C; Wright, D M; Bevan, A J; Coleman, J P; Fry, J R; Gabathuler, E; Gamet, R; Kay, M; Parry, R J; Payne, D J; Sloane, R J; Touramanis, C; Back, J J; Harrison, P F; Mohanty, G B; Brown, C L; Cowan, G; Flack, R L; Flaecher, H U; George, S; Green, M G; Kurup, A; Marker, C E; McMahon, T R; Ricciardi, S; Salvatore, F; Vaitsas, G; Winter, M A; Brown, D; Davis, C L; Allison, J; Barlow, N R; Barlow, R J; Hart, P A; Hodgkinson, M C; Lafferty, G D; Lyon, A J; Williams, J C; Farbin, A; Hulsbergen, W D; Jawahery, A; Kovalskyi, D; Lae, C K; Lillard, V; Roberts, D A; Blaylock, G; Dallapiccola, C; Flood, K T; Hertzbach, S S; Kofler, R; Koptchev, V B; Moore, T B; Saremi, S; Staengle, H; Willocq, S; Cowan, R; Sciolla, G; Taylor, F; Yamamoto, R K; Mangeol, D J J; Patel, P M; Robertson, S H; Lazzaro, A; Palombo, F; Bauer, J M; Cremaldi, L; Eschenburg, V; Godang, R; Kroeger, R; Reidy, J; Sanders, D A; Summers, D J; Zhao, H W; Brunet, S; Cote-Ahern, D; Taras, P; Nicholson, H; Cartaro, C; Cavallo, N; De Nardo, G; Fabozzi, F; Gatto, C; Lista, L; Paolucci, P; Piccolo, D; Sciacca, C; Baak, M A; Raven, G; Wilden, L; Jessop, C P; LoSecco, J M; Gabriel, T A; Allmendinger, T; Brau, B; Gan, K K; Honscheid, K; Hufnagel, D; Kagan, H; Kass, R; Pulliam, T; Ter-Antonyan, R; Wong, Q K; Brau, J; Frey, R; Igonkina, O; Potter, C T; Sinev, N B; Strom, D; Torrence, E; Colecchia, F; Dorigo, A; Galeazzi, F; Margoni, M; Morandin, M; Posocco, M; Rotondo, M; Simonetto, F; Stroili, R; Tiozzo, G; Voci, C; Benayoun, M; Briand, H; Chauveau, J; David, P; de la Vaissière, Ch; Del Buono, L; Hamon, O; John, M J J; Leruste, Ph; Ocariz, J; Pivk, M; Roos, L; T'Jampens, S; Therin, G; Manfredi, P F; Re, V; Behera, P K; Gladney, L; Guo, Q H; Panetta, J; Anulli, F; Biasini, M; Peruzzi, I M; Pioppi, M; Angelini, C; Batignani, G; Bettarini, S; Bondioli, M; Bucci, F; Calderini, G; Carpinelli, M; Del Gamba, V; Forti, F; Giorgi, M A; Lusiani, A; Marchiori, G; Martinez-Vidal, F; Morganti, M; Neri, N; Paoloni, E; Rama, M; Rizzo, G; Sandrelli, F; Walsh, J; Haire, M; Judd, D; Paick, K; Wagoner, D E; Danielson, N; Elmer, P; Lu, C; Miftakov, V; Olsen, J; Smith, A J S; Varnes, E W; Bellini, F; Cavoto, G; Faccini, R; Ferrarotto, F; Ferroni, F; Gaspero, M; Mazzoni, M A; Morganti, S; Pierini, M; Piredda, G; Safai Tehrani, F; Voena, C; Christ, S; Wagner, G; Waldi, R; Adye, T; De Groot, N; Franek, B; Geddes, N I; Gopal, G P; Olaiya, E O; Xella, S M; Aleksan, R; Emery, S; Gaidot, A; Ganzhur, S F; Giraud, P-F; Hamel de Monchenault, G; Kozanecki, W; Langer, M; Legendre, M; London, G W; Mayer, B; Schott, G; Vasseur, G; Yeche, Ch; Zito, M; Purohit, M V; Weidemann, A W; Yumiceva, F X; Aston, D; Bartoldus, R; Berger, N; Boyarski, A M; Buchmueller, O L; Convery, M R; Cristinziani, M; Dong, D; Dorfan, J; Dujmic, D; Dunwoodie, W; Elsen, E E; Field, R C; Glanzman, T; Gowdy, S J; Hadig, T; Halyo, V; Hryn'ova, T; Innes, W R; Kelsey, M H; Kim, P; Kocian, M L; Leith, D W G S; Libby, J; Luitz, S; Luth, V; Lynch, H L; Marsiske, H; Messner, R; Muller, D R; O'Grady, C P; Ozcan, V E; Perazzo, A; Perl, M; Petrak, S; Ratcliff, B N; Roodman, A; Salnikov, A A; Schindler, R H; Schwiening, J; Simi, G; Snyder, A; Soha, A; Stelzer, J; Su, D; Sullivan, M K; Va'vra, J; Wagner, S R; Weaver, M; Weinstein, A J R; Wisniewski, W J; Wright, D H; Young, C C; Burchat, P R; Edwards, A J; Meyer, T I; Petersen, B A; Roat, C; Ahmed, M; Ahmed, S; Alam, M S; Ernst, J A; Saeed, M A; Saleem, M; Wappler, F R; Bugg, W; Krishnamurthy, M; Spanier, S M; Eckmann, R; Kim, H; Ritchie, J L; Satpathy, A; Schwitters, R F; Izen, J M; Kitayama, I; Lou, X C; Ye, S; Bianchi, F; Bona, M; Gallo, F; Gamba, D; Borean, C; Bosisio, L; Cossutti, F; Della Ricca, G; Dittongo, S; Grancagnolo, S; Lanceri, L; Poropat, P; Vitale, L; Vuagnin, G; Panvini, R S; Banerjee, Sw; Brown, C M; Fortin, D; Jackson, P D; Kowalewski, R; Roney, J M; Band, H R; Dasu, S; Datta, M; Eichenbaum, A M; Johnson, J R; Kutter, P E; Li, H; Liu, R; Lodovico, F Di; Mihalyi, A; Mohapatra, A K; Pan, Y; Prepost, R; Sekula, S J; von Wimmersperg-Toeller, J H; Wu, J; Wu, S L; Yu, Z; Neal, H; Christinziani, B

2004-06-04

We have performed a search for the rare leptonic decay B+-->mu(+)nu(mu) with data collected at the Upsilon(4S) resonance by the BABAR experiment at the PEP-II storage ring. In a sample of 88.4 x 10(6) BB pairs, we find no significant evidence for a signal and set an upper limit on the branching fraction B(B+-->my(+)nu(my))< 6.6 x 10(-6) at the 90% confidence level.

Search for the lepton flavour violating decay μ ^+ → e^+ γ with the full dataset of the MEG experiment

NASA Astrophysics Data System (ADS)

Baldini, A. M.; Bao, Y.; Baracchini, E.; Bemporad, C.; Berg, F.; Biasotti, M.; Boca, G.; Cascella, M.; Cattaneo, P. W.; Cavoto, G.; Cei, F.; Cerri, C.; Chiarello, G.; Chiri, C.; Corvaglia, A.; de Bari, A.; De Gerone, M.; Doke, T.; D'Onofrio, A.; Dussoni, S.; Egger, J.; Fujii, Y.; Galli, L.; Gatti, F.; Grancagnolo, F.; Grassi, M.; Graziosi, A.; Grigoriev, D. N.; Haruyama, T.; Hildebrandt, M.; Hodge, Z.; Ieki, K.; Ignatov, F.; Iwamoto, T.; Kaneko, D.; Kang, T. I.; Kettle, P.-R.; Khazin, B. I.; Khomutov, N.; Korenchenko, A.; Kravchuk, N.; Lim, G. M. A.; Maki, A.; Mihara, S.; Molzon, W.; Mori, Toshinori; Morsani, F.; Mtchedilishvili, A.; Mzavia, D.; Nakaura, S.; Nardò, R.; Nicolò, D.; Nishiguchi, H.; Nishimura, M.; Ogawa, S.; Ootani, W.; Orito, S.; Panareo, M.; Papa, A.; Pazzi, R.; Pepino, A.; Piredda, G.; Pizzigoni, G.; Popov, A.; Raffaelli, F.; Renga, F.; Ripiccini, E.; Ritt, S.; Rossella, M.; Rutar, G.; Sawada, R.; Sergiampietri, F.; Signorelli, G.; Simonetta, M.; Tassielli, G. F.; Tenchini, F.; Uchiyama, Y.; Venturini, M.; Voena, C.; Yamamoto, A.; Yoshida, K.; You, Z.; Yudin, Yu. V.; Zanello, D.

2016-08-01

The final results of the search for the lepton flavour violating decay μ^+ → e^+ γ based on the full dataset collected by the MEG experiment at the Paul Scherrer Institut in the period 2009-2013 and totalling 7.5× 10^{14} stopped muons on target are presented. No significant excess of events is observed in the dataset with respect to the expected background and a new upper limit on the branching ratio of this decay of B (μ ^+ → e^+ γ ) < 4.2 × 10^{-13} (90 % confidence level) is established, which represents the most stringent limit on the existence of this decay to date.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Miftakov, V

The BABAR experiment at SLAC provides an opportunity for measurement of the Standard Model parameters describing CP violation. A method of measuring the CKM matrix element |V{sub cb}| using Inclusive Semileptonic B decays in events tagged by a fully reconstructed decay of one of the B mesons is presented here. This mode is considered to be one of the most powerful approaches due to its large branching fraction, simplicity of the theoretical description and very clean experimental signatures. Using fully reconstructed B mesons to flag B{bar B} event we were able to produce the spectrum and branching fraction for electronmore » momenta P{sub C.M.S.} > 0.5 GeV/c. Extrapolation to the lower momenta has been carried out with Heavy Quark Effective Theory. The branching fractions are measured separately for charged and neutral B mesons. For 82 fb{sup -1} of data collected at BABAR we obtain: BR(B{sup {+-}} {yields} X e{bar {nu}}) = 10.63 {+-} 0.24 {+-} 0.29%, BR(B{sup 0} {yields} X e{bar {nu}}) = 10.68 {+-} 0.34 {+-} 0.31%, averaged BR(B {yields} X e{bar {nu}}) = 10.65 {+-} 0.19 {+-} 0.27%, ratio of Branching fractions BR(B{sup {+-}})/BR(B{sup 0}) = 0.996 {+-} 0.039 {+-} 0.015 (errors are statistical and systematic, respectively). They also obtain V{sub cb} = 0.0409 {+-} 0.00074 {+-} 0.0010 {+-} 0.000858 (errors are: statistical, systematic and theoretical).« less

Recent results on search for new physics at BaBar

NASA Astrophysics Data System (ADS)

Oberhof, Benjamin

2017-04-01

We present some recent measurements for the search of New Physics using 514 fb-1 of e+e- collisions collected with the BaBar detector at the PEP-II e+e- collider at SLAC. First we present a search for the decay ϒ (1S) → γA0, A0 → cc¯, where A0 is a candidate for the CP-odd Higgs boson of the next-to-minimal supersymmetric standard model. No significant signal is observed and we set 90% confidence-level upper limits on B(ϒ(1S ) → γA0) × B(A0 → cc¯). We report the search for a light non-Standard Model gauge boson Z' coupling only to the second and third lepton families. Our results significantly improve current limits and further constrain the remaining region of the allowed parameter space. Finally, we present a search for a long-lived particle L that is produced in e+e- annihilations and decays into two oppositely charged tracks. We do not observe a significant signal and we and set 90% confidence level upper limits on the product of the L production cross section, branching fraction, and reconstruction efficiency as a function of the L mass. In addition, upper limits are provided on the branching fraction B(B → XsL), where Xs is an hadronic system with strangeness -1.

Measurement of the e+e-→π+π-π0π0 cross section using initial-state radiation at BABAR

NASA Astrophysics Data System (ADS)

Lees, J. P.; Poireau, V.; Tisserand, V.; Grauges, E.; Palano, A.; Eigen, G.; Brown, D. N.; Kolomensky, Yu. G.; Fritsch, M.; Koch, H.; Schroeder, T.; Hearty, C.; Mattison, T. S.; McKenna, J. A.; So, R. Y.; Blinov, V. E.; Buzykaev, A. R.; Druzhinin, V. P.; Golubev, V. B.; Kravchenko, E. A.; Onuchin, A. P.; Serednyakov, S. I.; Skovpen, Yu. I.; Solodov, E. P.; Todyshev, K. Yu.; Lankford, A. J.; Gary, J. W.; Long, O.; Eisner, A. M.; Lockman, W. S.; Panduro Vazquez, W.; Chao, D. S.; Cheng, C. H.; Echenard, B.; Flood, K. T.; Hitlin, D. G.; Kim, J.; Miyashita, T. S.; Ongmongkolkul, P.; Porter, F. C.; Röhrken, M.; Huard, Z.; Meadows, B. T.; Pushpawela, B. G.; Sokoloff, M. D.; Sun, L.; Smith, J. G.; Wagner, S. R.; Bernard, D.; Verderi, M.; Bettoni, D.; Bozzi, C.; Calabrese, R.; Cibinetto, G.; Fioravanti, E.; Garzia, I.; Luppi, E.; Santoro, V.; Calcaterra, A.; de Sangro, R.; Finocchiaro, G.; Martellotti, S.; Patteri, P.; Peruzzi, I. M.; Piccolo, M.; Rotondo, M.; Zallo, A.; Passaggio, S.; Patrignani, C.; Lacker, H. M.; Bhuyan, B.; Mallik, U.; Chen, C.; Cochran, J.; Prell, S.; Ahmed, H.; Gritsan, A. V.; Arnaud, N.; Davier, M.; Le Diberder, F.; Lutz, A. M.; Wormser, G.; Lange, D. J.; Wright, D. M.; Coleman, J. P.; Gabathuler, E.; Hutchcroft, D. E.; Payne, D. J.; Touramanis, C.; Bevan, A. J.; di Lodovico, F.; Sacco, R.; Cowan, G.; Banerjee, Sw.; Brown, D. N.; Davis, C. L.; Denig, A. G.; Gradl, W.; Griessinger, K.; Hafner, A.; Schubert, K. R.; Barlow, R. J.; Lafferty, G. D.; Cenci, R.; Jawahery, A.; Roberts, D. A.; Cowan, R.; Robertson, S. H.; Dey, B.; Neri, N.; Palombo, F.; Cheaib, R.; Cremaldi, L.; Godang, R.; Summers, D. J.; Taras, P.; de Nardo, G.; Sciacca, C.; Raven, G.; Jessop, C. P.; Losecco, J. M.; Honscheid, K.; Kass, R.; Gaz, A.; Margoni, M.; Posocco, M.; Simi, G.; Simonetto, F.; Stroili, R.; Akar, S.; Ben-Haim, E.; Bomben, M.; Bonneaud, G. R.; Calderini, G.; Chauveau, J.; Marchiori, G.; Ocariz, J.; Biasini, M.; Manoni, E.; Rossi, A.; Batignani, G.; Bettarini, S.; Carpinelli, M.; Casarosa, G.; Chrzaszcz, M.; Forti, F.; Giorgi, M. A.; Lusiani, A.; Oberhof, B.; Paoloni, E.; Rama, M.; Rizzo, G.; Walsh, J. J.; Smith, A. J. S.; Anulli, F.; Faccini, R.; Ferrarotto, F.; Ferroni, F.; Pilloni, A.; Piredda, G.; Bünger, C.; Dittrich, S.; Grünberg, O.; Heß, M.; Leddig, T.; Voß, C.; Waldi, R.; Adye, T.; Wilson, F. F.; Emery, S.; Vasseur, G.; Aston, D.; Cartaro, C.; Convery, M. R.; Dorfan, J.; Dunwoodie, W.; Ebert, M.; Field, R. C.; Fulsom, B. G.; Graham, M. T.; Hast, C.; Innes, W. R.; Kim, P.; Leith, D. W. G. S.; Luitz, S.; Macfarlane, D. B.; Muller, D. R.; Neal, H.; Ratcliff, B. N.; Roodman, A.; Sullivan, M. K.; Va'Vra, J.; Wisniewski, W. J.; Purohit, M. V.; Wilson, J. R.; Randle-Conde, A.; Sekula, S. J.; Bellis, M.; Burchat, P. R.; Puccio, E. M. T.; Alam, M. S.; Ernst, J. A.; Gorodeisky, R.; Guttman, N.; Peimer, D. R.; Soffer, A.; Spanier, S. M.; Ritchie, J. L.; Schwitters, R. F.; Izen, J. M.; Lou, X. C.; Bianchi, F.; de Mori, F.; Filippi, A.; Gamba, D.; Lanceri, L.; Vitale, L.; Martinez-Vidal, F.; Oyanguren, A.; Albert, J.; Beaulieu, A.; Bernlochner, F. U.; King, G. J.; Kowalewski, R.; Lueck, T.; Nugent, I. M.; Roney, J. M.; Sobie, R. J.; Tasneem, N.; Gershon, T. J.; Harrison, P. F.; Latham, T. E.; Prepost, R.; Wu, S. L.; Babar Collaboration

2017-11-01

The process e+e-→π+π-2 π0γ is investigated by means of the initial-state radiation technique, where a photon is emitted from the incoming electron or positron. Using 454.3 fb-1 of data collected around a center-of-mass energy of √{s }=10.58 GeV by the BABAR experiment at SLAC, approximately 150000 signal events are obtained. The corresponding nonradiative cross section is measured with a relative uncertainty of 3.6% in the energy region around 1.5 GeV, surpassing all existing measurements in precision. Using this new result, the channel's contribution to the leading order hadronic vacuum polarization contribution to the anomalous magnetic moment of the muon is calculated as (gμπ+π-2 π0-2 )/2 =(17.9 ±0.1stat±0.6syst)×10-10 in the energy range 0.85 GeV

Cluster Active Archive: lessons learnt

NASA Astrophysics Data System (ADS)

Laakso, H. E.; Perry, C. H.; Taylor, M. G.; Escoubet, C. P.; Masson, A.

2010-12-01

The ESA Cluster Active Archive (CAA) was opened to public in February 2006 after an initial three-year development phase. It provides access (both web GUI and command-line tool are available) to the calibrated full-resolution datasets of the four-satellite Cluster mission. The data archive is publicly accessible and suitable for science use and publication by the world-wide scientific community. There are more than 350 datasets from each spacecraft, including high-resolution magnetic and electric DC and AC fields as well as full 3-dimensional electron and ion distribution functions and moments from a few eV to hundreds of keV. The Cluster mission has been in operation since February 2001, and currently although the CAA can provide access to some recent observations, the ingestion of some other datasets can be delayed by a few years due to large and difficult calibration routines of aging detectors. The quality of the datasets is the central matter to the CAA. Having the same instrument on four spacecraft allows the cross-instrument comparisons and provide confidence on some of the instrumental calibration parameters. Furthermore it is highly important that many physical parameters are measured by more than one instrument which allow to perform extensive and continuous cross-calibration analyses. In addition some of the instruments can be regarded as absolute or reference measurements for other instruments. The CAA attempts to avoid as much as possible mission-specific acronyms and concepts and tends to use more generic terms in describing the datasets and their contents in order to ease the usage of the CAA data by “non-Cluster” scientists. Currently the CAA has more 1000 users and every month more than 150 different users log in the CAA for plotting and/or downloading observations. The users download about 1 TeraByte of data every month. The CAA has separated the graphical tool from the download tool because full-resolution datasets can be visualized in many ways and so there is no one-to-one correspondence between graphical products and full-resolution datasets. The CAA encourages users to contact the CAA team for all kind of issues whether it concerns the user interface, the content of the datasets, the quality of the observations or provision of new type of services. The CAA runs regular annual reviews on the data products and the user services in order to improve the quality and usability of the CAA system to the world-wide user community. The CAA is continuously being upgraded in terms of datasets and services.

Search for the lepton flavour violating decay $$\\mu ^+ \\rightarrow \\mathrm {e}^+ \\gamma $$ with the full dataset of the MEG experiment: MEG Collaboration

DOE PAGES

Baldini, A. M.; Bao, Y.; Baracchini, E.; ...

2016-08-03

Our final results of the search for the lepton flavour violating decay μ+→e+γ based on the full dataset collected by the MEG experiment at the Paul Scherrer Institut in the period 2009–2013 and totalling 7.5×1014 stopped muons on target are presented. Furthermore, there was not a significant excess of events observed in the dataset with respect to the expected background and a new upper limit on the branching ratio of this decay of B(μ+→e+γ)<4.2×10-13 (90 % confidence level) is established, which represents the most stringent limit on the existence of this decay to date.

Measurements of Branching Ratios And Search for CP Violation in the Modes B0 to Rho Pi, Rho K (in French)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Laplace, Sandrine; /Paris U., VI-VII

2006-09-18

The BABAR experiment, at the PEP-II collider at SLAC, has been studying since 1999 CP violation in the B meson system. After the precise measurement of sin2{beta}, one is now concentrating on measuring the angles {alpha} and {gamma} of the unitarity triangle. The work presented in this thesis concerns the measurement of the angle {alpha} in the B{sup 0} {yields} {rho}{pi} mode.

Progress on Development of the New FDIRC PID Detector

DOE Office of Scientific and Technical Information (OSTI.GOV)

Vavra, Jerry

2012-08-03

We present a progress status of a new concept of PID detector called FDIRC, intended to be used at the SuperB experiment, which requires {pi}/K separation up to a few GeV/c. The new photon camera is made of the solid fused-silica optics with a volume 25x smaller and speed increased by a factor of ten compared to the BaBar DIRC, and therefore will be much less sensitive to electromagnetic and neutron background

Radiative Penguin Decays at the B Factories

DOE Office of Scientific and Technical Information (OSTI.GOV)

Koneke, Karsten; /MIT, LNS

2007-11-16

In this article, I review the most recent results in radiative penguin decays from the B factories Belle and BABAR. Most notably, I will talk about the recent new observations in the decays B {yields} ({rho}/{omega}) {gamma}, a new analysis technique in b {yields} s{gamma}, and first measurements of radiative penguin decays in the B{sup 0}{sub s} meson system. Finally, I will summarize the current status and future prospects of radiative penguin B physics at the B factories.

Dalitz plot analysis of Ds+→K+K-π+

NASA Astrophysics Data System (ADS)

Del Amo Sanchez, P.; Lees, J. P.; Poireau, V.; Prencipe, E.; Tisserand, V.; Garra Tico, J.; Grauges, E.; Martinelli, M.; Milanes, D. A.; Palano, A.; Pappagallo, M.; Eigen, G.; Stugu, B.; Sun, L.; Brown, D. N.; Kerth, L. T.; Kolomensky, Yu. G.; Lynch, G.; Osipenkov, I. L.; Koch, H.; Schroeder, T.; Asgeirsson, D. J.; Hearty, C.; Mattison, T. S.; McKenna, J. A.; Khan, A.; Blinov, V. E.; Buzykaev, A. R.; Druzhinin, V. P.; Golubev, V. B.; Kravchenko, E. A.; Onuchin, A. P.; Serednyakov, S. I.; Skovpen, Yu. I.; Solodov, E. P.; Todyshev, K. Yu.; Yushkov, A. N.; Bondioli, M.; Curry, S.; Kirkby, D.; Lankford, A. J.; Mandelkern, M.; Martin, E. C.; Stoker, D. P.; Atmacan, H.; Gary, J. W.; Liu, F.; Long, O.; Vitug, G. M.; Campagnari, C.; Hong, T. M.; Kovalskyi, D.; Richman, J. D.; West, C.; Eisner, A. M.; Heusch, C. A.; Kroseberg, J.; Lockman, W. S.; Martinez, A. J.; Schalk, T.; Schumm, B. A.; Seiden, A.; Winstrom, L. O.; Cheng, C. H.; Doll, D. A.; Echenard, B.; Hitlin, D. G.; Ongmongkolkul, P.; Porter, F. C.; Rakitin, A. Y.; Andreassen, R.; Dubrovin, M. S.; Mancinelli, G.; Meadows, B. T.; Sokoloff, M. D.; Bloom, P. C.; Ford, W. T.; Gaz, A.; Nagel, M.; Nauenberg, U.; Smith, J. G.; Wagner, S. R.; Ayad, R.; Toki, W. H.; Jasper, H.; Karbach, T. M.; Petzold, A.; Spaan, B.; Kobel, M. J.; Schubert, K. R.; Schwierz, R.; Bernard, D.; Verderi, M.; Clark, P. J.; Playfer, S.; Watson, J. E.; Andreotti, M.; Bettoni, D.; Bozzi, C.; Calabrese, R.; Cecchi, A.; Cibinetto, G.; Fioravanti, E.; Franchini, P.; Garzia, I.; Luppi, E.; Munerato, M.; Negrini, M.; Petrella, A.; Piemontese, L.; Baldini-Ferroli, R.; Calcaterra, A.; de Sangro, R.; Finocchiaro, G.; Nicolaci, M.; Pacetti, S.; Patteri, P.; Peruzzi, I. M.; Piccolo, M.; Rama, M.; Zallo, A.; Contri, R.; Guido, E.; Lo Vetere, M.; Monge, M. R.; Passaggio, S.; Patrignani, C.; Robutti, E.; Tosi, S.; Bhuyan, B.; Prasad, V.; Lee, C. L.; Morii, M.; Edwards, A. J.; Adametz, A.; Marks, J.; Uwer, U.; Bernlochner, F. U.; Ebert, M.; Lacker, H. M.; Lueck, T.; Volk, A.; Dauncey, P. D.; Tibbetts, M.; Behera, P. K.; Mallik, U.; Chen, C.; Cochran, J.; Crawley, H. B.; Dong, L.; Meyer, W. T.; Prell, S.; Rosenberg, E. I.; Rubin, A. E.; Gritsan, A. V.; Guo, Z. J.; Arnaud, N.; Davier, M.; Derkach, D.; Firmino da Costa, J.; Grosdidier, G.; Le Diberder, F.; Lutz, A. M.; Malaescu, B.; Perez, A.; Roudeau, P.; Schune, M. H.; Serrano, J.; Sordini, V.; Stocchi, A.; Wang, L.; Wormser, G.; Lange, D. J.; Wright, D. M.; Bingham, I.; Chavez, C. A.; Coleman, J. P.; Fry, J. R.; Gabathuler, E.; Gamet, R.; Hutchcroft, D. E.; Payne, D. J.; Touramanis, C.; Bevan, A. J.; di Lodovico, F.; Sacco, R.; Sigamani, M.; Cowan, G.; Paramesvaran, S.; Wren, A. C.; Brown, D. N.; Davis, C. L.; Denig, A. G.; Fritsch, M.; Gradl, W.; Hafner, A.; Alwyn, K. E.; Bailey, D.; Barlow, R. J.; Jackson, G.; Lafferty, G. D.; Anderson, J.; Cenci, R.; Jawahery, A.; Roberts, D. A.; Simi, G.; Tuggle, J. M.; Dallapiccola, C.; Salvati, E.; Cowan, R.; Dujmic, D.; Sciolla, G.; Zhao, M.; Lindemann, D.; Patel, P. M.; Robertson, S. H.; Schram, M.; Biassoni, P.; Lazzaro, A.; Lombardo, V.; Palombo, F.; Stracka, S.; Cremaldi, L.; Godang, R.; Kroeger, R.; Sonnek, P.; Summers, D. J.; Nguyen, X.; Simard, M.; Taras, P.; de Nardo, G.; Monorchio, D.; Onorato, G.; Sciacca, C.; Raven, G.; Snoek, H. L.; Jessop, C. P.; Knoepfel, K. J.; Losecco, J. M.; Wang, W. F.; Corwin, L. A.; Honscheid, K.; Kass, R.; Morris, J. P.; Blount, N. L.; Brau, J.; Frey, R.; Igonkina, O.; Kolb, J. A.; Rahmat, R.; Sinev, N. B.; Strom, D.; Strube, J.; Torrence, E.; Castelli, G.; Feltresi, E.; Gagliardi, N.; Margoni, M.; Morandin, M.; Posocco, M.; Rotondo, M.; Simonetto, F.; Stroili, R.; Ben-Haim, E.; Bonneaud, G. R.; Briand, H.; Calderini, G.; Chauveau, J.; Hamon, O.; Leruste, Ph.; Marchiori, G.; Ocariz, J.; Prendki, J.; Sitt, S.; Biasini, M.; Manoni, E.; Rossi, A.; Angelini, C.; Batignani, G.; Bettarini, S.; Carpinelli, M.; Casarosa, G.; Cervelli, A.; Forti, F.; Giorgi, M. A.; Lusiani, A.; Neri, N.; Paoloni, E.; Rizzo, G.; Walsh, J. J.; Lopes Pegna, D.; Lu, C.; Olsen, J.; Smith, A. J. S.; Telnov, A. V.; Anulli, F.; Baracchini, E.; Cavoto, G.; Faccini, R.; Ferrarotto, F.; Ferroni, F.; Gaspero, M.; Li Gioi, L.; Mazzoni, M. A.; Piredda, G.; Renga, F.; Hartmann, T.; Leddig, T.; Schröder, H.; Waldi, R.; Adye, T.; Franek, B.; Olaiya, E. O.; Wilson, F. F.; Emery, S.; Hamel de Monchenault, G.; Vasseur, G.; Yèche, Ch.; Zito, M.; Allen, M. T.; Aston, D.; Bard, D. J.; Bartoldus, R.; Benitez, J. F.; Cartaro, C.; Convery, M. R.; Dorfan, J.; Dubois-Felsmann, G. P.; Dunwoodie, W.; Field, R. C.; Franco Sevilla, M.; Fulsom, B. G.; Gabareen, A. M.; Graham, M. T.; Grenier, P.; Hast, C.; Innes, W. R.; Kelsey, M. H.; Kim, H.; Kim, P.; Kocian, M. L.; Leith, D. W. G. S.; Li, S.; Lindquist, B.; Luitz, S.; Luth, V.; Lynch, H. L.; Macfarlane, D. B.; Marsiske, H.; Muller, D. R.; Neal, H.; Nelson, S.; O'Grady, C. P.; Ofte, I.; Perl, M.; Pulliam, T.; Ratcliff, B. N.; Roodman, A.; Salnikov, A. A.; Santoro, V.; Schindler, R. H.; Schwiening, J.; Snyder, A.; Su, D.; Sullivan, M. K.; Sun, S.; Suzuki, K.; Thompson, J. M.; Va'Vra, J.; Wagner, A. P.; Weaver, M.; Wisniewski, W. J.; Wittgen, M.; Wright, D. H.; Wulsin, H. W.; Yarritu, A. K.; Young, C. C.; Ziegler, V.; Chen, X. R.; Park, W.; Purohit, M. V.; White, R. M.; Wilson, J. R.; Randle-Conde, A.; Sekula, S. J.; Bellis, M.; Burchat, P. R.; Miyashita, T. S.; Ahmed, S.; Alam, M. S.; Ernst, J. A.; Pan, B.; Saeed, M. A.; Zain, S. B.; Guttman, N.; Soffer, A.; Lund, P.; Spanier, S. M.; Eckmann, R.; Ritchie, J. L.; Ruland, A. M.; Schilling, C. J.; Schwitters, R. F.; Wray, B. C.; Izen, J. M.; Lou, X. C.; Bianchi, F.; Gamba, D.; Pelliccioni, M.; Bomben, M.; Lanceri, L.; Vitale, L.; Lopez-March, N.; Martinez-Vidal, F.; Oyanguren, A.; Albert, J.; Banerjee, Sw.; Choi, H. H. F.; Hamano, K.; King, G. J.; Kowalewski, R.; Lewczuk, M. J.; Lindsay, C.; Nugent, I. M.; Roney, J. M.; Sobie, R. J.; Gershon, T. J.; Harrison, P. F.; Latham, T. E.; Pennington, M. R.; Puccio, E. M. T.; Band, H. R.; Dasu, S.; Flood, K. T.; Pan, Y.; Prepost, R.; Vuosalo, C. O.; Wu, S. L.

2011-03-01

We perform a Dalitz plot analysis of about 100 000 Ds+ decays to K+K-π+ and measure the complex amplitudes of the intermediate resonances which contribute to this decay mode. We also measure the relative branching fractions of Ds+→K+K+π- and Ds+→K+K+K-. For this analysis we use a 384 fb-1 data sample, recorded by the BABAR detector at the PEP-II asymmetric-energy e+e- collider running at center-of-mass energies near 10.58 GeV.

Exclusive B Decays to Charmonium Final States

DOE Office of Scientific and Technical Information (OSTI.GOV)

Barrera, Barbara

We report on exclusive decays of B mesons into final states containing charmonium using data collected with the BABAR detector at the PEP-II storage rings. The charmonium states considered here are J/{psi}, {psi}(2S), and {chi}{sub c1}. Branching fractions for several exclusive final states, a measurement of the decay amplitudes for the B{sup 0} {yields} J/{psi} K* decay, and measurements of the B{sup 0} and B{sup +} masses are presented. All of the results we present here are preliminary.

Multiple Myeloma and Glyphosate Use: A Re-Analysis of US Agricultural Health Study (AHS) Data

PubMed Central

Sorahan, Tom

2015-01-01

A previous publication of 57,311 pesticide applicators enrolled in the US Agricultural Health Study (AHS) produced disparate findings in relation to multiple myeloma risks in the period 1993–2001 and ever-use of glyphosate (32 cases of multiple myeloma in the full dataset of 54,315 applicators without adjustment for other variables: rate ratio (RR) 1.1, 95% confidence interval (CI) 0.5 to 2.4; 22 cases of multiple myeloma in restricted dataset of 40,719 applicators with adjustment for other variables: RR 2.6, 95% CI 0.7 to 9.4). It seemed important to determine which result should be preferred. RRs for exposed and non-exposed subjects were calculated using Poisson regression; subjects with missing data were not excluded from the main analyses. Using the full dataset adjusted for age and gender the analysis produced a RR of 1.12 (95% CI 0.50 to 2.49) for ever-use of glyphosate. Additional adjustment for lifestyle factors and use of ten other pesticides had little effect (RR 1.24, 95% CI 0.52 to 2.94). There were no statistically significant trends for multiple myeloma risks in relation to reported cumulative days (or intensity weighted days) of glyphosate use. The doubling of risk reported previously arose from the use of an unrepresentative restricted dataset and analyses of the full dataset provides no convincing evidence in the AHS for a link between multiple myeloma risk and glyphosate use. PMID:25635915

Multiple myeloma and glyphosate use: a re-analysis of US Agricultural Health Study (AHS) data.

PubMed

Sorahan, Tom

2015-01-28

A previous publication of 57,311 pesticide applicators enrolled in the US Agricultural Health Study (AHS) produced disparate findings in relation to multiple myeloma risks in the period 1993-2001 and ever-use of glyphosate (32 cases of multiple myeloma in the full dataset of 54,315 applicators without adjustment for other variables: rate ratio (RR) 1.1, 95% confidence interval (CI) 0.5 to 2.4; 22 cases of multiple myeloma in restricted dataset of 40,719 applicators with adjustment for other variables: RR 2.6, 95% CI 0.7 to 9.4). It seemed important to determine which result should be preferred. RRs for exposed and non-exposed subjects were calculated using Poisson regression; subjects with missing data were not excluded from the main analyses. Using the full dataset adjusted for age and gender the analysis produced a RR of 1.12 (95% CI 0.50 to 2.49) for ever-use of glyphosate. Additional adjustment for lifestyle factors and use of ten other pesticides had little effect (RR 1.24, 95% CI 0.52 to 2.94). There were no statistically significant trends for multiple myeloma risks in relation to reported cumulative days (or intensity weighted days) of glyphosate use. The doubling of risk reported previously arose from the use of an unrepresentative restricted dataset and analyses of the full dataset provides no convincing evidence in the AHS for a link between multiple myeloma risk and glyphosate use.

Hyperon and hyperon resonance properties from charm baryon decays at BABAR

NASA Astrophysics Data System (ADS)

Ziegler, Veronique

This thesis describes studies of hyperons and hyperon resonances produced in charm baryon decays at BABAR. Using two-body decays of the X0c and W0c , it is shown, for the first time, that the spin of the O - is 3/2. The O- analysis procedures are extended to three-body final states and properties of the xi(1690)0 are extracted from a detailed isobar model analysis of the L+c → ΛK¯0K + Dalitz plot. The mass and width values of the xi(1690) 0 are measured with much greater precision than attained previously. The hypothesis that the spin of the xi(1690) resonance is 1/2 yields an excellent description of the data, while spin values 3/2 and 5/2 are disfavored. The Λa0(980)+ decay mode of the L+c is observed for the first time. Similar techniques are then used to study xi(1530)0 production in L+c decay. The spin of the xi(1530) is established for the first time to be 3/2. The existence of an S-wave amplitude in the xi -pi+ system is shown, and its interference with the xi(1530) 0 amplitude provides the first clear demonstration of the Breit-Wigner phase motion expected for the xi(1530). The xi-pi + mass distribution in the vicinity of the xi(1690)0 exhibits interesting structure which may be interpreted as indicating that the xi(1690) has negative parity.

Study of \\Bpilnu and \\Brholnu decays and determination of \\Vub at \\babar

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wulsin, H.Wells

2011-02-07

The authors report a measurement of the branching fractions for B{sup 0} {yields} {pi}{sup -}{ell}{sup +}{nu} and B{sup 0} {yields} {rho}{sup -}{ell}{sup +}{nu} decays using charged and neutral B decays with isospin constraints. They find {beta}(B{sup 0} {yields} {pi}{sup -}{ell}{sup +}{nu}) = (1.41 {+-} 0.05 {+-} 0.07) x 10{sup -4}, and {beta}(B{sup 0} {yields} {rho}{sup -}{ell}{sup +}{nu}) = (1.75 {+-} 0.15 {+-} 0.27) x 10{sup -4}, where the first error is statistical and the second is systematic. They measure {Delta}{beta}/{Delta}q{sup 2}, with 6 q{sup 2} bins for B{sup 0} {yields} {pi}{sup -}{ell}{sup +}{nu} and 3 q{sup 2} bins for B{supmore » 0} {yields} {rho}{sup -}{ell}{sup +}{nu}, and compare the distributions in data with theoretical predictions for the form factors. They use these branching fractions and form-factor calculations to determine |V{sub ub}|. Based on a combined fit to the FNAL/MILC lattice QCD calculation and data over the full q{sup 2} range, they find |V{sub ub}| = (2.95 {+-} 0.31) x 10{sup -3}.« less

Online Tools for Bioinformatics Analyses in Nutrition Sciences12

PubMed Central

Malkaram, Sridhar A.; Hassan, Yousef I.; Zempleni, Janos

2012-01-01

Recent advances in “omics” research have resulted in the creation of large datasets that were generated by consortiums and centers, small datasets that were generated by individual investigators, and bioinformatics tools for mining these datasets. It is important for nutrition laboratories to take full advantage of the analysis tools to interrogate datasets for information relevant to genomics, epigenomics, transcriptomics, proteomics, and metabolomics. This review provides guidance regarding bioinformatics resources that are currently available in the public domain, with the intent to provide a starting point for investigators who want to take advantage of the opportunities provided by the bioinformatics field. PMID:22983844

Search for lepton-flavor violation in the decay tau- --> l- l+ l-.

PubMed

Aubert, B; Barate, R; Boutigny, D; Couderc, F; Gaillard, J-M; Hicheur, A; Karyotakis, Y; Lees, J P; Tisserand, V; Zghiche, A; Palano, A; Pompili, A; Chen, J C; Qi, N D; Rong, G; Wang, P; Zhu, Y S; Eigen, G; Ofte, I; Stugu, B; Abrams, G S; Borgland, A W; Breon, A B; Brown, D N; Button-Shafer, J; Cahn, R N; Charles, E; Day, C T; Gill, M S; Gritsan, A V; Groysman, Y; Jacobsen, R G; Kadel, R W; Kadyk, J; Kerth, L T; Kolomensky, Yu G; Kukartsev, G; LeClerc, C; Levi, M E; Lynch, G; Mir, L M; Oddone, P J; Orimoto, T J; Pripstein, M; Roe, N A; Ronan, M T; Shelkov, V G; Telnov, A V; Wenzel, W A; Ford, K; Harrison, T J; Hawkes, C M; Morgan, S E; Watson, A T; Watson, N K; Fritsch, M; Goetzen, K; Held, T; Koch, H; Lewandowski, B; Pelizaeus, M; Steinke, M; Boyd, J T; Chevalier, N; Cottingham, W N; Kelly, M P; Latham, T E; Wilson, F F; Abe, K; Cuhadar-Donszelmann, T; Hearty, C; Mattison, T S; McKenna, J A; Thiessen, D; Kyberd, P; Teodorescu, L; Blinov, V E; Bukin, A D; Druzhinin, V P; Golubev, V B; Ivanchenko, V N; Kravchenko, E A; Onuchin, A P; Serednyakov, S I; Skovpen, Yu I; Solodov, E P; Yushkov, A N; Best, D; Bruinsma, M; Chao, M; Eschrich, I; Kirkby, D; Lankford, A J; Mandelkern, M; Mommsen, R K; Roethel, W; Stoker, D P; Buchanan, C; Hartfiel, B L; Gary, J W; Shen, B C; Wang, K; Del Re, D; Hadavand, H K; Hill, E J; MacFarlane, D B; Paar, H P; Rahatlou, Sh; Sharma, V; Berryhill, J W; Campagnari, C; Dahmes, B; Levy, S L; Long, O; Lu, A; Mazur, M A; Richman, J D; Verkerke, W; Beck, T W; Eisner, A M; Heusch, C A; Lockman, W S; Schalk, T; Schmitz, R E; Schumm, B A; Seiden, A; Spradlin, P; Williams, D C; Wilson, M G; Albert, J; Chen, E; Dubois-Felsmann, G P; Dvoretskii, A; Hitlin, D G; Narsky, I; Piatenko, T; Porter, F C; Ryd, A; Samuel, A; Yang, S; Jayatilleke, S; Mancinelli, G; Meadows, B T; Sokoloff, M D; Abe, T; Blanc, F; Bloom, P; Chen, S; Clark, P J; Ford, W T; Nauenberg, U; Olivas, A; Rankin, P; Smith, J G; Van Hoek, W C; Zhang, L; Harton, J L; Hu, T; Soffer, A; Toki, W H; Wilson, R J; Altenburg, D; Brandt, T; Brose, J; Colberg, T; Dickopp, M; Feltresi, E; Hauke, A; Lacker, H M; Maly, E; Müller-Pfefferkorn, R; Nogowski, R; Otto, S; Schubert, J; Schubert, K R; Schwierz, R; Spaan, B; Bernard, D; Bonneaud, G R; Brochard, F; Grenier, P; Thiebaux, Ch; Vasileiadis, G; Verderi, M; Bard, D J; Khan, A; Lavin, D; Muheim, F; Playfer, S; Andreotti, M; Azzolini, V; Bettoni, D; Bozzi, C; Calabrese, R; Cibinetto, G; Luppi, E; Negrini, M; Sarti, A; Treadwell, E; Baldini-Ferroli, R; Calcaterra, A; De Sangro, R; Finocchiaro, G; Patteri, P; Piccolo, M; Zallo, A; Buzzo, A; Capra, R; Contri, R; Crosetti, G; Lo Vetere, M; Macri, M; Monge, M R; Passaggio, S; Patrignani, C; Robutti, E; Santroni, A; Tosi, S; Bailey, S; Brandenburg, G; Morii, M; Won, E; Dubitzky, R S; Langenegger, U; Bhimji, W; Bowerman, D A; Dauncey, P D; Egede, U; Gaillard, J R; Morton, G W; Nash, J A; Taylor, G P; Grenier, G J; Lee, S-J; Mallik, U; Cochran, J; Crawley, H B; Lamsa, J; Meyer, W T; Prell, S; Rosenberg, E I; Yi, J; Davier, M; Grosdidier, G; Höcker, A; Laplace, S; Le Diberder, F; Lepeltier, V; Lutz, A M; Petersen, T C; Plaszczynski, S; Schune, M H; Tantot, L; Wormser, G; Cheng, C H; Lange, D J; Simani, M C; Wright, D M; Bevan, A J; Coleman, J P; Fry, J R; Gabathuler, E; Gamet, R; Kay, M; Parry, R J; Payne, D J; Sloane, R J; Touramanis, C; Back, J J; Harrison, P F; Mohanty, G B; Brown, C L; Cowan, G; Flack, R L; Flaecher, H U; George, S; Green, M G; Kurup, A; Marker, C E; McMahon, T R; Ricciardi, S; Salvatore, F; Vaitsas, G; Winter, M A; Brown, D; Davis, C L; Allison, J; Barlow, N R; Barlow, R J; Hart, P A; Hodgkinson, M C; Lafferty, G D; Lyon, A J; Williams, J C; Farbin, A; Hulsbergen, W D; Jawahery, A; Kovalskyi, D; Lae, C K; Lillard, V; Roberts, D A; Blaylock, G; Dallapiccola, C; Flood, K T; Hertzbach, S S; Kofler, R; Koptchev, V B; Moore, T B; Saremi, S; Staengle, H; Willocq, S; Cowan, R; Sciolla, G; Taylor, F; Yamamoto, R K; Mangeol, D J J; Patel, P M; Robertson, S H; Lazzaro, A; Palombo, F; Bauer, J M; Cremaldi, L; Eschenburg, V; Godang, R; Kroeger, R; Reidy, J; Sanders, D A; Summers, D J; Zhao, H W; Brunet, S; Côté, D; Taras, P; Nicholson, H; Cartaro, C; Cavallo, N; Fabozzi, F; Gatto, C; Lista, L; Monorchio, D; Paolucci, P; Piccolo, D; Sciacca, C; Baak, M; Raven, G; Wilden, L; Jessop, C P; LoSecco, J M; Gabriel, T A; Allmendinger, T; Brau, B; Gan, K K; Honscheid, K; Hufnagel, D; Kagan, H; Kass, R; Pulliam, T; Ter-Antonyan, R; Wong, Q K; Brau, J; Frey, R; Igonkina, O; Potter, C T; Sinev, N B; Strom, D; Torrence, E; Colecchia, F; Dorigo, A; Galeazzi, F; Margoni, M; Morandin, M; Posocco, M; Rotondo, M; Simonetto, F; Stroili, R; Tiozzo, G; Voci, C; Benayoun, M; Briand, H; Chauveau, J; David, P; de la Vaissière, Ch; Del Buono, L; Hamon, O; John, M J J; Leruste, Ph; Ocariz, J; Pivk, M; Roos, L; T'Jampens, S; Therin, G; Manfredi, P F; Re, V; Behera, P K; Gladney, L; Guo, Q H; Panetta, J; Anulli, F; Biasini, M; Peruzzi, I M; Pioppi, M; Angelini, C; Batignani, G; Bettarini, S; Bondioli, M; Bucci, F; Calderini, G; Carpinelli, M; Del Gamba, V; Forti, F; Giorgi, M A; Lusiani, A; Marchiori, G; Martinez-Vidal, F; Morganti, M; Neri, N; Paoloni, E; Rama, M; Rizzo, G; Sandrelli, F; Walsh, J; Haire, M; Judd, D; Paick, K; Wagoner, D E; Danielson, N; Elmer, P; Lu, C; Miftakov, V; Olsen, J; Smith, A J S; Varnes, E W; Bellini, F; Cavoto, G; Faccini, R; Ferrarotto, F; Ferroni, F; Gaspero, M; Li Gioi, L; Mazzoni, M A; Morganti, S; Pierini, M; Piredda, G; Safai Tehrani, F; Voena, C; Christ, S; Wagner, G; Waldi, R; Adye, T; De Groot, N; Franek, B; Geddes, N I; Gopal, G P; Olaiya, E O; Xella, S M; Aleksan, R; Emery, S; Gaidot, A; Ganzhur, S F; Giraud, P-F; Hamel de Monchenault, G; Kozanecki, W; Langer, M; Legendre, M; London, G W; Mayer, B; Schott, G; Vasseur, G; Yèche, Ch; Zito, M; Purohit, M V; Weidemann, A W; Yumiceva, F X; Aston, D; Bartoldus, R; Berger, N; Boyarski, A M; Buchmueller, O L; Convery, M R; Cristinziani, M; De Nardo, G; Dong, D; Dorfan, J; Dujmic, D; Dunwoodie, W; Elsen, E E; Field, R C; Glanzman, T; Gowdy, S J; Hadig, T; Halyo, V; Hryn'ova, T; Innes, W R; Kelsey, M H; Kim, P; Kocian, M L; Leith, D W G S; Libby, J; Luitz, S; Luth, V; Lynch, H L; Marsiske, H; Messner, R; Muller, D R; O'Grady, C P; Ozcan, V E; Perazzo, A; Perl, M; Petrak, S; Ratcliff, B N; Roodman, A; Salnikov, A A; Schindler, R H; Schwiening, J; Simi, G; Snyder, A; Soha, A; Stelzer, J; Su, D; Sullivan, M K; Va'vra, J; Wagner, S R; Weaver, M; Weinstein, A J R; Wisniewski, W J; Wittgen, M; Wright, D H; Young, C C; Burchat, P R; Edwards, A J; Meyer, T I; Petersen, B A; Roat, C; Ahmed, S; Alam, M S; Ernst, J A; Saeed, M A; Saleem, M; Wappler, F R; Bugg, W; Krishnamurthy, M; Spanier, S M; Eckmann, R; Kim, H; Ritchie, J L; Satpathy, A; Schwitters, R F; Izen, J M; Kitayama, I; Lou, X C; Ye, S; Bianchi, F; Bona, M; Gallo, F; Gamba, D; Borean, C; Bosisio, L; Cossutti, F; Della Ricca, G; Dittongo, S; Grancagnolo, S; Lanceri, L; Poropat, P; Vitale, L; Vuagnin, G; Panvini, R S; Banerjee, Sw; Brown, C M; Fortin, D; Jackson, P D; Kowalewski, R; Roney, J M; Band, H R; Dasu, S; Datta, M; Eichenbaum, A M; Hollar, J J; Johnson, J R; Kutter, P E; Li, H; Liu, R; Di Lodovico, F; Mihalyi, A; Mohapatra, A K; Pan, Y; Prepost, R; Sekula, S J; Tan, P; von Wimmersperg-Toeller, J H; Wu, J; Wu, S L; Yu, Z; Neal, H

2004-03-26

A search for the lepton-flavor-violating decay of the tau into three charged leptons has been performed using 91.5 fb(-1) of data collected at an e(+)e(-)center-of-mass energy around 10.58 GeV with the BABAR detector at the SLAC storage ring PEP-II. In all six decay modes considered, the numbers of events found in data are compatible with the background expectations. Upper limits on the branching fractions are set in the range (1-3)x10(-7) at 90% confidence level.

Measurement of the branching fraction and polarization for the decay B--->D*0K*-.

PubMed

Aubert, B; Barate, R; Boutigny, D; Gaillard, J-M; Hicheur, A; Karyotakis, Y; Lees, J P; Robbe, P; Tisserand, V; Zghiche, A; Palano, A; Pompili, A; Chen, J C; Qi, N D; Rong, G; Wang, P; Zhu, Y S; Eigen, G; Ofte, I; Stugu, B; Abrams, G S; Borgland, A W; Breon, A B; Brown, D N; Button-Shafer, J; Cahn, R N; Charles, E; Day, C T; Gill, M S; Gritsan, A V; Groysman, Y; Jacobsen, R G; Kadel, R W; Kadyk, J; Kerth, L T; Kolomensky, Yu G; Kral, J F; Kukartsev, G; LeClerc, C; Levi, M E; Lynch, G; Mir, L M; Oddone, P J; Orimoto, T J; Pripstein, M; Roe, N A; Romosan, A; Ronan, M T; Shelkov, V G; Telnov, A V; Wenzel, W A; Ford, K; Harrison, T J; Hawkes, C M; Knowles, D J; Morgan, S E; Penny, R C; Watson, A T; Watson, N K; Goetzen, K; Held, T; Koch, H; Lewandowski, B; Pelizaeus, M; Peters, K; Schmuecker, H; Steinke, M; Barlow, N R; Boyd, J T; Chevalier, N; Cottingham, W N; Kelly, M P; Latham, T E; Mackay, C; Wilson, F F; Abe, K; Cuhadar-Donszelmann, T; Hearty, C; Mattison, T S; McKenna, J A; Thiessen, D; Kyberd, P; McKemey, A K; Blinov, V E; Bukin, A D; Golubev, V B; Ivanchenko, V N; Kravchenko, E A; Onuchin, A P; Serednyakov, S I; Skovpen, Yu I; Solodov, E P; Yushkov, A N; Best, D; Bruinsma, M; Chao, M; Kirkby, D; Lankford, A J; Mandelkern, M; Mommsen, R K; Roethel, W; Stoker, D P; Buchanan, C; Hartfiel, B L; Shen, B C; del Re, D; Hadavand, H K; Hill, E J; MacFarlane, D B; Paar, H P; Rahatlou, Sh; Sharma, V; Berryhill, J W; Campagnari, C; Dahmes, B; Kuznetsova, N; Levy, S L; Long, O; Lu, A; Mazur, M A; Richman, J D; Verkerke, W; Beck, T W; Beringer, J; Eisner, A M; Heusch, C A; Lockman, W S; Schalk, T; Schmitz, R E; Schumm, B A; Seiden, A; Turri, M; Walkowiak, W; Williams, D C; Wilson, M G; Albert, J; Chen, E; Dubois-Felsmann, G P; Dvoretskii, A; Hitlin, D G; Narsky, I; Porter, F C; Ryd, A; Samuel, A; Yang, S; Jayatilleke, S; Mancinelli, G; Meadows, B T; Sokoloff, M D; Abe, T; Blanc, F; Bloom, P; Chen, S; Clark, P J; Ford, W T; Nauenberg, U; Olivas, A; Rankin, P; Roy, J; Smith, J G; van Hoek, W C; Zhang, L; Harton, J L; Hu, T; Soffer, A; Toki, W H; Wilson, R J; Zhang, J; Altenburg, D; Brandt, T; Brose, J; Colberg, T; Dickopp, M; Dubitzky, R S; Hauke, A; Lacker, H M; Maly, E; Müller-Pfefferkorn, R; Nogowski, R; Otto, S; Schubert, J; Schubert, K R; Schwierz, R; Spaan, B; Wilden, L; Bernard, D; Bonneaud, G R; Brochard, F; Cohen-Tanugi, J; Grenier, P; Thiebaux, Ch; Vasileiadis, G; Verderi, M; Khan, A; Lavin, D; Muheim, F; Playfer, S; Swain, J E; Andreotti, M; Azzolini, V; Bettoni, D; Bozzi, C; Calabrese, R; Cibinetto, G; Luppi, E; Negrini, M; Piemontese, L; Sarti, A; Treadwell, E; Anulli, F; Baldini-Ferroli, R; Biasini, M; Calcaterra, A; De Sangro, R; Falciai, D; Finocchiaro, G; Patteri, P; Peruzzi, I M; Piccolo, M; Pioppi, M; Zallo, A; Buzzo, A; Capra, R; Contri, R; Crosetti, G; Lo Vetere, M; Macri, M; Monge, M R; Passaggio, S; Patrignani, C; Robutti, E; Santroni, A; Tosi, S; Bailey, S; Morii, M; Won, E; Bhimji, W; Bowerman, D A; Dauncey, P D; Egede, U; Eschrich, I; Gaillard, J R; Morton, G W; Nash, J A; Sanders, P; Taylor, G P; Grenier, G J; Lee, S-J; Mallik, U; Cochran, J; Crawley, H B; Lamsa, J; Meyer, W T; Prell, S; Rosenberg, E I; Yi, J; Davier, M; Grosdidier, G; Höcker, A; Laplace, S; Le Diberder, F; Lepeltier, V; Lutz, A M; Petersen, T C; Plaszczynski, S; Schune, M H; Tantot, L; Wormser, G; Brigljević, V; Cheng, C H; Lange, D J; Wright, D M; Bevan, A J; Coleman, J P; Fry, J R; Gabathuler, E; Gamet, R; Kay, M; Parry, R J; Payne, D J; Sloane, R J; Touramanis, C; Back, J J; Harrison, P F; Shorthouse, H W; Strother, P; Vidal, P B; Brown, C L; Cowan, G; Flack, R L; Flaecher, H U; George, S; Green, M G; Kurup, A; Marker, C E; McMahon, T R; Ricciardi, S; Salvatore, F; Vaitsas, G; Winter, M A; Brown, D; Davis, C L; Allison, J; Barlow, R J; Forti, A C; Hart, P A; Hodgkinson, M C; Jackson, F; Lafferty, G D; Lyon, A J; Weatherall, J H; Williams, J C; Farbin, A; Jawahery, A; Kovalskyi, D; Lae, C K; Lillard, V; Roberts, D A; Blaylock, G; Dallapiccola, C; Flood, K T; Hertzbach, S S; Kofler, R; Koptchev, V B; Moore, T B; Saremi, S; Staengle, H; Willocq, S; Cowan, R; Sciolla, G; Taylor, F; Yamamoto, R K; Mangeol, D J J; Patel, P M; Lazzaro, A; Palombo, F; Bauer, J M; Cremaldi, L; Eschenburg, V; Godang, R; Kroeger, R; Reidy, J; Sanders, D A; Summers, D J; Zhao, H W; Brunet, S; Cote-Ahern, D; Hast, C; Taras, P; Nicholson, H; Cartaro, C; Cavallo, N; De Nardo, G; Fabozzi, F; Gatto, C; Lista, L; Paolucci, P; Piccolo, D; Sciacca, C; Baak, M A; Raven, G; LoSecco, J M; Gabriel, T A; Brau, B; Gan, K K; Honscheid, K; Hufnagel, D; Kagan, H; Kass, R; Pulliam, T; Wong, Q K; Brau, J; Frey, R; Potter, C T; Sinev, N B; Strom, D; Torrence, E; Colecchia, F; Dorigo, A; Galeazzi, F; Margoni, M; Morandin, M; Posocco, M; Rotondo, M; Simonetto, F; Stroili, R; Tiozzo, G; Voci, C; Benayoun, M; Briand, H; Chauveau, J; David, P; de la Vaissière, Ch; Del Buono, L; Hamon, O; John, M J J; Leruste, Ph; Ocariz, J; Pivk, M; Roos, L; Stark, J; T'Jampens, S; Therin, G; Manfredi, P F; Re, V; Behera, P K; Gladney, L; Guo, Q H; Panetta, J; Angelini, C; Batignani, G; Bettarini, S; Bondioli, M; Bucci, F; Calderini, G; Carpinelli, M; Del Gamba, V; Forti, F; Giorgi, M A; Lusiani, A; Marchiori, G; Martinez-Vidal, F; Morganti, M; Neri, N; Paoloni, E; Rama, M; Rizzo, G; Sandrelli, F; Walsh, J; Haire, M; Judd, D; Paick, K; Wagoner, D E; Danielson, N; Elmer, P; Lu, C; Miftakov, V; Olsen, J; Smith, A J S; Tanaka, H A; Varnes, E W; Bellini, F; Cavoto, G; Faccini, R; Ferrarotto, F; Ferroni, F; Gaspero, M; Mazzoni, M A; Morganti, S; Pierini, M; Piredda, G; Safai Tehrani, F; Voena, C; Christ, S; Wagner, G; Waldi, R; Adye, T; De Groot, N; Franek, B; Geddes, N I; Gopal, G P; Olaiya, E O; Xella, S M; Aleksan, R; Emery, S; Gaidot, A; Ganzhur, S F; Giraud, P-F; Hamel de Monchenault, G; Kozanecki, W; Langer, M; Legendre, M; London, G W; Mayer, B; Schott, G; Vasseur, G; Yeche, Ch; Zito, M; Purohit, M V; Weidemann, A W; Yumiceva, F X; Aston, D; Bartoldus, R; Berger, N; Boyarski, A M; Buchmueller, O L; Convery, M R; Coupal, D P; Dong, D; Dorfan, J; Dujmic, D; Dunwoodie, W; Field, R C; Glanzman, T; Gowdy, S J; Grauges-Pous, E; Hadig, T; Halyo, V; Hryn'ova, T; Innes, W R; Jessop, C P; Kelsey, M H; Kim, P; Kocian, M L; Langenegger, U; Leith, D W G S; Luitz, S; Luth, V; Lynch, H L; Marsiske, H; Messner, R; Muller, D R; O'Grady, C P; Ozcan, V E; Perazzo, A; Perl, M; Petrak, S; Ratcliff, B N; Robertson, S H; Roodman, A; Salnikov, A A; Schindler, R H; Schwiening, J; Simi, G; Snyder, A; Soha, A; Stelzer, J; Su, D; Sullivan, M K; Va'vra, J; Wagner, S R; Weaver, M; Weinstein, A J R; Wisniewski, W J; Wright, D H; Young, C C; Burchat, P R; Edwards, A J; Meyer, T I; Petersen, B A; Roat, C; Ahmed, S; Alam, M S; Ernst, J A; Saleem, M; Wappler, F R; Bugg, W; Krishnamurthy, M; Spanier, S M; Eckmann, R; Kim, H; Ritchie, J L; Schwitters, R F; Izen, J M; Kitayama, I; Lou, X C; Ye, S; Bianchi, F; Bona, M; Gallo, F; Gamba, D; Borean, C; Bosisio, L; Della Ricca, G; Dittongo, S; Grancagnolo, S; Lanceri, L; Poropat, P; Vitale, L; Vuagnin, G; Panvini, R S; Banerjee, Sw; Brown, C M; Fortin, D; Jackson, P D; Kowalewski, R; Roney, J M; Band, H R; Dasu, S; Datta, M; Eichenbaum, A M; Johnson, J R; Kutter, P E; Li, H; Liu, R; Di Lodovico, F; Mihalyi, A; Mohapatra, A K; Pan, Y; Prepost, R; Sekula, S J; von Wimmersperg-Toeller, J H; Wu, J; Wu, S L; Yu, Z; Neal, H

2004-04-09

We present a study of the decay B--->D(*0)K(*-) based on a sample of 86 x 10(6) Upsilon(4S)-->BBmacr; decays collected with the BABAR detector at the PEP-II asymmetric-energy B Factory at SLAC. We measure the branching fraction B(B--->D(*0)K(*-))=(8.3+/-1.1(stat)+/-1.0(syst)) x 10(-4), and the fraction of longitudinal polarization in this decay to be Gamma(L)/Gamma=0.86+/-0.06(stat)+/-0.03(syst).

Measurement of the B(0) lifetime with partially reconstructed B(0)-->D(-)l(+)nu(l) decays.

PubMed

Aubert, B; Boutigny, D; Gaillard, J-M; Hicheur, A; Karyotakis, Y; Lees, J P; Robbe, P; Tisserand, V; Zghiche, A; Palano, A; Pompili, A; Chen, G P; Chen, J C; Qi, N D; Rong, G; Wang, P; Zhu, Y S; Eigen, G; Stugu, B; Abrams, G S; Borgland, A W; Breon, A B; Brown, D N; Button-Shafer, J; Cahn, R N; Clark, A R; Gill, M S; Gritsan, A V; Groysman, Y; Jacobsen, R G; Kadel, R W; Kadyk, J; Kerth, L T; Kolomensky, Yu G; Kral, J F; LeClerc, C; Levi, M E; Lynch, G; Oddone, P J; Pripstein, M; Roe, N A; Romosan, A; Ronan, M T; Shelkov, V G; Telnov, A V; Wenzel, W A; Harrison, T J; Hawkes, C M; Knowles, D J; O'Neale, S W; Penny, R C; Watson, A T; Watson, N K; Deppermann, T; Goetzen, K; Koch, H; Kunze, M; Lewandowski, B; Peters, K; Schmuecker, H; Steinke, M; Barlow, N R; Bhimji, W; Chevalier, N; Clark, P J; Cottingham, W N; Foster, B; Mackay, C; Wilson, F F; Abe, K; Hearty, C; Mattison, T S; McKenna, J A; Thiessen, D; Jolly, S; McKemey, A K; Blinov, V E; Bukin, A D; Bukin, D A; Buzykaev, A R; Golubev, V B; Ivanchenko, V N; Korol, A A; Kravchenko, E A; Onuchin, A P; Serednyakov, S I; Skovpen, Yu I; Telnov, V I; Yushkov, A N; Best, D; Chao, M; Kirkby, D; Lankford, A J; Mandelkern, M; McMahon, S; Stoker, D P; Arisaka, K; Buchanan, C; Chun, S; MacFarlane, D B; Prell, S; Rahatlou, Sh; Raven, G; Sharma, V; Campagnari, C; Dahmes, B; Hart, P A; Kuznetsova, N; Levy, S L; Long, O; Lu, A; Mazur, M A; Richman, J D; Verkerke, W; Beringer, J; Eisner, A M; Grothe, M; Heusch, C A; Lockman, W S; Pulliam, T; Schalk, T; Schmitz, R E; Schumm, B A; Seiden, A; Turri, M; Walkowiak, W; Williams, D C; Wilson, M G; Chen, E; Dubois-Felsmann, G P; Dvoretskii, A; Hitlin, D G; Metzler, S; Oyang, J; Porter, F C; Ryd, A; Samuel, A; Weaver, M; Yang, S; Zhu, R Y; Devmal, S; Geld, T L; Jayatilleke, S; Mancinelli, G; Meadows, B T; Sokoloff, M D; Barillari, T; Bloom, P; Dima, M O; Ford, W T; Nauenberg, U; Olivas, A; Rankin, P; Roy, J; Smith, J G; van Hoek, W C; Blouw, J; Harton, J L; Krishnamurthy, M; Soffer, A; Toki, W H; Wilson, R J; Zhang, J; Brandt, T; Brose, J; Colberg, T; Dickopp, M; Dubitzky, R S; Hauke, A; Maly, E; Müller-Pfefferkorn, R; Otto, S; Schubert, K R; Schwierz, R; Spaan, B; Wilden, L; Bernard, D; Bonneaud, G R; Brochard, F; Cohen-Tanugi, J; Ferrag, S; T'Jampens, S; Thiebaux, Ch; Vasileiadis, G; Verderi, M; Anjomshoaa, A; Bernet, R; Khan, A; Lavin, D; Muheim, F; Playfer, S; Swain, J E; Tinslay, J; Falbo, M; Borean, C; Bozzi, C; Dittongo, S; Piemontese, L; Treadwell, E; Anulli, F; Baldini-Ferroli, R; Calcaterra, A; de Sangro, R; Falciai, D; Finocchiaro, G; Patteri, P; Peruzzi, I M; Piccolo, M; Xie, Y; Zallo, A; Bagnasco, S; Buzzo, A; Contri, R; Crosetti, G; Lo Vetere, M; Macri, M; Monge, M R; Passaggio, S; Pastore, F C; Patrignani, C; Pia, M G; Robutti, E; Santroni, A; Tosi, S; Morii, M; Bartoldus, R; Hamilton, R; Mallik, U; Cochran, J; Crawley, H B; Fischer, P-A; Lamsa, J; Meyer, W T; Rosenberg, E I; Grosdidier, G; Hast, C; Höcker, A; Lacker, H M; Laplace, S; Lepeltier, V; Lutz, A M; Plaszczynski, S; Schune, M H; Trincaz-Duvoid, S; Wormser, G; Bionta, R M; Brigljević, V; Lange, D J; Mugge, M; van Bibber, K; Wright, D M; Bevan, A J; Fry, J R; Gabathuler, E; Gamet, R; George, M; Kay, M; Payne, D J; Sloane, R J; Touramanis, C; Aspinwall, M L; Bowerman, D A; Dauncey, P D; Egede, U; Eschrich, I; Gunawardane, N J W; Nash, J A; Sanders, P; Smith, D; Azzopardi, D E; Back, J J; Bellodi, G; Dixon, P; Harrison, P F; Potter, R J L; Shorthouse, H W; Strother, P; Vidal, P B; Cowan, G; George, S; Green, M G; Kurup, A; Marker, C E; McGrath, P; McMahon, T R; Ricciardi, S; Salvatore, F; Vaitsas, G; Brown, D; Davis, C L; Allison, J; Barlow, R J; Boyd, J T; Forti, A C; Fullwood, J; Jackson, F; Lafferty, G D; Savvas, N; Weatherall, J H; Williams, J C; Farbin, A; Jawahery, A; Lillard, V; Olsen, J; Roberts, D A; Schieck, J R; Blaylock, G; Dallapiccola, C; Flood, K T; Hertzbach, S S; Kofler, R; Koptchev, V B; Moore, T B; Staengle, H; Willocq, S; Brau, B; Cowan, R; Sciolla, G; Taylor, F; Yamamoto, R K; Milek, M; Patel, P M; Palombo, F; Bauer, J M; Cremaldi, L; Eschenburg, V; Kroeger, R; Reidy, J; Sanders, D A; Summers, D J; Nief, J Y; Taras, P; Nicholson, H; Cartaro, C; Cavallo, N; De Nardo, G; Fabozzi, F; Gatto, C; Lista, L; Paolucci, P; Piccolo, D; Sciacca, C; LoSecco, J M; Alsmiller, J R G; Gabriel, T A; Brau, J; Frey, R; Grauges, E; Iwasaki, M; Sinev, N B; Strom, D; Colecchia, F; Dal Corso, F; Dorigo, A; Galeazzi, F; Margoni, M; Michelon, G; Morandin, M; Posocco, M; Rotondo, M; Simonetto, F; Stroili, R; Torassa, E; Voci, C; Benayoun, M; Briand, H; Chauveau, J; David, P; de la Vaissière, Ch; Del Buono, L; Hamon, O; Le Diberder, F; Leruste, Ph; Ocariz, J; Roos, L; Stark, J; Manfredi, P F; Re, V; Speziali, V; Frank, E D; Gladney, L; Guo, Q H; Panetta, J; Angelini, C; Batignani, G; Bettarini, S; Bondioli, M; Bucci, F; Campagna, E; Carpinelli, M; Forti, F; Giorgi, M A; Lusiani, A; Marchiori, G; Martinez-Vidal, F; Morganti, M; Neri, N; Paoloni, E; Rama, M; Rizzo, G; Sandrelli, F; Simi, G; Triggiani, G; Walsh, J; Haire, M; Judd, D; Paick, K; Turnbull, L; Wagoner, D E; Albert, J; Elmer, P; Lu, C; Miftakov, V; Schaffner, S F; Smith, A J S; Tumanov, A; Varnes, E W; Cavoto, G; Del Re, D; Faccini, R; Ferrarotto, F; Ferroni, F; Lamanna, E; Mazzoni, M A; Morganti, S; Piredda, G; Safai Tehrani, F; Serra, M; Voena, C; Christ, S; Waldi, R; Adye, T; De Groot, N; Franek, B; Geddes, N I; Gopal, G P; Xella, S M; Aleksan, R; Emery, S; Gaidot, A; Ganzhur, S F; Giraud, P-F; Hamel de Monchenault, G; Kozanecki, W; Langer, M; London, G W; Mayer, B; Serfass, B; Vasseur, G; Yèche, Ch; Zito, M; Purohit, M V; Singh, H; Weidemann, A W; Yumiceva, F X; Adam, I; Aston, D; Berger, N; Boyarski, A M; Calderini, G; Convery, M R; Coupal, D P; Dong, D; Dorfan, J; Dunwoodie, W; Field, R C; Glanzman, T; Gowdy, S J; Haas, T; Halyo, V; Himel, T; Hryn'ova, T; Huffer, M E; Innes, W R; Jessop, C P; Kelsey, M H; Kim, P; Kocian, M L; Langenegger, U; Leith, D W G S; Luitz, S; Luth, V; Lynch, H L; Marsiske, H; Menke, S; Messner, R; Muller, D R; O'Grady, C P; Ozcan, V E; Perazzo, A; Perl, M; Petrak, S; Quinn, H; Ratcliff, B N; Robertson, S H; Roodman, A; Salnikov, A A; Schietinger, T; Schindler, R H; Schwiening, J; Snyder, A; Soha, A; Spanier, S M; Stelzer, J; Su, D; Sullivan, M K; Tanaka, H A; Va'vra, J; Wagner, S R; Weinstein, A J R; Wisniewski, W J; Wright, D H; Young, C C; Burchat, P R; Cheng, C H; Meyer, T I; Roat, C; Henderson, R; Bugg, W; Cohn, H; Izen, J M; Kitayama, I; Lou, X C; Bianchi, F; Bona, M; Gamba, D; Bosisio, L; Della Ricca, G; Lanceri, L; Poropat, P; Vuagnin, G; Panvini, R S; Brown, C M; Jackson, P D; Kowalewski, R; Roney, J M; Band, H R; Charles, E; Dasu, S; Eichenbaum, A M; Hu, H; Johnson, J R; Liu, R; Di Lodovico, F; Pan, Y; Prepost, R; Scott, I J; Sekula, S J; von Wimmersperg-Toeller, J H; Wu, S L; Yu, Z; Kordich, T M B; Neal, H

2002-07-01

The B(0) lifetime was measured with a sample of 23 million BB pairs collected by the BABAR detector at the PEP-II e(+)e(-) storage ring during 1999 and 2000. Events from the semileptonic decay B(0)-->D(*-)l(+)nu(l) have been selected with a partial reconstruction method in which only the charged lepton and the slow pi from the D*--->D(0)pi(-) decay are reconstructed. The result is tau(B(0)) = 1.529+/-0.012(stat)+/-0.029(syst) ps.

[Current problems in the data acquisition of digitized virtual human and the countermeasures].

PubMed

Zhong, Shi-zhen; Yuan, Lin

2003-06-01

As a relatively new field of medical science research that has attracted the attention from worldwide researchers, study of digitized virtual human still awaits long-term dedicated effort for its full development. In the full array of research projects of the integrated Virtual Chinese Human project, virtual visible human, virtual physical human, virtual physiome, and intellectualized virtual human must be included as the four essential constitutional opponents. The primary importance should be given to solving the problems concerning the data acquisition for the dataset of this immense project. Currently 9 virtual human datasets have been established worldwide, which are subjected to critical analyses in the paper with special attention given to the problems in the data storage and the techniques employed, for instance, in these datasets. On the basis of current research status of Virtual Chinese Human project, the authors propose some countermeasures for solving the problems in the data acquisition for the dataset, which include (1) giving the priority to the quality control instead of merely racing for quantity and speed, and (2) improving the setting up of the markers specific for the tissues and organs to meet the requirement from information technology, (3) with also attention to the development potential of the dataset which should have explicit pertinence to specific actual applications.

A Comprehensive, Automatically Updated Fungal ITS Sequence Dataset for Reference-Based Chimera Control in Environmental Sequencing Efforts.

PubMed

Nilsson, R Henrik; Tedersoo, Leho; Ryberg, Martin; Kristiansson, Erik; Hartmann, Martin; Unterseher, Martin; Porter, Teresita M; Bengtsson-Palme, Johan; Walker, Donald M; de Sousa, Filipe; Gamper, Hannes Andres; Larsson, Ellen; Larsson, Karl-Henrik; Kõljalg, Urmas; Edgar, Robert C; Abarenkov, Kessy

2015-01-01

The nuclear ribosomal internal transcribed spacer (ITS) region is the most commonly chosen genetic marker for the molecular identification of fungi in environmental sequencing and molecular ecology studies. Several analytical issues complicate such efforts, one of which is the formation of chimeric-artificially joined-DNA sequences during PCR amplification or sequence assembly. Several software tools are currently available for chimera detection, but rely to various degrees on the presence of a chimera-free reference dataset for optimal performance. However, no such dataset is available for use with the fungal ITS region. This study introduces a comprehensive, automatically updated reference dataset for fungal ITS sequences based on the UNITE database for the molecular identification of fungi. This dataset supports chimera detection throughout the fungal kingdom and for full-length ITS sequences as well as partial (ITS1 or ITS2 only) datasets. The performance of the dataset on a large set of artificial chimeras was above 99.5%, and we subsequently used the dataset to remove nearly 1,000 compromised fungal ITS sequences from public circulation. The dataset is available at http://unite.ut.ee/repository.php and is subject to web-based third-party curation.

A Comprehensive, Automatically Updated Fungal ITS Sequence Dataset for Reference-Based Chimera Control in Environmental Sequencing Efforts

PubMed Central

Nilsson, R. Henrik; Tedersoo, Leho; Ryberg, Martin; Kristiansson, Erik; Hartmann, Martin; Unterseher, Martin; Porter, Teresita M.; Bengtsson-Palme, Johan; Walker, Donald M.; de Sousa, Filipe; Gamper, Hannes Andres; Larsson, Ellen; Larsson, Karl-Henrik; Kõljalg, Urmas; Edgar, Robert C.; Abarenkov, Kessy

2015-01-01

The nuclear ribosomal internal transcribed spacer (ITS) region is the most commonly chosen genetic marker for the molecular identification of fungi in environmental sequencing and molecular ecology studies. Several analytical issues complicate such efforts, one of which is the formation of chimeric—artificially joined—DNA sequences during PCR amplification or sequence assembly. Several software tools are currently available for chimera detection, but rely to various degrees on the presence of a chimera-free reference dataset for optimal performance. However, no such dataset is available for use with the fungal ITS region. This study introduces a comprehensive, automatically updated reference dataset for fungal ITS sequences based on the UNITE database for the molecular identification of fungi. This dataset supports chimera detection throughout the fungal kingdom and for full-length ITS sequences as well as partial (ITS1 or ITS2 only) datasets. The performance of the dataset on a large set of artificial chimeras was above 99.5%, and we subsequently used the dataset to remove nearly 1,000 compromised fungal ITS sequences from public circulation. The dataset is available at http://unite.ut.ee/repository.php and is subject to web-based third-party curation. PMID:25786896

Scalable Machine Learning for Massive Astronomical Datasets

NASA Astrophysics Data System (ADS)

Ball, Nicholas M.; Gray, A.

2014-04-01

We present the ability to perform data mining and machine learning operations on a catalog of half a billion astronomical objects. This is the result of the combination of robust, highly accurate machine learning algorithms with linear scalability that renders the applications of these algorithms to massive astronomical data tractable. We demonstrate the core algorithms kernel density estimation, K-means clustering, linear regression, nearest neighbors, random forest and gradient-boosted decision tree, singular value decomposition, support vector machine, and two-point correlation function. Each of these is relevant for astronomical applications such as finding novel astrophysical objects, characterizing artifacts in data, object classification (including for rare objects), object distances, finding the important features describing objects, density estimation of distributions, probabilistic quantities, and exploring the unknown structure of new data. The software, Skytree Server, runs on any UNIX-based machine, a virtual machine, or cloud-based and distributed systems including Hadoop. We have integrated it on the cloud computing system of the Canadian Astronomical Data Centre, the Canadian Advanced Network for Astronomical Research (CANFAR), creating the world's first cloud computing data mining system for astronomy. We demonstrate results showing the scaling of each of our major algorithms on large astronomical datasets, including the full 470,992,970 objects of the 2 Micron All-Sky Survey (2MASS) Point Source Catalog. We demonstrate the ability to find outliers in the full 2MASS dataset utilizing multiple methods, e.g., nearest neighbors. This is likely of particular interest to the radio astronomy community given, for example, that survey projects contain groups dedicated to this topic. 2MASS is used as a proof-of-concept dataset due to its convenience and availability. These results are of interest to any astronomical project with large and/or complex datasets that wishes to extract the full scientific value from its data.

Scalable Machine Learning for Massive Astronomical Datasets

NASA Astrophysics Data System (ADS)

Ball, Nicholas M.; Astronomy Data Centre, Canadian

2014-01-01

We present the ability to perform data mining and machine learning operations on a catalog of half a billion astronomical objects. This is the result of the combination of robust, highly accurate machine learning algorithms with linear scalability that renders the applications of these algorithms to massive astronomical data tractable. We demonstrate the core algorithms kernel density estimation, K-means clustering, linear regression, nearest neighbors, random forest and gradient-boosted decision tree, singular value decomposition, support vector machine, and two-point correlation function. Each of these is relevant for astronomical applications such as finding novel astrophysical objects, characterizing artifacts in data, object classification (including for rare objects), object distances, finding the important features describing objects, density estimation of distributions, probabilistic quantities, and exploring the unknown structure of new data. The software, Skytree Server, runs on any UNIX-based machine, a virtual machine, or cloud-based and distributed systems including Hadoop. We have integrated it on the cloud computing system of the Canadian Astronomical Data Centre, the Canadian Advanced Network for Astronomical Research (CANFAR), creating the world's first cloud computing data mining system for astronomy. We demonstrate results showing the scaling of each of our major algorithms on large astronomical datasets, including the full 470,992,970 objects of the 2 Micron All-Sky Survey (2MASS) Point Source Catalog. We demonstrate the ability to find outliers in the full 2MASS dataset utilizing multiple methods, e.g., nearest neighbors, and the local outlier factor. 2MASS is used as a proof-of-concept dataset due to its convenience and availability. These results are of interest to any astronomical project with large and/or complex datasets that wishes to extract the full scientific value from its data.

TriageTools: tools for partitioning and prioritizing analysis of high-throughput sequencing data.

PubMed

Fimereli, Danai; Detours, Vincent; Konopka, Tomasz

2013-04-01

High-throughput sequencing is becoming a popular research tool but carries with it considerable costs in terms of computation time, data storage and bandwidth. Meanwhile, some research applications focusing on individual genes or pathways do not necessitate processing of a full sequencing dataset. Thus, it is desirable to partition a large dataset into smaller, manageable, but relevant pieces. We present a toolkit for partitioning raw sequencing data that includes a method for extracting reads that are likely to map onto pre-defined regions of interest. We show the method can be used to extract information about genes of interest from DNA or RNA sequencing samples in a fraction of the time and disk space required to process and store a full dataset. We report speedup factors between 2.6 and 96, depending on settings and samples used. The software is available at http://www.sourceforge.net/projects/triagetools/.

Measurement of the e + e - → π + π - π 0 π 0 cross section using initial-state radiation at BABAR

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lees, J. P.; Poireau, V.; Tisserand, V.

Here, the process e +e –→π +π –2π 0γ is investigated by means of the initial-state radiation technique, where a photon is emitted from the incoming electron or positron. Using 454.3 fb –1 of data collected around a center-of-mass energy of √s=10.58 GeV by the BABAR experiment at SLAC, approximately 150000 signal events are obtained. The corresponding nonradiative cross section is measured with a relative uncertainty of 3.6% in the energy region around 1.5 GeV, surpassing all existing measurements in precision. Using this new result, the channel’s contribution to the leading order hadronic vacuum polarization contribution to the anomalous magneticmore » moment of the muon is calculated as (gπ +π–2π0 μ–2)/2=(17.9 ± 0.1 stat ± 0.6 syst)×10–10 in the energy range 0.85 GeV < E CM < 1.8 GeV. In the same energy range, the impact on the running of the fine-structure constant at the Z 0-pole is determined as Δαπ +π–2π0(M 2 Z)=(4.44 ± 0.02 stat ± 0.14 syst) × 10 –4. Furthermore, intermediate resonances are studied and especially the cross section of the process e +e –→ωπ 0→π +π –2π 0 is measured.« less

Measurement of the e + e - → π + π - π 0 π 0 cross section using initial-state radiation at BABAR

DOE PAGES

Lees, J. P.; Poireau, V.; Tisserand, V.; ...

2017-11-29

Here, the process e +e –→π +π –2π 0γ is investigated by means of the initial-state radiation technique, where a photon is emitted from the incoming electron or positron. Using 454.3 fb –1 of data collected around a center-of-mass energy of √s=10.58 GeV by the BABAR experiment at SLAC, approximately 150000 signal events are obtained. The corresponding nonradiative cross section is measured with a relative uncertainty of 3.6% in the energy region around 1.5 GeV, surpassing all existing measurements in precision. Using this new result, the channel’s contribution to the leading order hadronic vacuum polarization contribution to the anomalous magneticmore » moment of the muon is calculated as (gπ +π–2π0 μ–2)/2=(17.9 ± 0.1 stat ± 0.6 syst)×10–10 in the energy range 0.85 GeV < E CM < 1.8 GeV. In the same energy range, the impact on the running of the fine-structure constant at the Z 0-pole is determined as Δαπ +π–2π0(M 2 Z)=(4.44 ± 0.02 stat ± 0.14 syst) × 10 –4. Furthermore, intermediate resonances are studied and especially the cross section of the process e +e –→ωπ 0→π +π –2π 0 is measured.« less

Comparing species tree estimation with large anchored phylogenomic and small Sanger-sequenced molecular datasets: an empirical study on Malagasy pseudoxyrhophiine snakes.

PubMed

Ruane, Sara; Raxworthy, Christopher J; Lemmon, Alan R; Lemmon, Emily Moriarty; Burbrink, Frank T

2015-10-12

Using molecular data generated by high throughput next generation sequencing (NGS) platforms to infer phylogeny is becoming common as costs go down and the ability to capture loci from across the genome goes up. While there is a general consensus that greater numbers of independent loci should result in more robust phylogenetic estimates, few studies have compared phylogenies resulting from smaller datasets for commonly used genetic markers with the large datasets captured using NGS. Here, we determine how a 5-locus Sanger dataset compares with a 377-locus anchored genomics dataset for understanding the evolutionary history of the pseudoxyrhophiine snake radiation centered in Madagascar. The Pseudoxyrhophiinae comprise ~86 % of Madagascar's serpent diversity, yet they are poorly known with respect to ecology, behavior, and systematics. Using the 377-locus NGS dataset and the summary statistics species-tree methods STAR and MP-EST, we estimated a well-supported species tree that provides new insights concerning intergeneric relationships for the pseudoxyrhophiines. We also compared how these and other methods performed with respect to estimating tree topology using datasets with varying numbers of loci. Using Sanger sequencing and an anchored phylogenomics approach, we sequenced datasets comprised of 5 and 377 loci, respectively, for 23 pseudoxyrhophiine taxa. For each dataset, we estimated phylogenies using both gene-tree (concatenation) and species-tree (STAR, MP-EST) approaches. We determined the similarity of resulting tree topologies from the different datasets using Robinson-Foulds distances. In addition, we examined how subsets of these data performed compared to the complete Sanger and anchored datasets for phylogenetic accuracy using the same tree inference methodologies, as well as the program *BEAST to determine if a full coalescent model for species tree estimation could generate robust results with fewer loci compared to the summary statistics species tree approaches. We also examined the individual gene trees in comparison to the 377-locus species tree using the program MetaTree. Using the full anchored dataset under a variety of methods gave us the same, well-supported phylogeny for pseudoxyrhophiines. The African pseudoxyrhophiine Duberria is the sister taxon to the Malagasy pseudoxyrhophiines genera, providing evidence for a monophyletic radiation in Madagascar. In addition, within Madagascar, the two major clades inferred correspond largely to the aglyphous and opisthoglyphous genera, suggesting that feeding specializations associated with tooth venom delivery may have played a major role in the early diversification of this radiation. The comparison of tree topologies from the concatenated and species-tree methods using different datasets indicated the 5-locus dataset cannot beused to infer a correct phylogeny for the pseudoxyrhophiines under any method tested here and that summary statistics methods require 50 or more loci to consistently recover the species-tree inferred using the complete anchored dataset. However, as few as 15 loci may infer the correct topology when using the full coalescent species tree method *BEAST. MetaTree analyses of each gene tree from the Sanger and anchored datasets found that none of the individual gene trees matched the 377-locus species tree, and that no gene trees were identical with respect to topology. Our results suggest that ≥50 loci may be necessary to confidently infer phylogenies when using summaryspecies-tree methods, but that the coalescent-based method *BEAST consistently recovers the same topology using only 15 loci. These results reinforce that datasets with small numbers of markers may result in misleading topologies, and further, that the method of inference used to generate a phylogeny also has a major influence on the number of loci necessary to infer robust species trees.

Study of CP Symmetry Violation in the Charmonium-K*(892) Channel By a Complete Time Dependent Angular Analysis (BaBar Experiment) (in French)

DOE Office of Scientific and Technical Information (OSTI.GOV)

T'Jampens, Stephane; /Orsay

2006-09-18

This thesis presents the full-angular time-dependent analysis of the vector-vector channel B{sub d}{sup 0} {yields} J/{psi}(K{sub S}{sup 0}{pi}{sup 0})*{sup 0}. After a review of the CP violation in the B meson system, the phenomenology of the charmonium-K*(892) channels is exposed. The method for the measurement of the transversity amplitudes of the B {yields} J/{psi}K*(892), based on a pseudo-likelihood method, is then exposed. The results from a 81.9 fb{sup -1} of collected data by the BABAR detector at the {Upsilon}(4S) resonance peak are |A{sub 0}|{sup 2} = 0.565 {+-} 0.011 {+-} 0.004, |A{sub {parallel}}|{sup 2} = 0.206 {+-} 0.016 {+-} 0.007,more » |A{sub {perpendicular}}|{sup 2} = 0.228 {+-} 0.016 {+-} 0.007, {delta}{sub {parallel}} = -2.766 {+-} 0.105 {+-} 0.040 and {delta}{sub {perpendicular}} = 2.935 {+-} 0.067 {+-} 0.040. Note that ({delta}{sub {parallel}}, {delta}{sub {perpendicular}}) {yields} (-{delta}{sub {parallel}}, {pi} - {delta}{sub {perpendicular}}) is also a solution. The strong phases {delta}{sub {parallel}} and {delta}{sub {perpendicular}} are at {approx}> 3{sigma} from {+-}{pi}, signing the presence of final state interactions and the breakdown of the factorization hypothesis. The forward-backward analysis of the K{pi} mass spectrum revealed the presence of a coherent S-wave interfering with the K*(892). It is the first evidence of this wave in the K{pi} system coming from a B meson. The particularity of the B{sub d}{sup 0} {yields} J/{psi}(K{sub S}{sup 0}{pi}{sup 0})*{sup 0} channel is to have a time-dependent but also an angular distribution which allows to measure sin 2{beta} but also cos2{beta}. The results from an unbinned maximum likelihood fit are sin 2{beta} = -0.10 {+-} 0.57 {+-} 0.14 and cos 2{beta} = 3.32{sub -0.96}{sup +0.76} {+-} 0.27 with the transversity amplitudes fixed to the values given above. The other solution for the strong phases flips the sign of cos 2{beta}. Theoretical considerations based on the s-quark helicity conservation favor the choice of the strong phases given above, leading to a positive sign for cos 2{beta}. The sign of cos 2{beta} is the one predicted by the Standard Model.« less

DOE Office of Scientific and Technical Information (OSTI.GOV)

Saaban, Azizan; Zainudin, Lutfi; Bakar, Mohd Nazari Abu

This paper intends to reveal the ability of the linear interpolation method to predict missing values in solar radiation time series. Reliable dataset is equally tends to complete time series observed dataset. The absence or presence of radiation data alters long-term variation of solar radiation measurement values. Based on that change, the opportunities to provide bias output result for modelling and the validation process is higher. The completeness of the observed variable dataset has significantly important for data analysis. Occurrence the lack of continual and unreliable time series solar radiation data widely spread and become the main problematic issue. However,more » the limited number of research quantity that has carried out to emphasize and gives full attention to estimate missing values in the solar radiation dataset.« less

An empirical evaluation of supervised learning approaches in assigning diagnosis codes to electronic medical records

PubMed Central

Kavuluru, Ramakanth; Rios, Anthony; Lu, Yuan

2015-01-01

Background Diagnosis codes are assigned to medical records in healthcare facilities by trained coders by reviewing all physician authored documents associated with a patient's visit. This is a necessary and complex task involving coders adhering to coding guidelines and coding all assignable codes. With the popularity of electronic medical records (EMRs), computational approaches to code assignment have been proposed in the recent years. However, most efforts have focused on single and often short clinical narratives, while realistic scenarios warrant full EMR level analysis for code assignment. Objective We evaluate supervised learning approaches to automatically assign international classification of diseases (ninth revision) - clinical modification (ICD-9-CM) codes to EMRs by experimenting with a large realistic EMR dataset. The overall goal is to identify methods that offer superior performance in this task when considering such datasets. Methods We use a dataset of 71,463 EMRs corresponding to in-patient visits with discharge date falling in a two year period (2011–2012) from the University of Kentucky (UKY) Medical Center. We curate a smaller subset of this dataset and also use a third gold standard dataset of radiology reports. We conduct experiments using different problem transformation approaches with feature and data selection components and employing suitable label calibration and ranking methods with novel features involving code co-occurrence frequencies and latent code associations. Results Over all codes with at least 50 training examples we obtain a micro F-score of 0.48. On the set of codes that occur at least in 1% of the two year dataset, we achieve a micro F-score of 0.54. For the smaller radiology report dataset, the classifier chaining approach yields best results. For the smaller subset of the UKY dataset, feature selection, data selection, and label calibration offer best performance. Conclusions We show that datasets at different scale (size of the EMRs, number of distinct codes) and with different characteristics warrant different learning approaches. For shorter narratives pertaining to a particular medical subdomain (e.g., radiology, pathology), classifier chaining is ideal given the codes are highly related with each other. For realistic in-patient full EMRs, feature and data selection methods offer high performance for smaller datasets. However, for large EMR datasets, we observe that the binary relevance approach with learning-to-rank based code reranking offers the best performance. Regardless of the training dataset size, for general EMRs, label calibration to select the optimal number of labels is an indispensable final step. PMID:26054428

An empirical evaluation of supervised learning approaches in assigning diagnosis codes to electronic medical records.

PubMed

Kavuluru, Ramakanth; Rios, Anthony; Lu, Yuan

2015-10-01

Diagnosis codes are assigned to medical records in healthcare facilities by trained coders by reviewing all physician authored documents associated with a patient's visit. This is a necessary and complex task involving coders adhering to coding guidelines and coding all assignable codes. With the popularity of electronic medical records (EMRs), computational approaches to code assignment have been proposed in the recent years. However, most efforts have focused on single and often short clinical narratives, while realistic scenarios warrant full EMR level analysis for code assignment. We evaluate supervised learning approaches to automatically assign international classification of diseases (ninth revision) - clinical modification (ICD-9-CM) codes to EMRs by experimenting with a large realistic EMR dataset. The overall goal is to identify methods that offer superior performance in this task when considering such datasets. We use a dataset of 71,463 EMRs corresponding to in-patient visits with discharge date falling in a two year period (2011-2012) from the University of Kentucky (UKY) Medical Center. We curate a smaller subset of this dataset and also use a third gold standard dataset of radiology reports. We conduct experiments using different problem transformation approaches with feature and data selection components and employing suitable label calibration and ranking methods with novel features involving code co-occurrence frequencies and latent code associations. Over all codes with at least 50 training examples we obtain a micro F-score of 0.48. On the set of codes that occur at least in 1% of the two year dataset, we achieve a micro F-score of 0.54. For the smaller radiology report dataset, the classifier chaining approach yields best results. For the smaller subset of the UKY dataset, feature selection, data selection, and label calibration offer best performance. We show that datasets at different scale (size of the EMRs, number of distinct codes) and with different characteristics warrant different learning approaches. For shorter narratives pertaining to a particular medical subdomain (e.g., radiology, pathology), classifier chaining is ideal given the codes are highly related with each other. For realistic in-patient full EMRs, feature and data selection methods offer high performance for smaller datasets. However, for large EMR datasets, we observe that the binary relevance approach with learning-to-rank based code reranking offers the best performance. Regardless of the training dataset size, for general EMRs, label calibration to select the optimal number of labels is an indispensable final step. Copyright © 2015 Elsevier B.V. All rights reserved.

Preliminary results of the cross-section measurement of e{sup +}e{sup −} → φ(1020)η process with the CMD-3 detector at VEPP-2000 collider

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ivanov, V. L., E-mail: yacheslav-lvovich-ivanov@mail.ru; Akhmetshin, R. R.; Amirkhanov, A. N.

2016-03-15

We report preliminary results on the cross section of the process e{sup +}e{sup −} → φ(1020)η measured at 30 center-of-mass energy points in the range from 1.59 up to 2.0 GeV. Data analysis is based on the integrated luminosity of 22 pb{sup −1} collected with the CMD-3 detector in 2011–2012. The obtained cross section agrees with the BaBar measurement and has better statistical accuracy.

Measurement of the absolute branching fraction of D0-->K-pi+.

PubMed

Aubert, B; Bona, M; Boutigny, D; Karyotakis, Y; Lees, J P; Poireau, V; Prudent, X; Tisserand, V; Zghiche, A; Garra Tico, J; Grauges, E; Lopez, L; Palano, A; Eigen, G; Ofte, I; Stugu, B; Sun, L; Abrams, G S; Battaglia, M; Brown, D N; Button-Shafer, J; Cahn, R N; Groysman, Y; Jacobsen, R G; Kadyk, J A; Kerth, L T; Kolomensky, Yu G; Kukartsev, G; Lopes Pegna, D; Lynch, G; Mir, L M; Orimoto, T J; Pripstein, M; Roe, N A; Ronan, M T; Tackmann, K; Wenzel, W A; Del Amo Sanchez, P; Hawkes, C M; Watson, A T; Held, T; Koch, H; Lewandowski, B; Pelizaeus, M; Schroeder, T; Steinke, M; Cottingham, W N; Walker, D; Asgeirsson, D J; Cuhadar-Donszelmann, T; Fulsom, B G; Hearty, C; Knecht, N S; Mattison, T S; McKenna, J A; Khan, A; Saleem, M; Teodorescu, L; Blinov, V E; Bukin, A D; Druzhinin, V P; Golubev, V B; Onuchin, A P; Serednyakov, S I; Skovpen, Yu I; Solodov, E P; Todyshev, K Yu; Bondioli, M; Curry, S; Eschrich, I; Kirkby, D; Lankford, A J; Lund, P; Mandelkern, M; Martin, E C; Stoker, D P; Abachi, S; Buchanan, C; Foulkes, S D; Gary, J W; Liu, F; Long, O; Shen, B C; Zhang, L; Paar, H P; Rahatlou, S; Sharma, V; Berryhill, J W; Campagnari, C; Cunha, A; Dahmes, B; Hong, T M; Kovalskyi, D; Richman, J D; Beck, T W; Eisner, A M; Flacco, C J; Heusch, C A; Kroseberg, J; Lockman, W S; Schalk, T; Schumm, B A; Seiden, A; Williams, D C; Wilson, M G; Winstrom, L O; Chen, E; Cheng, C H; Dvoretskii, A; Fang, F; Hitlin, D G; Narsky, I; Piatenko, T; Porter, F C; Mancinelli, G; Meadows, B T; Mishra, K; Sokoloff, M D; Blanc, F; Bloom, P C; Chen, S; Ford, W T; Hirschauer, J F; Kreisel, A; Nagel, M; Nauenberg, U; Olivas, A; Smith, J G; Ulmer, K A; Wagner, S R; Zhang, J; Gabareen, A M; Soffer, A; Toki, W H; Wilson, R J; Winklmeier, F; Zeng, Q; Altenburg, D D; Feltresi, E; Hauke, A; Jasper, H; Merkel, J; Petzold, A; Spaan, B; Wacker, K; Brandt, T; Klose, V; Lacker, H M; Mader, W F; Nogowski, R; Schubert, J; Schubert, K R; Schwierz, R; Sundermann, J E; Volk, A; Bernard, D; Bonneaud, G R; Latour, E; Lombardo, V; Thiebaux, Ch; Verderi, M; Clark, P J; Gradl, W; Muheim, F; Playfer, S; Robertson, A I; Xie, Y; Andreotti, M; Bettoni, D; Bozzi, C; Calabrese, R; Cecchi, A; Cibinetto, G; Franchini, P; Luppi, E; Negrini, M; Petrella, A; Piemontese, L; Prencipe, E; Santoro, V; Anulli, F; Baldini-Ferroli, R; Calcaterra, A; de Sangro, R; Finocchiaro, G; Pacetti, S; Patteri, P; Peruzzi, I M; Piccolo, M; Rama, M; Zallo, A; Buzzo, A; Contri, R; Lo Vetere, M; Macri, M M; Monge, M R; Passaggio, S; Patrignani, C; Robutti, E; Santroni, A; Tosi, S; Chaisanguanthum, K S; Morii, M; Wu, J; Dubitzky, R S; Marks, J; Schenk, S; Uwer, U; Bard, D J; Dauncey, P D; Flack, R L; Nash, J A; Nikolich, M B; Panduro Vazquez, W; Behera, P K; Chai, X; Charles, M J; Mallik, U; Meyer, N T; Ziegler, V; Cochran, J; Crawley, H B; Dong, L; Eyges, V; Meyer, W T; Prell, S; Rosenberg, E I; Rubin, A E; Gritsan, A V; Guo, Z J; Lae, C K; Denig, A G; Fritsch, M; Schott, G; Arnaud, N; Béquilleux, J; Davier, M; Grosdidier, G; Höcker, A; Lepeltier, V; Le Diberder, F; Lutz, A M; Pruvot, S; Rodier, S; Roudeau, P; Schune, M H; Serrano, J; Sordini, V; Stocchi, A; Wang, W F; Wormser, G; Lange, D J; Wright, D M; Chavez, C A; Forster, I J; Fry, J R; Gabathuler, E; Gamet, R; Hutchcroft, D E; Payne, D J; Schofield, K C; Touramanis, C; Bevan, A J; George, K A; Di Lodovico, F; Menges, W; Sacco, R; Cowan, G; Flaecher, H U; Hopkins, D A; Jackson, P S; McMahon, T R; Salvatore, F; Wren, A C; Brown, D N; Davis, C L; Allison, J; Barlow, N R; Barlow, R J; Chia, Y M; Edgar, C L; Lafferty, G D; West, T J; Yi, J I; Anderson, J; Chen, C; Jawahery, A; Roberts, D A; Simi, G; Tuggle, J M; Blaylock, G; Dallapiccola, C; Hertzbach, S S; Li, X; Moore, T B; Salvati, E; Saremi, S; Cowan, R; Fisher, P H; Sciolla, G; Sekula, S J; Spitznagel, M; Taylor, F; Yamamoto, R K; McLachlin, S E; Patel, P M; Robertson, S H; Lazzaro, A; Palombo, F; Bauer, J M; Cremaldi, L; Eschenburg, V; Godang, R; Kroeger, R; Sanders, D A; Summers, D J; Zhao, H W; Brunet, S; Côté, D; Simard, M; Taras, P; Viaud, F B; Nicholson, H; De Nardo, G; Fabozzi, F; Lista, L; Monorchio, D; Sciacca, C; Baak, M A; Raven, G; Snoek, H L; Jessop, C P; Losecco, J M; Benelli, G; Corwin, L A; Gan, K K; Honscheid, K; Hufnagel, D; Kagan, H; Kass, R; Morris, J P; Rahimi, A M; Regensburger, J J; Ter-Antonyan, R; Wong, Q K; Blount, N L; Brau, J; Frey, R; Igonkina, O; Kolb, J A; Lu, M; Rahmat, R; Sinev, N B; Strom, D; Strube, J; Torrence, E; Gagliardi, N; Gaz, A; Margoni, M; Morandin, M; Pompili, A; Posocco, M; Rotondo, M; Simonetto, F; Stroili, R; Voci, C; Ben-Haim, E; Briand, H; Chauveau, J; David, P; Del Buono, L; de la Vaissière, Ch; Hamon, O; Hartfiel, B L; Leruste, Ph; Malclès, J; Ocariz, J; Perez, A; Gladney, L; Biasini, M; Covarelli, R; Manoni, E; Angelini, C; Batignani, G; Bettarini, S; Calderini, G; Carpinelli, M; Cenci, R; Cervelli, A; Forti, F; Giorgi, M A; Lusiani, A; Marchiori, G; Mazur, M A; Morganti, M; Neri, N; Paoloni, E; Rizzo, G; Walsh, J J; Haire, M; Biesiada, J; Elmer, P; Lau, Y P; Lu, C; Olsen, J; Smith, A J S; Telnov, A V; Baracchini, E; Bellini, F; Cavoto, G; D'Orazio, A; Del Re, D; Di Marco, E; Faccini, R; Ferrarotto, F; Ferroni, F; Gaspero, M; Jackson, P D; Li Gioi, L; Mazzoni, M A; Morganti, S; Piredda, G; Polci, F; Renga, F; Voena, C; Ebert, M; Schröder, H; Waldi, R; Adye, T; Castelli, G; Franek, B; Olaiya, E O; Ricciardi, S; Roethel, W; Wilson, F F; Aleksan, R; Emery, S; Escalier, M; Gaidot, A; Ganzhur, S F; de Monchenault, G Hamel; Kozanecki, W; Legendre, M; Vasseur, G; Yèche, Ch; Zito, M; Chen, X R; Liu, H; Park, W; Purohit, M V; Wilson, J R; Allen, M T; Aston, D; Bartoldus, R; Bechtle, P; Berger, N; Claus, R; Coleman, J P; Convery, M R; Dingfelder, J C; Dorfan, J; Dubois-Felsmann, G P; Dujmic, D; Dunwoodie, W; Field, R C; Glanzman, T; Gowdy, S J; Graham, M T; Grenier, P; Hast, C; Hryn'ova, T; Innes, W R; Kelsey, M H; Kim, H; Kim, P; Leith, D W G S; Li, S; Luitz, S; Luth, V; Lynch, H L; Macfarlane, D B; Marsiske, H; Messner, R; Muller, D R; O'Grady, C P; Perazzo, A; Perl, M; Pulliam, T; Ratcliff, B N; Roodman, A; Salnikov, A A; Schindler, R H; Schwiening, J; Snyder, A; Stelzer, J; Su, D; Sullivan, M K; Suzuki, K; Swain, S K; Thompson, J M; Va'vra, J; van Bakel, N; Wagner, A P; Weaver, M; Wisniewski, W J; Wittgen, M; Wright, D H; Yarritu, A K; Yi, K; Young, C C; Burchat, P R; Edwards, A J; Majewski, S A; Petersen, B A; Wilden, L; Ahmed, S; Alam, M S; Bula, R; Ernst, J A; Jain, V; Pan, B; Saeed, M A; Wappler, F R; Zain, S B; Bugg, W; Krishnamurthy, M; Spanier, S M; Eckmann, R; Ritchie, J L; Ruland, A M; Schilling, C J; Schwitters, R F; Izen, J M; Lou, X C; Ye, S; Bianchi, F; Gallo, F; Gamba, D; Pelliccioni, M; Bomben, M; Bosisio, L; Cartaro, C; Cossutti, F; Della Ricca, G; Lanceri, L; Vitale, L; Azzolini, V; Lopez-March, N; Martinez-Vidal, F; Milanes, D A; Oyanguren, A; Albert, J; Banerjee, Sw; Bhuyan, B; Hamano, K; Kowalewski, R; Nugent, I M; Roney, J M; Sobie, R J; Back, J J; Harrison, P F; Latham, T E; Mohanty, G B; Pappagallo, M; Band, H R; Chen, X; Dasu, S; Flood, K T; Hollar, J J; Kutter, P E; Pan, Y; Pierini, M; Prepost, R; Wu, S L; Yu, Z; Neal, H

2008-02-08

We measure the absolute branching fraction for D(0)-->K(-)pi(+) using partial reconstruction of B(0)-->D(*+)Xl(-)nu(l) decays, in which only the charged lepton and the pion from the decay D(*+)-->D(0)pi(+) are used. Based on a data sample of 230 x 10(6) BB pairs collected at the Upsilon(4S) resonance with the BABAR detector at the PEP-II asymmetric-energy B factory at SLAC, we obtain B(D(0)-->K(-)pi(+)) = (4.007+/-0.037+/-0.072)%, where the first uncertainty is statistical and the second is systematic.

Measurement of J/psi production in continuum e(+)e(-) annihilations near square root of s = 10.6 GeV.

PubMed

Aubert, B; Boutigny, D; Gaillard, J M; Hicheur, A; Karyotakis, Y; Lees, J P; Robbe, P; Tisserand, V; Palano, A; Chen, G P; Chen, J C; Qi, N D; Rong, G; Wang, P; Zhu, Y S; Eigen, G; Reinertsen, P L; Stugu, B; Abbott, B; Abrams, G S; Borgland, A W; Breon, A B; Brown, D N; Button-Shafer, J; Cahn, R N; Clark, A R; Fan, Q; Gill, M S; Gritsan, A; Groysman, Y; Jacobsen, R G; Kadel, R W; Kadyk, J; Kerth, L T; Kluth, S; Kolomensky, Y G; Kral, J F; LeClerc, C; Levi, M E; Liu, T; Lynch, G; Meyer, A B; Momayezi, M; Oddone, P J; Perazzo, A; Pripstein, M; Roe, N A; Romosan, A; Ronan, M T; Shelkov, V G; Telnov, A V; Wenzel, W A; Bright-Thomas, P G; Harrison, T J; Hawkes, C M; Kirk, A; Knowles, D J; O'Neale, S W; Penny, R C; Watson, A T; Watson, N K; Deppermann, T; Goetzen, K; Koch, H; Krug, J; Kunze, M; Lewandowski, B; Peters, K; Schmuecker, H; Steinke, M; Andress, J C; Barlow, N R; Bhimji, W; Chevalier, N; Clark, P J; Cottingham, W N; De Groot, N; Dyce, N; Foster, B; Mass, A; McFall, J D; Wallom, D; Wilson, F F; Abe, K; Hearty, C; Mattison, T S; McKenna, J A; Thiessen, D; Camanzi, B; Jolly, S; McKemey, A K; Tinslay, J; Blinov, V E; Bukin, A D; Bukin, D A; Buzykaev, A R; Dubrovin, M S; Golubev, V B; Ivanchenko, V N; Korol, A A; Kravchenko, E A; Onuchin, A P; Salnikov, A A; Serednyakov, S I; Skovpen, Y I; Telnov, V I; Yushkov, A N; Best, D; Lankford, A J; Mandelkern, M; McMahon, S; Stoker, D P; Ahsan, A; Arisaka, K; Buchanan, C; Chun, S; Branson, J G; MacFarlane, D B; Prell, S; Rahatlou, S; Raven, G; Sharma, V; Campagnari, C; Dahmes, B; Hart, P A; Kuznetsova, N; Levy, S L; Long, O; Lu, A; Richman, J D; Verkerke, W; Witherell, M; Yellin, S; Beringer, J; Dorfan, D E; Eisner, A M; Frey, A; Grillo, A A; Grothe, M; Heusch, C A; Johnson, R P; Kroeger, W; Lockman, W S; Pulliam, T; Sadrozinski, H; Schalk, T; Schmitz, R E; Schumm, B A; Seiden, A; Turri, M; Walkowiak, W; Williams, D C; Wilson, M G; Chen, E; Dubois-Felsmann, G P; Dvoretskii, A; Hitlin, D G; Metzler, S; Oyang, J; Porter, F C; Ryd, A; Samuel, A; Weaver, M; Yang, S; Zhu, R Y; Devmal, S; Geld, T L; Jayatilleke, S; Mancinelli, G; Meadows, B T; Sokoloff, M D; Bloom, P; Dima, M O; Fahey, S; Ford, W T; Gaede, F; Johnson, D R; Michael, A K; Nauenberg, U; Olivas, A; Park, H; Rankin, P; Roy, J; Sen, S; Smith, J G; van Hoek, W C; Wagner, D L; Blouw, J; Harton, J L; Krishnamurthy, M; Soffer, A; Toki, W H; Wilson, R J; Zhang, J; Brandt, T; Brose, J; Colberg, T; Dahlinger, G; Dickopp, M; Dubitzky, R S; Maly, E; Müller-Pfefferkorn, R; Otto, S; Schubert, K R; Schwierz, R; Spaan, B; Wilden, L; Behr, L; Bernard, D; Bonneaud, G R; Brochard, F; Cohen-Tanugi, J; Ferrag, S; Roussot, E; T'Jampens, S; Thiebaux, C; Vasileiadis, G; Verderi, M; Anjomshoaa, A; Bernet, R; Khan, A; Muheim, F; Playfer, S; Swain, J E; Falbo, M; Borean, C; Bozzi, C; Dittongo, S; Folegani, M; Piemontese, L; Treadwell, E; Anulli, F; Baldini-Ferroli, R; Calcaterra, A; de Sangro, R; Falciai, D; Finocchiaro, G; Patteri, P; Peruzzi, I M; Piccolo, M; Xie, Y; Zallo, A; Bagnasco, S; Buzzo, A; Contri, R; Crosetti, G; Fabbricatore, P; Farinon, S; Lo Vetere, M; Macri, M; Monge, M R; Musenich, R; Pallavicini, M; Parodi, R; Passaggio, S; Pastore, F C; Patrignani, C; Pia, M G; Priano, C; Robutti, E; Santroni, A; Morii, M; Bartoldus, R; Dignan, T; Hamilton, R; Mallik, U; Cochran, J; Crawley, H B; Fischer, P A; Lamsa, J; Meyer, W T; Rosenberg, E I; Benkebil, M; Grosdidier, G; Hast, C; Höcker, A; Lacker, H M; Lepeltier, V; Lutz, A M; Plaszczynski, S; Schune, M H; Trincaz-Duvoid, S; Valassi, A; Wormser, G; Bionta, R M; Brigljević, V; Fackler, O; Fujino, D; Lange, D J; Mugge, M; Shi, X; van Bibber, K; Wenaus, T J; Wright, D M; Wuest, C R; Carroll, M; Fry, J R; Gabathuler, E; Gamet, R; George, M; Kay, M; Payne, D J; Sloane, R J; Touramanis, C; Aspinwall, M L; Bowerman, D A; Dauncey, P D; Egede, U; Eschrich, I; Gunawardane, N J; Martin, R; Nash, J A; Sanders, P; Smith, D; Azzopardi, D E; Back, J J; Dixon, P; Harrison, P F; Potter, R J; Shorthouse, H W; Strother, P; Vidal, P B; Williams, M I; Cowan, G; George, S; Green, M G; Kurup, A; Marker, C E; McGrath, P; McMahon, T R; Ricciardi, S; Salvatore, F; Scott, I; Vaitsas, G; Brown, D; Davis, C L; Allison, J; Barlow, R J; Boyd, J T; Forti, A C; Fullwood, J; Jackson, F; Lafferty, G D; Savvas, N; Simopoulos, E T; Weatherall, J H; Farbin, A; Jawahery, A; Lillard, V; Olsen, J; Roberts, D A; Schieck, J R; Blaylock, G; Dallapiccola, C; Flood, K T; Hertzbach, S S; Kofler, R; Lin, C S; Moore, T B; Staengle, H; Willocq, S; Wittlin, J; Brau, B; Cowan, R; Sciolla, G; Taylor, F; Yamamoto, R K; Britton, D I; Milek, M; Patel, P M; Trischuk, J; Lanni, F; Palombo, F; Bauer, J M; Booke, M; Cremaldi, L; Eschenburg, V; Kroeger, R; Reidy, J; Sanders, D A; Summers, D J; Martin, J P; Nief, J Y; Seitz, R; Taras, P; Zacek, V; Nicholson, H; Sutton, C S; Cartaro, C; Cavallo, N; De Nardo, G; Fabozzi, F; Gatto, C; Lista, L; Paolucci, P; Piccolo, D; Sciacca, C; LoSecco, J M; Alsmiller, J R; Gabriel, T A; Handler, T; Brau, J; Frey, R; Iwasaki, M; Sinev, N B; Strom, D; Colecchia, F; Dal Corso, F; Dorigo, A; Galeazzi, F; Margoni, M; Michelon, G; Morandin, M; Posocco, M; Rotondo, M; Simonetto, F; Stroili, R; Torassa, E; Voci, C; Benayoun, M; Briand, H; Chauveau, J; David, P; de la Vaissière, C; Del Buono, L; Hamon, O; Le Diberder, F; Leruste, P; Lory, J; Roos, L; Stark, J; Versillé, S; Manfredi, P F; Re, V; Speziali, V; Frank, E D; Gladney, L; Guo, Q H; Panetta, J H; Angelini, C; Batignani, G; Bettarini, S; Bondioli, M; Carpinelli, M; Forti, F; Giorgi, M A; Lusiani, A; Martinez-Vidal, F; Morganti, M; Neri, N; Paoloni, E; Rama, M; Rizzo, G; Sandrelli, F; Simi, G; Triggiani, G; Walsh, J; Haire, M; Judd, D; Paick, K; Turnbull, L; Wagoner, D E; Albert, J; Bula, C; Elmer, P; Lu, C; McDonald, K T; Miftakov, V; Schaffner, S F; Smith, A J; Tumanov, A; Varnes, E W; Cavoto, G; del Re, D; Faccini, R; Ferrarotto, F; Ferroni, F; Fratini, K; Lamanna, E; Leonardi, E; Mazzoni, M A; Morganti, S; Piredda, G; Safai Tehrani, F; Serra, M; Voena, C; Christ, S; Waldi, R; Adye, T; Franek, B; Geddes, N I; Gopal, G P; Xella, S M; Aleksan, R; De Domenico, G; Emery, S; Gaidot, A; Ganzhur, S F; Giraud, P F; Hamel de Monchenault, G; Kozanecki, W; Langer, M; London, G W; Mayer, B; Serfass, B; Vasseur, G; Yèche, C; Zito, M; Copty, N; Purohit, M V; Singh, H; Yumiceva, F X; Adam, I; Anthony, P L; Aston, D; Baird, K; Bloom, E; Boyarski, A M; Bulos, F; Calderini, G; Claus, R; Convery, M R; Coupal, D P; Coward, D H; Dorfan, J; Doser, M; Dunwoodie, W; Field, R C; Glanzman, T; Godfrey, G L; Gowdy, S J; Grosso, P; Himel, T; Huffer, M E; Innes, W R; Jessop, C P; Kelsey, M H; Kim, P; Kocian, M L; Langenegger, U; Leith, D W; Luitz, S; Luth, V; Lynch, H L; Manzin, G; Marsiske, H; Menke, S; Messner, R; Moffeit, K C; Mount, R; Muller, D R; O'Grady, C P; Perl, M; Petrak, S; Quinn, H; Ratcliff, B N; Robertson, S H; Rochester, L S; Roodman, A; Schietinger, T; Schindler, R H; Schwiening, J; Serbo, V V; Snyder, A; Soha, A; Spanier, S M; Stahl, A; Stelzer, J; Su, D; Sullivan, M K; Talby, M; Tanaka, H A; Trunov, A; Va'vra, J; Wagner, S R; Weinstein, A J; Wisniewski, W J; Wright, D H; Young, C C; Burchat, P R; Cheng, C H; Kirkby, D; Meyer, T I; Roat, C; Henderson, R; Bugg, W; Cohn, H; Hart, E; Weidemann, A W; Benninger, T; Izen, J M; Kitayama, I; Lou, X C; Turcotte, M; Bianchi, F; Bona, M; Di Girolamo, B; Gamba, D; Smol, A; Zanin, D; Lanceri, L; Pompili, A; Vaugin, G; Panvini, R S; Brown, C M; De Silva, A; Kowalewski, R; Roney, J M; Band, H R; Charles, E; Dasu, S; Di Lodovico, F; Eichenbaum, A M; Hu, H; Johnson, J R; Liu, R; Nielsen, J; Orejudos, W; Pan, Y; Prepost, R; Scott, I J; Sekula, S J; von Wimmersperg-Toeller, J H; Wu, S L; Yu, Z; Zobernig, H; Kordich, T M; Neal, H

2001-10-15

The production of J/psi mesons in continuum e(+)e(-) annihilations has been studied with the BABAR detector at energies near the Upsilon(4S) resonance. The mesons are distinguished from J/psi production in B decays through their center-of-mass momentum and energy. We measure the cross section e(+)e(-)-->J/psi X to be 2.52+/-0.21+/-0.21 pb. We set a 90% C.L. upper limit on the branching fraction for direct Upsilon(4S)-->J/psi X decays at 4.7 x 10(-4).

Search for CP violation in the decay D±→KS0π±

NASA Astrophysics Data System (ADS)

Del Amo Sanchez, P.; Lees, J. P.; Poireau, V.; Prencipe, E.; Tisserand, V.; Garra Tico, J.; Grauges, E.; Martinelli, M.; Milanes, D. A.; Palano, A.; Pappagallo, M.; Eigen, G.; Stugu, B.; Sun, L.; Brown, D. N.; Kerth, L. T.; Kolomensky, Yu. G.; Lynch, G.; Osipenkov, I. L.; Koch, H.; Schroeder, T.; Asgeirsson, D. J.; Hearty, C.; Mattison, T. S.; McKenna, J. A.; Khan, A.; Blinov, V. E.; Buzykaev, A. R.; Druzhinin, V. P.; Golubev, V. B.; Kravchenko, E. A.; Onuchin, A. P.; Serednyakov, S. I.; Skovpen, Yu. I.; Solodov, E. P.; Todyshev, K. Yu.; Yushkov, A. N.; Bondioli, M.; Curry, S.; Kirkby, D.; Lankford, A. J.; Mandelkern, M.; Martin, E. C.; Stoker, D. P.; Atmacan, H.; Gary, J. W.; Liu, F.; Long, O.; Vitug, G. M.; Campagnari, C.; Hong, T. M.; Kovalskyi, D.; Richman, J. D.; West, C. A.; Eisner, A. M.; Heusch, C. A.; Kroseberg, J.; Lockman, W. S.; Martinez, A. J.; Schalk, T.; Schumm, B. A.; Seiden, A.; Winstrom, L. O.; Cheng, C. H.; Doll, D. A.; Echenard, B.; Hitlin, D. G.; Ongmongkolkul, P.; Porter, F. C.; Rakitin, A. Y.; Andreassen, R.; Dubrovin, M. S.; Meadows, B. T.; Sokoloff, M. D.; Bloom, P. C.; Ford, W. T.; Gaz, A.; Nagel, M.; Nauenberg, U.; Smith, J. G.; Wagner, S. R.; Ayad, R.; Toki, W. H.; Jasper, H.; Petzold, A.; Spaan, B.; Kobel, M. J.; Schubert, K. R.; Schwierz, R.; Bernard, D.; Verderi, M.; Clark, P. J.; Playfer, S.; Watson, J. E.; Andreotti, M.; Bettoni, D.; Bozzi, C.; Calabrese, R.; Cecchi, A.; Cibinetto, G.; Fioravanti, E.; Franchini, P.; Garzia, I.; Luppi, E.; Munerato, M.; Negrini, M.; Petrella, A.; Piemontese, L.; Baldini-Ferroli, R.; Calcaterra, A.; de Sangro, R.; Finocchiaro, G.; Nicolaci, M.; Pacetti, S.; Patteri, P.; Peruzzi, I. M.; Piccolo, M.; Rama, M.; Zallo, A.; Contri, R.; Guido, E.; Lo Vetere, M.; Monge, M. R.; Passaggio, S.; Patrignani, C.; Robutti, E.; Bhuyan, B.; Prasad, V.; Lee, C. L.; Morii, M.; Edwards, A. J.; Adametz, A.; Marks, J.; Uwer, U.; Bernlochner, F. U.; Ebert, M.; Lacker, H. M.; Lueck, T.; Volk, A.; Dauncey, P. D.; Tibbetts, M.; Behera, P. K.; Mallik, U.; Chen, C.; Cochran, J.; Crawley, H. B.; Meyer, W. T.; Prell, S.; Rosenberg, E. I.; Rubin, A. E.; Gritsan, A. V.; Guo, Z. J.; Arnaud, N.; Davier, M.; Derkach, D.; Firmino da Costa, J.; Grosdidier, G.; Le Diberder, F.; Lutz, A. M.; Malaescu, B.; Perez, A.; Roudeau, P.; Schune, M. H.; Serrano, J.; Sordini, V.; Stocchi, A.; Wang, L.; Wormser, G.; Lange, D. J.; Wright, D. M.; Bingham, I.; Chavez, C. A.; Coleman, J. P.; Fry, J. R.; Gabathuler, E.; Hutchcroft, D. E.; Payne, D. J.; Touramanis, C.; Bevan, A. J.; di Lodovico, F.; Sacco, R.; Sigamani, M.; Cowan, G.; Paramesvaran, S.; Wren, A. C.; Brown, D. N.; Davis, C. L.; Denig, A. G.; Fritsch, M.; Gradl, W.; Hafner, A.; Alwyn, K. E.; Bailey, D.; Barlow, R. J.; Jackson, G.; Lafferty, G. D.; Anderson, J.; Cenci, R.; Jawahery, A.; Roberts, D. A.; Simi, G.; Tuggle, J. M.; Dallapiccola, C.; Salvati, E.; Cowan, R.; Dujmic, D.; Sciolla, G.; Zhao, M.; Lindemann, D.; Patel, P. M.; Robertson, S. H.; Schram, M.; Biassoni, P.; Lazzaro, A.; Lombardo, V.; Palombo, F.; Stracka, S.; Cremaldi, L.; Godang, R.; Kroeger, R.; Sonnek, P.; Summers, D. J.; Nguyen, X.; Simard, M.; Taras, P.; de Nardo, G.; Monorchio, D.; Onorato, G.; Sciacca, C.; Raven, G.; Snoek, H. L.; Jessop, C. P.; Knoepfel, K. J.; Losecco, J. M.; Wang, W. F.; Corwin, L. A.; Honscheid, K.; Kass, R.; Blount, N. L.; Brau, J.; Frey, R.; Igonkina, O.; Kolb, J. A.; Rahmat, R.; Sinev, N. B.; Strom, D.; Strube, J.; Torrence, E.; Castelli, G.; Feltresi, E.; Gagliardi, N.; Margoni, M.; Morandin, M.; Pompili, A.; Posocco, M.; Rotondo, M.; Simonetto, F.; Stroili, R.; Ben-Haim, E.; Bomben, M.; Bonneaud, G. R.; Briand, H.; Calderini, G.; Chauveau, J.; Hamon, O.; Leruste, Ph.; Marchiori, G.; Ocariz, J.; Prendki, J.; Sitt, S.; Biasini, M.; Manoni, E.; Rossi, A.; Angelini, C.; Batignani, G.; Bettarini, S.; Carpinelli, M.; Casarosa, G.; Cervelli, A.; Forti, F.; Giorgi, M. A.; Lusiani, A.; Neri, N.; Paoloni, E.; Rizzo, G.; Walsh, J. J.; Lopes Pegna, D.; Lu, C.; Olsen, J.; Smith, A. J. S.; Telnov, A. V.; Anulli, F.; Baracchini, E.; Cavoto, G.; Faccini, R.; Ferrarotto, F.; Ferroni, F.; Gaspero, M.; Li Gioi, L.; Mazzoni, M. A.; Piredda, G.; Renga, F.; Buenger, C.; Hartmann, T.; Leddig, T.; Schröder, H.; Waldi, R.; Adye, T.; Olaiya, E. O.; Wilson, F. F.; Emery, S.; Hamel de Monchenault, G.; Vasseur, G.; Yèche, Ch.; Allen, M. T.; Aston, D.; Bard, D. J.; Bartoldus, R.; Benitez, J. F.; Cartaro, C.; Convery, M. R.; Dorfan, J.; Dubois-Felsmann, G. P.; Dunwoodie, W.; Field, R. C.; Franco Sevilla, M.; Fulsom, B. G.; Gabareen, A. M.; Graham, M. T.; Grenier, P.; Hast, C.; Innes, W. R.; Kelsey, M. H.; Kim, H.; Kim, P.; Kocian, M. L.; Leith, D. W. G. S.; Lewis, P.; Li, S.; Lindquist, B.; Luitz, S.; Luth, V.; Lynch, H. L.; Macfarlane, D. B.; Muller, D. R.; Neal, H.; Nelson, S.; O'Grady, C. P.; Ofte, I.; Perl, M.; Pulliam, T.; Ratcliff, B. N.; Roodman, A.; Salnikov, A. A.; Santoro, V.; Schindler, R. H.; Schwiening, J.; Snyder, A.; Su, D.; Sullivan, M. K.; Sun, S.; Suzuki, K.; Thompson, J. M.; Va'Vra, J.; Wagner, A. P.; Weaver, M.; Wisniewski, W. J.; Wittgen, M.; Wright, D. H.; Wulsin, H. W.; Yarritu, A. K.; Young, C. C.; Ziegler, V.; Chen, X. R.; Park, W.; Purohit, M. V.; White, R. M.; Wilson, J. R.; Randle-Conde, A.; Sekula, S. J.; Bellis, M.; Burchat, P. R.; Miyashita, T. S.; Ahmed, S.; Alam, M. S.; Ernst, J. A.; Pan, B.; Saeed, M. A.; Zain, S. B.; Guttman, N.; Soffer, A.; Lund, P.; Spanier, S. M.; Eckmann, R.; Ritchie, J. L.; Ruland, A. M.; Schilling, C. J.; Schwitters, R. F.; Wray, B. C.; Izen, J. M.; Lou, X. C.; Bianchi, F.; Gamba, D.; Pelliccioni, M.; Lanceri, L.; Vitale, L.; Lopez-March, N.; Martinez-Vidal, F.; Oyanguren, A.; Ahmed, H.; Albert, J.; Banerjee, Sw.; Choi, H. H. F.; Hamano, K.; King, G. J.; Kowalewski, R.; Lewczuk, M. J.; Lindsay, C.; Nugent, I. M.; Roney, J. M.; Sobie, R. J.; Gershon, T. J.; Harrison, P. F.; Latham, T. E.; Puccio, E. M. T.; Band, H. R.; Dasu, S.; Flood, K. T.; Pan, Y.; Prepost, R.; Vuosalo, C. O.; Wu, S. L.

2011-04-01

We report on a search for CP violation in the decay D±→KS0π± using a data set corresponding to an integrated luminosity of 469fb-1 collected with the BABAR detector at the PEP-II asymmetric energy e+e- storage rings. The CP-violating decay rate asymmetry ACP is determined to be (-0.44±0.13(stat)±0.10(syst))%, consistent with zero at 2.7σ and with the standard model prediction of (-0.332±0.006)%. This is currently the most precise measurement of this parameter.

Branching Fraction and CP Asymmetry Measurements in Inclusive B → X s ℓ⁺ℓ⁻ and B → X sγ Decays from BABAR

DOE Office of Scientific and Technical Information (OSTI.GOV)

Eigen, G.

We present an update on total and partial branching fractions and on CP asymmetries in the semi-inclusive decay B → X sℓ⁺ℓ -. Further, we summarize our results on branching fractions and CP asymmetries for semi-inclusive and fully-inclusive B → X sγ decays. We present the first result on the CP asymmetry difference of charged and neutral B → X sγ decays yielding the first constraint on the ratio of Wilson coefficients Im(C 8 eff/C 7 eff).

On the nature of χ c2(2P): two-gluon decay

NASA Astrophysics Data System (ADS)

Achasov, N. N.; Kang, Xian-Wei

2017-12-01

We expect that BR(χ c2(2P)→gluongluon)≳2% if the Particle Data Group as well as the BaBar and Belle collaborations have correctly identified the state. In reality, this branching ratio corresponds to the one for χ c2(2P) decaying into light hadrons. We also discuss the detection possibilities of these decays. N.N. Achasov was supported in part by RFBR, (16-02-00065), and by Presidium of the Russian Academy of Sciences, Project (0314-2015-0011), XWK’s work is supported by MOST, Taiwan, (104-2112-M-001-022)

Suppressed Charmed B Decay

DOE Office of Scientific and Technical Information (OSTI.GOV)

Snoek, Hella Leonie

2009-06-02

This thesis describes the measurement of the branching fractions of the suppressed charmed B 0 → D *- a 0 + decays and the non-resonant B 0 → D *- ηπ + decays in approximately 230 million Υ(4S) → Bmore » $$\\bar{B}$$ events. The data have been collected with the BABAR detector at the PEP-II B factory at the Stanford Linear Accelerator Center in California. Theoretical predictions of the branching fraction of the B 0 → D *- a{sub 0} + decays show large QCD model dependent uncertainties. Non-factorizing terms, in the naive factorization model, that can be calculated by QCD factorizing models have a large impact on the branching fraction of these decay modes. The predictions of the branching fractions are of the order of 10 -6. The measurement of the branching fraction gives more insight into the theoretical models. In general a better understanding of QCD models will be necessary to conduct weak interaction physics at the next level. The presence of CP violation in electroweak interactions allows the differentiation between matter and antimatter in the laws of physics. In the Standard Model, CP violation is incorporated in the CKM matrix that describes the weak interaction between quarks. Relations amongst the CKM matrix elements are used to present the two relevant parameters as the apex of a triangle (Unitarity Triangle) in a complex plane. The over-constraining of the CKM triangle by experimental measurements is an important test of the Standard Model. At this moment no stringent direct measurements of the CKM angle γ, one of the interior angles of the Unitarity Triangle, are available. The measurement of the angle γ can be performed using the decays of neutral B mesons. The B 0 → D *- a 0 + decay is sensitive to the angle γ and, in comparison to the current decays that are being employed, could significantly enhance the measurement of this angle. However, the low expected branching fraction for the B 0 → D *- a 0 + decay channels could severely impact the measurement. A prerequisite of the measurement of the CKM angle is the observation of the B 0 → D *- a 0 + decay on which this thesis reports. The BABAR experiment consists of the BABAR detector and the PEP-II e +e - collider. The design of the experiment has been optimized for the study of CP violation in the decays of neutral B mesons but is also highly suitable for the search for rare B decays such as the B0 → D *- a 0 + decay. The PEP-II collider operates at the Υ(4S) resonance and is a clean source of B$$\\bar{B}$$ meson pairs.« less

Evidence for C P violation in B+→K*(892)+ π0 from a Dalitz plot analysis of B+→KS0 π+π0 decays

NASA Astrophysics Data System (ADS)

Lees, J. P.; Poireau, V.; Tisserand, V.; Grauges, E.; Palano, A.; Eigen, G.; Stugu, B.; Brown, D. N.; Kerth, L. T.; Kolomensky, Yu. G.; Lee, M. J.; Lynch, G.; Koch, H.; Schroeder, T.; Hearty, C.; Mattison, T. S.; McKenna, J. A.; So, R. Y.; Khan, A.; Blinov, V. E.; Buzykaev, A. R.; Druzhinin, V. P.; Golubev, V. B.; Kravchenko, E. A.; Onuchin, A. P.; Serednyakov, S. I.; Skovpen, Yu. I.; Solodov, E. P.; Todyshev, K. Yu.; Lankford, A. J.; Dey, B.; Gary, J. W.; Long, O.; Franco Sevilla, M.; Hong, T. M.; Kovalskyi, D.; Richman, J. D.; West, C. A.; Eisner, A. M.; Lockman, W. S.; Panduro Vazquez, W.; Schumm, B. A.; Seiden, A.; Chao, D. S.; Cheng, C. H.; Echenard, B.; Flood, K. T.; Hitlin, D. G.; Miyashita, T. S.; Ongmongkolkul, P.; Porter, F. C.; Röhrken, M.; Andreassen, R.; Huard, Z.; Meadows, B. T.; Pushpawela, B. G.; Sokoloff, M. D.; Sun, L.; Bloom, P. C.; Ford, W. T.; Gaz, A.; Smith, J. G.; Wagner, S. R.; Ayad, R.; Toki, W. H.; Spaan, B.; Bernard, D.; Verderi, M.; Playfer, S.; Bettoni, D.; Bozzi, C.; Calabrese, R.; Cibinetto, G.; Fioravanti, E.; Garzia, I.; Luppi, E.; Piemontese, L.; Santoro, V.; Calcaterra, A.; de Sangro, R.; Finocchiaro, G.; Martellotti, S.; Patteri, P.; Peruzzi, I. M.; Piccolo, M.; Rama, M.; Zallo, A.; Contri, R.; Monge, M. R.; Passaggio, S.; Patrignani, C.; Bhuyan, B.; Prasad, V.; Adametz, A.; Uwer, U.; Lacker, H. M.; Mallik, U.; Chen, C.; Cochran, J.; Prell, S.; Ahmed, H.; Gritsan, A. V.; Arnaud, N.; Davier, M.; Derkach, D.; Grosdidier, G.; Le Diberder, F.; Lutz, A. M.; Malaescu, B.; Roudeau, P.; Stocchi, A.; Wormser, G.; Lange, D. J.; Wright, D. M.; Coleman, J. P.; Fry, J. R.; Gabathuler, E.; Hutchcroft, D. E.; Payne, D. J.; Touramanis, C.; Bevan, A. J.; Di Lodovico, F.; Sacco, R.; Cowan, G.; Brown, D. N.; Davis, C. L.; Denig, A. G.; Fritsch, M.; Gradl, W.; Griessinger, K.; Hafner, A.; Schubert, K. R.; Barlow, R. J.; Lafferty, G. D.; Cenci, R.; Hamilton, B.; Jawahery, A.; Roberts, D. A.; Cowan, R.; Cheaib, R.; Patel, P. M.; Robertson, S. H.; Neri, N.; Palombo, F.; Cremaldi, L.; Godang, R.; Summers, D. J.; Simard, M.; Taras, P.; De Nardo, G.; Onorato, G.; Sciacca, C.; Raven, G.; Jessop, C. P.; LoSecco, J. M.; Honscheid, K.; Kass, R.; Margoni, M.; Morandin, M.; Posocco, M.; Rotondo, M.; Simi, G.; Simonetto, F.; Stroili, R.; Akar, S.; Ben-Haim, E.; Bomben, M.; Bonneaud, G. R.; Briand, H.; Calderini, G.; Chauveau, J.; Leruste, Ph.; Marchiori, G.; Ocariz, J.; Biasini, M.; Manoni, E.; Rossi, A.; Angelini, C.; Batignani, G.; Bettarini, S.; Carpinelli, M.; Casarosa, G.; Chrzaszcz, M.; Forti, F.; Giorgi, M. A.; Lusiani, A.; Oberhof, B.; Paoloni, E.; Rizzo, G.; Walsh, J. J.; Lopes Pegna, D.; Olsen, J.; Smith, A. J. S.; Anulli, F.; Faccini, R.; Ferrarotto, F.; Ferroni, F.; Gaspero, M.; Pilloni, A.; Piredda, G.; Bünger, C.; Dittrich, S.; Grünberg, O.; Hess, M.; Leddig, T.; Voß, C.; Waldi, R.; Adye, T.; Olaiya, E. O.; Wilson, F. F.; Emery, S.; Vasseur, G.; Aston, D.; Bard, D. J.; Cartaro, C.; Convery, M. R.; Dorfan, J.; Dubois-Felsmann, G. P.; Dunwoodie, W.; Ebert, M.; Field, R. C.; Fulsom, B. G.; Graham, M. T.; Hast, C.; Innes, W. R.; Kim, P.; Leith, D. W. G. S.; Lindemann, D.; Luitz, S.; Luth, V.; Lynch, H. L.; MacFarlane, D. B.; Muller, D. R.; Neal, H.; Perl, M.; Pulliam, T.; Ratcliff, B. N.; Roodman, A.; Schindler, R. H.; Snyder, A.; Su, D.; Sullivan, M. K.; Va'vra, J.; Wisniewski, W. J.; Wulsin, H. W.; Purohit, M. V.; Wilson, J. R.; Randle-Conde, A.; Sekula, S. J.; Bellis, M.; Burchat, P. R.; Puccio, E. M. T.; Alam, M. S.; Ernst, J. A.; Gorodeisky, R.; Guttman, N.; Peimer, D. R.; Soffer, A.; Spanier, S. M.; Ritchie, J. L.; Schwitters, R. F.; Izen, J. M.; Lou, X. C.; Bianchi, F.; De Mori, F.; Filippi, A.; Gamba, D.; Lanceri, L.; Vitale, L.; Martinez-Vidal, F.; Oyanguren, A.; Villanueva-Perez, P.; Albert, J.; Banerjee, Sw.; Beaulieu, A.; Bernlochner, F. U.; Choi, H. H. F.; King, G. J.; Kowalewski, R.; Lewczuk, M. J.; Lueck, T.; Nugent, I. M.; Roney, J. M.; Sobie, R. J.; Tasneem, N.; Gershon, T. J.; Harrison, P. F.; Latham, T. E.; Band, H. R.; Dasu, S.; Pan, Y.; Prepost, R.; Wu, S. L.; BaBar Collaboration

2017-10-01

We report a Dalitz plot analysis of charmless hadronic decays of charged B mesons to the final state KS0π+π0 using the full BABAR data set of 470.9 ±2.8 million B B ¯ events collected at the Υ (4 S ) resonance. We measure the overall branching fraction and C P asymmetry to be B (B+→K0π+π0) =(31.8 ±1.8 ±2. 1-0.0+6.0 ) ×10-6 and AC P(B+→K0π+π0) =0.07 ±0.05 ±0.0 3-0.03+0.02 , where the uncertainties are statistical, systematic, and due to the signal model, respectively. This is the first measurement of the branching fraction for B+→K0π+π0. We find first evidence of a C P asymmetry in B+→K*(892 )+π0decays: AC P(B+→K*(892 )+π0) =-0.52 ±0.14 ±0.0 4-0.02+0.04 . The significance of this asymmetry, including systematic and model uncertainties, is 3.4 standard deviations. We also measure the branching fractions and C P asymmetries for three other intermediate decay modes.

A Merged Dataset for Solar Probe Plus FIELDS Magnetometers

NASA Astrophysics Data System (ADS)

Bowen, T. A.; Dudok de Wit, T.; Bale, S. D.; Revillet, C.; MacDowall, R. J.; Sheppard, D.

2016-12-01

The Solar Probe Plus FIELDS experiment will observe turbulent magnetic fluctuations deep in the inner heliosphere. The FIELDS magnetometer suite implements a set of three magnetometers: two vector DC fluxgate magnetometers (MAGs), sensitive from DC- 100Hz, as well as a vector search coil magnetometer (SCM), sensitive from 10Hz-50kHz. Single axis measurements are additionally made up to 1MHz. To study the full range of observations, we propose merging data from the individual magnetometers into a single dataset. A merged dataset will improve the quality of observations in the range of frequencies observed by both magnetometers ( 10-100 Hz). Here we present updates on the individual MAG and SCM calibrations as well as our results on generating a cross-calibrated and merged dataset.

Extraction and Analysis of Regional Emission and Absorption Events of Greenhouse Gases with GOSAT and OCO-2

NASA Astrophysics Data System (ADS)

Kasai, K.; Shiomi, K.; Konno, A.; Tadono, T.; Hori, M.

2016-12-01

Global observation of greenhouse gases such as carbon dioxide (CO2) and methane (CH4) with high spatio-temporal resolution and accurate estimation of sources and sinks are important to understand greenhouse gases dynamics. Greenhouse Gases Observing Satellite (GOSAT) has observed column-averaged dry-air mole fractions of CO2 (XCO2) and CH4 (XCH4) over 7 years since January 2009 with wide swath but sparse pointing. Orbiting Carbon Observatory-2 (OCO-2) has observed XCO2 jointly on orbit since July 2014 with narrow swath but high resolution. We use two retrieved datasets as GOSAT observation data. One is ACOS GOSAT/TANSO-FTS Level 2 Full Product by NASA/JPL, and the other is NIES TANSO-FTS L2 column amount (SWIR). By using these GOSAT datasets and OCO-2 L2 Full Product, the biases among datasets, local sources and sinks, and temporal variability of greenhouse gases are clarified. In addition, CarbonTracker, which is a global model of atmospheric CO2 and CH4 developed by NOAA/ESRL, are also analyzed for comparing between satellite observation data and atmospheric model data. Before analyzing these datasets, outliers are screened by using quality flag, outcome flag, and warn level in land or sea parts. Time series data of XCO2 and XCH4 are obtained globally from satellite observation and atmospheric model datasets, and functions which express typical inter-annual and seasonal variation are fitted to each spatial grid. Consequently, anomalous events of XCO2 and XCH4 are extracted by the difference between each time series dataset and the fitted function. Regional emission and absorption events are analyzed by time series variation of satellite observation data and by comparing with atmospheric model data.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cheaib, Racha

The flavour changing neutral current (FCNC) process,more » $B^+$ → $K^+ τ^+ τ^-$ highly suppressed in the Standard Model (SM). This decay is forbidden at tree level and only occurs at lowest order via one-loop diagrams.$B^+$ → $K^+ τ^+ τ^-$ thus has the potential to provide a stringent test of the SM and a fertile ground for new physics searches. Contributions due to virtual particles in the loop allow one to probe, at relatively low energies, new physics at large mass scales. We search for the rare FCNC process $B^+$ → $K^+ τ^+ τ^-$ using data collected by the BaBaR detector at the SLAC National Accelerator Laboratory. The BaBaR data sample corresponds to a total integrated luminosity, at the energy of the Τ(4S) resonance, of 424.4 $fb^-1$ and 471 million $$B\\bar{B}$$ pairs. For this search, hadronic $$B_{tag}$$ reconstruction is employed, where one B is exclusively reconstructed via one of many possible hadronic modes. The remaining decay products in an event are then attributed to the signal B, on which the search for $B^+$ → $K^+ τ^+ τ^-$ is performed. Each τ is required to decay leptonically, into either an electron or a muon and the lepton neutrinos. Furthermore, a multi-variate analysis technique (neural network) is used to select for signal events and suppress dominant background modes. No significant signal is observed. The resulting branching fraction is measured to be $$\\beta(B^+$$ → $K^+ τ^+)$ = $$1.31^{0:66}_{-0:61}$$(stat.) $$^{+0:35}_{-0:25}$$(sys.) x 10$$^{-3}$$, which is consistent with zero at the 1.9σ level, with an upper limit of 2.25 x 10$$^{-3}$$, at the 90% confidence level.« less

Passive and Active Monitoring on a High Performance Research Network.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Matthews, Warren

2001-05-01

The bold network challenges described in ''Internet End-to-end Performance Monitoring for the High Energy and Nuclear Physics Community'' presented at PAM 2000 have been tackled by the intrepid administrators and engineers providing the network services. After less than a year, the BaBar collaboration has collected almost 100 million particle collision events in a database approaching 165TB (Tera=10{sup 12}). Around 20TB has been exported via the Internet to the BaBar regional center at IN2P3 in Lyon, France, for processing and around 40 TB of simulated events have been imported to SLAC from Lawrence Livermore National Laboratory (LLNL). An unforseen challenge hasmore » arisen due to recent events and highlighted security concerns at DoE funded labs. New rules and regulations suggest it is only a matter of time before many active performance measurements may not be possible between many sites. Yet, at the same time, the importance of understanding every aspect of the network and eradicating packet loss for high throughput data transfers has become apparent. Work at SLAC to employ passive monitoring using netflow and OC3MON is underway and techniques to supplement and possibly replace the active measurements are being considered. This paper will detail the special needs and traffic characterization of a remarkable research project, and how the networking hurdles have been resolved (or not!) to achieve the required high data throughput. Results from active and passive measurements will be compared, and methods for achieving high throughput and the effect on the network will be assessed along with tools that directly measure throughput and applications used to actually transfer data.« less

Seismic Surveys Negatively Affect Humpback Whale Singing Activity off Northern Angola

PubMed Central

Cerchio, Salvatore; Strindberg, Samantha; Collins, Tim; Bennett, Chanda; Rosenbaum, Howard

2014-01-01

Passive acoustic monitoring was used to document the presence of singing humpback whales off the coast of Northern Angola, and opportunistically test for the effect of seismic survey activity in the vicinity on the number of singing whales. Two Marine Autonomous Recording Units (MARUs) were deployed between March and December 2008 in the offshore environment. Song was first heard in mid June and continued through the remaining duration of the study. Seismic survey activity was heard regularly during two separate periods, consistently throughout July and intermittently in mid-October/November. Numbers of singers were counted during the first ten minutes of every hour for the period from 24 May to 1 December, and Generalized Additive Mixed Models (GAMMs) were used to assess the effect of survey day (seasonality), hour (diel variation), moon phase and received levels of seismic survey pulses (measured from a single pulse during each ten-minute sampled period) on singer number. Application of GAMMs indicated significant seasonal variation, which was the most pronounced effect when assessing the full dataset across the entire season (p<0.001); however seasonality almost entirely dropped out of top-ranked models when applied to a reduced dataset during the July period of seismic survey activity. Diel variation was significant in both the full and reduced datasets (from p<0.01 to p<0.05) and often included in the top-ranked models. The number of singers significantly decreased with increasing received level of seismic survey pulses (from p<0.01 to p<0.05); this explanatory variable was included among the top ranked models for one MARU in the full dataset and both MARUs in the reduced dataset. This suggests that the breeding display of humpback whales is disrupted by seismic survey activity, and thus merits further attention and study, and potentially conservation action in the case of sensitive breeding populations. PMID:24618836

Seismic surveys negatively affect humpback whale singing activity off northern Angola.

PubMed

Cerchio, Salvatore; Strindberg, Samantha; Collins, Tim; Bennett, Chanda; Rosenbaum, Howard

2014-01-01

Passive acoustic monitoring was used to document the presence of singing humpback whales off the coast of Northern Angola, and opportunistically test for the effect of seismic survey activity in the vicinity on the number of singing whales. Two Marine Autonomous Recording Units (MARUs) were deployed between March and December 2008 in the offshore environment. Song was first heard in mid June and continued through the remaining duration of the study. Seismic survey activity was heard regularly during two separate periods, consistently throughout July and intermittently in mid-October/November. Numbers of singers were counted during the first ten minutes of every hour for the period from 24 May to 1 December, and Generalized Additive Mixed Models (GAMMs) were used to assess the effect of survey day (seasonality), hour (diel variation), moon phase and received levels of seismic survey pulses (measured from a single pulse during each ten-minute sampled period) on singer number. Application of GAMMs indicated significant seasonal variation, which was the most pronounced effect when assessing the full dataset across the entire season (p<0.001); however seasonality almost entirely dropped out of top-ranked models when applied to a reduced dataset during the July period of seismic survey activity. Diel variation was significant in both the full and reduced datasets (from p<0.01 to p<0.05) and often included in the top-ranked models. The number of singers significantly decreased with increasing received level of seismic survey pulses (from p<0.01 to p<0.05); this explanatory variable was included among the top ranked models for one MARU in the full dataset and both MARUs in the reduced dataset. This suggests that the breeding display of humpback whales is disrupted by seismic survey activity, and thus merits further attention and study, and potentially conservation action in the case of sensitive breeding populations.

Metaxa: a software tool for automated detection and discrimination among ribosomal small subunit (12S/16S/18S) sequences of archaea, bacteria, eukaryotes, mitochondria, and chloroplasts in metagenomes and environmental sequencing datasets.

PubMed

Bengtsson, Johan; Eriksson, K Martin; Hartmann, Martin; Wang, Zheng; Shenoy, Belle Damodara; Grelet, Gwen-Aëlle; Abarenkov, Kessy; Petri, Anna; Rosenblad, Magnus Alm; Nilsson, R Henrik

2011-10-01

The ribosomal small subunit (SSU) rRNA gene has emerged as an important genetic marker for taxonomic identification in environmental sequencing datasets. In addition to being present in the nucleus of eukaryotes and the core genome of prokaryotes, the gene is also found in the mitochondria of eukaryotes and in the chloroplasts of photosynthetic eukaryotes. These three sets of genes are conceptually paralogous and should in most situations not be aligned and analyzed jointly. To identify the origin of SSU sequences in complex sequence datasets has hitherto been a time-consuming and largely manual undertaking. However, the present study introduces Metaxa ( http://microbiology.se/software/metaxa/ ), an automated software tool to extract full-length and partial SSU sequences from larger sequence datasets and assign them to an archaeal, bacterial, nuclear eukaryote, mitochondrial, or chloroplast origin. Using data from reference databases and from full-length organelle and organism genomes, we show that Metaxa detects and scores SSU sequences for origin with very low proportions of false positives and negatives. We believe that this tool will be useful in microbial and evolutionary ecology as well as in metagenomics.

A collection of Australian Drosophila datasets on climate adaptation and species distributions.

PubMed

Hangartner, Sandra B; Hoffmann, Ary A; Smith, Ailie; Griffin, Philippa C

2015-11-24

The Australian Drosophila Ecology and Evolution Resource (ADEER) collates Australian datasets on drosophilid flies, which are aimed at investigating questions around climate adaptation, species distribution limits and population genetics. Australian drosophilid species are diverse in climatic tolerance, geographic distribution and behaviour. Many species are restricted to the tropics, a few are temperate specialists, and some have broad distributions across climatic regions. Whereas some species show adaptability to climate changes through genetic and plastic changes, other species have limited adaptive capacity. This knowledge has been used to identify traits and genetic polymorphisms involved in climate change adaptation and build predictive models of responses to climate change. ADEER brings together 103 datasets from 39 studies published between 1982-2013 in a single online resource. All datasets can be downloaded freely in full, along with maps and other visualisations. These historical datasets are preserved for future studies, which will be especially useful for assessing climate-related changes over time.

Searches for Lepton Flavor Violation in the Decays τ±→e±γ and τ±→μ±γ

NASA Astrophysics Data System (ADS)

Aubert, B.; Karyotakis, Y.; Lees, J. P.; Poireau, V.; Prencipe, E.; Prudent, X.; Tisserand, V.; Garra Tico, J.; Grauges, E.; Martinelli, M.; Palano, A.; Pappagallo, M.; Eigen, G.; Stugu, B.; Sun, L.; Battaglia, M.; Brown, D. N.; Hooberman, B.; Kerth, L. T.; Kolomensky, Yu. G.; Lynch, G.; Osipenkov, I. L.; Tackmann, K.; Tanabe, T.; Hawkes, C. M.; Soni, N.; Watson, A. T.; Koch, H.; Schroeder, T.; Asgeirsson, D. J.; Hearty, C.; Mattison, T. S.; McKenna, J. A.; Barrett, M.; Khan, A.; Randle-Conde, A.; Blinov, V. E.; Bukin, A. D.; Buzykaev, A. R.; Druzhinin, V. P.; Golubev, V. B.; Onuchin, A. P.; Serednyakov, S. I.; Skovpen, Yu. I.; Solodov, E. P.; Todyshev, K. Yu.; Bondioli, M.; Curry, S.; Eschrich, I.; Kirkby, D.; Lankford, A. J.; Lund, P.; Mandelkern, M.; Martin, E. C.; Stoker, D. P.; Atmacan, H.; Gary, J. W.; Liu, F.; Long, O.; Vitug, G. M.; Yasin, Z.; Sharma, V.; Campagnari, C.; Hong, T. M.; Kovalskyi, D.; Mazur, M. A.; Richman, J. D.; Beck, T. W.; Eisner, A. M.; Heusch, C. A.; Kroseberg, J.; Lockman, W. S.; Martinez, A. J.; Schalk, T.; Schumm, B. A.; Seiden, A.; Wang, L.; Winstrom, L. O.; Cheng, C. H.; Doll, D. A.; Echenard, B.; Fang, F.; Hitlin, D. G.; Narsky, I.; Ongmongkolkul, P.; Piatenko, T.; Porter, F. C.; Andreassen, R.; Mancinelli, G.; Meadows, B. T.; Mishra, K.; Sokoloff, M. D.; Bloom, P. C.; Ford, W. T.; Gaz, A.; Hirschauer, J. F.; Nagel, M.; Nauenberg, U.; Smith, J. G.; Wagner, S. R.; Ayad, R.; Toki, W. H.; Feltresi, E.; Hauke, A.; Jasper, H.; Karbach, T. M.; Merkel, J.; Petzold, A.; Spaan, B.; Wacker, K.; Kobel, M. J.; Nogowski, R.; Schubert, K. R.; Schwierz, R.; Bernard, D.; Latour, E.; Verderi, M.; Clark, P. J.; Playfer, S.; Watson, J. E.; Andreotti, M.; Bettoni, D.; Bozzi, C.; Calabrese, R.; Cecchi, A.; Cibinetto, G.; Fioravanti, E.; Franchini, P.; Luppi, E.; Munerato, M.; Negrini, M.; Petrella, A.; Piemontese, L.; Santoro, V.; Baldini-Ferroli, R.; Calcaterra, A.; de Sangro, R.; Finocchiaro, G.; Pacetti, S.; Patteri, P.; Peruzzi, I. M.; Piccolo, M.; Rama, M.; Zallo, A.; Contri, R.; Guido, E.; Lo Vetere, M.; Monge, M. R.; Passaggio, S.; Patrignani, C.; Robutti, E.; Tosi, S.; Morii, M.; Adametz, A.; Marks, J.; Schenk, S.; Uwer, U.; Bernlochner, F. U.; Lacker, H. M.; Lueck, T.; Volk, A.; Dauncey, P. D.; Tibbetts, M.; Behera, P. K.; Charles, M. J.; Mallik, U.; Cochran, J.; Crawley, H. B.; Dong, L.; Eyges, V.; Meyer, W. T.; Prell, S.; Rosenberg, E. I.; Rubin, A. E.; Gao, Y. Y.; Gritsan, A. V.; Guo, Z. J.; Arnaud, N.; D'Orazio, A.; Davier, M.; Derkach, D.; Firmino da Costa, J.; Grosdidier, G.; Le Diberder, F.; Lepeltier, V.; Lutz, A. M.; Malaescu, B.; Roudeau, P.; Schune, M. H.; Serrano, J.; Sordini, V.; Stocchi, A.; Wormser, G.; Lange, D. J.; Wright, D. M.; Bingham, I.; Burke, J. P.; Chavez, C. A.; Fry, J. R.; Gabathuler, E.; Gamet, R.; Hutchcroft, D. E.; Payne, D. J.; Touramanis, C.; Bevan, A. J.; Clarke, C. K.; di Lodovico, F.; Sacco, R.; Sigamani, M.; Cowan, G.; Paramesvaran, S.; Wren, A. C.; Brown, D. N.; Davis, C. L.; Denig, A. G.; Fritsch, M.; Gradl, W.; Hafner, A.; Alwyn, K. E.; Bailey, D.; Barlow, R. J.; Jackson, G.; Lafferty, G. D.; West, T. J.; Yi, J. I.; Anderson, J.; Chen, C.; Jawahery, A.; Roberts, D. A.; Simi, G.; Tuggle, J. M.; Dallapiccola, C.; Salvati, E.; Cowan, R.; Dujmic, D.; Fisher, P. H.; Henderson, S. W.; Sciolla, G.; Spitznagel, M.; Yamamoto, R. K.; Zhao, M.; Patel, P. M.; Robertson, S. H.; Schram, M.; Biassoni, P.; Lazzaro, A.; Lombardo, V.; Palombo, F.; Stracka, S.; Cremaldi, L.; Godang, R.; Kroeger, R.; Sonnek, P.; Summers, D. J.; Zhao, H. W.; Nguyen, X.; Simard, M.; Taras, P.; Nicholson, H.; de Nardo, G.; Lista, L.; Monorchio, D.; Onorato, G.; Sciacca, C.; Raven, G.; Snoek, H. L.; Jessop, C. P.; Knoepfel, K. J.; Losecco, J. M.; Wang, W. F.; Corwin, L. A.; Honscheid, K.; Kagan, H.; Kass, R.; Morris, J. P.; Rahimi, A. M.; Sekula, S. J.; Blount, N. L.; Brau, J.; Frey, R.; Igonkina, O.; Kolb, J. A.; Lu, M.; Rahmat, R.; Sinev, N. B.; Strom, D.; Strube, J.; Torrence, E.; Castelli, G.; Gagliardi, N.; Margoni, M.; Morandin, M.; Posocco, M.; Rotondo, M.; Simonetto, F.; Stroili, R.; Voci, C.; Del Amo Sanchez, P.; Ben-Haim, E.; Bonneaud, G. R.; Briand, H.; Chauveau, J.; Hamon, O.; Leruste, Ph.; Marchiori, G.; Ocariz, J.; Perez, A.; Prendki, J.; Sitt, S.; Gladney, L.; Biasini, M.; Manoni, E.; Angelini, C.; Batignani, G.; Bettarini, S.; Calderini, G.; Carpinelli, M.; Cervelli, A.; Forti, F.; Giorgi, M. A.; Lusiani, A.; Morganti, M.; Neri, N.; Paoloni, E.; Rizzo, G.; Walsh, J. J.; Lopes Pegna, D.; Lu, C.; Olsen, J.; Smith, A. J. S.; Telnov, A. V.; Anulli, F.; Baracchini, E.; Cavoto, G.; Faccini, R.; Ferrarotto, F.; Ferroni, F.; Gaspero, M.; Jackson, P. D.; Li Gioi, L.; Mazzoni, M. A.; Morganti, S.; Piredda, G.; Renga, F.; Voena, C.; Ebert, M.; Hartmann, T.; Schröder, H.; Waldi, R.; Adye, T.; Franek, B.; Olaiya, E. O.; Wilson, F. F.; Emery, S.; Esteve, L.; Hamel de Monchenault, G.; Kozanecki, W.; Vasseur, G.; Yèche, Ch.; Zito, M.; Allen, M. T.; Aston, D.; Bard, D. J.; Bartoldus, R.; Benitez, J. F.; Cenci, R.; Coleman, J. P.; Convery, M. R.; Dingfelder, J. C.; Dorfan, J.; Dubois-Felsmann, G. P.; Dunwoodie, W.; Field, R. C.; Franco Sevilla, M.; Fulsom, B. G.; Gabareen, A. M.; Graham, M. T.; Grenier, P.; Hast, C.; Innes, W. R.; Kaminski, J.; Kelsey, M. H.; Kim, H.; Kim, P.; Kocian, M. L.; Leith, D. W. G. S.; Li, S.; Lindquist, B.; Luitz, S.; Luth, V.; Lynch, H. L.; Macfarlane, D. B.; Marsiske, H.; Messner, R.; Muller, D. R.; Neal, H.; Nelson, S.; O'Grady, C. P.; Ofte, I.; Perl, M.; Ratcliff, B. N.; Roodman, A.; Salnikov, A. A.; Schindler, R. H.; Schwiening, J.; Snyder, A.; Su, D.; Sullivan, M. K.; Suzuki, K.; Swain, S. K.; Thompson, J. M.; Va'Vra, J.; Wagner, A. P.; Weaver, M.; West, C. A.; Wisniewski, W. J.; Wittgen, M.; Wright, D. H.; Wulsin, H. W.; Yarritu, A. K.; Young, C. C.; Ziegler, V.; Chen, X. R.; Liu, H.; Park, W.; Purohit, M. V.; White, R. M.; Wilson, J. R.; Bellis, M.; Burchat, P. R.; Edwards, A. J.; Miyashita, T. S.; Ahmed, S.; Alam, M. S.; Ernst, J. A.; Pan, B.; Saeed, M. A.; Zain, S. B.; Soffer, A.; Spanier, S. M.; Wogsland, B. J.; Eckmann, R.; Ritchie, J. L.; Ruland, A. M.; Schilling, C. J.; Schwitters, R. F.; Wray, B. C.; Drummond, B. W.; Izen, J. M.; Lou, X. C.; Bianchi, F.; Gamba, D.; Pelliccioni, M.; Bomben, M.; Bosisio, L.; Cartaro, C.; Della Ricca, G.; Lanceri, L.; Vitale, L.; Azzolini, V.; Lopez-March, N.; Martinez-Vidal, F.; Milanes, D. A.; Oyanguren, A.; Albert, J.; Banerjee, Sw.; Bhuyan, B.; Choi, H. H. F.; Hamano, K.; King, G. J.; Kowalewski, R.; Lewczuk, M. J.; Lindsay, C. D.; Locke, C. B.; Nugent, I. M.; Roney, J. M.; Sobie, R. J.; Gershon, T. J.; Harrison, P. F.; Ilic, J.; Latham, T. E.; Mohanty, G. B.; Puccio, E. M. T.; Band, H. R.; Chen, X.; Dasu, S.; Flood, K. T.; Pan, Y.; Prepost, R.; Vuosalo, C. O.; Wu, S. L.; BaBar Collaboration

2010-01-01

Searches for lepton-flavor-violating decays of a τ lepton to a lighter mass lepton and a photon have been performed with the entire data set of (963±7)×106τ decays collected by the BABAR detector near the Υ(4S), Υ(3S) and Υ(2S) resonances. The searches yield no evidence of signals and we set upper limits on the branching fractions of B(τ±→e±γ)<3.3×10-8 and B(τ±→μ±γ)<4.4×10-8 at 90% confidence level.

Modelling of Peach Tree (Prunus persica) Full Blooming Dates Using APCC MME Seasonal Forecasts

NASA Astrophysics Data System (ADS)

Chun, Jong; Kim, Sung; Lee, Hyojin; Han, Hyun-Hee; Son, In-Chang; Cho, Kyung Hwa

2016-04-01

Due to global warming, recently, bud-burst and flowering dates of fruit crops have become earlier and the abnormal climate increases the variabilities of temperature in spring, suggesting that the risk of frost damage has increased. However, the full blooming date prediction model for peach tree used by the Rural Developmental Administration (RDA) were developed using only one cultivar (Youmyeong) and observations from a station (Suwon). This model might not adequately reflect the characteristics of peach cultivars or local orchards. the objectives of this study were to develops the site-and cultivar-specific blooming date prediction models for major peach cultivation regions and cultivars and presents a framework for applications of the APEC Climate Center Multimodel Ensemble (APCC MME) seasonal datasets.Developmental rate (DVR), and Sequential dormancy models (Chill day, New chill day, and fraction-time models) were used to develop the locally tailored full blooming date prediction models for major peach cultivars. For the development of these models, bud-burst and full blooming dates of peach tree for 5 cultivars (Cheonhong, Youmyeong, Changbangjosaeng, Cheonjoongdo, and Janghowon) were collected from the 6 major peach cultivation sites: Chuncheon, Suwon, Cheongwon, Cheongdo, Naju, and Jinju. For the chill day model, those measures for the entire dataset regardless the location and cultivar were 2.31%, 0.79, and 3.36 day for MAPE, R2, RMSE, respectively. For the new chill day model, those values (2.19%, 0.82, and 3.16 day for MAPE, R2, RMSE, respectively) were slightly better than those of the chill day model. The model results showed that the new chill day model was found slightly highest performance than others. Based on the considerations of the predictability of the statistical downscaling method and the observed periods of the full blooming dates at each site, we determined that the APCC MME seasonal datasets were applied for the new chill day model for the Changbangjosaeng and Youmyeong cultivars at the Suwon site. The values of the goodness-of-fit measures using the selected synthetic daily maximum and minimum temperatures reflecting APCC MME seasonal datasets and selected were worse than those using those collected from the Suwon station. It is concluded that further work was recommended that the predictability of APCC MME seasonal forecasts should be improved to reduce the prediction errors of full blooming dates of peach trees.

Depth calibration of the Experimental Advanced Airborne Research Lidar, EAARL-B

USGS Publications Warehouse

Wright, C. Wayne; Kranenburg, Christine J.; Troche, Rodolfo J.; Mitchell, Richard W.; Nagle, David B.

2016-05-17

The resulting calibrated EAARL-B data were then analyzed and compared with the original reference dataset, the jet-ski-based dataset from the same Fort Lauderdale site, as well as the depth-accuracy requirements of the International Hydrographic Organization (IHO). We do not claim to meet all of the IHO requirements and standards. The IHO minimum depth-accuracy requirements were used as a reference only and we do not address the other IHO requirements such as “ Full Seafloor Search”. Our results show good agreement between the calibrated EAARL-B data and all reference datasets, with results that are within the 95 percent depth accuracy of the IHO Order 1 (a and b) depth-accuracy requirements.

Detection of drug active ingredients by chemometric processing of solid-state NMR spectrometry data -- the case of acetaminophen.

PubMed

Paradowska, Katarzyna; Jamróz, Marta Katarzyna; Kobyłka, Mariola; Gowin, Ewelina; Maczka, Paulina; Skibiński, Robert; Komsta, Łukasz

2012-01-01

This paper presents a preliminary study in building discriminant models from solid-state NMR spectrometry data to detect the presence of acetaminophen in over-the-counter pharmaceutical formulations. The dataset, containing 11 spectra of pure substances and 21 spectra of various formulations, was processed by partial least squares discriminant analysis (PLS-DA). The model found coped with the discrimination, and its quality parameters were acceptable. It was found that standard normal variate preprocessing had almost no influence on unsupervised investigation of the dataset. The influence of variable selection with the uninformative variable elimination by PLS method was studied, reducing the dataset from 7601 variables to around 300 informative variables, but not improving the model performance. The results showed the possibility to construct well-working PLS-DA models from such small datasets without a full experimental design.

Persistent Identifiers Implementation in EOSDIS

NASA Technical Reports Server (NTRS)

Ramapriyan, H. K. " Rama"

2016-01-01

This presentation provides the motivation for and status of implementation of persistent identifiers in NASA's Earth Observation System Data and Information System (EOSDIS). The motivation is provided from the point of view of long-term preservation of datasets such that a number of questions raised by current and future users can be answered easily and precisely. A number of artifacts need to be preserved along with datasets to make this possible, especially when the authors of datasets are no longer available to address users questions. The artifacts and datasets need to be uniquely and persistently identified and linked with each other for full traceability, understandability and scientific reproducibility. Current work in the Earth Science Data and Information System (ESDIS) Project and the Distributed Active Archive Centers (DAACs) in assigning Digital Object Identifiers (DOI) is discussed as well as challenges that remain to be addressed in the future.

Three-Dimensional Anisotropic Acoustic and Elastic Full-Waveform Seismic Inversion

NASA Astrophysics Data System (ADS)

Warner, M.; Morgan, J. V.

2013-12-01

Three-dimensional full-waveform inversion is a high-resolution, high-fidelity, quantitative, seismic imaging technique that has advanced rapidly within the oil and gas industry. The method involves the iterative improvement of a starting model using a series of local linearized updates to solve the full non-linear inversion problem. During the inversion, forward modeling employs the full two-way three-dimensional heterogeneous anisotropic acoustic or elastic wave equation to predict the observed raw field data, wiggle-for-wiggle, trace-by-trace. The method is computationally demanding; it is highly parallelized, and runs on large multi-core multi-node clusters. Here, we demonstrate what can be achieved by applying this newly practical technique to several high-density 3D seismic datasets that were acquired to image four contrasting sedimentary targets: a gas cloud above an oil reservoir, a radially faulted dome, buried fluvial channels, and collapse structures overlying an evaporate sequence. We show that the resulting anisotropic p-wave velocity models match in situ measurements in deep boreholes, reproduce detailed structure observed independently on high-resolution seismic reflection sections, accurately predict the raw seismic data, simplify and sharpen reverse-time-migrated reflection images of deeper horizons, and flatten Kirchhoff-migrated common-image gathers. We also show that full-elastic 3D full-waveform inversion of pure pressure data can generate a reasonable shear-wave velocity model for one of these datasets. For two of the four datasets, the inclusion of significant transversely isotropic anisotropy with a vertical axis of symmetry was necessary in order to fit the kinematics of the field data properly. For the faulted dome, the full-waveform-inversion p-wave velocity model recovers the detailed structure of every fault that can be seen on coincident seismic reflection data. Some of the individual faults represent high-velocity zones, some represent low-velocity zones, some have more-complex internal structure, and some are visible merely as offsets between two regions with contrasting velocity. Although this has not yet been demonstrated quantitatively for this dataset, it seems likely that at least some of this fine structure in the recovered velocity model is related to the detailed lithology, strain history and fluid properties within the individual faults. We have here applied this technique to seismic data that were acquired by the extractive industries, however this inversion scheme is immediately scalable and applicable to a much wider range of problems given sufficient quality and density of observed data. Potential targets range from shallow magma chambers beneath active volcanoes, through whole-crustal sections across plate boundaries, to regional and whole-Earth models.

Benchmark of Machine Learning Methods for Classification of a SENTINEL-2 Image

NASA Astrophysics Data System (ADS)

Pirotti, F.; Sunar, F.; Piragnolo, M.

2016-06-01

Thanks to mainly ESA and USGS, a large bulk of free images of the Earth is readily available nowadays. One of the main goals of remote sensing is to label images according to a set of semantic categories, i.e. image classification. This is a very challenging issue since land cover of a specific class may present a large spatial and spectral variability and objects may appear at different scales and orientations. In this study, we report the results of benchmarking 9 machine learning algorithms tested for accuracy and speed in training and classification of land-cover classes in a Sentinel-2 dataset. The following machine learning methods (MLM) have been tested: linear discriminant analysis, k-nearest neighbour, random forests, support vector machines, multi layered perceptron, multi layered perceptron ensemble, ctree, boosting, logarithmic regression. The validation is carried out using a control dataset which consists of an independent classification in 11 land-cover classes of an area about 60 km2, obtained by manual visual interpretation of high resolution images (20 cm ground sampling distance) by experts. In this study five out of the eleven classes are used since the others have too few samples (pixels) for testing and validating subsets. The classes used are the following: (i) urban (ii) sowable areas (iii) water (iv) tree plantations (v) grasslands. Validation is carried out using three different approaches: (i) using pixels from the training dataset (train), (ii) using pixels from the training dataset and applying cross-validation with the k-fold method (kfold) and (iii) using all pixels from the control dataset. Five accuracy indices are calculated for the comparison between the values predicted with each model and control values over three sets of data: the training dataset (train), the whole control dataset (full) and with k-fold cross-validation (kfold) with ten folds. Results from validation of predictions of the whole dataset (full) show the random forests method with the highest values; kappa index ranging from 0.55 to 0.42 respectively with the most and least number pixels for training. The two neural networks (multi layered perceptron and its ensemble) and the support vector machines - with default radial basis function kernel - methods follow closely with comparable performance.

Markov random field based automatic image alignment for electron tomography.

PubMed

Amat, Fernando; Moussavi, Farshid; Comolli, Luis R; Elidan, Gal; Downing, Kenneth H; Horowitz, Mark

2008-03-01

We present a method for automatic full-precision alignment of the images in a tomographic tilt series. Full-precision automatic alignment of cryo electron microscopy images has remained a difficult challenge to date, due to the limited electron dose and low image contrast. These facts lead to poor signal to noise ratio (SNR) in the images, which causes automatic feature trackers to generate errors, even with high contrast gold particles as fiducial features. To enable fully automatic alignment for full-precision reconstructions, we frame the problem probabilistically as finding the most likely particle tracks given a set of noisy images, using contextual information to make the solution more robust to the noise in each image. To solve this maximum likelihood problem, we use Markov Random Fields (MRF) to establish the correspondence of features in alignment and robust optimization for projection model estimation. The resulting algorithm, called Robust Alignment and Projection Estimation for Tomographic Reconstruction, or RAPTOR, has not needed any manual intervention for the difficult datasets we have tried, and has provided sub-pixel alignment that is as good as the manual approach by an expert user. We are able to automatically map complete and partial marker trajectories and thus obtain highly accurate image alignment. Our method has been applied to challenging cryo electron tomographic datasets with low SNR from intact bacterial cells, as well as several plastic section and X-ray datasets.

Evidence for C P violation in B + → K * ( 892 ) + π 0 from a Dalitz plot analysis of B + → K S 0 π + π 0 decays

DOE PAGES

Lees, J. P.; Poireau, V.; Tisserand, V.; ...

2017-10-02

We report a Dalitz plot analysis of charmless hadronic decays of charged B mesons to the final state K 0 Sπ +π 0 using the full BABAR data set of 470.9 ± 2.8 million B¯B events collected at the Υ(4S) resonance. We measure the overall branching fraction and CP asymmetry to be B(B + → K 0π +π 0) = (31.8 ± 1.8 ± 2.1 +6.0 –0.0) × 10 –6 and ACP(B + → K 0π +π 0) = 0.07 ± 0.05 ± 0.03 +0.02 –0.03, where the uncertainties are statistical, systematic, and due to the signal model, respectively. Thismore » is the first measurement of the branching fraction for B + → K 0π +π 0. We find first evidence of a CP asymmetry in B + → K*(892) +π 0 decays: ACP(B + → K*(892) +π 0) = –0.52 ± 0.14 ± 0.04 +0.04 –0.02. The significance of this asymmetry, including systematic and model uncertainties, is 3.4 standard deviations. As a result, we also measure the branching fractions and CP asymmetries for three other intermediate decay modes.« less

Evidence for C P violation in B + → K * ( 892 ) + π 0 from a Dalitz plot analysis of B + → K S 0 π + π 0 decays

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lees, J. P.; Poireau, V.; Tisserand, V.

We report a Dalitz plot analysis of charmless hadronic decays of charged B mesons to the final state K 0 Sπ +π 0 using the full BABAR data set of 470.9 ± 2.8 million B¯B events collected at the Υ(4S) resonance. We measure the overall branching fraction and CP asymmetry to be B(B + → K 0π +π 0) = (31.8 ± 1.8 ± 2.1 +6.0 –0.0) × 10 –6 and ACP(B + → K 0π +π 0) = 0.07 ± 0.05 ± 0.03 +0.02 –0.03, where the uncertainties are statistical, systematic, and due to the signal model, respectively. Thismore » is the first measurement of the branching fraction for B + → K 0π +π 0. We find first evidence of a CP asymmetry in B + → K*(892) +π 0 decays: ACP(B + → K*(892) +π 0) = –0.52 ± 0.14 ± 0.04 +0.04 –0.02. The significance of this asymmetry, including systematic and model uncertainties, is 3.4 standard deviations. As a result, we also measure the branching fractions and CP asymmetries for three other intermediate decay modes.« less

Using Third Party Data to Update a Reference Dataset in a Quality Evaluation Service

NASA Astrophysics Data System (ADS)

Xavier, E. M. A.; Ariza-López, F. J.; Ureña-Cámara, M. A.

2016-06-01

Nowadays it is easy to find many data sources for various regions around the globe. In this 'data overload' scenario there are few, if any, information available about the quality of these data sources. In order to easily provide these data quality information we presented the architecture of a web service for the automation of quality control of spatial datasets running over a Web Processing Service (WPS). For quality procedures that require an external reference dataset, like positional accuracy or completeness, the architecture permits using a reference dataset. However, this reference dataset is not ageless, since it suffers the natural time degradation inherent to geospatial features. In order to mitigate this problem we propose the Time Degradation & Updating Module which intends to apply assessed data as a tool to maintain the reference database updated. The main idea is to utilize datasets sent to the quality evaluation service as a source of 'candidate data elements' for the updating of the reference database. After the evaluation, if some elements of a candidate dataset reach a determined quality level, they can be used as input data to improve the current reference database. In this work we present the first design of the Time Degradation & Updating Module. We believe that the outcomes can be applied in the search of a full-automatic on-line quality evaluation platform.

U.S. Heat Demand by Sector for Potential Application of Direct Use Geothermal

DOE Data Explorer

Katherine Young

2016-06-23

This dataset includes heat demand for potential application of direct use geothermal broken down into 4 sectors: agricultural, commercial, manufacturing and residential. The data for each sector are organized by county, were disaggregated specifically to assess the market demand for geothermal direct use, and were derived using methodologies customized for each sector based on the availability of data and other sector-specific factors. This dataset also includes a paper containing a full explanation of the methodologies used.

Distance to nearest road in the conterminous United States

USGS Publications Warehouse

Watts, Raymond D.

2005-01-01

The new dataset is the first member of the National Overview Road Metrics (NORM) family of road related indicators.  This indicator measures straight-line or Euclidean distance (ED) to the nearest road, and is given the compound name NORM ED.  NORM ED data can be viewed and downloaded from the transportation section of the web viewer for The National Map, http://nationalmap.usgs.gov.  The full-resolution dataset for the conterminous states is made of 8.7 billion values.

Optical Properties of the DIRC Fused Silica Radiator

DOE Office of Scientific and Technical Information (OSTI.GOV)

Convery, Mark R

2003-04-15

The DIRC detector is successfully operating as the hadronic particle identification system for the BaBar experiment at SLAC. The production of its Cherenkov radiator required much effort in practice, both in manufacture and conception, which in turn required a large number of R&D measurements. One of the major outcomes of this R&D work was an understanding of methods to select radiation hard and optically uniform fused silica material. Others included measurement of the wavelength dependency of the internal reflection coefficient, and its sensitivity to the surface pollution, selection of the radiator support, selection of good optical glue, etc. This notemore » summarizes the optical R&D test results.« less

Measurement of time-dependent CP asymmetries and constraints on sin(2beta+gamma) with partial reconstruction of B0-->D*-/+pi+/- decays.

PubMed

Aubert, B; Barate, R; Boutigny, D; Couderc, F; Gaillard, J-M; Hicheur, A; Karyotakis, Y; Lees, J P; Robbe, P; Tisserand, V; Zghiche, A; Palano, A; Pompili, A; Chen, J C; Qi, N D; Rong, G; Wang, P; Zhu, Y S; Eigen, G; Ofte, I; Stugu, B; Abrams, G S; Borgland, A W; Breon, A B; Brown, D N; Button-Shafer, J; Cahn, R N; Charles, E; Day, C T; Gill, M S; Gritsan, A V; Groysman, Y; Jacobsen, R G; Kadel, R W; Kadyk, J; Kerth, L T; Kolomensky, Yu G; Kukartsev, G; LeClerc, C; Levi, M E; Lynch, G; Mir, L M; Oddone, P J; Orimoto, T J; Pripstein, M; Roe, N A; Romosan, A; Ronan, M T; Shelkov, V G; Telnov, A V; Wenzel, W A; Ford, K; Harrison, T J; Hawkes, C M; Knowles, D J; Morgan, S E; Penny, R C; Watson, A T; Watson, N K; Goetzen, K; Held, T; Koch, H; Lewandowski, B; Pelizaeus, M; Peters, K; Schmuecker, H; Steinke, M; Boyd, J T; Chevalier, N; Cottingham, W N; Kelly, M P; Latham, T E; Mackay, C; Wilson, F F; Abe, K; Cuhadar-Donszelmann, T; Hearty, C; Mattison, T S; McKenna, J A; Thiessen, D; Kyberd, P; McKemey, A K; Teodorescu, L; Blinov, V E; Bukin, A D; Golubev, V B; Ivanchenko, V N; Kravchenko, E A; Onuchin, A P; Serednyakov, S I; Skovpen, Yu I; Solodov, E P; Yushkov, A N; Best, D; Bruinsma, M; Chao, M; Kirkby, D; Lankford, A J; Mandelkern, M; Mommsen, R K; Roethel, W; Stoker, D P; Buchanan, C; Hartfiel, B L; Gary, J W; Layter, J; Shen, B C; Wang, K; del Re, D; Hadavand, H K; Hill, E J; MacFarlane, D B; Paar, H P; Rahatlou, Sh; Sharma, V; Berryhill, J W; Campagnari, C; Dahmes, B; Levy, S L; Long, O; Lu, A; Mazur, M A; Richman, J D; Verkerke, W; Beck, T W; Beringer, J; Eisner, A M; Heusch, C A; Lockman, W S; Schalk, T; Schmitz, R E; Schumm, B A; Seiden, A; Spradlin, P; Turri, M; Walkowiak, W; Williams, D C; Wilson, M G; Albert, J; Chen, E; Dubois-Felsmann, G P; Dvoretskii, A; Erwin, R J; Hitlin, D G; Narsky, I; Piatenko, T; Porter, F C; Ryd, A; Samuel, A; Yang, S; Jayatilleke, S; Mancinelli, G; Meadows, B T; Sokoloff, M D; Abe, T; Blanc, F; Bloom, P; Chen, S; Clark, P J; Ford, W T; Nauenberg, U; Olivas, A; Rankin, P; Roy, J; Smith, J G; van Hoek, W C; Zhang, L; Harton, J L; Hu, T; Soffer, A; Toki, W H; Wilson, R J; Zhang, J; Altenburg, D; Brandt, T; Brose, J; Colberg, T; Dickopp, M; Dubitzky, R S; Hauke, A; Lacker, H M; Maly, E; Müller-Pfefferkorn, R; Nogowski, R; Otto, S; Schubert, J; Schubert, K R; Schwierz, R; Spaan, B; Wilden, L; Bernard, D; Bonneaud, G R; Brochard, F; Cohen-Tanugi, J; Grenier, P; Thiebaux, Ch; Vasileiadis, G; Verderi, M; Khan, A; Lavin, D; Muheim, F; Playfer, S; Swain, J E; Andreotti, M; Azzolini, V; Bettoni, D; Bozzi, C; Calabrese, R; Cibinetto, G; Luppi, E; Negrini, M; Piemontese, L; Sarti, A; Treadwell, E; Baldini-Ferroli, R; Calcaterra, A; de Sangro, R; Falciai, D; Finocchiaro, G; Patteri, P; Piccolo, M; Zallo, A; Buzzo, A; Capra, R; Contri, R; Crosetti, G; Lo Vetere, M; Macri, M; Monge, M R; Passaggio, S; Patrignani, C; Robutti, E; Santroni, A; Tosi, S; Bailey, S; Morii, M; Won, E; Bhimji, W; Bowerman, D A; Dauncey, P D; Egede, U; Eschrich, I; Gaillard, J R; Morton, G W; Nash, J A; Taylor, G P; Grenier, G J; Lee, S-J; Mallik, U; Cochran, J; Crawley, H B; Lamsa, J; Meyer, W T; Prell, S; Rosenberg, E I; Yi, J; Davier, M; Grosdidier, G; Höcker, A; Laplace, S; Diberder, F Le; Lepeltier, V; Lutz, A M; Petersen, T C; Plaszczynski, S; Schune, M H; Tantot, L; Wormser, G; Brigljević, V; Cheng, C H; Lange, D J; Simani, M C; Wright, D M; Bevan, A J; Coleman, J P; Fry, J R; Gabathuler, E; Gamet, R; Kay, M; Parry, R J; Payne, D J; Sloane, R J; Touramanis, C; Back, J J; Harrison, P F; Shorthouse, H W; Vidal, P B; Brown, C L; Cowan, G; Flack, R L; Flaecher, H U; George, S; Green, M G; Kurup, A; Marker, C E; McMahon, T R; Ricciardi, S; Salvatore, F; Vaitsas, G; Winter, M A; Brown, D; Davis, C L; Allison, J; Barlow, N R; Barlow, R J; Hart, P A; Hodgkinson, M C; Jackson, F; Lafferty, G D; Lyon, A J; Weatherall, J H; Williams, J C; Farbin, A; Jawahery, A; Kovalskyi, D; Lae, C K; Lillard, V; Roberts, D A; Blaylock, G; Dallapiccola, C; Flood, K T; Hertzbach, S S; Kofler, R; Koptchev, V B; Moore, T B; Saremi, S; Staengle, H; Willocq, S; Cowan, R; Sciolla, G; Taylor, F; Yamamoto, R K; Mangeol, D J J; Patel, P M; Robertson, S H; Lazzaro, A; Palombo, F; Bauer, J M; Cremaldi, L; Eschenburg, V; Godang, R; Kroeger, R; Reidy, J; Sanders, D A; Summers, D J; Zhao, H W; Brunet, S; Cote-Ahern, D; Taras, P; Nicholson, H; Cartaro, C; Cavallo, N; De Nardo, G; Fabozzi, F; Gatto, C; Lista, L; Paolucci, P; Piccolo, D; Sciacca, C; Baak, M A; Raven, G; LoSecco, J M; Gabriel, T A; Brau, B; Gan, K K; Honscheid, K; Hufnagel, D; Kagan, H; Kass, R; Pulliam, T; Wong, Q K; Brau, J; Frey, R; Igonkina, O; Potter, C T; Sinev, N B; Strom, D; Torrence, E; Colecchia, F; Dorigo, A; Galeazzi, F; Margoni, M; Morandin, M; Posocco, M; Rotondo, M; Simonetto, F; Stroili, R; Tiozzo, G; Voci, C; Benayoun, M; Briand, H; Chauveau, J; David, P; de la Vaissière, Ch; Del Buono, L; Hamon, O; John, M J J; Leruste, Ph; Ocariz, J; Pivk, M; Roos, L; Stark, J; T'Jampens, S; Therin, G; Manfredi, P F; Re, V; Behera, P K; Gladney, L; Guo, Q H; Panetta, J; Anulli, F; Biasini, M; Peruzzi, I M; Pioppi, M; Angelini, C; Batignani, G; Bettarini, S; Bondioli, M; Bucci, F; Calderini, G; Carpinelli, M; Del Gamba, V; Forti, F; Giorgi, M A; Lusiani, A; Marchiori, G; Martinez-Vidal, F; Morganti, M; Neri, N; Paoloni, E; Rama, M; Rizzo, G; Sandrelli, F; Walsh, J; Haire, M; Judd, D; Paick, K; Wagoner, D E; Danielson, N; Elmer, P; Lu, C; Miftakov, V; Olsen, J; Smith, A J S; Tanaka, H A; Varnes, E W; Bellini, F; Cavoto, G; Faccini, R; Ferrarotto, F; Ferroni, F; Gaspero, M; Mazzoni, M A; Morganti, S; Pierini, M; Piredda, G; SafaiTehrani, F; Voena, C; Christ, S; Wagner, G; Waldi, R; Adye, T; De Groot, N; Franek, B; Geddes, N I; Gopal, G P; Olaiya, E O; Xella, S M; Aleksan, R; Emery, S; Gaidot, A; Ganzhur, S F; Giraud, P-F; Hamel de Monchenault, G; Kozanecki, W; Langer, M; Legendre, M; London, G W; Mayer, B; Schott, G; Vasseur, G; Yeche, Ch; Zito, M; Purohit, M V; Weidemann, A W; Yumiceva, F X; Aston, D; Bartoldus, R; Berger, N; Boyarski, A M; Buchmueller, O L; Convery, M R; Cristinziani, M; Dong, D; Dorfan, J; Dujmic, D; Dunwoodie, W; Elsen, E E; Field, R C; Glanzman, T; Gowdy, S J; Grauges-Pous, E; Hadig, T; Halyo, V; Hryn'ova, T; Innes, W R; Jessop, C P; Kelsey, M H; Kim, P; Kocian, M L; Langenegger, U; Leith, D W G S; Libby, J; Luitz, S; Luth, V; Lynch, H L; Marsiske, H; Messner, R; Muller, D R; O'Grady, C P; Ozcan, V E; Perazzo, A; Perl, M; Petrak, S; Ratcliff, B N; Roodman, A; Salnikov, A A; Schindler, R H; Schwiening, J; Simi, G; Snyder, A; Soha, A; Stelzer, J; Su, D; Sullivan, M K; Va'vra, J; Wagner, S R; Weaver, M; Weinstein, A J R; Wisniewski, W J; Wright, D H; Young, C C; Burchat, P R; Edwards, A J; Meyer, T I; Petersen, B A; Roat, C; Ahmed, M; Ahmed, S; Alam, M S; Ernst, J A; Saeed, M A; Saleem, M; Wappler, F R; Bugg, W; Krishnamurthy, M; Spanier, S M; Eckmann, R; Kim, H; Ritchie, J L; Schwitters, R F; Izen, J M; Kitayama, I; Lou, X C; Ye, S; Bianchi, F; Bona, M; Gallo, F; Gamba, D; Borean, C; Bosisio, L; Della Ricca, G; Dittongo, S; Grancagnolo, S; Lanceri, L; Poropat, P; Vitale, L; Vuagnin, G; Panvini, R S; Banerjee, Sw; Brown, C M; Fortin, D; Jackson, P D; Kowalewski, R; Roney, J M; Band, H R; Dasu, S; Datta, M; Eichenbaum, A M; Johnson, J R; Kutter, P E; Li, H; Liu, R; Di Lodovico, F; Mihalyi, A; Mohapatra, A K; Pan, Y; Prepost, R; Sekula, S J; von Wimmersperg-Toeller, J H; Wu, J; Wu, S L; Yu, Z; Neal, H

2004-06-25

We present a measurement of time-dependent CP-violating asymmetries in decays of neutral B mesons to the final states D(*-/+)pi(+/-), using approximately 82x10(6) BBmacr; events recorded by the BABAR experiment at the PEP-II e(+)e(-) storage ring. Events containing these decays are selected with a partial reconstruction technique, in which only the high-momentum pi(+/-) from the B decay and the low-momentum pi(-/+) from the D(*-/+) decay are used. We measure the amplitude of the asymmetry to be -0.063+/-0.024(stat)+/-0.014(syst) and compute bounds on |sin((2beta+gamma)|.

Measurement of branching fractions and rate asymmetries in the rare decays B→K (*)l⁺l⁻

DOE PAGES

Lees, J. P.; Poireau, V.; Tisserand, V.; ...

2012-08-24

In a sample of 471×10⁶ BB¯¯¯ events collected with the BABAR detector at the PEP-II e⁺e⁻ collider we study the rare decays B→K (*)l⁺l⁻, where l⁺l⁻ is either e⁺e⁻ or μ⁺μ⁻. We report results on partial branching fractions and isospin asymmetries in seven bins of dilepton mass-squared. We further present CP and lepton-flavor asymmetries for dilepton masses below and above the J/ψ resonance. We find no evidence for CP or lepton-flavor violation. The partial branching fractions and isospin asymmetries are consistent with the Standard Model predictions and with results from other experiments.

Dalitz plot analyses of J / ψ → π + π - π 0 , J / ψ → K + K - π 0 , and J / ψ → K s 0 K ± π ∓ produced via e + e - annihilation with initial-state radiation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lees, J. P.; Poireau, V.; Tisserand, V.

We study the processes e + e - → γ ISR J / ψ , where J / ψ → π + π - π 0 , J / ψ → K + K - π 0 , and J / ψ → Kmore » $$0\\atop{S}$$ K ± π ∓ using a data sample of 519 fb - 1 recorded with the BABAR detector operating at the SLAC PEP-II asymmetric-energy e + e - collider at center-of-mass energies at and near the Υ ( n S ) ( n = 2 , 3 , 4 ) resonances.« less

Measurement of inclusive production of charmonium states in B meson decays

DOE Office of Scientific and Technical Information (OSTI.GOV)

Barrera, Barbara

The authors reconstruct the charmonium mesons J/{psi}, {psi}(2S) and {chi}{sub c} using a sample of 8.46 x 10{sup 6} B{bar B} events collected by the BABAR detector operating at e{sup +}e{sup -} center of mass energies near the {Lambda}(4S) resonance. by measuring rates relative to the branching fraction of the J/{psi}, they obtain preliminary inclusive B branching fractions of (0.25 {+-} 0.02 {+-} 0.02)% to the {psi}(2S) and (0.39 {+-} 0.04 {+-} 0.04)% to the {chi}{sub c1}, and set a 90% confidence level limit of 0.24% on decays through the {chi}{sub c2}.

A global gridded dataset of daily precipitation going back to 1950, ideal for analysing precipitation extremes

NASA Astrophysics Data System (ADS)

Contractor, S.; Donat, M.; Alexander, L. V.

2017-12-01

Reliable observations of precipitation are necessary to determine past changes in precipitation and validate models, allowing for reliable future projections. Existing gauge based gridded datasets of daily precipitation and satellite based observations contain artefacts and have a short length of record, making them unsuitable to analyse precipitation extremes. The largest limiting factor for the gauge based datasets is a dense and reliable station network. Currently, there are two major data archives of global in situ daily rainfall data, first is Global Historical Station Network (GHCN-Daily) hosted by National Oceanic and Atmospheric Administration (NOAA) and the other by Global Precipitation Climatology Centre (GPCC) part of the Deutsche Wetterdienst (DWD). We combine the two data archives and use automated quality control techniques to create a reliable long term network of raw station data, which we then interpolate using block kriging to create a global gridded dataset of daily precipitation going back to 1950. We compare our interpolated dataset with existing global gridded data of daily precipitation: NOAA Climate Prediction Centre (CPC) Global V1.0 and GPCC Full Data Daily Version 1.0, as well as various regional datasets. We find that our raw station density is much higher than other datasets. To avoid artefacts due to station network variability, we provide multiple versions of our dataset based on various completeness criteria, as well as provide the standard deviation, kriging error and number of stations for each grid cell and timestep to encourage responsible use of our dataset. Despite our efforts to increase the raw data density, the in situ station network remains sparse in India after the 1960s and in Africa throughout the timespan of the dataset. Our dataset would allow for more reliable global analyses of rainfall including its extremes and pave the way for better global precipitation observations with lower and more transparent uncertainties.

Adaptive Swarm Balancing Algorithms for rare-event prediction in imbalanced healthcare data

PubMed Central

Wong, Raymond K.; Mohammed, Sabah; Fiaidhi, Jinan; Sung, Yunsick

2017-01-01

Clinical data analysis and forecasting have made substantial contributions to disease control, prevention and detection. However, such data usually suffer from highly imbalanced samples in class distributions. In this paper, we aim to formulate effective methods to rebalance binary imbalanced dataset, where the positive samples take up only the minority. We investigate two different meta-heuristic algorithms, particle swarm optimization and bat algorithm, and apply them to empower the effects of synthetic minority over-sampling technique (SMOTE) for pre-processing the datasets. One approach is to process the full dataset as a whole. The other is to split up the dataset and adaptively process it one segment at a time. The experimental results reported in this paper reveal that the performance improvements obtained by the former methods are not scalable to larger data scales. The latter methods, which we call Adaptive Swarm Balancing Algorithms, lead to significant efficiency and effectiveness improvements on large datasets while the first method is invalid. We also find it more consistent with the practice of the typical large imbalanced medical datasets. We further use the meta-heuristic algorithms to optimize two key parameters of SMOTE. The proposed methods lead to more credible performances of the classifier, and shortening the run time compared to brute-force method. PMID:28753613

Comprehensive curation and analysis of global interaction networks in Saccharomyces cerevisiae

PubMed Central

Reguly, Teresa; Breitkreutz, Ashton; Boucher, Lorrie; Breitkreutz, Bobby-Joe; Hon, Gary C; Myers, Chad L; Parsons, Ainslie; Friesen, Helena; Oughtred, Rose; Tong, Amy; Stark, Chris; Ho, Yuen; Botstein, David; Andrews, Brenda; Boone, Charles; Troyanskya, Olga G; Ideker, Trey; Dolinski, Kara; Batada, Nizar N; Tyers, Mike

2006-01-01

Background The study of complex biological networks and prediction of gene function has been enabled by high-throughput (HTP) methods for detection of genetic and protein interactions. Sparse coverage in HTP datasets may, however, distort network properties and confound predictions. Although a vast number of well substantiated interactions are recorded in the scientific literature, these data have not yet been distilled into networks that enable system-level inference. Results We describe here a comprehensive database of genetic and protein interactions, and associated experimental evidence, for the budding yeast Saccharomyces cerevisiae, as manually curated from over 31,793 abstracts and online publications. This literature-curated (LC) dataset contains 33,311 interactions, on the order of all extant HTP datasets combined. Surprisingly, HTP protein-interaction datasets currently achieve only around 14% coverage of the interactions in the literature. The LC network nevertheless shares attributes with HTP networks, including scale-free connectivity and correlations between interactions, abundance, localization, and expression. We find that essential genes or proteins are enriched for interactions with other essential genes or proteins, suggesting that the global network may be functionally unified. This interconnectivity is supported by a substantial overlap of protein and genetic interactions in the LC dataset. We show that the LC dataset considerably improves the predictive power of network-analysis approaches. The full LC dataset is available at the BioGRID () and SGD () databases. Conclusion Comprehensive datasets of biological interactions derived from the primary literature provide critical benchmarks for HTP methods, augment functional prediction, and reveal system-level attributes of biological networks. PMID:16762047

Enrichment of Data Publications in Earth Sciences - Data Reports as a Missing Link

NASA Astrophysics Data System (ADS)

Elger, Kirsten; Bertelmann, Roland; Haberland, Christian; Evans, Peter L.

2015-04-01

During the past decade, the relevance of research data stewardship has been rising significantly. Preservation and publication of scientific data for long-term use, including the storage in adequate repositories has been identified as a key issue by the scientific community as well as by bodies like research agencies. Essential for any kind of re-use is a proper description of the datasets. As a result of the increasing interest, data repositories have been developed and the included research data is accompanied with at least a minimum set of metadata. This metadata is useful for data discovery and a first insight to the content of a dataset. But often data re-use needs more and extended information. Many datasets are accompanied by a small 'readme file' with basic information on the data structure, or other accompanying documents. A source of additional information could be an article published in one of the newly emerging data journals (e.g. Copernicus's ESSD Earth System Science Data or Nature's Scientific Data). Obviously there is an information gap between a 'readme file', that is only accessible after data download (which often leads to less usage of published datasets than if the information was available beforehand) and the much larger effort to prepare an article for a peer-reviewed data journal. For many years, GFZ German Research Centre for Geosciences publishes 'Scientific Technical Reports (STR)' as a report series which is electronically persistently available and citable with assigned DOIs. This series was opened for the description of parallel published datasets as 'STR Data'. These are internally reviewed and offer a flexible publication format describing published data in depth, suitable for different datasets ranging from long-term monitoring time series of observatories to field data, to (meta-)databases, and software publications. STR Data offer a full and consistent overview and description to all relevant parameters of a linked published dataset. These reports are readable and citable on their own, but are, of course, closely connected to the respective datasets. Therefore, they give full insight into the framework of the data before data download. This is especially relevant for large and often heterogeneous datasets, like e.g. controlled-source seismic data gathered with instruments of the 'Geophysical Instrument Pool Potsdam GIPP'. Here, details of the instrumentation, data organization, data format, accuracy, geographical coordinates, timing and data completeness, etc. need to be documented. STR Data are also attractive for the publication of historic datasets, e.g. 30-40 years old seismic experiments. It is also possible for one STR Data to describe several datasets, e.g. from multiple diverse instruments types, or distinct regions of interest. The publication of DOI-assigned data reports is a helpful tool to fill the gap between basic metadata and restricted 'readme' information on the one hand and preparing extended journal articles on the other hand. They open the way for informed re-use and, with their comprehensive data description, may act as 'appetizer' for the re-use of published datasets.

Statistical Compression for Climate Model Output

NASA Astrophysics Data System (ADS)

Hammerling, D.; Guinness, J.; Soh, Y. J.

2017-12-01

Numerical climate model simulations run at high spatial and temporal resolutions generate massive quantities of data. As our computing capabilities continue to increase, storing all of the data is not sustainable, and thus is it important to develop methods for representing the full datasets by smaller compressed versions. We propose a statistical compression and decompression algorithm based on storing a set of summary statistics as well as a statistical model describing the conditional distribution of the full dataset given the summary statistics. We decompress the data by computing conditional expectations and conditional simulations from the model given the summary statistics. Conditional expectations represent our best estimate of the original data but are subject to oversmoothing in space and time. Conditional simulations introduce realistic small-scale noise so that the decompressed fields are neither too smooth nor too rough compared with the original data. Considerable attention is paid to accurately modeling the original dataset-one year of daily mean temperature data-particularly with regard to the inherent spatial nonstationarity in global fields, and to determining the statistics to be stored, so that the variation in the original data can be closely captured, while allowing for fast decompression and conditional emulation on modest computers.

Search for popcorn mesons in events with two charmed baryons

NASA Astrophysics Data System (ADS)

Hartfiel, Brandon

The physics of this dissertation is divided into two parts. The first part measures the Λc → pi kp continuum momentum spectrum at a center of mass energy of 10.54 GeV/c, which is just below the Υ(4s) resonance. The data sample consists of 15,400 Λc baryons from 9.46 fb-1 of integrated luminosity collected with the BaBar detector at the PEP-II asymmetric B factory at the Stanford Linear Accelerator Center. With more than 13 times more data than the best previous measurement, we are able to exclude some of the simpler, one parameter fragmentation functions. In the second part, we add the Λc → K0p mode, and look for events with a Λc+ and a Λ c- in order to look for "popcorn" mesons formed between the baryon and antibaryon. We add on-resonance data, with a kinematic cut to eliminate background from B decays, as well as BaBar run 3 and 4 data to increase the total data size to 219.70 fb-1. We find 619 events after background subtraction. After a subtraction of 1.06+/-.09 charged pions coming from decays of known resonances to Λc + npi, we are left with 2.63+/-.21 additional charged pious in each of these events. This is significantly higher than the .5 popcorn mesons per bayon pair used in the current tuning of Pythia 6.2, the most widely used Monte Carlo generator. The extra mesons we find appear to be the first direct evidence of popcorn mesons, although some of them could be arising from hypothetical unresolved, unobserved charmed baryon resonances contributing decay mesons to our data. To contribute a significant fraction, this hypothesis requires a large number of such broad unresolved states and seems unlikely, but can not be completely excluded.

Pole Figure Explorer v. 1.8

DOE Office of Scientific and Technical Information (OSTI.GOV)

Van Benthem, Mark H.

2016-05-04

This software is employed for 3D visualization of X-ray diffraction (XRD) data with functionality for slicing, reorienting, isolating and plotting of 2D color contour maps and 3D renderings of large datasets. The program makes use of the multidimensionality of textured XRD data where diffracted intensity is not constant over a given set of angular positions (as dictated by the three defined dimensional angles of phi, chi, and two-theta). Datasets are rendered in 3D with intensity as a scaler which is represented as a rainbow color scale. A GUI interface and scrolling tools along with interactive function via the mouse allowmore » for fast manipulation of these large datasets so as to perform detailed analysis of diffraction results with full dimensionality of the diffraction space.« less

An automated curation procedure for addressing chemical errors and inconsistencies in public datasets used in QSAR modelling.

PubMed

Mansouri, K; Grulke, C M; Richard, A M; Judson, R S; Williams, A J

2016-11-01

The increasing availability of large collections of chemical structures and associated experimental data provides an opportunity to build robust QSAR models for applications in different fields. One common concern is the quality of both the chemical structure information and associated experimental data. Here we describe the development of an automated KNIME workflow to curate and correct errors in the structure and identity of chemicals using the publicly available PHYSPROP physicochemical properties and environmental fate datasets. The workflow first assembles structure-identity pairs using up to four provided chemical identifiers, including chemical name, CASRNs, SMILES, and MolBlock. Problems detected included errors and mismatches in chemical structure formats, identifiers and various structure validation issues, including hypervalency and stereochemistry descriptions. Subsequently, a machine learning procedure was applied to evaluate the impact of this curation process. The performance of QSAR models built on only the highest-quality subset of the original dataset was compared with the larger curated and corrected dataset. The latter showed statistically improved predictive performance. The final workflow was used to curate the full list of PHYSPROP datasets, and is being made publicly available for further usage and integration by the scientific community.

Measurements of Time-Dependent CP-Asymmetry Parameters in B Meson Decays to η' K 0 and of Branching Fractions of SU(3) Related Modes with BaBar Experiment at SLAC

DOE Office of Scientific and Technical Information (OSTI.GOV)

Biassoni, Pietro

2009-01-01

In this thesis work we have measured the following upper limits at 90% of confidence level, for B meson decays (in units of 10 -6), using a statistics of 465.0 x 10 6 Bmore » $$\\bar{B}$$ pairs: β(B 0 → ηK 0) < 1.6 β(B 0 → ηη) < 1.4 β(B 0 → η'η') < 2.1 β(B 0 → ηΦ) < 0.52 β(B 0 → ηω) < 1.6 β(B 0 → η'Φ) < 1.2 β(B 0 → η'ω) < 1.7 We have no observation of any decay mode, statistical significance for our measurements is in the range 1.3-3.5 standard deviation. We have a 3.5σ evidence for B → ηω and a 3.1 σ evidence for B → η'ω. The absence of observation of the B 0 → ηK 0 open an issue related to the large difference compared to the charged mode B + → ηK + branching fraction, which is measured to be 3.7 ± 0.4 ± 0.1 [118]. Our results represent substantial improvements of the previous ones [109, 110, 111] and are consistent with theoretical predictions. All these results were presented at Flavor Physics and CP Violation (FPCP) 2008 Conference, that took place in Taipei, Taiwan. They will be soon included into a paper to be submitted to Physical Review D. For time-dependent analysis, we have reconstructed 1820 ± 48 flavor-tagged B 0 → η'K 0 events, using the final BABAR statistic of 467.4 x 10 6 B$$\\bar{B}$$ pairs. We use these events to measure the time-dependent asymmetry parameters S and C. We find S = 0.59 ± 0.08 ± 0.02, and C = -0.06 ± 0.06 ± 0.02. A non-zero value of C would represent a directly CP non-conserving component in B 0 → η'K 0, while S would be equal to sin2β measured in B 0 → J/ΨK s 0 [108], a mixing-decay interference effect, provided the decay is dominated by amplitudes of a single weak phase. The new measured value of S can be considered in agreement with the expectations of the 'Standard Model', inside the experimental and theoretical uncertainties. Inconsistency of our result for S with CP conservation (S = 0) has a significance of 7.1 standard deviations (statistical and systematics included). Our result for the direct-CP violation parameter C is 0.9 standard deviations from zero (statistical and systematics included). Our results are in agreement with the previous ones [18]. Despite the statistics is only 20% larger than the one used in previous measurement, we improved of 20% the error on S and of 14% the error on C. This error is the smaller ever achieved, by both BABAR and Belle, in Time-Dependent CP Violation Parameters measurement is a b → s transition.« less

SU-D-17A-02: Four-Dimensional CBCT Using Conventional CBCT Dataset and Iterative Subtraction Algorithm of a Lung Patient

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hu, E; Lasio, G; Yi, B

2014-06-01

Purpose: The Iterative Subtraction Algorithm (ISA) method generates retrospectively a pre-selected motion phase cone-beam CT image from the full motion cone-beam CT acquired at standard rotation speed. This work evaluates ISA method with real lung patient data. Methods: The goal of the ISA algorithm is to extract motion and no- motion components form the full reconstruction CBCT. The workflow consists of subtracting from the full CBCT all of the undesired motion phases and obtain a motion de-blurred single-phase CBCT image, followed by iteration of this subtraction process. ISA is realized as follows: 1) The projections are sorted to various phases,more » and from all phases, a full reconstruction is performed to generate an image CTM. 2) Generate forward projections of CTM at the desired phase projection angles, the subtraction of projection and the forward projection will reconstruct a CTSub1, which diminishes the desired phase component. 3) By adding back the CTSub1 to CTm, no motion CBCT, CTS1, can be computed. 4) CTS1 still contains residual motion component. 5) This residual motion component can be further reduced by iteration.The ISA 4DCBCT technique was implemented using Varian Trilogy accelerator OBI system. To evaluate the method, a lung patient CBCT dataset was used. The reconstruction algorithm is FDK. Results: The single phase CBCT reconstruction generated via ISA successfully isolates the desired motion phase from the full motion CBCT, effectively reducing motion blur. It also shows improved image quality, with reduced streak artifacts with respect to the reconstructions from unprocessed phase-sorted projections only. Conclusion: A CBCT motion de-blurring algorithm, ISA, has been developed and evaluated with lung patient data. The algorithm allows improved visualization of a single phase motion extracted from a standard CBCT dataset. This study has been supported by National Institute of Health through R01CA133539.« less

Historic AVHRR Processing in the Eumetsat Climate Monitoring Satellite Application Facility (cmsaf) (Invited)

NASA Astrophysics Data System (ADS)

Karlsson, K.

2010-12-01

The EUMETSAT CMSAF project (www.cmsaf.eu) compiles climatological datasets from various satellite sources with emphasis on the use of EUMETSAT-operated satellites. However, since climate monitoring primarily has a global scope, also datasets merging data from various satellites and satellite operators are prepared. One such dataset is the CMSAF historic GAC (Global Area Coverage) dataset which is based on AVHRR data from the full historic series of NOAA-satellites and the European METOP satellite in mid-morning orbit launched in October 2006. The CMSAF GAC dataset consists of three groups of products: Macroscopical cloud products (cloud amount, cloud type and cloud top), cloud physical products (cloud phase, cloud optical thickness and cloud liquid water path) and surface radiation products (including surface albedo). Results will be presented and discussed for all product groups, including some preliminary inter-comparisons with other datasets (e.g., PATMOS-X, MODIS and CloudSat/CALIPSO datasets). A background will also be given describing the basic methodology behind the derivation of all products. This will include a short historical review of AVHRR cloud processing and resulting AVHRR applications at SMHI. Historic GAC processing is one of five pilot projects selected by the SCOPE-CM (Sustained Co-Ordinated Processing of Environmental Satellite data for Climate Monitoring) project organised by the WMO Space programme. The pilot project is carried out jointly between CMSAF and NOAA with the purpose of finding an optimal GAC processing approach. The initial activity is to inter-compare results of the CMSAF GAC dataset and the NOAA PATMOS-X dataset for the case when both datasets have been derived using the same inter-calibrated AVHRR radiance dataset. The aim is to get further knowledge of e.g. most useful multispectral methods and the impact of ancillary datasets (for example from meteorological reanalysis datasets from NCEP and ECMWF). The CMSAF project is currently defining plans for another five years (2012-2017) of operations and development. New GAC reprocessing efforts are planned and new methodologies will be tested. Central questions here will be how to increase the quantitative use of the products through improving error and uncertainty estimates and how to compile the information in a way to allow meaningful and efficient ways of using the data for e.g. validation of climate model information.

The Physics of the B Factories

NASA Astrophysics Data System (ADS)

Bevan, A. J.; Golob, B.; Mannel, Th.; Prell, S.; Yabsley, B. D.; Aihara, H.; Anulli, F.; Arnaud, N.; Aushev, T.; Beneke, M.; Beringer, J.; Bianchi, F.; Bigi, I. I.; Bona, M.; Brambilla, N.; Brodzicka, J.; Chang, P.; Charles, M. J.; Cheng, C. H.; Cheng, H.-Y.; Chistov, R.; Colangelo, P.; Coleman, J. P.; Drutskoy, A.; Druzhinin, V. P.; Eidelman, S.; Eigen, G.; Eisner, A. M.; Faccini, R.; Flood, K. T.; Gambino, P.; Gaz, A.; Gradl, W.; Hayashii, H.; Higuchi, T.; Hulsbergen, W. D.; Hurth, T.; Iijima, T.; Itoh, R.; Jackson, P. D.; Kass, R.; Kolomensky, Yu. G.; Kou, E.; Križan, P.; Kronfeld, A.; Kumano, S.; Kwon, Y. J.; Latham, T. E.; Leith, D. W. G. S.; Lüth, V.; Martinez-Vidal, F.; Meadows, B. T.; Mussa, R.; Nakao, M.; Nishida, S.; Ocariz, J.; Olsen, S. L.; Pakhlov, P.; Pakhlova, G.; Palano, A.; Pich, A.; Playfer, S.; Poluektov, A.; Porter, F. C.; Robertson, S. H.; Roney, J. M.; Roodman, A.; Sakai, Y.; Schwanda, C.; Schwartz, A. J.; Seidl, R.; Sekula, S. J.; Steinhauser, M.; Sumisawa, K.; Swanson, E. S.; Tackmann, F.; Trabelsi, K.; Uehara, S.; Uno, S.; van de Water, R.; Vasseur, G.; Verkerke, W.; Waldi, R.; Wang, M. Z.; Wilson, F. F.; Zupan, J.; Zupanc, A.; Adachi, I.; Albert, J.; Banerjee, Sw.; Bellis, M.; Ben-Haim, E.; Biassoni, P.; Cahn, R. N.; Cartaro, C.; Chauveau, J.; Chen, C.; Chiang, C. C.; Cowan, R.; Dalseno, J.; Davier, M.; Davies, C.; Dingfelder, J. C.; Echenard, B.; Epifanov, D.; Fulsom, B. G.; Gabareen, A. M.; Gary, J. W.; Godang, R.; Graham, M. T.; Hafner, A.; Hamilton, B.; Hartmann, T.; Hayasaka, K.; Hearty, C.; Iwasaki, Y.; Khodjamirian, A.; Kusaka, A.; Kuzmin, A.; Lafferty, G. D.; Lazzaro, A.; Li, J.; Lindemann, D.; Long, O.; Lusiani, A.; Marchiori, G.; Martinelli, M.; Miyabayashi, K.; Mizuk, R.; Mohanty, G. B.; Muller, D. R.; Nakazawa, H.; Ongmongkolkul, P.; Pacetti, S.; Palombo, F.; Pedlar, T. K.; Piilonen, L. E.; Pilloni, A.; Poireau, V.; Prothmann, K.; Pulliam, T.; Rama, M.; Ratcliff, B. N.; Roudeau, P.; Schrenk, S.; Schroeder, T.; Schubert, K. R.; Shen, C. P.; Shwartz, B.; Soffer, A.; Solodov, E. P.; Somov, A.; Starič, M.; Stracka, S.; Telnov, A. V.; Todyshev, K. Yu.; Tsuboyama, T.; Uglov, T.; Vinokurova, A.; Walsh, J. J.; Watanabe, Y.; Won, E.; Wormser, G.; Wright, D. H.; Ye, S.; Zhang, C. C.; Abachi, S.; Abashian, A.; Abe, K.; Abe, N.; Abe, R.; Abe, T.; Abrams, G. S.; Adam, I.; Adamczyk, K.; Adametz, A.; Adye, T.; Agarwal, A.; Ahmed, H.; Ahmed, M.; Ahmed, S.; Ahn, B. S.; Ahn, H. S.; Aitchison, I. J. R.; Akai, K.; Akar, S.; Akatsu, M.; Akemoto, M.; Akhmetshin, R.; Akre, R.; Alam, M. S.; Albert, J. N.; Aleksan, R.; Alexander, J. P.; Alimonti, G.; Allen, M. T.; Allison, J.; Allmendinger, T.; Alsmiller, J. R. G.; Altenburg, D.; Alwyn, K. E.; An, Q.; Anderson, J.; Andreassen, R.; Andreotti, D.; Andreotti, M.; Andress, J. C.; Angelini, C.; Anipko, D.; Anjomshoaa, A.; Anthony, P. L.; Antillon, E. A.; Antonioli, E.; Aoki, K.; Arguin, J. F.; Arinstein, K.; Arisaka, K.; Asai, K.; Asai, M.; Asano, Y.; Asgeirsson, D. J.; Asner, D. M.; Aso, T.; Aspinwall, M. L.; Aston, D.; Atmacan, H.; Aubert, B.; Aulchenko, V.; Ayad, R.; Azemoon, T.; Aziz, T.; Azzolini, V.; Azzopardi, D. E.; Baak, M. A.; Back, J. J.; Bagnasco, S.; Bahinipati, S.; Bailey, D. S.; Bailey, S.; Bailly, P.; van Bakel, N.; Bakich, A. M.; Bala, A.; Balagura, V.; Baldini-Ferroli, R.; Ban, Y.; Banas, E.; Band, H. R.; Banerjee, S.; Baracchini, E.; Barate, R.; Barberio, E.; Barbero, M.; Bard, D. J.; Barillari, T.; Barlow, N. R.; Barlow, R. J.; Barrett, M.; Bartel, W.; Bartelt, J.; Bartoldus, R.; Batignani, G.; Battaglia, M.; Bauer, J. M.; Bay, A.; Beaulieu, M.; Bechtle, P.; Beck, T. W.; Becker, J.; Becla, J.; Bedny, I.; Behari, S.; Behera, P. K.; Behn, E.; Behr, L.; Beigbeder, C.; Beiline, D.; Bell, R.; Bellini, F.; Bellodi, G.; Belous, K.; Benayoun, M.; Benelli, G.; Benitez, J. F.; Benkebil, M.; Berger, N.; Bernabeu, J.; Bernard, D.; Bernet, R.; Bernlochner, F. U.; Berryhill, J. W.; Bertsche, K.; Besson, P.; Best, D. S.; Bettarini, S.; Bettoni, D.; Bhardwaj, V.; Bhimji, W.; Bhuyan, B.; Biagini, M. E.; Biasini, M.; van Bibber, K.; Biesiada, J.; Bingham, I.; Bionta, R. M.; Bischofberger, M.; Bitenc, U.; Bizjak, I.; Blanc, F.; Blaylock, G.; Blinov, V. E.; Bloom, E.; Bloom, P. C.; Blount, N. L.; Blouw, J.; Bly, M.; Blyth, S.; Boeheim, C. T.; Bomben, M.; Bondar, A.; Bondioli, M.; Bonneaud, G. R.; Bonvicini, G.; Booke, M.; Booth, J.; Borean, C.; Borgland, A. W.; Borsato, E.; Bosi, F.; Bosisio, L.; Botov, A. A.; Bougher, J.; Bouldin, K.; Bourgeois, P.; Boutigny, D.; Bowerman, D. A.; Boyarski, A. M.; Boyce, R. F.; Boyd, J. T.; Bozek, A.; Bozzi, C.; Bračko, M.; Brandenburg, G.; Brandt, T.; Brau, B.; Brau, J.; Breon, A. B.; Breton, D.; Brew, C.; Briand, H.; Bright-Thomas, P. G.; Brigljević, V.; Britton, D. I.; Brochard, F.; Broomer, B.; Brose, J.; Browder, T. E.; Brown, C. L.; Brown, C. M.; Brown, D. N.; Browne, M.; Bruinsma, M.; Brunet, S.; Bucci, F.; Buchanan, C.; Buchmueller, O. L.; Bünger, C.; Bugg, W.; Bukin, A. D.; Bula, R.; Bulten, H.; Burchat, P. R.; Burgess, W.; Burke, J. P.; Button-Shafer, J.; Buzykaev, A. R.; Buzzo, A.; Cai, Y.; Calabrese, R.; Calcaterra, A.; Calderini, G.; Camanzi, B.; Campagna, E.; Campagnari, C.; Capra, R.; Carassiti, V.; Carpinelli, M.; Carroll, M.; Casarosa, G.; Casey, B. C. K.; Cason, N. M.; Castelli, G.; Cavallo, N.; Cavoto, G.; Cecchi, A.; Cenci, R.; Cerizza, G.; Cervelli, A.; Ceseracciu, A.; Chai, X.; Chaisanguanthum, K. S.; Chang, M. C.; Chang, Y. H.; Chang, Y. W.; Chao, D. S.; Chao, M.; Chao, Y.; Charles, E.; Chavez, C. A.; Cheaib, R.; Chekelian, V.; Chen, A.; Chen, E.; Chen, G. P.; Chen, H. F.; Chen, J.-H.; Chen, J. C.; Chen, K. F.; Chen, P.; Chen, S.; Chen, W. T.; Chen, X.; Chen, X. R.; Chen, Y. Q.; Cheng, B.; Cheon, B. G.; Chevalier, N.; Chia, Y. M.; Chidzik, S.; Chilikin, K.; Chistiakova, M. V.; Cizeron, R.; Cho, I. S.; Cho, K.; Chobanova, V.; Choi, H. H. F.; Choi, K. S.; Choi, S. K.; Choi, Y.; Choi, Y. K.; Christ, S.; Chu, P. H.; Chun, S.; Chuvikov, A.; Cibinetto, G.; Cinabro, D.; Clark, A. R.; Clark, P. J.; Clarke, C. K.; Claus, R.; Claxton, B.; Clifton, Z. C.; Cochran, J.; Cohen-Tanugi, J.; Cohn, H.; Colberg, T.; Cole, S.; Colecchia, F.; Condurache, C.; Contri, R.; Convert, P.; Convery, M. R.; Cooke, P.; Copty, N.; Cormack, C. M.; Dal Corso, F.; Corwin, L. A.; Cossutti, F.; Cote, D.; Cotta Ramusino, A.; Cottingham, W. N.; Couderc, F.; Coupal, D. P.; Covarelli, R.; Cowan, G.; Craddock, W. W.; Crane, G.; Crawley, H. B.; Cremaldi, L.; Crescente, A.; Cristinziani, M.; Crnkovic, J.; Crosetti, G.; Cuhadar-Donszelmann, T.; Cunha, A.; Curry, S.; D'Orazio, A.; Dû, S.; Dahlinger, G.; Dahmes, B.; Dallapiccola, C.; Danielson, N.; Danilov, M.; Das, A.; Dash, M.; Dasu, S.; Datta, M.; Daudo, F.; Dauncey, P. D.; David, P.; Davis, C. L.; Day, C. T.; De Mori, F.; De Domenico, G.; De Groot, N.; De la Vaissière, C.; de la Vaissière, Ch.; de Lesquen, A.; De Nardo, G.; de Sangro, R.; De Silva, A.; DeBarger, S.; Decker, F. J.; del Amo Sanchez, P.; Del Buono, L.; Del Gamba, V.; del Re, D.; Della Ricca, G.; Denig, A. G.; Derkach, D.; Derrington, I. M.; DeStaebler, H.; Destree, J.; Devmal, S.; Dey, B.; Di Girolamo, B.; Marco, E. Di; Dickopp, M.; Dima, M. O.; Dittrich, S.; Dittongo, S.; Dixon, P.; Dneprovsky, L.; Dohou, F.; Doi, Y.; Doležal, Z.; Doll, D. A.; Donald, M.; Dong, L.; Dong, L. Y.; Dorfan, J.; Dorigo, A.; Dorsten, M. P.; Dowd, R.; Dowdell, J.; Drásal, Z.; Dragic, J.; Drummond, B. W.; Dubitzky, R. S.; Dubois-Felsmann, G. P.; Dubrovin, M. S.; Duh, Y. C.; Duh, Y. T.; Dujmic, D.; Dungel, W.; Dunwoodie, W.; Dutta, D.; Dvoretskii, A.; Dyce, N.; Ebert, M.; Eckhart, E. A.; Ecklund, S.; Eckmann, R.; Eckstein, P.; Edgar, C. L.; Edwards, A. J.; Egede, U.; Eichenbaum, A. M.; Elmer, P.; Emery, S.; Enari, Y.; Enomoto, R.; Erdos, E.; Erickson, R.; Ernst, J. A.; Erwin, R. J.; Escalier, M.; Eschenburg, V.; Eschrich, I.; Esen, S.; Esteve, L.; Evangelisti, F.; Everton, C. W.; Eyges, V.; Fabby, C.; Fabozzi, F.; Fahey, S.; Falbo, M.; Fan, S.; Fang, F.; Fanin, C.; Farbin, A.; Farhat, H.; Fast, J. E.; Feindt, M.; Fella, A.; Feltresi, E.; Ferber, T.; Fernholz, R. E.; Ferrag, S.; Ferrarotto, F.; Ferroni, F.; Field, R. C.; Filippi, A.; Finocchiaro, G.; Fioravanti, E.; Firmino da Costa, J.; Fischer, P.-A.; Fisher, A. S.; Fisher, P. H.; Flacco, C. J.; Flack, R. L.; Flaecher, H. U.; Flanagan, J.; Flanigan, J. M.; Ford, K. E.; Ford, W. T.; Forster, I. J.; Forti, A. C.; Forti, F.; Fortin, D.; Foster, B.; Foulkes, S. D.; Fouque, G.; Fox, J.; Franchini, P.; Franco Sevilla, M.; Franek, B.; Frank, E. D.; Fransham, K. B.; Fratina, S.; Fratini, K.; Frey, A.; Frey, R.; Friedl, M.; Fritsch, M.; Fry, J. R.; Fujii, H.; Fujikawa, M.; Fujita, Y.; Fujiyama, Y.; Fukunaga, C.; Fukushima, M.; Fullwood, J.; Funahashi, Y.; Funakoshi, Y.; Furano, F.; Furman, M.; Furukawa, K.; Futterschneider, H.; Gabathuler, E.; Gabriel, T. A.; Gabyshev, N.; Gaede, F.; Gagliardi, N.; Gaidot, A.; Gaillard, J.-M.; Gaillard, J. R.; Galagedera, S.; Galeazzi, F.; Gallo, F.; Gamba, D.; Gamet, R.; Gan, K. K.; Gandini, P.; Ganguly, S.; Ganzhur, S. F.; Gao, Y. Y.; Gaponenko, I.; Garmash, A.; Garra Tico, J.; Garzia, I.; Gaspero, M.; Gastaldi, F.; Gatto, C.; Gaur, V.; Geddes, N. I.; Geld, T. L.; Genat, J.-F.; George, K. A.; George, M.; George, S.; Georgette, Z.; Gershon, T. J.; Gill, M. S.; Gillard, R.; Gilman, J. D.; Giordano, F.; Giorgi, M. A.; Giraud, P.-F.; Gladney, L.; Glanzman, T.; Glattauer, R.; Go, A.; Goetzen, K.; Goh, Y. M.; Gokhroo, G.; Goldenzweig, P.; Golubev, V. B.; Gopal, G. P.; Gordon, A.; Gorišek, A.; Goriletsky, V. I.; Gorodeisky, R.; Gosset, L.; Gotow, K.; Gowdy, S. J.; Graffin, P.; Grancagnolo, S.; Grauges, E.; Graziani, G.; Green, M. G.; Greene, M. G.; Grenier, G. J.; Grenier, P.; Griessinger, K.; Grillo, A. A.; Grinyov, B. V.; Gritsan, A. V.; Grosdidier, G.; Grosse Perdekamp, M.; Grosso, P.; Grothe, M.; Groysman, Y.; Grünberg, O.; Guido, E.; Guler, H.; Gunawardane, N. J. W.; Guo, Q. H.; Guo, R. S.; Guo, Z. J.; Guttman, N.; Ha, H.; Ha, H. C.; Haas, T.; Haba, J.; Hachtel, J.; Hadavand, H. K.; Hadig, T.; Hagner, C.; Haire, M.; Haitani, F.; Haji, T.; Haller, G.; Halyo, V.; Hamano, K.; Hamasaki, H.; Hamel de Monchenault, G.; Hamilton, J.; Hamilton, R.; Hamon, O.; Han, B. Y.; Han, Y. L.; Hanada, H.; Hanagaki, K.; Handa, F.; Hanson, J. E.; Hanushevsky, A.; Hara, K.; Hara, T.; Harada, Y.; Harrison, P. F.; Harrison, T. J.; Harrop, B.; Hart, A. J.; Hart, P. A.; Hartfiel, B. L.; Harton, J. L.; Haruyama, T.; Hasan, A.; Hasegawa, Y.; Hast, C.; Hastings, N. C.; Hasuko, K.; Hauke, A.; Hawkes, C. M.; Hayashi, K.; Hazumi, M.; Hee, C.; Heenan, E. M.; Heffernan, D.; Held, T.; Henderson, R.; Henderson, S. W.; Hertzbach, S. S.; Hervé, S.; Heß, M.; Heusch, C. A.; Hicheur, A.; Higashi, Y.; Higasino, Y.; Higuchi, I.; Hikita, S.; Hill, E. J.; Himel, T.; Hinz, L.; Hirai, T.; Hirano, H.; Hirschauer, J. F.; Hitlin, D. G.; Hitomi, N.; Hodgkinson, M. C.; Höcker, A.; Hoi, C. T.; Hojo, T.; Hokuue, T.; Hollar, J. J.; Hong, T. M.; Honscheid, K.; Hooberman, B.; Hopkins, D. A.; Horii, Y.; Hoshi, Y.; Hoshina, K.; Hou, S.; Hou, W. S.; Hryn'ova, T.; Hsiung, Y. B.; Hsu, C. L.; Hsu, S. C.; Hu, H.; Hu, T.; Huang, H. C.; Huang, T. J.; Huang, Y. C.; Huard, Z.; Huffer, M. E.; Hufnagel, D.; Hung, T.; Hutchcroft, D. E.; Hyun, H. J.; Ichizawa, S.; Igaki, T.; Igarashi, A.; Igarashi, S.; Igarashi, Y.; Igonkina, O.; Ikado, K.; Ikeda, H.; Ikeda, H.; Ikeda, K.; Ilic, J.; Inami, K.; Innes, W. R.; Inoue, Y.; Ishikawa, A.; Ishino, H.; Itagaki, K.; Itami, S.; Itoh, K.; Ivanchenko, V. N.; Iverson, R.; Iwabuchi, M.; Iwai, G.; Iwai, M.; Iwaida, S.; Iwamoto, M.; Iwasaki, H.; Iwasaki, M.; Iwashita, T.; Izen, J. M.; Jackson, D. J.; Jackson, F.; Jackson, G.; Jackson, P. S.; Jacobsen, R. G.; Jacoby, C.; Jaegle, I.; Jain, V.; Jalocha, P.; Jang, H. K.; Jasper, H.; Jawahery, A.; Jayatilleke, S.; Jen, C. M.; Jensen, F.; Jessop, C. P.; Ji, X. B.; John, M. J. J.; Johnson, D. R.; Johnson, J. R.; Jolly, S.; Jones, M.; Joo, K. K.; Joshi, N.; Joshi, N. J.; Judd, D.; Julius, T.; Kadel, R. W.; Kadyk, J. A.; Kagan, H.; Kagan, R.; Kah, D. H.; Kaiser, S.; Kaji, H.; Kajiwara, S.; Kakuno, H.; Kameshima, T.; Kaminski, J.; Kamitani, T.; Kaneko, J.; Kang, J. H.; Kang, J. S.; Kani, T.; Kapusta, P.; Karbach, T. M.; Karolak, M.; Karyotakis, Y.; Kasami, K.; Katano, G.; Kataoka, S. U.; Katayama, N.; Kato, E.; Kato, Y.; Kawai, H.; Kawai, M.; Kawamura, N.; Kawasaki, T.; Kay, J.; Kay, M.; Kelly, M. P.; Kelsey, M. H.; Kent, N.; Kerth, L. T.; Khan, A.; Khan, H. R.; Kharakh, D.; Kibayashi, A.; Kichimi, H.; Kiesling, C.; Kikuchi, M.; Kikutani, E.; Kim, B. H.; Kim, C. H.; Kim, D. W.; Kim, H.; Kim, H. J.; Kim, H. O.; Kim, H. W.; Kim, J. B.; Kim, J. H.; Kim, K. T.; Kim, M. J.; Kim, P.; Kim, S. K.; Kim, S. M.; Kim, T. H.; Kim, Y. I.; Kim, Y. J.; King, G. J.; Kinoshita, K.; Kirk, A.; Kirkby, D.; Kitayama, I.; Klemetti, M.; Klose, V.; Klucar, J.; Knecht, N. S.; Knoepfel, K. J.; Knowles, D. J.; Ko, B. R.; Kobayashi, N.; Kobayashi, S.; Kobayashi, T.; Kobel, M. J.; Koblitz, S.; Koch, H.; Kocian, M. L.; Kodyš, P.; Koeneke, K.; Kofler, R.; Koike, S.; Koishi, S.; Koiso, H.; Kolb, J. A.; Kolya, S. D.; Kondo, Y.; Konishi, H.; Koppenburg, P.; Koptchev, V. B.; Kordich, T. M. B.; Korol, A. A.; Korotushenko, K.; Korpar, S.; Kouzes, R. T.; Kovalskyi, D.; Kowalewski, R.; Kozakai, Y.; Kozanecki, W.; Kral, J. F.; Krasnykh, A.; Krause, R.; Kravchenko, E. A.; Krebs, J.; Kreisel, A.; Kreps, M.; Krishnamurthy, M.; Kroeger, R.; Kroeger, W.; Krokovny, P.; Kronenbitter, B.; Kroseberg, J.; Kubo, T.; Kuhr, T.; Kukartsev, G.; Kulasiri, R.; Kulikov, A.; Kumar, R.; Kumar, S.; Kumita, T.; Kuniya, T.; Kunze, M.; Kuo, C. C.; Kuo, T.-L.; Kurashiro, H.; Kurihara, E.; Kurita, N.; Kuroki, Y.; Kurup, A.; Kutter, P. E.; Kuznetsova, N.; Kvasnička, P.; Kyberd, P.; Kyeong, S. H.; Lacker, H. M.; Lae, C. K.; Lamanna, E.; Lamsa, J.; Lanceri, L.; Landi, L.; Lang, M. I.; Lange, D. J.; Lange, J. S.; Langenegger, U.; Langer, M.; Lankford, A. J.; Lanni, F.; Laplace, S.; Latour, E.; Lau, Y. P.; Lavin, D. R.; Layter, J.; Lebbolo, H.; LeClerc, C.; Leddig, T.; Leder, G.; Le Diberder, F.; Lee, C. L.; Lee, J.; Lee, J. S.; Lee, M. C.; Lee, M. H.; Lee, M. J.; Lee, S.-J.; Lee, S. E.; Lee, S. H.; Lee, Y. J.; Lees, J. P.; Legendre, M.; Leitgab, M.; Leitner, R.; Leonardi, E.; Leonidopoulos, C.; Lepeltier, V.; Leruste, Ph.; Lesiak, T.; Levi, M. E.; Levy, S. 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C.; Simard, M.; Simi, G.; Simon, F.; Simonetto, F.; Sinev, N. B.; Singh, H.; Singh, J. B.; Sinha, R.; Sitt, S.; Skovpen, Yu. I.; Sloane, R. J.; Smerkol, P.; Smith, A. J. S.; Smith, D.; Smith, D. S.; Smith, J. G.; Smol, A.; Snoek, H. L.; Snyder, A.; So, R. Y.; Sobie, R. J.; Soderstrom, E.; Soha, A.; Sohn, Y. S.; Sokoloff, M. D.; Sokolov, A.; Solagna, P.; Solovieva, E.; Soni, N.; Sonnek, P.; Sordini, V.; Spaan, B.; Spanier, S. M.; Spencer, E.; Speziali, V.; Spitznagel, M.; Spradlin, P.; Staengle, H.; Stamen, R.; Stanek, M.; Stanič, S.; Stark, J.; Steder, M.; Steininger, H.; Steinke, M.; Stelzer, J.; Stevanato, E.; Stocchi, A.; Stock, R.; Stoeck, H.; Stoker, D. P.; Stroili, R.; Strom, D.; Strother, P.; Strube, J.; Stugu, B.; Stypula, J.; Su, D.; Suda, R.; Sugahara, R.; Sugi, A.; Sugimura, T.; Sugiyama, A.; Suitoh, S.; Sullivan, M. K.; Sumihama, M.; Sumiyoshi, T.; Summers, D. J.; Sun, L.; Sun, S.; Sundermann, J. E.; Sung, H. F.; Susaki, Y.; Sutcliffe, P.; Suzuki, A.; Suzuki, J.; Suzuki, J. I.; Suzuki, K.; Suzuki, S.; Suzuki, S. Y.; Swain, J. E.; Swain, S. K.; T'Jampens, S.; Tabata, M.; Tackmann, K.; Tajima, H.; Tajima, O.; Takahashi, K.; Takahashi, S.; Takahashi, T.; Takasaki, F.; Takayama, T.; Takita, M.; Tamai, K.; Tamponi, U.; Tamura, N.; Tan, N.; Tan, P.; Tanabe, K.; Tanabe, T.; Tanaka, H. A.; Tanaka, J.; Tanaka, M.; Tanaka, S.; Tanaka, Y.; Tanida, K.; Taniguchi, N.; Taras, P.; Tasneem, N.; Tatishvili, G.; Tatomi, T.; Tawada, M.; Taylor, F.; Taylor, G. N.; Taylor, G. P.; Telnov, V. I.; Teodorescu, L.; Ter-Antonyan, R.; Teramoto, Y.; Teytelman, D.; Thérin, G.; Thiebaux, Ch.; Thiessen, D.; Thomas, E. W.; Thompson, J. M.; Thorne, F.; Tian, X. C.; Tibbetts, M.; Tikhomirov, I.; Tinslay, J. S.; Tiozzo, G.; Tisserand, V.; Tocut, V.; Toki, W. H.; Tomassini, E. W.; Tomoto, M.; Tomura, T.; Torassa, E.; Torrence, E.; Tosi, S.; Touramanis, C.; Toussaint, J. C.; Tovey, S. N.; Trapani, P. 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M.; Zhulanov, V.; Ziegler, T.; Ziegler, V.; Zioulas, G.; Zisman, M.; Zito, M.; Zürcher, D.; Zwahlen, N.; Zyukova, O.; Živko, T.; Žontar, D.

2014-11-01

This work is on the Physics of the B Factories. Part A of this book contains a brief description of the SLAC and KEK B Factories as well as their detectors, BaBar and Belle, and data taking related issues. Part B discusses tools and methods used by the experiments in order to obtain results. The results themselves can be found in Part C. Please note that version 3 on the archive is the auxiliary version of the Physics of the B Factories book. This uses the notation alpha, beta, gamma for the angles of the Unitarity Triangle. The nominal version uses the notation phi_1, phi_2 and phi_3. Please cite this work as Eur. Phys. J. C74 (2014) 3026.

Recent results on rare B decays with BaBar

NASA Astrophysics Data System (ADS)

Margoni, Martino; BaBar Collaboration

2017-04-01

Flavor Changing Neutral Current transitions b → sl+l- and b → sγ provide an excellent laboratory for the search for physics beyond the Standard Model. Standard Model tests are performed through measurements of the lepton forward-backward asymmetry AFB and the longitudinal K* polarization FL in the decay B →K*l+l-, and the search for the rare decay B+ →K+τ+τ-. From the study of the Kπ+π- system in B radiative-penguin decays, the time-dependent CP asymmetry in the decay B0 →KS0 π+π- γ is measured, together with the branching fractions of B+ →K+π-π+ γ and B0 →K0π-π+ γ.

Leptoquarks in Flavour Physics

NASA Astrophysics Data System (ADS)

Müller, Dario

2018-05-01

While the LHC has not directly observed any new particle so far, experimental results from LHCb, BELLE and BABAR point towards the violation of lepton flavour universality in b ⟶ sℓ+ and b ⟶ c-ℓν. In this context, also the discrepancy in the anomalous magnetic moment of the muon can be interpreted as a sign of lepton flavour universality violation. Here we discuss how these hints for new physics can also be explained by introducing leptoquarks as an extension of the Standard Model. Indeed, leptoquarks are good candidates to explain the anomaly in the anomalous magnetic moment of the muon because of an mg/mμ enhanced contribution giving correlated effects in Z boson decays which is particularly interesting in the light of future precision experiments.

Standard model predictions for B→Kℓ(+)ℓ- with form factors from lattice QCD.

PubMed

Bouchard, Chris; Lepage, G Peter; Monahan, Christopher; Na, Heechang; Shigemitsu, Junko

2013-10-18

We calculate, for the first time using unquenched lattice QCD form factors, the standard model differential branching fractions dB/dq2(B→Kℓ(+)ℓ(-)) for ℓ=e, μ, τ and compare with experimental measurements by Belle, BABAR, CDF, and LHCb. We report on B(B→Kℓ(+)ℓ(-)) in q2 bins used by experiment and predict B(B→Kτ(+)τ(-))=(1.41±0.15)×10(-7). We also calculate the ratio of branching fractions R(e)(μ)=1.00029(69) and predict R(ℓ)(τ)=1.176(40), for ℓ=e, μ. Finally, we calculate the "flat term" in the angular distribution of the differential decay rate F(H)(e,μ,τ) in experimentally motivated q2 bins.

The GlueX DIRC project

DOE PAGES

Stevens, J.; Barbosa, F.; Bessuille, J.; ...

2016-07-20

Here, the GlueX experiment was designed to search for and study the pattern of gluonic excitations in the meson spectrum produced through photoproduction reactions at a new tagged photon beam facility in Hall D at Jefferson Laboratory. The particle identification capabilities of the GlueX experiment will be enhanced by constructing a DIRC (Detection of Internally Reflected Cherenkov light) detector, utilizing components of the decommissioned BaBar DIRC. The DIRC will allow systematic studies of kaon final states that are essential for inferring the quark flavor content of both hybrid and conventional mesons. In this contribution, the design for the GlueX DIRCmore » will be discussed including new expansion volumes, read out with MaPMTs, that are currently under development.« less

Measurement of the decays B--> phiK and B--> phiK*.

PubMed

Aubert, B; Boutigny, D; Gaillard, J M; Hicheur, A; Karyotakis, Y; Lees, J P; Robbe, P; Tisserand, V; Palano, A; Chen, G P; Chen, J C; Qi, N D; Rong, G; Wang, P; Zhu, Y S; Eigen, G; Reinertsen, P L; Stugu, B; Abbott, B; Abrams, G S; Borgland, A W; Breon, A B; Brown, D N; Button-Shafer, J; Cahn, R N; Clark, A R; Fan, Q; Gill, M S; Gowdy, S J; Gritsan, A; Groysman, Y; Jacobsen, R G; Kadel, R W; Kadyk, J; Kerth, L T; Kluth, S; Kolomensky, Y G; Kral, J F; LeClerc, C; Levi, M E; Liu, T; Lynch, G; Meyer, A B; Momayezi, M; Oddone, P J; Perazzo, A; Pripstein, M; Roe, N A; Romosan, A; Ronan, M T; Shelkov, V G; Telnov, A V; Wenzel, W A; Bright-Thomas, P G; Harrison, T J; Hawkes, C M; Kirk, A; Knowles, D J; O'Neale, S W; Penny, R C; Watson, A T; Watson, N K; Deppermann, T; Koch, H; Krug, J; Kunze, M; Lewandowski, B; Peters, K; Schmuecker, H; Steinke, M; Andress, J C; Barlow, N R; Bhimji, W; Chevalier, N; Clark, P J; Cottingham, W N; De Groot, N; Dyce, N; Foster, B; Mass, A; McFall, J D; Wallom, D; Wilson, F F; Abe, K; Hearty, C; Mattison, T S; McKenna, J A; Thiessen, D; Camanzi, B; Jolly, S; McKemey, A K; Tinslay, J; Blinov, V E; Bukin, A D; Bukin, D A; Buzykaev, A R; Dubrovin, M S; Golubev, V B; Ivanchenko, V N; Korol, A A; Kravchenko, E A; Onuchin, A P; Salnikov, A A; Serednyakov, S I; Skovpen, Y I; Telnov, V I; Yushkov, A N; Lankford, A J; Mandelkern, M; McMahon, S; Stoker, D P; Ahsan, A; Arisaka, K; Buchanan, C; Chun, S; Branson, J G; MacFarlane, D B; Prell, S; Rahatlou, S; Raven, G; Sharma, V; Campagnari, C; Dahmes, B; Hart, P A; Kuznetsova, N; Levy, S L; Long, O; Lu, A; Richman, J D; Verkerke, W; Witherell, M; Yellin, S; Beringer, J; Dorfan, D E; Eisner, A M; Frey, A; Grillo, A A; Grothe, M; Heusch, C A; Johnson, R P; Kroeger, W; Lockman, W S; Pulliam, T; Sadrozinski, H; Schalk, T; Schmitz, R E; Schumm, B A; Seiden, A; Turri, M; Walkowiak, W; Williams, D C; Wilson, M G; Chen, E; Dubois-Felsmann, G P; Dvoretskii, A; Hitlin, D G; Metzler, S; Oyang, J; Porter, F C; Ryd, A; Samuel, A; Weaver, M; Yang, S; Zhu, R Y; Devmal, S; Geld, T L; Jayatilleke, S; Mancinelli, G; Meadows, B T; Sokoloff, M D; Bloom, P; Fahey, S; Ford, W T; Gaede, F; Johnson, D R; Michael, A K; Nauenberg, U; Olivas, A; Park, H; Rankin, P; Roy, J; Sen, S; Smith, J G; van Hoek, W C; Wagner, D L; Blouw, J; Harton, J L; Krishnamurthy, M; Soffer, A; Toki, W H; Wilson, R J; Zhang, J; Brandt, T; Brose, J; Colberg, T; Dahlinger, G; Dickopp, M; Dubitzky, R S; Maly, E; Müller-Pfefferkorn, R; Otto, S; Schubert, K R; Schwierz, R; Spaan, B; Wilden, L; Behr, L; Bernard, D; Bonneaud, G R; Brochard, F; Cohen-Tanugi, J; Ferrag, S; Roussot, E; T'Jampens, S; Thiebaux, C; Vasileiadis, G; Verderi, M; Anjomshoaa, A; Bernet, R; Di Lodovico, F; Khan, A; Muheim, F; Playfer, S; Swain, J E; Falbo, M; Bozzi, C; Dittongo, S; Folegani, M; Piemontese, L; Treadwell, E; Anulli, F; Baldini-Ferroli, R; Calcaterra, A; de Sangro, R; Falciai, D; Finocchiaro, G; Patteri, P; Peruzzi, I M; Piccolo, M; Xie, Y; Zallo, A; Bagnasco, S; Buzzo, A; Contri, R; Crosetti, G; Fabbricatore, P; Farinon, S; Lo Vetere, M; Macri, M; Monge, M R; Musenich, R; Pallavicini, M; Parodi, R; Passaggio, S; Pastore, F C; Patrignani, C; Pia, M G; Priano, C; Robutti, E; Santroni, A; Morii, M; Bartoldus, R; Dignan, T; Hamilton, R; Mallik, U; Cochran, J; Crawley, H B; Fischer, P A; Lamsa, J; Meyer, W T; Rosenberg, E I; Benkebil, M; Grosdidier, G; Hast, C; Höcker, A; Lacker, H M; LePeltier, V; Lutz, A M; Plaszczynski, S; Schune, M H; Trincaz-Duvoid, S; Valassi, A; Wormser, G; Bionta, R M; Brigljevic, V; Fackler, O; Fujino, D; Lange, D J; Mugge, M; Shi, X; van Bibber, K; Wenaus, T J; Wright, D M; Wuest, C R; Carroll, M; Fry, J R; Gabathuler, E; Gamet, R; George, M; Kay, M; Payne, D J; Sloane, R J; Touramanis, C; Aspinwall, M L; Bowerman, D A; Dauncey, P D; Egede, U; Eschrich, I; Gunawardane, N J; Martin, R; Nash, J A; Sanders, P; Smith, D; Azzopardi, D E; Back, J J; Dixon, P; Harrison, P F; Potter, R J; Shorthouse, H W; Strother, P; Vidal, P B; Williams, M I; Cowan, G; George, S; Green, M G; Kurup, A; Marker, C E; McGrath, P; McMahon, T R; Ricciardi, S; Salvatore, F; Scott, I; Vaitsas, G; Brown, D; Davis, C L; Allison, J; Barlow, R J; Boyd, J T; Forti, A; Fullwood, J; Jackson, F; Lafferty, G D; Savvas, N; Simopoulos, E T; Weatherall, J H; Farbin, A; Jawahery, A; Lillard, V; Olsen, J; Roberts, D A; Schieck, J R; Blaylock, G; Dallapiccola, C; Flood, K T; Hertzbach, S S; Kofler, R; Lin, C S; Moore, T B; Staengle, H; Willocq, S; Wittlin, J; Brau, B; Cowan, R; Sciolla, G; Taylor, F; Yamamoto, R K; Britton, D I; Milek, M; Patel, P M; Trischuk, J; Lanni, F; Palombo, F; Bauer, J M; Booke, M; Cremaldi, L; Eschenburg, V; Kroeger, R; Reidy, J; Sanders, D A; Summers, D J; Martin, J P; Nief, J Y; Seitz, R; Taras, P; Zacek, V; Nicholson, H; Sutton, C S; Cartaro, C; Cavallo, N; De Nardo, G; Fabozzi, F; Gatto, C; Lista, L; Paolucci, P; Piccolo, D; Sciacca, C; LoSecco, J M; Alsmiller, J R; Gabriel, T A; Handler, T; Brau, J; Frey, R; Iwasaki, M; Sinev, N B; Strom, D; Colecchia, F; Dal Corso, F; Dorigo, A; Galeazzi, F; Margoni, M; Michelon, G; Morandin, M; Posocco, M; Rotondo, M; Simonetto, F; Stroili, R; Torassa, E; Voci, C; Benayoun, M; Briand, H; Chauveau, J; David, P; De La Vaissière, C; Del Buono, L; Hamon, O; Le Diberder, F; Leruste, P; Lory, J; Roos, L; Stark, J; Versillé, S; Manfredi, P F; Re, V; Speziali, V; Frank, E D; Gladney, L; Guo, Q H; Panetta, J H; Angelini, C; Batignani, G; Bettarini, S; Bondioli, M; Carpinelli, M; Forti, F; Giorgi, M A; Lusiani, A; Martinez-Vidal, F; Morganti, M; Neri, N; Paoloni, E; Rama, M; Rizzo, G; Sandrelli, F; Simi, G; Triggiani, G; Walsh, J; Haire, M; Judd, D; Paick, K; Turnbull, L; Wagoner, D E; Albert, J; Bula, C; Lu, C; McDonald, K T; Miftakov, V; Schaffner, S F; Smith, A J; Tumanov, A; Varnes, E W; Cavoto, G; del Re, D; Faccini, R; Ferrarotto, F; Ferroni, F; Fratini, K; Lamanna, E; Leonardi, E; Mazzoni, M A; Morganti, S; Piredda, G; Safai Tehrani, F; Serra, M; Voena, C; Christ, S; Waldi, R; Adye, T; Franek, B; Geddes, N I; Gopal, G P; Xella, S M; Aleksan, R; De Domenico, G; Emery, S; Gaidot, A; Ganzhur, S F; Giraud, P F; Hamel De Monchenault, G; Kozanecki, W; Langer, M; London, G W; Mayer, B; Serfass, B; Vasseur, G; Yeche, C; Zito, M; Copty, N; Purohit, M V; Singh, H; Yumiceva, F X; Adam, I; Anthony, P L; Aston, D; Baird, K; Bartelt, J; Bloom, E; Boyarski, A M; Bulos, F; Calderini, G; Claus, R; Convery, M R; Coupal, D P; Coward, D H; Dorfan, J; Doser, M; Dunwoodie, W; Field, R C; Glanzman, T; Godfrey, G L; Grosso, P; Himel, T; Huffer, M E; Innes, W R; Jessop, C P; Kelsey, M H; Kim, P; Kocian, M L; Langenegger, U; Leith, D W; Luitz, S; Luth, V; Lynch, H L; Manzin, G; Marsiske, H; Menke, S; Messner, R; Moffeit, K C; Mount, R; Muller, D R; O'Grady, C P; Petrak, S; Quinn, H; Ratcliff, B N; Robertson, S H; Rochester, L S; Roodman, A; Schietinger, T; Schindler, R H; Schwiening, J; Serbo, V V; Snyder, A; Soha, A; Spanier, S M; Stahl, A; Stelzer, J; Su, D; Sullivan, M K; Talby, M; Tanaka, H A; Trunov, A; Va'vra, J; Wagner, S R; Weinstein, A J; Wisniewski, W J; Young, C C; Burchat, P R; Cheng, C H; Kirkby, D; Meyer, T I; Roat, C; De Silva, A; Henderson, R; Bugg, W; Cohn, H; Hart, E; Weidemann, A W; Benninger, T; Izen, J M; Kitayama, I; Lou, X C; Turcotte, M; Bianchi, F; Bona, M; Di Girolamo, B; Gamba, D; Smol, A; Zanin, D; Bosisio, L; Della Ricca, G; Lanceri, L; Pompili, A; Poropat, P; Prest, M; Vallazza, E; Vuagnin, G; Panvini, R S; Brown, C M; Kowalewski, R; Roney, J M; Band, H R; Charles, E; Dasu, S; Elmer, P; Hu, H; Johnson, J R; Liu, R; Nielsen, J; Orejudos, W; Pan, Y; Prepost, R; Scott, I J; Sekula, S J; von Wimmersperg-Toeller, J H; Wu, S L; Yu, Z; Zobering, H; Kordich, T M; Neal, H

2001-10-08

We have observed the decays B--> phiK and phiK(*) in a sample of over 45 million B mesons collected with the BABAR detector at the PEP-II collider. The measured branching fractions are B(B+--> phiK+) = (7.7(+1.6)(-1.4)+/-0.8)x10(-6), B(B0--> phiK0) = (8.1(+3.1)(-2.5)+/-0.8)x10(-6), B(B+--> phiK(*+)) = (9.7(+4.2)(-3.4)+/-1.7)x10(-6), and B(B0--> phiK(*0)) = (8.7(+2.5)(-2.1)+/-1.1)x10(-6). We also report the upper limit B(B+--> phipi(+))<1.4x10(-6) ( 90% C.L.).

Study of radiative bottomonium transitions using converted photons

NASA Astrophysics Data System (ADS)

Lees, J. P.; Poireau, V.; Prencipe, E.; Tisserand, V.; Garra Tico, J.; Grauges, E.; Martinelli, M.; Milanes, D. A.; Palano, A.; Pappagallo, M.; Eigen, G.; Stugu, B.; Sun, L.; Brown, D. N.; Kerth, L. T.; Kolomensky, Yu. G.; Lynch, G.; Koch, H.; Schroeder, T.; Asgeirsson, D. J.; Hearty, C.; Mattison, T. S.; McKenna, J. A.; Khan, A.; Blinov, V. E.; Buzykaev, A. R.; Druzhinin, V. P.; Golubev, V. B.; Kravchenko, E. A.; Onuchin, A. P.; Serednyakov, S. I.; Skovpen, Yu. I.; Solodov, E. P.; Todyshev, K. Yu.; Yushkov, A. N.; Bondioli, M.; Curry, S.; Kirkby, D.; Lankford, A. J.; Mandelkern, M.; Stoker, D. P.; Atmacan, H.; Gary, J. W.; Liu, F.; Long, O.; Vitug, G. M.; Campagnari, C.; Hong, T. M.; Kovalskyi, D.; Richman, J. D.; West, C. A.; Eisner, A. M.; Kroseberg, J.; Lockman, W. S.; Martinez, A. J.; Schalk, T.; Schumm, B. A.; Seiden, A.; Cheng, C. H.; Doll, D. A.; Echenard, B.; Flood, K. T.; Hitlin, D. G.; Ongmongkolkul, P.; Porter, F. C.; Rakitin, A. Y.; Andreassen, R.; Dubrovin, M. S.; Meadows, B. T.; Sokoloff, M. D.; Bloom, P. C.; Ford, W. T.; Gaz, A.; Nagel, M.; Nauenberg, U.; Smith, J. G.; Wagner, S. R.; Ayad, R.; Toki, W. H.; Spaan, B.; Kobel, M. J.; Schubert, K. R.; Schwierz, R.; Bernard, D.; Verderi, M.; Clark, P. J.; Playfer, S.; Watson, J. E.; Bettoni, D.; Bozzi, C.; Calabrese, R.; Cibinetto, G.; Fioravanti, E.; Garzia, I.; Luppi, E.; Munerato, M.; Negrini, M.; Piemontese, L.; Baldini-Ferroli, R.; Calcaterra, A.; de Sangro, R.; Finocchiaro, G.; Nicolaci, M.; Pacetti, S.; Patteri, P.; Peruzzi, I. M.; Piccolo, M.; Rama, M.; Zallo, A.; Contri, R.; Guido, E.; Lo Vetere, M.; Monge, M. R.; Passaggio, S.; Patrignani, C.; Robutti, E.; Bhuyan, B.; Prasad, V.; Lee, C. L.; Morii, M.; Edwards, A. J.; Adametz, A.; Marks, J.; Uwer, U.; Bernlochner, F. U.; Ebert, M.; Lacker, H. M.; Lueck, T.; Dauncey, P. D.; Tibbetts, M.; Behera, P. K.; Mallik, U.; Chen, C.; Cochran, J.; Crawley, H. B.; Meyer, W. T.; Prell, S.; Rosenberg, E. I.; Rubin, A. E.; Gritsan, A. V.; Guo, Z. J.; Arnaud, N.; Davier, M.; Derkach, D.; Grosdidier, G.; Le Diberder, F.; Lutz, A. M.; Malaescu, B.; Roudeau, P.; Schune, M. H.; Stocchi, A.; Wormser, G.; Lange, D. J.; Wright, D. M.; Bingham, I.; Chavez, C. A.; Coleman, J. P.; Fry, J. R.; Gabathuler, E.; Hutchcroft, D. E.; Payne, D. J.; Touramanis, C.; Bevan, A. J.; di Lodovico, F.; Sacco, R.; Sigamani, M.; Cowan, G.; Paramesvaran, S.; Brown, D. N.; Davis, C. L.; Denig, A. G.; Fritsch, M.; Gradl, W.; Hafner, A.; Alwyn, K. E.; Bailey, D.; Barlow, R. J.; Jackson, G.; Lafferty, G. D.; Cenci, R.; Hamilton, B.; Jawahery, A.; Roberts, D. A.; Simi, G.; Dallapiccola, C.; Salvati, E.; Cowan, R.; Dujmic, D.; Sciolla, G.; Lindemann, D.; Patel, P. M.; Robertson, S. H.; Schram, M.; Biassoni, P.; Lazzaro, A.; Lombardo, V.; Palombo, F.; Stracka, S.; Cremaldi, L.; Godang, R.; Kroeger, R.; Sonnek, P.; Summers, D. J.; Nguyen, X.; Taras, P.; de Nardo, G.; Monorchio, D.; Onorato, G.; Sciacca, C.; Raven, G.; Snoek, H. L.; Jessop, C. P.; Knoepfel, K. J.; Losecco, J. M.; Wang, W. F.; Honscheid, K.; Kass, R.; Brau, J.; Frey, R.; Sinev, N. B.; Strom, D.; Torrence, E.; Feltresi, E.; Gagliardi, N.; Margoni, M.; Morandin, M.; Posocco, M.; Rotondo, M.; Simonetto, F.; Stroili, R.; Ben-Haim, E.; Bomben, M.; Bonneaud, G. R.; Briand, H.; Calderini, G.; Chauveau, J.; Hamon, O.; Leruste, Ph.; Marchiori, G.; Ocariz, J.; Sitt, S.; Biasini, M.; Manoni, E.; Rossi, A.; Angelini, C.; Batignani, G.; Bettarini, S.; Carpinelli, M.; Casarosa, G.; Cervelli, A.; Forti, F.; Giorgi, M. A.; Lusiani, A.; Neri, N.; Oberhof, B.; Paoloni, E.; Perez, A.; Rizzo, G.; Walsh, J. J.; Lopes Pegna, D.; Lu, C.; Olsen, J.; Smith, A. J. S.; Telnov, A. V.; Anulli, F.; Cavoto, G.; Faccini, R.; Ferrarotto, F.; Ferroni, F.; Gaspero, M.; Li Gioi, L.; Mazzoni, M. A.; Piredda, G.; Bünger, C.; Hartmann, T.; Leddig, T.; Schröder, H.; Waldi, R.; Adye, T.; Olaiya, E. O.; Wilson, F. F.; Emery, S.; Hamel de Monchenault, G.; Vasseur, G.; Yèche, Ch.; Aston, D.; Bard, D. J.; Bartoldus, R.; Benitez, J. F.; Cartaro, C.; Convery, M. R.; Dorfan, J.; Dubois-Felsmann, G. P.; Dunwoodie, W.; Field, R. C.; Franco Sevilla, M.; Fulsom, B. G.; Gabareen, A. M.; Graham, M. T.; Grenier, P.; Hast, C.; Innes, W. R.; Kelsey, M. H.; Kim, H.; Kim, P.; Kocian, M. L.; Leith, D. W. G. S.; Lewis, P.; Li, S.; Lindquist, B.; Luitz, S.; Luth, V.; Lynch, H. L.; Macfarlane, D. B.; Muller, D. R.; Neal, H.; Nelson, S.; Ofte, I.; Perl, M.; Pulliam, T.; Ratcliff, B. N.; Roodman, A.; Salnikov, A. A.; Santoro, V.; Schindler, R. H.; Snyder, A.; Su, D.; Sullivan, M. K.; Va'Vra, J.; Wagner, A. P.; Weaver, M.; Wisniewski, W. J.; Wittgen, M.; Wright, D. H.; Wulsin, H. W.; Yarritu, A. K.; Young, C. C.; Ziegler, V.; Park, W.; Purohit, M. V.; White, R. M.; Wilson, J. R.; Randle-Conde, A.; Sekula, S. J.; Bellis, M.; Burchat, P. R.; Miyashita, T. S.; Alam, M. S.; Ernst, J. A.; Gorodeisky, R.; Guttman, N.; Peimer, D. R.; Soffer, A.; Lund, P.; Spanier, S. M.; Eckmann, R.; Ritchie, J. L.; Ruland, A. M.; Schilling, C. J.; Schwitters, R. F.; Wray, B. C.; Izen, J. M.; Lou, X. C.; Bianchi, F.; Gamba, D.; Lanceri, L.; Vitale, L.; Lopez-March, N.; Martinez-Vidal, F.; Oyanguren, A.; Ahmed, H.; Albert, J.; Banerjee, Sw.; Choi, H. H. F.; King, G. J.; Kowalewski, R.; Lewczuk, M. J.; Lindsay, C.; Nugent, I. M.; Roney, J. M.; Sobie, R. J.; Gershon, T. J.; Harrison, P. F.; Latham, T. E.; Puccio, E. M. T.; Band, H. R.; Dasu, S.; Pan, Y.; Prepost, R.; Vuosalo, C. O.; Wu, S. L.

2011-10-01

We use (111±1) million Υ(3S) and (89±1) million Υ(2S) events recorded by the BABAR detector at the PEP-II B-factory at SLAC to perform a study of radiative transitions between bottomonium states using photons that have been converted to e+e- pairs by the detector material. We observe Υ(3S)→γχb0,2(1P) decay, make precise measurements of the branching fractions for χb1,2(1P,2P)→γΥ(1S) and χb1,2(2P)→γΥ(2S) decays, and search for radiative decay to the ηb(1S) and ηb(2S) states.

Constraints on light mediators: Confronting dark matter searches with B physics

NASA Astrophysics Data System (ADS)

Schmidt-Hoberg, Kai; Staub, Florian; Winkler, Martin Wolfgang

2013-12-01

Light scalars appear in many well-motivated extensions of the Standard Model including supersymmetric models with additional gauge singlets. Such scalars could mediate the interactions between dark matter and nuclei, giving rise to the tentative signals observed by several dark matter direct detection experiments including CDMS-Si. In this Letter, we derive strong new limits on light scalar mediators by using the LHCb, Belle and BaBar searches for rare ϒ and B decays. These limits rule out significant parts of the parameter space favored by CDMS-Si. Nevertheless, as current searches are not optimized for investigating weakly coupled light scalars, a further increase in experimental sensitivity could be achieved by relaxing requirements in the event selection.

Critical Aspects of the Coastal Drought Index: Length of Salinity Data Record and Ecological Response Data

NASA Astrophysics Data System (ADS)

Conrads, P. A.; Tufford, D. L.; Darby, L. S.

2015-12-01

The phenomenon of coastal drought has a different dynamic from upland droughts that are typically characterized by agricultural, hydrologic, meteorological, and(or) socio-economic impacts. Because of the uniqueness of drought impacts on coastal ecosystems, a coastal drought index (CDI) that uses existing salinity datasets for sites in South Carolina, Georgia, and Florida was developed using an approach similar to the Standardized Precipitation Index (SPI). CDIs characterizing the 1- to 24-month salinity conditions were developed and the evaluation of the CDI indicates that the index can be used for different estuary types (for example, brackish, olioghaline, or mesohaline), for regional comparison between estuaries, and as an index for wet conditions (high freshwater inflow) in addition to drought conditions. Unlike the SPI where long-term precipitation datasets of 50 to 100 years are available for computing the index, there are a limited number of salinity data sets of greater than 10 or 15 years for computing the CDI. To evaluate the length of salinity record necessary to compute the CDI, a 29-year dataset was resampled into 5-, 10-, 15-, and 20-year interval datasets. Comparison of the CDI for the different periods of record show that the range of salinity conditions in the 10-, 15-, and 20-year datasets were similar and results were a close approximation to the CDI computed by using the full period of record. The CDI computed with the 5-year dataset had the largest differences with the CDI computed with the 29-year dataset but did provide useful information on coastal drought and freshwater conditions. An ongoing National Integrated Drought Information System (NIDIS) drought early warning project in the Carolinas is developing ecological linkages to the CDI and evaluating the effectiveness of the CDI as a prediction tool for adaptation planning for future droughts. However, identifying potential coastal drought response datasets is a challenge. Coastal drought is a relatively new concept and existing datasets may not have been collected or understood as "drought response" datasets. We have considered drought response datasets including tree growth and liter fall, harmful algal blooms occurrence, Vibrio infection occurrence, shellfish harvesting data, and shark attacks.

Trends in ice sheet mass balance, 1992 to 2017

NASA Astrophysics Data System (ADS)

Shepherd, A.; Ivins, E. R.; Smith, B.; Velicogna, I.; Whitehouse, P. L.; Rignot, E. J.; van den Broeke, M. R.; Briggs, K.; Hogg, A.; Krinner, G.; Joughin, I. R.; Nowicki, S.; Payne, A. J.; Scambos, T.; Schlegel, N.; Moyano, G.; Konrad, H.

2017-12-01

The Ice Sheet Mass Balance Inter-Comparison Exercise (IMBIE) is a community effort, jointly supported by ESA and NASA, that aims to provide a consensus estimate of ice sheet mass balance from satellite gravimetry, altimetry and mass budget assessments, on an annual basis. The project has five experiment groups, one for each of the satellite techniques and two others to analyse surface mass balance (SMB) and glacial isostatic adjustment (GIA). The basic premise for the exercise is that individual ice sheet mass balance datasets are generated by project participants using common spatial and temporal domains to allow meaningful inter-comparison, and this controlled comparison in turn supports aggregation of the individual datasets over their full period. Participation is open to the full community, and the quality and consistency of submissions is regulated through a series of data standards and documentation requirements. The second phase of IMBIE commenced in 2015, with participant data submitted in 2016 and a combined estimate due for public release in 2017. Data from 48 participant groups were submitted to one of the three satellite mass balance technique groups or to the ancillary dataset groups. The individual mass balance estimates and ancillary datasets have been compared and combined within the respective groups. Following this, estimates of ice sheet mass balance derived from the individual techniques were then compared and combined. The result is single estimates of ice sheet mass balance for Greenland, East Antarctica, West Antarctica, and the Antarctic Peninsula. The participants, methodology and results of the exercise will be presented in this paper.

The Falling Time Cost of College: Evidence from Half a Century of Time Use Data. NBER Working Paper No. 15954

ERIC Educational Resources Information Center

Babcock, Philip S.; Marks, Mindy

2010-01-01

Using multiple datasets from different time periods, we document declines in academic time investment by full-time college students in the United States between 1961 and 2003. Full-time students allocated 40 hours per week toward class and studying in 1961, whereas by 2003 they were investing about 27 hours per week. Declines were extremely…

A Novel Approach to Data Collection for Difficult Structures: Data Management for Large Numbers of Crystals with the BLEND Software.

PubMed

Mylona, Anastasia; Carr, Stephen; Aller, Pierre; Moraes, Isabel; Treisman, Richard; Evans, Gwyndaf; Foadi, James

2017-08-04

The present article describes how to use the computer program BLEND to help assemble complete datasets for the solution of macromolecular structures, starting from partial or complete datasets, derived from data collection from multiple crystals. The program is demonstrated on more than two hundred X-ray diffraction datasets obtained from 50 crystals of a complex formed between the SRF transcription factor, its cognate DNA, and a peptide from the SRF cofactor MRTF-A. This structure is currently in the process of being fully solved. While full details of the structure are not yet available, the repeated application of BLEND on data from this structure, as they have become available, has made it possible to produce electron density maps clear enough to visualise the potential location of MRTF sequences.

A Novel Approach to Data Collection for Difficult Structures: Data Management for Large Numbers of Crystals with the BLEND Software

PubMed Central

Mylona, Anastasia; Carr, Stephen; Aller, Pierre; Moraes, Isabel; Treisman, Richard; Evans, Gwyndaf; Foadi, James

2018-01-01

The present article describes how to use the computer program BLEND to help assemble complete datasets for the solution of macromolecular structures, starting from partial or complete datasets, derived from data collection from multiple crystals. The program is demonstrated on more than two hundred X-ray diffraction datasets obtained from 50 crystals of a complex formed between the SRF transcription factor, its cognate DNA, and a peptide from the SRF cofactor MRTF-A. This structure is currently in the process of being fully solved. While full details of the structure are not yet available, the repeated application of BLEND on data from this structure, as they have become available, has made it possible to produce electron density maps clear enough to visualise the potential location of MRTF sequences. PMID:29456874

Predictive modeling of treatment resistant depression using data from STAR*D and an independent clinical study.

PubMed

Nie, Zhi; Vairavan, Srinivasan; Narayan, Vaibhav A; Ye, Jieping; Li, Qingqin S

2018-01-01

Identification of risk factors of treatment resistance may be useful to guide treatment selection, avoid inefficient trial-and-error, and improve major depressive disorder (MDD) care. We extended the work in predictive modeling of treatment resistant depression (TRD) via partition of the data from the Sequenced Treatment Alternatives to Relieve Depression (STAR*D) cohort into a training and a testing dataset. We also included data from a small yet completely independent cohort RIS-INT-93 as an external test dataset. We used features from enrollment and level 1 treatment (up to week 2 response only) of STAR*D to explore the feature space comprehensively and applied machine learning methods to model TRD outcome at level 2. For TRD defined using QIDS-C16 remission criteria, multiple machine learning models were internally cross-validated in the STAR*D training dataset and externally validated in both the STAR*D testing dataset and RIS-INT-93 independent dataset with an area under the receiver operating characteristic curve (AUC) of 0.70-0.78 and 0.72-0.77, respectively. The upper bound for the AUC achievable with the full set of features could be as high as 0.78 in the STAR*D testing dataset. Model developed using top 30 features identified using feature selection technique (k-means clustering followed by χ2 test) achieved an AUC of 0.77 in the STAR*D testing dataset. In addition, the model developed using overlapping features between STAR*D and RIS-INT-93, achieved an AUC of > 0.70 in both the STAR*D testing and RIS-INT-93 datasets. Among all the features explored in STAR*D and RIS-INT-93 datasets, the most important feature was early or initial treatment response or symptom severity at week 2. These results indicate that prediction of TRD prior to undergoing a second round of antidepressant treatment could be feasible even in the absence of biomarker data.

Refining new-physics searches in B→Dτν with lattice QCD.

PubMed

Bailey, Jon A; Bazavov, A; Bernard, C; Bouchard, C M; Detar, C; Du, Daping; El-Khadra, A X; Foley, J; Freeland, E D; Gámiz, E; Gottlieb, Steven; Heller, U M; Kim, Jongjeong; Kronfeld, A S; Laiho, J; Levkova, L; Mackenzie, P B; Meurice, Y; Neil, E T; Oktay, M B; Qiu, Si-Wei; Simone, J N; Sugar, R; Toussaint, D; Van de Water, R S; Zhou, Ran

2012-08-17

The semileptonic decay channel B→Dτν is sensitive to the presence of a scalar current, such as that mediated by a charged-Higgs boson. Recently, the BABAR experiment reported the first observation of the exclusive semileptonic decay B→Dτ(-)ν, finding an approximately 2σ disagreement with the standard-model prediction for the ratio R(D)=BR(B→Dτν)/BR(B→Dℓν), where ℓ = e,μ. We compute this ratio of branching fractions using hadronic form factors computed in unquenched lattice QCD and obtain R(D)=0.316(12)(7), where the errors are statistical and total systematic, respectively. This result is the first standard-model calculation of R(D) from ab initio full QCD. Its error is smaller than that of previous estimates, primarily due to the reduced uncertainty in the scalar form factor f(0)(q(2)). Our determination of R(D) is approximately 1σ higher than previous estimates and, thus, reduces the tension with experiment. We also compute R(D) in models with electrically charged scalar exchange, such as the type-II two-Higgs-doublet model. Once again, our result is consistent with, but approximately 1σ higher than, previous estimates for phenomenologically relevant values of the scalar coupling in the type-II model. As a by-product of our calculation, we also present the standard-model prediction for the longitudinal-polarization ratio P(L)(D)=0.325(4)(3).

Branching ratio measurements of B meson decays to J/psi meson eta meson kaon and charged B meson decays to neutral D meson charged kaon with neutral D meson decays to positive pion negative pion neutral pion

NASA Astrophysics Data System (ADS)

Zeng, Qinglin

Results are presented for the decays of B → J/psietaK and B+/- → DK+/-, respectively, with experimental data collected with BABAR detector at PEP-II, located at Stanford Linear Accelerator Center (SLAC). With 90 x 106 BB¯ events at the Upsilon(4S) resonance, we obtained branching fractions of B (B+/- → J/psietaK +/-) = [10.8 +/- 2.3(stat) +/- 2.4(syst)] x 10-5 and B (B0 → J/psieta K0S ) = [8.4 +/- 2.6(stat) +/- 2.7( syst)] x 10-5; and we set an upper limit of B [B+/- → X(3872) K+/- → J/psietaK +/-] < 7.7 x 10-6 at 90% confidence level. The branching fraction of decay chain B (B+/- → DK +/- → pi+pi-pi 0K+/-) = [5.5 +/- 1.0( stat) +/- 0.7(syst)] x 10-6 with 229 x 106 BB¯ events at Upsilon(4S) resonance, here D represents the neutral D meson. The decay rate asymmetry is A = 0.02 +/- 0.16(stat) +/- 0.03(syst) for this full decay chain. This decay can be used to extract the unitarity angle gamma, a weak CP violation phase, through the interference of decay production of D0 and D¯ 0 to pi+pi-pi 0.

The effect of leverage and/or influential on structure-activity relationships.

PubMed

Bolboacă, Sorana D; Jäntschi, Lorentz

2013-05-01

In the spirit of reporting valid and reliable Quantitative Structure-Activity Relationship (QSAR) models, the aim of our research was to assess how the leverage (analysis with Hat matrix, h(i)) and the influential (analysis with Cook's distance, D(i)) of QSAR models may reflect the models reliability and their characteristics. The datasets included in this research were collected from previously published papers. Seven datasets which accomplished the imposed inclusion criteria were analyzed. Three models were obtained for each dataset (full-model, h(i)-model and D(i)-model) and several statistical validation criteria were applied to the models. In 5 out of 7 sets the correlation coefficient increased when compounds with either h(i) or D(i) higher than the threshold were removed. Withdrawn compounds varied from 2 to 4 for h(i)-models and from 1 to 13 for D(i)-models. Validation statistics showed that D(i)-models possess systematically better agreement than both full-models and h(i)-models. Removal of influential compounds from training set significantly improves the model and is recommended to be conducted in the process of quantitative structure-activity relationships developing. Cook's distance approach should be combined with hat matrix analysis in order to identify the compounds candidates for removal.

Multi-azimuth 3D Seismic Exploration and Processing in the Jeju Basin, the Northern East China Sea

NASA Astrophysics Data System (ADS)

Yoon, Youngho; Kang, Moohee; Kim, Jin-Ho; Kim, Kyong-O.

2015-04-01

Multi-azimuth(MAZ) 3D seismic exploration is one of the most advanced seismic survey methods to improve illumination and multiple attenuation for better image of the subsurface structures. 3D multi-channel seismic data were collected in two phases during 2012, 2013, and 2014 in Jeju Basin, the northern part of the East China Sea Basin where several oil and gas fields were discovered. Phase 1 data were acquired at 135° and 315° azimuths in 2012 and 2013 comprised a full 3D marine seismic coverage of 160 km2. In 2014, phase 2 data were acquired at the azimuths 45° and 225°, perpendicular to those of phase 1. These two datasets were processed through the same processing workflow prior to velocity analysis and merged to one MAZ dataset. We performed velocity analysis on the MAZ dataset as well as two phases data individually and then stacked these three datasets separately. We were able to pick more accurate velocities in the MAZ dataset compare to phase 1 and 2 data while velocity picking. Consequently, the MAZ seismic volume provide us better resolution and improved images since different shooting directions illuminate different parts of the structures and stratigraphic features.

Privacy preserving data publishing of categorical data through k-anonymity and feature selection.

PubMed

Aristodimou, Aristos; Antoniades, Athos; Pattichis, Constantinos S

2016-03-01

In healthcare, there is a vast amount of patients' data, which can lead to important discoveries if combined. Due to legal and ethical issues, such data cannot be shared and hence such information is underused. A new area of research has emerged, called privacy preserving data publishing (PPDP), which aims in sharing data in a way that privacy is preserved while the information lost is kept at a minimum. In this Letter, a new anonymisation algorithm for PPDP is proposed, which is based on k-anonymity through pattern-based multidimensional suppression (kPB-MS). The algorithm uses feature selection for reducing the data dimensionality and then combines attribute and record suppression for obtaining k-anonymity. Five datasets from different areas of life sciences [RETINOPATHY, Single Proton Emission Computed Tomography imaging, gene sequencing and drug discovery (two datasets)], were anonymised with kPB-MS. The produced anonymised datasets were evaluated using four different classifiers and in 74% of the test cases, they produced similar or better accuracies than using the full datasets.

Mapping Global Ocean Surface Albedo from Satellite Observations: Models, Algorithms, and Datasets

NASA Astrophysics Data System (ADS)

Li, X.; Fan, X.; Yan, H.; Li, A.; Wang, M.; Qu, Y.

2018-04-01

Ocean surface albedo (OSA) is one of the important parameters in surface radiation budget (SRB). It is usually considered as a controlling factor of the heat exchange among the atmosphere and ocean. The temporal and spatial dynamics of OSA determine the energy absorption of upper level ocean water, and have influences on the oceanic currents, atmospheric circulations, and transportation of material and energy of hydrosphere. Therefore, various parameterizations and models have been developed for describing the dynamics of OSA. However, it has been demonstrated that the currently available OSA datasets cannot full fill the requirement of global climate change studies. In this study, we present a literature review on mapping global OSA from satellite observations. The models (parameterizations, the coupled ocean-atmosphere radiative transfer (COART), and the three component ocean water albedo (TCOWA)), algorithms (the estimation method based on reanalysis data, and the direct-estimation algorithm), and datasets (the cloud, albedo and radiation (CLARA) surface albedo product, dataset derived by the TCOWA model, and the global land surface satellite (GLASS) phase-2 surface broadband albedo product) of OSA have been discussed, separately.

Multiple local feature representations and their fusion based on an SVR model for iris recognition using optimized Gabor filters

NASA Astrophysics Data System (ADS)

He, Fei; Liu, Yuanning; Zhu, Xiaodong; Huang, Chun; Han, Ye; Dong, Hongxing

2014-12-01

Gabor descriptors have been widely used in iris texture representations. However, fixed basic Gabor functions cannot match the changing nature of diverse iris datasets. Furthermore, a single form of iris feature cannot overcome difficulties in iris recognition, such as illumination variations, environmental conditions, and device variations. This paper provides multiple local feature representations and their fusion scheme based on a support vector regression (SVR) model for iris recognition using optimized Gabor filters. In our iris system, a particle swarm optimization (PSO)- and a Boolean particle swarm optimization (BPSO)-based algorithm is proposed to provide suitable Gabor filters for each involved test dataset without predefinition or manual modulation. Several comparative experiments on JLUBR-IRIS, CASIA-I, and CASIA-V4-Interval iris datasets are conducted, and the results show that our work can generate improved local Gabor features by using optimized Gabor filters for each dataset. In addition, our SVR fusion strategy may make full use of their discriminative ability to improve accuracy and reliability. Other comparative experiments show that our approach may outperform other popular iris systems.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Baldini, A. M.; Bao, Y.; Baracchini, E.

Our final results of the search for the lepton flavour violating decay μ+→e+γ based on the full dataset collected by the MEG experiment at the Paul Scherrer Institut in the period 2009–2013 and totalling 7.5×1014 stopped muons on target are presented. Furthermore, there was not a significant excess of events observed in the dataset with respect to the expected background and a new upper limit on the branching ratio of this decay of B(μ+→e+γ)<4.2×10-13 (90 % confidence level) is established, which represents the most stringent limit on the existence of this decay to date.

ENSO related variability in the Southern Hemisphere, 1948-2000

NASA Astrophysics Data System (ADS)

Ribera, Pedro; Mann, Michael E.

2003-01-01

The spatiotemporal evolution of Southern Hemisphere climate variability is diagnosed based on the use of the NCEP reanalysis (1948-2000) dataset. Using the MTM-SVD analysis method, significant narrowband variability is isolated from the multi-variate dataset. It is found that the ENSO signal exhibits statistically significant behavior at quasiquadrennial (3-6 yr) timescales for the full time-period. A significant quasibiennial (2-3 yr) timescales emerges only for the latter half of period. Analyses of the spatial evolution of the two reconstructed signals shed additional light on linkages between low and high-latitude Southern Hemisphere climate anomalies.

Interoperability Using Lightweight Metadata Standards: Service & Data Casting, OpenSearch, OPM Provenance, and Shared SciFlo Workflows

NASA Astrophysics Data System (ADS)

Wilson, B. D.; Manipon, G.; Hua, H.; Fetzer, E.

2011-12-01

Under several NASA grants, we are generating multi-sensor merged atmospheric datasets to enable the detection of instrument biases and studies of climate trends over decades of data. For example, under a NASA MEASURES grant we are producing a water vapor climatology from the A-Train instruments, stratified by the Cloudsat cloud classification for each geophysical scene. The generation and proper use of such multi-sensor climate data records (CDR's) requires a high level of openness, transparency, and traceability. To make the datasets self-documenting and provide access to full metadata and traceability, we have implemented a set of capabilities and services using known, interoperable protocols. These protocols include OpenSearch, OPeNDAP, Open Provenance Model, service & data casting technologies using Atom feeds, and REST-callable analysis workflows implemented as SciFlo (XML) documents. We advocate that our approach can serve as a blueprint for how to openly "document and serve" complex, multi-sensor CDR's with full traceability. The capabilities and services provided include: - Discovery of the collections by keyword search, exposed using OpenSearch protocol; - Space/time query across the CDR's granules and all of the input datasets via OpenSearch; - User-level configuration of the production workflows so that scientists can select additional physical variables from the A-Train to add to the next iteration of the merged datasets; - Efficient data merging using on-the-fly OPeNDAP variable slicing & spatial subsetting of data out of input netCDF and HDF files (without moving the entire files); - Self-documenting CDR's published in a highly usable netCDF4 format with groups used to organize the variables, CF-style attributes for each variable, numeric array compression, & links to OPM provenance; - Recording of processing provenance and data lineage into a query-able provenance trail in Open Provenance Model (OPM) format, auto-captured by the workflow engine; - Open Publishing of all of the workflows used to generate products as machine-callable REST web services, using the capabilities of the SciFlo workflow engine; - Advertising of the metadata (e.g. physical variables provided, space/time bounding box, etc.) for our prepared datasets as "datacasts" using the Atom feed format; - Publishing of all datasets via our "DataDrop" service, which exploits the WebDAV protocol to enable scientists to access remote data directories as local files on their laptops; - Rich "web browse" of the CDR's with full metadata and the provenance trail one click away; - Advertising of all services as Google-discoverable "service casts" using the Atom format. The presentation will describe our use of the interoperable protocols and demonstrate the capabilities and service GUI's.

A hybrid Land Cover Dataset for Russia: a new methodology for merging statistics, remote sensing and in-situ information

NASA Astrophysics Data System (ADS)

Schepaschenko, D.; McCallum, I.; Shvidenko, A.; Kraxner, F.; Fritz, S.

2009-04-01

There is a critical need for accurate land cover information for resource assessment, biophysical modeling, greenhouse gas studies, and for estimating possible terrestrial responses and feedbacks to climate change. However, practically all existing land cover datasets have quite a high level of uncertainty and suffer from a lack of important details that does not allow for relevant parameterization, e.g., data derived from different forest inventories. The objective of this study is to develop a methodology in order to create a hybrid land cover dataset at the level which would satisfy requirements of the verified terrestrial biota full greenhouse gas account (Shvidenko et al., 2008) for large regions i.e. Russia. Such requirements necessitate a detailed quantification of land classes (e.g., for forests - dominant species, age, growing stock, net primary production, etc.) with additional information on uncertainties of the major biometric and ecological parameters in the range of 10-20% and a confidence interval of around 0.9. The approach taken here allows the integration of different datasets to explore synergies and in particular the merging and harmonization of land and forest inventories, ecological monitoring, remote sensing data and in-situ information. The following datasets have been integrated: Remote sensing: Global Land Cover 2000 (Fritz et al., 2003), Vegetation Continuous Fields (Hansen et al., 2002), Vegetation Fire (Sukhinin, 2007), Regional land cover (Schmullius et al., 2005); GIS: Soil 1:2.5 Mio (Dokuchaev Soil Science Institute, 1996), Administrative Regions 1:2.5 Mio, Vegetation 1:4 Mio, Bioclimatic Zones 1:4 Mio (Stolbovoi & McCallum, 2002), Forest Enterprises 1:2.5 Mio, Rivers/Lakes and Roads/Railways 1:1 Mio (IIASA's data base); Inventories and statistics: State Land Account (FARSC RF, 2006), State Forest Account - SFA (FFS RF, 2003), Disturbances in forests (FFS RF, 2006). The resulting hybrid land cover dataset at 1-km resolution comprises the following classes: Forest (each grid links to the SFA database, which contains 86,613 records); Agriculture (5 classes, parameterized by 89 administrative units); Wetlands (8 classes, parameterized by 83 zone/region units); Open Woodland, Burnt area; Shrub/grassland (50 classes, parameterized by 300 zone/region units); Water; Unproductive area. This study has demonstrated the ability to produce a highly detailed (both spatially and thematically) land cover dataset over Russia. Future efforts include further validation of the hybrid land cover dataset for Russia, and its use for assessment of the terrestrial biota full greenhouse gas budget across Russia. The methodology proposed in this study could be applied at the global level. Results of such an undertaking would however be highly dependent upon the quality of the available ground data. The implementation of the hybrid land cover dataset was undertaken in a way that it can be regularly updated based on new ground data and remote sensing products (ie. MODIS).

Genome-wide study of resistant hypertension identified from electronic health records.

PubMed

Dumitrescu, Logan; Ritchie, Marylyn D; Denny, Joshua C; El Rouby, Nihal M; McDonough, Caitrin W; Bradford, Yuki; Ramirez, Andrea H; Bielinski, Suzette J; Basford, Melissa A; Chai, High Seng; Peissig, Peggy; Carrell, David; Pathak, Jyotishman; Rasmussen, Luke V; Wang, Xiaoming; Pacheco, Jennifer A; Kho, Abel N; Hayes, M Geoffrey; Matsumoto, Martha; Smith, Maureen E; Li, Rongling; Cooper-DeHoff, Rhonda M; Kullo, Iftikhar J; Chute, Christopher G; Chisholm, Rex L; Jarvik, Gail P; Larson, Eric B; Carey, David; McCarty, Catherine A; Williams, Marc S; Roden, Dan M; Bottinger, Erwin; Johnson, Julie A; de Andrade, Mariza; Crawford, Dana C

2017-01-01

Resistant hypertension is defined as high blood pressure that remains above treatment goals in spite of the concurrent use of three antihypertensive agents from different classes. Despite the important health consequences of resistant hypertension, few studies of resistant hypertension have been conducted. To perform a genome-wide association study for resistant hypertension, we defined and identified cases of resistant hypertension and hypertensives with treated, controlled hypertension among >47,500 adults residing in the US linked to electronic health records (EHRs) and genotyped as part of the electronic MEdical Records & GEnomics (eMERGE) Network. Electronic selection logic using billing codes, laboratory values, text queries, and medication records was used to identify resistant hypertension cases and controls at each site, and a total of 3,006 cases of resistant hypertension and 876 controlled hypertensives were identified among eMERGE Phase I and II sites. After imputation and quality control, a total of 2,530,150 SNPs were tested for an association among 2,830 multi-ethnic cases of resistant hypertension and 876 controlled hypertensives. No test of association was genome-wide significant in the full dataset or in the dataset limited to European American cases (n = 1,719) and controls (n = 708). The most significant finding was CLNK rs13144136 at p = 1.00x10-6 (odds ratio = 0.68; 95% CI = 0.58-0.80) in the full dataset with similar results in the European American only dataset. We also examined whether SNPs known to influence blood pressure or hypertension also influenced resistant hypertension. None was significant after correction for multiple testing. These data highlight both the difficulties and the potential utility of EHR-linked genomic data to study clinically-relevant traits such as resistant hypertension.

Study of B+/ --> J/psi pi+/- and B+/ -->J/psi K+/- decays: measurement of the ratio of branching fractions and search for direct CP violation.

PubMed

Aubert, B; Barate, R; Boutigny, D; Couderc, F; Gaillard, J-M; Hicheur, A; Karyotakis, Y; Lees, J P; Tisserand, V; Zghiche, A; Palano, A; Pompili, A; Chen, J C; Qi, N D; Rong, G; Wang, P; Zhu, Y S; Eigen, G; Ofte, I; Stugu, B; Abrams, G S; Borgland, A W; Breon, A B; Brown, D N; Button-Shafer, J; Cahn, R N; Charles, E; Day, C T; Gill, M S; Gritsan, A V; Groysman, Y; Jacobsen, R G; Kadel, R W; Kadyk, J; Kerth, L T; Kolomensky, Yu G; Kukartsev, G; LeClerc, C; Levi, M E; Lynch, G; Mir, L M; Oddone, P J; Orimoto, T J; Pripstein, M; Roe, N A; Ronan, M T; Shelkov, V G; Telnov, A V; Wenzel, W A; Ford, K; Harrison, T J; Hawkes, C M; Morgan, S E; Watson, A T; Watson, N K; Fritsch, M; Goetzen, K; Held, T; Koch, H; Lewandowski, B; Pelizaeus, M; Steinke, M; Boyd, J T; Chevalier, N; Cottingham, W N; Kelly, M P; Latham, T E; Wilson, F F; Abe, K; Cuhadar-Donszelmann, T; Hearty, C; Mattison, T S; McKenna, J A; Thiessen, D; Kyberd, P; Teodorescu, L; Blinov, V E; Bukin, A D; Druzhinin, V P; Golubev, V B; Ivanchenko, V N; Kravchenko, E A; Onuchin, A P; Serednyakov, S I; Skovpen, Yu I; Solodov, E P; Yushkov, A N; Best, D; Bruinsma, M; Chao, M; Eschrich, I; Kirkby, D; Lankford, A J; Mandelkern, M; Mommsen, R K; Roethel, W; Stoker, D P; Buchanan, C; Hartfiel, B L; Gary, J W; Shen, B C; Wang, K; del Re, D; Hadavand, H K; Hill, E J; MacFarlane, D B; Paar, H P; Rahatlou, Sh; Sharma, V; Berryhill, J W; Campagnari, C; Dahmes, B; Levy, S L; Long, O; Lu, A; Mazur, M A; Richman, J D; Verkerke, W; Beck, T W; Eisner, A M; Heusch, C A; Lockman, W S; Schalk, T; Schmitz, R E; Schumm, B A; Seiden, A; Spradlin, P; Williams, D C; Wilson, M G; Albert, J; Chen, E; Dubois-Felsmann, G P; Dvoretskii, A; Hitlin, D G; Narsky, I; Piatenko, T; Porter, F C; Ryd, A; Samuel, A; Yang, S; Jayatilleke, S; Mancinelli, G; Meadows, B T; Sokoloff, M D; Abe, T; Blanc, F; Bloom, P; Chen, S; Clark, P J; Ford, W T; Nauenberg, U; Olivas, A; Rankin, P; Smith, J G; van Hoek, W C; Zhang, L; Harton, J L; Hu, T; Soffer, A; Toki, W H; Wilson, R J; Altenburg, D; Brandt, T; Brose, J; Colberg, T; Dickopp, M; Feltresi, E; Hauke, A; Lacker, H M; Maly, E; Müller-Pfefferkorn, R; Nogowski, R; Otto, S; Schubert, J; Schubert, K R; Schwierz, R; Spaan, B; Bernard, D; Bonneaud, G R; Brochard, F; Grenier, P; Thiebaux, Ch; Vasileiadis, G; Verderi, M; Bard, D J; Khan, A; Lavin, D; Muheim, F; Playfer, S; Andreotti, M; Azzolini, V; Bettoni, D; Bozzi, C; Calabrese, R; Cibinetto, G; Luppi, E; Negrini, M; Sarti, A; Treadwell, E; Baldini-Ferroli, R; Calcaterra, A; de Sangro, R; Finocchiaro, G; Patteri, P; Piccolo, M; Zallo, A; Buzzo, A; Capra, R; Contri, R; Crosetti, G; Lo Vetere, M; Macri, M; Monge, M R; Passaggio, S; Patrignani, C; Robutti, E; Santroni, A; Tosi, S; Bailey, S; Brandenburg, G; Morii, M; Won, E; Dubitzky, R S; Langenegger, U; Bhimji, W; Bowerman, D A; Dauncey, P D; Egede, U; Gaillard, J R; Morton, G W; Nash, J A; Taylor, G P; Grenier, G J; Lee, S-J; Mallik, U; Cochran, J; Crawley, H B; Lamsa, J; Meyer, W T; Prell, S; Rosenberg, E I; Yi, J; Davier, M; Grosdidier, G; Höcker, A; Laplace, S; Le Diberder, F; Lepeltier, V; Lutz, A M; Petersen, T C; Plaszczynski, S; Schune, M H; Tantot, L; Wormser, G; Cheng, C H; Lange, D J; Simani, M C; Wright, D M; Bevan, A J; Coleman, J P; Fry, J R; Gabathuler, E; Gamet, R; Kay, M; Parry, R J; Payne, D J; Sloane, R J; Touramanis, C; Back, J J; Harrison, P F; Mohanty, G B; Brown, C L; Cowan, G; Flack, R L; Flaecher, H U; George, S; Green, M G; Kurup, A; Marker, C E; McMahon, T R; Ricciardi, S; Salvatore, F; Vaitsas, G; Winter, M A; Brown, D; Davis, C L; Allison, J; Barlow, N R; Barlow, R J; Hart, P A; Hodgkinson, M C; Lafferty, G D; Lyon, A J; Williams, J C; Farbin, A; Hulsbergen, W D; Jawahery, A; Kovalskyi, D; Lae, C K; Lillard, V; Roberts, D A; Blaylock, G; Dallapiccola, C; Flood, K T; Hertzbach, S S; Kofler, R; Koptchev, V B; Moore, T B; Saremi, S; Staengle, H; Willocq, S; Cowan, R; Sciolla, G; Taylor, F; Yamamoto, R K; Mangeol, D J J; Patel, P M; Robertson, S H; Lazzaro, A; Palombo, F; Bauer, J M; Cremaldi, L; Eschenburg, V; Godang, R; Kroeger, R; Reidy, J; Sanders, D A; Summers, D J; Zhao, H W; Brunet, S; Côté, D; Taras, P; Nicholson, H; Cartaro, C; Cavallo, N; Fabozzi, F; Gatto, C; Lista, L; Monorchio, D; Paolucci, P; Piccolo, D; Sciacca, C; Baak, M; Raven, G; Wilden, L; Jessop, C P; LoSecco, J M; Gabriel, T A; Allmendinger, T; Brau, B; Gan, K K; Honscheid, K; Hufnagel, D; Kagan, H; Kass, R; Pulliam, T; Ter-Antonyan, R; Wong, Q K; Brau, J; Frey, R; Igonkina, O; Potter, C T; Sinev, N B; Strom, D; Torrence, E; Colecchia, F; Dorigo, A; Galeazzi, F; Margoni, M; Morandin, M; Posocco, M; Rotondo, M; Simonetto, F; Stroili, R; Tiozzo, G; Voci, C; Benayoun, M; Briand, H; Chauveau, J; David, P; de laVassière, Ch; Del Buono, L; Hamon, O; John, M J J; Leruste, Ph; Ocariz, J; Pivk, M; Roos, L; T'Jampens, S; Therin, G; Manfredi, P F; Re, V; Behera, P K; Gladney, L; Guo, Q H; Panetta, J; Anulli, F; Biasini, M; Peruzzi, I M; Pioppi, M; Angelini, C; Batignani, G; Bettarini, S; Bondioli, M; Bucci, F; Calderini, G; Carpinelli, M; Del Gamba, V; Forti, F; Giorgi, M A; Lusiani, A; Marchiori, G; Martinez-Vidal, F; Morganti, M; Neri, N; Paoloni, E; Rama, M; Rizzo, G; Sandrelli, F; Walsh, J; Haire, M; Judd, D; Paick, K; Wagoner, D E; Danielson, N; Elmer, P; Lu, C; Miftakov, V; Olsen, J; Smith, A J S; Varnes, E W; Bellini, F; Cavoto, G; Faccini, R; Ferrarotto, F; Ferroni, F; Gaspero, M; Li Gioi, L; Mazzoni, M A; Morganti, S; Pierini, M; Piredda, G; Safai Tehrani, F; Voena, C; Christ, S; Wagner, G; Waldi, R; Adye, T; De Groot, N; Franek, B; Geddes, N I; Gopal, G P; Olaiya, E O; Xella, S M; Aleksan, R; Emery, S; Gaidot, A; Ganzhur, S F; Giraud, P-F; Hamel de Monchenault, G; Kozanecki, W; Langer, M; Legendre, M; London, G W; Mayer, B; Schott, G; Vasseur, G; Yèche, Ch; Zito, M; Purohit, M V; Weidemann, A W; Yumiceva, F X; Aston, D; Bartoldus, R; Berger, N; Boyarski, A M; Buchmueller, O L; Convery, M R; Cristinziani, M; De Nardo, G; Dong, D; Dorfan, J; Dujmic, D; Dunwoodie, W; Elsen, E E; Field, R C; Glanzman, T; Gowdy, S J; Hadig, T; Halyo, V; Hryn'ova, T; Innes, W R; Kelsey, M H; Kim, P; Kocian, M L; Leith, D W G S; Libby, J; Luitz, S; Luth, V; Lynch, H L; Marsiske, H; Messner, R; Muller, D R; O'Grady, C P; Ozcan, V E; Perazzo, A; Perl, M; Petrak, S; Ratcliff, B N; Roodman, A; Salnikov, A A; Schindler, R H; Schwiening, J; Simi, G; Snyder, A; Soha, A; Stelzer, J; Su, D; Sullivan, M K; Va'vra, J; Wagner, S R; Weaver, M; Weinstein, A J R; Wisniewski, W J; Wittgen, M; Wright, D H; Young, C C; Burchat, P R; Edwards, A J; Meyer, T I; Petersen, B A; Roat, C; Ahmed, S; Alam, M S; Ernst, J A; Saeed, M A; Saleem, M; Wappler, F R; Bugg, W; Krishnamurthy, M; Spanier, S M; Eckmann, R; Kim, H; Ritchie, J L; Satpathy, A; Schwitters, R F; Izen, J M; Kitayama, I; Lou, X C; Ye, S; Bianchi, F; Bona, M; Gallo, F; Gamba, D; Borean, C; Bosisio, L; Cossutti, F; Della Ricca, G; Dittongo, S; Grancagnolo, S; Lanceri, L; Poropat, P; Vitale, L; Vuagnin, G; Panvini, R S; Banerjee, Sw; Brown, C M; Fortin, D; Jackson, P D; Kowalewski, R; Roney, J M; Band, H R; Dasu, S; Datta, M; Eichenbaum, A M; Hollar, J J; Johnson, J R; Kutter, P E; Li, H; Liu, R; Di Lodovico, F; Mihalyi, A; Mohapatra, A K; Pan, Y; Prepost, R; Sekula, S J; Tan, P; von Wimmersperg-Toeller, J H; Wu, J; Wu, S L; Yu, Z; Neal, H

2004-06-18

We study B+/ --> J/psi pi(+/-) and B+/ --> J/psi K+/- decays in a sample of about 89 x 10(6) BB pairs collected with the BABAR detector at the PEP-II asymmetric B factory at SLAC. We observe a signal of 244+/-20 B+/ --> J/psi pi(+/-) events and determine the ratio B(B+/ --> J/psi pi(+/-))/B(B+/ --> J/psi K+/-) to be [5.37+/-0.45(stat)+/-0.11(syst)]%. The charge asymmetries for the B+/ --> J/psi pi(+/-) and B+/ --> J/psi K+/- decays are determined to be A(pi)=0.123+/-0.085(stat)+/-0.004(syst) and A(K)=0.030+/-0.015(stat)+/-0.006(syst), respectively.

Amplitude analysis of the B+/--->phiK*(892)+/- decay.

PubMed

Aubert, B; Bona, M; Boutigny, D; Karyotakis, Y; Lees, J P; Poireau, V; Prudent, X; Tisserand, V; Zghiche, A; Garra Tico, J; Grauges, E; Lopez, L; Palano, A; Eigen, G; Stugu, B; Sun, L; Abrams, G S; Battaglia, M; Brown, D N; Button-Shafer, J; Cahn, R N; Groysman, Y; Jacobsen, R G; Kadyk, J A; Kerth, L T; Kolomensky, Yu G; Kukartsev, G; Lopes Pegna, D; Lynch, G; Mir, L M; Orimoto, T J; Ronan, M T; Tackmann, K; Wenzel, W A; del Amo Sanchez, P; Hawkes, C M; Watson, A T; Held, T; Koch, H; Lewandowski, B; Pelizaeus, M; Schroeder, T; Steinke, M; Walker, D; Asgeirsson, D J; Cuhadar-Donszelmann, T; Fulsom, B G; Hearty, C; Mattison, T S; McKenna, J A; Khan, A; Saleem, M; Teodorescu, L; Blinov, V E; Bukin, A D; Druzhinin, V P; Golubev, V B; Onuchin, A P; Serednyakov, S I; Skovpen, Yu I; Solodov, E P; Todyshev, K Yu; Bondioli, M; Curry, S; Eschrich, I; Kirkby, D; Lankford, A J; Lund, P; Mandelkern, M; Martin, E C; Stoker, D P; Abachi, S; Buchanan, C; Foulkes, S D; Gary, J W; Liu, F; Long, O; Shen, B C; Zhang, L; Paar, H P; Rahatlou, S; Sharma, V; Berryhill, J W; Campagnari, C; Cunha, A; Dahmes, B; Hong, T M; Kovalskyi, D; Richman, J D; Beck, T W; Eisner, A M; Flacco, C J; Heusch, C A; Kroseberg, J; Lockman, W S; Schalk, T; Schumm, B A; Seiden, A; Williams, D C; Wilson, M G; Winstrom, L O; Chen, E; Cheng, C H; Fang, F; Hitlin, D G; Narsky, I; Piatenko, T; Porter, F C; Andreassen, R; Mancinelli, G; Meadows, B T; Mishra, K; Sokoloff, M D; Blanc, F; Bloom, P C; Chen, S; Ford, W T; Hirschauer, J F; Kreisel, A; Nagel, M; Nauenberg, U; Olivas, A; Smith, J G; Ulmer, K A; Wagner, S R; Zhang, J; Gabareen, A M; Soffer, A; Toki, W H; Wilson, R J; Winklmeier, F; Zeng, Q; Altenburg, D D; Feltresi, E; Hauke, A; Jasper, H; Merkel, J; Petzold, A; Spaan, B; Wacker, K; Brandt, T; Klose, V; Kobel, M J; Lacker, H M; Mader, W F; Nogowski, R; Schubert, J; Schubert, K R; Schwierz, R; Sundermann, J E; Volk, A; Bernard, D; Bonneaud, G R; Latour, E; Lombardo, V; Thiebaux, Ch; Verderi, M; Clark, P J; Gradl, W; Muheim, F; Playfer, S; Robertson, A I; Xie, Y; Andreotti, M; Bettoni, D; Bozzi, C; Calabrese, R; Cecchi, A; Cibinetto, G; Franchini, P; Luppi, E; Negrini, M; Petrella, A; Piemontese, L; Prencipe, E; Santoro, V; Anulli, F; Baldini-Ferroli, R; Calcaterra, A; de Sangro, R; Finocchiaro, G; Pacetti, S; Patteri, P; Peruzzi, I M; Piccolo, M; Rama, M; Zallo, A; Buzzo, A; Contri, R; Lo Vetere, M; Macri, M M; Monge, M R; Passaggio, S; Patrignani, C; Robutti, E; Santroni, A; Tosi, S; Chaisanguanthum, K S; Morii, M; Wu, J; Dubitzky, R S; Marks, J; Schenk, S; Uwer, U; Bard, D J; Dauncey, P D; Flack, R L; Nash, J A; Nikolich, M B; Panduro Vazquez, W; Tibbetts, M; Behera, P K; Chai, X; Charles, M J; Mallik, U; Meyer, N T; Ziegler, V; Cochran, J; Crawley, H B; Dong, L; Eyges, V; Meyer, W T; Prell, S; Rosenberg, E I; Rubin, A E; Gao, Y Y; Gritsan, A V; Guo, Z J; Lae, C K; Denig, A G; Fritsch, M; Schott, G; Arnaud, N; Béquilleux, J; Davier, M; Grosdidier, G; Höcker, A; Lepeltier, V; Le Diberder, F; Lutz, A M; Pruvot, S; Rodier, S; Roudeau, P; Schune, M H; Serrano, J; Sordini, V; Stocchi, A; Wang, W F; Wormser, G; Lange, D J; Wright, D M; Bingham, I; Chavez, C A; Forster, I J; Fry, J R; Gabathuler, E; Gamet, R; Hutchcroft, D E; Payne, D J; Schofield, K C; Touramanis, C; Bevan, A J; George, K A; Di Lodovico, F; Menges, W; Sacco, R; Cowan, G; Flaecher, H U; Hopkins, D A; Paramesvaran, S; Salvatore, F; Wren, A C; Brown, D N; Davis, C L; Allison, J; Barlow, N R; Barlow, R J; Chia, Y M; Edgar, C L; Lafferty, G D; West, T J; Yi, J I; Anderson, J; Chen, C; Jawahery, A; Roberts, D A; Simi, G; Tuggle, J M; Blaylock, G; Dallapiccola, C; Hertzbach, S S; Li, X; Moore, T B; Salvati, E; Saremi, S; Cowan, R; Dujmic, D; Fisher, P H; Koeneke, K; Sciolla, G; Sekula, S J; Spitznagel, M; Taylor, F; Yamamoto, R K; Zhao, M; Zheng, Y; Mclachlin, S E; Patel, P M; Robertson, S H; Lazzaro, A; Palombo, F; Bauer, J M; Cremaldi, L; Eschenburg, V; Godang, R; Kroeger, R; Sanders, D A; Summers, D J; Zhao, H W; Brunet, S; Côté, D; Simard, M; Taras, P; Viaud, F B; Nicholson, H; De Nardo, G; Fabozzi, F; Lista, L; Monorchio, D; Sciacca, C; Baak, M A; Raven, G; Snoek, H L; Jessop, C P; LoSecco, J M; Benelli, G; Corwin, L A; Honscheid, K; Kagan, H; Kass, R; Morris, J P; Rahimi, A M; Regensburger, J J; Wong, Q K; Blount, N L; Brau, J; Frey, R; Igonkina, O; Kolb, J A; Lu, M; Rahmat, R; Sinev, N B; Strom, D; Strube, J; Torrence, E; Gagliardi, N; Gaz, A; Margoni, M; Morandin, M; Pompili, A; Posocco, M; Rotondo, M; Simonetto, F; Stroili, R; Voci, C; Ben-Haim, E; Briand, H; Calderini, G; Chauveau, J; David, P; Del Buono, L; de la Vaissière, Ch; Hamon, O; Leruste, Ph; Malclès, J; Ocariz, J; Perez, A; Gladney, L; Biasini, M; Covarelli, R; Manoni, E; Angelini, C; Batignani, G; Bettarini, S; Carpinelli, M; Cenci, R; Cervelli, A; Forti, F; Giorgi, M A; Lusiani, A; Marchiori, G; Mazur, M A; Morganti, M; Neri, N; Paoloni, E; Rizzo, G; Walsh, J J; Haire, M; Biesiada, J; Elmer, P; Lau, Y P; Lu, C; Olsen, J; Smith, A J S; Telnov, A V; Baracchini, E; Bellini, F; Cavoto, G; D'Orazio, A; del Re, D; Di Marco, E; Faccini, R; Ferrarotto, F; Ferroni, F; Gaspero, M; Jackson, P D; Li Gioi, L; Mazzoni, M A; Morganti, S; Piredda, G; Polci, F; Renga, F; Voena, C; Ebert, M; Hartmann, T; Schröder, H; Waldi, R; Adye, T; Castelli, G; Franek, B; Olaiya, E O; Ricciardi, S; Roethel, W; Wilson, F F; Aleksan, R; Emery, S; Escalier, M; Gaidot, A; Ganzhur, S F; Hamel de Monchenault, G; Kozanecki, W; Vasseur, G; Yèche, Ch; Zito, M; Chen, X R; Liu, H; Park, W; Purohit, M V; Wilson, J R; Allen, M T; Aston, D; Bartoldus, R; Bechtle, P; Berger, N; Claus, R; Coleman, J P; Convery, M R; Dingfelder, J C; Dorfan, J; Dubois-Felsmann, G P; Dunwoodie, W; Field, R C; Glanzman, T; Gowdy, S J; Graham, M T; Grenier, P; Hast, C; Hryn'ova, T; Innes, W R; Kaminski, J; Kelsey, M H; Kim, H; Kim, P; Kocian, M L; Leith, D W G S; Li, S; Luitz, S; Luth, V; Lynch, H L; MacFarlane, D B; Marsiske, H; Messner, R; Muller, D R; O'Grady, C P; Ofte, I; Perazzo, A; Perl, M; Pulliam, T; Ratcliff, B N; Roodman, A; Salnikov, A A; Schindler, R H; Schwiening, J; Snyder, A; Stelzer, J; Su, D; Sullivan, M K; Suzuki, K; Swain, S K; Thompson, J M; Va'vra, J; van Bakel, N; Wagner, A P; Weaver, M; Wisniewski, W J; Wittgen, M; Wright, D H; Yarritu, A K; Yi, K; Young, C C; Burchat, P R; Edwards, A J; Majewski, S A; Petersen, B A; Wilden, L; Ahmed, S; Alam, M S; Bula, R; Ernst, J A; Jain, V; Pan, B; Saeed, M A; Wappler, F R; Zain, S B; Bugg, W; Krishnamurthy, M; Spanier, S M; Eckmann, R; Ritchie, J L; Ruland, A M; Schilling, C J; Schwitters, R F; Izen, J M; Lou, X C; Ye, S; Bianchi, F; Gallo, F; Gamba, D; Pelliccioni, M; Bomben, M; Bosisio, L; Cartaro, C; Cossutti, F; Della Ricca, G; Lanceri, L; Vitale, L; Azzolini, V; Lopez-March, N; Martinez-Vidal, F; Milanes, D A; Oyanguren, A; Albert, J; Banerjee, Sw; Bhuyan, B; Hamano, K; Kowalewski, R; Nugent, I M; Roney, J M; Sobie, R J; Back, J J; Harrison, P F; Ilic, J; Latham, T E; Mohanty, G B; Pappagallo, M; Band, H R; Chen, X; Dasu, S; Flood, K T; Hollar, J J; Kutter, P E; Pan, Y; Pierini, M; Prepost, R; Wu, S L; Neal, H

2007-11-16

We perform an amplitude analysis of B+/--->phi(1020)K*(892)+/- decay with a sample of about 384 x 10(6) BB[over ] pairs recorded with the BABAR detector. Overall, twelve parameters are measured, including the fractions of longitudinal fL and parity-odd transverse f perpendicular amplitudes, branching fraction, strong phases, and six parameters sensitive to CP violation. We use the dependence on the Kpi invariant mass of the interference between the JP=1(-) and 0+ Kpi components to resolve the discrete ambiguity in the determination of the strong and weak phases. Our measurements of fL=0.49+/-0.05+/-0.03, f perpendicular=0.21+/-0.05+/-0.02, and the strong phases point to the presence of a substantial helicity-plus amplitude from a presently unknown source.

Study of CP asymmetry in B^{0}-B[over ¯]^{0} mixing with inclusive dilepton events.

PubMed

Lees, J P; Poireau, V; Tisserand, V; Grauges, E; Palano, A; Eigen, G; Stugu, B; Brown, D N; Kerth, L T; Kolomensky, Yu G; Lee, M J; Lynch, G; Koch, H; Schroeder, T; Hearty, C; Mattison, T S; McKenna, J A; So, R Y; Khan, A; Blinov, V E; Buzykaev, A R; Druzhinin, V P; Golubev, V B; Kravchenko, E A; Onuchin, A P; Serednyakov, S I; Skovpen, Yu I; Solodov, E P; Todyshev, K Yu; Lankford, A J; Mandelkern, M; Dey, B; Gary, J W; Long, O; Campagnari, C; Franco Sevilla, M; Hong, T M; Kovalskyi, D; Richman, J D; West, C A; Eisner, A M; Lockman, W S; Panduro Vazquez, W; Schumm, B A; Seiden, A; Chao, D S; Cheng, C H; Echenard, B; Flood, K T; Hitlin, D G; Miyashita, T S; Ongmongkolkul, P; Porter, F C; Röhrken, M; Andreassen, R; Huard, Z; Meadows, B T; Pushpawela, B G; Sokoloff, M D; Sun, L; Bloom, P C; Ford, W T; Gaz, A; Smith, J G; Wagner, S R; Ayad, R; Toki, W H; Spaan, B; Bernard, D; Verderi, M; Playfer, S; Bettoni, D; Bozzi, C; Calabrese, R; Cibinetto, G; Fioravanti, E; Garzia, I; Luppi, E; Piemontese, L; Santoro, V; Calcaterra, A; de Sangro, R; Finocchiaro, G; Martellotti, S; Patteri, P; Peruzzi, I M; Piccolo, M; Rama, M; Zallo, A; Contri, R; Lo Vetere, M; Monge, M R; Passaggio, S; Patrignani, C; Robutti, E; Bhuyan, B; Prasad, V; Adametz, A; Uwer, U; Lacker, H M; Dauncey, P D; Mallik, U; Chen, C; Cochran, J; Prell, S; Ahmed, H; Gritsan, A V; Arnaud, N; Davier, M; Derkach, D; Grosdidier, G; Le Diberder, F; Lutz, A M; Malaescu, B; Roudeau, P; Stocchi, A; Wormser, G; Lange, D J; Wright, D M; Coleman, J P; Fry, J R; Gabathuler, E; Hutchcroft, D E; Payne, D J; Touramanis, C; Bevan, A J; Di Lodovico, F; Sacco, R; Cowan, G; Bougher, J; Brown, D N; Davis, C L; Denig, A G; Fritsch, M; Gradl, W; Griessinger, K; Hafner, A; Schubert, K R; Barlow, R J; Lafferty, G D; Cenci, R; Hamilton, B; Jawahery, A; Roberts, D A; Cowan, R; Sciolla, G; Cheaib, R; Patel, P M; Robertson, S H; Neri, N; Palombo, F; Cremaldi, L; Godang, R; Sonnek, P; Summers, D J; Simard, M; Taras, P; De Nardo, G; Onorato, G; Sciacca, C; Martinelli, M; Raven, G; Jessop, C P; LoSecco, J M; Honscheid, K; Kass, R; Feltresi, E; Margoni, M; Morandin, M; Posocco, M; Rotondo, M; Simi, G; Simonetto, F; Stroili, R; Akar, S; Ben-Haim, E; Bomben, M; Bonneaud, G R; Briand, H; Calderini, G; Chauveau, J; Leruste, Ph; Marchiori, G; Ocariz, J; Biasini, M; Manoni, E; Pacetti, S; Rossi, A; Angelini, C; Batignani, G; Bettarini, S; Carpinelli, M; Casarosa, G; Cervelli, A; Chrzaszcz, M; Forti, F; Giorgi, M A; Lusiani, A; Oberhof, B; Paoloni, E; Perez, A; Rizzo, G; Walsh, J J; Lopes Pegna, D; Olsen, J; Smith, A J S; Faccini, R; Ferrarotto, F; Ferroni, F; Gaspero, M; Li Gioi, L; Pilloni, A; Piredda, G; Bünger, C; Dittrich, S; Grünberg, O; Hess, M; Leddig, T; Voß, C; Waldi, R; Adye, T; Olaiya, E O; Wilson, F F; Emery, S; Vasseur, G; Anulli, F; Aston, D; Bard, D J; Cartaro, C; Convery, M R; Dorfan, J; Dubois-Felsmann, G P; Dunwoodie, W; Ebert, M; Field, R C; Fulsom, B G; Graham, M T; Hast, C; Innes, W R; Kim, P; Leith, D W G S; Lewis, P; Lindemann, D; Luitz, S; Luth, V; Lynch, H L; MacFarlane, D B; Muller, D R; Neal, H; Perl, M; Pulliam, T; Ratcliff, B N; Roodman, A; Salnikov, A A; Schindler, R H; Snyder, A; Su, D; Sullivan, M K; Va'vra, J; Wisniewski, W J; Wulsin, H W; Purohit, M V; White, R M; Wilson, J R; Randle-Conde, A; Sekula, S J; Bellis, M; Burchat, P R; Puccio, E M T; Alam, M S; Ernst, J A; Gorodeisky, R; Guttman, N; Peimer, D R; Soffer, A; Spanier, S M; Ritchie, J L; Ruland, A M; Schwitters, R F; Wray, B C; Izen, J M; Lou, X C; Bianchi, F; De Mori, F; Filippi, A; Gamba, D; Lanceri, L; Vitale, L; Martinez-Vidal, F; Oyanguren, A; Villanueva-Perez, P; Albert, J; Banerjee, Sw; Beaulieu, A; Bernlochner, F U; Choi, H H F; King, G J; Kowalewski, R; Lewczuk, M J; Lueck, T; Nugent, I M; Roney, J M; Sobie, R J; Tasneem, N; Gershon, T J; Harrison, P F; Latham, T E; Band, H R; Dasu, S; Pan, Y; Prepost, R; Wu, S L

2015-02-27

We present a measurement of the asymmetry A_{CP} between same-sign inclusive dilepton samples ℓ^{+}ℓ^{+} and ℓ^{-}ℓ^{-} (ℓ=e, μ) from semileptonic B decays in ϒ(4S)→BB[over ¯] events, using the complete data set recorded by the BABAR experiment near the ϒ(4S) resonance, corresponding to 471×10^{6} BB[over ¯] pairs. The asymmetry A_{CP} allows comparison between the mixing probabilities P(B[over ¯]^{0}→B^{0}) and P(B^{0}→B[over ¯]^{0}), and therefore probes CP and T violation. The result, A_{CP}=[-3.9±3.5(stat)±1.9(syst)]×10^{-3}, is consistent with the standard model expectation.

Improved Measurement of the Cabibbo-Kobayashi-Maskawa Angle {alpha} Using B{sup 0}(B){yields}{rho}{sup +}{rho}{sup -} Decays

DOE Office of Scientific and Technical Information (OSTI.GOV)

Aubert, B.; Barate, R.; Boutigny, D.

2005-07-22

We present results from an analysis of B{sup 0}(B{sup 0}){yields}{rho}{sup +}{rho}{sup -} using 232x10{sup 6} {upsilon}(4S){yields}BB decays collected with the BABAR detector at the PEP-II asymmetric-energy B factory at SLAC. We measure the longitudinal polarization fraction f{sub L}=0.978{+-}0.014(stat)(+0.021/-0.029)(syst) and the CP-violating parameters S{sub L}=-0.33{+-}0.24(stat)(+0.08/-0.14)(syst) and C{sub L}=-0.03{+-}0.18(stat){+-}0.09(syst). Using an isospin analysis of B{yields}{rho}{rho} decays, we determine the unitarity triangle parameter {alpha}. The solution compatible with the standard model is {alpha}=(100{+-}13) deg.

Measurement of CP-violating asymmetries in B0 decays to CP eigenstates.

PubMed

Aubert, B; Boutigny, D; De Bonis, I; Gaillard, J M; Jeremie, A; Karyotakis, Y; Lees, J P; Robbe, P; Tisserand, V; Palano, A; Chen, G P; Chen, J C; Qi, N D; Rong, G; Wang, P; Zhu, Y S; Eigen, G; Reinertsen, P L; Stugu, B; Abbott, B; Abrams, G S; Borgland, A W; Breon, A B; Brown, D N; Button-Shafer, J; Cahn, R N; Clark, A R; Dardin, S; Day, C; Dow, S F; Elioff, T; Fan, Q; Gaponenko, I; Gill, M S; Goozen, F R; Gowdy, S J; Gritsan, A; Groysman, Y; Jacobsen, R G; Jared, R C; Kadel, R W; Kadyk, J; Karcher, A; Kerth, L T; Kipnis, I; Kluth, S; Kolomensky, Y G; Kral, J F; Lafever, R; LeClerc, C; Levi, M E; Lewis, S A; Lionberger, C; Liu, T; Long, M; Lynch, G; Marino, M; Marks, K; Meyer, A B; Mokhtarani, A; Momayezi, M; Nyman, M; Oddone, P J; Ohnemus, J; Oshatz, D; Patton, S; Perazzo, A; Peters, C; Pope, W; Pripstein, M; Quarrie, D R; Rasson, J E; Roe, N A; Romosan, A; Ronan, M T; Shelkov, V G; Stone, R; Telnov, A V; von der Lippe, H; Weber, T; Wenzel, W A; Zisman, M S; Bright-Thomas, P G; Harrison, T J; Hawkes, C M; Kirk, A; Knowles, D J; O'Neale, S W; Watson, A T; Watson, N K; Deppermann, T; Koch, H; Krug, J; Kunze, M; Lewandowski, B; Peters, K; Schmuecker, H; Steinke, M; Andress, J C; Barlow, N R; Bhimji, W; Chevalier, N; Clark, P J; Cottingham, W N; De Groot, N; Dyce, N; Foster, B; Mass, A; McFall, J D; Wallom, D; Wilson, F F; Abe, K; Hearty, C; Mattison, T S; McKenna, J A; Thiessen, D; Camanzi, B; Jolly, S; McKemey, A K; Tinslay, J; Blinov, V E; Bukin, A D; Bukin, D A; Buzykaev, A R; Dubrovin, M S; Golubev, V B; Ivanchenko, V N; Kolachev, G M; Korol, A A; Kravchenko, E A; Onuchin, A P; Salnikov, A A; Serednyakov, S I; Skovpen, Y I; Telnov, V I; Yushkov, A N; Lankford, A J; Mandelkern, M; McMahon, S; Stoker, D P; Ahsan, A; Buchanan, C; Chun, S; MacFarlane, D B; Prell, S; Rahatlou, S; Raven, G; Sharma, V; Burke, S; Campagnari, C; Dahmes, B; Hale, D; Hart, P A; Kuznetsova, N; Kyre, S; Levy, S L; Long, O; Lu, A; Richman, J D; Verkerke, W; Witherell, M; Yellin, S; Beringer, J; Dorfan, D E; Eisner, A M; Frey, A; Grillo, A A; Grothe, M; Heusch, C A; Johnson, R P; Kroeger, W; Lockman, W S; Pulliam, T; Sadrozinski, H; Schalk, T; Schmitz, R E; Schumm, B A; Seiden, A; Spencer, E N; Turri, M; Walkowiak, W; Williams, D C; Chen, E; Dubois-Felsmann, G P; Dvoretskii, A; Hanson, J E; Hitlin, D G; Metzler, S; Oyang, J; Porter, F C; Ryd, A; Samuel, A; Weaver, M; Yang, S; Zhu, R Y; Devmal, S; Geld, T L; Jayatilleke, S; Jayatilleke, S M; Mancinelli, G; Meadows, B T; Sokoloff, M D; Bloom, P; Fahey, S; Ford, W T; Gaede, F; van Hoek, W C; Johnson, D R; Michael, A K; Nauenberg, U; Olivas, A; Park, H; Rankin, P; Roy, J; Sen, S; Smith, J G; Wagner, D L; Blouw, J; Harton, J L; Krishnamurthy, M; Soffer, A; Toki, W H; Warner, D W; Wilson, R J; Zhang, J; Brandt, T; Brose, J; Colberg, T; Dahlinger, G; Dickopp, M; Dubitzky, R S; Eckstein, P; Futterschneider, H; Krause, R; Maly, E; Müller-Pfefferkorn, R; Otto, S; Schubert, K R; Schwierz, R; Spaan, B; Wilden, L; Behr, L; Bernard, D; Bonneaud, G R; Brochard, F; Cohen-Tanugi, J; Ferrag, S; Fouque, G; Gastaldi, F; Matricon, P; Mora de Freitas, P; Renard, C; Roussot, E; T'Jampens, S; Thiebaux, C; Vasileiadis, G; Verderi, M; Anjomshoaa, A; Bernet, R; Di Lodovico, F; Khan, A; Muheim, F; Playfer, S; Swain, J E; Falbo, M; Bozzi, C; Dittongo, S; Folegani, M; Piemontese, L; Treadwell, E; Anulli, F; Baldini-Ferroli, R; Calcaterra, A; de Sangro, R; Falciai, D; Finocchiaro, G; Patteri, P; Peruzzi, I M; Piccolo, M; Xie, Y; Zallo, A; Bagnasco, S; Buzzo, A; Contri, R; Crosetti, G; Lo Vetere, M; Macri, M; Monge, M R; Pallavicini, M; Passaggio, S; Pastore, F C; Patrignani, C; Pia, M G; Robutti, E; Santroni, A; Morii, M; Bartoldus, R; Dignan, T; Hamilton, R; Mallik, U; Cochran, J; Crawley, H B; Fischer, P A; Lamsa, J; McKay, R; Meyer, W T; Rosenberg, E I; Albert, J N; Beigbeder, C; Benkebil, M; Breton, D; Cizeron, R; Du, S; Grosdidier, G; Hast, C; Höcker, A; LePeltier, V; Lutz, A M; Plaszczynski, S; Schune, M H; Trincaz-Duvoid, S; Truong, K; Valassi, A; Wormser, G; Bionta, R M; Brigljević, V; Brooks, A; Fackler, O; Fujino, D; Lange, D J; Mugge, M; O'Connor, T G; Pedrotti, B; Shi, X; van Bibber, K; Wenaus, T J; Wright, D M; Wuest, C R; Yamamoto, B; Carroll, M; Fry, J R; Gabathuler, E; Gamet, R; George, M; Kay, M; Payne, D J; Sloane, R J; Touramanis, C; Aspinwall, M L; Bowerman, D A; Dauncey, P D; Egede, U; Eschrich, I; Gunawardane, N J; Martin, R; Nash, J A; Price, D R; Sanders, P; Smith, D; Azzopardi, D E; Back, J J; Dixon, P; Harrison, P F; Newman-Coburn, D; Potter, R J; Shorthouse, H W; Strother, P; Vidal, P B; Williams, M I; Cowan, G; George, S; Green, M G; Kurup, A; Marker, C E; McGrath, P; McMahon, T R; Salvatore, F; Scott, I; Vaitsas, G; Brown, D; Davis, C L; Ford, K; Li, Y; Pavlovich, J; Allison, J; Barlow, R J; Boyd, J T; Fullwood, J; Jackson, F; Lafferty, G D; Savvas, N; Simopoulos, E T; Thompson, R J; Weatherall, J H; Bard, R; Farbin, A; Jawahery, A; Lillard, V; Olsen, J; Roberts, D A; Schieck, J R; Blaylock, G; Dallapiccola, C; Flood, K T; Hertzbach, S S; Kofler, R; Lin, C S; Staengle, H; Willocq, S; Wittlin, J; Brau, B; Cowan, R; Sciolla, G; Taylor, F; Yamamoto, R K; Britton, D I; Milek, M; Patel, P M; Trischuk, J; Lanni, F; Palombo, F; Bauer, J M; Booke, M; Cremaldi, L; Eschenberg, V; Kroeger, R; Reep, M; Reidy, J; Sanders, D A; Summers, D J; Beaulieu, M; Martin, J P; Nief, J Y; Seitz, R; Taras, P; Zacek, V; Nicholson, H; Sutton, C S; Cavallo, N; Cartaro, C; De Nardo, G; Fabozzi, F; Gatto, C; Lista, L; Paolucci, P; Piccolo, D; Sciacca, C; LoSecco, J M; Alsmiller, J R; Gabriel, T A; Handler, T; Heck, J; Brau, J E; Frey, R; Iwasaki, M; Sinev, N B; Strom, D; Borsato, E; Colecchia, F; Dal Corso, F; Galeazzi, F; Margoni, M; Marzolla, M; Michelon, G; Morandin, M; Posocco, M; Rotondo, M; Simonetto, F; Stroili, R; Torassa, E; Voci, C; Bailly, P; Benayoun, M; Briand, H; Chauveau, J; David, P; De La Vaissière, C; Del Buono, L; Genat, J F; Hamon, O; Le Diberder, F; Lebbolo, H; Leruste, P; Lory, J; Martin, L; Roos, L; Stark, J; Versillé, S; Zhang, B; Manfredi, P F; Ratti, L; Re, V; Speziali, V; Frank, E D; Gladney, L; Guo, Q H; Panetta, J H; Angelini, C; Batignani, G; Bettarini, S; Bondioli, M; Bosi, F; Carpinelli, M; Forti, F; Giorgi, M A; Lusiani, A; Martinez-Vidal, F; Morganti, M; Neri, N; Paoloni, E; Rama, M; Rizzo, G; Sandrelli, F; Simi, G; Triggiani, G; Walsh, J; Hairre, M; Judd, D; Paick, K; Turnbull, L; Wagoner, D E; Albert, J; Bula, C; Fernholz, R; Lu, C; McDonald, K T; Miftakov, V; Sands, B; Schaffner, S F; Smith, A J; Tumanov, A; Varnes, E W; Bronzini, F; Buccheri, A; Bulfon, C; Cavoto, G; del Re, D; Faccini, R; Ferrarotto, F; Ferroni, F; Fratini, K; Lamanna, E; Leonardi, E; Mazzoni, M A; Morganti, S; Piredda, G; Safai Tehrani, F; Serra, M; Voena, C; Waldi, R; Jacques, P F; Kalelkar, M; Plano, R J; Adye, T; Claxton, B; Franek, B; Galagedera, S; Geddes, N I; Gopal, G P; Lidbury, J; Xella, S M; Aleksan, R; Besson, P; Bourgeois, P; De Domenico, G; Emery, S; Gaidot, A; Ganzhur, S F; Gosset, L; Hamel de Monchenault, G; Kozanecki, W; Langer, M; London, G W; Mayer, B; Serfass, B; Vasseur, G; Yeche, C; Zito, M; Copty, N; Purohit, M V; Singh, H; Yumiceva, F X; Adam, I; Anthony, P L; Aston, D; Baird, K; Bartelt, J; Becla, J; Bell, R; Bloom, E; Boeheim, C T; Boyarski, A M; Boyce, R F; Bulos, F; Burgess, W; Byers, B; Calderini, G; Claus, R; Convery, M R; Coombes, R; Cottrell, L; Coupal, D P; Coward, D H; Craddock, W W; DeStaebler, H; Dorfan, J; Doser, M; Dunwoodie, W; Ecklund, S; Fieguth, T H; Field, R C; Freytag, D R; Glanzman, T; Godfrey, G L; Grosso, P; Haller, G; Hanushevsky, A; Harris, J; Hasan, A; Hewett, J L; Himel, T; Huffer, M E; Innes, W R; Jessop, C P; Kawahara, H; Keller, L; Kelsey, M H; Kim, P; Klaisner, L A; Kocian, M L; Krebs, H J; Kunz, P F; Langenegger, U; Langeveld, W; Leith, D W; Louie, S K; Luitz, S; Luth, V; Lynch, H L; MacDonald, J; Manzin, G; Mariske, H; McCulloch, M; McShurley, D; Menke, S; Messner, R; Metcalfe, S; Moffeit, K C; Mount, R; Muller, D R; Nelson, D; Nordby, M; O'Grady, C P; O'Neill, F G; Oxoby, G; Pavel, T; Perl, J; Petrak, S; Putallaz, G; Quinn, H; Raines, P E; Ratcliff, B N; Reif, R; Robertson, S H; Rochester, L S; Roodman, A; Russell, J J; Sapozhnikov, L; Saxton, O H; Schietinger, T; Schindler, R H; Schwiening, J; Seeman, J T; Serbo, V V; Skarpass, K; Snyder, A; Soha, A; Spanier, S M; Stahl, A; Stelzer, J; Su, D; Sullivan, M K; Talby, M; Tanaka, H A; Va'vra, J; Wagner, S R; Weinstein, A J; White, J L; Wienands, U; Wisniewski, W J; Young, C C; Zioulas, G; Burchat, P R; Cheng, C H; Kirkby, D; Meyer, T I; Roat, C; De Silva, A; Henderson, R; Berridge, S; Bugg, W; Cohn, H; Hart, E; Weidemann, A W; Benninger, T; Izen, J M; Kitayama, I; Lou, X C; Turcotte, M; Bianchi, F; Bona, M; Di Girolamo, B; Gamba, D; Smol, A; Zanin, D; Bosisio, L; Della Ricca, G; Lanceri, L; Pompili, A; Poropat, P; Vuagnin, G; Panvini, R S; Brown, C M; Kowalewski, R; Roney, J M; Band, H R; Charles, E; Dasu, S; Elmer, P; Hu, H; Johnson, J R; Nielsen, J; Orejudos, W; Pan, Y; Prepost, R; Scott, I J; von Wimmersperg-Toeller, J H; Wu, S L; Yu, Z; Zobernig, H; Kordich, T M; Moore, T B; Neal, H

2001-03-19

We present measurements of time-dependent CP-violating asymmetries in neutral B decays to several CP eigenstates. The measurement uses a data sample of 23x10(6) Upsilon(4S)-->BbarB decays collected by the BABAR detector at the PEP-II asymmetric B Factory at SLAC. In this sample, we find events in which one neutral B meson is fully reconstructed in a CP eigenstate containing charmonium and the flavor of the other neutral B meson is determined from its decay products. The amplitude of the CP-violating asymmetry, which in the standard model is proportional to sin2beta, is derived from the decay time distributions in such events. The result is sin2beta = 0.34+/-0.20 (stat)+/-0.05 (syst).

DsJ(2860) as the First Radial Excitation of Ds0*(2317)

NASA Astrophysics Data System (ADS)

van Beveren, Eef; Rupp, George

2006-11-01

A coupled-channel model previously employed to describe the narrow Ds0*(2317) and broad D0*(2400) charmed scalar mesons is generalized so as to include all ground-state pseudoscalar-pseudoscalar and vector-vector two-meson channels. All parameters are chosen fixed at published values, except for the overall coupling constant, which is fine-tuned to reproduce the Ds0*(2317) mass. Thus, the radial excitations Ds0*(2850) and D0*(2740) are predicted, both with a width of about 50 MeV. The former state appears to correspond to the new DsJ(2860) resonance decaying to DK announced by BABAR in the course of this work. Also, the D0*(2400) resonance is roughly reproduced, though perhaps with a somewhat too low central resonance peak.

Astronaut Photography of the Earth: A Long-Term Dataset for Earth Systems Research, Applications, and Education

NASA Technical Reports Server (NTRS)

Stefanov, William L.

2017-01-01

The NASA Earth observations dataset obtained by humans in orbit using handheld film and digital cameras is freely accessible to the global community through the online searchable database at https://eol.jsc.nasa.gov, and offers a useful compliment to traditional ground-commanded sensor data. The dataset includes imagery from the NASA Mercury (1961) through present-day International Space Station (ISS) programs, and currently totals over 2.6 million individual frames. Geographic coverage of the dataset includes land and oceans areas between approximately 52 degrees North and South latitudes, but is spatially and temporally discontinuous. The photographic dataset includes some significant impediments for immediate research, applied, and educational use: commercial RGB films and camera systems with overlapping bandpasses; use of different focal length lenses, unconstrained look angles, and variable spacecraft altitudes; and no native geolocation information. Such factors led to this dataset being underutilized by the community but recent advances in automated and semi-automated image geolocation, image feature classification, and web-based services are adding new value to the astronaut-acquired imagery. A coupled ground software and on-orbit hardware system for the ISS is in development for planned deployment in mid-2017; this system will capture camera pose information for each astronaut photograph to allow automated, full georegistration of the data. The ground system component of the system is currently in use to fully georeference imagery collected in response to International Disaster Charter activations, and the auto-registration procedures are being applied to the extensive historical database of imagery to add value for research and educational purposes. In parallel, machine learning techniques are being applied to automate feature identification and classification throughout the dataset, in order to build descriptive metadata that will improve search capabilities. It is expected that these value additions will increase interest and use of the dataset by the global community.

Human3.6M: Large Scale Datasets and Predictive Methods for 3D Human Sensing in Natural Environments.

PubMed

Ionescu, Catalin; Papava, Dragos; Olaru, Vlad; Sminchisescu, Cristian

2014-07-01

We introduce a new dataset, Human3.6M, of 3.6 Million accurate 3D Human poses, acquired by recording the performance of 5 female and 6 male subjects, under 4 different viewpoints, for training realistic human sensing systems and for evaluating the next generation of human pose estimation models and algorithms. Besides increasing the size of the datasets in the current state-of-the-art by several orders of magnitude, we also aim to complement such datasets with a diverse set of motions and poses encountered as part of typical human activities (taking photos, talking on the phone, posing, greeting, eating, etc.), with additional synchronized image, human motion capture, and time of flight (depth) data, and with accurate 3D body scans of all the subject actors involved. We also provide controlled mixed reality evaluation scenarios where 3D human models are animated using motion capture and inserted using correct 3D geometry, in complex real environments, viewed with moving cameras, and under occlusion. Finally, we provide a set of large-scale statistical models and detailed evaluation baselines for the dataset illustrating its diversity and the scope for improvement by future work in the research community. Our experiments show that our best large-scale model can leverage our full training set to obtain a 20% improvement in performance compared to a training set of the scale of the largest existing public dataset for this problem. Yet the potential for improvement by leveraging higher capacity, more complex models with our large dataset, is substantially vaster and should stimulate future research. The dataset together with code for the associated large-scale learning models, features, visualization tools, as well as the evaluation server, is available online at http://vision.imar.ro/human3.6m.

Quantifying the accuracy of the tumor motion and area as a function of acceleration factor for the simulation of the dynamic keyhole magnetic resonance imaging method.

PubMed

Lee, Danny; Greer, Peter B; Pollock, Sean; Kim, Taeho; Keall, Paul

2016-05-01

The dynamic keyhole is a new MR image reconstruction method for thoracic and abdominal MR imaging. To date, this method has not been investigated with cancer patient magnetic resonance imaging (MRI) data. The goal of this study was to assess the dynamic keyhole method for the task of lung tumor localization using cine-MR images reconstructed in the presence of respiratory motion. The dynamic keyhole method utilizes a previously acquired a library of peripheral k-space datasets at similar displacement and phase (where phase is simply used to determine whether the breathing is inhale to exhale or exhale to inhale) respiratory bins in conjunction with central k-space datasets (keyhole) acquired. External respiratory signals drive the process of sorting, matching, and combining the two k-space streams for each respiratory bin, thereby achieving faster image acquisition without substantial motion artifacts. This study was the first that investigates the impact of k-space undersampling on lung tumor motion and area assessment across clinically available techniques (zero-filling and conventional keyhole). In this study, the dynamic keyhole, conventional keyhole and zero-filling methods were compared to full k-space dataset acquisition by quantifying (1) the keyhole size required for central k-space datasets for constant image quality across sixty four cine-MRI datasets from nine lung cancer patients, (2) the intensity difference between the original and reconstructed images in a constant keyhole size, and (3) the accuracy of tumor motion and area directly measured by tumor autocontouring. For constant image quality, the dynamic keyhole method, conventional keyhole, and zero-filling methods required 22%, 34%, and 49% of the keyhole size (P < 0.0001), respectively, compared to the full k-space image acquisition method. Compared to the conventional keyhole and zero-filling reconstructed images with the keyhole size utilized in the dynamic keyhole method, an average intensity difference of the dynamic keyhole reconstructed images (P < 0.0001) was minimal, and resulted in the accuracy of tumor motion within 99.6% (P < 0.0001) and the accuracy of tumor area within 98.0% (P < 0.0001) for lung tumor monitoring applications. This study demonstrates that the dynamic keyhole method is a promising technique for clinical applications such as image-guided radiation therapy requiring the MR monitoring of thoracic tumors. Based on the results from this study, the dynamic keyhole method could increase the imaging frequency by up to a factor of five compared with full k-space methods for real-time lung tumor MRI.

Comparison of CORA and EN4 in-situ datasets validation methods, toward a better quality merged dataset.

NASA Astrophysics Data System (ADS)

Szekely, Tanguy; Killick, Rachel; Gourrion, Jerome; Reverdin, Gilles

2017-04-01

CORA and EN4 are both global delayed time mode validated in-situ ocean temperature and salinity datasets distributed by the Met Office (http://www.metoffice.gov.uk/) and Copernicus (www.marine.copernicus.eu). A large part of the profiles distributed by CORA and EN4 in recent years are Argo profiles from the ARGO DAC, but profiles are also extracted from the World Ocean Database and TESAC profiles from GTSPP. In the case of CORA, data coming from the EUROGOOS Regional operationnal oserving system( ROOS) operated by European institutes no managed by National Data Centres and other datasets of profiles povided by scientific sources can also be found (Sea mammals profiles from MEOP, XBT datasets from cruises ...). (EN4 also takes data from the ASBO dataset to supplement observations in the Arctic). First advantage of this new merge product is to enhance the space and time coverage at global and european scales for the period covering 1950 till a year before the current year. This product is updated once a year and T&S gridded fields are alos generated for the period 1990-year n-1. The enhancement compared to the revious CORA product will be presented Despite the fact that the profiles distributed by both datasets are mostly the same, the quality control procedures developed by the Met Office and Copernicus teams differ, sometimes leading to different quality control flags for the same profile. Started in 2016 a new study started that aims to compare both validation procedures to move towards a Copernicus Marine Service dataset with the best features of CORA and EN4 validation.A reference data set composed of the full set of in-situ temperature and salinity measurements collected by Coriolis during 2015 is used. These measurements have been made thanks to wide range of instruments (XBTs, CTDs, Argo floats, Instrumented sea mammals,...), covering the global ocean. The reference dataset has been validated simultaneously by both teams.An exhaustive comparison of the validation test results is now performed to find the best features of both datasets. The study shows the differences between the EN4 and CORA validation results. It highlights the complementarity between the EN4 and CORA higher order tests. The design of the CORA and EN4 validation charts is discussed to understand how a different approach on the dataset scope can lead to differences in data validation. The new validation chart of the Copernicus Marine Service dataset is presented.

Evaluating new SMAP soil moisture for drought monitoring in the rangelands of the US High Plains

USGS Publications Warehouse

Velpuri, Naga Manohar; Senay, Gabriel B.; Morisette, Jeffrey T.

2016-01-01

Level 3 soil moisture datasets from the recently launched Soil Moisture Active Passive (SMAP) satellite are evaluated for drought monitoring in rangelands.Validation of SMAP soil moisture (SSM) with in situ and modeled estimates showed high level of agreement.SSM showed the highest correlation with surface soil moisture (0-5 cm) and a strong correlation to depths up to 20 cm.SSM showed a reliable and expected response of capturing seasonal dynamics in relation to precipitation, land surface temperature, and evapotranspiration.Further evaluation using multi-year SMAP datasets is necessary to quantify the full benefits and limitations for drought monitoring in rangelands.

Entropy-based heavy tailed distribution transformation and visual analytics for monitoring massive network traffic

NASA Astrophysics Data System (ADS)

Han, Keesook J.; Hodge, Matthew; Ross, Virginia W.

2011-06-01

For monitoring network traffic, there is an enormous cost in collecting, storing, and analyzing network traffic datasets. Data mining based network traffic analysis has a growing interest in the cyber security community, but is computationally expensive for finding correlations between attributes in massive network traffic datasets. To lower the cost and reduce computational complexity, it is desirable to perform feasible statistical processing on effective reduced datasets instead of on the original full datasets. Because of the dynamic behavior of network traffic, traffic traces exhibit mixtures of heavy tailed statistical distributions or overdispersion. Heavy tailed network traffic characterization and visualization are important and essential tasks to measure network performance for the Quality of Services. However, heavy tailed distributions are limited in their ability to characterize real-time network traffic due to the difficulty of parameter estimation. The Entropy-Based Heavy Tailed Distribution Transformation (EHTDT) was developed to convert the heavy tailed distribution into a transformed distribution to find the linear approximation. The EHTDT linearization has the advantage of being amenable to characterize and aggregate overdispersion of network traffic in realtime. Results of applying the EHTDT for innovative visual analytics to real network traffic data are presented.

Inter-fraction variations in respiratory motion models

NASA Astrophysics Data System (ADS)

McClelland, J. R.; Hughes, S.; Modat, M.; Qureshi, A.; Ahmad, S.; Landau, D. B.; Ourselin, S.; Hawkes, D. J.

2011-01-01

Respiratory motion can vary dramatically between the planning stage and the different fractions of radiotherapy treatment. Motion predictions used when constructing the radiotherapy plan may be unsuitable for later fractions of treatment. This paper presents a methodology for constructing patient-specific respiratory motion models and uses these models to evaluate and analyse the inter-fraction variations in the respiratory motion. The internal respiratory motion is determined from the deformable registration of Cine CT data and related to a respiratory surrogate signal derived from 3D skin surface data. Three different models for relating the internal motion to the surrogate signal have been investigated in this work. Data were acquired from six lung cancer patients. Two full datasets were acquired for each patient, one before the course of radiotherapy treatment and one at the end (approximately 6 weeks later). Separate models were built for each dataset. All models could accurately predict the respiratory motion in the same dataset, but had large errors when predicting the motion in the other dataset. Analysis of the inter-fraction variations revealed that most variations were spatially varying base-line shifts, but changes to the anatomy and the motion trajectories were also observed.

neXtA5: accelerating annotation of articles via automated approaches in neXtProt.

PubMed

Mottin, Luc; Gobeill, Julien; Pasche, Emilie; Michel, Pierre-André; Cusin, Isabelle; Gaudet, Pascale; Ruch, Patrick

2016-01-01

The rapid increase in the number of published articles poses a challenge for curated databases to remain up-to-date. To help the scientific community and database curators deal with this issue, we have developed an application, neXtA5, which prioritizes the literature for specific curation requirements. Our system, neXtA5, is a curation service composed of three main elements. The first component is a named-entity recognition module, which annotates MEDLINE over some predefined axes. This report focuses on three axes: Diseases, the Molecular Function and Biological Process sub-ontologies of the Gene Ontology (GO). The automatic annotations are then stored in a local database, BioMed, for each annotation axis. Additional entities such as species and chemical compounds are also identified. The second component is an existing search engine, which retrieves the most relevant MEDLINE records for any given query. The third component uses the content of BioMed to generate an axis-specific ranking, which takes into account the density of named-entities as stored in the Biomed database. The two ranked lists are ultimately merged using a linear combination, which has been specifically tuned to support the annotation of each axis. The fine-tuning of the coefficients is formally reported for each axis-driven search. Compared with PubMed, which is the system used by most curators, the improvement is the following: +231% for Diseases, +236% for Molecular Functions and +3153% for Biological Process when measuring the precision of the top-returned PMID (P0 or mean reciprocal rank). The current search methods significantly improve the search effectiveness of curators for three important curation axes. Further experiments are being performed to extend the curation types, in particular protein-protein interactions, which require specific relationship extraction capabilities. In parallel, user-friendly interfaces powered with a set of JSON web services are currently being implemented into the neXtProt annotation pipeline.Available on: http://babar.unige.ch:8082/neXtA5Database URL: http://babar.unige.ch:8082/neXtA5/fetcher.jsp. © The Author(s) 2016. Published by Oxford University Press.

neXtA5: accelerating annotation of articles via automated approaches in neXtProt

PubMed Central

Mottin, Luc; Gobeill, Julien; Pasche, Emilie; Michel, Pierre-André; Cusin, Isabelle; Gaudet, Pascale; Ruch, Patrick

2016-01-01

The rapid increase in the number of published articles poses a challenge for curated databases to remain up-to-date. To help the scientific community and database curators deal with this issue, we have developed an application, neXtA5, which prioritizes the literature for specific curation requirements. Our system, neXtA5, is a curation service composed of three main elements. The first component is a named-entity recognition module, which annotates MEDLINE over some predefined axes. This report focuses on three axes: Diseases, the Molecular Function and Biological Process sub-ontologies of the Gene Ontology (GO). The automatic annotations are then stored in a local database, BioMed, for each annotation axis. Additional entities such as species and chemical compounds are also identified. The second component is an existing search engine, which retrieves the most relevant MEDLINE records for any given query. The third component uses the content of BioMed to generate an axis-specific ranking, which takes into account the density of named-entities as stored in the Biomed database. The two ranked lists are ultimately merged using a linear combination, which has been specifically tuned to support the annotation of each axis. The fine-tuning of the coefficients is formally reported for each axis-driven search. Compared with PubMed, which is the system used by most curators, the improvement is the following: +231% for Diseases, +236% for Molecular Functions and +3153% for Biological Process when measuring the precision of the top-returned PMID (P0 or mean reciprocal rank). The current search methods significantly improve the search effectiveness of curators for three important curation axes. Further experiments are being performed to extend the curation types, in particular protein–protein interactions, which require specific relationship extraction capabilities. In parallel, user-friendly interfaces powered with a set of JSON web services are currently being implemented into the neXtProt annotation pipeline. Available on: http://babar.unige.ch:8082/neXtA5 Database URL: http://babar.unige.ch:8082/neXtA5/fetcher.jsp PMID:27374119

CANFAR + Skytree: Mining Massive Datasets as an Essential Part of the Future of Astronomy

NASA Astrophysics Data System (ADS)

Ball, Nicholas M.

2013-01-01

The future study of large astronomical datasets, consisting of hundreds of millions to billions of objects, will be dominated by large computing resources, and by analysis tools of the necessary scalability and sophistication to extract useful information. Significant effort will be required to fulfil their potential as a provider of the next generation of science results. To-date, computing systems have allowed either sophisticated analysis of small datasets, e.g., most astronomy software, or simple analysis of large datasets, e.g., database queries. At the Canadian Astronomy Data Centre, we have combined our cloud computing system, the Canadian Advanced Network for Astronomical Research (CANFAR), with the world's most advanced machine learning software, Skytree, to create the world's first cloud computing system for data mining in astronomy. This allows the full sophistication of the huge fields of data mining and machine learning to be applied to the hundreds of millions of objects that make up current large datasets. CANFAR works by utilizing virtual machines, which appear to the user as equivalent to a desktop. Each machine is replicated as desired to perform large-scale parallel processing. Such an arrangement carries far more flexibility than other cloud systems, because it enables the user to immediately install and run the same code that they already utilize for science on their desktop. We demonstrate the utility of the CANFAR + Skytree system by showing science results obtained, including assigning photometric redshifts with full probability density functions (PDFs) to a catalog of approximately 133 million galaxies from the MegaPipe reductions of the Canada-France-Hawaii Telescope Legacy Wide and Deep surveys. Each PDF is produced nonparametrically from 100 instances of the photometric parameters for each galaxy, generated by perturbing within the errors on the measurements. Hence, we produce, store, and assign redshifts to, a catalog of over 13 billion object instances. This catalog is comparable in size to those expected from next-generation surveys, such as Large Synoptic Survey Telescope. The CANFAR+Skytree system is open for use by any interested member of the astronomical community.

Large-scale seismic waveform quality metric calculation using Hadoop

NASA Astrophysics Data System (ADS)

Magana-Zook, S.; Gaylord, J. M.; Knapp, D. R.; Dodge, D. A.; Ruppert, S. D.

2016-09-01

In this work we investigated the suitability of Hadoop MapReduce and Apache Spark for large-scale computation of seismic waveform quality metrics by comparing their performance with that of a traditional distributed implementation. The Incorporated Research Institutions for Seismology (IRIS) Data Management Center (DMC) provided 43 terabytes of broadband waveform data of which 5.1 TB of data were processed with the traditional architecture, and the full 43 TB were processed using MapReduce and Spark. Maximum performance of 0.56 terabytes per hour was achieved using all 5 nodes of the traditional implementation. We noted that I/O dominated processing, and that I/O performance was deteriorating with the addition of the 5th node. Data collected from this experiment provided the baseline against which the Hadoop results were compared. Next, we processed the full 43 TB dataset using both MapReduce and Apache Spark on our 18-node Hadoop cluster. These experiments were conducted multiple times with various subsets of the data so that we could build models to predict performance as a function of dataset size. We found that both MapReduce and Spark significantly outperformed the traditional reference implementation. At a dataset size of 5.1 terabytes, both Spark and MapReduce were about 15 times faster than the reference implementation. Furthermore, our performance models predict that for a dataset of 350 terabytes, Spark running on a 100-node cluster would be about 265 times faster than the reference implementation. We do not expect that the reference implementation deployed on a 100-node cluster would perform significantly better than on the 5-node cluster because the I/O performance cannot be made to scale. Finally, we note that although Big Data technologies clearly provide a way to process seismic waveform datasets in a high-performance and scalable manner, the technology is still rapidly changing, requires a high degree of investment in personnel, and will likely require significant changes in other parts of our infrastructure. Nevertheless, we anticipate that as the technology matures and third-party tool vendors make it easier to manage and operate clusters, Hadoop (or a successor) will play a large role in our seismic data processing.

NCAR's Research Data Archive: OPeNDAP Access for Complex Datasets

NASA Astrophysics Data System (ADS)

Dattore, R.; Worley, S. J.

2014-12-01

Many datasets have complex structures including hundreds of parameters and numerous vertical levels, grid resolutions, and temporal products. Making these data accessible is a challenge for a data provider. OPeNDAP is powerful protocol for delivering in real-time multi-file datasets that can be ingested by many analysis and visualization tools, but for these datasets there are too many choices about how to aggregate. Simple aggregation schemes can fail to support, or at least make it very challenging, for many potential studies based on complex datasets. We address this issue by using a rich file content metadata collection to create a real-time customized OPeNDAP service to match the full suite of access possibilities for complex datasets. The Climate Forecast System Reanalysis (CFSR) and it's extension, the Climate Forecast System Version 2 (CFSv2) datasets produced by the National Centers for Environmental Prediction (NCEP) and hosted by the Research Data Archive (RDA) at the Computational and Information Systems Laboratory (CISL) at NCAR are examples of complex datasets that are difficult to aggregate with existing data server software. CFSR and CFSv2 contain 141 distinct parameters on 152 vertical levels, six grid resolutions and 36 products (analyses, n-hour forecasts, multi-hour averages, etc.) where not all parameter/level combinations are available at all grid resolution/product combinations. These data are archived in the RDA with the data structure provided by the producer; no additional re-organization or aggregation have been applied. Since 2011, users have been able to request customized subsets (e.g. - temporal, parameter, spatial) from the CFSR/CFSv2, which are processed in delayed-mode and then downloaded to a user's system. Until now, the complexity has made it difficult to provide real-time OPeNDAP access to the data. We have developed a service that leverages the already-existing subsetting interface and allows users to create a virtual dataset with its own structure (das, dds). The user receives a URL to the customized dataset that can be used by existing tools to ingest, analyze, and visualize the data. This presentation will detail the metadata system and OPeNDAP server that enable user-customized real-time access and show an example of how a visualization tool can access the data.

Evaluation of in vitro models for predicting acidosis risk of barley grain in finishing beef cattle.

PubMed

Anele, U Y; Swift, M-L; McAllister, T A; Galyean, M L; Yang, W Z

2015-10-01

Our objective was to develop a model to predict the acidosis potential of barley based on the in vitro batch culture incubation of 50 samples varying in bulk density, starch content, processing method, growing location, and agronomic practices. The model was an adaptation of the acidosis index (calculated from a combination of in situ and in vitro analyses and from several components of grain chemical composition) developed in Australia for use in the feed industry to estimate the potential for grains to increase the risk of ruminal acidosis. Of the independent variables considered, DM disappearance at 6 h of incubation (DMD6) using reduced-strength (20%) buffer in the batch culture accounted for 90.5% of the variation in the acidosis index with a root mean square error (RMSE) of 4.46%. To evaluate our model using independent datasets (derived from previous batch culture studies using full-strength [100%] buffer), we performed another batch culture study using full-strength buffer. The full-strength buffer model using in vitro DMD6 (DMD6-FS) accounted for 66.5% of the variation in the acidosis index with an RMSE of 8.30%. When the new full-strength buffer model was applied to 3 independent datasets to predict acidosis, it accounted for 20.1, 28.5, and 30.2% of the variation in the calculated acidosis index. Significant ( < 0.001) mean bias was evident in 2 of the datasets, for which the DMD6 model underpredicted the acidosis index by 46.9 and 5.73%. Ranking of samples from the most diverse independent dataset using the DMD6-FS model and the Black (2008) model (calculated using in situ starch degradation) indicated the relationship between the rankings using Spearman's rank correlation was negative (ρ = -0.30; = 0.059). When the reduced-strength buffer model was used, however, there were similarities in the acidosis index ranking of barley samples by the models as shown by the result of a correlation analysis between calculated (using the Australian model) and predicted (using the reduced-strength buffer DMD6 model) acidosis index (ρ = 0.67; < 0.001). Results suggest that our model, which is based on a reduced-strength buffer in vitro DMD6, has the potential to predict acidosis risk and can rank barley samples based on their acidotic risk. Nonetheless, the model would benefit from further refinement by expanding the database.

Collection, processing, and quality assurance of time-series electromagnetic-induction log datasets, 1995–2016, south Florida

USGS Publications Warehouse

Prinos, Scott T.; Valderrama, Robert

2016-12-13

Time-series electromagnetic-induction log (TSEMIL) datasets are collected from polyvinyl-chloride cased or uncased monitoring wells to evaluate changes in water conductivity over time. TSEMIL datasets consist of a series of individual electromagnetic-induction logs, generally collected at a frequency of once per month or once per year that have been compiled into a dataset by eliminating small uniform offsets in bulk conductivity between logs probably caused by minor variations in calibration. These offsets are removed by selecting a depth at which no changes are apparent from year to year, and by adjusting individual logs to the median of all logs at the selected depth. Generally, the selected depths are within the freshwater saturated part of the aquifer, well below the water table. TSEMIL datasets can be used to monitor changes in water conductivity throughout the full thickness of an aquifer, without the need for long open-interval wells which have, in some instances, allowed vertical water flow within the well bore that has biased water conductivity profiles. The TSEMIL dataset compilation process enhances the ability to identify small differences between logs that were otherwise obscured by the offsets. As a result of TSEMIL dataset compilation, the root mean squared error of the linear regression between bulk conductivity of the electromagnetic-induction log measurements and the chloride concentration of water samples decreased from 17.4 to 1.7 millisiemens per meter in well G–3611 and from 3.7 to 2.2 millisiemens per meter in well G–3609. The primary use of the TSEMIL datasets in south Florida is to detect temporal changes in bulk conductivity associated with saltwater intrusion in the aquifer; however, other commonly observed changes include (1) variations in bulk conductivity near the water table where water saturation of pore spaces might vary and water temperature might be more variable, and (2) dissipation of conductive water in high-porosity rock layers, which might have entered these layers during drilling. Although TSEMIL dataset processing of even a few logs improves evaluations of the differences between the logs that are related to changes in the salinity, about 16 logs are needed to estimate the bulk conductivity within ±2 millisiemens per meter. Unlike many other types of data published by the U.S. Geological Survey, the median of TSEMIL datasets should not be considered final until 16 logs are collected and the median of the dataset is stable.

Search for D0-D(-)0 mixing and a measurement of the doubly Cabibbo-suppressed decay rate in D0-->Kpi decays.

PubMed

Aubert, B; Barate, R; Boutigny, D; Gaillard, J-M; Hicheur, A; Karyotakis, Y; Lees, J P; Robbe, P; Tisserand, V; Zghiche, A; Palano, A; Pompili, A; Chen, J C; Qi, N D; Rong, G; Wang, P; Zhu, Y S; Eigen, G; Ofte, I; Stugu, B; Abrams, G S; Borgland, A W; Breon, A B; Brown, D N; Button-Shafer, J; Cahn, R N; Charles, E; Day, C T; Gill, M S; Gritsan, A V; Groysman, Y; Jacobsen, R G; Kadel, R W; Kadyk, J; Kerth, L T; Kolomensky, Yu G; Kral, J F; Kukartsev, G; LeClerc, C; Levi, M E; Lynch, G; Mir, L M; Oddone, P J; Orimoto, T J; Pripstein, M; Roe, N A; Romosan, A; Ronan, M T; Shelkov, V G; Telnov, A V; Wenzel, W A; Harrison, T J; Hawkes, C M; Knowles, D J; Penny, R C; Watson, A T; Watson, N K; Deppermann, T; Goetzen, K; Koch, H; Lewandowski, B; Pelizaeus, M; Peters, K; Schmuecker, H; Steinke, M; Barlow, N R; Bhimji, W; Boyd, J T; Chevalier, N; Cottingham, W N; Mackay, C; Wilson, F F; Hearty, C; Mattison, T S; McKenna, J A; Thiessen, D; Kyberd, P; McKemey, A K; Blinov, V E; Bukin, A D; Golubev, V B; Ivanchenko, V N; Kravchenko, E A; Onuchin, A P; Serednyakov, S I; Skovpen, Yu I; Solodov, E P; Yushkov, A N; Best, D; Chao, M; Kirkby, D; Lankford, A J; Mandelkern, M; McMahon, S; Mommsen, R K; Roethel, W; Stoker, D P; Buchanan, C; Hadavand, H K; Hill, E J; MacFarlane, D B; Paar, H P; Rahatlou, Sh; Schwanke, U; Sharma, V; Berryhill, J W; Campagnari, C; Dahmes, B; Kuznetsova, N; Levy, S L; Long, O; Lu, A; Mazur, M A; Richman, J D; Verkerke, W; Beringer, J; Eisner, A M; Grothe, M; Heusch, C A; Lockman, W S; Schalk, T; Schmitz, R E; Schumm, B A; Seiden, A; Turri, M; Walkowiak, W; Williams, D C; Wilson, M G; Albert, J; Chen, E; Dorsten, M P; Dubois-Felsmann, G P; Dvoretskii, A; Hitlin, D G; Narsky, I; Porter, F C; Ryd, A; Samuel, A; Yang, S; Jayatilleke, S; Mancinelli, G; Meadows, B T; Sokoloff, M D; Barillari, T; Blanc, F; Bloom, P; Clark, P J; Ford, W T; Nauenberg, U; Olivas, A; Rankin, P; Roy, J; Smith, J G; van Hoek, W C; Zhang, L; Harton, J L; Hu, T; Soffer, A; Toki, W H; Wilson, R J; Zhang, J; Altenburg, D; Brandt, T; Brose, J; Colberg, T; Dickopp, M; Dubitzky, R S; Hauke, A; Lacker, H M; Maly, E; Müller-Pfefferkorn, R; Nogowski, R; Otto, S; Schubert, K R; Schwierz, R; Spaan, B; Wilden, L; Bernard, D; Bonneaud, G R; Brochard, F; Cohen-Tanugi, J; Thiebaux, Ch; Vasileiadis, G; Verderi, M; Khan, A; Lavin, D; Muheim, F; Playfer, S; Swain, J E; Tinslay, J; Bozzi, C; Piemontese, L; Sarti, A; Treadwell, E; Anulli, F; Baldini-Ferroli, R; Calcaterra, A; de Sangro, R; Falciai, D; Finocchiaro, G; Patteri, P; Peruzzi, I M; Piccolo, M; Zallo, A; Buzzo, A; Contri, R; Crosetti, G; Lo Vetere, M; Macri, M; Monge, M R; Passaggio, S; Pastore, F C; Patrignani, C; Robutti, E; Santroni, A; Tosi, S; Bailey, S; Morii, M; Grenier, G J; Lee, S-J; Mallik, U; Cochran, J; Crawley, H B; Lamsa, J; Meyer, W T; Prell, S; Rosenberg, E I; Yi, J; Davier, M; Grosdidier, G; Höcker, A; Laplace, S; Le Diberder, F; Lepeltier, V; Lutz, A M; Petersen, T C; Plaszczynski, S; Schune, M H; Tantot, L; Wormser, G; Bionta, R M; Brigljević, V; Cheng, C H; Lange, D J; Wright, D M; Bevan, A J; Fry, J R; Gabathuler, E; Gamet, R; Kay, M; Payne, D J; Sloane, R J; Touramanis, C; Aspinwall, M L; Bowerman, D A; Dauncey, P D; Egede, U; Eschrich, I; Morton, G W; Nash, J A; Sanders, P; Taylor, G P; Back, J J; Bellodi, G; Harrison, P F; Shorthouse, H W; Strother, P; Vidal, P B; Cowan, G; Flaecher, H U; George, S; Green, M G; Kurup, A; Marker, C E; McMahon, T R; Ricciardi, S; Salvatore, F; Vaitsas, G; Winter, M A; Brown, D; Davis, C L; Allison, J; Barlow, R J; Forti, A C; Hart, P A; Jackson, F; Lafferty, G D; Lyon, A J; Weatherall, J H; Williams, J C; Farbin, A; Jawahery, A; Kovalskyi, D; Lae, C K; Lillard, V; Roberts, D A; Blaylock, G; Dallapiccola, C; Flood, K T; Hertzbach, S S; Kofler, R; Koptchev, V B; Moore, T B; Staengle, H; Willocq, S; Cowan, R; Sciolla, G; Taylor, F; Yamamoto, R K; Mangeol, D J J; Milek, M; Patel, P M; Lazzaro, A; Palombo, F; Bauer, J M; Cremaldi, L; Eschenburg, V; Godang, R; Kroeger, R; Reidy, J; Sanders, D A; Summers, D J; Zhao, H W; Hast, C; Taras, P; Nicholson, H; Cartaro, C; Cavallo, N; De Nardo, G; Fabozzi, F; Gatto, C; Lista, L; Paolucci, P; Piccolo, D; Sciacca, C; Baak, M A; Raven, G; LoSecco, J M; Gabriel, T A; Brau, B; Pulliam, T; Brau, J; Frey, R; Iwasaki, M; Potter, C T; Sinev, N B; Strom, D; Torrence, E; Colecchia, F; Dorigo, A; Galeazzi, F; Margoni, M; Morandin, M; Posocco, M; Rotondo, M; Simonetto, F; Stroili, R; Tiozzo, G; Voci, C; Benayoun, M; Briand, H; Chauveau, J; David, P; de la Vaissière, Ch; Del Buono, L; Hamon, O; Leruste, Ph; Ocariz, J; Pivk, M; Roos, L; Stark, J; T'Jampens, S; Manfredi, P F; Re, V; Gladney, L; Guo, Q H; Panetta, J; Angelini, C; Batignani, G; Bettarini, S; Bondioli, M; Bucci, F; Calderini, G; Carpinelli, M; Forti, F; Giorgi, M A; Lusiani, A; Marchiori, G; Martinez-Vidal, F; Morganti, M; Neri, N; Paoloni, E; Rama, M; Rizzo, G; Sandrelli, F; Walsh, J; Haire, M; Judd, D; Paick, K; Wagoner, D E; Danielson, N; Elmer, P; Lu, C; Miftakov, V; Olsen, J; Smith, A J S; Varnes, E W; Bellini, F; Cavoto, G; del Re, D; Faccini, R; Ferrarotto, F; Ferroni, F; Gaspero, M; Leonardi, E; Mazzoni, M A; Morganti, S; Pierini, M; Piredda, G; Safai Tehrani, F; Serra, M; Voena, C; Christ, S; Wagner, G; Waldi, R; Adye, T; De Groot, N; Franek, B; Geddes, N I; Gopal, G P; Olaiya, E O; Xella, S M; Aleksan, R; Emery, S; Gaidot, A; Ganzhur, S F; Giraud, P-F; Hamel de Monchenault, G; Kozanecki, W; Langer, M; London, G W; Mayer, B; Schott, G; Vasseur, G; Yeche, Ch; Zito, M; Purohit, M V; Weidemann, A W; Yumiceva, F X; Aston, D; Bartoldus, R; Berger, N; Boyarski, A M; Buchmueller, O L; Convery, M R; Coupal, D P; Dong, D; Dorfan, J; Dujmic, D; Dunwoodie, W; Field, R C; Glanzman, T; Gowdy, S J; Grauges-Pous, E; Hadig, T; Halyo, V; Hryn'ova, T; Innes, W R; Jessop, C P; Kelsey, M H; Kim, P; Kocian, M L; Langenegger, U; Leith, D W G S; Luitz, S; Luth, V; Lynch, H L; Marsiske, H; Menke, S; Messner, R; Muller, D R; O'Grady, C P; Ozcan, V E; Perazzo, A; Perl, M; Petrak, S; Ratcliff, B N; Robertson, S H; Roodman, A; Salnikov, A A; Schindler, R H; Schwiening, J; Simi, G; Snyder, A; Soha, A; Stelzer, J; Su, D; Sullivan, M K; Tanaka, H A; Va'vra, J; Wagner, S R; Weaver, M; Weinstein, A J R; Wisniewski, W J; Wright, D H; Young, C C; Burchat, P R; Meyer, T I; Roat, C; Ahmed, S; Ernst, J A; Bugg, W; Krishnamurthy, M; Spanier, S M; Eckmann, R; Kim, H; Ritchie, J L; Schwitters, R F; Izen, J M; Kitayama, I; Lou, X C; Ye, S; Bianchi, F; Bona, M; Gallo, F; Gamba, D; Borean, C; Bosisio, L; Della Ricca, G; Dittongo, S; Grancagnolo, S; Lanceri, L; Poropat, P; Vitale, L; Vuagnin, G; Panvini, R S; Banerjee, Sw; Brown, C M; Fortin, D; Jackson, P D; Kowalewski, R; Roney, J M; Band, H R; Dasu, S; Datta, M; Eichenbaum, A M; Hu, H; Johnson, J R; Liu, R; Lodovico, F Di; Mohapatra, A K; Pan, Y; Prepost, R; Sekula, S J; von Wimmersperg-Toeller, J H; Wu, J; Wu, S L; Yu, Z; Neal, H

2003-10-24

We present results of a search for D0-D(-)0 mixing and a measurement of R(D), the ratio of doubly Cabibbo-suppressed decays to Cabibbo-favored decays, using D0-->K+pi- decays from 57.1 fb(-1) of data collected near sqrt[s]=10.6 GeV with the BABAR detector at the PEP-II collider. At the 95% confidence level, allowing for CP violation, we find the mixing parameters x('2)<0.0022 and -0.056

Measurement of the branching fraction of Gamma(4S) --> B0B0.

PubMed

Aubert, B; Barate, R; Boutigny, D; Couderc, F; Karyotakis, Y; Lees, J P; Poireau, V; Tisserand, V; Zghiche, A; Grauges-Pous, E; Palano, A; Pappagallo, M; Pompili, A; Chen, J C; Qi, N D; Rong, G; Wang, P; Zhu, Y S; Eigen, G; Ofte, I; Stugu, B; Abrams, G S; Borgland, A W; Breon, A B; Brown, D N; Button-Shafer, J; Cahn, R N; Charles, E; Day, C T; Gill, M S; Gritsan, A V; Groysman, Y; Jacobsen, R G; Kadel, R W; Kadyk, J; Kerth, L T; Kolomensky, Yu G; Kukartsev, G; Lynch, G; Mir, L M; Oddone, P J; Orimoto, T J; Pripstein, M; Roe, N A; Ronan, M T; Wenzel, W A; Barrett, M; Ford, K E; Harrison, T J; Hart, A J; Hawkes, C M; Morgan, S E; Watson, A T; Fritsch, M; Goetzen, K; Held, T; Koch, H; Lewandowski, B; Pelizaeus, M; Peters, K; Schroeder, T; Steinke, M; Boyd, J T; Burke, J P; Chevalier, N; Cottingham, W N; Kelly, M P; Cuhadar-Donszelmann, T; Hearty, C; Knecht, N S; Mattison, T S; McKenna, J A; Thiessen, D; Khan, A; Kyberd, P; Teodorescu, L; Blinov, A E; Blinov, V E; Bukin, A D; Druzhinin, V P; Golubev, V B; Ivanchenko, V N; Kravchenko, E A; Onuchin, A P; Serednyakov, S I; Skovpen, Yu I; Solodov, E P; Yushkov, A N; Best, D; Bondioli, M; Bruinsma, M; Chao, M; Eschrich, I; Kirkby, D; Lankford, A J; Mandelkern, M; Mommsen, R K; Roethel, W; Stoker, D P; Buchanan, C; Hartfiel, B L; Weinstein, A J R; Foulkes, S D; Gary, J W; Long, O; Shen, B C; Wang, K; Zhang, L; Del Re, D; Hadavand, H K; Hill, E J; MacFarlane, D B; Paar, H P; Rahatlou, Sh; Sharma, V; Berryhill, J W; Campagnari, C; Cunha, A; Dahmes, B; Hong, T M; Lu, A; Mazur, M A; Richman, J D; Verkerke, W; Beck, T W; Eisner, A M; Flacco, C J; Heusch, C A; Kroseberg, J; Lockman, W S; Nesom, G; Schalk, T; Schumm, B A; Seiden, A; Spradlin, P; Williams, D C; Wilson, M G; Albert, J; Chen, E; Dubois-Felsmann, G P; Dvoretskii, A; Hitlin, D G; Narsky, I; Piatenko, T; Porter, F C; Ryd, A; Samuel, A; Yang, S; Jayatilleke, S; Mancinelli, G; Meadows, B T; Sokoloff, M D; Blanc, F; Bloom, P; Chen, S; Ford, W T; Nauenberg, U; Olivas, A; Rankin, P; Ruddick, W O; Smith, J G; Ulmer, K A; Zhang, J; Chen, A; Eckhart, E A; Harton, J L; Soffer, A; Toki, W H; Wilson, R J; Zeng, Q; Spaan, B; Altenburg, D; Brandt, T; Brose, J; Dickopp, M; Feltresi, E; Hauke, A; Lacker, H M; Maly, E; Nogowski, R; Otto, S; Petzold, A; Schott, G; Schubert, J; Schubert, K R; Schwierz, R; Sundermann, J E; Bernard, D; Bonneaud, G R; Grenier, P; Schrenk, S; Thiebaux, Ch; Vasileiadis, G; Verderi, M; Bard, D J; Clark, P J; Gradl, W; Muheim, F; Playfer, S; Xie, Y; Andreotti, M; Azzolini, V; Bettoni, D; Bozzi, C; Calabrese, R; Cibinetto, G; Luppi, E; Negrini, M; Piemontese, L; Sarti, A; Anulli, F; Baldini-Ferroli, R; Calcaterra, A; de Sangro, R; Finocchiaro, G; Patteri, P; Peruzzi, I M; Piccolo, M; Zallo, A; Buzzo, A; Capra, R; Contri, R; Lo Vetere, M; Macri, M; Monge, M R; Passaggio, S; Patrignani, C; Robutti, E; Santroni, A; Tosi, S; Bailey, S; Brandenburg, G; Chaisanguanthum, K S; Morii, M; Won, E; Dubitzky, R S; Langenegger, U; Marks, J; Uwer, U; Bhimji, W; Bowerman, D A; Dauncey, P D; Egede, U; Gaillard, J R; Morton, G W; Nash, J A; Nikolich, M B; Taylor, G P; Charles, M J; Grenier, G J; Mallik, U; Cochran, J; Crawley, H B; Meyer, W T; Prell, S; Rosenberg, E I; Rubin, A E; Yi, J; Arnaud, N; Davier, M; Giroux, X; Grosdidier, G; Höcker, A; Le Diberder, F; Lepeltier, V; Lutz, A M; Petersen, T C; Pierini, M; Plaszczynski, S; Rodier, S; Roudeau, P; Schune, M H; Stocchi, A; Wormser, G; Cheng, C H; Lange, D J; Simani, M C; Wright, D M; Bevan, A J; Chavez, C A; Coleman, J P; Forster, I J; Fry, J R; Gabathuler, E; Gamet, R; George, K A; Hutchcroft, D E; Parry, R J; Payne, D J; Touramanis, C; Cormack, C M; Di Lodovico, F; Brown, C L; Cowan, G; Flack, R L; Flaecher, H U; Green, M G; Jackson, P S; McMahon, T R; Ricciardi, S; Salvatore, F; Winter, M A; Brown, D; Davis, C L; Allison, J; Barlow, N R; Barlow, R J; Hodgkinson, M C; Lafferty, G D; Naisbit, M T; Williams, J C; Chen, C; Farbin, A; Hulsbergen, W D; Jawahery, A; Kovalskyi, D; Lae, C K; Lillard, V; Roberts, D A; Blaylock, G; Dallapiccola, C; Hertzbach, S S; Kofler, R; Koptchev, V B; Moore, T B; Saremi, S; Staengle, H; Willocq, S; Cowan, R; Koeneke, K; Sciolla, G; Sekula, S J; Taylor, F; Yamamoto, R K; Patel, P M; Robertson, S H; Lazzaro, A; Lombardo, V; Palombo, F; Bauer, J M; Cremaldi, L; Eschenburg, V; Godang, R; Kroeger, R; Reidy, J; Sanders, D A; Summers, D J; Zhao, H W; Brunet, S; Côté, D; Taras, P; Nicholson, H; Cavallo, N; De Nardo, G; Fabozzi, F; Gatto, C; Lista, L; Monorchio, D; Paolucci, P; Piccolo, D; Sciacca, C; Baak, M; Bulten, H; Raven, G; Snoek, H L; Wilden, L; Jessop, C P; Losecco, J M; Allmendinger, T; Benelli, G; Gan, K K; Honscheid, K; Hufnagel, D; Kagan, H; Kass, R; Pulliam, T; Rahimi, A M; Ter-Antonyan, R; Wong, Q K; Brau, J; Frey, R; Igonkina, O; Lu, M; Potter, C T; Sinev, N B; Strom, D; Torrence, E; Colecchia, F; Dorigo, A; Galeazzi, F; Margoni, M; Morandin, M; Posocco, M; Rotondo, M; Simonetto, F; Stroili, R; Voci, C; Benayoun, M; Briand, H; Chauveau, J; David, P; Del Buono, L; de la Vaissière, Ch; Hamon, O; John, M J J; Leruste, Ph; Malclès, J; Ocariz, J; Roos, L; Therin, G; Behera, P K; Gladney, L; Guo, Q H; Panetta, J; Biasini, M; Covarelli, R; Pioppi, M; Angelini, C; Batignani, G; Bettarini, S; Bucci, F; Calderini, G; Carpinelli, M; Forti, F; Giorgi, M A; Lusiani, A; Marchiori, G; Morganti, M; Neri, N; Paoloni, E; Rama, M; Rizzo, G; Simi, G; Walsh, J; Haire, M; Judd, D; Paick, K; Wagoner, D E; Danielson, N; Elmer, P; Lau, Y P; Lu, C; Olsen, J; Smith, A J S; Telnov, A V; Bellini, F; Cavoto, G; D'Orazio, A; Di Marco, E; Faccini, R; Ferrarotto, F; Ferroni, F; Gaspero, M; Li Gioi, L; Mazzoni, M A; Morganti, S; Piredda, G; Polci, F; Tehrani, F Safai; Voena, C; Christ, S; Schröder, H; Wagner, G; Waldi, R; Adye, T; De Groot, N; Franek, B; Gopal, G P; Olaiya, E O; Wilson, F F; Aleksan, R; Emery, S; Gaidot, A; Ganzhur, S F; Giraud, P-F; Graziani, G; de Monchenault, G Hamel; Kozanecki, W; Legendre, M; London, G W; Mayer, B; Vasseur, G; Yèche, Ch; Zito, M; Purohit, M V; Weidemann, A W; Wilson, J R; Yumiceva, F X; Abe, T; Allen, M; Aston, D; Bartoldus, R; Berger, N; Boyarski, A M; Buchmueller, O L; Claus, R; Convery, M R; Cristinziani, M; Dingfelder, J C; Dong, D; Dorfan, J; Dujmic, D; Dunwoodie, W; Fan, S; Field, R C; Glanzman, T; Gowdy, S J; Hadig, T; Halyo, V; Hast, C; Hryn'ova, T; Innes, W R; Kelsey, M H; Kim, P; Kocian, M L; Leith, D W G S; Libby, J; Luitz, S; Luth, V; Lynch, H L; Marsiske, H; Messner, R; Mohapatra, A K; Muller, D R; O'Grady, C P; Ozcan, V E; Perazzo, A; Perl, M; Ratcliff, B N; Roodman, A; Salnikov, A A; Schindler, R H; Schwiening, J; Snyder, A; Soha, A; Stelzer, J; Strube, J; Su, D; Sullivan, M K; Thompson, J; Va'vra, J; Wagner, S R; Weaver, M; Wisniewski, W J; Wittgen, M; Wright, D H; Yarritu, A K; Young, C C; Burchat, P R; Edwards, A J; Majewski, S A; Petersen, B A; Roat, C; Ahmed, M; Ahmed, S; Alam, M S; Ernst, J A; Saeed, M A; Saleem, M; Wappler, F R; Bugg, W; Krishnamurthy, M; Spanier, S M; Eckmann, R; Kim, H; Ritchie, J L; Satpathy, A; Schwitters, R F; Izen, J M; Kitayama, I; Lou, X C; Ye, S; Bianchi, F; Bona, M; Gallo, F; Gamba, D; Bomben, M; Bosisio, L; Cartaro, C; Cossutti, F; Ricca, G Della; Dittongo, S; Grancagnolo, S; Lanceri, L; Poropat, P; Vitale, L; Vuagnin, G; Martinez-Vidal, F; Panvini, R S; Banerjee, Sw; Bhuyan, B; Brown, C M; Fortin, D; Hamano, K; Jackson, P D; Kowalewski, R; Roney, J M; Sobie, R J; Back, J J; Harrison, P F; Latham, T E; Mohanty, G B; Band, H R; Chen, X; Cheng, B; Dasu, S; Datta, M; Eichenbaum, A M; Flood, K T; Graham, M; Hollar, J J; Johnson, J R; Kutter, P E; Li, H; Liu, R; Mellado, B; Mihalyi, A; Pan, Y; Prepost, R; Tan, P; von Wimmersperg-Toeller, J H; Wu, J; Wu, S L; Yu, Z; Greene, M G; Neal, H

2005-07-22

We report the first measurement of the branching fraction f(00) for Gamma(4S) --> B(0)B(0). The data sample consists of 81.7 fb(-1) collected at the Gamma(4S) resonance with the BABAR detector at the SLAC PEP-II asymmetric-energy e(+)e(-) storage ring. Using partial reconstruction of the decay B(0) --> D(*+) l(-)nu(l) in which only the charged lepton and the soft pion from the decay D(*+) --> D(0)pi(+) are reconstructed, we obtain f(00) = 0.487 +/- 0.010(stat) +/- 0.008(syst). Our result does not depend on the branching fractions of B(0) --> D(*+)l(-)nu(l) and D(*+) --> D(0)pi(+) decays, on the ratio of the charged and neutral B meson lifetimes, nor on the assumption of isospin symmetry.

Search for the decay modes B ±→h ±τl

DOE PAGES

Lees, J. P.; Poireau, V.; Tisserand, V.; ...

2012-07-16

We present a search for the lepton flavor violating decay modes B ±→h ±τl (h=K, π; l=e, μ) using the BABAR data sample, which corresponds to 472×10⁶ BB¯¯¯ pairs. The search uses events where one B meson is fully reconstructed in one of several hadronic final states. Using the momenta of the reconstructed B, h, and l candidates, we are able to fully determine the τ four-momentum. The resulting τ candidate mass is our main discriminant against combinatorial background. We see no evidence for B ±→h ±τl decays and set a 90% confidence level upper limit on each branching fractionmore » at the level of a few times 10⁻⁵.« less

Trapping penguins with entangled B mesons

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dadisman, Ryan; Gardner, Susan; Yan, Xinshuai

2016-01-08

Our first direct observation of time-reversal (T) violation in the BBsystem was reported by the BaBar Collaboration, employing the method of Bañuls and Bernabéu. Given this, we generalize their analysis of the time-dependent T-violating asymmetry (AT) to consider different choices of CP tags for which the dominant amplitudes have the same weak phase. As one application, we find that it is possible to measure departures from the universality of sin(2β)directly. If sin(2β)is universal, as in the Standard Model, the method permits the direct determination of penguin effects in these channels. This method, although no longer a strict test of T,more » can yield tests of the sin(2β)universality, or, alternatively, of penguin effects, of much improved precision even with existing data sets.« less

Search for a light Higgs boson decaying to two gluons or ss̄ in the radiative decays of Υ(1S)

DOE PAGES

Lees, J. P.; Poireau, V.; Tisserand, V.; ...

2013-08-06

We search for the decay Υ(1S)→γA⁰, A⁰→gg or ss̄, where A⁰ is the pseudoscalar light Higgs boson predicted by the next-to-minimal supersymmetric Standard Model. We use a sample of (17.6±0.3)×10⁶ Υ(1S) mesons produced in the BABAR experiment via e⁺e⁻→Υ(2S)→π⁺π⁻Υ(1S). We see no significant signal and set 90%-confidence-level upper limits on the product branching fraction B(Υ(1S)→γA⁰)·B(A⁰→gg or ss̄) ranging from 10⁻⁶ to 10⁻² for A⁰ masses in the range 0.5–9.0 GeV/c².

Measurement of the branching fractions for B0 -->D*-pi+ and B0 -->D*rho+

DOE Office of Scientific and Technical Information (OSTI.GOV)

Barrera, Barbara

Using 5.2 fb{sup -1} annihilation data recorded with the BABAR detector at the PEP-II storage ring while operating on the {Upsilon}(4S) resonance, a sample of fully reconstructed B{sup 0} decays in the hadronic modes B{sup 0} {yields} D*{sup -} {pi}{sup +} and B{sup 0} {yields} D*{sup -} {rho}{sup +} have been reconstructed. In this paper, a study of these events is reported, including preliminary measurements of the absolute branching fractions for these modes, which are found to be B(B{sup 0} {yields} D*{sup -} {pi}{sup +} = 2.9 {+-} 0.3 {+-} 0.3) x 10{sup -3} and B(B{sup 0} {yields} D*{sup -}more » {rho}{sup +}) = (11.2 {+-} 1.1 {+-} 2.5) x 10{sup -3}.« less

Observation of the baryonic B decay B{sup 0}{yields}{Lambda}{sub c}{sup +}{Lambda}K{sup -}

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lees, J. P.; Poireau, V.; Tisserand, V.

2011-10-01

We report the observation of the baryonic B decay B{sup 0}{yields}{Lambda}{sub c}{sup +}{Lambda}K{sup -} with a significance larger than 7 standard deviations based on 471x10{sup 6} BB pairs collected with the BABAR detector at the PEP-II storage ring at SLAC. We measure the branching fraction for the decay B{sup 0}{yields}{Lambda}{sub c}{sup +}{Lambda}K{sup -} to be (3.8{+-}0.8{sub stat}{+-}0.2{sub sys}{+-}1.0{sub {Lambda}}{sub c}{sup +})x10{sup -5}. The uncertainties are statistical, systematic, and due to the uncertainty in the {Lambda}{sub c}{sup +} branching fraction. We find that the {Lambda}{sub c}{sup +}K{sup -} invariant-mass distribution shows an enhancement above 3.5 GeV/c{sup 2}.

Fort Bliss Geothermal Area Data: Temperature profile, logs, schematic model and cross section

DOE Data Explorer

Adam Brandt

2015-11-15

This dataset contains a variety of data about the Fort Bliss geothermal area, part of the southern portion of the Tularosa Basin, New Mexico. The dataset contains schematic models for the McGregor Geothermal System, a shallow temperature survey of the Fort Bliss geothermal area. The dataset also contains Century OH logs, a full temperature profile, and complete logs from well RMI 56-5, including resistivity and porosity data, drill logs with drill rate, depth, lithology, mineralogy, fractures, temperature, pit total, gases, and descriptions among other measurements as well as CDL, CNL, DIL, GR Caliper and Temperature files. A shallow (2 meter depth) temperature survey of the Fort Bliss geothermal area with 63 data points is also included. Two cross sections through the Fort Bliss area, also included, show well position and depth. The surface map included shows faults and well spatial distribution. Inferred and observed fault distributions from gravity surveys around the Fort Bliss geothermal area.

A dataset mapping the potential biophysical effects of vegetation cover change

NASA Astrophysics Data System (ADS)

Duveiller, Gregory; Hooker, Josh; Cescatti, Alessandro

2018-02-01

Changing the vegetation cover of the Earth has impacts on the biophysical properties of the surface and ultimately on the local climate. Depending on the specific type of vegetation change and on the background climate, the resulting competing biophysical processes can have a net warming or cooling effect, which can further vary both spatially and seasonally. Due to uncertain climate impacts and the lack of robust observations, biophysical effects are not yet considered in land-based climate policies. Here we present a dataset based on satellite remote sensing observations that provides the potential changes i) of the full surface energy balance, ii) at global scale, and iii) for multiple vegetation transitions, as would now be required for the comprehensive evaluation of land based mitigation plans. We anticipate that this dataset will provide valuable information to benchmark Earth system models, to assess future scenarios of land cover change and to develop the monitoring, reporting and verification guidelines required for the implementation of mitigation plans that account for biophysical land processes.

A dataset mapping the potential biophysical effects of vegetation cover change

PubMed Central

Duveiller, Gregory; Hooker, Josh; Cescatti, Alessandro

2018-01-01

Changing the vegetation cover of the Earth has impacts on the biophysical properties of the surface and ultimately on the local climate. Depending on the specific type of vegetation change and on the background climate, the resulting competing biophysical processes can have a net warming or cooling effect, which can further vary both spatially and seasonally. Due to uncertain climate impacts and the lack of robust observations, biophysical effects are not yet considered in land-based climate policies. Here we present a dataset based on satellite remote sensing observations that provides the potential changes i) of the full surface energy balance, ii) at global scale, and iii) for multiple vegetation transitions, as would now be required for the comprehensive evaluation of land based mitigation plans. We anticipate that this dataset will provide valuable information to benchmark Earth system models, to assess future scenarios of land cover change and to develop the monitoring, reporting and verification guidelines required for the implementation of mitigation plans that account for biophysical land processes. PMID:29461538

Identification and evaluation of the cost-effectiveness of highway design features to reduce nonrecurrent congestion. [supporting datasets

DOT National Transportation Integrated Search

2014-01-01

This project focused specifically on design treatments that can be used to improve travel time reliability. The objectives of this research were to (1) identify the full range of possible roadway design features used by transportation agencies to imp...

Fluctuation of Indoor Radon and VOC Concentrations Due to Seasonal Variations

EPA Science Inventory

This research was conducted to better characterize the spatial and temporal variability of vapor intrusion by collecting a full year’s dataset of weekly measurements of subslab soil gas, external soil gas, and indoor air, on a single house that is impacted by vapor intrusion of r...

Locality-Constrained Discriminative Learning and Coding

DTIC Science & Technology

2015-06-12

female Caucasian subjects (show in Fig. 3 (d)). There are 4 makeup statues (a) no makeup; (b) lipstick only; (c) eye makeup only; and (d) a full makeup...including lipstick , foundation, blush and eye makeup. Hence, the assembled dataset contains total 204 images and four images per subject. We randomly

DAPAGLOCO - A global daily precipitation dataset from satellite and rain-gauge measurements

NASA Astrophysics Data System (ADS)

Spangehl, T.; Danielczok, A.; Dietzsch, F.; Andersson, A.; Schroeder, M.; Fennig, K.; Ziese, M.; Becker, A.

2017-12-01

The BMBF funded project framework MiKlip(Mittelfristige Klimaprognosen) develops a global climate forecast system on decadal time scales for operational applications. Herein, the DAPAGLOCO project (Daily Precipitation Analysis for the validation of Global medium-range Climate predictions Operationalized) provides a global precipitation dataset as a combination of microwave-based satellite measurements over ocean and rain gauge measurements over land on daily scale. The DAPAGLOCO dataset is created for the evaluation of the MiKlip forecast system in the first place. The HOAPS dataset (Hamburg Ocean Atmosphere Parameter and Fluxes from Satellite data) is used for the derivation of precipitation rates over ocean and is extended by the use of measurements from TMI, GMI, and AMSR-E, in addition to measurements from SSM/I and SSMIS. A 1D-Var retrieval scheme is developed to retrieve rain rates from microwave imager data, which also allows for the determination of uncertainty estimates. Over land, the GPCC (Global Precipitation Climatology Center) Full Data Daily product is used. It consists of rain gauge measurements that are interpolated on a regular grid by ordinary Kriging. The currently available dataset is based on a neuronal network approach, consists of 21 years of data from 1988 to 2008 and is currently extended until 2015 using the 1D-Var scheme and with improved sampling. Three different spatial resolved dataset versions are available with 1° and 2.5° global, and 0.5° for Europe. The evaluation of the MiKlip forecast system by DAPAGLOCO is based on ETCCDI (Expert Team on Climate Change and Detection Indices). Hindcasts are used for the index-based comparison between model and observations. These indices allow for the evaluation of precipitation extremes, their spatial and temporal distribution as well as for the duration of dry and wet spells, average precipitation amounts and percentiles on global scale. Besides, an ETCCDI-based climatology of the DAPAGLOCO precipitation dataset has been derived.

A new dataset validation system for the Planetary Science Archive

NASA Astrophysics Data System (ADS)

Manaud, N.; Zender, J.; Heather, D.; Martinez, S.

2007-08-01

The Planetary Science Archive is the official archive for the Mars Express mission. It has received its first data by the end of 2004. These data are delivered by the PI teams to the PSA team as datasets, which are formatted conform to the Planetary Data System (PDS). The PI teams are responsible for analyzing and calibrating the instrument data as well as the production of reduced and calibrated data. They are also responsible of the scientific validation of these data. ESA is responsible of the long-term data archiving and distribution to the scientific community and must ensure, in this regard, that all archived products meet quality. To do so, an archive peer-review is used to control the quality of the Mars Express science data archiving process. However a full validation of its content is missing. An independent review board recently recommended that the completeness of the archive as well as the consistency of the delivered data should be validated following well-defined procedures. A new validation software tool is being developed to complete the overall data quality control system functionality. This new tool aims to improve the quality of data and services provided to the scientific community through the PSA, and shall allow to track anomalies in and to control the completeness of datasets. It shall ensure that the PSA end-users: (1) can rely on the result of their queries, (2) will get data products that are suitable for scientific analysis, (3) can find all science data acquired during a mission. We defined dataset validation as the verification and assessment process to check the dataset content against pre-defined top-level criteria, which represent the general characteristics of good quality datasets. The dataset content that is checked includes the data and all types of information that are essential in the process of deriving scientific results and those interfacing with the PSA database. The validation software tool is a multi-mission tool that has been designed to provide the user with the flexibility of defining and implementing various types of validation criteria, to iteratively and incrementally validate datasets, and to generate validation reports.

Global-Mode Analysis of Full-Disk Data from the Michelson Doppler Imager and the Helioseismic and Magnetic Imager

NASA Astrophysics Data System (ADS)

Larson, Timothy P.; Schou, Jesper

2018-02-01

Building upon our previous work, in which we analyzed smoothed and subsampled velocity data from the Michelson Doppler Imager (MDI), we extend our analysis to unsmoothed, full-resolution MDI data. We also present results from the Helioseismic and Magnetic Imager (HMI), in both full resolution and processed to be a proxy for the low-resolution MDI data. We find that the systematic errors that we saw previously, namely peaks in both the high-latitude rotation rate and the normalized residuals of odd a-coefficients, are almost entirely absent in the two full-resolution analyses. Furthermore, we find that both systematic errors seem to depend almost entirely on how the input images are apodized, rather than on resolution or smoothing. Using the full-resolution HMI data, we confirm our previous findings regarding the effect of using asymmetric profiles on mode parameters, and also find that they occasionally result in more stable fits. We also confirm our previous findings regarding discrepancies between 360-day and 72-day analyses. We further investigate a six-month period previously seen in f-mode frequency shifts using the low-resolution datasets, this time accounting for solar-cycle dependence using magnetic-field data. Both HMI and MDI saw prominent six-month signals in the frequency shifts, but we were surprised to discover that the strongest signal at that frequency occurred in the mode coverage for the low-resolution proxy. Finally, a comparison of mode parameters from HMI and MDI shows that the frequencies and a-coefficients agree closely, encouraging the concatenation of the two datasets.

Mining Peripheral Arterial Disease Cases from Narrative Clinical Notes Using Natural Language Processing

PubMed Central

Afzal, Naveed; Sohn, Sunghwan; Abram, Sara; Scott, Christopher G.; Chaudhry, Rajeev; Liu, Hongfang; Kullo, Iftikhar J.; Arruda-Olson, Adelaide M.

2016-01-01

Objective Lower extremity peripheral arterial disease (PAD) is highly prevalent and affects millions of individuals worldwide. We developed a natural language processing (NLP) system for automated ascertainment of PAD cases from clinical narrative notes and compared the performance of the NLP algorithm to billing code algorithms, using ankle-brachial index (ABI) test results as the gold standard. Methods We compared the performance of the NLP algorithm to 1) results of gold standard ABI; 2) previously validated algorithms based on relevant ICD-9 diagnostic codes (simple model) and 3) a combination of ICD-9 codes with procedural codes (full model). A dataset of 1,569 PAD patients and controls was randomly divided into training (n= 935) and testing (n= 634) subsets. Results We iteratively refined the NLP algorithm in the training set including narrative note sections, note types and service types, to maximize its accuracy. In the testing dataset, when compared with both simple and full models, the NLP algorithm had better accuracy (NLP: 91.8%, full model: 81.8%, simple model: 83%, P<.001), PPV (NLP: 92.9%, full model: 74.3%, simple model: 79.9%, P<.001), and specificity (NLP: 92.5%, full model: 64.2%, simple model: 75.9%, P<.001). Conclusions A knowledge-driven NLP algorithm for automatic ascertainment of PAD cases from clinical notes had greater accuracy than billing code algorithms. Our findings highlight the potential of NLP tools for rapid and efficient ascertainment of PAD cases from electronic health records to facilitate clinical investigation and eventually improve care by clinical decision support. PMID:28189359

Multisite Evaluation of a Data Quality Tool for Patient-Level Clinical Data Sets

PubMed Central

Huser, Vojtech; DeFalco, Frank J.; Schuemie, Martijn; Ryan, Patrick B.; Shang, Ning; Velez, Mark; Park, Rae Woong; Boyce, Richard D.; Duke, Jon; Khare, Ritu; Utidjian, Levon; Bailey, Charles

2016-01-01

Introduction: Data quality and fitness for analysis are crucial if outputs of analyses of electronic health record data or administrative claims data should be trusted by the public and the research community. Methods: We describe a data quality analysis tool (called Achilles Heel) developed by the Observational Health Data Sciences and Informatics Collaborative (OHDSI) and compare outputs from this tool as it was applied to 24 large healthcare datasets across seven different organizations. Results: We highlight 12 data quality rules that identified issues in at least 10 of the 24 datasets and provide a full set of 71 rules identified in at least one dataset. Achilles Heel is a freely available software that provides a useful starter set of data quality rules with the ability to add additional rules. We also present results of a structured email-based interview of all participating sites that collected qualitative comments about the value of Achilles Heel for data quality evaluation. Discussion: Our analysis represents the first comparison of outputs from a data quality tool that implements a fixed (but extensible) set of data quality rules. Thanks to a common data model, we were able to compare quickly multiple datasets originating from several countries in America, Europe and Asia. PMID:28154833

Basin Characteristics for Selected Streamflow-Gaging Stations In and Near West Virginia

USGS Publications Warehouse

Paybins, Katherine S.

2008-01-01

Basin characteristics have long been used to develop equations describing streamflow. In the past, flow equations used in West Virginia were based on a few hand-calculated basin characteristics. More recently, the use of a Geographic Information System (GIS) to generate basin characteristics from existing datasets has refined the process for developing equations to describe flow values in the Mountain State. These basin characteristics are described in this document for streamflow-gaging stations in and near West Virginia. The GIS program developed in ArcGIS Workstation by Environmental Systems Research Institute (ESRI?) used data that included National Elevation Dataset (NED) at 1:24,000 scale, climate data from the National Oceanic and Atmospheric Agency (NOAA), streamlines from the National Hydrologic Dataset (NHD), and LandSat-based land-cover data (NLCD) for the period 1999-2003. Full automation of data generation was not achieved due to some inaccuracies in the elevation dataset, as well as inaccuracies in the streamflow-gage locations retrieved from the National Water Information System (NWIS). A Pearson?s correlation examination of the data indicates that several of the basin characteristics are correlated with drainage area. However, the GIS-generated data provide a consistent and documented set of basin characteristics for resource managers and researchers to use.

Data publication, documentation and user friendly landing pages - improving data discovery and reuse

NASA Astrophysics Data System (ADS)

Elger, Kirsten; Ulbricht, Damian; Bertelmann, Roland

2016-04-01

Research data are the basis for scientific research and often irreplaceable (e.g. observational data). Storage of such data in appropriate, theme specific or institutional repositories is an essential part of ensuring their long term preservation and access. The free and open access to research data for reuse and scrutiny has been identified as a key issue by the scientific community as well as by research agencies and the public. To ensure the datasets to intelligible and usable for others they must be accompanied by comprehensive data description and standardized metadata for data discovery, and ideally should be published using digital object identifier (DOI). These make datasets citable and ensure their long-term accessibility and are accepted in reference lists of journal articles (http://www.copdess.org/statement-of-commitment/). The GFZ German Research Centre for Geosciences is the national laboratory for Geosciences in Germany and part of the Helmholtz Association, Germany's largest scientific organization. The development and maintenance of data systems is a key component of 'GFZ Data Services' to support state-of-the-art research. The datasets, archived in and published by the GFZ Data Repository cover all geoscientific disciplines and range from large dynamic datasets deriving from global monitoring seismic or geodetic networks with real-time data acquisition, to remotely sensed satellite products, to automatically generated data publications from a database for data from micro meteorological stations, to various model results, to geochemical and rock mechanical analyses from various labs, and field observations. The user-friendly presentation of published datasets via a DOI landing page is as important for reuse as the storage itself, and the required information is highly specific for each scientific discipline. If dataset descriptions are too general, or require the download of a dataset before knowing its suitability, many researchers often decide not to reuse a published dataset. In contrast to large data repositories without thematic specification, theme-specific data repositories have a large expertise in data discovery and opportunity to develop usable, discipline-specific formats and layouts for specific datasets, including consultation to different formats for the data description (e.g., via a Data Report or an article in a Data Journal) with full consideration of international metadata standards.

Quantifying the accuracy of the tumor motion and area as a function of acceleration factor for the simulation of the dynamic keyhole magnetic resonance imaging method

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lee, Danny; Pollock, Sean; Keall, Paul, E-mail: paul.keall@sydney.edu.au

2016-05-15

Purpose: The dynamic keyhole is a new MR image reconstruction method for thoracic and abdominal MR imaging. To date, this method has not been investigated with cancer patient magnetic resonance imaging (MRI) data. The goal of this study was to assess the dynamic keyhole method for the task of lung tumor localization using cine-MR images reconstructed in the presence of respiratory motion. Methods: The dynamic keyhole method utilizes a previously acquired a library of peripheral k-space datasets at similar displacement and phase (where phase is simply used to determine whether the breathing is inhale to exhale or exhale to inhale)more » respiratory bins in conjunction with central k-space datasets (keyhole) acquired. External respiratory signals drive the process of sorting, matching, and combining the two k-space streams for each respiratory bin, thereby achieving faster image acquisition without substantial motion artifacts. This study was the first that investigates the impact of k-space undersampling on lung tumor motion and area assessment across clinically available techniques (zero-filling and conventional keyhole). In this study, the dynamic keyhole, conventional keyhole and zero-filling methods were compared to full k-space dataset acquisition by quantifying (1) the keyhole size required for central k-space datasets for constant image quality across sixty four cine-MRI datasets from nine lung cancer patients, (2) the intensity difference between the original and reconstructed images in a constant keyhole size, and (3) the accuracy of tumor motion and area directly measured by tumor autocontouring. Results: For constant image quality, the dynamic keyhole method, conventional keyhole, and zero-filling methods required 22%, 34%, and 49% of the keyhole size (P < 0.0001), respectively, compared to the full k-space image acquisition method. Compared to the conventional keyhole and zero-filling reconstructed images with the keyhole size utilized in the dynamic keyhole method, an average intensity difference of the dynamic keyhole reconstructed images (P < 0.0001) was minimal, and resulted in the accuracy of tumor motion within 99.6% (P < 0.0001) and the accuracy of tumor area within 98.0% (P < 0.0001) for lung tumor monitoring applications. Conclusions: This study demonstrates that the dynamic keyhole method is a promising technique for clinical applications such as image-guided radiation therapy requiring the MR monitoring of thoracic tumors. Based on the results from this study, the dynamic keyhole method could increase the imaging frequency by up to a factor of five compared with full k-space methods for real-time lung tumor MRI.« less

A spatio-temporal index for aerial full waveform laser scanning data

NASA Astrophysics Data System (ADS)

Laefer, Debra F.; Vo, Anh-Vu; Bertolotto, Michela

2018-04-01

Aerial laser scanning is increasingly available in the full waveform version of the raw signal, which can provide greater insight into and control over the data and, thus, richer information about the scanned scenes. However, when compared to conventional discrete point storage, preserving raw waveforms leads to vastly larger and more complex data volumes. To begin addressing these challenges, this paper introduces a novel bi-level approach for storing and indexing full waveform (FWF) laser scanning data in a relational database environment, while considering both the spatial and the temporal dimensions of that data. In the storage scheme's upper level, the full waveform datasets are partitioned into spatial and temporal coherent groups that are indexed by a two-dimensional R∗-tree. To further accelerate intra-block data retrieval, at the lower level a three-dimensional local octree is created for each pulse block. The local octrees are implemented in-memory and can be efficiently written to a database for reuse. The indexing solution enables scalable and efficient three-dimensional (3D) spatial and spatio-temporal queries on the actual pulse data - functionalities not available in other systems. The proposed FWF laser scanning data solution is capable of managing multiple FWF datasets derived from large flight missions. The flight structure is embedded into the data storage model and can be used for querying predicates. Such functionality is important to FWF data exploration since aircraft locations and orientations are frequently required for FWF data analyses. Empirical tests on real datasets of up to 1 billion pulses from Dublin, Ireland prove the almost perfect scalability of the system. The use of the local 3D octree in the indexing structure accelerated pulse clipping by 1.2-3.5 times for non-axis-aligned (NAA) polyhedron shaped clipping windows, while axis-aligned (AA) polyhedron clipping was better served using only the top indexing layer. The distinct behaviours of the hybrid indexing for AA and NAA clipping windows are attributable to the different proportion of the local-index-related overheads with respect to the total querying costs. When temporal constraints were added, generally the number of costly spatial checks were reduced, thereby shortening the querying times.

PLANETarium Pilot: visualizing PLANET Earth inside-out on the planetarium's full-dome

NASA Astrophysics Data System (ADS)

Ballmer, Maxim; Wiethoff, Tobias

2016-04-01

In the past decade, projection systems in most planetariums, traditional sites of outreach and education, have advanced from interfaces that can display the motion of stars as moving beam spots to systems that are able to visualize multicolor, high-resolution, immersive full-dome videos or images. These extraordinary capabilities are ideally suited for visualization of global processes occurring on the surface and within the interior of the Earth, a spherical body just as the full dome. So far, however, our community has largely ignored this wonderful interface for outreach and education, and any previous geo-shows have mostly been limited to cartoon-style animations. Thus, we here propose a framework to convey recent scientific results on the origin and evolution of our PLANET to the >100 million per-year worldwide audience of planetariums, making the traditionally astronomy-focussed interface a true PLANETarium. In order to do this most efficiently, we intend to show "inside-out" visualizations of scientific datasets and models, as if the audience was positioned in the Earth's core. Such visualizations are expected to be renderable to the dome with little or no effort. For example, showing global geophysical datasets (e.g., gravity, air temperature), or horizontal slices of seismic-tomography images and spherical computer models requires no rendering at all. Rendering of 3D Cartesian datasets or models may further be achieved using standard techiques. Here, we show several example pilot animations. These animations rendered for the full dome are projected back to 2D for visualization on the flatscreen. Present-day science visualizations are typically as intuitive as cartoon-style animations, yet more appealing visually, and clearly with a higher level of detail. In addition to e.g. climate change and natural hazards, themes for any future geo-shows may include the coupled evolution of the Earth's interior and life, from the accretion of our planet to the evolution of mantle convection as well as the sustainment of a magnetic field and habitable conditions. We believe that high-quality tax-funded science visualizations should not exclusively be used for communication among scientists, but also recycled to raise the public's awareness and appreciation of the Geosciences.

PLANETarium Pilot: visualizing PLANET Earth inside-out on the planetarium's full-dome

NASA Astrophysics Data System (ADS)

Ballmer, M. D.; Wiethoff, T.

2014-12-01

In the past decade, projection systems in most planetariums, traditional sites of outreach and education, have advanced from interfaces that can display the motion of stars as moving beam spots to systems that are able to visualize multicolor, high-resolution, immersive full-dome videos or images. These extraordinary capabilities are ideally suited for visualization of global processes occurring on the surface and within the interior of the Earth, a spherical body just as the full dome. So far, however, our community has largely ignored this wonderful interface for outreach and education, and any previous geo-shows have mostly been limited to cartoon-style animations. Thus, we here propose a framework to convey recent scientific results on the origin and evolution of our PLANET to the >100 million per-year worldwide audience of planetariums, making the traditionally astronomy-focussed interface a true PLANETarium. In order to do this most efficiently, we intend to show „inside-out" visualizations of scientific datasets and models, as if the audience was positioned in the Earth's inner core. Such visualizations are expected to be renderable to the dome with little or no effort. For example, showing global geophysical datasets (e.g., gravity, air temperature), or horizontal slices of seismic-tomography images and spherical computer models requires no rendering at all. Rendering of 3D Cartesian datasets or models may further be achieved using standard techiques. Here, we show several example pilot animations. These animations rendered for the full dome are projected back to 2D for visualization on a flatscreen. Present-day science visualizations are typically as intuitive as cartoon-style animations, yet more appealing visually, and clearly with a higher level of detail. In addition to e.g. climate change and natural hazards, themes for any future geo-shows may include the coupled evolution of the Earth's interior and life, from the accretion of our planet to the evolution of mantle convection as well as the sustainment of a magnetic field and habitable conditions. We believe that high-quality tax-funded science visualizations should not exclusively be used for communication among scientists, but also recycled to raise the public's awareness and appreciation of the geosciences.

MSWEP: 3-hourly 0.25° global gridded precipitation (1979-2015) by merging gauge, satellite, and reanalysis data

NASA Astrophysics Data System (ADS)

Beck, Hylke E.; van Dijk, Albert I. J. M.; Levizzani, Vincenzo; Schellekens, Jaap; Miralles, Diego G.; Martens, Brecht; de Roo, Ad

2017-01-01

Current global precipitation (P) datasets do not take full advantage of the complementary nature of satellite and reanalysis data. Here, we present Multi-Source Weighted-Ensemble Precipitation (MSWEP) version 1.1, a global P dataset for the period 1979-2015 with a 3-hourly temporal and 0.25° spatial resolution, specifically designed for hydrological modeling. The design philosophy of MSWEP was to optimally merge the highest quality P data sources available as a function of timescale and location. The long-term mean of MSWEP was based on the CHPclim dataset but replaced with more accurate regional datasets where available. A correction for gauge under-catch and orographic effects was introduced by inferring catchment-average P from streamflow (Q) observations at 13 762 stations across the globe. The temporal variability of MSWEP was determined by weighted averaging of P anomalies from seven datasets; two based solely on interpolation of gauge observations (CPC Unified and GPCC), three on satellite remote sensing (CMORPH, GSMaP-MVK, and TMPA 3B42RT), and two on atmospheric model reanalysis (ERA-Interim and JRA-55). For each grid cell, the weight assigned to the gauge-based estimates was calculated from the gauge network density, while the weights assigned to the satellite- and reanalysis-based estimates were calculated from their comparative performance at the surrounding gauges. The quality of MSWEP was compared against four state-of-the-art gauge-adjusted P datasets (WFDEI-CRU, GPCP-1DD, TMPA 3B42, and CPC Unified) using independent P data from 125 FLUXNET tower stations around the globe. MSWEP obtained the highest daily correlation coefficient (R) among the five P datasets for 60.0 % of the stations and a median R of 0.67 vs. 0.44-0.59 for the other datasets. We further evaluated the performance of MSWEP using hydrological modeling for 9011 catchments (< 50 000 km2) across the globe. Specifically, we calibrated the simple conceptual hydrological model HBV (Hydrologiska Byråns Vattenbalansavdelning) against daily Q observations with P from each of the different datasets. For the 1058 sparsely gauged catchments, representative of 83.9 % of the global land surface (excluding Antarctica), MSWEP obtained a median calibration NSE of 0.52 vs. 0.29-0.39 for the other P datasets. MSWEP is available via http://www.gloh2o.org.

Gender Diversity Strategy in Academic Departments: Exploring Organizational Determinants

ERIC Educational Resources Information Center

Su, Xuhong; Johnson, Japera; Bozeman, Barry

2015-01-01

Full inclusion of women into the academics remains a daunting challenge in the United States. The situation is particularly acute within science, technology, engineering and mathematics (STEM) fields where the underrepresentation of women and their career disadvantages attract a great deal of attention. Based on a dataset combining a survey of…

Analysis of Methane Mitigation Options using the MARKAL Model for the US: Calibration Data for Methane Emissions

EPA Pesticide Factsheets

This dataset contains the output for modeling runs that were performed to investigate the effectiveness of various technologies and lay the groundwork for the formulation of policies for reducing methane emissions. See the full report at http://www.epa.gov/methane/projections.html.

Using Python to generate AHPS-based precipitation simulations over CONUS using Amazon distributed computing

NASA Astrophysics Data System (ADS)

Machalek, P.; Kim, S. M.; Berry, R. D.; Liang, A.; Small, T.; Brevdo, E.; Kuznetsova, A.

2012-12-01

We describe how the Climate Corporation uses Python and Clojure, a language impleneted on top of Java, to generate climatological forecasts for precipitation based on the Advanced Hydrologic Prediction Service (AHPS) radar based daily precipitation measurements. A 2-year-long forecasts is generated on each of the ~650,000 CONUS land based 4-km AHPS grids by constructing 10,000 ensembles sampled from a 30-year reconstructed AHPS history for each grid. The spatial and temporal correlations between neighboring AHPS grids and the sampling of the analogues are handled by Python. The parallelization for all the 650,000 CONUS stations is further achieved by utilizing the MAP-REDUCE framework (http://code.google.com/edu/parallel/mapreduce-tutorial.html). Each full scale computational run requires hundreds of nodes with up to 8 processors each on the Amazon Elastic MapReduce (http://aws.amazon.com/elasticmapreduce/) distributed computing service resulting in 3 terabyte datasets. We further describe how we have productionalized a monthly run of the simulations process at full scale of the 4km AHPS grids and how the resultant terabyte sized datasets are handled.

Quantarctica: A Unique, Open, Standalone GIS Package for Antarctic Research and Education

NASA Astrophysics Data System (ADS)

Roth, G.; Matsuoka, K.; Skoglund, A.; Melvaer, Y.; Tronstad, S.

2016-12-01

The Norwegian Polar Institute has developed Quantarctica, an open GIS package for use by the international Antarctic community. Quantarctica includes a wide range of cartographic basemap layers, geophysical and glaciological datasets, and satellite imagery in standardized file formats with a consistent Antarctic map projection and customized layer and labeling styles for quick, effective cartography. Quantarctica's strengths as an open science platform lie in 1) The complete, ready-to-use data package which includes full-resolution, original-quality vector and raster data, 2) A policy for freely-redistributable and modifiable data including all metadata and citations, and 3) QGIS, a free, full-featured, modular, offline-capable open-source GIS suite with a rapid and active development and support community. The Quantarctica team is actively seeking new contributions of peer-reviewed, freely distributable pan-Antarctic geospatial datasets for the next version release in 2017. As part of this ongoing development, we are investigating the best approaches for quickly and seamlessly distributing new and updated data to users, storing datasets in efficient file formats while maintaining full quality, and coexisting with numerous online data portals in a way that most actively benefits the Antarctic community. A recent survey of Quantarctica users showed broad geographical adoption among Antarctic Treaty countries, including those outside the large US and UK Antarctic programs. Maps and figures produced by Quantarctica have also appeared in open-access journals and outside of the formal scientific community on popular science and GIS blogs. Our experience with the Quantarctica project has shown the tremendous value of education and outreach, not only in promoting open software, data formats, and practices, but in empowering Antarctic science groups to more effectively use GIS and geospatial data. Open practices are making a huge impact in Antarctic GIS, where individual countries have historically maintained their own restricted Antarctic geodatabases and where a majority of the next generation of scientists are entering the field with experience in using geospatial thinking for planning, visualization, and problem solving.

Measurement of time-dependent CP asymmetries in B0-->D(*)+/-pi-/+ decays and constraints on sin(2beta+gamma).

PubMed

Aubert, B; Barate, R; Boutigny, D; Gaillard, J-M; Hicheur, A; Karyotakis, Y; Lees, J P; Robbe, P; Tisserand, V; Zghiche, A; Palano, A; Pompili, A; Chen, J C; Qi, N D; Rong, G; Wang, P; Zhu, Y S; Eigen, G; Ofte, I; Stugu, B; Abrams, G S; Borgland, A W; Breon, A B; Brown, D N; Button-Shafer, J; Cahn, R N; Charles, E; Day, C T; Gill, M S; Gritsan, A V; Groysman, Y; Jacobsen, R G; Kadel, R W; Kadyk, J; Kerth, L T; Kolomensky, Yu G; Kukartsev, G; LeClerc, C; Levi, M E; Lynch, G; Mir, L M; Oddone, P J; Orimoto, T J; Pripstein, M; Roe, N A; Romosan, A; Ronan, M T; Shelkov, V G; Telnov, A V; Wenzel, W A; Ford, K; Harrison, T J; Hawkes, C M; Knowles, D J; Morgan, S E; Penny, R C; Watson, A T; Watson, N K; Goetzen, K; Held, T; Koch, H; Lewandowski, B; Pelizaeus, M; Peters, K; Schmuecker, H; Steinke, M; Boyd, J T; Chevalier, N; Cottingham, W N; Kelly, M P; Latham, T E; Mackay, C; Wilson, F F; Abe, K; Cuhadar-Donszelmann, T; Hearty, C; Mattison, T S; McKenna, J A; Thiessen, D; Kyberd, P; McKemey, A K; Teodorescu, L; Blinov, V E; Bukin, A D; Golubev, V B; Ivanchenko, V N; Kravchenko, E A; Onuchin, A P; Serednyakov, S I; Skovpen, Yu I; Solodov, E P; Yushkov, A N; Best, D; Bruinsma, M; Chao, M; Kirkby, D; Lankford, A J; Mandelkern, M; Mommsen, R K; Roethel, W; Stoker, D P; Buchanan, C; Hartfiel, B L; Gary, J W; Layter, J; Shen, B C; Wang, K; del Re, D; Hadavand, H K; Hill, E J; MacFarlane, D B; Paar, H P; Rahatlou, Sh; Sharma, V; Berryhill, J W; Campagnari, C; Dahmes, B; Kuznetsova, N; Levy, S L; Long, O; Lu, A; Mazur, M A; Richman, J D; Verkerke, W; Beck, T W; Beringer, J; Eisner, A M; Heusch, C A; Lockman, W S; Schalk, T; Schmitz, R E; Schumm, B A; Seiden, A; Turri, M; Walkowiak, W; Williams, D C; Wilson, M G; Albert, J; Chen, E; Dubois-Felsmann, G P; Dvoretskii, A; Erwin, R J; Hitlin, D G; Narsky, I; Piatenko, T; Porter, F C; Ryd, A; Samuel, A; Yang, S; Jayatilleke, S; Mancinelli, G; Meadows, B T; Sokoloff, M D; Abe, T; Blanc, F; Bloom, P; Chen, S; Clark, P J; Ford, W T; Nauenberg, U; Olivas, A; Rankin, P; Roy, J; Smith, J G; van Hoek, W C; Zhang, L; Harton, J L; Hu, T; Soffer, A; Toki, W H; Wilson, R J; Zhang, J; Altenburg, D; Brandt, T; Brose, J; Colberg, T; Dickopp, M; Dubitzky, R S; Hauke, A; Lacker, H M; Maly, E; Müller-Pfefferkorn, R; Nogowski, R; Otto, S; Schubert, J; Schubert, K R; Schwierz, R; Spaan, B; Wilden, L; Bernard, D; Bonneaud, G R; Brochard, F; Cohen-Tanugi, J; Grenier, P; Thiebaux, Ch; Vasileiadis, G; Verderi, M; Khan, A; Lavin, D; Muheim, F; Playfer, S; Swain, J E; Andreotti, M; Azzolini, V; Bettoni, D; Bozzi, C; Calabrese, R; Cibinetto, G; Luppi, E; Negrini, M; Piemontese, L; Sarti, A; Treadwell, E; Anulli, F; Baldini-Ferroli, R; Biasini, M; Calcaterra, A; de Sangro, R; Falciai, D; Finocchiaro, G; Patteri, P; Peruzzi, I M; Piccolo, M; Pioppi, M; Zallo, A; Buzzo, A; Capra, R; Contri, R; Crosetti, G; Lo Vetere, M; Macri, M; Monge, M R; Passaggio, S; Patrignani, C; Robutti, E; Santroni, A; Tosi, S; Bailey, S; Morii, M; Won, E; Bhimji, W; Bowerman, D A; Dauncey, P D; Egede, U; Eschrich, I; Gaillard, J R; Morton, G W; Nash, J A; Sanders, P; Taylor, G P; Grenier, G J; Lee, S-J; Mallik, U; Cochran, J; Crawley, H B; Lamsa, J; Meyer, W T; Prell, S; Rosenberg, E I; Yi, J; Davier, M; Grosdidier, G; Höcker, A; Laplace, S; Le Diberder, F; Lepeltier, V; Lutz, A M; Petersen, T C; Plaszczynski, S; Schune, M H; Tantot, L; Wormser, G; Brigljević, V; Cheng, C H; Lange, D J; Simani, M C; Wright, D M; Bevan, A J; Coleman, J P; Fry, J R; Gabathuler, E; Gamet, R; Kay, M; Parry, R J; Payne, D J; Sloane, R J; Touramanis, C; Back, J J; Harrison, P F; Shorthouse, H W; Vidal, P B; Brown, C L; Cowan, G; Flack, R L; Flaecher, H U; George, S; Green, M G; Kurup, A; Marker, C E; McMahon, T R; Ricciardi, S; Salvatore, F; Vaitsas, G; Winter, M A; Brown, D; Davis, C L; Allison, J; Barlow, N R; Barlow, R J; Hart, P A; Hodgkinson, M C; Jackson, F; Lafferty, G D; Lyon, A J; Weatherall, J H; Williams, J C; Farbin, A; Jawahery, A; Kovalskyi, D; Lae, C K; Lillard, V; Roberts, D A; Blaylock, G; Dallapiccola, C; Flood, K T; Hertzbach, S S; Kofler, R; Koptchev, V B; Moore, T B; Saremi, S; Staengle, H; Willocq, S; Cowan, R; Sciolla, G; Taylor, F; Yamamoto, R K; Mangeol, D J J; Patel, P M; Robertson, S H; Lazzaro, A; Palombo, F; Bauer, J M; Cremaldi, L; Eschenburg, V; Godang, R; Kroeger, R; Reidy, J; Sanders, D A; Summers, D J; Zhao, H W; Brunet, S; Cote-Ahern, D; Taras, P; Nicholson, H; Cartaro, C; Cavallo, N; De Nardo, G; Fabozzi, F; Gatto, C; Lista, L; Paolucci, P; Piccolo, D; Sciacca, C; Baak, M A; Raven, G; LoSecco, J M; Gabriel, T A; Brau, B; Gan, K K; Honscheid, K; Hufnagel, D; Kagan, H; Kass, R; Pulliam, T; Wong, Q K; Brau, J; Frey, R; Potter, C T; Sinev, N B; Strom, D; Torrence, E; Colecchia, F; Dorigo, A; Galeazzi, F; Margoni, M; Morandin, M; Posocco, M; Rotondo, M; Simonetto, F; Stroili, R; Tiozzo, G; Voci, C; Benayoun, M; Briand, H; Chauveau, J; David, P; de la Vaissière, Ch; Del Buono, L; Hamon, O; John, M J J; Leruste, Ph; Ocariz, J; Pivk, M; Roos, L; Stark, J; T'Jampens, S; Therin, G; Manfredi, P F; Re, V; Behera, P K; Gladney, L; Guo, Q H; Panetta, J; Angelini, C; Batignani, G; Bettarini, S; Bondioli, M; Bucci, F; Calderini, G; Carpinelli, M; Del Gamba, V; Forti, F; Giorgi, M A; Lusiani, A; Marchiori, G; Martinez-Vidal, F; Morganti, M; Neri, N; Paoloni, E; Rama, M; Rizzo, G; Sandrelli, F; Walsh, J; Haire, M; Judd, D; Paick, K; Wagoner, D E; Danielson, N; Elmer, P; Lu, C; Miftakov, V; Olsen, J; Smith, A J S; Tanaka, H A; Varnes, E W; Bellini, F; Cavoto, G; Faccini, R; Ferrarotto, F; Ferroni, F; Gaspero, M; Mazzoni, M A; Morganti, S; Pierini, M; Piredda, G; Tehrani, F Safai; Voena, C; Christ, S; Wagner, G; Waldi, R; Adye, T; De Groot, N; Franek, B; Geddes, N I; Gopal, G P; Olaiya, E O; Xella, S M; Aleksan, R; Emery, S; Gaidot, A; Ganzhur, S F; Giraud, P-F; Hamel de Monchenault, G; Kozanecki, W; Langer, M; Legendre, M; London, G W; Mayer, B; Schott, G; Vasseur, G; Yeche, Ch; Zito, M; Purohit, M V; Weidemann, A W; Yumiceva, F X; Aston, D; Bartoldus, R; Berger, N; Boyarski, A M; Buchmueller, O L; Convery, M R; Coupal, D P; Dong, D; Dorfan, J; Dujmic, D; Dunwoodie, W; Field, R C; Glanzman, T; Gowdy, S J; Grauges-Pous, E; Hadig, T; Halyo, V; Hryn'ova, T; Innes, W R; Jessop, C P; Kelsey, M H; Kim, P; Kocian, M L; Langenegger, U; Leith, D W G S; Libby, J; Luitz, S; Luth, V; Lynch, H L; Marsiske, H; Messner, R; Muller, D R; O'Grady, C P; Ozcan, V E; Perazzo, A; Perl, M; Petrak, S; Ratcliff, B N; Roodman, A; Salnikov, A A; Schindler, R H; Schwiening, J; Simi, G; Snyder, A; Soha, A; Stelzer, J; Su, D; Sullivan, M K; Va'vra, J; Wagner, S R; Weaver, M; Weinstein, A J R; Wisniewski, W J; Wright, D H; Young, C C; Burchat, P R; Edwards, A J; Meyer, T I; Petersen, B A; Roat, C; Ahmed, M; Ahmed, S; Alam, M S; Ernst, J A; Saeed, M A; Saleem, M; Wappler, F R; Bugg, W; Krishnamurthy, M; Spanier, S M; Eckmann, R; Kim, H; Ritchie, J L; Schwitters, R F; Izen, J M; Kitayama, I; Lou, X C; Ye, S; Bianchi, F; Bona, M; Gallo, F; Gamba, D; Borean, C; Bosisio, L; Della Ricca, G; Dittongo, S; Grancagnolo, S; Lanceri, L; Poropat, P; Vitale, L; Vuagnin, G; Panvini, R S; Banerjee, Sw; Brown, C M; Fortin, D; Jackson, P D; Kowalewski, R; Roney, J M; Band, H R; Dasu, S; Datta, M; Eichenbaum, A M; Johnson, J R; Kutter, P E; Li, H; Liu, R; Di Lodovico, F; Mihalyi, A; Mohapatra, A K; Pan, Y; Prepost, R; Sekula, S J; von Wimmersperg-Toeller, J H; Wu, J; Wu, S L; Yu, Z; Neal, H

2004-06-25

We present a measurement of CP-violating asymmetries in fully reconstructed B0-->D(*)+/-pi-/+ decays in approximately 88 x 10(6) upsilon(4S)-->BBmacr; decays collected with the BABAR detector at the PEP-II asymmetric-energy B factory at SLAC. From a time-dependent maximum-likelihood fit we obtain the following for the CP-violating parameters: a=-0.022+/-0.038 (stat)+/-0.020 (syst), a*=-0.068+/-0.038 (stat)+/-0.020 (syst), c(lep)=+0.025+/-0.068 (stat)+/-0.033 (syst), and c*(lep)=+0.031+/-0.070 (stat)+/-0.033 (syst). Using other measurements and theoretical assumptions we interpret the results in terms of the angles of the Cabibbo-Kobayashi-Maskawa unitarity triangle, and find |sin((2beta+gamma)|>0.69 at 68% confidence level. We exclude the hypothesis of no CP violation [sin(2beta+gamma)=0] at 83% confidence level.

Observation of the decay B-->J/psietaK and search for X(3872)-->J/psieta.

PubMed

Aubert, B; Barate, R; Boutigny, D; Couderc, F; Gaillard, J M; Hicheur, A; Karyotakis, Y; Lees, J P; Tisserand, V; Zghiche, A; Palano, A; Pompili, A; Chen, J C; Qi, N D; Rong, G; Wang, P; Zhu, Y S; Eigen, G; Ofte, I; Stugu, B; Abrams, G S; Borgland, A W; Breon, A B; Brown, D N; Button-Shafer, J; Cahn, R N; Charles, E; Day, C T; Gill, M S; Gritsan, A V; Groysman, Y; Jacobsen, R G; Kadel, R W; Kadyk, J; Kerth, L T; Kolomensky, Yu G; Kukartsev, G; LeClerc, C; Levi, M E; Lynch, G; Mir, L M; Oddone, P J; Orimoto, T J; Pripstein, M; Roe, N A; Ronan, M T; Shelkov, V G; Telnov, A V; Wenzel, W A; Ford, K; Harrison, T J; Hawkes, C M; Morgan, S E; Watson, A T; Watson, N K; Fritsch, M; Goetzen, K; Held, T; Koch, H; Lewandowski, B; Pelizaeus, M; Steinke, M; Boyd, J T; Chevalier, N; Cottingham, W N; Kelly, M P; Latham, T E; Wilson, F F; Abe, K; Cuhadar-Donszelmann, T; Hearty, C; Mattison, T S; McKenna, J A; Thiessen, D; Kyberd, P; Teodorescu, L; Blinov, V E; Bukin, A D; Druzhinin, V P; Golubev, V B; Ivanchenko, V N; Kravchenko, E A; Onuchin, A P; Serednyakov, S I; Skovpen, Yu I; Solodov, E P; Yushkov, A N; Best, D; Bruinsma, M; Chao, M; Eschrich, I; Kirkby, D; Lankford, A J; Mandelkern, M; Mommsen, R K; Roethel, W; Stoker, D P; Buchanan, C; Hartfiel, B L; Gary, J W; Shen, B C; Wang, K; del Re, D; Hadavand, H K; Hill, E J; MacFarlane, D B; Paar, H P; Rahatlou, Sh; Sharma, V; Berryhill, J W; Campagnari, C; Dahmes, B; Levy, S L; Long, O; Lu, A; Mazur, M A; Richman, J D; Verkerke, W; Beck, T W; Eisner, A M; Heusch, C A; Lockman, W S; Schalk, T; Schmitz, R E; Schumm, B A; Seiden, A; Spradlin, P; Williams, D C; Wilson, M G; Albert, J; Chen, E; Dubois-Felsmann, G P; Dvoretskii, A; Hitlin, D G; Narsky, I; Piatenko, T; Porter, F C; Ryd, A; Samuel, A; Yang, S; Jayatilleke, S; Mancinelli, G; Meadows, B T; Sokoloff, M D; Abe, T; Blanc, F; Bloom, P; Chen, S; Clark, P J; Ford, W T; Nauenberg, U; Olivas, A; Rankin, P; Smith, J G; van Hoek, W C; Zhang, L; Harton, J L; Hu, T; Soffer, A; Toki, W H; Wilson, R J; Zeng, Q; Altenburg, D; Brandt, T; Brose, J; Colberg, T; Dickopp, M; Feltresi, E; Hauke, A; Lacker, H M; Maly, E; Müller-Pfefferkorn, R; Nogowski, R; Otto, S; Schubert, J; Schubert, K R; Schwierz, R; Spaan, B; Bernard, D; Bonneaud, G R; Brochard, F; Grenier, P; Thiebaux, Ch; Vasileiadis, G; Verderi, M; Bard, D J; Khan, A; Lavin, D; Muheim, F; Playfer, S; Andreotti, M; Azzolini, V; Bettoni, D; Bozzi, C; Calabrese, R; Cibinetto, G; Luppi, E; Negrini, M; Sarti, A; Treadwell, E; Baldini-Ferroli, R; Calcaterra, A; de Sangro, R; Finocchiaro, G; Patteri, P; Piccolo, M; Zallo, A; Buzzo, A; Capra, R; Contri, R; Crosetti, G; Lo Vetere, M; Macri, M; Monge, M R; Passaggio, S; Patrignani, C; Robutti, E; Santroni, A; Tosi, S; Bailey, S; Brandenburg, G; Morii, M; Won, E; Dubitzky, R S; Langenegger, U; Bhimji, W; Bowerman, D A; Dauncey, P D; Egede, U; Gaillard, J R; Morton, G W; Nash, J A; Taylor, G P; Grenier, G J; Lee, S J; Mallik, U; Cochran, J; Crawley, H B; Lamsa, J; Meyer, W T; Prell, S; Rosenberg, E I; Yi, J; Davier, M; Grosdidier, G; Höcker, A; Laplace, S; Le Diberder, F; Lepeltier, V; Lutz, A M; Petersen, T C; Plaszczynski, S; Schune, M H; Tantot, L; Wormser, G; Cheng, C H; Lange, D J; Simani, M C; Wright, D M; Bevan, A J; Coleman, J P; Fry, J R; Gabathuler, E; Gamet, R; Kay, M; Parry, R J; Payne, D J; Sloane, R J; Touramanis, C; Back, J J; Harrison, P F; Mohanty, G B; Brown, C L; Cowan, G; Flack, R L; Flaecher, H U; George, S; Green, M G; Kurup, A; Marker, C E; McMahon, T R; Ricciardi, S; Salvatore, F; Vaitsas, G; Winter, M A; Brown, D; Davis, C L; Allison, J; Barlow, N R; Barlow, R J; Hart, P A; Hodgkinson, M C; Lafferty, G D; Lyon, A J; Williams, J C; Farbin, A; Hulsbergen, W D; Jawahery, A; Kovalskyi, D; Lae, C K; Lillard, V; Roberts, D A; Blaylock, G; Dallapiccola, C; Flood, K T; Hertzbach, S S; Kofler, R; Koptchev, V B; Moore, T B; Saremi, S; Staengle, H; Willocq, S; Cowan, R; Sciolla, G; Taylor, F; Yamamoto, R K; Mangeol, D J J; Patel, P M; Robertson, S H; Lazzaro, A; Palombo, F; Bauer, J M; Cremaldi, L; Eschenburg, V; Godang, R; Kroeger, R; Reidy, J; Sanders, D A; Summers, D J; Zhao, H W; Brunet, S; Côté, D; Taras, P; Nicholson, H; Cartaro, C; Cavallo, N; Fabozzi, F; Gatto, C; Lista, L; Monorchio, D; Paolucci, P; Piccolo, D; Sciacca, C; Baak, M; Raven, G; Wilden, L; Jessop, C P; LoSecco, J M; Gabriel, T A; Allmendinger, T; Brau, B; Gan, K K; Honscheid, K; Hufnagel, D; Kagan, H; Kass, R; Pulliam, T; Ter-Antonyan, R; Wong, Q K; Brau, J; Frey, R; Igonkina, O; Potter, C T; Sinev, N B; Strom, D; Torrence, E; Colecchia, F; Dorigo, A; Galeazzi, F; Margoni, M; Morandin, M; Posocco, M; Rotondo, M; Simonetto, F; Stroili, R; Tiozzo, G; Voci, C; Benayoun, M; Briand, H; Chauveau, J; David, P; de la Vaissière, Ch; Del Buono, L; Hamon, O; John, M J J; Leruste, Ph; Ocariz, J; Pivk, M; Roos, L; T'Jampens, S; Therin, G; Manfredi, P F; Re, V; Behera, P K; Gladney, L; Guo, Q H; Panetta, J; Anulli, F; Biasini, M; Peruzzi, I M; Pioppi, M; Angelini, C; Batignani, G; Bettarini, S; Bondioli, M; Bucci, F; Calderini, G; Carpinelli, M; Del Gamba, V; Forti, F; Giorgi, M A; Lusiani, A; Marchiori, G; Martinez-Vidal, F; Morganti, M; Neri, N; Paoloni, E; Rama, M; Rizzo, G; Sandrelli, F; Walsh, J; Haire, M; Judd, D; Paick, K; Wagoner, D E; Danielson, N; Elmer, P; Lu, C; Miftakov, V; Olsen, J; Smith, A J S; Varnes, E W; Bellini, F; Cavoto, G; Faccini, R; Ferrarotto, F; Ferroni, F; Gaspero, M; Li Gioi, L; Mazzoni, M A; Morganti, S; Pierini, M; Piredda, G; Tehrani, F Safai; Voena, C; Christ, S; Wagner, G; Waldi, R; Adye, T; De Groot, N; Franek, B; Geddes, N I; Gopal, G P; Olaiya, E O; Xella, S M; Aleksan, R; Emery, S; Gaidot, A; Ganzhur, S F; Giraud, P F; Hamel de Monchenault, G; Kozanecki, W; Langer, M; Legendre, M; London, G W; Mayer, B; Schott, G; Vasseur, G; Yèche, Ch; Zito, M; Purohit, M V; Weidemann, A W; Yumiceva, F X; Aston, D; Bartoldus, R; Berger, N; Boyarski, A M; Buchmueller, O L; Convery, M R; Cristinziani, M; De Nardo, G; Dong, D; Dorfan, J; Dujmic, D; Dunwoodie, W; Elsen, E E; Field, R C; Glanzman, T; Gowdy, S J; Hadig, T; Halyo, V; Hryn'ova, T; Innes, W R; Kelsey, M H; Kim, P; Kocian, M L; Leith, D W G S; Libby, J; Luitz, S; Luth, V; Lynch, H L; Marsiske, H; Messner, R; Muller, D R; O'Grady, C P; Ozcan, V E; Perazzo, A; Perl, M; Petrak, S; Ratcliff, B N; Roodman, A; Salnikov, A A; Schindler, R H; Schwiening, J; Simi, G; Snyder, A; Soha, A; Stelzer, J; Su, D; Sullivan, M K; Va'vra, J; Wagner, S R; Weaver, M; Weinstein, A J R; Wisniewski, W J; Wittgen, M; Wright, D H; Young, C C; Burchat, P R; Edwards, A J; Meyer, T I; Petersen, B A; Roat, C; Ahmed, S; Alam, M S; Ernst, J A; Saeed, M A; Saleem, M; Wappler, F R; Bugg, W; Krishnamurthy, M; Spanier, S M; Eckmann, R; Kim, H; Ritchie, J L; Satpathy, A; Schwitters, R F; Izen, J M; Kitayama, I; Lou, X C; Ye, S; Bianchi, F; Bona, M; Gallo, F; Gamba, D; Borean, C; Bosisio, L; Cossutti, F; Della Ricca, G; Dittongo, S; Grancagnolo, S; Lanceri, L; Poropat, P; Vitale, L; Vuagnin, G; Panvini, R S; Banerjee, Sw; Brown, C M; Fortin, D; Jackson, P D; Kowalewski, R; Roney, J M; Band, H R; Dasu, S; Datta, M; Eichenbaum, A M; Hollar, J J; Johnson, J R; Kutter, P E; Li, H; Liu, R; Di Lodovico, F; Mihalyi, A; Mohapatra, A K; Pan, Y; Prepost, R; Sekula, S J; Tan, P; von Wimmersperg-Toeller, J H; Wu, J; Wu, S L; Yu, Z; Neal, H

2004-07-23

We report the observation of the B meson decay B+/- -->J/psietaK+/- and evidence for the decay B0-->J/psietaK0S, using 90 x 10(6) BB; events collected at the Upsilon(4S) resonance with the BABAR detector at the SLAC PEP-II e+e- asymmetric-energy storage ring. We obtain branching fractions of B(B+/- -->J/psietaK+/-) = [10.8 +/- 2.3(stat) +/- 2.4(syst)] x 10(-5) and B(B0-->J/psietaK0S) = [8.4 +/- 2.6(stat) +/- 2.7(syst)] x 10(-5). We search for the new narrow mass state, the X(3872), recently reported by the Belle Collaboration, in the decay B+/- -->X(3872)K+/-,X(3872)-->J/psieta and determine an upper limit of B[B +/- -->X(3872)K+/- -->J/psietaK+/-] < 7.7 x 10(-6) at 90% confidence level. Copyright 2004 The American Physical Society

Measurement of branching fractions and charge asymmetries in B+/--->rho+/-pi0 and B+/--->rho0pi+/- decays, and search for B0-->rho0pi0.

PubMed

Aubert, B; Barate, R; Boutigny, D; Couderc, F; Gaillard, J-M; Hicheur, A; Karyotakis, Y; Lees, J P; Robbe, P; Tisserand, V; Zghiche, A; Palano, A; Pompili, A; Chen, J C; Qi, N D; Rong, G; Wang, P; Zhu, Y S; Eigen, G; Ofte, I; Stugu, B; Abrams, G S; Borgland, A W; Breon, A B; Brown, D N; Button-Shafer, J; Cahn, R N; Charles, E; Day, C T; Gill, M S; Gritsan, A V; Groysman, Y; Jacobsen, R G; Kadel, R W; Kadyk, J; Kerth, L T; Kolomensky, Yu G; Kukartsev, G; LeClerc, C; Levi, M E; Lynch, G; Mir, L M; Oddone, P J; Orimoto, T J; Pripstein, M; Roe, N A; Romosan, A; Ronan, M T; Shelkov, V G; Telnov, A V; Wenzel, W A; Ford, K; Harrison, T J; Hawkes, C M; Knowles, D J; Morgan, S E; Penny, R C; Watson, A T; Watson, N K; Goetzen, K; Held, T; Koch, H; Lewandowski, B; Pelizaeus, M; Peters, K; Schmuecker, H; Steinke, M; Boyd, J T; Chevalier, N; Cottingham, W N; Kelly, M P; Latham, T E; Mackay, C; Wilson, F F; Abe, K; Cuhadar-Donszelmann, T; Hearty, C; Mattison, T S; McKenna, J A; Thiessen, D; Kyberd, P; McKemey, A K; Teodorescu, L; Blinov, V E; Bukin, A D; Golubev, V B; Ivanchenko, V N; Kravchenko, E A; Onuchin, A P; Serednyakov, S I; Skovpen, Yu I; Solodov, E P; Yushkov, A N; Best, D; Bruinsma, M; Chao, M; Kirkby, D; Lankford, A J; Mandelkern, M; Mommsen, R K; Roethel, W; Stoker, D P; Buchanan, C; Hartfiel, B L; Gary, J W; Layter, J; Shen, B C; Wang, K; del Re, D; Hadavand, H K; Hill, E J; MacFarlane, D B; Paar, H P; Rahatlou, Sh; Sharma, V; Berryhill, J W; Campagnari, C; Dahmes, B; Levy, S L; Long, O; Lu, A; Mazur, M A; Richman, J D; Verkerke, W; Beck, T W; Beringer, J; Eisner, A M; Heusch, C A; Lockman, W S; Schalk, T; Schmitz, R E; Schumm, B A; Seiden, A; Spradlin, P; Turri, M; Walkowiak, W; Williams, D C; Wilson, M G; Albert, J; Chen, E; Dubois-Felsmann, G P; Dvoretskii, A; Erwin, R J; Hitlin, D G; Narsky, I; Piatenko, T; Porter, F C; Ryd, A; Samuel, A; Yang, S; Jayatilleke, S; Mancinelli, G; Meadows, B T; Sokoloff, M D; Abe, T; Blanc, F; Bloom, P; Chen, S; Clark, P J; Ford, W T; Nauenberg, U; Olivas, A; Rankin, P; Roy, J; Smith, J G; van Hoek, W C; Zhang, L; Harton, J L; Hu, T; Soffer, A; Toki, W H; Wilson, R J; Zhang, J; Altenburg, D; Brandt, T; Brose, J; Colberg, T; Dickopp, M; Dubitzky, R S; Hauke, A; Lacker, H M; Maly, E; Müller-Pfefferkorn, R; Nogowski, R; Otto, S; Schubert, J; Schubert, K R; Schwierz, R; Spaan, B; Wilden, L; Bernard, D; Bonneaud, G R; Brochard, F; Cohen-Tanugi, J; Grenier, P; Thiebaux, Ch; Vasileiadis, G; Verderi, M; Khan, A; Lavin, D; Muheim, F; Playfer, S; Swain, J E; Andreotti, M; Azzolini, V; Bettoni, D; Bozzi, C; Calabrese, R; Cibinetto, G; Luppi, E; Negrini, M; Piemontese, L; Sarti, A; Treadwell, E; Baldini-Ferroli, R; Calcaterra, A; de Sangro, R; Falciai, D; Finocchiaro, G; Patteri, P; Piccolo, M; Zallo, A; Buzzo, A; Capra, R; Contri, R; Crosetti, G; Lo Vetere, M; Macri, M; Monge, M R; Passaggio, S; Patrignani, C; Robutti, E; Santroni, A; Tosi, S; Bailey, S; Morii, M; Won, E; Bhimji, W; Bowerman, D A; Dauncey, P D; Egede, U; Eschrich, I; Gaillard, J R; Morton, G W; Nash, J A; Taylor, G P; Grenier, G J; Lee, S-J; Mallik, U; Cochran, J; Crawley, H B; Lamsa, J; Meyer, W T; Prell, S; Rosenberg, E I; Yi, J; Davier, M; Grosdidier, G; Höcker, A; Laplace, S; Le Diberder, F; Lepeltier, V; Lutz, A M; Petersen, T C; Plaszczynski, S; Schune, M H; Tantot, L; Wormser, G; Brigljević, V; Cheng, C H; Lange, D J; Simani, M C; Wright, D M; Bevan, A J; Coleman, J P; Fry, J R; Gabathuler, E; Gamet, R; Kay, M; Parry, R J; Payne, D J; Sloane, R J; Touramanis, C; Back, J J; Harrison, P F; Shorthouse, H W; Vidal, P B; Brown, C L; Cowan, G; Flack, R L; Flaecher, H U; George, S; Green, M G; Kurup, A; Marker, C E; McMahon, T R; Ricciardi, S; Salvatore, F; Vaitsas, G; Winter, M A; Brown, D; Davis, C L; Allison, J; Barlow, N R; Barlow, R J; Hart, P A; Hodgkinson, M C; Jackson, F; Lafferty, G D; Lyon, A J; Weatherall, J H; Williams, J C; Farbin, A; Jawahery, A; Kovalskyi, D; Lae, C K; Lillard, V; Roberts, D A; Blaylock, G; Dallapiccola, C; Flood, K T; Hertzbach, S S; Kofler, R; Koptchev, V B; Moore, T B; Saremi, S; Staengle, H; Willocq, S; Cowan, R; Sciolla, G; Taylor, F; Yamamoto, R K; Mangeol, D J J; Patel, P M; Robertson, S H; Lazzaro, A; Palombo, F; Bauer, J M; Cremaldi, L; Eschenburg, V; Godang, R; Kroeger, R; Reidy, J; Sanders, D A; Summers, D J; Zhao, H W; Brunet, S; Cote-Ahern, D; Taras, P; Nicholson, H; Cartaro, C; Cavallo, N; De Nardo, G; Fabozzi, F; Gatto, C; Lista, L; Paolucci, P; Piccolo, D; Sciacca, C; Baak, M A; Raven, G; LoSecco, J M; Gabriel, T A; Brau, B; Gan, K K; Honscheid, K; Hufnagel, D; Kagan, H; Kass, R; Pulliam, T; Wong, Q K; Brau, J; Frey, R; Igonkina, O; Potter, C T; Sinev, N B; Strom, D; Torrence, E; Colecchia, F; Dorigo, A; Galeazzi, F; Margoni, M; Morandin, M; Posocco, M; Rotondo, M; Simonetto, F; Stroili, R; Tiozzo, G; Voci, C; Benayoun, M; Briand, H; Chauveau, J; David, P; de la Vaissière, Ch; Del Buono, L; Hamon, O; John, M J J; Leruste, Ph; Ocariz, J; Pivk, M; Roos, L; Stark, J; T'Jampens, S; Therin, G; Manfredi, P F; Re, V; Behera, P K; Gladney, L; Guo, Q H; Panetta, J; Anulli, F; Biasini, M; Peruzzi, I M; Pioppi, M; Angelini, C; Batignani, G; Bettarini, S; Bondioli, M; Bucci, F; Calderini, G; Carpinelli, M; Del Gamba, V; Forti, F; Giorgi, M A; Lusiani, A; Marchiori, G; Martinez-Vidal, F; Morganti, M; Neri, N; Paoloni, E; Rama, M; Rizzo, G; Sandrelli, F; Walsh, J; Haire, M; Judd, D; Paick, K; Wagoner, D E; Danielson, N; Elmer, P; Lu, C; Miftakov, V; Olsen, J; Smith, A J S; Tanaka, H A; Varnes, E W; Bellini, F; Cavoto, G; Faccini, R; Ferrarotto, F; Ferroni, F; Gaspero, M; Mazzoni, M A; Morganti, S; Pierini, M; Piredda, G; Safai Tehrani, F; Voena, C; Christ, S; Wagner, G; Waldi, R; Adye, T; De Groot, N; Franek, B; Geddes, N I; Gopal, G P; Olaiya, E O; Xella, S M; Aleksan, R; Emery, S; Gaidot, A; Ganzhur, S F; Giraud, P-F; Hamel de Monchenault, G; Kozanecki, W; Langer, M; Legendre, M; London, G W; Mayer, B; Schott, G; Vasseur, G; Yeche, Ch; Zito, M; Purohit, M V; Weidemann, A W; Yumiceva, F X; Aston, D; Bartoldus, R; Berger, N; Boyarski, A M; Buchmueller, O L; Convery, M R; Cristinziani, M; Dong, D; Dorfan, J; Dujmic, D; Dunwoodie, W; Elsen, E E; Field, R C; Glanzman, T; Gowdy, S J; Grauges-Pous, E; Hadig, T; Halyo, V; Hast, C; Hryn'ova, T; Innes, W R; Jessop, C P; Kelsey, M H; Kim, P; Kocian, M L; Langenegger, U; Leith, D W G S; Libby, J; Luitz, S; Luth, V; Lynch, H L; Marsiske, H; Messner, R; Muller, D R; O'Grady, C P; Ozcan, V E; Perazzo, A; Perl, M; Petrak, S; Ratcliff, B N; Roodman, A; Salnikov, A A; Schindler, R H; Schwiening, J; Simi, G; Snyder, A; Soha, A; Stelzer, J; Su, D; Sullivan, M K; Va'vra, J; Wagner, S R; Weaver, M; Weinstein, A J R; Wisniewski, W J; Wright, D H; Young, C C; Burchat, P R; Edwards, A J; Meyer, T I; Petersen, B A; Roat, C; Ahmed, M; Ahmed, S; Alam, M S; Ernst, J A; Saeed, M A; Saleem, M; Wappler, F R; Bugg, W; Krishnamurthy, M; Spanier, S M; Eckmann, R; Kim, H; Ritchie, J L; Schwitters, R F; Izen, J M; Kitayama, I; Lou, X C; Ye, S; Bianchi, F; Bona, M; Gallo, F; Gamba, D; Borean, C; Bosisio, L; Della Ricca, G; Dittongo, S; Grancagnolo, S; Lanceri, L; Poropat, P; Vitale, L; Vuagnin, G; Panvini, R S; Banerjee, Sw; Brown, C M; Fortin, D; Jackson, P D; Kowalewski, R; Roney, J M; Band, H R; Dasu, S; Datta, M; Eichenbaum, A M; Johnson, J R; Kutter, P E; Li, H; Liu, R; Di Lodovico, F; Mihalyi, A; Mohapatra, A K; Pan, Y; Prepost, R; Sekula, S J; von Wimmersperg-Toeller, J H; Wu, J; Wu, S L; Yu, Z; Neal, H

2004-07-30

We present measurements of branching fractions and charge asymmetries in B-meson decays to rho(+)pi(0), rho(0)pi(+), and rho(0)pi(0). The data sample comprises 89x10(6) Upsilon(4S)-->BBmacr; decays collected with the BABAR detector at the PEP-II asymmetric-energy B Factory at SLAC. We find the charge-averaged branching fractions B(B+-->rho(+)pi(0))=[10.9+/-1.9(stat)+/-1.9(syst)]x10(-6) and B(B+-->rho(0)pi(+))=(9.5+/-1.1+/-0.9)x10(-6), and we set a 90% confidence-level upper limit B(B0-->rho(0)pi(0))<2.9x10(-6). We measure the charge asymmetries ACP(pi(0))(rho(+))=0.24+/-0.16+/-0.06 and ACP(pi(+))(rho(0))=-0.19+/-0.11+/-0.02.

No-Go Theorem for Nonstandard Explanations of the τ →KSπ ντ C P Asymmetry

NASA Astrophysics Data System (ADS)

Cirigliano, Vincenzo; Crivellin, Andreas; Hoferichter, Martin

2018-04-01

The C P asymmetry in τ →KSπ ντ , as measured by the BABAR collaboration, differs from the standard model prediction by 2.8 σ . Most nonstandard interactions do not allow for the required strong phase needed to produce a nonvanishing C P asymmetry, leaving only new tensor interactions as a possible mechanism. We demonstrate that, contrary to previous assumptions in the literature, the crucial interference between vector and tensor phases is suppressed by at least 2 orders of magnitude due to Watson's final-state-interaction theorem. Furthermore, we find that the strength of the relevant C P -violating tensor interaction is strongly constrained by bounds from the neutron electric dipole moment and D - D ¯ mixing. These observations together imply that it is extremely difficult to explain the current τ →KSπ ντ measurement in terms of physics beyond the standard model originating in the ultraviolet.

Improved Limits on $$B^{0}$$ Decays to Invisible $(+gamma)$ Final States

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lees, J.P.; Poireau, V.; Tisserand, V.

2013-11-01

We establish improved upper limits on branching fractions for B{sup 0} decays to final states where the decay products are purely invisible (i.e., no observable final state particles) and for final states where the only visible product is a photon. Within the Standard Model, these decays have branching fractions that are below the current experimental sensitivity, but various models of physics beyond the Standard Model predict significant contributions for these channels. Using 471 million B{bar B} pairs collected at the {Upsilon} (4S) resonance by the BABAR experiment at the PEP-II e{sup +}e{sup -} storage ring at the SLAC National Acceleratormore » Laboratory, we establish upper limits at the 90% confidence level of 2.4 x 10{sup -5} for the branching fraction of B{sup 0} {yields} invisible and 1.7 x 10{sup -5} for the branching fraction of B{sup 0} {yields} invisible + {gamma}.« less

Charmonium Decays of Y(4260), psi(4160), and psi(4040).

PubMed

Coan, T E; Gao, Y S; Liu, F; Artuso, M; Blusk, S; Butt, J; Li, J; Menaa, N; Mountain, R; Nisar, S; Randrianarivony, K; Redjimi, R; Sia, R; Skwarnicki, T; Stone, S; Wang, J C; Zhang, K; Csorna, S E; Bonvicini, G; Cinabro, D; Dubrovin, M; Lincoln, A; Asner, D M; Edwards, K W; Briere, R A; Brock, I; Chen, J; Ferguson, T; Tatishvili, G; Vogel, H; Watkins, M E; Rosner, J L; Adam, N E; Alexander, J P; Berkelman, K; Cassel, D G; Duboscq, J E; Ecklund, K M; Ehrlich, R; Fields, L; Galik, R S; Gibbons, L; Gray, R; Gray, S W; Hartill, D L; Heltsley, B K; Hertz, D; Jones, C D; Kandaswamy, J; Kreinick, D L; Kuznetsov, V E; Mahlke-Krüger, H; Meyer, T O; Onyisi, P U E; Patterson, J R; Peterson, D; Phillips, E A; Pivarski, J; Riley, D; Ryd, A; Sadoff, A J; Schwarthoff, H; Shi, X; Stroiney, S; Sun, W M; Wilksen, T; Weinberger, M; Athar, S B; Avery, P; Breva-Newell, L; Patel, R; Potlia, V; Stoeck, H; Yelton, J; Rubin, P; Cawlfield, C; Eisenstein, B I; Karliner, I; Kim, D; Lowrey, N; Naik, P; Sedlack, C; Selen, M; White, E J; Wiss, J; Shepherd, M R; Besson, D; Pedlar, T K; Cronin-Hennessy, D; Gao, K Y; Gong, D T; Hietala, J; Kubota, Y; Klein, T; Lang, B W; Poling, R; Scott, A W; Smith, A; Dobbs, S; Metreveli, Z; Seth, K K; Tomaradze, A; Zweber, P; Ernst, J; Severini, H; Dytman, S A; Love, W; Savinov, V; Aquines, O; Li, Z; Lopez, A; Mehrabyan, S; Mendez, H; Ramirez, J; Huang, G S; Miller, D H; Pavlunin, V; Sanghi, B; Shipsey, I P J; Xin, B; Adams, G S; Anderson, M; Cummings, J P; Danko, I; Napolitano, J; He, Q; Insler, J; Muramatsu, H; Park, C S; Thorndike, E H

2006-04-28

Using data collected with the CLEO detector operating at the CESR e+e- collider at sqrt[s]=3.97-4.26 GeV, we investigate 15 charmonium decay modes of the psi(4040), psi(4160), and Y(4260) resonances. We confirm, at 11 sigma significance, the BABAR Y(4260)-->pi+pi- J/psi discovery, make the first observation of Y(4260)--> pi(0)pi(0) J/psi (5.1 sigma), and find the first evidence for Y(4260)-->K+K- J/psi(3.7 sigma). We measure e+e- cross sections at sqrt[s]=4.26 GeV as sigma(pi+pi- J/psi)=58(+12)(-10)+/-4 pb, sigma(pi(0)pi(0) J/psi)=23(+12)(-8)+/-1 pb, and sigma(K+K- J/psi)=9(+9)(-5)+/-1 pb, in which the uncertainties are statistical and systematic, respectively. Upper limits are placed on other decay rates from all three resonances.

The branching ratio ω → π ^+π ^- revisited

NASA Astrophysics Data System (ADS)

Hanhart, C.; Holz, S.; Kubis, B.; Kupść, A.; Wirzba, A.; Xiao, C. W.

2017-02-01

We analyze the most recent data for the pion vector form factor in the timelike region, employing a model-independent approach based on dispersion theory. We confirm earlier observations about the inconsistency of different modern high-precision data sets. Excluding the BaBar data, we find an updated value for the isospin-violating branching ratio B(ω → π ^+π ^-) = (1.46± 0.08) × 10^{-2}. As a side result, we also extract an improved value for the pion vector or charge radius, √{< r_V^2rangle } = 0.6603(5)(4) {fm}, where the first uncertainty is statistical as derived from the fit, while the second estimates the possible size of nonuniversal radiative corrections. In addition, we demonstrate that modern high-quality data for the decay η '→ π ^+π ^-γ will allow for an even improved determination of the transition strength ω → π ^+π ^-.

Observation of the decay B- → D(s)((*)+) K- ℓ- ν(ℓ).

PubMed

Sanchez, P del Amo; Lees, J P; Poireau, V; Prencipe, E; Tisserand, V; Garra Tico, J; Grauges, E; Martinelli, M; Palano, A; Pappagallo, M; Eigen, G; Stugu, B; Sun, L; Battaglia, M; Brown, D N; Hooberman, B; Kerth, L T; Kolomensky, Yu G; Lynch, G; Osipenkov, I L; Tanabe, T; Hawkes, C M; Watson, A T; Koch, H; Schroeder, T; Asgeirsson, D J; Hearty, C; Mattison, T S; McKenna, J A; Khan, A; Randle-Conde, A; Blinov, V E; Buzykaev, A R; Druzhinin, V P; Golubev, V B; Onuchin, A P; Serednyakov, S I; Skovpen, Yu I; Solodov, E P; Todyshev, K Yu; Yushkov, A N; Bondioli, M; Curry, S; Kirkby, D; Lankford, A J; Mandelkern, M; Martin, E C; Stoker, D P; Atmacan, H; Gary, J W; Liu, F; Long, O; Vitug, G M; Campagnari, C; Hong, T M; Kovalskyi, D; Richman, J D; Eisner, A M; Heusch, C A; Kroseberg, J; Lockman, W S; Martinez, A J; Schalk, T; Schumm, B A; Seiden, A; Winstrom, L O; Cheng, C H; Doll, D A; Echenard, B; Hitlin, D G; Ongmongkolkul, P; Porter, F C; Rakitin, A Y; Andreassen, R; Dubrovin, M S; Mancinelli, G; Meadows, B T; Sokoloff, M D; Bloom, P C; Ford, W T; Gaz, A; Nagel, M; Nauenberg, U; Smith, J G; Wagner, S R; Ayad, R; Toki, W H; Jasper, H; Karbach, T M; Merkel, J; Petzold, A; Spaan, B; Wacker, K; Kobel, M J; Schubert, K R; Schwierz, R; Bernard, D; Verderi, M; Clark, P J; Playfer, S; Watson, J E; Andreotti, M; Bettoni, D; Bozzi, C; Calabrese, R; Cecchi, A; Cibinetto, G; Fioravanti, E; Franchini, P; Luppi, E; Munerato, M; Negrini, M; Petrella, A; Piemontese, L; Baldini-Ferroli, R; Calcaterra, A; de Sangro, R; Finocchiaro, G; Nicolaci, M; Pacetti, S; Patteri, P; Peruzzi, I M; Piccolo, M; Rama, M; Zallo, A; Contri, R; Guido, E; Lo Vetere, M; Monge, M R; Passaggio, S; Patrignani, C; Robutti, E; Tosi, S; Bhuyan, B; Prasad, V; Lee, C L; Morii, M; Adametz, A; Marks, J; Schenk, S; Uwer, U; Bernlochner, F U; Ebert, M; Lacker, H M; Lueck, T; Volk, A; Dauncey, P D; Tibbetts, M; Behera, P K; Mallik, U; Chen, C; Cochran, J; Crawley, H B; Dong, L; Meyer, W T; Prell, S; Rosenberg, E I; Rubin, A E; Gao, Y Y; Gritsan, A V; Guo, Z J; Arnaud, N; Davier, M; Derkach, D; da Costa, J Firmino; Grosdidier, G; Le Diberder, F; Lutz, A M; Malaescu, B; Perez, A; Roudeau, P; Schune, M H; Serrano, J; Sordini, V; Stocchi, A; Wang, L; Wormser, G; Lange, D J; Wright, D M; Bingham, I; Chavez, C A; Coleman, J P; Fry, J R; Gabathuler, E; Gamet, R; Hutchcroft, D E; Payne, D J; Touramanis, C; Bevan, A J; Di Lodovico, F; Sacco, R; Sigamani, M; Cowan, G; Paramesvaran, S; Wren, A C; Brown, D N; Davis, C L; Denig, A G; Fritsch, M; Gradl, W; Hafner, A; Alwyn, K E; Bailey, D; Barlow, R J; Jackson, G; Lafferty, G D; West, T J; Anderson, J; Cenci, R; Jawahery, A; Roberts, D A; Simi, G; Tuggle, J M; Dallapiccola, C; Salvati, E; Cowan, R; Dujmic, D; Fisher, P H; Sciolla, G; Zhao, M; Lindemann, D; Patel, P M; Robertson, S H; Schram, M; Biassoni, P; Lazzaro, A; Lombardo, V; Palombo, F; Stracka, S; Cremaldi, L; Godang, R; Kroeger, R; Sonnek, P; Summers, D J; Nguyen, X; Simard, M; Taras, P; De Nardo, G; Monorchio, D; Onorato, G; Sciacca, C; Raven, G; Snoek, H L; Jessop, C P; Knoepfel, K J; LoSecco, J M; Wang, W F; Corwin, L A; Honscheid, K; Kass, R; Morris, J P; Rahimi, A M; Blount, N L; Brau, J; Frey, R; Igonkina, O; Kolb, J A; Rahmat, R; Sinev, N B; Strom, D; Strube, J; Torrence, E; Castelli, G; Feltresi, E; Gagliardi, N; Margoni, M; Morandin, M; Posocco, M; Rotondo, M; Simonetto, F; Stroili, R; Ben-Haim, E; Bonneaud, G R; Briand, H; Calderini, G; Chauveau, J; Hamon, O; Leruste, Ph; Marchiori, G; Ocariz, J; Prendki, J; Sitt, S; Biasini, M; Manoni, E; Rossi, A; Angelini, C; Batignani, G; Bettarini, S; Carpinelli, M; Casarosa, G; Cervelli, A; Forti, F; Giorgi, M A; Lusiani, A; Neri, N; Paoloni, E; Rizzo, G; Walsh, J J; Pegna, D Lopes; Lu, C; Olsen, J; Smith, A J S; Telnov, A V; Anulli, F; Baracchini, E; Cavoto, G; Faccini, R; Ferrarotto, F; Ferroni, F; Gaspero, M; Li Gioi, L; Mazzoni, M A; Piredda, G; Renga, F; Hartmann, T; Leddig, T; Schröder, H; Waldi, R; Adye, T; Franek, B; Olaiya, E O; Wilson, F F; Emery, S; de Monchenault, G Hamel; Vasseur, G; Yèche, Ch; Zito, M; Allen, M T; Aston, D; Bard, D J; Bartoldus, R; Benitez, J F; Cartaro, C; Convery, M R; Dorfan, J; Dubois-Felsmann, G P; Dunwoodie, W; Field, R C; Sevilla, M Franco; Fulsom, B G; Gabareen, A M; Graham, M T; Grenier, P; Hast, C; Innes, W R; Kelsey, M H; Kim, H; Kim, P; Kocian, M L; Leith, D W G S; Li, S; Lindquist, B; Luitz, S; Luth, V; Lynch, H L; MacFarlane, D B; Marsiske, H; Muller, D R; Neal, H; Nelson, S; O'Grady, C P; Ofte, I; Perl, M; Pulliam, T; Ratcliff, B N; Roodman, A; Salnikov, A A; Santoro, V; Schindler, R H; Schwiening, J; Snyder, A; Su, D; Sullivan, M K; Sun, S; Suzuki, K; Thompson, J M; Va'vra, J; Wagner, A P; Weaver, M; West, C A; Wisniewski, W J; Wittgen, M; Wright, D H; Wulsin, H W; Yarritu, A K; Young, C C; Ziegler, V; Chen, X R; Park, W; Purohit, M V; White, R M; Wilson, J R; Sekula, S J; Bellis, M; Burchat, P R; Edwards, A J; Miyashita, T S; Ahmed, S; Alam, M S; Ernst, J A; Pan, B; Saeed, M A; Zain, S B; Guttman, N; Soffer, A; Lund, P; Spanier, S M; Eckmann, R; Ritchie, J L; Ruland, A M; Schilling, C J; Schwitters, R F; Wray, B C; Izen, J M; Lou, X C; Bianchi, F; Gamba, D; Pelliccioni, M; Bomben, M; Lanceri, L; Vitale, L; Lopez-March, N; Martinez-Vidal, F; Milanes, D A; Oyanguren, A; Albert, J; Banerjee, Sw; Choi, H H F; Hamano, K; King, G J; Kowalewski, R; Lewczuk, M J; Nugent, I M; Roney, J M; Sobie, R J; Gershon, T J; Harrison, P F; Latham, T E; Puccio, E M T; Band, H R; Dasu, S; Flood, K T; Pan, Y; Prepost, R; Vuosalo, C O; Wu, S L

2011-07-22

We report the observation of the decay B- → D(s)((*)+) K- ℓ- ν(ℓ) based on 342  fb(-1) of data collected at the Υ(4S) resonance with the BABAR detector at the PEP-II e+ e- storage rings at SLAC. A simultaneous fit to three D(s)(+) decay chains is performed to extract the signal yield from measurements of the squared missing mass in the B meson decay. We observe the decay B- → D(s)((*)+) K- ℓ- ν(ℓ) with a significance greater than 5 standard deviations (including systematic uncertainties) and measure its branching fraction to be B(B- → D(s)((*)+) K- ℓ- ν(ℓ)) = [6.13(-1.03)(+1.04)(stat)±0.43(syst)±0.51(B(D(s)))]×10(-4), where the last error reflects the limited knowledge of the D(s) branching fractions.

Study of the process e+e-→π+π-η using initial state radiation

NASA Astrophysics Data System (ADS)

Lees, J. P.; Poireau, V.; Tisserand, V.; Grauges, E.; Palano, A.; Eigen, G.; Brown, D. N.; Kolomensky, Yu. G.; Fritsch, M.; Koch, H.; Schroeder, T.; Hearty, C.; Mattison, T. S.; McKenna, J. A.; So, R. Y.; Blinov, V. E.; Buzykaev, A. R.; Druzhinin, V. P.; Golubev, V. B.; Kozyrev, E. A.; Kravchenko, E. A.; Onuchin, A. P.; Serednyakov, S. I.; Skovpen, Yu. I.; Solodov, E. P.; Todyshev, K. Yu.; Lankford, A. J.; Gary, J. W.; Long, O.; Eisner, A. M.; Lockman, W. S.; Panduro Vazquez, W.; Chao, D. S.; Cheng, C. H.; Echenard, B.; Flood, K. T.; Hitlin, D. G.; Kim, J.; Li, Y.; Miyashita, T. S.; Ongmongkolkul, P.; Porter, F. C.; Röhrken, M.; Huard, Z.; Meadows, B. T.; Pushpawela, B. G.; Sokoloff, M. D.; Sun, L.; Smith, J. G.; Wagner, S. R.; Bernard, D.; Verderi, M.; Bettoni, D.; Bozzi, C.; Calabrese, R.; Cibinetto, G.; Fioravanti, E.; Garzia, I.; Luppi, E.; Santoro, V.; Calcaterra, A.; de Sangro, R.; Finocchiaro, G.; Martellotti, S.; Patteri, P.; Peruzzi, I. M.; Piccolo, M.; Rotondo, M.; Zallo, A.; Passaggio, S.; Patrignani, C.; Lacker, H. M.; Bhuyan, B.; Mallik, U.; Chen, C.; Cochran, J.; Prell, S.; Gritsan, A. V.; Arnaud, N.; Davier, M.; Le Diberder, F.; Lutz, A. M.; Wormser, G.; Lange, D. J.; Wright, D. M.; Coleman, J. P.; Gabathuler, E.; Hutchcroft, D. E.; Payne, D. J.; Touramanis, C.; Bevan, A. J.; Di Lodovico, F.; Sacco, R.; Cowan, G.; Banerjee, Sw.; Brown, D. N.; Davis, C. L.; Denig, A. G.; Gradl, W.; Griessinger, K.; Hafner, A.; Schubert, K. R.; Barlow, R. J.; Lafferty, G. D.; Cenci, R.; Jawahery, A.; Roberts, D. A.; Cowan, R.; Robertson, S. H.; Seddon, R. M.; Dey, B.; Neri, N.; Palombo, F.; Cheaib, R.; Cremaldi, L.; Godang, R.; Summers, D. J.; Taras, P.; De Nardo, G.; Sciacca, C.; Raven, G.; Jessop, C. P.; LoSecco, J. M.; Honscheid, K.; Kass, R.; Gaz, A.; Margoni, M.; Posocco, M.; Simi, G.; Simonetto, F.; Stroili, R.; Akar, S.; Ben-Haim, E.; Bomben, M.; Bonneaud, G. R.; Calderini, G.; Chauveau, J.; Marchiori, G.; Ocariz, J.; Biasini, M.; Manoni, E.; Rossi, A.; Batignani, G.; Bettarini, S.; Carpinelli, M.; Casarosa, G.; Chrzaszcz, M.; Forti, F.; Giorgi, M. A.; Lusiani, A.; Oberhof, B.; Paoloni, E.; Rama, M.; Rizzo, G.; Walsh, J. J.; Zani, L.; Smith, A. J. S.; Anulli, F.; Faccini, R.; Ferrarotto, F.; Ferroni, F.; Pilloni, A.; Piredda, G.; Bünger, C.; Dittrich, S.; Grünberg, O.; Heß, M.; Leddig, T.; Voß, C.; Waldi, R.; Adye, T.; Wilson, F. F.; Emery, S.; Vasseur, G.; Aston, D.; Cartaro, C.; Convery, M. R.; Dorfan, J.; Dunwoodie, W.; Ebert, M.; Field, R. C.; Fulsom, B. G.; Graham, M. T.; Hast, C.; Innes, W. R.; Kim, P.; Leith, D. W. G. S.; Luitz, S.; MacFarlane, D. B.; Muller, D. R.; Neal, H.; Ratcliff, B. N.; Roodman, A.; Sullivan, M. K.; Va'vra, J.; Wisniewski, W. J.; Purohit, M. V.; Wilson, J. R.; Randle-Conde, A.; Sekula, S. J.; Ahmed, H.; Bellis, M.; Burchat, P. R.; Puccio, E. M. T.; Alam, M. S.; Ernst, J. A.; Gorodeisky, R.; Guttman, N.; Peimer, D. R.; Soffer, A.; Spanier, S. M.; Ritchie, J. L.; Schwitters, R. F.; Izen, J. M.; Lou, X. C.; Bianchi, F.; De Mori, F.; Filippi, A.; Gamba, D.; Lanceri, L.; Vitale, L.; Martinez-Vidal, F.; Oyanguren, A.; Albert, J.; Beaulieu, A.; Bernlochner, F. U.; King, G. J.; Kowalewski, R.; Lueck, T.; Nugent, I. M.; Roney, J. M.; Sobie, R. J.; Tasneem, N.; Gershon, T. J.; Harrison, P. F.; Latham, T. E.; Prepost, R.; Wu, S. L.; BaBar Collaboration

2018-03-01

We study the process e+e- →π+π- η γ , where the photon is radiated from the initial state. About 8000 fully reconstructed events of this process are selected from the BABAR data sample with an integrated luminosity of 469 fb-1 . Using the π+π-η invariant mass spectrum, we measure the e+e-→π+π- η cross section in the e+e- center-of-mass energy range from 1.15 to 3.5 GeV. The cross section is well described by the Vector-Meson dominance model with four ρ -like states. We observe 49 ±9 events of the J /ψ decay to π+π- η and measure the product ΓJ /Ψ →e+e-BJ /Ψ →π+π-η=2.34 ±0.4 3stat±0.1 6syst eV .

The PANDA DIRC detectors at FAIR

NASA Astrophysics Data System (ADS)

Schwarz, C.; Ali, A.; Belias, A.; Dzhygadlo, R.; Gerhardt, A.; Götzen, K.; Kalicy, G.; Krebs, M.; Lehmann, D.; Nerling, F.; Patsyuk, M.; Peters, K.; Schepers, G.; Schmitt, L.; Schwiening, J.; Traxler, M.; Zühlsdorf, M.; Böhm, M.; Britting, A.; Eyrich, W.; Lehmann, A.; Pfaffinger, M.; Uhlig, F.; Düren, M.; Etzelmüller, E.; Föhl, K.; Hayrapetyan, A.; Kreutzfeld, K.; Kröck, B.; Merle, O.; Rieke, J.; Schmidt, M.; Wasem, T.; Achenbach, P.; Cardinali, M.; Hoek, M.; Lauth, W.; Schlimme, S.; Sfienti, C.; Thiel, M.; Allison, L.; Hyde, C.

2017-07-01

The PANDA detector at the international accelerator Facility for Antiproton and Ion Research in Europe (FAIR) addresses fundamental questions of hadron physics. An excellent hadronic particle identification (PID) will be accomplished by two DIRC (Detection of Internally Reflected Cherenkov light) counters in the target spectrometer. The design for the barrel region covering polar angles between 22o to 140o is based on the successful BABAR DIRC with several key improvements, such as fast photon timing and a compact imaging region. The novel Endcap Disc DIRC will cover the smaller forward angles between 5o (10o) to 22o in the vertical (horizontal) direction. Both DIRC counters will use lifetime-enhanced microchannel plate PMTs for photon detection in combination with fast readout electronics. Geant4 simulations and tests with several prototypes at various beam facilities have been used to evaluate the designs and validate the expected PID performance of both PANDA DIRC counters.

Search for the decay D0→γγ and measurement of the branching fraction for D0→π0π0

NASA Astrophysics Data System (ADS)

Lees, J. P.; Poireau, V.; Prencipe, E.; Tisserand, V.; Garra Tico, J.; Grauges, E.; Martinelli, M.; Milanes, D. A.; Palano, A.; Pappagallo, M.; Eigen, G.; Stugu, B.; Sun, L.; Brown, D. N.; Kerth, L. T.; Kolomensky, Yu. G.; Lynch, G.; Koch, H.; Schroeder, T.; Asgeirsson, D. J.; Hearty, C.; Mattison, T. S.; McKenna, J. A.; Khan, A.; Blinov, V. E.; Buzykaev, A. R.; Druzhinin, V. P.; Golubev, V. B.; Kravchenko, E. A.; Onuchin, A. P.; Serednyakov, S. I.; Skovpen, Yu. I.; Solodov, E. P.; Todyshev, K. Yu.; Yushkov, A. N.; Bondioli, M.; Curry, S.; Kirkby, D.; Lankford, A. J.; Mandelkern, M.; Stoker, D. P.; Atmacan, H.; Gary, J. W.; Liu, F.; Long, O.; Vitug, G. M.; Campagnari, C.; Hong, T. M.; Kovalskyi, D.; Richman, J. D.; West, C. A.; Eisner, A. M.; Kroseberg, J.; Lockman, W. S.; Martinez, A. J.; Schalk, T.; Schumm, B. A.; Seiden, A.; Cheng, C. H.; Doll, D. A.; Echenard, B.; Flood, K. T.; Hitlin, D. G.; Ongmongkolkul, P.; Porter, F. C.; Rakitin, A. Y.; Andreassen, R.; Dubrovin, M. S.; Meadows, B. T.; Sokoloff, M. D.; Bloom, P. C.; Ford, W. T.; Gaz, A.; Nagel, M.; Nauenberg, U.; Smith, J. G.; Wagner, S. R.; Ayad, R.; Toki, W. H.; Spaan, B.; Kobel, M. J.; Schubert, K. R.; Schwierz, R.; Bernard, D.; Verderi, M.; Clark, P. J.; Playfer, S.; Watson, J. E.; Bettoni, D.; Bozzi, C.; Calabrese, R.; Cibinetto, G.; Fioravanti, E.; Garzia, I.; Luppi, E.; Munerato, M.; Negrini, M.; Piemontese, L.; Baldini-Ferroli, R.; Calcaterra, A.; de Sangro, R.; Finocchiaro, G.; Nicolaci, M.; Pacetti, S.; Patteri, P.; Peruzzi, I. M.; Piccolo, M.; Rama, M.; Zallo, A.; Contri, R.; Guido, E.; Lo Vetere, M.; Monge, M. R.; Passaggio, S.; Patrignani, C.; Robutti, E.; Bhuyan, B.; Prasad, V.; Lee, C. L.; Morii, M.; Edwards, A. J.; Adametz, A.; Marks, J.; Uwer, U.; Bernlochner, F. U.; Ebert, M.; Lacker, H. M.; Lueck, T.; Dauncey, P. D.; Tibbetts, M.; Behera, P. K.; Mallik, U.; Chen, C.; Cochran, J.; Crawley, H. B.; Meyer, W. T.; Prell, S.; Rosenberg, E. I.; Rubin, A. E.; Gritsan, A. V.; Guo, Z. J.; Arnaud, N.; Davier, M.; Derkach, D.; Grosdidier, G.; Le Diberder, F.; Lutz, A. M.; Malaescu, B.; Roudeau, P.; Schune, M. H.; Stocchi, A.; Wormser, G.; Lange, D. J.; Wright, D. M.; Bingham, I.; Chavez, C. A.; Coleman, J. P.; Fry, J. R.; Gabathuler, E.; Hutchcroft, D. E.; Payne, D. J.; Touramanis, C.; Bevan, A. J.; Di Lodovico, F.; Sacco, R.; Sigamani, M.; Cowan, G.; Paramesvaran, S.; Brown, D. N.; Davis, C. L.; Denig, A. G.; Fritsch, M.; Gradl, W.; Hafner, A.; Alwyn, K. E.; Bailey, D.; Barlow, R. J.; Jackson, G.; Lafferty, G. D.; Cenci, R.; Hamilton, B.; Jawahery, A.; Roberts, D. A.; Simi, G.; Dallapiccola, C.; Salvati, E.; Cowan, R.; Dujmic, D.; Sciolla, G.; Lindemann, D.; Patel, P. M.; Robertson, S. H.; Schram, M.; Biassoni, P.; Lazzaro, A.; Lombardo, V.; Palombo, F.; Stracka, S.; Cremaldi, L.; Godang, R.; Kroeger, R.; Sonnek, P.; Summers, D. J.; Nguyen, X.; Taras, P.; De Nardo, G.; Monorchio, D.; Onorato, G.; Sciacca, C.; Raven, G.; Snoek, H. L.; Jessop, C. P.; Knoepfel, K. J.; LoSecco, J. M.; Wang, W. F.; Honscheid, K.; Kass, R.; Morris, J. P.; Brau, J.; Frey, R.; Sinev, N. B.; Strom, D.; Torrence, E.; Feltresi, E.; Gagliardi, N.; Margoni, M.; Morandin, M.; Posocco, M.; Rotondo, M.; Simonetto, F.; Stroili, R.; Ben-Haim, E.; Bomben, M.; Bonneaud, G. R.; Briand, H.; Calderini, G.; Chauveau, J.; Hamon, O.; Leruste, Ph.; Marchiori, G.; Ocariz, J.; Sitt, S.; Biasini, M.; Manoni, E.; Rossi, A.; Angelini, C.; Batignani, G.; Bettarini, S.; Carpinelli, M.; Casarosa, G.; Cervelli, A.; Forti, F.; Giorgi, M. A.; Lusiani, A.; Neri, N.; Oberhof, B.; Paoloni, E.; Perez, A.; Rizzo, G.; Walsh, J. J.; Lopes Pegna, D.; Lu, C.; Olsen, J.; Smith, A. J. S.; Telnov, A. V.; Anulli, F.; Cavoto, G.; Faccini, R.; Ferrarotto, F.; Ferroni, F.; Gaspero, M.; Li Gioi, L.; Mazzoni, M. A.; Piredda, G.; Buenger, C.; Hartmann, T.; Leddig, T.; Schröder, H.; Waldi, R.; Adye, T.; Olaiya, E. O.; Wilson, F. F.; Emery, S.; Hamel de Monchenault, G.; Vasseur, G.; Yèche, Ch.; Aston, D.; Bard, D. J.; Bartoldus, R.; Benitez, J. F.; Cartaro, C.; Convery, M. R.; Dorfan, J.; Dubois-Felsmann, G. P.; Dunwoodie, W.; Field, R. C.; Franco Sevilla, M.; Fulsom, B. G.; Gabareen, A. M.; Graham, M. T.; Grenier, P.; Hast, C.; Innes, W. R.; Kelsey, M. H.; Kim, H.; Kim, P.; Kocian, M. L.; Leith, D. W. G. S.; Lewis, P.; Li, S.; Lindquist, B.; Luitz, S.; Luth, V.; Lynch, H. L.; MacFarlane, D. B.; Muller, D. R.; Neal, H.; Nelson, S.; Ofte, I.; Perl, M.; Pulliam, T.; Ratcliff, B. N.; Roodman, A.; Salnikov, A. A.; Santoro, V.; Schindler, R. H.; Snyder, A.; Su, D.; Sullivan, M. K.; Va'vra, J.; Wagner, A. P.; Weaver, M.; Wisniewski, W. J.; Wittgen, M.; Wright, D. H.; Wulsin, H. W.; Yarritu, A. K.; Young, C. C.; Ziegler, V.; Park, W.; Purohit, M. V.; White, R. M.; Wilson, J. R.; Randle-Conde, A.; Sekula, S. J.; Bellis, M.; Burchat, P. R.; Miyashita, T. S.; Alam, M. S.; Ernst, J. A.; Gorodeisky, R.; Guttman, N.; Peimer, D. R.; Soffer, A.; Lund, P.; Spanier, S. M.; Eckmann, R.; Ritchie, J. L.; Ruland, A. M.; Schilling, C. J.; Schwitters, R. F.; Wray, B. C.; Izen, J. M.; Lou, X. C.; Bianchi, F.; Gamba, D.; Lanceri, L.; Vitale, L.; Lopez-March, N.; Martinez-Vidal, F.; Oyanguren, A.; Ahmed, H.; Albert, J.; Banerjee, Sw.; Choi, H. H. F.; King, G. J.; Kowalewski, R.; Lewczuk, M. J.; Lindsay, C.; Nugent, I. M.; Roney, J. M.; Sobie, R. J.; Gershon, T. J.; Harrison, P. F.; Latham, T. E.; Puccio, E. M. T.; Band, H. R.; Dasu, S.; Pan, Y.; Prepost, R.; Vuosalo, C. O.; Wu, S. L.

2012-05-01

We search for the rare decay of the D0 meson to two photons, D0→γγ, and present a measurement of the branching fraction for a D0 meson decaying to two neutral pions, B(D0→π0π0). The data sample analyzed corresponds to an integrated luminosity of 470.5fb-1 collected by the BABAR detector at the PEP-II asymmetric-energy e+e- collider at SLAC. We place an upper limit on the branching fraction, B(D0→γγ)<2.2×10-6, at 90% confidence level. This limit improves on the existing limit by an order of magnitude. We also find B(D0→π0π0)=(8.4±0.1±0.4±0.3)×10-4.

Search for Production of Invisible Final States in Single-Photon Decays of Υ(1S)

NASA Astrophysics Data System (ADS)

Del Amo Sanchez, P.; Lees, J. P.; Poireau, V.; Prencipe, E.; Tisserand, V.; Garra Tico, J.; Grauges, E.; Martinelli, M.; Milanes, D. A.; Palano, A.; Pappagallo, M.; Eigen, G.; Stugu, B.; Sun, L.; Brown, D. N.; Chistiakova, M. V.; Jensen, F.; Kerth, L. T.; Kolomensky, Yu. G.; Lynch, G.; Osipenkov, I. L.; Koch, H.; Schroeder, T.; Asgeirsson, D. J.; Hearty, C.; Mattison, T. S.; McKenna, J. A.; Khan, A.; Randle-Conde, A.; Blinov, V. E.; Buzykaev, A. R.; Druzhinin, V. P.; Golubev, V. B.; Kravchenko, E. A.; Onuchin, A. P.; Serednyakov, S. I.; Skovpen, Yu. I.; Solodov, E. P.; Todyshev, K. Yu.; Yushkov, A. N.; Bondioli, M.; Curry, S.; Kirkby, D.; Lankford, A. J.; Mandelkern, M.; Martin, E. C.; Stoker, D. P.; Atmacan, H.; Gary, J. W.; Liu, F.; Long, O.; Vitug, G. M.; Campagnari, C.; Hong, T. M.; Kovalskyi, D.; Richman, J. D.; West, C.; Eisner, A. M.; Heusch, C. A.; Kroseberg, J.; Lockman, W. S.; Martinez, A. J.; Schalk, T.; Schumm, B. A.; Seiden, A.; Winstrom, L. O.; Cheng, C. H.; Doll, D. A.; Echenard, B.; Hitlin, D. G.; Ongmongkolkul, P.; Porter, F. C.; Rakitin, A. Y.; Andreassen, R.; Dubrovin, M. S.; Mancinelli, G.; Meadows, B. T.; Sokoloff, M. D.; Bloom, P. C.; Ford, W. T.; Gaz, A.; Nagel, M.; Nauenberg, U.; Smith, J. G.; Wagner, S. R.; Ayad, R.; Toki, W. H.; Jasper, H.; Karbach, T. M.; Petzold, A.; Spaan, B.; Kobel, M. J.; Schubert, K. R.; Schwierz, R.; Bernard, D.; Verderi, M.; Clark, P. J.; Playfer, S.; Watson, J. E.; Andreotti, M.; Bettoni, D.; Bozzi, C.; Calabrese, R.; Cecchi, A.; Cibinetto, G.; Fioravanti, E.; Franchini, P.; Garzia, I.; Luppi, E.; Munerato, M.; Negrini, M.; Petrella, A.; Piemontese, L.; Baldini-Ferroli, R.; Calcaterra, A.; de Sangro, R.; Finocchiaro, G.; Nicolaci, M.; Pacetti, S.; Patteri, P.; Peruzzi, I. M.; Piccolo, M.; Rama, M.; Zallo, A.; Contri, R.; Guido, E.; Lo Vetere, M.; Monge, M. R.; Passaggio, S.; Patrignani, C.; Robutti, E.; Tosi, S.; Bhuyan, B.; Prasad, V.; Lee, C. L.; Morii, M.; Adametz, A.; Marks, J.; Uwer, U.; Bernlochner, F. U.; Ebert, M.; Lacker, H. M.; Lueck, T.; Volk, A.; Dauncey, P. D.; Tibbetts, M.; Behera, P. K.; Mallik, U.; Chen, C.; Cochran, J.; Crawley, H. B.; Dong, L.; Meyer, W. T.; Prell, S.; Rosenberg, E. I.; Rubin, A. E.; Gritsan, A. V.; Guo, Z. J.; Arnaud, N.; Davier, M.; Derkach, D.; Firmino da Costa, J.; Grosdidier, G.; Le Diberder, F.; Lutz, A. M.; Malaescu, B.; Perez, A.; Roudeau, P.; Schune, M. H.; Serrano, J.; Sordini, V.; Stocchi, A.; Wang, L.; Wormser, G.; Lange, D. J.; Wright, D. M.; Bingham, I.; Chavez, C. A.; Coleman, J. P.; Fry, J. R.; Gabathuler, E.; Gamet, R.; Hutchcroft, D. E.; Payne, D. J.; Touramanis, C.; Bevan, A. J.; di Lodovico, F.; Sacco, R.; Sigamani, M.; Cowan, G.; Paramesvaran, S.; Wren, A. C.; Brown, D. N.; Davis, C. L.; Denig, A. G.; Fritsch, M.; Gradl, W.; Hafner, A.; Alwyn, K. E.; Bailey, D.; Barlow, R. J.; Jackson, G.; Lafferty, G. D.; Anderson, J.; Cenci, R.; Jawahery, A.; Roberts, D. A.; Simi, G.; Tuggle, J. M.; Dallapiccola, C.; Salvati, E.; Cowan, R.; Dujmic, D.; Sciolla, G.; Zhao, M.; Lindemann, D.; Patel, P. M.; Robertson, S. H.; Schram, M.; Biassoni, P.; Lazzaro, A.; Lombardo, V.; Palombo, F.; Stracka, S.; Cremaldi, L.; Godang, R.; Kroeger, R.; Sonnek, P.; Summers, D. J.; Nguyen, X.; Simard, M.; Taras, P.; de Nardo, G.; Monorchio, D.; Onorato, G.; Sciacca, C.; Raven, G.; Snoek, H. L.; Jessop, C. P.; Knoepfel, K. J.; Losecco, J. M.; Wang, W. F.; Corwin, L. A.; Honscheid, K.; Kass, R.; Morris, J. P.; Blount, N. L.; Brau, J.; Frey, R.; Igonkina, O.; Kolb, J. A.; Rahmat, R.; Sinev, N. B.; Strom, D.; Strube, J.; Torrence, E.; Castelli, G.; Feltresi, E.; Gagliardi, N.; Margoni, M.; Morandin, M.; Posocco, M.; Rotondo, M.; Simonetto, F.; Stroili, R.; Ben-Haim, E.; Bonneaud, G. R.; Briand, H.; Calderini, G.; Chauveau, J.; Hamon, O.; Leruste, Ph.; Marchiori, G.; Ocariz, J.; Prendki, J.; Sitt, S.; Biasini, M.; Manoni, E.; Rossi, A.; Angelini, C.; Batignani, G.; Bettarini, S.; Carpinelli, M.; Casarosa, G.; Cervelli, A.; Forti, F.; Giorgi, M. A.; Lusiani, A.; Neri, N.; Paoloni, E.; Rizzo, G.; Walsh, J. J.; Lopes Pegna, D.; Lu, C.; Olsen, J.; Smith, A. J. S.; Telnov, A. V.; Anulli, F.; Baracchini, E.; Cavoto, G.; Faccini, R.; Ferrarotto, F.; Ferroni, F.; Gaspero, M.; Li Gioi, L.; Mazzoni, M. A.; Piredda, G.; Renga, F.; Hartmann, T.; Leddig, T.; Schröder, H.; Waldi, R.; Adye, T.; Franek, B.; Olaiya, E. O.; Wilson, F. F.; Emery, S.; Hamel de Monchenault, G.; Vasseur, G.; Yèche, Ch.; Zito, M.; Allen, M. T.; Aston, D.; Bard, D. J.; Bartoldus, R.; Benitez, J. F.; Cartaro, C.; Convery, M. R.; Dorfan, J.; Dubois-Felsmann, G. P.; Dunwoodie, W.; Field, R. C.; Franco Sevilla, M.; Fulsom, B. G.; Gabareen, A. M.; Graham, M. T.; Grenier, P.; Hast, C.; Innes, W. R.; Kelsey, M. H.; Kim, H.; Kim, P.; Kocian, M. L.; Leith, D. W. G. S.; Li, S.; Lindquist, B.; Luitz, S.; Luth, V.; Lynch, H. L.; Macfarlane, D. B.; Marsiske, H.; Muller, D. R.; Neal, H.; Nelson, S.; O'Grady, C. P.; Ofte, I.; Perl, M.; Pulliam, T.; Ratcliff, B. N.; Roodman, A.; Salnikov, A. A.; Santoro, V.; Schindler, R. H.; Schwiening, J.; Snyder, A.; Su, D.; Sullivan, M. K.; Sun, S.; Suzuki, K.; Thompson, J. M.; Va'Vra, J.; Wagner, A. P.; Weaver, M.; Wisniewski, W. J.; Wittgen, M.; Wright, D. H.; Wulsin, H. W.; Yarritu, A. K.; Young, C. C.; Ziegler, V.; Chen, X. R.; Park, W.; Purohit, M. V.; White, R. M.; Wilson, J. R.; Sekula, S. J.; Bellis, M.; Burchat, P. R.; Edwards, A. J.; Miyashita, T. S.; Ahmed, S.; Alam, M. S.; Ernst, J. A.; Pan, B.; Saeed, M. A.; Zain, S. B.; Guttman, N.; Soffer, A.; Lund, P.; Spanier, S. M.; Eckmann, R.; Ritchie, J. L.; Ruland, A. M.; Schilling, C. J.; Schwitters, R. F.; Wray, B. C.; Izen, J. M.; Lou, X. C.; Bianchi, F.; Gamba, D.; Pelliccioni, M.; Bomben, M.; Lanceri, L.; Vitale, L.; Lopez-March, N.; Martinez-Vidal, F.; Oyanguren, A.; Albert, J.; Banerjee, Sw.; Choi, H. H. F.; Hamano, K.; King, G. J.; Kowalewski, R.; Lewczuk, M. J.; Lindsay, C.; Nugent, I. M.; Roney, J. M.; Sobie, R. J.; Gershon, T. J.; Harrison, P. F.; Latham, T. E.; Puccio, E. M. T.; Band, H. R.; Dasu, S.; Flood, K. T.; Pan, Y.; Prepost, R.; Vuosalo, C. O.; Wu, S. L.

2011-07-01

We search for single-photon decays of the Υ(1S) resonance, Υ→γ+invisible, where the invisible state is either a particle of definite mass, such as a light Higgs boson A0, or a pair of dark matter particles, χχ¯. Both A0 and χ are assumed to have zero spin. We tag Υ(1S) decays with a dipion transition Υ(2S)→π+π-Υ(1S) and look for events with a single energetic photon and significant missing energy. We find no evidence for such processes in the mass range mA0≤9.2GeV and mχ≤4.5GeV in the sample of 98×106 Υ(2S) decays collected with the BABAR detector and set stringent limits on new physics models that contain light dark matter states.

Measurement of the mass and width of the Ds1(2536)+ meson

NASA Astrophysics Data System (ADS)

Lees, J. P.; Poireau, V.; Prencipe, E.; Tisserand, V.; Garra Tico, J.; Grauges, E.; Martinelli, M.; Milanes, D. A.; Palano, A.; Pappagallo, M.; Eigen, G.; Stugu, B.; Sun, L.; Brown, D. N.; Kerth, L. T.; Kolomensky, Yu. G.; Lynch, G.; Osipenkov, I. L.; Koch, H.; Schroeder, T.; Asgeirsson, D. J.; Hearty, C.; Mattison, T. S.; McKenna, J. A.; Khan, A.; Blinov, V. E.; Buzykaev, A. R.; Druzhinin, V. P.; Golubev, V. B.; Kravchenko, E. A.; Onuchin, A. P.; Serednyakov, S. I.; Skovpen, Yu. I.; Solodov, E. P.; Todyshev, K. Yu.; Yushkov, A. N.; Bondioli, M.; Curry, S.; Kirkby, D.; Lankford, A. J.; Mandelkern, M.; Stoker, D. P.; Atmacan, H.; Gary, J. W.; Liu, F.; Long, O.; Vitug, G. M.; Campagnari, C.; Hong, T. M.; Kovalskyi, D.; Richman, J. D.; West, C. A.; Eisner, A. M.; Kroseberg, J.; Lockman, W. S.; Martinez, A. J.; Schalk, T.; Schumm, B. A.; Seiden, A.; Cheng, C. H.; Doll, D. A.; Echenard, B.; Flood, K. T.; Hitlin, D. G.; Ongmongkolkul, P.; Porter, F. C.; Rakitin, A. Y.; Andreassen, R.; Dubrovin, M. S.; Meadows, B. T.; Sokoloff, M. D.; Bloom, P. C.; Ford, W. T.; Gaz, A.; Nagel, M.; Nauenberg, U.; Smith, J. G.; Wagner, S. R.; Ayad, R.; Toki, W. H.; Jasper, H.; Petzold, A.; Spaan, B.; Kobel, M. J.; Schubert, K. R.; Schwierz, R.; Bernard, D.; Verderi, M.; Clark, P. J.; Playfer, S.; Watson, J. E.; Bettoni, D.; Bozzi, C.; Calabrese, R.; Cibinetto, G.; Fioravanti, E.; Garzia, I.; Luppi, E.; Munerato, M.; Negrini, M.; Piemontese, L.; Baldini-Ferroli, R.; Calcaterra, A.; de Sangro, R.; Finocchiaro, G.; Nicolaci, M.; Pacetti, S.; Patteri, P.; Peruzzi, I. M.; Piccolo, M.; Rama, M.; Zallo, A.; Contri, R.; Guido, E.; Lo Vetere, M.; Monge, M. R.; Passaggio, S.; Patrignani, C.; Robutti, E.; Bhuyan, B.; Prasad, V.; Lee, C. L.; Morii, M.; Edwards, A. J.; Adametz, A.; Marks, J.; Uwer, U.; Bernlochner, F. U.; Ebert, M.; Lacker, H. M.; Lueck, T.; Dauncey, P. D.; Tibbetts, M.; Behera, P. K.; Mallik, U.; Chen, C.; Cochran, J.; Crawley, H. B.; Meyer, W. T.; Prell, S.; Rosenberg, E. I.; Rubin, A. E.; Gritsan, A. V.; Guo, Z. J.; Arnaud, N.; Davier, M.; Derkach, D.; Firmino da Costa, J.; Grosdidier, G.; Le Diberder, F.; Lutz, A. M.; Malaescu, B.; Perez, A.; Roudeau, P.; Schune, M. H.; Stocchi, A.; Wang, L.; Wormser, G.; Lange, D. J.; Wright, D. M.; Bingham, I.; Chavez, C. A.; Coleman, J. P.; Fry, J. R.; Gabathuler, E.; Hutchcroft, D. E.; Payne, D. J.; Touramanis, C.; Bevan, A. J.; di Lodovico, F.; Sacco, R.; Sigamani, M.; Cowan, G.; Paramesvaran, S.; Wren, A. C.; Brown, D. N.; Davis, C. L.; Denig, A. G.; Fritsch, M.; Gradl, W.; Hafner, A.; Alwyn, K. E.; Bailey, D.; Barlow, R. J.; Jackson, G.; Lafferty, G. D.; Cenci, R.; Hamilton, B.; Jawahery, A.; Roberts, D. A.; Simi, G.; Dallapiccola, C.; Salvati, E.; Cowan, R.; Dujmic, D.; Sciolla, G.; Lindemann, D.; Patel, P. M.; Robertson, S. H.; Schram, M.; Biassoni, P.; Lazzaro, A.; Lombardo, V.; Palombo, F.; Stracka, S.; Cremaldi, L.; Godang, R.; Kroeger, R.; Sonnek, P.; Summers, D. J.; Nguyen, X.; Taras, P.; de Nardo, G.; Monorchio, D.; Onorato, G.; Sciacca, C.; Raven, G.; Snoek, H. L.; Jessop, C. P.; Knoepfel, K. J.; Losecco, J. M.; Wang, W. F.; Corwin, L. A.; Honscheid, K.; Kass, R.; Blount, N. L.; Brau, J.; Frey, R.; Kolb, J. A.; Rahmat, R.; Sinev, N. B.; Strom, D.; Strube, J.; Torrence, E.; Castelli, G.; Feltresi, E.; Gagliardi, N.; Margoni, M.; Morandin, M.; Posocco, M.; Rotondo, M.; Simonetto, F.; Stroili, R.; Ben-Haim, E.; Bomben, M.; Bonneaud, G. R.; Briand, H.; Calderini, G.; Chauveau, J.; Hamon, O.; Leruste, Ph.; Marchiori, G.; Ocariz, J.; Sitt, S.; Biasini, M.; Manoni, E.; Rossi, A.; Angelini, C.; Batignani, G.; Bettarini, S.; Carpinelli, M.; Casarosa, G.; Cervelli, A.; Forti, F.; Giorgi, M. A.; Lusiani, A.; Neri, N.; Paoloni, E.; Rizzo, G.; Walsh, J. J.; Lopes Pegna, D.; Lu, C.; Olsen, J.; Smith, A. J. S.; Telnov, A. V.; Anulli, F.; Cavoto, G.; Faccini, R.; Ferrarotto, F.; Ferroni, F.; Gaspero, M.; Li Gioi, L.; Mazzoni, M. A.; Piredda, G.; Buenger, C.; Hartmann, T.; Leddig, T.; Schröder, H.; Waldi, R.; Adye, T.; Olaiya, E. O.; Wilson, F. F.; Emery, S.; Hamel de Monchenault, G.; Vasseur, G.; Yèche, Ch.; Allen, M. T.; Aston, D.; Bard, D. J.; Bartoldus, R.; Benitez, J. F.; Cartaro, C.; Convery, M. R.; Dorfan, J.; Dubois-Felsmann, G. P.; Dunwoodie, W.; Field, R. C.; Franco Sevilla, M.; Fulsom, B. G.; Gabareen, A. M.; Graham, M. T.; Grenier, P.; Hast, C.; Innes, W. R.; Kelsey, M. H.; Kim, H.; Kim, P.; Kocian, M. L.; Leith, D. W. G. S.; Lewis, P.; Li, S.; Lindquist, B.; Luitz, S.; Luth, V.; Lynch, H. L.; Macfarlane, D. B.; Muller, D. R.; Neal, H.; Nelson, S.; O'Grady, C. P.; Ofte, I.; Perl, M.; Pulliam, T.; Ratcliff, B. N.; Robertson, S. H.; Roodman, A.; Salnikov, A. A.; Santoro, V.; Schindler, R. H.; Schwiening, J.; Snyder, A.; Su, D.; Sullivan, M. K.; Sun, S.; Suzuki, K.; Thompson, J. M.; Va'Vra, J.; Wagner, A. P.; Weaver, M.; Wisniewski, W. J.; Wittgen, M.; Wright, D. H.; Wulsin, H. W.; Yarritu, A. K.; Young, C. C.; Ziegler, V.; Chen, X. R.; Park, W.; Purohit, M. V.; White, R. M.; Wilson, J. R.; Randle-Conde, A.; Sekula, S. J.; Bellis, M.; Burchat, P. R.; Miyashita, T. S.; Alam, M. S.; Ernst, J. A.; Guttman, N.; Soffer, A.; Lund, P.; Spanier, S. M.; Eckmann, R.; Ritchie, J. L.; Ruland, A. M.; Schilling, C. J.; Schwitters, R. F.; Wray, B. C.; Izen, J. M.; Lou, X. C.; Bianchi, F.; Gamba, D.; Pelliccioni, M.; Lanceri, L.; Vitale, L.; Lopez-March, N.; Martinez-Vidal, F.; Oyanguren, A.; Ahmed, H.; Albert, J.; Banerjee, Sw.; Choi, H. H. F.; Hamano, K.; King, G. J.; Kowalewski, R.; Lewczuk, M. J.; Lindsay, C.; Nugent, I. M.; Roney, J. M.; Sobie, R. J.; Gershon, T. J.; Harrison, P. F.; Latham, T. E.; Puccio, E. M. T.; Band, H. R.; Dasu, S.; Pan, Y.; Prepost, R.; Vuosalo, C. O.; Wu, S. L.

2011-04-01

The decay width and mass of the Ds1(2536)+ meson are measured via the decay channel Ds1+→D*+KS0 using 385fb-1 of data recorded with the BABAR detector in the vicinity of the Υ(4S) resonance at the PEP-II asymmetric-energy electron-positron collider. The result for the decay width is Γ(Ds1+)=0.92±0.03(stat.)±0.04(syst.)MeV. For the mass, a value of m(Ds1+)=2535.08±0.01(stat.)±0.15(syst.)MeV/c2 is obtained. The mass difference between the Ds1+ and the D*+ is measured to be m(Ds1+)-m(D*+)=524.83±0.01(stat.)±0.04(syst.)MeV/c2, representing a significant improvement compared to the current world average. The unnatural spin-parity assignment for the Ds1+ meson is confirmed.

Measurement of the e + e - → K s 0 K ± π ∓ π 0 and K s 0 K ± π ∓ η cross sections using initial-state radiation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lees, J. P.; Poireau, V.; Tisserand, V.

The processes e + e - → Kmore » $$0\\atop{S}$$ K ±π ∓π 0 and e + e - → K$$0\\atop{S}$$ K ±π ∓η are studied over a continuum of energies from threshold to 4 GeV with the initial-state photon radiation method. Using 454 fb -1 of data collected with the BABAR detector at the SLAC PEP-II storage ring, the first measurements of the cross sections for these processes are obtained. The intermediate resonance structures from K* 0(Kπ) 0, K *(892) ± (Kπ) ∓ , and K$$0\\atop{S}$$K ±ρ ∓ are studied. Lastly, the J / ψ is observed in all of these channels, and corresponding branching fractions are measured.« less

Measurement of the e + e - → K s 0 K ± π ∓ π 0 and K s 0 K ± π ∓ η cross sections using initial-state radiation

DOE PAGES

Lees, J. P.; Poireau, V.; Tisserand, V.; ...

2017-05-30

The processes e + e - → Kmore » $$0\\atop{S}$$ K ±π ∓π 0 and e + e - → K$$0\\atop{S}$$ K ±π ∓η are studied over a continuum of energies from threshold to 4 GeV with the initial-state photon radiation method. Using 454 fb -1 of data collected with the BABAR detector at the SLAC PEP-II storage ring, the first measurements of the cross sections for these processes are obtained. The intermediate resonance structures from K* 0(Kπ) 0, K *(892) ± (Kπ) ∓ , and K$$0\\atop{S}$$K ±ρ ∓ are studied. Lastly, the J / ψ is observed in all of these channels, and corresponding branching fractions are measured.« less

A Measurement of the Charged and Neutral B Meson Lifetimes Using Fully Reconstructed Decays

DOE Office of Scientific and Technical Information (OSTI.GOV)

Barrera, Barbara

Data collected with the BABAR detector at the PEP-II asymmetric B Factory at SLAC are used to study the lifetimes of the B{sup 0} and B{sup +} mesons. The data sample consists of 7.4 fb{sup -1} collected near the {Upsilon}(4S) resonance. B{sup 0} and B{sup +} mesons are fully reconstructed in several exclusive hadronic decay modes to charm and charmonium final states. The B lifetimes are determined from the flight length difference between the two B mesons which are pair-produced in the {Upsilon}(4S) decay. The preliminary measurements of the lifetimes are {tau}B{sup 0} = 1.506 {+-} 0.052 (stat) {+-} 0.029more » (syst) ps, {tau}B{sup +} = 1.602 {+-} 0.049 (stat) {+-} 0.035 (syst) ps, and of their ratio is {tau}B{sup +}/{tau}B{sup 0} = 1.065 {+-} 0.044 (stat) {+-} 0.021 (syst).« less

A Measurement of the Charged and Neutral B Meson Lifetimes Using Fully Reconstructed Decays

DOE Office of Scientific and Technical Information (OSTI.GOV)

Barrera, Barbara

Data collected with the BABAR detector at the PEP-II asymmetric B Factory at SLAC are used to study the lifetimes of the B{sup 0} and B{sup +} mesons. The data sample consists of 7.4 fb{sup {minus}1} collected near the Upsilon(4S) resonance. B{sup 0} and B{sup +} mesons are fully reconstructed in several exclusive hadronic decay modes to charm and charmonium final states. The B lifetimes are determined from the flight length difference between the two B mesons which are pair-produced in the Upsilon(4S) decay. The preliminary measurements of the lifetimes are tau{sub B0} = 1.506 {+-} 0.052 (stat) {+-} 0.029more » (syst) ps, tau{sub B+} = 1.602 {+-} 0.049 (stat) {+-} 0.035 (syst) ps, and of their ratio is tau{sub B+}/tau{sub B0} = 1.065 {+-} 0.044 (stat) {+-} 0.021 (syst).« less

Measurement of the time dependence of B0-B0(bar) oscillations using inclusive dilepton events

DOE Office of Scientific and Technical Information (OSTI.GOV)

Barrera, Barbara

A preliminary study of time dependence of B{sup 0}{bar B}{sup 0} oscillations using dilepton events is presented. The flavor of the B meson is determined by the charge sign of the lepton. To separate signal leptons from cascade and fake leptons we have used a method which combines several discriminating variables in a neural network. The time evolution of the oscillations is studied by reconstructing the time difference between the decays of the B mesons produced by the {Upsilon}(4S) decay. With an integrated luminosity of 7.7 fb{sup -1} collected on resonance by BABAR at the PEP-II asymmetric B Factory, wemore » measure the difference in mass of the neutral B eigenstates, {Delta}m{sub B{sup 0}}, to be (0.507 {+-} 0.015 {+-} 0.022) x 10{sup 12} {Dirac_h} s{sup -1}.« less

Software Management for the NOνAExperiment

NASA Astrophysics Data System (ADS)

Davies, G. S.; Davies, J. P.; C Group; Rebel, B.; Sachdev, K.; Zirnstein, J.

2015-12-01

The NOvAsoftware (NOνASoft) is written in C++, and built on the Fermilab Computing Division's art framework that uses ROOT analysis software. NOνASoftmakes use of more than 50 external software packages, is developed by more than 50 developers and is used by more than 100 physicists from over 30 universities and laboratories in 3 continents. The software builds are handled by Fermilab's custom version of Software Release Tools (SRT), a UNIX based software management system for large, collaborative projects that is used by several experiments at Fermilab. The system provides software version control with SVN configured in a client-server mode and is based on the code originally developed by the BaBar collaboration. In this paper, we present efforts towards distributing the NOvA software via the CernVM File System distributed file system. We will also describe our recent work to use a CMake build system and Jenkins, the open source continuous integration system, for NOνASoft.

Dimension Reduction of Multivariable Optical Emission Spectrometer Datasets for Industrial Plasma Processes

PubMed Central

Yang, Jie; McArdle, Conor; Daniels, Stephen

2014-01-01

A new data dimension-reduction method, called Internal Information Redundancy Reduction (IIRR), is proposed for application to Optical Emission Spectroscopy (OES) datasets obtained from industrial plasma processes. For example in a semiconductor manufacturing environment, real-time spectral emission data is potentially very useful for inferring information about critical process parameters such as wafer etch rates, however, the relationship between the spectral sensor data gathered over the duration of an etching process step and the target process output parameters is complex. OES sensor data has high dimensionality (fine wavelength resolution is required in spectral emission measurements in order to capture data on all chemical species involved in plasma reactions) and full spectrum samples are taken at frequent time points, so that dynamic process changes can be captured. To maximise the utility of the gathered dataset, it is essential that information redundancy is minimised, but with the important requirement that the resulting reduced dataset remains in a form that is amenable to direct interpretation of the physical process. To meet this requirement and to achieve a high reduction in dimension with little information loss, the IIRR method proposed in this paper operates directly in the original variable space, identifying peak wavelength emissions and the correlative relationships between them. A new statistic, Mean Determination Ratio (MDR), is proposed to quantify the information loss after dimension reduction and the effectiveness of IIRR is demonstrated using an actual semiconductor manufacturing dataset. As an example of the application of IIRR in process monitoring/control, we also show how etch rates can be accurately predicted from IIRR dimension-reduced spectral data. PMID:24451453

Spatially Explicit Models to Investigate Geographic Patterns in the Distribution of Forensic STRs: Application to the North-Eastern Mediterranean.

PubMed

Messina, Francesco; Finocchio, Andrea; Akar, Nejat; Loutradis, Aphrodite; Michalodimitrakis, Emmanuel I; Brdicka, Radim; Jodice, Carla; Novelletto, Andrea

2016-01-01

Human forensic STRs used for individual identification have been reported to have little power for inter-population analyses. Several methods have been developed which incorporate information on the spatial distribution of individuals to arrive at a description of the arrangement of diversity. We genotyped at 16 forensic STRs a large population sample obtained from many locations in Italy, Greece and Turkey, i.e. three countries crucial to the understanding of discontinuities at the European/Asian junction and the genetic legacy of ancient migrations, but seldom represented together in previous studies. Using spatial PCA on the full dataset, we detected patterns of population affinities in the area. Additionally, we devised objective criteria to reduce the overall complexity into reduced datasets. Independent spatially explicit methods applied to these latter datasets converged in showing that the extraction of information on long- to medium-range geographical trends and structuring from the overall diversity is possible. All analyses returned the picture of a background clinal variation, with regional discontinuities captured by each of the reduced datasets. Several aspects of our results are confirmed on external STR datasets and replicate those of genome-wide SNP typings. High levels of gene flow were inferred within the main continental areas by coalescent simulations. These results are promising from a microevolutionary perspective, in view of the fast pace at which forensic data are being accumulated for many locales. It is foreseeable that this will allow the exploitation of an invaluable genotypic resource, assembled for other (forensic) purposes, to clarify important aspects in the formation of local gene pools.

Evaluating a Priori Ozone Profile Information Used in TEMPO (Tropospheric Emissions: Monitoring of Pollution) Tropospheric Ozone Retrievals

NASA Technical Reports Server (NTRS)

Johnson, Matthew Stephen

2017-01-01

A primary objective for TOLNet is the evaluation and validation of space-based tropospheric O3 retrievals from future systems such as the Tropospheric Emissions: Monitoring of Pollution (TEMPO) satellite. This study is designed to evaluate the tropopause-based O3 climatology (TB-Clim) dataset which will be used as the a priori profile information in TEMPO O3 retrievals. This study also evaluates model simulated O3 profiles, which could potentially serve as a priori O3 profile information in TEMPO retrievals, from near-real-time (NRT) data assimilation model products (NASA Global Modeling and Assimilation Office (GMAO) Goddard Earth Observing System (GEOS-5) Forward Processing (FP) and Modern-Era Retrospective analysis for Research and Applications version 2 (MERRA2)) and full chemical transport model (CTM), GEOS-Chem, simulations. The TB-Clim dataset and model products are evaluated with surface (0-2 km) and tropospheric (0-10 km) TOLNet observations to demonstrate the accuracy of the suggested a priori dataset and information which could potentially be used in TEMPO O3 algorithms. This study also presents the impact of individual a priori profile sources on the accuracy of theoretical TEMPO O3 retrievals in the troposphere and at the surface. Preliminary results indicate that while the TB-Clim climatological dataset can replicate seasonally-averaged tropospheric O3 profiles observed by TOLNet, model-simulated profiles from a full CTM (GEOS-Chem is used as a proxy for CTM O3 predictions) resulted in more accurate tropospheric and surface-level O3 retrievals from TEMPO when compared to hourly (diurnal cycle evaluation) and daily-averaged (daily variability evaluation) TOLNet observations. Furthermore, it was determined that when large daily-averaged surface O3 mixing ratios are observed (65 ppb), which are important for air quality purposes, TEMPO retrieval values at the surface display higher correlations and less bias when applying CTM a priori profile information compared to all other data products. The primary reason for this is that CTM predictions better capture the spatio-temporal variability of the vertical profiles of observed tropospheric O3 compared to the TB-Clim dataset and other NRT data assimilation models evaluated during this study.

Large-scale seismic waveform quality metric calculation using Hadoop

DOE PAGES

Magana-Zook, Steven; Gaylord, Jessie M.; Knapp, Douglas R.; ...

2016-05-27

Here in this work we investigated the suitability of Hadoop MapReduce and Apache Spark for large-scale computation of seismic waveform quality metrics by comparing their performance with that of a traditional distributed implementation. The Incorporated Research Institutions for Seismology (IRIS) Data Management Center (DMC) provided 43 terabytes of broadband waveform data of which 5.1 TB of data were processed with the traditional architecture, and the full 43 TB were processed using MapReduce and Spark. Maximum performance of ~0.56 terabytes per hour was achieved using all 5 nodes of the traditional implementation. We noted that I/O dominated processing, and that I/Omore » performance was deteriorating with the addition of the 5th node. Data collected from this experiment provided the baseline against which the Hadoop results were compared. Next, we processed the full 43 TB dataset using both MapReduce and Apache Spark on our 18-node Hadoop cluster. We conducted these experiments multiple times with various subsets of the data so that we could build models to predict performance as a function of dataset size. We found that both MapReduce and Spark significantly outperformed the traditional reference implementation. At a dataset size of 5.1 terabytes, both Spark and MapReduce were about 15 times faster than the reference implementation. Furthermore, our performance models predict that for a dataset of 350 terabytes, Spark running on a 100-node cluster would be about 265 times faster than the reference implementation. We do not expect that the reference implementation deployed on a 100-node cluster would perform significantly better than on the 5-node cluster because the I/O performance cannot be made to scale. Finally, we note that although Big Data technologies clearly provide a way to process seismic waveform datasets in a high-performance and scalable manner, the technology is still rapidly changing, requires a high degree of investment in personnel, and will likely require significant changes in other parts of our infrastructure. Nevertheless, we anticipate that as the technology matures and third-party tool vendors make it easier to manage and operate clusters, Hadoop (or a successor) will play a large role in our seismic data processing.« less

Large-scale seismic waveform quality metric calculation using Hadoop

DOE Office of Scientific and Technical Information (OSTI.GOV)

Magana-Zook, Steven; Gaylord, Jessie M.; Knapp, Douglas R.

Here in this work we investigated the suitability of Hadoop MapReduce and Apache Spark for large-scale computation of seismic waveform quality metrics by comparing their performance with that of a traditional distributed implementation. The Incorporated Research Institutions for Seismology (IRIS) Data Management Center (DMC) provided 43 terabytes of broadband waveform data of which 5.1 TB of data were processed with the traditional architecture, and the full 43 TB were processed using MapReduce and Spark. Maximum performance of ~0.56 terabytes per hour was achieved using all 5 nodes of the traditional implementation. We noted that I/O dominated processing, and that I/Omore » performance was deteriorating with the addition of the 5th node. Data collected from this experiment provided the baseline against which the Hadoop results were compared. Next, we processed the full 43 TB dataset using both MapReduce and Apache Spark on our 18-node Hadoop cluster. We conducted these experiments multiple times with various subsets of the data so that we could build models to predict performance as a function of dataset size. We found that both MapReduce and Spark significantly outperformed the traditional reference implementation. At a dataset size of 5.1 terabytes, both Spark and MapReduce were about 15 times faster than the reference implementation. Furthermore, our performance models predict that for a dataset of 350 terabytes, Spark running on a 100-node cluster would be about 265 times faster than the reference implementation. We do not expect that the reference implementation deployed on a 100-node cluster would perform significantly better than on the 5-node cluster because the I/O performance cannot be made to scale. Finally, we note that although Big Data technologies clearly provide a way to process seismic waveform datasets in a high-performance and scalable manner, the technology is still rapidly changing, requires a high degree of investment in personnel, and will likely require significant changes in other parts of our infrastructure. Nevertheless, we anticipate that as the technology matures and third-party tool vendors make it easier to manage and operate clusters, Hadoop (or a successor) will play a large role in our seismic data processing.« less

Science Enabling Applications of Gridded Radiances and Products

NASA Astrophysics Data System (ADS)

Goldberg, M.; Wolf, W.; Zhou, L.

2005-12-01

New generations of hyperspectral sounders and imagers are not only providing vastly improved information to monitor, assess and predict the Earth's environment, they also provide tremendous volumes of data to manage. Key management challenges must include data processing, distribution, archive and utilization. At the NOAA/NESDIS Office of Research and Applications, we have started to address the challenge of utilizing high volume satellite by thinning observations and developing gridded datasets from the observations made from the NASA AIRS, AMSU and MODIS instrument. We have developed techniques for intelligent thinning of AIRS data for numerical weather prediction, by selecting the clearest AIRS 14 km field of view within a 3 x 3 array. The selection uses high spatial resolution 1 km MODIS data which are spatially convolved to the AIRS field of view. The MODIS cloud masks and AIRS cloud tests are used to select the clearest. During the real-time processing the data are thinned and gridded to support monitoring, validation and scientific studies. Products from AIRS, which includes profiles of temperature, water vapor and ozone and cloud-corrected infrared radiances for more than 2000 channels, are derived from a single AIRS/AMSU field of regard, which is a 3 x 3 array of AIRS footprints (each with a 14 km spatial resolution) collocated with a single AMSU footprint (42 km). One of our key gridded dataset is a daily 3 x 3 latitude/longitude projection which contains the nearest AIRS/AMSU field of regard with respect to the center of the 3 x 3 lat/lon grid. This particular gridded dataset is 1/40 the size of the full resolution data. This gridded dataset is the type of product request that can be used to support algorithm validation and improvements. It also provides for a very economical approach for reprocessing, testing and improving algorithms for climate studies without having to reprocess the full resolution data stored at the DAAC. For example, on a single CPU workstation, all the AIRS derived products can be derived from a single year of gridded data in 5 days. This relatively short turnaround time, which can be reduced considerably to 3 hours by using a cluster of 40 pc G5processors, allows for repeated reprocessing at the PIs home institution before substantial investments are made to reprocess the full resolution data sets archived at the DAAC. In other words, do not reprocess the full resolution data until the science community have tested and selected the optimal algorithm on the gridded data. Development and applications of gridded radiances and products will be discussed. The applications can be provided as part of a web-based service.

Anisotropy effects on 3D waveform inversion

NASA Astrophysics Data System (ADS)

Stekl, I.; Warner, M.; Umpleby, A.

2010-12-01

In the recent years 3D waveform inversion has become achievable procedure for seismic data processing. A number of datasets has been inverted and presented (Warner el al 2008, Ben Hadj at all, Sirgue et all 2010) using isotropic 3D waveform inversion. However the question arises will the results be affected by isotropic assumption. Full-wavefield inversion techniques seek to match field data, wiggle-for-wiggle, to synthetic data generated by a high-resolution model of the sub-surface. In this endeavour, correctly matching the travel times of the principal arrivals is a necessary minimal requirement. In many, perhaps most, long-offset and wide-azimuth datasets, it is necessary to introduce some form of p-wave velocity anisotropy to match the travel times successfully. If this anisotropy is not also incorporated into the wavefield inversion, then results from the inversion will necessarily be compromised. We have incorporated anisotropy into our 3D wavefield tomography codes, characterised as spatially varying transverse isotropy with a tilted axis of symmetry - TTI anisotropy. This enhancement approximately doubles both the run time and the memory requirements of the code. We show that neglect of anisotropy can lead to significant artefacts in the recovered velocity models. We will present inversion results of inverting anisotropic 3D dataset by assuming isotropic earth and compare them with anisotropic inversion result. As a test case Marmousi model extended to 3D with no velocity variation in third direction and with added spatially varying anisotropy is used. Acquisition geometry is assumed as OBC with sources and receivers everywhere at the surface. We attempted inversion using both 2D and full 3D acquisition for this dataset. Results show that if no anisotropy is taken into account although image looks plausible most features are miss positioned in depth and space, even for relatively low anisotropy, which leads to incorrect result. This may lead to misinterpretation of results. However if correct physics is used results agree with correct model. Our algorithm is relatively affordable and runs on standard pc clusters in acceptable time. Refferences: H. Ben Hadj Ali, S. Operto and J. Virieux. Velocity model building by 3D frequency-domain full-waveform inversion of wide-aperture seismic data, Geophysics (Special issue: Velocity Model Building), 73(6), P. VE101-VE117 (2008). L. Sirgue, O.I. Barkved, J. Dellinger, J. Etgen, U. Albertin, J.H. Kommedal, Full waveform inversion: the next leap forward in imaging at Valhall, First Brake April 2010 - Issue 4 - Volume 28 M. Warner, I. Stekl, A. Umpleby, Efficient and Effective 3D Wavefield Tomography, 70th EAGE Conference & Exhibition (2008)

Mining peripheral arterial disease cases from narrative clinical notes using natural language processing.

PubMed

Afzal, Naveed; Sohn, Sunghwan; Abram, Sara; Scott, Christopher G; Chaudhry, Rajeev; Liu, Hongfang; Kullo, Iftikhar J; Arruda-Olson, Adelaide M

2017-06-01

Lower extremity peripheral arterial disease (PAD) is highly prevalent and affects millions of individuals worldwide. We developed a natural language processing (NLP) system for automated ascertainment of PAD cases from clinical narrative notes and compared the performance of the NLP algorithm with billing code algorithms, using ankle-brachial index test results as the gold standard. We compared the performance of the NLP algorithm to (1) results of gold standard ankle-brachial index; (2) previously validated algorithms based on relevant International Classification of Diseases, Ninth Revision diagnostic codes (simple model); and (3) a combination of International Classification of Diseases, Ninth Revision codes with procedural codes (full model). A dataset of 1569 patients with PAD and controls was randomly divided into training (n = 935) and testing (n = 634) subsets. We iteratively refined the NLP algorithm in the training set including narrative note sections, note types, and service types, to maximize its accuracy. In the testing dataset, when compared with both simple and full models, the NLP algorithm had better accuracy (NLP, 91.8%; full model, 81.8%; simple model, 83%; P < .001), positive predictive value (NLP, 92.9%; full model, 74.3%; simple model, 79.9%; P < .001), and specificity (NLP, 92.5%; full model, 64.2%; simple model, 75.9%; P < .001). A knowledge-driven NLP algorithm for automatic ascertainment of PAD cases from clinical notes had greater accuracy than billing code algorithms. Our findings highlight the potential of NLP tools for rapid and efficient ascertainment of PAD cases from electronic health records to facilitate clinical investigation and eventually improve care by clinical decision support. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

Visualization of conserved structures by fusing highly variable datasets.

PubMed

Silverstein, Jonathan C; Chhadia, Ankur; Dech, Fred

2002-01-01

Skill, effort, and time are required to identify and visualize anatomic structures in three-dimensions from radiological data. Fundamentally, automating these processes requires a technique that uses symbolic information not in the dynamic range of the voxel data. We were developing such a technique based on mutual information for automatic multi-modality image fusion (MIAMI Fuse, University of Michigan). This system previously demonstrated facility at fusing one voxel dataset with integrated symbolic structure information to a CT dataset (different scale and resolution) from the same person. The next step of development of our technique was aimed at accommodating the variability of anatomy from patient to patient by using warping to fuse our standard dataset to arbitrary patient CT datasets. A standard symbolic information dataset was created from the full color Visible Human Female by segmenting the liver parenchyma, portal veins, and hepatic veins and overwriting each set of voxels with a fixed color. Two arbitrarily selected patient CT scans of the abdomen were used for reference datasets. We used the warping functions in MIAMI Fuse to align the standard structure data to each patient scan. The key to successful fusion was the focused use of multiple warping control points that place themselves around the structure of interest automatically. The user assigns only a few initial control points to align the scans. Fusion 1 and 2 transformed the atlas with 27 points around the liver to CT1 and CT2 respectively. Fusion 3 transformed the atlas with 45 control points around the liver to CT1 and Fusion 4 transformed the atlas with 5 control points around the portal vein. The CT dataset is augmented with the transformed standard structure dataset, such that the warped structure masks are visualized in combination with the original patient dataset. This combined volume visualization is then rendered interactively in stereo on the ImmersaDesk in an immersive Virtual Reality (VR) environment. The accuracy of the fusions was determined qualitatively by comparing the transformed atlas overlaid on the appropriate CT. It was examined for where the transformed structure atlas was incorrectly overlaid (false positive) and where it was incorrectly not overlaid (false negative). According to this method, fusions 1 and 2 were correct roughly 50-75% of the time, while fusions 3 and 4 were correct roughly 75-100%. The CT dataset augmented with transformed dataset was viewed arbitrarily in user-centered perspective stereo taking advantage of features such as scaling, windowing and volumetric region of interest selection. This process of auto-coloring conserved structures in variable datasets is a step toward the goal of a broader, standardized automatic structure visualization method for radiological data. If successful it would permit identification, visualization or deletion of structures in radiological data by semi-automatically applying canonical structure information to the radiological data (not just processing and visualization of the data's intrinsic dynamic range). More sophisticated selection of control points and patterns of warping may allow for more accurate transforms, and thus advances in visualization, simulation, education, diagnostics, and treatment planning.

Sampling errors for a nadir viewing instrument on the International Space Station

NASA Astrophysics Data System (ADS)

Berger, H. I.; Pincus, R.; Evans, F.; Santek, D.; Ackerman, S.; Ackerman, S.

2001-12-01

In an effort to improve the observational charactarization of ice clouds in the earth's atmosphere, we are developing a sub-millimeter wavelength radiometer which we propose to fly on the International Space Station for two years. Our goal is to accurately measure the ice water path and mass-weighted particle size at the finest possible temporal and spatial resolution. The ISS orbit precesses, sampling through the dirunal cycle every 16 days, but technological constraints limit our instrument to a single pixel viewed near nadir. We discuss sampling errors associated with this instrument/platform configuration. We use as "truth" the ISCCP dataset of pixel-level cloud optical retrievals, which acts as a proxy for ice water path; this dataset is sampled according to the orbital characteristics of the space station, and the statistics computed from the sub-sampled population are compared with those from the full dataset. We explore the tradeoffs in average sampling error as a function of the averaging time and spatial scale, and explore the possibility of resolving the dirunal cycle.

A dataset of stereoscopic images and ground-truth disparity mimicking human fixations in peripersonal space

PubMed Central

Canessa, Andrea; Gibaldi, Agostino; Chessa, Manuela; Fato, Marco; Solari, Fabio; Sabatini, Silvio P.

2017-01-01

Binocular stereopsis is the ability of a visual system, belonging to a live being or a machine, to interpret the different visual information deriving from two eyes/cameras for depth perception. From this perspective, the ground-truth information about three-dimensional visual space, which is hardly available, is an ideal tool both for evaluating human performance and for benchmarking machine vision algorithms. In the present work, we implemented a rendering methodology in which the camera pose mimics realistic eye pose for a fixating observer, thus including convergent eye geometry and cyclotorsion. The virtual environment we developed relies on highly accurate 3D virtual models, and its full controllability allows us to obtain the stereoscopic pairs together with the ground-truth depth and camera pose information. We thus created a stereoscopic dataset: GENUA PESTO—GENoa hUman Active fixation database: PEripersonal space STereoscopic images and grOund truth disparity. The dataset aims to provide a unified framework useful for a number of problems relevant to human and computer vision, from scene exploration and eye movement studies to 3D scene reconstruction. PMID:28350382

Sub-sampling genetic data to estimate black bear population size: A case study

USGS Publications Warehouse

Tredick, C.A.; Vaughan, M.R.; Stauffer, D.F.; Simek, S.L.; Eason, T.

2007-01-01

Costs for genetic analysis of hair samples collected for individual identification of bears average approximately US$50 [2004] per sample. This can easily exceed budgetary allowances for large-scale studies or studies of high-density bear populations. We used 2 genetic datasets from 2 areas in the southeastern United States to explore how reducing costs of analysis by sub-sampling affected precision and accuracy of resulting population estimates. We used several sub-sampling scenarios to create subsets of the full datasets and compared summary statistics, population estimates, and precision of estimates generated from these subsets to estimates generated from the complete datasets. Our results suggested that bias and precision of estimates improved as the proportion of total samples used increased, and heterogeneity models (e.g., Mh[CHAO]) were more robust to reduced sample sizes than other models (e.g., behavior models). We recommend that only high-quality samples (>5 hair follicles) be used when budgets are constrained, and efforts should be made to maximize capture and recapture rates in the field.

PHOXTRACK-a tool for interpreting comprehensive datasets of post-translational modifications of proteins.

PubMed

Weidner, Christopher; Fischer, Cornelius; Sauer, Sascha

2014-12-01

We introduce PHOXTRACK (PHOsphosite-X-TRacing Analysis of Causal Kinases), a user-friendly freely available software tool for analyzing large datasets of post-translational modifications of proteins, such as phosphorylation, which are commonly gained by mass spectrometry detection. In contrast to other currently applied data analysis approaches, PHOXTRACK uses full sets of quantitative proteomics data and applies non-parametric statistics to calculate whether defined kinase-specific sets of phosphosite sequences indicate statistically significant concordant differences between various biological conditions. PHOXTRACK is an efficient tool for extracting post-translational information of comprehensive proteomics datasets to decipher key regulatory proteins and to infer biologically relevant molecular pathways. PHOXTRACK will be maintained over the next years and is freely available as an online tool for non-commercial use at http://phoxtrack.molgen.mpg.de. Users will also find a tutorial at this Web site and can additionally give feedback at https://groups.google.com/d/forum/phoxtrack-discuss. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Intellicount: High-Throughput Quantification of Fluorescent Synaptic Protein Puncta by Machine Learning

PubMed Central

Fantuzzo, J. A.; Mirabella, V. R.; Zahn, J. D.

2017-01-01

Abstract Synapse formation analyses can be performed by imaging and quantifying fluorescent signals of synaptic markers. Traditionally, these analyses are done using simple or multiple thresholding and segmentation approaches or by labor-intensive manual analysis by a human observer. Here, we describe Intellicount, a high-throughput, fully-automated synapse quantification program which applies a novel machine learning (ML)-based image processing algorithm to systematically improve region of interest (ROI) identification over simple thresholding techniques. Through processing large datasets from both human and mouse neurons, we demonstrate that this approach allows image processing to proceed independently of carefully set thresholds, thus reducing the need for human intervention. As a result, this method can efficiently and accurately process large image datasets with minimal interaction by the experimenter, making it less prone to bias and less liable to human error. Furthermore, Intellicount is integrated into an intuitive graphical user interface (GUI) that provides a set of valuable features, including automated and multifunctional figure generation, routine statistical analyses, and the ability to run full datasets through nested folders, greatly expediting the data analysis process. PMID:29218324

New Data Pre-processing on Assessing of Obstructive Sleep Apnea Syndrome: Line Based Normalization Method (LBNM)

NASA Astrophysics Data System (ADS)

Akdemir, Bayram; Güneş, Salih; Yosunkaya, Şebnem

Sleep disorders are a very common unawareness illness among public. Obstructive Sleep Apnea Syndrome (OSAS) is characterized with decreased oxygen saturation level and repetitive upper respiratory tract obstruction episodes during full night sleep. In the present study, we have proposed a novel data normalization method called Line Based Normalization Method (LBNM) to evaluate OSAS using real data set obtained from Polysomnography device as a diagnostic tool in patients and clinically suspected of suffering OSAS. Here, we have combined the LBNM and classification methods comprising C4.5 decision tree classifier and Artificial Neural Network (ANN) to diagnose the OSAS. Firstly, each clinical feature in OSAS dataset is scaled by LBNM method in the range of [0,1]. Secondly, normalized OSAS dataset is classified using different classifier algorithms including C4.5 decision tree classifier and ANN, respectively. The proposed normalization method was compared with min-max normalization, z-score normalization, and decimal scaling methods existing in literature on the diagnosis of OSAS. LBNM has produced very promising results on the assessing of OSAS. Also, this method could be applied to other biomedical datasets.

Exploratory visualization software for reporting environmental survey results.

PubMed

Fisher, P; Arnot, C; Bastin, L; Dykes, J

2001-08-01

Environmental surveys yield three principal products: maps, a set of data tables, and a textual report. The relationships between these three elements, however, are often cumbersome to present, making full use of all the information in an integrated and systematic sense difficult. The published paper report is only a partial solution. Modern developments in computing, particularly in cartography, GIS, and hypertext, mean that it is increasingly possible to conceive of an easier and more interactive approach to the presentation of such survey results. Here, we present such an approach which links map and tabular datasets arising from a vegetation survey, allowing users ready access to a complex dataset using dynamic mapping techniques. Multimedia datasets equipped with software like this provide an exciting means of quick and easy visual data exploration and comparison. These techniques are gaining popularity across the sciences as scientists and decision-makers are presented with increasing amounts of diverse digital data. We believe that the software environment actively encourages users to make complex interrogations of the survey information, providing a new vehicle for the reader of an environmental survey report.

Data in support of energy performance of double-glazed windows.

PubMed

Shakouri, Mahmoud; Banihashemi, Saeed

2016-06-01

This paper provides the data used in a research project to propose a new simplified windows rating system based on saved annual energy ("Developing an empirical predictive energy-rating model for windows by using Artificial Neural Network" (Shakouri Hassanabadi and Banihashemi Namini, 2012) [1], "Climatic, parametric and non-parametric analysis of energy performance of double-glazed windows in different climates" (Banihashemi et al., 2015) [2]). A full factorial simulation study was conducted to evaluate the performance of 26 different types of windows in a four-story residential building. In order to generalize the results, the selected windows were tested in four climates of cold, tropical, temperate, and hot and arid; and four different main orientations of North, West, South and East. The accompanied datasets include the annual saved cooling and heating energy in different climates and orientations by using the selected windows. Moreover, a complete dataset is provided that includes the specifications of 26 windows, climate data, month, and orientation of the window. This dataset can be used to make predictive models for energy efficiency assessment of double glazed windows.

Optimizing data collection for public health decisions: a data mining approach

PubMed Central

2014-01-01

Background Collecting data can be cumbersome and expensive. Lack of relevant, accurate and timely data for research to inform policy may negatively impact public health. The aim of this study was to test if the careful removal of items from two community nutrition surveys guided by a data mining technique called feature selection, can (a) identify a reduced dataset, while (b) not damaging the signal inside that data. Methods The Nutrition Environment Measures Surveys for stores (NEMS-S) and restaurants (NEMS-R) were completed on 885 retail food outlets in two counties in West Virginia between May and November of 2011. A reduced dataset was identified for each outlet type using feature selection. Coefficients from linear regression modeling were used to weight items in the reduced datasets. Weighted item values were summed with the error term to compute reduced item survey scores. Scores produced by the full survey were compared to the reduced item scores using a Wilcoxon rank-sum test. Results Feature selection identified 9 store and 16 restaurant survey items as significant predictors of the score produced from the full survey. The linear regression models built from the reduced feature sets had R2 values of 92% and 94% for restaurant and grocery store data, respectively. Conclusions While there are many potentially important variables in any domain, the most useful set may only be a small subset. The use of feature selection in the initial phase of data collection to identify the most influential variables may be a useful tool to greatly reduce the amount of data needed thereby reducing cost. PMID:24919484

pySAPC, a python package for sparse affinity propagation clustering: Application to odontogenesis whole genome time series gene-expression data.

PubMed

Cao, Huojun; Amendt, Brad A

2016-11-01

Developmental dental anomalies are common forms of congenital defects. The molecular mechanisms of dental anomalies are poorly understood. Systematic approaches such as clustering genes based on similar expression patterns could identify novel genes involved in dental anomalies and provide a framework for understanding molecular regulatory mechanisms of these genes during tooth development (odontogenesis). A python package (pySAPC) of sparse affinity propagation clustering algorithm for large datasets was developed. Whole genome pair-wise similarity was calculated based on expression pattern similarity based on 45 microarrays of several stages during odontogenesis. pySAPC identified 743 gene clusters based on expression pattern similarity during mouse tooth development. Three clusters are significantly enriched for genes associated with dental anomalies (with FDR <0.1). The three clusters of genes have distinct expression patterns during odontogenesis. Clustering genes based on similar expression profiles recovered several known regulatory relationships for genes involved in odontogenesis, as well as many novel genes that may be involved with the same genetic pathways as genes that have already been shown to contribute to dental defects. By using sparse similarity matrix, pySAPC use much less memory and CPU time compared with the original affinity propagation program that uses a full similarity matrix. This python package will be useful for many applications where dataset(s) are too large to use full similarity matrix. This article is part of a Special Issue entitled "System Genetics" Guest Editor: Dr. Yudong Cai and Dr. Tao Huang. Copyright © 2016. Published by Elsevier B.V.

A new method to generate a high-resolution global distribution map of lake chlorophyll

USGS Publications Warehouse

Sayers, Michael J; Grimm, Amanda G.; Shuchman, Robert A.; Deines, Andrew M.; Bunnell, David B.; Raymer, Zachary B; Rogers, Mark W.; Woelmer, Whitney; Bennion, David; Brooks, Colin N.; Whitley, Matthew A.; Warner, David M.; Mychek-Londer, Justin G.

2015-01-01

A new method was developed, evaluated, and applied to generate a global dataset of growing-season chlorophyll-a (chl) concentrations in 2011 for freshwater lakes. Chl observations from freshwater lakes are valuable for estimating lake productivity as well as assessing the role that these lakes play in carbon budgets. The standard 4 km NASA OceanColor L3 chlorophyll concentration products generated from MODIS and MERIS sensor data are not sufficiently representative of global chl values because these can only resolve larger lakes, which generally have lower chl concentrations than lakes of smaller surface area. Our new methodology utilizes the 300 m-resolution MERIS full-resolution full-swath (FRS) global dataset as input and does not rely on the land mask used to generate standard NASA products, which masks many lakes that are otherwise resolvable in MERIS imagery. The new method produced chl concentration values for 78,938 and 1,074 lakes in the northern and southern hemispheres, respectively. The mean chl for lakes visible in the MERIS composite was 19.2 ± 19.2, the median was 13.3, and the interquartile range was 3.90–28.6 mg m−3. The accuracy of the MERIS-derived values was assessed by comparison with temporally near-coincident and globally distributed in situmeasurements from the literature (n = 185, RMSE = 9.39, R2 = 0.72). This represents the first global-scale dataset of satellite-derived chl estimates for medium to large lakes.

Optimizing data collection for public health decisions: a data mining approach.

PubMed

Partington, Susan N; Papakroni, Vasil; Menzies, Tim

2014-06-12

Collecting data can be cumbersome and expensive. Lack of relevant, accurate and timely data for research to inform policy may negatively impact public health. The aim of this study was to test if the careful removal of items from two community nutrition surveys guided by a data mining technique called feature selection, can (a) identify a reduced dataset, while (b) not damaging the signal inside that data. The Nutrition Environment Measures Surveys for stores (NEMS-S) and restaurants (NEMS-R) were completed on 885 retail food outlets in two counties in West Virginia between May and November of 2011. A reduced dataset was identified for each outlet type using feature selection. Coefficients from linear regression modeling were used to weight items in the reduced datasets. Weighted item values were summed with the error term to compute reduced item survey scores. Scores produced by the full survey were compared to the reduced item scores using a Wilcoxon rank-sum test. Feature selection identified 9 store and 16 restaurant survey items as significant predictors of the score produced from the full survey. The linear regression models built from the reduced feature sets had R2 values of 92% and 94% for restaurant and grocery store data, respectively. While there are many potentially important variables in any domain, the most useful set may only be a small subset. The use of feature selection in the initial phase of data collection to identify the most influential variables may be a useful tool to greatly reduce the amount of data needed thereby reducing cost.

The Trade-Off between Child Labour and Schooling in India

ERIC Educational Resources Information Center

Rammohan, Anu

2014-01-01

In this paper, using the "2005-2006 National Family Health Survey" dataset from India, we study the likelihood of a school-age child working, combining work with schooling or being idle, rather than attending school full time. Our analysis finds that with the inclusion of household chores in the child labour definition, boys are…

GHPsRUS Project

DOE Data Explorer

Battocletti, Liz

2013-07-09

The GHPsRUS Project's full name is "Measuring the Costs and Benefits of Nationwide Geothermal Heat Pump Deployment." The dataset contains employment and installation price data collected by four economic surveys: (1)GHPsRUS Project Manufacturer & OEM Survey, (2) GHPsRUS Project Geothermal Loop Survey, (3) GHPsRUS Project Mechanical Equipment Installation Survey, and (4) GHPsRUS Geothermal Heat Pump Industry Survey

Management and land use implications of continuous nitrogen and phosphorus monitoring in a small non-karst catchment in southeastern PA

USDA-ARS?s Scientific Manuscript database

Long-term climate and water quality monitoring data provide some of the most essential and informative information to the scientific community. These datasets however, are often incomplete and do not have frequent enough sampling to provide full explanations of trends. With the advent of continuous ...

Parachute Dynamics Investigations Using a Sensor Package Airdropped from a Small-Scale Airplane

NASA Technical Reports Server (NTRS)

Dooley, Jessica; Lorenz, Ralph D.

2005-01-01

We explore the utility of various sensors by recovering parachute-probe dynamics information from a package released from a small-scale, remote-controlled airplane. The airdrops aid in the development of datasets for the exploration of planetary probe trajectory recovery algorithms, supplementing data collected from instrumented, full-scale tests and computer models.

The Isan Culture Maintenance and Revitalisation Programme's Multilingual Signage Attitude Survey: Phase II

ERIC Educational Resources Information Center

Draper, John

2016-01-01

This article contextualises and presents to the academic community the full dataset of the Isan Culture Maintenance and Revitalisation Programme's (ICMRP) multilingual signage survey. The ICMRP is a four-year European Union co-sponsored project in Northeast Thailand. This article focuses on one aspect of the project, four surveys each of 1,500…

Search for B to K nu nubar decays with a semileptonic tag

NASA Astrophysics Data System (ADS)

Vuosalo, Carl

Flavor-changing neutral-current transitions such as b → snunu are absent at tree level in the Standard Model and can only occur via loop diagrams. Several new physics models may enhance the rate of these transitions. This document presents searches for the exclusive decays B+u → K+nunu and B0d → K0S nunu, which have a predicted theoretical branching fraction of ( 3.8+1.2-0.6 ) x 10-6. The presence of two neutrinos in the final state makes recognition of the signal challenging, so the full reconstruction of one B meson in the semileptonic decay channel B → D(*) lnu is used to facilitate the search for the signal in the recoiling B. This analysis uses approximately 420 fb-1 or 460 million BB¯ pairs collected over runs 1-6 with the BABAR detector at the PEP-II B factory. This analysis finds 90% confidence level upper limits on the branching fractions of 1.3 x 10-5 for B+u → K+nunu, 5.6 x 10-5 for B0d → K0nunu, and the first upper limits on the partial branching fractions for B+u → K+nunu of 3.1 x 10-5 for K+ CMS momentum < 1.5 GeV/c and of 0.89 x 10-5 for K+ CMS momentum > 1.5 GeV/c. These results improve upon the previous best upper limits, which came from the Belle experiment, of 1.4 x 10-5 for B+u → K+nunu and 16 x 10-5 for B0d → K0nunu. They also rule out a new physics model of scalar dark matter for scalar particle masses below 1.7 GeV/c2.

$$|V_{ub}|$$ from $$B\\to\\pi\\ell\

DOE PAGES

Bailey, Jon A.; et al.

2015-07-23

We present a lattice-QCD calculation of the B → πℓν semileptonic form factors and a new determination of the CKM matrix element |V ub|. We use the MILC asqtad (2+1)-flavor lattice configurations at four lattice spacings and light-quark masses down to 1/20 of the physical strange-quark mass. We extrapolate the lattice form factors to the continuum using staggered chiral perturbation theory in the hard-pion and SU(2) limits. We employ a model-independent z parametrization to extrapolate our lattice form factors from large-recoil momentum to the full kinematic range. We introduce a new functional method to propagate information from the chiral-continuum extrapolationmore » to the z expansion. We present our results together with a complete systematic error budget, including a covariance matrix to enable the combination of our form factors with other lattice-QCD and experimental results. To obtain |V ub|, we simultaneously fit the experimental data for the B → πℓν differential decay rate obtained by the BABAR and Belle collaborations together with our lattice form-factor results. We find |V ub|=(3.72±0.16) × 10 –3, where the error is from the combined fit to lattice plus experiments and includes all sources of uncertainty. Our form-factor results bring the QCD error on |V ub| to the same level as the experimental error. We also provide results for the B → πℓν vector and scalar form factors obtained from the combined lattice and experiment fit, which are more precisely determined than from our lattice-QCD calculation alone. Lastly, these results can be used in other phenomenological applications and to test other approaches to QCD.« less

B → Dℓν form factors at nonzero recoil and |V cb| from 2+1-flavor lattice QCD

DOE PAGES

Bailey, Jon A.

2015-08-10

We present the first unquenched lattice-QCD calculation of the hadronic form factors for the exclusive decay B¯→Dℓν¯ at nonzero recoil. We carry out numerical simulations on 14 ensembles of gauge-field configurations generated with 2+1 flavors of asqtad-improved staggered sea quarks. The ensembles encompass a wide range of lattice spacings (approximately 0.045 to 0.12 fm) and ratios of light (up and down) to strange sea-quark masses ranging from 0.05 to 0.4. For the b and c valence quarks we use improved Wilson fermions with the Fermilab interpretation, while for the light valence quarks we use asqtad-improved staggered fermions. We extrapolate ourmore » results to the physical point using rooted staggered heavy-light meson chiral perturbation theory. We then parametrize the form factors and extend them to the full kinematic range using model-independent functions based on analyticity and unitarity. We present our final results for f +(q 2) and f 0(q 2), including statistical and systematic errors, as coefficients of a series in the variable z and the covariance matrix between these coefficients. We then fit the lattice form-factor data jointly with the experimentally measured differential decay rate from BABAR to determine the CKM matrix element, |V cb|=(39.6 ± 1.7 QCD+exp ± 0.2 QED) × 10 –3. As a byproduct of the joint fit we obtain the form factors with improved precision at large recoil. In conclusion, we use them to update our calculation of the ratio R(D) in the Standard Model, which yields R(D)=0.299(11).« less

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bailey, Jon A.; et al.

We present a lattice-QCD calculation of the B → πℓν semileptonic form factors and a new determination of the CKM matrix element |V ub|. We use the MILC asqtad (2+1)-flavor lattice configurations at four lattice spacings and light-quark masses down to 1/20 of the physical strange-quark mass. We extrapolate the lattice form factors to the continuum using staggered chiral perturbation theory in the hard-pion and SU(2) limits. We employ a model-independent z parametrization to extrapolate our lattice form factors from large-recoil momentum to the full kinematic range. We introduce a new functional method to propagate information from the chiral-continuum extrapolationmore » to the z expansion. We present our results together with a complete systematic error budget, including a covariance matrix to enable the combination of our form factors with other lattice-QCD and experimental results. To obtain |V ub|, we simultaneously fit the experimental data for the B → πℓν differential decay rate obtained by the BABAR and Belle collaborations together with our lattice form-factor results. We find |V ub|=(3.72±0.16) × 10 –3, where the error is from the combined fit to lattice plus experiments and includes all sources of uncertainty. Our form-factor results bring the QCD error on |V ub| to the same level as the experimental error. We also provide results for the B → πℓν vector and scalar form factors obtained from the combined lattice and experiment fit, which are more precisely determined than from our lattice-QCD calculation alone. Lastly, these results can be used in other phenomenological applications and to test other approaches to QCD.« less

Measurement of CP asymmetries and branching fractions in charmless two-body B-meson decays to pions and kaons

NASA Astrophysics Data System (ADS)

Lees, J. P.; Poireau, V.; Tisserand, V.; Garra Tico, J.; Grauges, E.; Palano, A.; Eigen, G.; Stugu, B.; Brown, D. N.; Kerth, L. T.; Kolomensky, Yu. G.; Lynch, G.; Koch, H.; Schroeder, T.; Asgeirsson, D. J.; Hearty, C.; Mattison, T. S.; McKenna, J. A.; So, R. Y.; Khan, A.; Blinov, V. E.; Buzykaev, A. R.; Druzhinin, V. P.; Golubev, V. B.; Kravchenko, E. A.; Onuchin, A. P.; Serednyakov, S. I.; Skovpen, Yu. I.; Solodov, E. P.; Todyshev, K. Yu.; Yushkov, A. N.; Bondioli, M.; Kirkby, D.; Lankford, A. J.; Mandelkern, M.; Atmacan, H.; Gary, J. W.; Liu, F.; Long, O.; Vitug, G. M.; Campagnari, C.; Hong, T. M.; Kovalskyi, D.; Richman, J. D.; West, C. A.; Eisner, A. M.; Kroseberg, J.; Lockman, W. S.; Martinez, A. J.; Schumm, B. A.; Seiden, A.; Chao, D. S.; Cheng, C. H.; Echenard, B.; Flood, K. T.; Hitlin, D. G.; Ongmongkolkul, P.; Porter, F. C.; Rakitin, A. Y.; Andreassen, R.; Huard, Z.; Meadows, B. T.; Sokoloff, M. D.; Sun, L.; Bloom, P. C.; Ford, W. T.; Gaz, A.; Nauenberg, U.; Smith, J. G.; Wagner, S. R.; Ayad, R.; Toki, W. H.; Spaan, B.; Schubert, K. R.; Schwierz, R.; Bernard, D.; Verderi, M.; Clark, P. J.; Playfer, S.; Bettoni, D.; Bozzi, C.; Calabrese, R.; Cibinetto, G.; Fioravanti, E.; Garzia, I.; Luppi, E.; Munerato, M.; Negrini, M.; Piemontese, L.; Santoro, V.; Baldini-Ferroli, R.; Calcaterra, A.; de Sangro, R.; Finocchiaro, G.; Patteri, P.; Peruzzi, I. M.; Piccolo, M.; Rama, M.; Zallo, A.; Contri, R.; Guido, E.; Lo Vetere, M.; Monge, M. R.; Passaggio, S.; Patrignani, C.; Robutti, E.; Bhuyan, B.; Prasad, V.; Lee, C. L.; Morii, M.; Edwards, A. J.; Adametz, A.; Uwer, U.; Lacker, H. M.; Lueck, T.; Dauncey, P. D.; Behera, P. K.; Mallik, U.; Chen, C.; Cochran, J.; Meyer, W. T.; Prell, S.; Rubin, A. E.; Gritsan, A. V.; Guo, Z. J.; Arnaud, N.; Davier, M.; Derkach, D.; Grosdidier, G.; Le Diberder, F.; Lutz, A. M.; Malaescu, B.; Roudeau, P.; Schune, M. H.; Stocchi, A.; Wormser, G.; Lange, D. J.; Wright, D. M.; Chavez, C. A.; Coleman, J. P.; Fry, J. R.; Gabathuler, E.; Hutchcroft, D. E.; Payne, D. J.; Touramanis, C.; Bevan, A. J.; Di Lodovico, F.; Sacco, R.; Sigamani, M.; Cowan, G.; Brown, D. N.; Davis, C. L.; Denig, A. G.; Fritsch, M.; Gradl, W.; Griessinger, K.; Hafner, A.; Prencipe, E.; Barlow, R. J.; Jackson, G.; Lafferty, G. D.; Behn, E.; Cenci, R.; Hamilton, B.; Jawahery, A.; Roberts, D. A.; Dallapiccola, C.; Cowan, R.; Dujmic, D.; Sciolla, G.; Cheaib, R.; Lindemann, D.; Patel, P. M.; Robertson, S. H.; Biassoni, P.; Neri, N.; Palombo, F.; Stracka, S.; Cremaldi, L.; Godang, R.; Kroeger, R.; Sonnek, P.; Summers, D. J.; Nguyen, X.; Simard, M.; Taras, P.; De Nardo, G.; Monorchio, D.; Onorato, G.; Sciacca, C.; Martinelli, M.; Raven, G.; Jessop, C. P.; LoSecco, J. M.; Wang, W. F.; Honscheid, K.; Kass, R.; Brau, J.; Frey, R.; Sinev, N. B.; Strom, D.; Torrence, E.; Feltresi, E.; Gagliardi, N.; Margoni, M.; Morandin, M.; Posocco, M.; Rotondo, M.; Simi, G.; Simonetto, F.; Stroili, R.; Akar, S.; Ben-Haim, E.; Bomben, M.; Bonneaud, G. R.; Briand, H.; Calderini, G.; Chauveau, J.; Hamon, O.; Leruste, Ph.; Marchiori, G.; Ocariz, J.; Sitt, S.; Biasini, M.; Manoni, E.; Pacetti, S.; Rossi, A.; Angelini, C.; Batignani, G.; Bettarini, S.; Carpinelli, M.; Casarosa, G.; Cervelli, A.; Forti, F.; Giorgi, M. A.; Lusiani, A.; Oberhof, B.; Paoloni, E.; Perez, A.; Rizzo, G.; Walsh, J. J.; Lopes Pegna, D.; Olsen, J.; Smith, A. J. S.; Telnov, A. V.; Anulli, F.; Faccini, R.; Ferrarotto, F.; Ferroni, F.; Gaspero, M.; Li Gioi, L.; Mazzoni, M. A.; Piredda, G.; Bünger, C.; Grünberg, O.; Hartmann, T.; Leddig, T.; Schröder, H.; Voss, C.; Waldi, R.; Adye, T.; Olaiya, E. O.; Wilson, F. F.; Emery, S.; Hamel de Monchenault, G.; Vasseur, G.; Yèche, Ch.; Aston, D.; Bard, D. J.; Bartoldus, R.; Benitez, J. F.; Cartaro, C.; Convery, M. R.; Dorfan, J.; Dubois-Felsmann, G. P.; Dunwoodie, W.; Ebert, M.; Field, R. C.; Franco Sevilla, M.; Fulsom, B. G.; Gabareen, A. M.; Graham, M. T.; Grenier, P.; Hast, C.; Innes, W. R.; Kelsey, M. H.; Kim, P.; Kocian, M. L.; Leith, D. W. G. S.; Lewis, P.; Lindquist, B.; Luitz, S.; Luth, V.; Lynch, H. L.; MacFarlane, D. B.; Muller, D. R.; Neal, H.; Nelson, S.; Perl, M.; Pulliam, T.; Ratcliff, B. N.; Roodman, A.; Salnikov, A. A.; Schindler, R. H.; Snyder, A.; Su, D.; Sullivan, M. K.; Va'vra, J.; Wagner, A. P.; Wisniewski, W. J.; Wittgen, M.; Wright, D. H.; Wulsin, H. W.; Young, C. C.; Ziegler, V.; Park, W.; Purohit, M. V.; White, R. M.; Wilson, J. R.; Randle-Conde, A.; Sekula, S. J.; Bellis, M.; Burchat, P. R.; Miyashita, T. S.; Alam, M. S.; Ernst, J. A.; Gorodeisky, R.; Guttman, N.; Peimer, D. R.; Soffer, A.; Lund, P.; Spanier, S. M.; Ritchie, J. L.; Ruland, A. M.; Schwitters, R. F.; Wray, B. C.; Izen, J. M.; Lou, X. C.; Bianchi, F.; Gamba, D.; Lanceri, L.; Vitale, L.; Martinez-Vidal, F.; Oyanguren, A.; Ahmed, H.; Albert, J.; Banerjee, Sw.; Bernlochner, F. U.; Choi, H. H. F.; King, G. J.; Kowalewski, R.; Lewczuk, M. J.; Nugent, I. M.; Roney, J. M.; Sobie, R. J.; Tasneem, N.; Gershon, T. J.; Harrison, P. F.; Latham, T. E.; Puccio, E. M. T.; Band, H. R.; Dasu, S.; Pan, Y.; Prepost, R.; Wu, S. L.

2013-03-01

We present improved measurements of CP-violation parameters in the decays B0→π+π-, B0→K+π-, and B0→π0π0, and of the branching fractions for B0→π0π0 and B0→K0π0. The results are obtained with the full data set collected at the Υ(4S) resonance by the BABAR experiment at the PEP-II asymmetric-energy B factory at the SLAC National Accelerator Laboratory, corresponding to (467±5)×106 BB¯ pairs. We find the CP-violation parameter values and branching fractions: Sπ+π-=-0.68±0.10±0.03, Cπ+π-=-0.25±0.08±0.02, AK-π+=-0.107±0.016-0.004+0.006, Cπ0π0=-0.43±0.26±0.05, B(B0→π0π0)=(1.83±0.21±0.13)×10-6, B(B0→K0π0)=(10.1±0.6±0.4)×10-6, where in each case, the first uncertainties are statistical and the second are systematic. We observe CP violation with a significance of 6.7 standard deviations for B0→π+π- and 6.1 standard deviations for B0→K+π-, including systematic uncertainties. Constraints on the unitarity triangle angle α are determined from the isospin relations among the B→ππ rates and asymmetries. Considering only the solution preferred by the Standard Model, we find α to be in the range [71°,109°] at the 68% confidence level.

On the quantification and efficient propagation of imprecise probabilities resulting from small datasets

NASA Astrophysics Data System (ADS)

Zhang, Jiaxin; Shields, Michael D.

2018-01-01

This paper addresses the problem of uncertainty quantification and propagation when data for characterizing probability distributions are scarce. We propose a methodology wherein the full uncertainty associated with probability model form and parameter estimation are retained and efficiently propagated. This is achieved by applying the information-theoretic multimodel inference method to identify plausible candidate probability densities and associated probabilities that each method is the best model in the Kullback-Leibler sense. The joint parameter densities for each plausible model are then estimated using Bayes' rule. We then propagate this full set of probability models by estimating an optimal importance sampling density that is representative of all plausible models, propagating this density, and reweighting the samples according to each of the candidate probability models. This is in contrast with conventional methods that try to identify a single probability model that encapsulates the full uncertainty caused by lack of data and consequently underestimate uncertainty. The result is a complete probabilistic description of both aleatory and epistemic uncertainty achieved with several orders of magnitude reduction in computational cost. It is shown how the model can be updated to adaptively accommodate added data and added candidate probability models. The method is applied for uncertainty analysis of plate buckling strength where it is demonstrated how dataset size affects the confidence (or lack thereof) we can place in statistical estimates of response when data are lacking.

Publishing NASA Metadata as Linked Open Data for Semantic Mashups

NASA Astrophysics Data System (ADS)

Wilson, Brian; Manipon, Gerald; Hua, Hook

2014-05-01

Data providers are now publishing more metadata in more interoperable forms, e.g. Atom or RSS 'casts', as Linked Open Data (LOD), or as ISO Metadata records. A major effort on the part of the NASA's Earth Science Data and Information System (ESDIS) project is the aggregation of metadata that enables greater data interoperability among scientific data sets regardless of source or application. Both the Earth Observing System (EOS) ClearingHOuse (ECHO) and the Global Change Master Directory (GCMD) repositories contain metadata records for NASA (and other) datasets and provided services. These records contain typical fields for each dataset (or software service) such as the source, creation date, cognizant institution, related access URL's, and domain and variable keywords to enable discovery. Under a NASA ACCESS grant, we demonstrated how to publish the ECHO and GCMD dataset and services metadata as LOD in the RDF format. Both sets of metadata are now queryable at SPARQL endpoints and available for integration into "semantic mashups" in the browser. It is straightforward to reformat sets of XML metadata, including ISO, into simple RDF and then later refine and improve the RDF predicates by reusing known namespaces such as Dublin core, georss, etc. All scientific metadata should be part of the LOD world. In addition, we developed an "instant" drill-down and browse interface that provides faceted navigation so that the user can discover and explore the 25,000 datasets and 3000 services. The available facets and the free-text search box appear in the left panel, and the instantly updated results for the dataset search appear in the right panel. The user can constrain the value of a metadata facet simply by clicking on a word (or phrase) in the "word cloud" of values for each facet. The display section for each dataset includes the important metadata fields, a full description of the dataset, potentially some related URL's, and a "search" button that points to an OpenSearch GUI that is pre-configured to search for granules within the dataset. We will present our experiences with converting NASA metadata into LOD, discuss the challenges, illustrate some of the enabled mashups, and demonstrate the latest version of the "instant browse" interface for navigating multiple metadata collections.

Study of CP Violation in Dalitz-Plot Analyses of B-Meson Decays to Three Kaons

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lindquist, Brian

The Standard Model (SM) explains CP violation in terms of the CKM matrix. The BABAR experiment was designed mainly to test the CKM model in B decays. B decays that proceed through b → s loop diagrams, of which B {yields} KKK decays are an example, are sensitive to new physics effects that could lead to deviations from the CKM predictions for CP violation. We present studies of CP violation in the decays B + → K +K -K +, B + → K S 0K S 0K +, and B 0 → K +K -K S 0, using a Dalitz plot amplitude analysis. These studies are based on approximately 470 million Bmore » $$\\bar{B}$$ decays collected by BABAR at the PEP-II collider at SLAC. We perform measurements of time-dependent CP violation in B 0 → K +K -K S 0, including B 0 → ΦK S 0. We measure a CP-violating phase β eff (ΦK S 0) = 0.36 ± 0.11 ± 0.04 rad., in agreement with the SM. This is the world's most precise measurement of this quantity. We also measure direct CP asymmetries in all three decay modes, including the direct CP asymmetry A CP (ΦK +) = (12.8 ± 4.4 ± 1.3)%, which is 2.8 sigma away from zero. This measurement is in tension with the SM, which predicts an asymmetry of a few percent. We also study the resonant and nonresonant features in the B → KKK Dalitz plots. We find that the hypothetical scalar f X(1500) resonance, introduced by prior analyses to explain an unknown peak in the m KK spectrum, cannot adequately describe the data. We conclude instead that the f X(1500) can be explained as the sum of the f 0(1500), f' 2(1525), and f 0(1710) resonances, removing the need for the hypothetical f X(1500). We also find that an exponential nonresonant model, used by previous analyses to describe the broad nonresonant feature seen in B → KKK decays, cannot fully model the data. We introduce a new nonresonant model that contains more free parameters, allows for phase motion, and contains both S-wave and P-wave components.« less

A Study of Double-Charm and Charm-Strange Baryons inElectron-Positron Annihilations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Edwards, Adam J.; /SLAC

2007-10-15

In this dissertation I describe a study of double-charm and charm-strange baryons based on data collected with the BABAR Detector at the Stanford Linear Accelerator Center. In this study I search for new baryons and make precise measurements of their properties and decay modes. I seek to verify and expand upon double-charm and charm-strange baryon observations made by other experiments. The BABAR Detector is used to measure subatomic particles that are produced at the PEP-II storage rings. I analyze approximately 300 million e+e- {yields} c{bar c} events in a search for the production of double-charm baryons. I search for themore » double-charm baryons {Xi}{sup +}{sub cc} (containing the quarks ccd) and {Xi}{sup ++}{sub cc} (ccu) in decays to {Lambda}{sup +}{sub c}K{sup -}{pi}{sup +} and {Lambda}{sup +}{sub c}K{sup -}{pi}{sup +}{pi}{sup +}, respectively. No statistically significant signals for their production are found, and upper limits on their production are determined. Statistically significant signals for excited charm-strange baryons are observed with my analysis of approximately 500 million e+e- {yields} c{bar c} events. The charged charm-strange baryons {Xi}{sub c}(2970){sup +}, {Xi}{sub c}(3055){sup +}, {Xi}{sub c}(3123){sup +} are found in decays to {Lambda}{sup +}{sub c}K{sup -}{pi}{sup +}, the same decay mode used in the {Xi}{sup +}{sub cc} search. The neutral charm-strange baryon {Xi}{sub c}(3077){sup 0} is observed in decays to {Lambda}{sup +}{sub c}K{sub 8}{pi}{sup -}. I also search for excited charm-strange baryon decays to {Lambda}{sup +}{sub c}K{sub 8}, {Lambda}{sup +}{sub c}K{sup -}, {Lambda}{sup +}{sub c}K{sub 8}{pi}{sup -}{pi}{sup +}, and {Lambda}{sup +}{sub c}K{sup -}{pi}{sup -}{pi}{sup +}. No significant charm-strange baryon signals a f h these decay modes. For each excited charm-strange baryon state that I observe, I measure its mass, natural width (lifetime), and production rate. The properties of these excited charm-strange baryons and their decay modes provide constraints for phenomenological models of quark interactions through quantum chromodynamics. My discovery of the two new charm-strange baryons {Xi}{sub c}(3055){sup +} and {Xi}{sub c}(3123){sup +} influences our theoretical understanding of charm-strange baryon states.« less

Using NASA's Giovanni Web Portal to Access and Visualize Satellite-Based Earth Science Data in the Classroom

NASA Astrophysics Data System (ADS)

Lloyd, S. A.; Acker, J. G.; Prados, A. I.; Leptoukh, G. G.

2008-12-01

One of the biggest obstacles for the average Earth science student today is locating and obtaining satellite- based remote sensing datasets in a format that is accessible and optimal for their data analysis needs. At the Goddard Earth Sciences Data and Information Services Center (GES-DISC) alone, on the order of hundreds of Terabytes of data are available for distribution to scientists, students and the general public. The single biggest and time-consuming hurdle for most students when they begin their study of the various datasets is how to slog through this mountain of data to arrive at a properly sub-setted and manageable dataset to answer their science question(s). The GES DISC provides a number of tools for data access and visualization, including the Google-like Mirador search engine and the powerful GES-DISC Interactive Online Visualization ANd aNalysis Infrastructure (Giovanni) web interface. Giovanni provides a simple way to visualize, analyze and access vast amounts of satellite-based Earth science data. Giovanni's features and practical examples of its use will be demonstrated, with an emphasis on how satellite remote sensing can help students understand recent events in the atmosphere and biosphere. Giovanni is actually a series of sixteen similar web-based data interfaces, each of which covers a single satellite dataset (such as TRMM, TOMS, OMI, AIRS, MLS, HALOE, etc.) or a group of related datasets (such as MODIS and MISR for aerosols, SeaWIFS and MODIS for ocean color, and the suite of A-Train observations co-located along the CloudSat orbital path). Recently, ground-based datasets have been included in Giovanni, including the Northern Eurasian Earth Science Partnership Initiative (NEESPI), and EPA fine particulate matter (PM2.5) for air quality. Model data such as the Goddard GOCART model and MERRA meteorological reanalyses (in process) are being increasingly incorporated into Giovanni to facilitate model- data intercomparison. A full suite of data analysis and visualization tools is also available within Giovanni. The GES DISC is currently developing a systematic series of training modules for Earth science satellite data, associated with our development of additional datasets and data visualization tools for Giovanni. Training sessions will include an overview of the Earth science datasets archived at Goddard, an overview of terms and techniques associated with satellite remote sensing, dataset-specific issues, an overview of Giovanni functionality, and a series of examples of how data can be readily accessed and visualized.

Evaluating Functional Diversity: Missing Trait Data and the Importance of Species Abundance Structure and Data Transformation

PubMed Central

Bryndová, Michala; Kasari, Liis; Norberg, Anna; Weiss, Matthias; Bishop, Tom R.; Luke, Sarah H.; Sam, Katerina; Le Bagousse-Pinguet, Yoann; Lepš, Jan; Götzenberger, Lars; de Bello, Francesco

2016-01-01

Functional diversity (FD) is an important component of biodiversity that quantifies the difference in functional traits between organisms. However, FD studies are often limited by the availability of trait data and FD indices are sensitive to data gaps. The distribution of species abundance and trait data, and its transformation, may further affect the accuracy of indices when data is incomplete. Using an existing approach, we simulated the effects of missing trait data by gradually removing data from a plant, an ant and a bird community dataset (12, 59, and 8 plots containing 62, 297 and 238 species respectively). We ranked plots by FD values calculated from full datasets and then from our increasingly incomplete datasets and compared the ranking between the original and virtually reduced datasets to assess the accuracy of FD indices when used on datasets with increasingly missing data. Finally, we tested the accuracy of FD indices with and without data transformation, and the effect of missing trait data per plot or per the whole pool of species. FD indices became less accurate as the amount of missing data increased, with the loss of accuracy depending on the index. But, where transformation improved the normality of the trait data, FD values from incomplete datasets were more accurate than before transformation. The distribution of data and its transformation are therefore as important as data completeness and can even mitigate the effect of missing data. Since the effect of missing trait values pool-wise or plot-wise depends on the data distribution, the method should be decided case by case. Data distribution and data transformation should be given more careful consideration when designing, analysing and interpreting FD studies, especially where trait data are missing. To this end, we provide the R package “traitor” to facilitate assessments of missing trait data. PMID:26881747

Evaluating Functional Diversity: Missing Trait Data and the Importance of Species Abundance Structure and Data Transformation.

PubMed

Májeková, Maria; Paal, Taavi; Plowman, Nichola S; Bryndová, Michala; Kasari, Liis; Norberg, Anna; Weiss, Matthias; Bishop, Tom R; Luke, Sarah H; Sam, Katerina; Le Bagousse-Pinguet, Yoann; Lepš, Jan; Götzenberger, Lars; de Bello, Francesco

2016-01-01

Functional diversity (FD) is an important component of biodiversity that quantifies the difference in functional traits between organisms. However, FD studies are often limited by the availability of trait data and FD indices are sensitive to data gaps. The distribution of species abundance and trait data, and its transformation, may further affect the accuracy of indices when data is incomplete. Using an existing approach, we simulated the effects of missing trait data by gradually removing data from a plant, an ant and a bird community dataset (12, 59, and 8 plots containing 62, 297 and 238 species respectively). We ranked plots by FD values calculated from full datasets and then from our increasingly incomplete datasets and compared the ranking between the original and virtually reduced datasets to assess the accuracy of FD indices when used on datasets with increasingly missing data. Finally, we tested the accuracy of FD indices with and without data transformation, and the effect of missing trait data per plot or per the whole pool of species. FD indices became less accurate as the amount of missing data increased, with the loss of accuracy depending on the index. But, where transformation improved the normality of the trait data, FD values from incomplete datasets were more accurate than before transformation. The distribution of data and its transformation are therefore as important as data completeness and can even mitigate the effect of missing data. Since the effect of missing trait values pool-wise or plot-wise depends on the data distribution, the method should be decided case by case. Data distribution and data transformation should be given more careful consideration when designing, analysing and interpreting FD studies, especially where trait data are missing. To this end, we provide the R package "traitor" to facilitate assessments of missing trait data.

Impact of Missing Physiologic Data on Performance of the Simplified Acute Physiology Score 3 Risk-Prediction Model.

PubMed

Engerström, Lars; Nolin, Thomas; Mårdh, Caroline; Sjöberg, Folke; Karlström, Göran; Fredrikson, Mats; Walther, Sten M

2017-12-01

The Simplified Acute Physiology 3 outcome prediction model has a narrow time window for recording physiologic measurements. Our objective was to examine the prevalence and impact of missing physiologic data on the Simplified Acute Physiology 3 model's performance. Retrospective analysis of prospectively collected data. Sixty-three ICUs in the Swedish Intensive Care Registry. Patients admitted during 2011-2014 (n = 107,310). None. Model performance was analyzed using the area under the receiver operating curve, scaled Brier's score, and standardized mortality rate. We used a recalibrated Simplified Acute Physiology 3 model and examined model performance in the original dataset and in a dataset of complete records where missing data were generated (simulated dataset). One or more data were missing in 40.9% of the admissions, more common in survivors and low-risk admissions than in nonsurvivors and high-risk admissions. Discrimination did not decrease with one to two missing variables, but accuracy was highest with no missing data. Calibration was best in the original dataset with a mix of full records and records with some missing values (area under the receiver operating curve was 0.85, scaled Brier 27%, and standardized mortality rate 0.99). With zero, one, and two data missing, the scaled Brier was 31%, 26%, and 21%; area under the receiver operating curve was 0.84, 0.87, and 0.89; and standardized mortality rate was 0.92, 1.05 and 1.10, respectively. Datasets where the missing data were simulated for oxygenation or oxygenation and hydrogen ion concentration together performed worse than datasets with these data originally missing. There is a coupling between missing physiologic data, admission type, low risk, and survival. Increased loss of physiologic data reduced model performance and will deflate mortality risk, resulting in falsely high standardized mortality rates.

Large scale validation of the M5L lung CAD on heterogeneous CT datasets.

PubMed

Torres, E Lopez; Fiorina, E; Pennazio, F; Peroni, C; Saletta, M; Camarlinghi, N; Fantacci, M E; Cerello, P

2015-04-01

M5L, a fully automated computer-aided detection (CAD) system for the detection and segmentation of lung nodules in thoracic computed tomography (CT), is presented and validated on several image datasets. M5L is the combination of two independent subsystems, based on the Channeler Ant Model as a segmentation tool [lung channeler ant model (lungCAM)] and on the voxel-based neural approach. The lungCAM was upgraded with a scan equalization module and a new procedure to recover the nodules connected to other lung structures; its classification module, which makes use of a feed-forward neural network, is based of a small number of features (13), so as to minimize the risk of lacking generalization, which could be possible given the large difference between the size of the training and testing datasets, which contain 94 and 1019 CTs, respectively. The lungCAM (standalone) and M5L (combined) performance was extensively tested on 1043 CT scans from three independent datasets, including a detailed analysis of the full Lung Image Database Consortium/Image Database Resource Initiative database, which is not yet found in literature. The lungCAM and M5L performance is consistent across the databases, with a sensitivity of about 70% and 80%, respectively, at eight false positive findings per scan, despite the variable annotation criteria and acquisition and reconstruction conditions. A reduced sensitivity is found for subtle nodules and ground glass opacities (GGO) structures. A comparison with other CAD systems is also presented. The M5L performance on a large and heterogeneous dataset is stable and satisfactory, although the development of a dedicated module for GGOs detection could further improve it, as well as an iterative optimization of the training procedure. The main aim of the present study was accomplished: M5L results do not deteriorate when increasing the dataset size, making it a candidate for supporting radiologists on large scale screenings and clinical programs.

Aerosol Climate Time Series in ESA Aerosol_cci

NASA Astrophysics Data System (ADS)

Popp, Thomas; de Leeuw, Gerrit; Pinnock, Simon

2016-04-01

Within the ESA Climate Change Initiative (CCI) Aerosol_cci (2010 - 2017) conducts intensive work to improve algorithms for the retrieval of aerosol information from European sensors. Meanwhile, full mission time series of 2 GCOS-required aerosol parameters are completely validated and released: Aerosol Optical Depth (AOD) from dual view ATSR-2 / AATSR radiometers (3 algorithms, 1995 - 2012), and stratospheric extinction profiles from star occultation GOMOS spectrometer (2002 - 2012). Additionally, a 35-year multi-sensor time series of the qualitative Absorbing Aerosol Index (AAI) together with sensitivity information and an AAI model simulator is available. Complementary aerosol properties requested by GCOS are in a "round robin" phase, where various algorithms are inter-compared: fine mode AOD, mineral dust AOD (from the thermal IASI spectrometer, but also from ATSR instruments and the POLDER sensor), absorption information and aerosol layer height. As a quasi-reference for validation in few selected regions with sparse ground-based observations the multi-pixel GRASP algorithm for the POLDER instrument is used. Validation of first dataset versions (vs. AERONET, MAN) and inter-comparison to other satellite datasets (MODIS, MISR, SeaWIFS) proved the high quality of the available datasets comparable to other satellite retrievals and revealed needs for algorithm improvement (for example for higher AOD values) which were taken into account for a reprocessing. The datasets contain pixel level uncertainty estimates which were also validated and improved in the reprocessing. For the three ATSR algorithms the use of an ensemble method was tested. The paper will summarize and discuss the status of dataset reprocessing and validation. The focus will be on the ATSR, GOMOS and IASI datasets. Pixel level uncertainties validation will be summarized and discussed including unknown components and their potential usefulness and limitations. Opportunities for time series extension with successor instruments of the Sentinel family will be described and the complementarity of the different satellite aerosol products (e.g. dust vs. total AOD, ensembles from different algorithms for the same sensor) will be discussed.

Release of a 10-m-resolution DEM for the whole Italian territory: a new, freely available resource for research purposes

NASA Astrophysics Data System (ADS)

Tarquini, S.; Nannipieri, L.; Favalli, M.; Fornaciai, A.; Vinci, S.; Doumaz, F.

2012-04-01

Digital elevation models (DEMs) are fundamental in any kind of environmental or morphological study. DEMs are obtained from a variety of sources and generated in several ways. Nowadays, a few global-coverage elevation datasets are available for free (e.g., SRTM, http://www.jpl.nasa.gov/srtm; ASTER, http://asterweb.jpl.nasa.gov/). When the matrix of a DEM is used also for computational purposes, the choice of the elevation dataset which better suits the target of the study is crucial. Recently, the increasing use of DEM-based numerical simulation tools (e.g. for gravity driven mass flows), would largely benefit from the use of a higher resolution/higher accuracy topography than those available at planetary scale. Similar elevation datasets are neither easily nor freely available for all countries worldwide. Here we introduce a new web resource which made available for free (for research purposes only) a 10 m-resolution DEM for the whole Italian territory. The creation of this elevation dataset was presented by Tarquini et al. (2007). This DEM was obtained in triangular irregular network (TIN) format starting from heterogeneous vector datasets, mostly consisting in elevation contour lines and elevation points derived from several sources. The input vector database was carefully cleaned up to obtain an improved seamless TIN refined by using the DEST algorithm, thus improving the Delaunay tessellation. The whole TINITALY/01 DEM was converted in grid format (10-m cell size) according to a tiled structure composed of 193, 50-km side square elements. The grid database consists of more than 3 billions of cells and occupies almost 12 GB of disk memory. A web-GIS has been created (http://tinitaly.pi.ingv.it/ ) where a seamless layer of images in full resolution (10 m) obtained from the whole DEM (both in color-shaded and anaglyph mode) is open for browsing. Accredited navigators are allowed to download the elevation dataset.

Derivation of a Provisional, Age-dependent, AIS2+ Thoracic Risk Curve for the THOR50 Test Dummy via Integration of NASS Cases, PMHS Tests, and Simulation Data.

PubMed

Laituri, Tony R; Henry, Scott; El-Jawahri, Raed; Muralidharan, Nirmal; Li, Guosong; Nutt, Marvin

2015-11-01

A provisional, age-dependent thoracic risk equation (or, "risk curve") was derived to estimate moderate-to-fatal injury potential (AIS2+), pertaining to men with responses gaged by the advanced mid-sized male test dummy (THOR50). The derivation involved two distinct data sources: cases from real-world crashes (e.g., the National Automotive Sampling System, NASS) and cases involving post-mortem human subjects (PMHS). The derivation was therefore more comprehensive, as NASS datasets generally skew towards younger occupants, and PMHS datasets generally skew towards older occupants. However, known deficiencies had to be addressed (e.g., the NASS cases had unknown stimuli, and the PMHS tests required transformation of known stimuli into THOR50 stimuli). For the NASS portion of the analysis, chest-injury outcomes for adult male drivers about the size of the THOR50 were collected from real-world, 11-1 o'clock, full-engagement frontal crashes (NASS, 1995-2012 calendar years, 1985-2012 model-year light passenger vehicles). The screening for THOR50-sized men involved application of a set of newly-derived "correction" equations for self-reported height and weight data in NASS. Finally, THOR50 stimuli were estimated via field simulations involving attendant representative restraint systems, and those stimuli were then assigned to corresponding NASS cases (n=508). For the PMHS portion of the analysis, simulation-based closure equations were developed to convert PMHS stimuli into THOR50 stimuli. Specifically, closure equations were derived for the four measurement locations on the THOR50 chest by cross-correlating the results of matched-loading simulations between the test dummy and the age-dependent, Ford Human Body Model. The resulting closure equations demonstrated acceptable fidelity (n=75 matched simulations, R2≥0.99). These equations were applied to the THOR50-sized men in the PMHS dataset (n=20). The NASS and PMHS datasets were combined and subjected to survival analysis with event-frequency weighting and arbitrary censoring. The resulting risk curve--a function of peak THOR50 chest compression and age--demonstrated acceptable fidelity for recovering the AIS2+ chest injury rate of the combined dataset (i.e., IR_dataset=1.97% vs. curve-based IR_dataset=1.98%). Additional sensitivity analyses showed that (a) binary logistic regression yielded a risk curve with nearly-identical fidelity, (b) there was only a slight advantage of combining the small-sample PMHS dataset with the large-sample NASS dataset, (c) use of the PMHS-based risk curve for risk estimation of the combined dataset yielded relatively poor performance (194% difference), and (d) when controlling for the type of contact (lab-consistent or not), the resulting risk curves were similar.

Neutrino constraints: what large-scale structure and CMB data are telling us?

NASA Astrophysics Data System (ADS)

Costanzi, Matteo; Sartoris, Barbara; Viel, Matteo; Borgani, Stefano

2014-10-01

We discuss the reliability of neutrino mass constraints, either active or sterile, from the combination of different low redshift Universe probes with measurements of CMB anisotropies. In our analyses we consider WMAP 9-year or Planck Cosmic Microwave Background (CMB) data in combination with Baryonic Acoustic Oscillations (BAO) measurements from BOSS DR11, galaxy shear measurements from CFHTLenS, SDSS Ly α forest constraints and galaxy cluster mass function from Chandra observations. At odds with recent similar studies, to avoid model dependence of the constraints we perform a full likelihood analysis for all the datasets employed. As for the cluster data analysis we rely on to the most recent calibration of massive neutrino effects in the halo mass function and we explore the impact of the uncertainty in the mass bias and re-calibration of the halo mass function due to baryonic feedback processes on cosmological parameters. We find that none of the low redshift probes alone provide evidence for massive neutrino in combination with CMB measurements, while a larger than 2σ detection of non zero neutrino mass, either active or sterile, is achieved combining cluster or shear data with CMB and BAO measurements. Yet, the significance of the detection exceeds 3σ if we combine all four datasets. For a three active neutrino scenario, from the joint analysis of CMB, BAO, shear and cluster data including the uncertainty in the mass bias we obtain ∑ mν =0.29+0.18-0.21 eV and ∑ mν =0.22+0.17-0.18 eV 95%CL) using WMAP9 or Planck as CMB dataset, respectively. The preference for massive neutrino is even larger in the sterile neutrino scenario, for which we get mseff=0.44+0.28-0.26 eV and Δ Neff=0.78+0.60-0.59 95%CL) from the joint analysis of Planck, BAO, shear and cluster datasets. For this data combination the vanilla ΛCDM model is rejected at more than 3σ and a sterile neutrino mass as motivated by accelerator anomaly is within the 2σ errors. Conversely, the Ly α data favour vanishing neutrino masses and from the data combination Planck+BAO+Ly α we get the tight upper limits ∑ mν <0.14 eV and mseff<0.22 eV—Δ Neff<1.11 95%CL) for the active and sterile neutrino model, respectively. Finally, results from the full data combination reflect the tension between the σ8 constraints obtained from cluster and shear data and that inferred from Ly α forest measurements; in the active neutrino scenario for both CMB datasets employed, the full data combination yields only an upper limits on ∑ mν, while assuming an extra sterile neutrino we still get preference for non-vanishing mass, mseff=0.26+0.22-0.24 eV, and dark contribution to the radiation content, Δ Neff=0.82±0.55.

Data reuse and the open data citation advantage

PubMed Central

Vision, Todd J.

2013-01-01

Background. Attribution to the original contributor upon reuse of published data is important both as a reward for data creators and to document the provenance of research findings. Previous studies have found that papers with publicly available datasets receive a higher number of citations than similar studies without available data. However, few previous analyses have had the statistical power to control for the many variables known to predict citation rate, which has led to uncertain estimates of the “citation benefit”. Furthermore, little is known about patterns in data reuse over time and across datasets. Method and Results. Here, we look at citation rates while controlling for many known citation predictors and investigate the variability of data reuse. In a multivariate regression on 10,555 studies that created gene expression microarray data, we found that studies that made data available in a public repository received 9% (95% confidence interval: 5% to 13%) more citations than similar studies for which the data was not made available. Date of publication, journal impact factor, open access status, number of authors, first and last author publication history, corresponding author country, institution citation history, and study topic were included as covariates. The citation benefit varied with date of dataset deposition: a citation benefit was most clear for papers published in 2004 and 2005, at about 30%. Authors published most papers using their own datasets within two years of their first publication on the dataset, whereas data reuse papers published by third-party investigators continued to accumulate for at least six years. To study patterns of data reuse directly, we compiled 9,724 instances of third party data reuse via mention of GEO or ArrayExpress accession numbers in the full text of papers. The level of third-party data use was high: for 100 datasets deposited in year 0, we estimated that 40 papers in PubMed reused a dataset by year 2, 100 by year 4, and more than 150 data reuse papers had been published by year 5. Data reuse was distributed across a broad base of datasets: a very conservative estimate found that 20% of the datasets deposited between 2003 and 2007 had been reused at least once by third parties. Conclusion. After accounting for other factors affecting citation rate, we find a robust citation benefit from open data, although a smaller one than previously reported. We conclude there is a direct effect of third-party data reuse that persists for years beyond the time when researchers have published most of the papers reusing their own data. Other factors that may also contribute to the citation benefit are considered. We further conclude that, at least for gene expression microarray data, a substantial fraction of archived datasets are reused, and that the intensity of dataset reuse has been steadily increasing since 2003. PMID:24109559

Deep learning based state recognition of substation switches

NASA Astrophysics Data System (ADS)

Wang, Jin

2018-06-01

Different from the traditional method which recognize the state of substation switches based on the running rules of electrical power system, this work proposes a novel convolutional neuron network-based state recognition approach of substation switches. Inspired by the theory of transfer learning, we first establish a convolutional neuron network model trained on the large-scale image set ILSVRC2012, then the restricted Boltzmann machine is employed to replace the full connected layer of the convolutional neuron network and trained on our small image dataset of 110kV substation switches to get a stronger model. Experiments conducted on our image dataset of 110kV substation switches show that, the proposed approach can be applicable to the substation to reduce the running cost and implement the real unattended operation.

Cloud computing for detecting high-order genome-wide epistatic interaction via dynamic clustering.

PubMed

Guo, Xuan; Meng, Yu; Yu, Ning; Pan, Yi

2014-04-10

Taking the advantage of high-throughput single nucleotide polymorphism (SNP) genotyping technology, large genome-wide association studies (GWASs) have been considered to hold promise for unravelling complex relationships between genotype and phenotype. At present, traditional single-locus-based methods are insufficient to detect interactions consisting of multiple-locus, which are broadly existing in complex traits. In addition, statistic tests for high order epistatic interactions with more than 2 SNPs propose computational and analytical challenges because the computation increases exponentially as the cardinality of SNPs combinations gets larger. In this paper, we provide a simple, fast and powerful method using dynamic clustering and cloud computing to detect genome-wide multi-locus epistatic interactions. We have constructed systematic experiments to compare powers performance against some recently proposed algorithms, including TEAM, SNPRuler, EDCF and BOOST. Furthermore, we have applied our method on two real GWAS datasets, Age-related macular degeneration (AMD) and Rheumatoid arthritis (RA) datasets, where we find some novel potential disease-related genetic factors which are not shown up in detections of 2-loci epistatic interactions. Experimental results on simulated data demonstrate that our method is more powerful than some recently proposed methods on both two- and three-locus disease models. Our method has discovered many novel high-order associations that are significantly enriched in cases from two real GWAS datasets. Moreover, the running time of the cloud implementation for our method on AMD dataset and RA dataset are roughly 2 hours and 50 hours on a cluster with forty small virtual machines for detecting two-locus interactions, respectively. Therefore, we believe that our method is suitable and effective for the full-scale analysis of multiple-locus epistatic interactions in GWAS.

Spatially Explicit Models to Investigate Geographic Patterns in the Distribution of Forensic STRs: Application to the North-Eastern Mediterranean

PubMed Central

Messina, Francesco; Finocchio, Andrea; Akar, Nejat; Loutradis, Aphrodite; Michalodimitrakis, Emmanuel I.; Brdicka, Radim; Jodice, Carla

2016-01-01

Human forensic STRs used for individual identification have been reported to have little power for inter-population analyses. Several methods have been developed which incorporate information on the spatial distribution of individuals to arrive at a description of the arrangement of diversity. We genotyped at 16 forensic STRs a large population sample obtained from many locations in Italy, Greece and Turkey, i.e. three countries crucial to the understanding of discontinuities at the European/Asian junction and the genetic legacy of ancient migrations, but seldom represented together in previous studies. Using spatial PCA on the full dataset, we detected patterns of population affinities in the area. Additionally, we devised objective criteria to reduce the overall complexity into reduced datasets. Independent spatially explicit methods applied to these latter datasets converged in showing that the extraction of information on long- to medium-range geographical trends and structuring from the overall diversity is possible. All analyses returned the picture of a background clinal variation, with regional discontinuities captured by each of the reduced datasets. Several aspects of our results are confirmed on external STR datasets and replicate those of genome-wide SNP typings. High levels of gene flow were inferred within the main continental areas by coalescent simulations. These results are promising from a microevolutionary perspective, in view of the fast pace at which forensic data are being accumulated for many locales. It is foreseeable that this will allow the exploitation of an invaluable genotypic resource, assembled for other (forensic) purposes, to clarify important aspects in the formation of local gene pools. PMID:27898725

Cloud computing for detecting high-order genome-wide epistatic interaction via dynamic clustering

PubMed Central

2014-01-01

Backgroud Taking the advan tage of high-throughput single nucleotide polymorphism (SNP) genotyping technology, large genome-wide association studies (GWASs) have been considered to hold promise for unravelling complex relationships between genotype and phenotype. At present, traditional single-locus-based methods are insufficient to detect interactions consisting of multiple-locus, which are broadly existing in complex traits. In addition, statistic tests for high order epistatic interactions with more than 2 SNPs propose computational and analytical challenges because the computation increases exponentially as the cardinality of SNPs combinations gets larger. Results In this paper, we provide a simple, fast and powerful method using dynamic clustering and cloud computing to detect genome-wide multi-locus epistatic interactions. We have constructed systematic experiments to compare powers performance against some recently proposed algorithms, including TEAM, SNPRuler, EDCF and BOOST. Furthermore, we have applied our method on two real GWAS datasets, Age-related macular degeneration (AMD) and Rheumatoid arthritis (RA) datasets, where we find some novel potential disease-related genetic factors which are not shown up in detections of 2-loci epistatic interactions. Conclusions Experimental results on simulated data demonstrate that our method is more powerful than some recently proposed methods on both two- and three-locus disease models. Our method has discovered many novel high-order associations that are significantly enriched in cases from two real GWAS datasets. Moreover, the running time of the cloud implementation for our method on AMD dataset and RA dataset are roughly 2 hours and 50 hours on a cluster with forty small virtual machines for detecting two-locus interactions, respectively. Therefore, we believe that our method is suitable and effective for the full-scale analysis of multiple-locus epistatic interactions in GWAS. PMID:24717145

Toward robust estimation of the components of forest population change: simulation results

Treesearch

Francis A. Roesch

2014-01-01

This report presents the full simulation results of the work described in Roesch (2014), in which multiple levels of simulation were used to test the robustness of estimators for the components of forest change. In that study, a variety of spatial-temporal populations were created based on, but more variable than, an actual forest monitoring dataset, and then those...

Introducing a Model for Optimal Design of Sequential Objective Structured Clinical Examinations

ERIC Educational Resources Information Center

Mortaz Hejri, Sara; Yazdani, Kamran; Labaf, Ali; Norcini, John J.; Jalili, Mohammad

2016-01-01

In a sequential OSCE which has been suggested to reduce testing costs, candidates take a short screening test and who fail the test, are asked to take the full OSCE. In order to introduce an effective and accurate sequential design, we developed a model for designing and evaluating screening OSCEs. Based on two datasets from a 10-station…

Validation of the DIFFAL, HPAC and HotSpot Dispersion Models Using the Full-Scale Radiological Dispersal Device (FSRDD) Field Trials Witness Plate Deposition Dataset.

PubMed

Purves, Murray; Parkes, David

2016-05-01

Three atmospheric dispersion models--DIFFAL, HPAC, and HotSpot--of differing complexities have been validated against the witness plate deposition dataset taken during the Full-Scale Radiological Dispersal Device (FSRDD) Field Trials. The small-scale nature of these trials in comparison to many other historical radiological dispersion trials provides a unique opportunity to evaluate the near-field performance of the models considered. This paper performs validation of these models using two graphical methods of comparison: deposition contour plots and hotline profile graphs. All of the models tested are assessed to perform well, especially considering that previous model developments and validations have been focused on larger-scale scenarios. Of the models, HPAC generally produced the most accurate results, especially at locations within ∼100 m of GZ. Features present within the observed data, such as hot spots, were not well modeled by any of the codes considered. Additionally, it was found that an increase in the complexity of the meteorological data input to the models did not necessarily lead to an improvement in model accuracy; this is potentially due to the small-scale nature of the trials.

Phylotranscriptomic consolidation of the jawed vertebrate timetree.

PubMed

Irisarri, Iker; Baurain, Denis; Brinkmann, Henner; Delsuc, Frédéric; Sire, Jean-Yves; Kupfer, Alexander; Petersen, Jörn; Jarek, Michael; Meyer, Axel; Vences, Miguel; Philippe, Hervé

2017-09-01

Phylogenomics is extremely powerful but introduces new challenges as no agreement exists on "standards" for data selection, curation and tree inference. We use jawed vertebrates (Gnathostomata) as model to address these issues. Despite considerable efforts in resolving their evolutionary history and macroevolution, few studies have included a full phylogenetic diversity of gnathostomes and some relationships remain controversial. We tested a novel bioinformatic pipeline to assemble large and accurate phylogenomic datasets from RNA sequencing and find this phylotranscriptomic approach successful and highly cost-effective. Increased sequencing effort up to ca. 10Gbp allows recovering more genes, but shallower sequencing (1.5Gbp) is sufficient to obtain thousands of full-length orthologous transcripts. We reconstruct a robust and strongly supported timetree of jawed vertebrates using 7,189 nuclear genes from 100 taxa, including 23 new transcriptomes from previously unsampled key species. Gene jackknifing of genomic data corroborates the robustness of our tree and allows calculating genome-wide divergence times by overcoming gene sampling bias. Mitochondrial genomes prove insufficient to resolve the deepest relationships because of limited signal and among-lineage rate heterogeneity. Our analyses emphasize the importance of large curated nuclear datasets to increase the accuracy of phylogenomics and provide a reference framework for the evolutionary history of jawed vertebrates.

Iterative random vs. Kennard-Stone sampling for IR spectrum-based classification task using PLS2-DA

NASA Astrophysics Data System (ADS)

Lee, Loong Chuen; Liong, Choong-Yeun; Jemain, Abdul Aziz

2018-04-01

External testing (ET) is preferred over auto-prediction (AP) or k-fold-cross-validation in estimating more realistic predictive ability of a statistical model. With IR spectra, Kennard-stone (KS) sampling algorithm is often used to split the data into training and test sets, i.e. respectively for model construction and for model testing. On the other hand, iterative random sampling (IRS) has not been the favored choice though it is theoretically more likely to produce reliable estimation. The aim of this preliminary work is to compare performances of KS and IRS in sampling a representative training set from an attenuated total reflectance - Fourier transform infrared spectral dataset (of four varieties of blue gel pen inks) for PLS2-DA modeling. The `best' performance achievable from the dataset is estimated with AP on the full dataset (APF, error). Both IRS (n = 200) and KS were used to split the dataset in the ratio of 7:3. The classic decision rule (i.e. maximum value-based) is employed for new sample prediction via partial least squares - discriminant analysis (PLS2-DA). Error rate of each model was estimated repeatedly via: (a) AP on full data (APF, error); (b) AP on training set (APS, error); and (c) ET on the respective test set (ETS, error). A good PLS2-DA model is expected to produce APS, error and EVS, error that is similar to the APF, error. Bearing that in mind, the similarities between (a) APS, error vs. APF, error; (b) ETS, error vs. APF, error and; (c) APS, error vs. ETS, error were evaluated using correlation tests (i.e. Pearson and Spearman's rank test), using series of PLS2-DA models computed from KS-set and IRS-set, respectively. Overall, models constructed from IRS-set exhibits more similarities between the internal and external error rates than the respective KS-set, i.e. less risk of overfitting. In conclusion, IRS is more reliable than KS in sampling representative training set.

Reconstructing the outburst history of Eta Carinae from WFPC2 proper motions

NASA Astrophysics Data System (ADS)

Smith, Nathan

2011-10-01

The HST archive contains several epochs of WFPC2 images of the nebula around Eta Carinae taken over a 15-year timespan, although only the earliest few years of data have been analyzed and published. The fact that all these images were taken with the same instrument, with the same pixel sampling and field distortion, makes them an invaluable resource for accurately measuring the expanding ejecta. So far, analysis of a subset of the data {with only a few year baseline} has shown that Eta Car's nebula was ejected around the time of the Great Eruption in the 1840s, but the full 15-yr dataset has much greater untapped potential. Historical data show multiple peaks in the light curve during the 1840s eruption, possibly the result of violent stellar collisions in the eccentric binary system. Proper motions with the full 15-yr dataset will definitively show if one of these is associated with the main mass ejection. Older material outside the main bipolar nebula traces previous major outbursts of the star with no recorded historical observations. We propose an ambitious reduction and analysis of the complete WFPC2 imaging dataset of Eta Car. These data can reconstruct its violent mass-loss history over the past several thousand years. This will constrain the behavior and timescale of eruptive mass loss in pre-SN evolution. The existence of several epochs over a long timespan will date older parts of the nebula that have not yet been measured, and can even measure the deceleration of the ejecta for the first time, essential for understanding their shaping and shock excitation during the nebula's continuing hydrodynamic evolution.

Benchmarking the mesoscale variability in global ocean eddy-permitting numerical systems

NASA Astrophysics Data System (ADS)

Cipollone, Andrea; Masina, Simona; Storto, Andrea; Iovino, Doroteaciro

2017-10-01

The role of data assimilation procedures on representing ocean mesoscale variability is assessed by applying eddy statistics to a state-of-the-art global ocean reanalysis (C-GLORS), a free global ocean simulation (performed with the NEMO system) and an observation-based dataset (ARMOR3D) used as an independent benchmark. Numerical results are computed on a 1/4 ∘ horizontal grid (ORCA025) and share the same resolution with ARMOR3D dataset. This "eddy-permitting" resolution is sufficient to allow ocean eddies to form. Further to assessing the eddy statistics from three different datasets, a global three-dimensional eddy detection system is implemented in order to bypass the need of regional-dependent definition of thresholds, typical of commonly adopted eddy detection algorithms. It thus provides full three-dimensional eddy statistics segmenting vertical profiles from local rotational velocities. This criterion is crucial for discerning real eddies from transient surface noise that inevitably affects any two-dimensional algorithm. Data assimilation enhances and corrects mesoscale variability on a wide range of features that cannot be well reproduced otherwise. The free simulation fairly reproduces eddies emerging from western boundary currents and deep baroclinic instabilities, while underestimates shallower vortexes that populate the full basin. The ocean reanalysis recovers most of the missing turbulence, shown by satellite products , that is not generated by the model itself and consistently projects surface variability deep into the water column. The comparison with the statistically reconstructed vertical profiles from ARMOR3D show that ocean data assimilation is able to embed variability into the model dynamics, constraining eddies with in situ and altimetry observation and generating them consistently with local environment.

Defining upper gastrointestinal bleeding from linked primary and secondary care data and the effect on occurrence and 28 day mortality.

PubMed

Crooks, Colin John; Card, Timothy Richard; West, Joe

2012-11-13

Primary care records from the UK have frequently been used to identify episodes of upper gastrointestinal bleeding in studies of drug toxicity because of their comprehensive population coverage and longitudinal recording of prescriptions and diagnoses. Recent linkage within England of primary and secondary care data has augmented this data but the timing and coding of concurrent events, and how the definition of events in linked data effects occurrence and 28 day mortality is not known. We used the recently linked English Hospital Episodes Statistics and General Practice Research Database, 1997-2010, to define events by; a specific upper gastrointestinal bleed code in either dataset, a specific bleed code in both datasets, or a less specific but plausible code from the linked dataset. This approach resulted in 81% of secondary care defined bleeds having a corresponding plausible code within 2 months in primary care. However only 62% of primary care defined bleeds had a corresponding plausible HES admission within 2 months. The more restrictive and specific case definitions excluded severe events and almost halved the 28 day case fatality when compared to broader and more sensitive definitions. Restrictive definitions of gastrointestinal bleeding in linked datasets fail to capture the full heterogeneity in coding possible following complex clinical events. Conversely too broad a definition in primary care introduces events not severe enough to warrant hospital admission. Ignoring these issues may unwittingly introduce selection bias into a study's results.

Optimization of Scan Parameters to Reduce Acquisition Time for Diffusion Kurtosis Imaging at 1.5T.

PubMed

Yokosawa, Suguru; Sasaki, Makoto; Bito, Yoshitaka; Ito, Kenji; Yamashita, Fumio; Goodwin, Jonathan; Higuchi, Satomi; Kudo, Kohsuke

2016-01-01

To shorten acquisition of diffusion kurtosis imaging (DKI) in 1.5-tesla magnetic resonance (MR) imaging, we investigated the effects of the number of b-values, diffusion direction, and number of signal averages (NSA) on the accuracy of DKI metrics. We obtained 2 image datasets with 30 gradient directions, 6 b-values up to 2500 s/mm(2), and 2 signal averages from 5 healthy volunteers and generated DKI metrics, i.e., mean, axial, and radial kurtosis (MK, K∥, and K⊥) maps, from various combinations of the datasets. These maps were estimated by using the intraclass correlation coefficient (ICC) with those from the full datasets. The MK and K⊥ maps generated from the datasets including only the b-value of 2500 s/mm(2) showed excellent agreement (ICC, 0.96 to 0.99). Under the same acquisition time and diffusion directions, agreement was better of MK, K∥, and K⊥ maps obtained with 3 b-values (0, 1000, and 2500 s/mm(2)) and 4 signal averages than maps obtained with any other combination of numbers of b-value and varied NSA. Good agreement (ICC > 0.6) required at least 20 diffusion directions in all the metrics. MK and K⊥ maps with ICC greater than 0.95 can be obtained at 1.5T within 10 min (b-value = 0, 1000, and 2500 s/mm(2); 20 diffusion directions; 4 signal averages; slice thickness, 6 mm with no interslice gap; number of slices, 12).

Rapid, semi-automatic fracture and contact mapping for point clouds, images and geophysical data

NASA Astrophysics Data System (ADS)

Thiele, Samuel T.; Grose, Lachlan; Samsu, Anindita; Micklethwaite, Steven; Vollgger, Stefan A.; Cruden, Alexander R.

2017-12-01

The advent of large digital datasets from unmanned aerial vehicle (UAV) and satellite platforms now challenges our ability to extract information across multiple scales in a timely manner, often meaning that the full value of the data is not realised. Here we adapt a least-cost-path solver and specially tailored cost functions to rapidly interpolate structural features between manually defined control points in point cloud and raster datasets. We implement the method in the geographic information system QGIS and the point cloud and mesh processing software CloudCompare. Using these implementations, the method can be applied to a variety of three-dimensional (3-D) and two-dimensional (2-D) datasets, including high-resolution aerial imagery, digital outcrop models, digital elevation models (DEMs) and geophysical grids. We demonstrate the algorithm with four diverse applications in which we extract (1) joint and contact patterns in high-resolution orthophotographs, (2) fracture patterns in a dense 3-D point cloud, (3) earthquake surface ruptures of the Greendale Fault associated with the Mw7.1 Darfield earthquake (New Zealand) from high-resolution light detection and ranging (lidar) data, and (4) oceanic fracture zones from bathymetric data of the North Atlantic. The approach improves the consistency of the interpretation process while retaining expert guidance and achieves significant improvements (35-65 %) in digitisation time compared to traditional methods. Furthermore, it opens up new possibilities for data synthesis and can quantify the agreement between datasets and an interpretation.

Multibeam 3D Underwater SLAM with Probabilistic Registration.

PubMed

Palomer, Albert; Ridao, Pere; Ribas, David

2016-04-20

This paper describes a pose-based underwater 3D Simultaneous Localization and Mapping (SLAM) using a multibeam echosounder to produce high consistency underwater maps. The proposed algorithm compounds swath profiles of the seafloor with dead reckoning localization to build surface patches (i.e., point clouds). An Iterative Closest Point (ICP) with a probabilistic implementation is then used to register the point clouds, taking into account their uncertainties. The registration process is divided in two steps: (1) point-to-point association for coarse registration and (2) point-to-plane association for fine registration. The point clouds of the surfaces to be registered are sub-sampled in order to decrease both the computation time and also the potential of falling into local minima during the registration. In addition, a heuristic is used to decrease the complexity of the association step of the ICP from O(n2) to O(n) . The performance of the SLAM framework is tested using two real world datasets: First, a 2.5D bathymetric dataset obtained with the usual down-looking multibeam sonar configuration, and second, a full 3D underwater dataset acquired with a multibeam sonar mounted on a pan and tilt unit.

PharmacoGx: an R package for analysis of large pharmacogenomic datasets.

PubMed

Smirnov, Petr; Safikhani, Zhaleh; El-Hachem, Nehme; Wang, Dong; She, Adrian; Olsen, Catharina; Freeman, Mark; Selby, Heather; Gendoo, Deena M A; Grossmann, Patrick; Beck, Andrew H; Aerts, Hugo J W L; Lupien, Mathieu; Goldenberg, Anna; Haibe-Kains, Benjamin

2016-04-15

Pharmacogenomics holds great promise for the development of biomarkers of drug response and the design of new therapeutic options, which are key challenges in precision medicine. However, such data are scattered and lack standards for efficient access and analysis, consequently preventing the realization of the full potential of pharmacogenomics. To address these issues, we implemented PharmacoGx, an easy-to-use, open source package for integrative analysis of multiple pharmacogenomic datasets. We demonstrate the utility of our package in comparing large drug sensitivity datasets, such as the Genomics of Drug Sensitivity in Cancer and the Cancer Cell Line Encyclopedia. Moreover, we show how to use our package to easily perform Connectivity Map analysis. With increasing availability of drug-related data, our package will open new avenues of research for meta-analysis of pharmacogenomic data. PharmacoGx is implemented in R and can be easily installed on any system. The package is available from CRAN and its source code is available from GitHub. bhaibeka@uhnresearch.ca or benjamin.haibe.kains@utoronto.ca Supplementary data are available at Bioinformatics online. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

The swiss army knife of job submission tools: grid-control

NASA Astrophysics Data System (ADS)

Stober, F.; Fischer, M.; Schleper, P.; Stadie, H.; Garbers, C.; Lange, J.; Kovalchuk, N.

2017-10-01

grid-control is a lightweight and highly portable open source submission tool that supports all common workflows in high energy physics (HEP). It has been used by a sizeable number of HEP analyses to process tasks that sometimes consist of up to 100k jobs. grid-control is built around a powerful plugin and configuration system, that allows users to easily specify all aspects of the desired workflow. Job submission to a wide range of local or remote batch systems or grid middleware is supported. Tasks can be conveniently specified through the parameter space that will be processed, which can consist of any number of variables and data sources with complex dependencies on each other. Dataset information is processed through a configurable pipeline of dataset filters, partition plugins and partition filters. The partition plugins can take the number of files, size of the work units, metadata or combinations thereof into account. All changes to the input datasets or variables are propagated through the processing pipeline and can transparently trigger adjustments to the parameter space and the job submission. While the core functionality is completely experiment independent, full integration with the CMS computing environment is provided by a small set of plugins.

A Time-Series Water Level Forecasting Model Based on Imputation and Variable Selection Method.

PubMed

Yang, Jun-He; Cheng, Ching-Hsue; Chan, Chia-Pan

2017-01-01

Reservoirs are important for households and impact the national economy. This paper proposed a time-series forecasting model based on estimating a missing value followed by variable selection to forecast the reservoir's water level. This study collected data from the Taiwan Shimen Reservoir as well as daily atmospheric data from 2008 to 2015. The two datasets are concatenated into an integrated dataset based on ordering of the data as a research dataset. The proposed time-series forecasting model summarily has three foci. First, this study uses five imputation methods to directly delete the missing value. Second, we identified the key variable via factor analysis and then deleted the unimportant variables sequentially via the variable selection method. Finally, the proposed model uses a Random Forest to build the forecasting model of the reservoir's water level. This was done to compare with the listing method under the forecasting error. These experimental results indicate that the Random Forest forecasting model when applied to variable selection with full variables has better forecasting performance than the listing model. In addition, this experiment shows that the proposed variable selection can help determine five forecast methods used here to improve the forecasting capability.

A comparison of database systems for XML-type data.

PubMed

Risse, Judith E; Leunissen, Jack A M

2010-01-01

In the field of bioinformatics interchangeable data formats based on XML are widely used. XML-type data is also at the core of most web services. With the increasing amount of data stored in XML comes the need for storing and accessing the data. In this paper we analyse the suitability of different database systems for storing and querying large datasets in general and Medline in particular. All reviewed database systems perform well when tested with small to medium sized datasets, however when the full Medline dataset is queried a large variation in query times is observed. There is not one system that is vastly superior to the others in this comparison and, depending on the database size and the query requirements, different systems are most suitable. The best all-round solution is the Oracle 11~g database system using the new binary storage option. Alias-i's Lingpipe is a more lightweight, customizable and sufficiently fast solution. It does however require more initial configuration steps. For data with a changing XML structure Sedna and BaseX as native XML database systems or MySQL with an XML-type column are suitable.

Leveraging genome-wide datasets to quantify the functional role of the anti-Shine-Dalgarno sequence in regulating translation efficiency.

PubMed

Hockenberry, Adam J; Pah, Adam R; Jewett, Michael C; Amaral, Luís A N

2017-01-01

Studies dating back to the 1970s established that sequence complementarity between the anti-Shine-Dalgarno (aSD) sequence on prokaryotic ribosomes and the 5' untranslated region of mRNAs helps to facilitate translation initiation. The optimal location of aSD sequence binding relative to the start codon, the full extents of the aSD sequence and the functional form of the relationship between aSD sequence complementarity and translation efficiency have not been fully resolved. Here, we investigate these relationships by leveraging the sequence diversity of endogenous genes and recently available genome-wide estimates of translation efficiency. We show that-after accounting for predicted mRNA structure-aSD sequence complementarity increases the translation of endogenous mRNAs by roughly 50%. Further, we observe that this relationship is nonlinear, with translation efficiency maximized for mRNAs with intermediate levels of aSD sequence complementarity. The mechanistic insights that we observe are highly robust: we find nearly identical results in multiple datasets spanning three distantly related bacteria. Further, we verify our main conclusions by re-analysing a controlled experimental dataset. © 2017 The Authors.

Multi-view L2-SVM and its multi-view core vector machine.

PubMed

Huang, Chengquan; Chung, Fu-lai; Wang, Shitong

2016-03-01

In this paper, a novel L2-SVM based classifier Multi-view L2-SVM is proposed to address multi-view classification tasks. The proposed Multi-view L2-SVM classifier does not have any bias in its objective function and hence has the flexibility like μ-SVC in the sense that the number of the yielded support vectors can be controlled by a pre-specified parameter. The proposed Multi-view L2-SVM classifier can make full use of the coherence and the difference of different views through imposing the consensus among multiple views to improve the overall classification performance. Besides, based on the generalized core vector machine GCVM, the proposed Multi-view L2-SVM classifier is extended into its GCVM version MvCVM which can realize its fast training on large scale multi-view datasets, with its asymptotic linear time complexity with the sample size and its space complexity independent of the sample size. Our experimental results demonstrated the effectiveness of the proposed Multi-view L2-SVM classifier for small scale multi-view datasets and the proposed MvCVM classifier for large scale multi-view datasets. Copyright © 2015 Elsevier Ltd. All rights reserved.

ChemMaps: Towards an approach for visualizing the chemical space based on adaptive satellite compounds

PubMed Central

Naveja, J. Jesús; Medina-Franco, José L.

2017-01-01

We present a novel approach called ChemMaps for visualizing chemical space based on the similarity matrix of compound datasets generated with molecular fingerprints’ similarity. The method uses a ‘satellites’ approach, where satellites are, in principle, molecules whose similarity to the rest of the molecules in the database provides sufficient information for generating a visualization of the chemical space. Such an approach could help make chemical space visualizations more efficient. We hereby describe a proof-of-principle application of the method to various databases that have different diversity measures. Unsurprisingly, we found the method works better with databases that have low 2D diversity. 3D diversity played a secondary role, although it seems to be more relevant as 2D diversity increases. For less diverse datasets, taking as few as 25% satellites seems to be sufficient for a fair depiction of the chemical space. We propose to iteratively increase the satellites number by a factor of 5% relative to the whole database, and stop when the new and the prior chemical space correlate highly. This Research Note represents a first exploratory step, prior to the full application of this method for several datasets. PMID:28794856

ChemMaps: Towards an approach for visualizing the chemical space based on adaptive satellite compounds.

PubMed

Naveja, J Jesús; Medina-Franco, José L

2017-01-01

We present a novel approach called ChemMaps for visualizing chemical space based on the similarity matrix of compound datasets generated with molecular fingerprints' similarity. The method uses a 'satellites' approach, where satellites are, in principle, molecules whose similarity to the rest of the molecules in the database provides sufficient information for generating a visualization of the chemical space. Such an approach could help make chemical space visualizations more efficient. We hereby describe a proof-of-principle application of the method to various databases that have different diversity measures. Unsurprisingly, we found the method works better with databases that have low 2D diversity. 3D diversity played a secondary role, although it seems to be more relevant as 2D diversity increases. For less diverse datasets, taking as few as 25% satellites seems to be sufficient for a fair depiction of the chemical space. We propose to iteratively increase the satellites number by a factor of 5% relative to the whole database, and stop when the new and the prior chemical space correlate highly. This Research Note represents a first exploratory step, prior to the full application of this method for several datasets.

An Open Source Software and Web-GIS Based Platform for Airborne SAR Remote Sensing Data Management, Distribution and Sharing

NASA Astrophysics Data System (ADS)

Changyong, Dou; Huadong, Guo; Chunming, Han; Ming, Liu

2014-03-01

With more and more Earth observation data available to the community, how to manage and sharing these valuable remote sensing datasets is becoming an urgent issue to be solved. The web based Geographical Information Systems (GIS) technology provides a convenient way for the users in different locations to share and make use of the same dataset. In order to efficiently use the airborne Synthetic Aperture Radar (SAR) remote sensing data acquired in the Airborne Remote Sensing Center of the Institute of Remote Sensing and Digital Earth (RADI), Chinese Academy of Sciences (CAS), a Web-GIS based platform for airborne SAR data management, distribution and sharing was designed and developed. The major features of the system include map based navigation search interface, full resolution imagery shown overlaid the map, and all the software adopted in the platform are Open Source Software (OSS). The functions of the platform include browsing the imagery on the map navigation based interface, ordering and downloading data online, image dataset and user management, etc. At present, the system is under testing in RADI and will come to regular operation soon.

Identification of Predictive Cis-Regulatory Elements Using a Discriminative Objective Function and a Dynamic Search Space

PubMed Central

Karnik, Rahul; Beer, Michael A.

2015-01-01

The generation of genomic binding or accessibility data from massively parallel sequencing technologies such as ChIP-seq and DNase-seq continues to accelerate. Yet state-of-the-art computational approaches for the identification of DNA binding motifs often yield motifs of weak predictive power. Here we present a novel computational algorithm called MotifSpec, designed to find predictive motifs, in contrast to over-represented sequence elements. The key distinguishing feature of this algorithm is that it uses a dynamic search space and a learned threshold to find discriminative motifs in combination with the modeling of motifs using a full PWM (position weight matrix) rather than k-mer words or regular expressions. We demonstrate that our approach finds motifs corresponding to known binding specificities in several mammalian ChIP-seq datasets, and that our PWMs classify the ChIP-seq signals with accuracy comparable to, or marginally better than motifs from the best existing algorithms. In other datasets, our algorithm identifies novel motifs where other methods fail. Finally, we apply this algorithm to detect motifs from expression datasets in C. elegans using a dynamic expression similarity metric rather than fixed expression clusters, and find novel predictive motifs. PMID:26465884

Identification of Predictive Cis-Regulatory Elements Using a Discriminative Objective Function and a Dynamic Search Space.

PubMed

Karnik, Rahul; Beer, Michael A

2015-01-01

The generation of genomic binding or accessibility data from massively parallel sequencing technologies such as ChIP-seq and DNase-seq continues to accelerate. Yet state-of-the-art computational approaches for the identification of DNA binding motifs often yield motifs of weak predictive power. Here we present a novel computational algorithm called MotifSpec, designed to find predictive motifs, in contrast to over-represented sequence elements. The key distinguishing feature of this algorithm is that it uses a dynamic search space and a learned threshold to find discriminative motifs in combination with the modeling of motifs using a full PWM (position weight matrix) rather than k-mer words or regular expressions. We demonstrate that our approach finds motifs corresponding to known binding specificities in several mammalian ChIP-seq datasets, and that our PWMs classify the ChIP-seq signals with accuracy comparable to, or marginally better than motifs from the best existing algorithms. In other datasets, our algorithm identifies novel motifs where other methods fail. Finally, we apply this algorithm to detect motifs from expression datasets in C. elegans using a dynamic expression similarity metric rather than fixed expression clusters, and find novel predictive motifs.

A Bootstrap Metropolis-Hastings Algorithm for Bayesian Analysis of Big Data.

PubMed

Liang, Faming; Kim, Jinsu; Song, Qifan

2016-01-01

Markov chain Monte Carlo (MCMC) methods have proven to be a very powerful tool for analyzing data of complex structures. However, their computer-intensive nature, which typically require a large number of iterations and a complete scan of the full dataset for each iteration, precludes their use for big data analysis. In this paper, we propose the so-called bootstrap Metropolis-Hastings (BMH) algorithm, which provides a general framework for how to tame powerful MCMC methods to be used for big data analysis; that is to replace the full data log-likelihood by a Monte Carlo average of the log-likelihoods that are calculated in parallel from multiple bootstrap samples. The BMH algorithm possesses an embarrassingly parallel structure and avoids repeated scans of the full dataset in iterations, and is thus feasible for big data problems. Compared to the popular divide-and-combine method, BMH can be generally more efficient as it can asymptotically integrate the whole data information into a single simulation run. The BMH algorithm is very flexible. Like the Metropolis-Hastings algorithm, it can serve as a basic building block for developing advanced MCMC algorithms that are feasible for big data problems. This is illustrated in the paper by the tempering BMH algorithm, which can be viewed as a combination of parallel tempering and the BMH algorithm. BMH can also be used for model selection and optimization by combining with reversible jump MCMC and simulated annealing, respectively.

A Bootstrap Metropolis–Hastings Algorithm for Bayesian Analysis of Big Data

PubMed Central

Kim, Jinsu; Song, Qifan

2016-01-01

Markov chain Monte Carlo (MCMC) methods have proven to be a very powerful tool for analyzing data of complex structures. However, their computer-intensive nature, which typically require a large number of iterations and a complete scan of the full dataset for each iteration, precludes their use for big data analysis. In this paper, we propose the so-called bootstrap Metropolis-Hastings (BMH) algorithm, which provides a general framework for how to tame powerful MCMC methods to be used for big data analysis; that is to replace the full data log-likelihood by a Monte Carlo average of the log-likelihoods that are calculated in parallel from multiple bootstrap samples. The BMH algorithm possesses an embarrassingly parallel structure and avoids repeated scans of the full dataset in iterations, and is thus feasible for big data problems. Compared to the popular divide-and-combine method, BMH can be generally more efficient as it can asymptotically integrate the whole data information into a single simulation run. The BMH algorithm is very flexible. Like the Metropolis-Hastings algorithm, it can serve as a basic building block for developing advanced MCMC algorithms that are feasible for big data problems. This is illustrated in the paper by the tempering BMH algorithm, which can be viewed as a combination of parallel tempering and the BMH algorithm. BMH can also be used for model selection and optimization by combining with reversible jump MCMC and simulated annealing, respectively. PMID:29033469

Measurement of CP Violation in B Anti-B Mixing on the Recoil of Partially Reconstructed Anti-B0 to D* L- Anti-Nu/L Using Kaon Tags

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gaz, Alessandro

2011-11-16

After its formulation in 1960's the Standard Model of Fundamental Interactions has gone through an impressive series of successes, begun with the discovery of neutral weak currents [1] and the experimental observations of the massive carriers of weak interactions, the W ± and Z 0 bosons [2], [3]. High precision measurements performed at LEP and SLAC test the validity of the theory to an unprecedented level of accuracy and do not show any significant deviations with respect to the Standard Model predictions. One of the attractive features of the Standard Model is the description of the phenomena which violate the matter-antimatter symmetry (CP), and this violation uniquely depends (in the quark sector) on a weak phase in the matrix describing the couplings among different quark flavors. CP-violation was discovered in 1964 as a tiny effect in the mixing of the K 0 -more » $$\\bar{K}$$ 0 system [12] but, after a few decades of study of the physics of K mesons, no strong confirmation of the Standard Model can be obtained on the mechanism which generates CP-violation. On the other hand the physics of B mesons is suitable for a pretty large number of measurements which can confirm or disprove this aspect of the theory. The main goal of the BABAR and Belle experiments physics program is to test the description of CP-violation and flavor physics mainly from the decays of B u and B d mesons. Soon after the beginning of data-taking in 1999, CP-violation was discovered in the interference between mixing and decay in the golden channel B 0 → J/Ψ}K 0 [17] [18], while in 2004 a large direct charge asymmetry was observed in the B 0 → K +π - channel [16]. There is a third kind of CP-violation which can be exhibited by the B d - $$\\bar{B}$$ d system, the so called CP-violation in mixing. The Standard Model predicts this asymmetry to be small, possibly out of reach of current experiments, but several New Physics models contain new particles and couplings which can enhance it up to detectable levels. In this thesis we search for CP-violation in B d - $$\\bar{B}$$ d mixing at the BABAR experiment. We reconstruct one of the two B mesons produced at the PEP-II electromagnetic collider using the partial reconstruction technique, while the flavor of the other B is inferred by the charge of a kaon identified among its decay products. Given the smallness of the physical asymmetry we want to measure, a crucial aspect of this analysis is the control of spurious charge asymmetries arising from the interaction of particles with the detector material. We accomplish this by using a control sample of charged kaons on the same data we use in our analysis. After a brief introduction of the theoretical framework and the phenomenology of the decays of B mesons at a B-factory (chapters 1 and 2), we will review in chapter 3 the current experimental results on this topic. We will then describe the characteristics of the collider and the experimental apparatus (chapter 4) used to perform our measurement. The available dataset and the event pre-selection techniques are treated in chapter 5, while the analysis method is discussed in detail in the following one. In chapters 7 and 8 the definitions of the probability density functions used to model each component of our sample are given and then they are tested in samples of simulated data. Toy and reweighted Monte Carlo data are used in chapter 9 to test the sensitivity of our fitting procedure to the physical parameters related to CP violation; chapter 10 discusses the possibility of modeling some of the components of our sample directly on the data. Finally the fit on the real data sample is described in chapter 11 and the treatment of systematic uncertainties is done in chapter 12, while the final result is given in chapter 13.« less

Bayesian Peptide Peak Detection for High Resolution TOF Mass Spectrometry.

PubMed

Zhang, Jianqiu; Zhou, Xiaobo; Wang, Honghui; Suffredini, Anthony; Zhang, Lin; Huang, Yufei; Wong, Stephen

2010-11-01

In this paper, we address the issue of peptide ion peak detection for high resolution time-of-flight (TOF) mass spectrometry (MS) data. A novel Bayesian peptide ion peak detection method is proposed for TOF data with resolution of 10 000-15 000 full width at half-maximum (FWHW). MS spectra exhibit distinct characteristics at this resolution, which are captured in a novel parametric model. Based on the proposed parametric model, a Bayesian peak detection algorithm based on Markov chain Monte Carlo (MCMC) sampling is developed. The proposed algorithm is tested on both simulated and real datasets. The results show a significant improvement in detection performance over a commonly employed method. The results also agree with expert's visual inspection. Moreover, better detection consistency is achieved across MS datasets from patients with identical pathological condition.

Network Anomaly Detection Based on Wavelet Analysis

NASA Astrophysics Data System (ADS)

Lu, Wei; Ghorbani, Ali A.

2008-12-01

Signal processing techniques have been applied recently for analyzing and detecting network anomalies due to their potential to find novel or unknown intrusions. In this paper, we propose a new network signal modelling technique for detecting network anomalies, combining the wavelet approximation and system identification theory. In order to characterize network traffic behaviors, we present fifteen features and use them as the input signals in our system. We then evaluate our approach with the 1999 DARPA intrusion detection dataset and conduct a comprehensive analysis of the intrusions in the dataset. Evaluation results show that the approach achieves high-detection rates in terms of both attack instances and attack types. Furthermore, we conduct a full day's evaluation in a real large-scale WiFi ISP network where five attack types are successfully detected from over 30 millions flows.

Bayesian Peptide Peak Detection for High Resolution TOF Mass Spectrometry

PubMed Central

Zhang, Jianqiu; Zhou, Xiaobo; Wang, Honghui; Suffredini, Anthony; Zhang, Lin; Huang, Yufei; Wong, Stephen

2011-01-01

In this paper, we address the issue of peptide ion peak detection for high resolution time-of-flight (TOF) mass spectrometry (MS) data. A novel Bayesian peptide ion peak detection method is proposed for TOF data with resolution of 10 000–15 000 full width at half-maximum (FWHW). MS spectra exhibit distinct characteristics at this resolution, which are captured in a novel parametric model. Based on the proposed parametric model, a Bayesian peak detection algorithm based on Markov chain Monte Carlo (MCMC) sampling is developed. The proposed algorithm is tested on both simulated and real datasets. The results show a significant improvement in detection performance over a commonly employed method. The results also agree with expert’s visual inspection. Moreover, better detection consistency is achieved across MS datasets from patients with identical pathological condition. PMID:21544266

Low-carbon, low-water scenarios with life cycle water factors for ES&T paper

EPA Pesticide Factsheets

The dataset includes all data used in the creation of figures and graphs in the paper: Scenarios for low carbon and low water electric power plant operations: implications for upstream water use. Data includes regional electricity mixes, full life cycle water use, and water use for each life cycle stage. These encompass a range of scenarios out to 2050, and should not be used as predictions, forecasts or official baselines. The scenarios and results are for research purposes only, and do not represent current or future U.S. EPA policies or regulations.This dataset is associated with the following publication:Dodder , R., J. Barnwell , and W. Yelverton. Scenarios for low carbon and low water electric power plant operations: implications for upstream water use. ENVIRONMENTAL SCIENCE & TECHNOLOGY. American Chemical Society, Washington, DC, USA, 50(21): 11460-11470, (2016).

CHiCP: a web-based tool for the integrative and interactive visualization of promoter capture Hi-C datasets.

PubMed

Schofield, E C; Carver, T; Achuthan, P; Freire-Pritchett, P; Spivakov, M; Todd, J A; Burren, O S

2016-08-15

Promoter capture Hi-C (PCHi-C) allows the genome-wide interrogation of physical interactions between distal DNA regulatory elements and gene promoters in multiple tissue contexts. Visual integration of the resultant chromosome interaction maps with other sources of genomic annotations can provide insight into underlying regulatory mechanisms. We have developed Capture HiC Plotter (CHiCP), a web-based tool that allows interactive exploration of PCHi-C interaction maps and integration with both public and user-defined genomic datasets. CHiCP is freely accessible from www.chicp.org and supports most major HTML5 compliant web browsers. Full source code and installation instructions are available from http://github.com/D-I-L/django-chicp ob219@cam.ac.uk. © The Author 2016. Published by Oxford University Press. All rights reserved.

An inter-comparison of PM10 source apportionment using PCA and PMF receptor models in three European sites.

PubMed

Cesari, Daniela; Amato, F; Pandolfi, M; Alastuey, A; Querol, X; Contini, D

2016-08-01

Source apportionment of aerosol is an important approach to investigate aerosol formation and transformation processes as well as to assess appropriate mitigation strategies and to investigate causes of non-compliance with air quality standards (Directive 2008/50/CE). Receptor models (RMs) based on chemical composition of aerosol measured at specific sites are a useful, and widely used, tool to perform source apportionment. However, an analysis of available studies in the scientific literature reveals heterogeneities in the approaches used, in terms of "working variables" such as the number of samples in the dataset and the number of chemical species used as well as in the modeling tools used. In this work, an inter-comparison of PM10 source apportionment results obtained at three European measurement sites is presented, using two receptor models: principal component analysis coupled with multi-linear regression analysis (PCA-MLRA) and positive matrix factorization (PMF). The inter-comparison focuses on source identification, quantification of source contribution to PM10, robustness of the results, and how these are influenced by the number of chemical species available in the datasets. Results show very similar component/factor profiles identified by PCA and PMF, with some discrepancies in the number of factors. The PMF model appears to be more suitable to separate secondary sulfate and secondary nitrate with respect to PCA at least in the datasets analyzed. Further, some difficulties have been observed with PCA in separating industrial and heavy oil combustion contributions. Commonly at all sites, the crustal contributions found with PCA were larger than those found with PMF, and the secondary inorganic aerosol contributions found by PCA were lower than those found by PMF. Site-dependent differences were also observed for traffic and marine contributions. The inter-comparison of source apportionment performed on complete datasets (using the full range of available chemical species) and incomplete datasets (with reduced number of chemical species) allowed to investigate the sensitivity of source apportionment (SA) results to the working variables used in the RMs. Results show that, at both sites, the profiles and the contributions of the different sources calculated with PMF are comparable within the estimated uncertainties indicating a good stability and robustness of PMF results. In contrast, PCA outputs are more sensitive to the chemical species present in the datasets. In PCA, the crustal contributions are higher in the incomplete datasets and the traffic contributions are significantly lower for incomplete datasets.

Crowdsourcing Physical Network Topology Mapping With Net.Tagger

DTIC Science & Technology

2016-03-01

backend server infrastructure . This in- cludes a full security audit, better web services handling, and integration with the OSM stack and dataset to...a novel approach to network infrastructure mapping that combines smartphone apps with crowdsourced collection to gather data for offline aggregation...and analysis. The project aims to build a map of physical network infrastructure such as fiber-optic cables, facilities, and access points. The

Creating Diverse Ensemble Classifiers to Reduce Supervision

DTIC Science & Technology

2005-12-01

artificial examples. Quite often training with noise improves network generalization (Bishop, 1995; Raviv & Intrator, 1996). Adding noise to training...full training set, as seen by comparing to the to- tal dataset sizes. Hence, improving on the data utilization of DECORATE is a fairly difficult task...prohibitively expensive, except (perhaps) with an incremen- tal learner such as Naive Bayes. Our AFA framework is significantly more efficient because

Data for Sediments Paper

EPA Pesticide Factsheets

The full report on sediment resuspension in drinking water storage tanks and a link to an animation of results.This dataset is associated with the following publication:Ho, C., R. Murray , J. Christian, E. Ching, J. Slavin, J. Ortega, and L. Rossman. Sediment Resuspension and Transport in Water Distribution Storage Tanks. JOURNAL OF THE AMERICAN WATER WORKS ASSOCIATION. American Water Works Association, Denver, CO, USA, 108(6): ., (2016).

The MITLL-AFRL IWSLT 2016 Systems

DTIC Science & Technology

2016-12-08

Processing for MT We preprocessed the Arabic- English dataset from the QED corpus to correct sentence alignment errors and run-together words. These...are often split across lines, sometimes leaving the matching English and Arabic words on different lines. We used line-final punctua- tion as a guide...to assemble English lines into full sentences, while simultaneously concatenating their Arabic counterparts. Some Arabic files contain lines with just

Quantarctica: A Unique, Open, Standalone GIS Package for Antarctic Research and Education

NASA Astrophysics Data System (ADS)

Roth, George; Matsuoka, Kenichi; Skoglund, Anders; Melvær, Yngve; Tronstad, Stein

2017-04-01

The Norwegian Polar Institute has developed Quantarctica (http://quantarctica.npolar.no), an open GIS package for use by the international Antarctic community. Quantarctica includes a wide range of cartographic basemap layers, geophysical and glaciological datasets, and satellite imagery in standardized open file formats with a consistent Antarctic map projection and customized layer and labeling styles for quick, effective cartography. Quantarctica's strengths as an open science platform lie in 1) The complete, ready-to-use data package which includes full-resolution, original-quality vector and raster data, 2) A policy for freely-redistributable and modifiable data including all metadata and citations, and 3) QGIS, a free, full-featured, modular, offline-capable open-source GIS suite with a rapid and active development and support community. The Quantarctica team is actively incorporating more up-to-date, peer-reviewed, freely distributable pan-Antarctic geospatial datasets for the next version release in 2017. As part of this ongoing development, we are investigating the best approaches for quickly and seamlessly distributing new and updated data to users, storing datasets in efficient, open file formats while maintaining full data integrity, and coexisting with numerous online data portals in a way that most actively benefits the Antarctic community. A recent survey of Quantarctica users showed broad geographical adoption among Antarctic Treaty countries, including those outside the large US and UK Antarctic programs. Maps and figures produced by Quantarctica have also appeared in open-access journals and outside of the formal scientific community on popular science and GIS blogs. Our experience with the Quantarctica project has shown the tremendous value of education and outreach, not only in promoting open software, data formats, and practices, but in empowering Antarctic science groups to more effectively use GIS and geospatial data. Open practices are making a huge impact in Antarctic GIS, where individual countries have historically maintained their own restricted Antarctic geodatabases and where the next generation of scientists are entering the field with experience in using geospatial thinking for planning, visualization, and problem solving.

The Benefits and Complexities of Operating Geographic Information Systems (GIS) in a High Performance Computing (HPC) Environment

NASA Astrophysics Data System (ADS)

Shute, J.; Carriere, L.; Duffy, D.; Hoy, E.; Peters, J.; Shen, Y.; Kirschbaum, D.

2017-12-01

The NASA Center for Climate Simulation (NCCS) at the Goddard Space Flight Center is building and maintaining an Enterprise GIS capability for its stakeholders, to include NASA scientists, industry partners, and the public. This platform is powered by three GIS subsystems operating in a highly-available, virtualized environment: 1) the Spatial Analytics Platform is the primary NCCS GIS and provides users discoverability of the vast DigitalGlobe/NGA raster assets within the NCCS environment; 2) the Disaster Mapping Platform provides mapping and analytics services to NASA's Disaster Response Group; and 3) the internal (Advanced Data Analytics Platform/ADAPT) enterprise GIS provides users with the full suite of Esri and open source GIS software applications and services. All systems benefit from NCCS's cutting edge infrastructure, to include an InfiniBand network for high speed data transfers; a mixed/heterogeneous environment featuring seamless sharing of information between Linux and Windows subsystems; and in-depth system monitoring and warning systems. Due to its co-location with the NCCS Discover High Performance Computing (HPC) environment and the Advanced Data Analytics Platform (ADAPT), the GIS platform has direct access to several large NCCS datasets including DigitalGlobe/NGA, Landsat, MERRA, and MERRA2. Additionally, the NCCS ArcGIS Desktop Windows virtual machines utilize existing NetCDF and OPeNDAP assets for visualization, modelling, and analysis - thus eliminating the need for data duplication. With the advent of this platform, Earth scientists have full access to vast data repositories and the industry-leading tools required for successful management and analysis of these multi-petabyte, global datasets. The full system architecture and integration with scientific datasets will be presented. Additionally, key applications and scientific analyses will be explained, to include the NASA Global Landslide Catalog (GLC) Reporter crowdsourcing application, the NASA GLC Viewer discovery and analysis tool, the DigitalGlobe/NGA Data Discovery Tool, the NASA Disaster Response Group Mapping Platform (https://maps.disasters.nasa.gov), and support for NASA's Arctic - Boreal Vulnerability Experiment (ABoVE).

HadISD: a quality-controlled global synoptic report database for selected variables at long-term stations from 1973-2011

NASA Astrophysics Data System (ADS)

Dunn, R. J. H.; Willett, K. M.; Thorne, P. W.; Woolley, E. V.; Durre, I.; Dai, A.; Parker, D. E.; Vose, R. S.

2012-10-01

This paper describes the creation of HadISD: an automatically quality-controlled synoptic resolution dataset of temperature, dewpoint temperature, sea-level pressure, wind speed, wind direction and cloud cover from global weather stations for 1973-2011. The full dataset consists of over 6000 stations, with 3427 long-term stations deemed to have sufficient sampling and quality for climate applications requiring sub-daily resolution. As with other surface datasets, coverage is heavily skewed towards Northern Hemisphere mid-latitudes. The dataset is constructed from a large pre-existing ASCII flatfile data bank that represents over a decade of substantial effort at data retrieval, reformatting and provision. These raw data have had varying levels of quality control applied to them by individual data providers. The work proceeded in several steps: merging stations with multiple reporting identifiers; reformatting to netCDF; quality control; and then filtering to form a final dataset. Particular attention has been paid to maintaining true extreme values where possible within an automated, objective process. Detailed validation has been performed on a subset of global stations and also on UK data using known extreme events to help finalise the QC tests. Further validation was performed on a selection of extreme events world-wide (Hurricane Katrina in 2005, the cold snap in Alaska in 1989 and heat waves in SE Australia in 2009). Some very initial analyses are performed to illustrate some of the types of problems to which the final data could be applied. Although the filtering has removed the poorest station records, no attempt has been made to homogenise the data thus far, due to the complexity of retaining the true distribution of high-resolution data when applying adjustments. Hence non-climatic, time-varying errors may still exist in many of the individual station records and care is needed in inferring long-term trends from these data. This dataset will allow the study of high frequency variations of temperature, pressure and humidity on a global basis over the last four decades. Both individual extremes and the overall population of extreme events could be investigated in detail to allow for comparison with past and projected climate. A version-control system has been constructed for this dataset to allow for the clear documentation of any updates and corrections in the future.

Computer-aided diagnosis of periapical cyst and keratocystic odontogenic tumor on cone beam computed tomography.

PubMed

Yilmaz, E; Kayikcioglu, T; Kayipmaz, S

2017-07-01

In this article, we propose a decision support system for effective classification of dental periapical cyst and keratocystic odontogenic tumor (KCOT) lesions obtained via cone beam computed tomography (CBCT). CBCT has been effectively used in recent years for diagnosing dental pathologies and determining their boundaries and content. Unlike other imaging techniques, CBCT provides detailed and distinctive information about the pathologies by enabling a three-dimensional (3D) image of the region to be displayed. We employed 50 CBCT 3D image dataset files as the full dataset of our study. These datasets were identified by experts as periapical cyst and KCOT lesions according to the clinical, radiographic and histopathologic features. Segmentation operations were performed on the CBCT images using viewer software that we developed. Using the tools of this software, we marked the lesional volume of interest and calculated and applied the order statistics and 3D gray-level co-occurrence matrix for each CBCT dataset. A feature vector of the lesional region, including 636 different feature items, was created from those statistics. Six classifiers were used for the classification experiments. The Support Vector Machine (SVM) classifier achieved the best classification performance with 100% accuracy, and 100% F-score (F1) scores as a result of the experiments in which a ten-fold cross validation method was used with a forward feature selection algorithm. SVM achieved the best classification performance with 96.00% accuracy, and 96.00% F1 scores in the experiments in which a split sample validation method was used with a forward feature selection algorithm. SVM additionally achieved the best performance of 94.00% accuracy, and 93.88% F1 in which a leave-one-out (LOOCV) method was used with a forward feature selection algorithm. Based on the results, we determined that periapical cyst and KCOT lesions can be classified with a high accuracy with the models that we built using the new dataset selected for this study. The studies mentioned in this article, along with the selected 3D dataset, 3D statistics calculated from the dataset, and performance results of the different classifiers, comprise an important contribution to the field of computer-aided diagnosis of dental apical lesions. Copyright © 2017 Elsevier B.V. All rights reserved.

Gain of employment and perceived health status among previously unemployed persons: evidence from a longitudinal study in the United States.

PubMed

Park, S; Chan, K C G; Williams, E C

2016-04-01

Using longitudinal datasets, we investigated whether gaining employment was associated with improvements in perceived mental health and overall health among previously unemployed U.S. residents. We additionally examined whether the association varied across types of employment and socio-demographic characteristics. We used multiple two-year panel datasets of the Medical Expenditure Panel Survey during 2004-2012. We studied two health outcomes: perceived mental health and overall health. Our independent variables were employment status: full-time, part-time, self-employment, and unemployment. To examine the association between gaining employment and perceived health, we employed population-averaged models with generalized estimating equations. We secondarily examined the association across subpopulations (gender, race/ethnicity, and education). Those who gained full-time, part-time, and self-employment were more likely to report good mental health than those who stayed unemployed (AOR [Adjusted Odds Ratio] = 2.90, 95% CI 2.23 to 3.78, AOR = 1.63, 95% CI 1.28 to 2.06, and AOR = 3.24, 95% CI 1.08 to 9.70, respectively). Those who became full-time and part-time employed were more likely to report good overall health relative to those who stayed unemployed (AOR = 2.28, 95% CI 1.82 to 2.86 and AOR = 1.91, 95% CI 1.52 to 2.40, respectively). For both measures of perceived health, the magnitudes of the association were larger for those who gained full-time employment than part-time employment. AORs were relatively higher for males, black persons, and people with less than a college education relative to other groups in each subpopulation. Improving employment outcomes may improve perceived health. Transiting toward full-time employment, in particular, may maximize the benefits of employment. Copyright © 2015 The Royal Institute of Public Health. All rights reserved.

Limits on the decay-rate difference of neutral B mesons and on CP, T, and CPT violation in B(0-0)B oscillations.

PubMed

Aubert, B; Barate, R; Boutigny, D; Gaillard, J-M; Hicheur, A; Karyotakis, Y; Lees, J P; Robbe, P; Tisserand, V; Zghiche, A; Palano, A; Pompili, A; Chen, J C; Qi, N D; Rong, G; Wang, P; Zhu, Y S; Eigen, G; Ofte, I; Stugu, B; Abrams, G S; Borgland, A W; Breon, A B; Brown, D N; Button-Shafer, J; Cahn, R N; Charles, E; Day, C T; Gill, M S; Gritsan, A V; Groysman, Y; Jacobsen, R G; Kadel, R W; Kadyk, J; Kerth, L T; Kolomensky, Yu G; Kral, J F; Kukartsev, G; LeClerc, C; Levi, M E; Lynch, G; Mir, L M; Oddone, P J; Orimoto, T J; Pripstein, M; Roe, N A; Romosan, A; Ronan, M T; Shelkov, V G; Telnov, A V; Wenzel, W A; Ford, K; Harrison, T J; Hawkes, C M; Knowles, D J; Morgan, S E; Penny, R C; Watson, A T; Watson, N K; Deppermann, T; Goetzen, K; Held, T; Koch, H; Lewandowski, B; Pelizaeus, M; Peters, K; Schmuecker, H; Steinke, M; Barlow, N R; Boyd, J T; Chevalier, N; Cottingham, W N; Kelly, M P; Latham, T E; Mackay, C; Wilson, F F; Abe, K; Cuhadar-Donszelmann, T; Hearty, C; Mattison, T S; McKenna, J A; Thiessen, D; Kyberd, P; McKemey, A K; Blinov, V E; Bukin, A D; Golubev, V B; Ivanchenko, V N; Kravchenko, E A; Onuchin, A P; Serednyakov, S I; Skovpen, Yu I; Solodov, E P; Yushkov, A N; Best, D; Bruinsma, M; Chao, M; Kirkby, D; Lankford, A J; Mandelkern, M; Mommsen, R K; Roethel, W; Stoker, D P; Buchanan, C; Hartfiel, B L; Shen, B C; del Re, D; Hadavand, H K; Hill, E J; MacFarlane, D B; Paar, H P; Rahatlou, Sh; Sharma, V; Berryhill, J W; Campagnari, C; Dahmes, B; Levy, S L; Long, O; Lu, A; Mazur, M A; Richman, J D; Verkerke, W; Beck, T W; Beringer, J; Eisner, A M; Heusch, C A; Lockman, W S; Schalk, T; Schmitz, R E; Schumm, B A; Seiden, A; Turri, M; Walkowiak, W; Williams, D C; Wilson, M G; Albert, J; Chen, E; Dubois-Felsmann, G P; Dvoretskii, A; Hitlin, D G; Narsky, I; Porter, F C; Ryd, A; Samuel, A; Yang, S; Jayatilleke, S; Mancinelli, G; Meadows, B T; Sokoloff, M D; Abe, T; Blanc, F; Bloom, P; Chen, S; Clark, P J; Ford, W T; Nauenberg, U; Olivas, A; Rankin, P; Roy, J; Smith, J G; van Hoek, W C; Zhang, L; Harton, J L; Hu, T; Soffer, A; Toki, W H; Wilson, R J; Zhang, J; Altenburg, D; Brandt, T; Brose, J; Colberg, T; Dickopp, M; Dubitzky, R S; Hauke, A; Lacker, H M; Maly, E; Müller-Pfefferkorn, R; Nogowski, R; Otto, S; Schubert, J; Schubert, K R; Schwierz, R; Spaan, B; Wilden, L; Bernard, D; Bonneaud, G R; Brochard, F; Cohen-Tanugi, J; Grenier, P; Thiebaux, Ch; Vasileiadis, G; Verderi, M; Khan, A; Lavin, D; Muheim, F; Playfer, S; Swain, J E; Tinslay, J; Andreotti, M; Azzolini, V; Bettoni, D; Bozzi, C; Calabrese, R; Cibinetto, G; Luppi, E; Negrini, M; Piemontese, L; Sarti, A; Treadwell, E; Anulli, F; Baldini-Ferroli, R; Biasini, M; Calcaterra, A; de Sangro, R; Falciai, D; Finocchiaro, G; Patteri, P; Peruzzi, I M; Piccolo, M; Pioppi, M; Zallo, A; Buzzo, A; Capra, R; Contri, R; Crosetti, G; Lo Vetere, M; Macri, M; Monge, M R; Passaggio, S; Patrignani, C; Robutti, E; Santroni, A; Tosi, S; Bailey, S; Morii, M; Won, E; Bhimji, W; Bowerman, D A; Dauncey, P D; Egede, U; Eschrich, I; Gaillard, J R; Morton, G W; Nash, J A; Sanders, P; Taylor, G P; Grenier, G J; Lee, S-J; Mallik, U; Cochran, J; Crawley, H B; Lamsa, J; Meyer, W T; Prell, S; Rosenberg, E I; Yi, J; Davier, M; Grosdidier, G; Höcker, A; Laplace, S; Le Diberder, F; Lepeltier, V; Lutz, A M; Petersen, T C; Plaszczynski, S; Schune, M H; Tantot, L; Wormser, G; Brigljević, V; Cheng, C H; Lange, D J; Wright, D M; Bevan, A J; Coleman, J P; Fry, J R; Gabathuler, E; Gamet, R; Kay, M; Parry, R J; Payne, D J; Sloane, R J; Touramanis, C; Back, J J; Harrison, P F; Shorthouse, H W; Strother, P; Vidal, P B; Brown, C L; Cowan, G; Flack, R L; Flaecher, H U; George, S; Green, M G; Kurup, A; Marker, C E; McMahon, T R; Ricciardi, S; Salvatore, F; Vaitsas, G; Winter, M A; Brown, D; Davis, C L; Allison, J; Barlow, R J; Forti, A C; Hart, P A; Jackson, F; Lafferty, G D; Lyon, A J; Weatherall, J H; Williams, J C; Farbin, A; Jawahery, A; Kovalskyi, D; Lae, C K; Lillard, V; Roberts, D A; Blaylock, G; Dallapiccola, C; Flood, K T; Hertzbach, S S; Kofler, R; Koptchev, V B; Moore, T B; Saremi, S; Staengle, H; Willocq, S; Cowan, R; Sciolla, G; Taylor, F; Yamamoto, R K; Mangeol, D J J; Milek, M; Patel, P M; Lazzaro, A; Palombo, F; Bauer, J M; Cremaldi, L; Eschenburg, V; Godang, R; Kroeger, R; Reidy, J; Sanders, D A; Summers, D J; Zhao, H W; Brunet, S; Cote-Ahern, D; Hast, C; Taras, P; Nicholson, H; Cartaro, C; Cavallo, N; De Nardo, G; Fabozzi, F; Gatto, C; Lista, L; Paolucci, P; Piccolo, D; Sciacca, C; Baak, M A; Raven, G; LoSecco, J M; Gabriel, T A; Brau, B; Gan, K K; Honscheid, K; Hufnagel, D; Kagan, H; Kass, R; Pulliam, T; Wong, Q K; Brau, J; Frey, R; Potter, C T; Sinev, N B; Strom, D; Torrence, E; Colecchia, F; Dorigo, A; Galeazzi, F; Margoni, M; Morandin, M; Posocco, M; Rotondo, M; Simonetto, F; Stroili, R; Tiozzo, G; Voci, C; Benayoun, M; Briand, H; Chauveau, J; David, P; de la Vaissière, Ch; Del Buono, L; Hamon, O; John, M J J; Leruste, Ph; Ocariz, J; Pivk, M; Roos, L; Stark, J; T'Jampens, S; Therin, G; Manfredi, P F; Re, V; Behera, P K; Gladney, L; Guo, Q H; Panetta, J; Angelini, C; Batignani, G; Bettarini, S; Bondioli, M; Bucci, F; Calderini, G; Carpinelli, M; Forti, F; Giorgi, M A; Lusiani, A; Marchiori, G; Martinez-Vidal, F; Morganti, M; Neri, N; Paoloni, E; Rama, M; Rizzo, G; Sandrelli, F; Walsh, J; Haire, M; Judd, D; Paick, K; Wagoner, D E; Danielson, N; Elmer, P; Lu, C; Miftakov, V; Olsen, J; Smith, A J S; Tanaka, H A; Varnes, E W; Bellini, F; Cavoto, G; Faccini, R; Ferrarotto, F; Ferroni, F; Gaspero, M; Mazzoni, M A; Morganti, S; Pierini, M; Piredda, G; Safai Tehrani, F; Voena, C; Christ, S; Wagner, G; Waldi, R; Adye, T; De Groot, N; Franek, B; Geddes, N I; Gopal, G P; Olaiya, E O; Xella, S M; Aleksan, R; Emery, S; Gaidot, A; Ganzhur, S F; Giraud, P-F; Hamel de Monchenault, G; Kozanecki, W; Langer, M; Legendre, M; London, G W; Mayer, B; Schott, G; Vasseur, G; Yeche, Ch; Zito, M; Purohit, M V; Weidemann, A W; Yumiceva, F X; Aston, D; Bartoldus, R; Berger, N; Boyarski, A M; Buchmueller, O L; Convery, M R; Coupal, D P; Dong, D; Dorfan, J; Dujmic, D; Dunwoodie, W; Field, R C; Glanzman, T; Gowdy, S J; Granges-Pous, E; Hadig, T; Halyo, V; Hryn'ova, T; Innes, W R; Jessop, C P; Kelsey, M H; Kim, P; Kocian, M L; Langenegger, U; Leith, D W G S; Luitz, S; Luth, V; Lynch, H L; Marsiske, H; Messner, R; Muller, D R; O'Grady, C P; Ozcan, V E; Perazzo, A; Perl, M; Petrak, S; Ratcliff, B N; Robertson, S H; Roodman, A; Salnikov, A A; Schindler, R H; Schwiening, J; Simi, G; Snyder, A; Soha, A; Stelzer, J; Su, D; Sullivan, M K; Va'vra, J; Wagner, S R; Weaver, M; Weinstein, A J R; Wisniewski, W J; Wright, D H; Young, C C; Burchat, P R; Edwards, A J; Meyer, T I; Petersen, B A; Roat, C; Ahmed, M; Ahmed, S; Alam, M S; Ernst, J A; Saleem, M; Wappler, F R; Bugg, W; Krishnamurthy, M; Spanier, S M; Eckmann, R; Kim, H; Ritchie, J L; Schwitters, R F; Izen, J M; Kitayama, I; Lou, X C; Ye, S; Bianchi, F; Bona, M; Gallo, F; Gamba, D; Borean, C; Bosisio, L; Della Ricca, G; Dittongo, S; Grancagnolo, S; Lanceri, L; Poropat, P; Vitale, L; Vuagnin, G; Panvini, R S; Banerjee, Sw; Brown, C M; Fortin, D; Jackson, P D; Kowalewski, R; Roney, J M; Band, H R; Dasu, S; Datta, M; Eichenbaum, A M; Johnson, J R; Kutter, P E; Li, H; Liu, R; Di Lodovico, F; Mihalyi, A; Mohapatra, A K; Pan, Y; Prepost, R; Sekula, S J; von Wimmersperg-Toeller, J H; Wu, J; Wu, S L; Yu, Z; Neal, H

2004-05-07

Using events in which one of two neutral B mesons from the decay of an Upsilon(4S) meson is fully reconstructed, we determine parameters governing decay (DeltaGamma(d)/Gamma(d)), CP, and T violation (|q/p|), and CP and CPT violation (Re z,Im z). The results, obtained from an analysis of 88 x 10(6) Upsilon(4S) decays recorded by BABAR, are sgn(Re lambda(CP))DeltaGamma(d)/Gamma(d)=-0.008+/-0.037(stat)+/-0.018(syst)[-0.084,0.068],|q/p|=1.029+/-0.013(stat)+/-0.011(syst)[1.001,1.057],(Re lambda(CP)/|lambda(CP)|) Re z=0.014+/-0.035(stat)+/-0.034(syst)[-0.072,0.101],Im z=0.038+/-0.029(stat)+/-0.025(syst)[-0.028,0.104]. The values inside the square brackets indicate the 90% confidence-level intervals. These results are consistent with standard model expectations.

Measurements of the mass and width of the eta(c) meson and of an eta(c)(2S) candidate.

PubMed

Aubert, B; Barate, R; Boutigny, D; Gaillard, J-M; Hicheur, A; Karyotakis, Y; Lees, J P; Robbe, P; Tisserand, V; Zghiche, A; Palano, A; Pompili, A; Chen, J C; Qi, N D; Rong, G; Wang, P; Zhu, Y S; Eigen, G; Ofte, I; Stugu, B; Abrams, G S; Borgland, A W; Breon, A B; Brown, D N; Button-Shafer, J; Cahn, R N; Charles, E; Day, C T; Gill, M S; Gritsan, A V; Groysman, Y; Jacobsen, R G; Kadel, R W; Kadyk, J; Kerth, L T; Kolomensky, Yu G; Kral, J F; Kukartsev, G; LeClerc, C; Levi, M E; Lynch, G; Mir, L M; Oddone, P J; Orimoto, T J; Pripstein, M; Roe, N A; Romosan, A; Ronan, M T; Shelkov, V G; Telnov, A V; Wenzel, W A; Ford, K; Harrison, T J; Hawkes, C M; Knowles, D J; Morgan, S E; Penny, R C; Watson, A T; Watson, N K; Deppermann, T; Goetzen, K; Koch, H; Lewandowski, B; Pelizaeus, M; Peters, K; Schmuecker, H; Steinke, M; Barlow, N R; Boyd, J T; Chevalier, N; Cottingham, W N; Kelly, M P; Latham, T E; Mackay, C; Wilson, F F; Abe, K; Cuhadar-Donszelmann, T; Hearty, C; Mattison, T S; McKenna, J A; Thiessen, D; Kyberd, P; McKemey, A K; Blinov, V E; Bukin, A D; Golubev, V B; Ivanchenko, V N; Kravchenko, E A; Onuchin, A P; Serednyakov, S I; Skovpen, Yu I; Solodov, E P; Yushkov, A N; Best, D; Bruinsma, M; Chao, M; Kirkby, D; Lankford, A J; Mandelkern, M; Mommsen, R K; Roethel, W; Stoker, D P; Buchanan, C; Hartfiel, B L; Shen, B C; Del Re, D; Hadavand, H K; Hill, E J; MacFarlane, D B; Paar, H P; Rahatlou, Sh; Schwanke, U; Sharma, V; Berryhill, J W; Campagnari, C; Dahmes, B; Kuznetsova, N; Levy, S L; Long, O; Lu, A; Mazur, M A; Richman, J D; Verkerke, W; Beck, T W; Beringer, J; Eisner, A M; Heusch, C A; Lockman, W S; Schalk, T; Schmitz, R E; Schumm, B A; Seiden, A; Turri, M; Walkowiak, W; Williams, D C; Wilson, M G; Albert, J; Chen, E; Dubois-Felsmann, G P; Dvoretskii, A; Hitlin, D G; Narsky, I; Porter, F C; Ryd, A; Samuel, A; Yang, S; Jayatilleke, S; Mancinelli, G; Meadows, B T; Sokoloff, M D; Abe, T; Blanc, F; Bloom, P; Chen, S; Clark, P J; Ford, W T; Nauenberg, U; Olivas, A; Rankin, P; Roy, J; Smith, J G; Van Hoek, W C; Zhang, L; Harton, J L; Hu, T; Soffer, A; Toki, W H; Wilson, R J; Zhang, J; Altenburg, D; Brandt, T; Brose, J; Colberg, T; Dickopp, M; Dubitzky, R S; Hauke, A; Lacker, H M; Maly, E; Müller-Pfefferkorn, R; Nogowski, R; Otto, S; Schubert, J; Schubert, K R; Schwierz, R; Spaan, B; Wilden, L; Bernard, D; Bonneaud, G R; Brochard, F; Cohen-Tanugi, J; Grenier, P; Thiebaux, Ch; Vasileiadis, G; Verderi, M; Khan, A; Lavin, D; Muheim, F; Playfer, S; Swain, J E; Tinslay, J; Andreotti, M; Azzolini, V; Bettoni, D; Bozzi, C; Calabrese, R; Cibinetto, G; Luppi, E; Negrini, M; Piemontese, L; Sarti, A; Treadwell, E; Anulli, F; Baldini-Ferroli, R; Biasini, M; Calcaterra, A; De Sangro, R; Falciai, D; Finocchiaro, G; Patteri, P; Peruzzi, I M; Piccolo, M; Pioppi, M; Zallo, A; Buzzo, A; Capra, R; Contri, R; Crosetti, G; Lo Vetere, M; Macri, M; Monge, M R; Passaggio, S; Patrignani, C; Robutti, E; Santroni, A; Tosi, S; Bailey, S; Morii, M; Won, E; Bhimji, W; Bowerman, D A; Dauncey, P D; Egede, U; Eschrich, I; Gaillard, J R; Morton, G W; Nash, J A; Sanders, P; Taylor, G P; Grenier, G J; Lee, S-J; Mallik, U; Cochran, J; Crawley, H B; Lamsa, J; Meyer, W T; Prell, S; Rosenberg, E I; Yi, J; Davier, M; Grosdidier, G; Höcker, A; Laplace, S; Le Diberder, F; Lepeltier, V; Lutz, A M; Petersen, T C; Plaszczynski, S; Schune, M H; Tantot, L; Wormser, G; Brigljević, V; Cheng, C H; Lange, D J; Wright, D M; Bevan, A J; Coleman, J P; Fry, J R; Gabathuler, E; Gamet, R; Kay, M; Parry, R J; Payne, D J; Sloane, R J; Touramanis, C; Back, J J; Harrison, P F; Shorthouse, H W; Strother, P; Vidal, P B; Brown, C L; Cowan, G; Flack, R L; Flaecher, H U; George, S; Green, M G; Kurup, A; Marker, C E; McMahon, T R; Ricciardi, S; Salvatore, F; Vaitsas, G; Winter, M A; Brown, D; Davis, C L; Allison, J; Barlow, R J; Forti, A C; Hart, P A; Jackson, F; Lafferty, G D; Lyon, A J; Weatherall, J H; Williams, J C; Farbin, A; Jawahery, A; Kovalskyi, D; Lae, C K; Lillard, V; Roberts, D A; Blaylock, G; Dallapiccola, C; Flood, K T; Hertzbach, S S; Kofler, R; Koptchev, V B; Moore, T B; Saremi, S; Staengle, H; Willocq, S; Cowan, R; Sciolla, G; Taylor, F; Yamamoto, R K; Mangeol, D J J; Milek, M; Patel, P M; Lazzaro, A; Palombo, F; Bauer, J M; Cremaldi, L; Eschenburg, V; Godang, R; Kroeger, R; Reidy, J; Sanders, D A; Summers, D J; Zhao, H W; Brunet, S; Cote-Ahern, D; Hast, C; Taras, P; Nicholson, H; Cartaro, C; Cavallo, N; De Nardo, G; Fabozzi, F; Gatto, C; Lista, L; Paolucci, P; Piccolo, D; Sciacca, C; Baak, M A; Raven, G; LoSecco, J M; Gabriel, T A; Brau, B; Gan, K K; Honscheid, K; Hufnagel, D; Kagan, H; Kass, R; Pulliam, T; Wong, Q K; Brau, J; Frey, R; Potter, C T; Sinev, N B; Strom, D; Torrence, E; Colecchia, F; Dorigo, A; Galeazzi, F; Margoni, M; Morandin, M; Posocco, M; Rotondo, M; Simonetto, F; Stroili, R; Tiozzo, G; Voci, C; Benayoun, M; Briand, H; Chauveau, J; David, P; de la Vaissière, Ch; Del Buono, L; Hamon, O; John, M J J; Leruste, Ph; Ocariz, J; Pivk, M; Roos, L; Stark, J; T'Jampens, S; Therin, G; Manfredi, P F; Re, V; Behera, P K; Gladney, L; Guo, Q H; Panetta, J; Angelini, C; Batignani, G; Bettarini, S; Bondioli, M; Bucci, F; Calderini, G; Carpinelli, M; Forti, F; Giorgi, M A; Lusiani, A; Marchiori, G; Martinez-Vidal, F; Morganti, M; Neri, N; Paoloni, E; Rama, M; Rizzo, G; Sandrelli, F; Walsh, J; Haire, M; Judd, D; Paick, K; Wagoner, D E; Danielson, N; Elmer, P; Lu, C; Miftakov, V; Olsen, J; Smith, A J S; Tanaka, H A; Varnes, E W; Bellini, F; Cavoto, G; Faccini, R; Ferrarotto, F; Ferroni, F; Gaspero, M; Mazzoni, M A; Morganti, S; Pierini, M; Piredda, G; Safai Tehrani, F; Voena, C; Christ, S; Wagner, G; Waldi, R; Adye, T; De Groot, N; Franek, B; Geddes, N I; Gopal, G P; Olaiya, E O; Xella, S M; Aleksan, R; Emery, S; Gaidot, A; Ganzhur, S F; Giraud, P-F; Hamel de Monchenault, G; Kozanecki, W; Langer, M; Legendre, M; London, G W; Mayer, B; Schott, G; Vasseur, G; Yeche, Ch; Zito, M; Purohit, M V; Weidemann, A W; Yumiceva, F X; Aston, D; Bartoldus, R; Berger, N; Boyarski, A M; Buchmueller, O L; Convery, M R; Coupal, D P; Dong, D; Dorfan, J; Dujmic, D; Dunwoodie, W; Field, R C; Glanzman, T; Gowdy, S J; Grauges-Pous, E; Hadig, T; Halyo, V; Hryn'ova, T; Innes, W R; Jessop, C P; Kelsey, M H; Kim, P; Kocian, M L; Langenegger, U; Leith, D W G S; Luitz, S; Luth, V; Lynch, H L; Marsiske, H; Messner, R; Muller, D R; O'Grady, C P; Ozcan, V E; Perazzo, A; Perl, M; Petrak, S; Ratcliff, B N; Robertson, S H; Roodman, A; Salnikov, A A; Schindler, R H; Schwiening, J; Simi, G; Snyder, A; Soha, A; Stelzer, J; Su, D; Sullivan, M K; Va'vra, J; Wagner, S R; Weaver, M; Weinstein, A J R; Wisniewski, W J; Wright, D H; Young, C C; Burchat, P R; Edwards, A J; Meyer, T I; Petersen, B A; Roat, C; Ahmed, S; Alam, M S; Ernst, J A; Saleem, M; Wappler, F R; Bugg, W; Krishnamurthy, M; Spanier, S M; Eckmann, R; Kim, H; Ritchie, J L; Schwitters, R F; Izen, J M; Kitayama, I; Lou, X C; Ye, S; Bianchi, F; Bona, M; Gallo, F; Gamba, D; Borean, C; Bosisio, L; Della Ricca, G; Dittongo, S; Grancagnolo, S; Lanceri, L; Poropat, P; Vitale, L; Vuagnin, G; Panvini, R S; Banerjee, Sw; Brown, C M; Fortin, D; Jackson, P D; Kowalewski, R; Roney, J M; Band, H R; Dasu, S; Datta, M; Eichenbaum, A M; Johnson, J R; Kutter, P E; Li, H; Liu, R; Di Lodovico, F; Mihalyi, A; Mohapatra, A K; Pan, Y; Prepost, R; Sekula, S J; von Wimmersperg-Toeller, J H; Wu, J; Wu, S L; Yu, Z; Neal, H

2004-04-09

The mass m(eta(c)) and total width Gamma(eta(c))(tot) of the eta(c) meson have been measured in two-photon interactions at the SLAC e(+)e(-) asymmetric B Factory with the BABAR detector. With a sample of approximately 2500 reconstructed eta(c)-->K(0)(S)K+/-pi(-/+) decays in 88 fb(-1) of data, the results are m(eta(c))=2982.5+/-1.1(stat)+/-0.9(syst) MeV/c(2) and Gamma(eta(c))(tot)=34.3+/-2.3(stat)+/-0.9(syst) MeV/c(2). Using the same decay mode, a second resonance with 112+/-24 events is observed with a mass of 3630.8+/-3.4(stat)+/-1.0(syst) MeV/c(2) and width of 17.0+/-8.3(stat)+/-2.5(syst) MeV/c(2). This observation is consistent with expectations for the eta(c)(2S) state.

Tau lepton production and decays: perspective of multi-dimensional distributions and Monte Carlo methods

NASA Astrophysics Data System (ADS)

Was, Z.

2017-06-01

Status of τ lepton decay Monte Carlo generator TAUOLA, its main applications and recent developments are reviewed. It is underlined, that in recent efforts on development of new hadronic currents, the multi-dimensional nature of distributions of the experimental data must be taken with a great care: lesson from comparison and fits to the BaBar and Belle data is recalled. It was found, that as in the past at a time of comparisons with CLEO and ALEPH data, proper fitting, to as detailed as possible representation of the experimental data, is essential for appropriate developments of models of τ decay dynamic. This multi-dimensional nature of distributions is also important for observables where τ leptons are used to constrain experimental data. In later part of the presentation, use of the TAUOLA program for phenomenology of W, Z, H decays at LHC is addressed, in particular in the context of the Higgs boson parity measurements. Some new results, relevant for QED lepton pair emission are mentioned as well.

No-Go Theorem for Nonstandard Explanations of the τ → K S π ν τ C P Asymmetry

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cirigliano, Vincenzo; Crivellin, Andreas; Hoferichter, Martin

Tmore » he C P asymmetry in τ → K S π ν τ C P , as measured by the BABAR collaboration, differs from the standard model prediction by 2.8 σ . Most nonstandard interactions do not allow for the required strong phase needed to produce a nonvanishing C P asymmetry, leaving only new tensor interactions as a possible mechanism. We demonstrate that, contrary to previous assumptions in the literature, the crucial interference between vector and tensor phases is suppressed by at least 2 orders of magnitude due to Watson’s final-state-interaction theorem. Furthermore, we find that the strength of the relevant C P -violating tensor interaction is strongly constrained by bounds from the neutron electric dipole moment and D – ¯ D mixing. hese observations together imply that it is extremely difficult to explain the current τ → K S π ν τ C P measurement in terms of physics beyond the standard model originating in the ultraviolet.« less

No-Go Theorem for Nonstandard Explanations of the τ → K S π ν τ C P Asymmetry

DOE PAGES

Cirigliano, Vincenzo; Crivellin, Andreas; Hoferichter, Martin

2018-04-06

Tmore » he C P asymmetry in τ → K S π ν τ C P , as measured by the BABAR collaboration, differs from the standard model prediction by 2.8 σ . Most nonstandard interactions do not allow for the required strong phase needed to produce a nonvanishing C P asymmetry, leaving only new tensor interactions as a possible mechanism. We demonstrate that, contrary to previous assumptions in the literature, the crucial interference between vector and tensor phases is suppressed by at least 2 orders of magnitude due to Watson’s final-state-interaction theorem. Furthermore, we find that the strength of the relevant C P -violating tensor interaction is strongly constrained by bounds from the neutron electric dipole moment and D – ¯ D mixing. hese observations together imply that it is extremely difficult to explain the current τ → K S π ν τ C P measurement in terms of physics beyond the standard model originating in the ultraviolet.« less

Study of B to X \\gamma Decays and Determination of |V_{td}/V_{ts}|

DOE Office of Scientific and Technical Information (OSTI.GOV)

del Amo Sanchez, P.; Lees, J.P.; Poireau, V.

2011-08-22

Using a sample of 471 million B{bar B} events collected with the BABAR detector, we study the sum of seven exclusive final states B {yields} X{sub s(d){gamma}}, where X{sub s(d)} is a strange (non-strange) hadronic system with a mass of up to 2.0 GeV/c{sup 2}. After correcting for unobserved decay modes, we obtain a branching fraction for b {yields} d{gamma} of (9.2 {+-} 2.0(stat.) {+-} 2.3(syst.)) x 10{sup -6} in this mass range, and a branching fraction for b {yields} s{gamma} of (23.0 {+-} 0.8(stat.) {+-} 3.0(syst.)) x 10{sup -5} in the same mass range. We find {Beta}(b{yields}d{gamma})/{Beta}(b{yields}s{gamma}) = 0.040more » {+-} 0.009(stat.) {+-} 0.010(syst.), from which we determine |V{sub td}/V{sub ts}| = 0.199 {+-} 0.022(stat.) {+-} 0.024(syst.) {+-} 0.002(th.).« less

Study of B{yields}X{gamma} decays and determination of |V{sub td}/V{sub ts}|

DOE Office of Scientific and Technical Information (OSTI.GOV)

del Amo Sanchez, P.; Lees, J. P.; Poireau, V.

2010-09-01

Using a sample of 471x10{sup 6} BB events collected with the BABAR detector, we study the sum of seven exclusive final states B{yields}X{sub s(d){gamma}}, where X{sub s(d)} is a strange (nonstrange) hadronic system with a mass of up to 2.0 GeV/c{sup 2}. After correcting for unobserved decay modes, we obtain a branching fraction for b{yields}d{gamma} of (9.2{+-}2.0(stat){+-}2.3(syst))x10{sup -6} in this mass range, and a branching fraction for b{yields}s{gamma} of (23.0{+-}0.8(stat){+-}3.0(syst))x10{sup -5} in the same mass range. We find (B(b{yields}d{gamma})/B(b{yields}s{gamma}))=0.040{+-}0.009(stat){+-}0.010(syst), from which we determine |V{sub td}/V{sub ts}|=0.199{+-}0.022(stat){+-}0.024(syst){+-}0.002(th).

Measurement of |V(cb)| and the form-factor slope in B --> Dl- nu(l) decays in events tagged by a fully reconstructed B meson.

PubMed

Aubert, B; Karyotakis, Y; Lees, J P; Poireau, V; Prencipe, E; Prudent, X; Tisserand, V; Garra Tico, J; Grauges, E; Martinelli, M; Palano, A; Pappagallo, M; Eigen, G; Stugu, B; Sun, L; Battaglia, M; Brown, D N; Kerth, L T; Kolomensky, Yu G; Lynch, G; Osipenkov, I L; Tackmann, K; Tanabe, T; Hawkes, C M; Soni, N; Watson, A T; Koch, H; Schroeder, T; Asgeirsson, D J; Fulsom, B G; Hearty, C; Mattison, T S; McKenna, J A; Barrett, M; Khan, A; Randle-Conde, A; Blinov, V E; Bukin, A D; Buzykaev, A R; Druzhinin, V P; Golubev, V B; Onuchin, A P; Serednyakov, S I; Skovpen, Yu I; Solodov, E P; Todyshev, K Yu; Bondioli, M; Curry, S; Eschrich, I; Kirkby, D; Lankford, A J; Lund, P; Mandelkern, M; Martin, E C; Stoker, D P; Atmacan, H; Gary, J W; Liu, F; Long, O; Vitug, G M; Yasin, Z; Zhang, L; Sharma, V; Campagnari, C; Hong, T M; Kovalskyi, D; Mazur, M A; Richman, J D; Beck, T W; Eisner, A M; Heusch, C A; Kroseberg, J; Lockman, W S; Martinez, A J; Schalk, T; Schumm, B A; Seiden, A; Wang, L; Winstrom, L O; Cheng, C H; Doll, D A; Echenard, B; Fang, F; Hitlin, D G; Narsky, I; Piatenko, T; Porter, F C; Andreassen, R; Mancinelli, G; Meadows, B T; Mishra, K; Sokoloff, M D; Bloom, P C; Ford, W T; Gaz, A; Hirschauer, J F; Nagel, M; Nauenberg, U; Smith, J G; Wagner, S R; Ayad, R; Toki, W H; Wilson, R J; Feltresi, E; Hauke, A; Jasper, H; Karbach, T M; Merkel, J; Petzold, A; Spaan, B; Wacker, K; Kobel, M J; Nogowski, R; Schubert, K R; Schwierz, R; Volk, A; Bernard, D; Latour, E; Verderi, M; Clark, P J; Playfer, S; Watson, J E; Andreotti, M; Bettoni, D; Bozzi, C; Calabrese, R; Cecchi, A; Cibinetto, G; Fioravanti, E; Franchini, P; Luppi, E; Munerato, M; Negrini, M; Petrella, A; Piemontese, L; Santoro, V; Baldini-Ferroli, R; Calcaterra, A; de Sangro, R; Finocchiaro, G; Pacetti, S; Patteri, P; Peruzzi, I M; Piccolo, M; Rama, M; Zallo, A; Contri, R; Guido, E; Lo Vetere, M; Monge, M R; Passaggio, S; Patrignani, C; Robutti, E; Tosi, S; Chaisanguanthum, K S; Morii, M; Adametz, A; Marks, J; Schenk, S; Uwer, U; Bernlochner, F U; Klose, V; Lacker, H M; Bard, D J; Dauncey, P D; Tibbetts, M; Behera, P K; Charles, M J; Mallik, U; Cochran, J; Crawley, H B; Dong, L; Eyges, V; Meyer, W T; Prell, S; Rosenberg, E I; Rubin, A E; Gao, Y Y; Gritsan, A V; Guo, Z J; Arnaud, N; Béquilleux, J; D'Orazio, A; Davier, M; Derkach, D; da Costa, J Firmino; Grosdidier, G; Le Diberder, F; Lepeltier, V; Lutz, A M; Malaescu, B; Pruvot, S; Roudeau, P; Schune, M H; Serrano, J; Sordini, V; Stocchi, A; Wormser, G; Lange, D J; Wright, D M; Bingham, I; Burke, J P; Chavez, C A; Fry, J R; Gabathuler, E; Gamet, R; Hutchcroft, D E; Payne, D J; Touramanis, C; Bevan, A J; Clarke, C K; Di Lodovico, F; Sacco, R; Sigamani, M; Cowan, G; Paramesvaran, S; Wren, A C; Brown, D N; Davis, C L; Denig, A G; Fritsch, M; Gradl, W; Hafner, A; Alwyn, K E; Bailey, D; Barlow, R J; Jackson, G; Lafferty, G D; West, T J; Yi, J I; Anderson, J; Chen, C; Jawahery, A; Roberts, D A; Simi, G; Tuggle, J M; Dallapiccola, C; Salvati, E; Saremi, S; Cowan, R; Dujmic, D; Fisher, P H; Henderson, S W; Sciolla, G; Spitznagel, M; Yamamoto, R K; Zhao, M; Patel, P M; Robertson, S H; Schram, M; Lazzaro, A; Lombardo, V; Palombo, F; Stracka, S; Bauer, J M; Cremaldi, L; Godang, R; Kroeger, R; Sonnek, P; Summers, D J; Zhao, H W; Simard, M; Taras, P; Nicholson, H; De Nardo, G; Lista, L; Monorchio, D; Onorato, G; Sciacca, C; Raven, G; Snoek, H L; Jessop, C P; Knoepfel, K J; LoSecco, J M; Wang, W F; Corwin, L A; Honscheid, K; Kagan, H; Kass, R; Morris, J P; Rahimi, A M; Regensburger, J J; Sekula, S J; Wong, Q K; Blount, N L; Brau, J; Frey, R; Igonkina, O; Kolb, J A; Lu, M; Rahmat, R; Sinev, N B; Strom, D; Strube, J; Torrence, E; Castelli, G; Gagliardi, N; Margoni, M; Morandin, M; Posocco, M; Rotondo, M; Simonetto, F; Stroili, R; Voci, C; Sanchez, P del Amo; Ben-Haim, E; Bonneaud, G R; Briand, H; Chauveau, J; Hamon, O; Leruste, Ph; Marchiori, G; Ocariz, J; Perez, A; Prendki, J; Sitt, S; Gladney, L; Biasini, M; Manoni, E; Angelini, C; Batignani, G; Bettarini, S; Calderini, G; Carpinelli, M; Cervelli, A; Forti, F; Giorgi, M A; Lusiani, A; Morganti, M; Neri, N; Paoloni, E; Rizzo, G; Walsh, J J; Pegna, D Lopes; Lu, C; Olsen, J; Smith, A J S; Telnov, A V; Anulli, F; Baracchini, E; Cavoto, G; Faccini, R; Ferrarotto, F; Ferroni, F; Gaspero, M; Jackson, P D; Gioi, L Li; Mazzoni, M A; Morganti, S; Piredda, G; Renga, F; Voena, C; Ebert, M; Hartmann, T; Schröder, H; Waldi, R; Adye, T; Franek, B; Olaiya, E O; Wilson, F F; Emery, S; Esteve, L; de Monchenault, G Hamel; Kozanecki, W; Vasseur, G; Yèche, Ch; Zito, M; Allen, M T; Aston, D; Bartoldus, R; Benitez, J F; Cenci, R; Coleman, J P; Convery, M R; Dingfelder, J C; Dorfan, J; Dubois-Felsmann, G P; Dunwoodie, W; Field, R C; Sevilla, M Franco; Gabareen, A M; Graham, M T; Grenier, P; Hast, C; Innes, W R; Kaminski, J; Kelsey, M H; Kim, H; Kim, P; Kocian, M L; Leith, D W G S; Li, S; Lindquist, B; Luitz, S; Luth, V; Lynch, H L; MacFarlane, D B; Marsiske, H; Messner, R; Muller, D R; Neal, H; Nelson, S; O'Grady, C P; Ofte, I; Perl, M; Ratcliff, B N; Roodman, A; Salnikov, A A; Schindler, R H; Schwiening, J; Snyder, A; Su, D; Sullivan, M K; Suzuki, K; Swain, S K; Thompson, J M; Va'vra, J; Wagner, A P; Weaver, M; West, C A; Wisniewski, W J; Wittgen, M; Wright, D H; Wulsin, H W; Yarritu, A K; Young, C C; Ziegler, V; Chen, X R; Liu, H; Park, W; Purohit, M V; White, R M; Wilson, J R; Burchat, P R; Edwards, A J; Miyashita, T S; Ahmed, S; Alam, M S; Ernst, J A; Pan, B; Saeed, M A; Zain, S B; Soffer, A; Spanier, S M; Wogsland, B J; Eckmann, R; Ritchie, J L; Ruland, A M; Schilling, C J; Schwitters, R F; Wray, B C; Drummond, B W; Izen, J M; Lou, X C; Bianchi, F; Gamba, D; Pelliccioni, M; Bomben, M; Bosisio, L; Cartaro, C; Della Ricca, G; Lanceri, L; Vitale, L; Azzolini, V; Lopez-March, N; Martinez-Vidal, F; Milanes, D A; Oyanguren, A; Albert, J; Banerjee, Sw; Bhuyan, B; Choi, H H F; Hamano, K; King, G J; Kowalewski, R; Lewczuk, M J; Nugent, I M; Roney, J M; Sobie, R J; Gershon, T J; Harrison, P F; Ilic, J; Latham, T E; Mohanty, G B; Puccio, E M T; Band, H R; Chen, X; Dasu, S; Flood, K T; Pan, Y; Prepost, R; Vuosalo, C O; Wu, S L

2010-01-08

We present a measurement of the Cabibbo-Kobayashi-Maskawa matrix element |V(cb)| and the form-factor slope rho2 in B --> Dl- nu(l) decays based on 460x10(6) BB events recorded at the Upsilon(4S) resonance with the BABAR detector. B --> Dl- nu(l) decays are selected in events in which a hadronic decay of the second B meson is fully reconstructed. We measure B(B- --> D0 l- nu(l))/B(B- --> Xl- nu(l)) = (0.255+/-0.009+/-0.009) and B(B0 --> D+ l- nu(l))/B(B0 --> Xl- nu(l)) = (0.230+/-0.011+/-0.011), along with the differential decay distribution in B --> Dl- nu(l) decays. We then determine G(1)|V(cb)| = (42.3+/-1.9+/-1.4)x10(-3) and rho2 = 1.20+/-0.09+/-0.04, where G(1) is the hadronic form factor at the point of zero recoil.

Measurement of the e +e -→π +π - cross section between 600 and 900 MeV using initial state radiation

DOE PAGES

Ablikim, M.

2015-11-28

We extract the e +e -→π +π - cross section in the energy range between 600 and 900 MeV, exploiting the method of initial state radiation. A data set with an integrated luminosity of 2.93 fb -1 taken at a center-of-mass energy of 3.773 GeV with the BESIII detector at the BEPCII collider is used. The cross section is measured with a systematic uncertainty of 0.9%. We extract the pion form factor |F π| 2 as well as the contribution of the measured cross section to the leading-order hadronic vacuum polarization contribution to (g-2) μ. In conclusion, we find thismore » value to be a π μ π,LO (600–900 MeV) = (368.2 ±2.5 stat±3.3 sys) ·10 -10, which is between the corresponding values using the BaBar or KLOE data.« less

Measurement of partial branching fractions of inclusive charmless B meson decays to K+, K0, and π+

NASA Astrophysics Data System (ADS)

Del Amo Sanchez, P.; Lees, J. P.; Poireau, V.; Prencipe, E.; Tisserand, V.; Garra Tico, J.; Grauges, E.; Martinelli, M.; Milanes, D. A.; Palano, A.; Pappagallo, M.; Eigen, G.; Stugu, B.; Sun, L.; Brown, D. N.; Kerth, L. T.; Kolomensky, Yu. G.; Lynch, G.; Osipenkov, I. L.; Koch, H.; Schroeder, T.; Asgeirsson, D. J.; Hearty, C.; Mattison, T. S.; McKenna, J. A.; Khan, A.; Blinov, V. E.; Buzykaev, A. R.; Druzhinin, V. P.; Golubev, V. B.; Kravchenko, E. A.; Onuchin, A. P.; Serednyakov, S. I.; Skovpen, Yu. I.; Solodov, E. P.; Todyshev, K. Yu.; Yushkov, A. N.; Bondioli, M.; Curry, S.; Kirkby, D.; Lankford, A. J.; Mandelkern, M.; Martin, E. C.; Stoker, D. P.; Atmacan, H.; Gary, J. W.; Liu, F.; Long, O.; Vitug, G. M.; Campagnari, C.; Hong, T. M.; Kovalskyi, D.; Richman, J. D.; West, C. A.; Eisner, A. M.; Heusch, C. A.; Kroseberg, J.; Lockman, W. S.; Martinez, A. J.; Schalk, T.; Schumm, B. A.; Seiden, A.; Winstrom, L. O.; Cheng, C. H.; Doll, D. A.; Echenard, B.; Hitlin, D. G.; Ongmongkolkul, P.; Porter, F. C.; Rakitin, A. Y.; Andreassen, R.; Dubrovin, M. S.; Meadows, B. T.; Sokoloff, M. D.; Blanc, F.; Bloom, P. C.; Ford, W. T.; Gaz, A.; Nagel, M.; Nauenberg, U.; Smith, J. G.; Wagner, S. R.; Ayad, R.; Toki, W. H.; Jasper, H.; Petzold, A.; Spaan, B.; Kobel, M. J.; Schubert, K. R.; Schwierz, R.; Bernard, D.; Verderi, M.; Clark, P. J.; Playfer, S.; Watson, J. E.; Andreotti, M.; Bettoni, D.; Bozzi, C.; Calabrese, R.; Cecchi, A.; Cibinetto, G.; Fioravanti, E.; Franchini, P.; Garzia, I.; Luppi, E.; Munerato, M.; Negrini, M.; Petrella, A.; Piemontese, L.; Baldini-Ferroli, R.; Calcaterra, A.; de Sangro, R.; Finocchiaro, G.; Nicolaci, M.; Pacetti, S.; Patteri, P.; Peruzzi, I. M.; Piccolo, M.; Rama, M.; Zallo, A.; Contri, R.; Guido, E.; Lo Vetere, M.; Monge, M. R.; Passaggio, S.; Patrignani, C.; Robutti, E.; Bhuyan, B.; Prasad, V.; Lee, C. L.; Morii, M.; Edwards, A. J.; Adametz, A.; Marks, J.; Uwer, U.; Bernlochner, F. U.; Ebert, M.; Lacker, H. M.; Lueck, T.; Volk, A.; Dauncey, P. D.; Tibbetts, M.; Behera, P. K.; Mallik, U.; Chen, C.; Cochran, J.; Crawley, H. B.; Meyer, W. T.; Prell, S.; Rosenberg, E. I.; Rubin, A. E.; Gritsan, A. V.; Guo, Z. J.; Arnaud, N.; Davier, M.; Derkach, D.; Firmino da Costa, J.; Grosdidier, G.; Le Diberder, F.; Lutz, A. M.; Malaescu, B.; Perez, A.; Roudeau, P.; Schune, M. H.; Serrano, J.; Sordini, V.; Stocchi, A.; Wang, L.; Wormser, G.; Lange, D. J.; Wright, D. M.; Bingham, I.; Chavez, C. A.; Coleman, J. P.; Fry, J. R.; Gabathuler, E.; Hutchcroft, D. E.; Payne, D. J.; Touramanis, C.; Bevan, A. J.; di Lodovico, F.; Sacco, R.; Sigamani, M.; Cowan, G.; Paramesvaran, S.; Wren, A. C.; Brown, D. N.; Davis, C. L.; Denig, A. G.; Fritsch, M.; Gradl, W.; Hafner, A.; Alwyn, K. E.; Bailey, D.; Barlow, R. J.; Jackson, G.; Lafferty, G. D.; Anderson, J.; Cenci, R.; Jawahery, A.; Roberts, D. A.; Simi, G.; Tuggle, J. M.; Dallapiccola, C.; Salvati, E.; Cowan, R.; Dujmic, D.; Sciolla, G.; Zhao, M.; Lindemann, D.; Patel, P. M.; Robertson, S. H.; Schram, M.; Biassoni, P.; Lazzaro, A.; Lombardo, V.; Palombo, F.; Stracka, S.; Cremaldi, L.; Godang, R.; Kroeger, R.; Sonnek, P.; Summers, D. J.; Nguyen, X.; Simard, M.; Taras, P.; de Nardo, G.; Monorchio, D.; Onorato, G.; Sciacca, C.; Raven, G.; Snoek, H. L.; Jessop, C. P.; Knoepfel, K. J.; Losecco, J. M.; Wang, W. F.; Corwin, L. A.; Honscheid, K.; Kass, R.; Blount, N. L.; Brau, J.; Frey, R.; Igonkina, O.; Kolb, J. A.; Rahmat, R.; Sinev, N. B.; Strom, D.; Strube, J.; Torrence, E.; Castelli, G.; Feltresi, E.; Gagliardi, N.; Margoni, M.; Morandin, M.; Posocco, M.; Rotondo, M.; Simonetto, F.; Stroili, R.; Ben-Haim, E.; Bomben, M.; Bonneaud, G. R.; Briand, H.; Calderini, G.; Chauveau, J.; Hamon, O.; Leruste, Ph.; Marchiori, G.; Ocariz, J.; Prendki, J.; Sitt, S.; Biasini, M.; Manoni, E.; Rossi, A.; Angelini, C.; Batignani, G.; Bettarini, S.; Carpinelli, M.; Casarosa, G.; Cervelli, A.; Forti, F.; Giorgi, M. A.; Lusiani, A.; Neri, N.; Paoloni, E.; Rizzo, G.; Walsh, J. J.; Lopes Pegna, D.; Lu, C.; Olsen, J.; Smith, A. J. S.; Telnov, A. V.; Anulli, F.; Baracchini, E.; Cavoto, G.; Faccini, R.; Ferrarotto, F.; Ferroni, F.; Gaspero, M.; Li Gioi, L.; Mazzoni, M. A.; Piredda, G.; Renga, F.; Buenger, C.; Hartmann, T.; Leddig, T.; Schröder, H.; Waldi, R.; Adye, T.; Olaiya, E. O.; Wilson, F. F.; Emery, S.; Hamel de Monchenault, G.; Vasseur, G.; Yèche, Ch.; Allen, M. T.; Aston, D.; Bard, D. J.; Bartoldus, R.; Benitez, J. F.; Cartaro, C.; Convery, M. R.; Dorfan, J.; Dubois-Felsmann, G. P.; Dunwoodie, W.; Field, R. C.; Franco Sevilla, M.; Fulsom, B. G.; Gabareen, A. M.; Graham, M. T.; Grenier, P.; Hast, C.; Innes, W. R.; Kelsey, M. H.; Kim, H.; Kim, P.; Kocian, M. L.; Leith, D. W. G. S.; Lewis, P.; Li, S.; Lindquist, B.; Luitz, S.; Luth, V.; Lynch, H. L.; Macfarlane, D. B.; Muller, D. R.; Neal, H.; Nelson, S.; O'Grady, C. P.; Ofte, I.; Perl, M.; Pulliam, T.; Ratcliff, B. N.; Roodman, A.; Salnikov, A. A.; Santoro, V.; Schindler, R. H.; Schwiening, J.; Snyder, A.; Su, D.; Sullivan, M. K.; Sun, S.; Suzuki, K.; Thompson, J. M.; Va'Vra, J.; Wagner, A. P.; Weaver, M.; Wisniewski, W. J.; Wittgen, M.; Wright, D. H.; Wulsin, H. W.; Yarritu, A. K.; Young, C. C.; Ziegler, V.; Chen, X. R.; Park, W.; Purohit, M. V.; White, R. M.; Wilson, J. R.; Randle-Conde, A.; Sekula, S. J.; Bellis, M.; Burchat, P. R.; Miyashita, T. S.; Ahmed, S.; Alam, M. S.; Ernst, J. A.; Pan, B.; Saeed, M. A.; Zain, S. B.; Guttman, N.; Soffer, A.; Lund, P.; Spanier, S. M.; Eckmann, R.; Ritchie, J. L.; Ruland, A. M.; Schilling, C. J.; Schwitters, R. F.; Wray, B. C.; Izen, J. M.; Lou, X. C.; Bianchi, F.; Gamba, D.; Pelliccioni, M.; Lanceri, L.; Vitale, L.; Lopez-March, N.; Martinez-Vidal, F.; Oyanguren, A.; Ahmed, H.; Albert, J.; Banerjee, Sw.; Choi, H. H. F.; Hamano, K.; King, G. J.; Kowalewski, R.; Lewczuk, M. J.; Lindsay, C.; Nugent, I. M.; Roney, J. M.; Sobie, R. J.; Gershon, T. J.; Harrison, P. F.; Latham, T. E.; Puccio, E. M. T.; Band, H. R.; Dasu, S.; Flood, K. T.; Pan, Y.; Prepost, R.; Vuosalo, C. O.; Wu, S. L.

2011-02-01

We present measurements of partial branching fractions of B→K+X, B→K0X, and B→π+X, where X denotes any accessible final state above the endpoint for B decays to charmed mesons, specifically for momenta of the candidate hadron greater than 2.34 (2.36) GeV for kaons (pions) in the B rest frame. These measurements are sensitive to potential new-physics particles which could enter the b→s(d) loop transitions. The analysis is performed on a data sample consisting of 383×106BB¯ pairs collected with the BABAR detector at the PEP-II e+e- asymmetric energy collider. We observe the inclusive B→π+X process, and we set upper limits for B→K+X and B→K0X. Our results for these inclusive branching fractions are consistent with those of known exclusive modes, and exclude large enhancements due to sources of new physics.

Evidence for the hb(1P) meson in the decay Υ(3S)→π0hb(1P)

NASA Astrophysics Data System (ADS)

Lees, J. P.; Poireau, V.; Prencipe, E.; Tisserand, V.; Garra Tico, J.; Grauges, E.; Martinelli, M.; Milanes, D. A.; Palano, A.; Pappagallo, M.; Eigen, G.; Stugu, B.; Sun, L.; Brown, D. N.; Kerth, L. T.; Kolomensky, Yu. G.; Lynch, G.; Osipenkov, I. L.; Koch, H.; Schroeder, T.; Asgeirsson, D. J.; Hearty, C.; Mattison, T. S.; McKenna, J. A.; Khan, A.; Blinov, V. E.; Buzykaev, A. R.; Druzhinin, V. P.; Golubev, V. B.; Kravchenko, E. A.; Onuchin, A. P.; Serednyakov, S. I.; Skovpen, Yu. I.; Solodov, E. P.; Todyshev, K. Yu.; Yushkov, A. N.; Bondioli, M.; Curry, S.; Kirkby, D.; Lankford, A. J.; Mandelkern, M.; Stoker, D. P.; Atmacan, H.; Gary, J. W.; Liu, F.; Long, O.; Vitug, G. M.; Campagnari, C.; Hong, T. M.; Kovalskyi, D.; Richman, J. D.; West, C. A.; Eisner, A. M.; Kroseberg, J.; Lockman, W. S.; Martinez, A. J.; Schalk, T.; Schumm, B. A.; Seiden, A.; Cheng, C. H.; Doll, D. A.; Echenard, B.; Flood, K. T.; Hitlin, D. G.; Ongmongkolkul, P.; Porter, F. C.; Rakitin, A. Y.; Andreassen, R.; Dubrovin, M. S.; Meadows, B. T.; Sokoloff, M. D.; Bloom, P. C.; Ford, W. T.; Gaz, A.; Nagel, M.; Nauenberg, U.; Smith, J. G.; Wagner, S. R.; Ayad, R.; Toki, W. H.; Jasper, H.; Petzold, A.; Spaan, B.; Kobel, M. J.; Schubert, K. R.; Schwierz, R.; Bernard, D.; Verderi, M.; Clark, P. J.; Playfer, S.; Watson, J. E.; Bettoni, D.; Bozzi, C.; Calabrese, R.; Cibinetto, G.; Fioravanti, E.; Garzia, I.; Luppi, E.; Munerato, M.; Negrini, M.; Piemontese, L.; Baldini-Ferroli, R.; Calcaterra, A.; de Sangro, R.; Finocchiaro, G.; Nicolaci, M.; Pacetti, S.; Patteri, P.; Peruzzi, I. M.; Piccolo, M.; Rama, M.; Zallo, A.; Contri, R.; Guido, E.; Lo Vetere, M.; Monge, M. R.; Passaggio, S.; Patrignani, C.; Robutti, E.; Bhuyan, B.; Prasad, V.; Lee, C. L.; Morii, M.; Edwards, A. J.; Adametz, A.; Marks, J.; Uwer, U.; Bernlochner, F. U.; Ebert, M.; Lacker, H. M.; Lueck, T.; Dauncey, P. D.; Tibbetts, M.; Behera, P. K.; Mallik, U.; Chen, C.; Cochran, J.; Crawley, H. B.; Meyer, W. T.; Prell, S.; Rosenberg, E. I.; Rubin, A. E.; Gritsan, A. V.; Guo, Z. J.; Arnaud, N.; Davier, M.; Derkach, D.; Firmino da Costa, J.; Grosdidier, G.; Le Diberder, F.; Lutz, A. M.; Malaescu, B.; Perez, A.; Roudeau, P.; Schune, M. H.; Stocchi, A.; Wang, L.; Wormser, G.; Lange, D. J.; Wright, D. M.; Bingham, I.; Chavez, C. A.; Coleman, J. P.; Fry, J. R.; Gabathuler, E.; Hutchcroft, D. E.; Payne, D. J.; Touramanis, C.; Bevan, A. J.; di Lodovico, F.; Sacco, R.; Sigamani, M.; Cowan, G.; Paramesvaran, S.; Wren, A. C.; Brown, D. N.; Davis, C. L.; Denig, A. G.; Fritsch, M.; Gradl, W.; Hafner, A.; Alwyn, K. E.; Bailey, D.; Barlow, R. J.; Jackson, G.; Lafferty, G. D.; Cenci, R.; Hamilton, B.; Jawahery, A.; Roberts, D. A.; Simi, G.; Dallapiccola, C.; Salvati, E.; Cowan, R.; Dujmic, D.; Sciolla, G.; Lindemann, D.; Patel, P. M.; Robertson, S. H.; Schram, M.; Biassoni, P.; Lazzaro, A.; Lombardo, V.; Palombo, F.; Stracka, S.; Cremaldi, L.; Godang, R.; Kroeger, R.; Sonnek, P.; Summers, D. J.; Nguyen, X.; Taras, P.; de Nardo, G.; Monorchio, D.; Onorato, G.; Sciacca, C.; Raven, G.; Snoek, H. L.; Jessop, C. P.; Knoepfel, K. J.; Losecco, J. M.; Wang, W. F.; Corwin, L. A.; Honscheid, K.; Kass, R.; Blount, N. L.; Brau, J.; Frey, R.; Kolb, J. A.; Rahmat, R.; Sinev, N. B.; Strom, D.; Strube, J.; Torrence, E.; Castelli, G.; Feltresi, E.; Gagliardi, N.; Margoni, M.; Morandin, M.; Posocco, M.; Rotondo, M.; Simonetto, F.; Stroili, R.; Ben-Haim, E.; Bomben, M.; Bonneaud, G. R.; Briand, H.; Calderini, G.; Chauveau, J.; Hamon, O.; Leruste, Ph.; Marchiori, G.; Ocariz, J.; Sitt, S.; Biasini, M.; Manoni, E.; Rossi, A.; Angelini, C.; Batignani, G.; Bettarini, S.; Carpinelli, M.; Casarosa, G.; Cervelli, A.; Forti, F.; Giorgi, M. A.; Lusiani, A.; Neri, N.; Paoloni, E.; Rizzo, G.; Walsh, J. J.; Lopes Pegna, D.; Lu, C.; Olsen, J.; Smith, A. J. S.; Telnov, A. V.; Anulli, F.; Cavoto, G.; Faccini, R.; Ferrarotto, F.; Ferroni, F.; Gaspero, M.; Li Gioi, L.; Mazzoni, M. A.; Piredda, G.; Bünger, C.; Hartmann, T.; Leddig, T.; Schröder, H.; Waldi, R.; Adye, T.; Olaiya, E. O.; Wilson, F. F.; Emery, S.; Hamel de Monchenault, G.; Vasseur, G.; Yèche, Ch.; Allen, M. T.; Aston, D.; Bard, D. J.; Bartoldus, R.; Benitez, J. F.; Cartaro, C.; Convery, M. R.; Dorfan, J.; Dubois-Felsmann, G. P.; Dunwoodie, W.; Field, R. C.; Franco Sevilla, M.; Fulsom, B. G.; Gabareen, A. M.; Graham, M. T.; Grenier, P.; Hast, C.; Innes, W. R.; Kelsey, M. H.; Kim, H.; Kim, P.; Kocian, M. L.; Leith, D. W. G. S.; Lewis, P.; Li, S.; Lindquist, B.; Luitz, S.; Luth, V.; Lynch, H. L.; Macfarlane, D. B.; Muller, D. R.; Neal, H.; Nelson, S.; O'Grady, C. P.; Ofte, I.; Perl, M.; Pulliam, T.; Ratcliff, B. N.; Robertson, S. H.; Roodman, A.; Salnikov, A. A.; Santoro, V.; Schindler, R. H.; Schwiening, J.; Snyder, A.; Su, D.; Sullivan, M. K.; Sun, S.; Suzuki, K.; Thompson, J. M.; Va'Vra, J.; Wagner, A. P.; Weaver, M.; Wisniewski, W. J.; Wittgen, M.; Wright, D. H.; Wulsin, H. W.; Yarritu, A. K.; Young, C. C.; Ziegler, V.; Chen, X. R.; Park, W.; Purohit, M. V.; White, R. M.; Wilson, J. R.; Randle-Conde, A.; Sekula, S. J.; Bellis, M.; Burchat, P. R.; Miyashita, T. S.; Alam, M. S.; Ernst, J. A.; Guttman, N.; Soffer, A.; Lund, P.; Spanier, S. M.; Eckmann, R.; Ritchie, J. L.; Ruland, A. M.; Schilling, C. J.; Schwitters, R. F.; Wray, B. C.; Izen, J. M.; Lou, X. C.; Bianchi, F.; Gamba, D.; Pelliccioni, M.; Lanceri, L.; Vitale, L.; Lopez-March, N.; Martinez-Vidal, F.; Oyanguren, A.; Ahmed, H.; Albert, J.; Banerjee, Sw.; Choi, H. H. F.; Hamano, K.; King, G. J.; Kowalewski, R.; Lewczuk, M. J.; Lindsay, C.; Nugent, I. M.; Roney, J. M.; Sobie, R. J.; Gershon, T. J.; Harrison, P. F.; Latham, T. E.; Puccio, E. M. T.; Band, H. R.; Dasu, S.; Pan, Y.; Prepost, R.; Vuosalo, C. O.; Wu, S. L.

2011-11-01

Using a sample of 122×106 Υ(3S) events recorded with the BABAR detector at the PEP-II asymmetric-energy e+e- collider at SLAC, we search for the hb(1P) spin-singlet partner of the P-wave χbJ(1P) states in the sequential decay Υ(3S)→π0hb(1P), hb(1P)→γηb(1S). We observe an excess of events above background in the distribution of the recoil mass against the π0 at mass 9902±4(stat)±2(syst)MeV/c2. The width of the observed signal is consistent with experimental resolution, and its significance is 3.1σ, including systematic uncertainties. We obtain the value (4.3±1.1(stat)±0.9(syst))×10-4 for the product branching fraction B(Υ(3S)→π0hb)×B(hb→γηb).

Amplitude analysis of B0→K+π-π0 and evidence of direct CP violation in B→K*π decays

NASA Astrophysics Data System (ADS)

Lees, J. P.; Poireau, V.; Prencipe, E.; Tisserand, V.; Garra Tico, J.; Grauges, E.; Martinelli, M.; Milanes, D. A.; Palano, A.; Pappagallo, M.; Eigen, G.; Stugu, B.; Sun, L.; Brown, D. N.; Kerth, L. T.; Kolomensky, Yu. G.; Lynch, G.; Koch, H.; Schroeder, T.; Asgeirsson, D. J.; Hearty, C.; Mattison, T. S.; McKenna, J. A.; Khan, A.; Blinov, V. E.; Buzykaev, A. R.; Druzhinin, V. P.; Golubev, V. B.; Kravchenko, E. A.; Onuchin, A. P.; Serednyakov, S. I.; Skovpen, Yu. I.; Solodov, E. P.; Todyshev, K. Yu.; Yushkov, A. N.; Bondioli, M.; Curry, S.; Kirkby, D.; Lankford, A. J.; Mandelkern, M.; Stoker, D. P.; Atmacan, H.; Gary, J. W.; Liu, F.; Long, O.; Vitug, G. M.; Campagnari, C.; Hong, T. M.; Kovalskyi, D.; Richman, J. D.; West, C. A.; Eisner, A. M.; Kroseberg, J.; Lockman, W. S.; Martinez, A. J.; Schalk, T.; Schumm, B. A.; Seiden, A.; Cheng, C. H.; Doll, D. A.; Echenard, B.; Flood, K. T.; Hitlin, D. G.; Ongmongkolkul, P.; Porter, F. C.; Rakitin, A. Y.; Andreassen, R.; Dubrovin, M. S.; Meadows, B. T.; Sokoloff, M. D.; Bloom, P. C.; Ford, W. T.; Gaz, A.; Nagel, M.; Nauenberg, U.; Smith, J. G.; Wagner, S. R.; Ayad, R.; Toki, W. H.; Spaan, B.; Kobel, M. J.; Schubert, K. R.; Schwierz, R.; Bernard, D.; Verderi, M.; Clark, P. J.; Playfer, S.; Watson, J. E.; Bettoni, D.; Bozzi, C.; Calabrese, R.; Cibinetto, G.; Fioravanti, E.; Garzia, I.; Luppi, E.; Munerato, M.; Negrini, M.; Piemontese, L.; Baldini-Ferroli, R.; Calcaterra, A.; de Sangro, R.; Finocchiaro, G.; Nicolaci, M.; Pacetti, S.; Patteri, P.; Peruzzi, I. M.; Piccolo, M.; Rama, M.; Zallo, A.; Contri, R.; Guido, E.; Lo Vetere, M.; Monge, M. R.; Passaggio, S.; Patrignani, C.; Robutti, E.; Bhuyan, B.; Prasad, V.; Lee, C. L.; Morii, M.; Edwards, A. J.; Adametz, A.; Marks, J.; Uwer, U.; Bernlochner, F. U.; Ebert, M.; Lacker, H. M.; Lueck, T.; Dauncey, P. D.; Tibbetts, M.; Behera, P. K.; Mallik, U.; Chen, C.; Cochran, J.; Crawley, H. B.; Meyer, W. T.; Prell, S.; Rosenberg, E. I.; Rubin, A. E.; Gritsan, A. V.; Guo, Z. J.; Arnaud, N.; Davier, M.; Derkach, D.; Grosdidier, G.; Le Diberder, F.; Lutz, A. M.; Malaescu, B.; Roudeau, P.; Schune, M. H.; Stocchi, A.; Wormser, G.; Lange, D. J.; Wright, D. M.; Bingham, I.; Chavez, C. A.; Coleman, J. P.; Fry, J. R.; Gabathuler, E.; Hutchcroft, D. E.; Payne, D. J.; Touramanis, C.; Bevan, A. J.; di Lodovico, F.; Sacco, R.; Sigamani, M.; Cowan, G.; Paramesvaran, S.; Brown, D. N.; Davis, C. L.; Denig, A. G.; Fritsch, M.; Gradl, W.; Hafner, A.; Alwyn, K. E.; Bailey, D.; Barlow, R. J.; Jackson, G.; Lafferty, G. D.; Cenci, R.; Hamilton, B.; Jawahery, A.; Roberts, D. A.; Simi, G.; Dallapiccola, C.; Salvati, E.; Cowan, R.; Dujmic, D.; Sciolla, G.; Lindemann, D.; Patel, P. M.; Robertson, S. H.; Schram, M.; Biassoni, P.; Lazzaro, A.; Lombardo, V.; Palombo, F.; Stracka, S.; Cremaldi, L.; Godang, R.; Kroeger, R.; Sonnek, P.; Summers, D. J.; Nguyen, X.; Taras, P.; de Nardo, G.; Monorchio, D.; Onorato, G.; Sciacca, C.; Raven, G.; Snoek, H. L.; Jessop, C. P.; Knoepfel, K. J.; Losecco, J. M.; Wang, W. F.; Honscheid, K.; Kass, R.; Brau, J.; Frey, R.; Sinev, N. B.; Strom, D.; Torrence, E.; Feltresi, E.; Gagliardi, N.; Margoni, M.; Morandin, M.; Posocco, M.; Rotondo, M.; Simonetto, F.; Stroili, R.; Ben-Haim, E.; Bomben, M.; Bonneaud, G. R.; Briand, H.; Calderini, G.; Chauveau, J.; Hamon, O.; Leruste, Ph.; Marchiori, G.; Ocariz, J.; Sitt, S.; Biasini, M.; Manoni, E.; Rossi, A.; Angelini, C.; Batignani, G.; Bettarini, S.; Carpinelli, M.; Casarosa, G.; Cervelli, A.; Forti, F.; Giorgi, M. A.; Lusiani, A.; Neri, N.; Oberhof, B.; Paoloni, E.; Perez, A.; Rizzo, G.; Walsh, J. J.; Lopes Pegna, D.; Lu, C.; Olsen, J.; Smith, A. J. S.; Telnov, A. V.; Anulli, F.; Cavoto, G.; Faccini, R.; Ferrarotto, F.; Ferroni, F.; Gaspero, M.; Li Gioi, L.; Mazzoni, M. A.; Piredda, G.; Bünger, C.; Hartmann, T.; Leddig, T.; Schröder, H.; Waldi, R.; Adye, T.; Olaiya, E. O.; Wilson, F. F.; Emery, S.; Hamel de Monchenault, G.; Vasseur, G.; Yèche, Ch.; Aston, D.; Bard, D. J.; Bartoldus, R.; Benitez, J. F.; Cartaro, C.; Convery, M. R.; Dorfan, J.; Dubois-Felsmann, G. P.; Dunwoodie, W.; Field, R. C.; Franco Sevilla, M.; Fulsom, B. G.; Gabareen, A. M.; Graham, M. T.; Grenier, P.; Hast, C.; Innes, W. R.; Kelsey, M. H.; Kim, H.; Kim, P.; Kocian, M. L.; Leith, D. W. G. S.; Lewis, P.; Li, S.; Lindquist, B.; Luitz, S.; Luth, V.; Lynch, H. L.; Macfarlane, D. B.; Muller, D. R.; Neal, H.; Nelson, S.; Ofte, I.; Perl, M.; Pulliam, T.; Ratcliff, B. N.; Roodman, A.; Salnikov, A. A.; Santoro, V.; Schindler, R. H.; Snyder, A.; Su, D.; Sullivan, M. K.; Va'Vra, J.; Wagner, A. P.; Weaver, M.; Wisniewski, W. J.; Wittgen, M.; Wright, D. H.; Wulsin, H. W.; Yarritu, A. K.; Young, C. C.; Ziegler, V.; Park, W.; Purohit, M. V.; White, R. M.; Wilson, J. R.; Randle-Conde, A.; Sekula, S. J.; Bellis, M.; Burchat, P. R.; Miyashita, T. S.; Alam, M. S.; Ernst, J. A.; Gorodeisky, R.; Guttman, N.; Peimer, D. R.; Soffer, A.; Lund, P.; Spanier, S. M.; Eckmann, R.; Ritchie, J. L.; Ruland, A. M.; Schilling, C. J.; Schwitters, R. F.; Wray, B. C.; Izen, J. M.; Lou, X. C.; Bianchi, F.; Gamba, D.; Lanceri, L.; Vitale, L.; Lopez-March, N.; Martinez-Vidal, F.; Oyanguren, A.; Ahmed, H.; Albert, J.; Banerjee, Sw.; Choi, H. H. F.; King, G. J.; Kowalewski, R.; Lewczuk, M. J.; Lindsay, C.; Nugent, I. M.; Roney, J. M.; Sobie, R. J.; Gershon, T. J.; Harrison, P. F.; Latham, T. E.; Puccio, E. M. T.; Band, H. R.; Dasu, S.; Pan, Y.; Prepost, R.; Vuosalo, C. O.; Wu, S. L.

2011-06-01

We analyze the decay B0→K+π-π0 with a sample of 4.54×108 BB¯ events collected by the BABAR detector at the PEP-II asymmetric-energy B factory at SLAC, and extract the complex amplitudes of seven interfering resonances over the Dalitz plot. These results are combined with amplitudes measured in B0→KS0π+π- decays to construct isospin amplitudes from B0→K*π and B0→ρK decays. We measure the phase of the isospin amplitude Φ3/2, useful in constraining the Cabibbo-Kobayashi-Maskawa unitarity triangle angle γ and evaluate a CP rate asymmetry sum rule sensitive to the presence of new physics operators. We measure direct CP violation in B0→K*+π- decays at the level of 3σ when measurements from both B0→K+π-π0 and B0→KS0π+π- decays are combined.

Search for b→u transitions in B±→[K∓π±π0]DK± decays

NASA Astrophysics Data System (ADS)

Lees, J. P.; Poireau, V.; Tisserand, V.; Garra Tico, J.; Grauges, E.; Martinelli, M.; Milanes, D. A.; Palano, A.; Pappagallo, M.; Eigen, G.; Stugu, B.; Sun, L.; Brown, D. N.; Kerth, L. T.; Kolomensky, Yu. G.; Lynch, G.; Koch, H.; Schroeder, T.; Asgeirsson, D. J.; Hearty, C.; Mattison, T. S.; McKenna, J. A.; Khan, A.; Blinov, V. E.; Buzykaev, A. R.; Druzhinin, V. P.; Golubev, V. B.; Kravchenko, E. A.; Onuchin, A. P.; Serednyakov, S. I.; Skovpen, Yu. I.; Solodov, E. P.; Todyshev, K. Yu.; Yushkov, A. N.; Bondioli, M.; Curry, S.; Kirkby, D.; Lankford, A. J.; Mandelkern, M.; Stoker, D. P.; Atmacan, H.; Gary, J. W.; Liu, F.; Long, O.; Vitug, G. M.; Campagnari, C.; Hong, T. M.; Kovalskyi, D.; Richman, J. D.; West, C. A.; Eisner, A. M.; Kroseberg, J.; Lockman, W. S.; Martinez, A. J.; Schalk, T.; Schumm, B. A.; Seiden, A.; Cheng, C. H.; Doll, D. A.; Echenard, B.; Flood, K. T.; Hitlin, D. G.; Ongmongkolkul, P.; Porter, F. C.; Rakitin, A. Y.; Andreassen, R.; Dubrovin, M. S.; Meadows, B. T.; Sokoloff, M. D.; Bloom, P. C.; Ford, W. T.; Gaz, A.; Nagel, M.; Nauenberg, U.; Smith, J. G.; Wagner, S. R.; Ayad, R.; Toki, W. H.; Spaan, B.; Kobel, M. J.; Schubert, K. R.; Schwierz, R.; Bernard, D.; Verderi, M.; Clark, P. J.; Playfer, S.; Watson, J. E.; Bettoni, D.; Bozzi, C.; Calabrese, R.; Cibinetto, G.; Fioravanti, E.; Garzia, I.; Luppi, E.; Munerato, M.; Negrini, M.; Piemontese, L.; Baldini-Ferroli, R.; Calcaterra, A.; de Sangro, R.; Finocchiaro, G.; Nicolaci, M.; Pacetti, S.; Patteri, P.; Peruzzi, I. M.; Piccolo, M.; Rama, M.; Zallo, A.; Contri, R.; Guido, E.; Lo Vetere, M.; Monge, M. R.; Passaggio, S.; Patrignani, C.; Robutti, E.; Bhuyan, B.; Prasad, V.; Lee, C. L.; Morii, M.; Edwards, A. J.; Adametz, A.; Marks, J.; Uwer, U.; Bernlochner, F. U.; Ebert, M.; Lacker, H. M.; Lueck, T.; Dauncey, P. D.; Tibbetts, M.; Behera, P. K.; Mallik, U.; Chen, C.; Cochran, J.; Crawley, H. B.; Meyer, W. T.; Prell, S.; Rosenberg, E. I.; Rubin, A. E.; Gritsan, A. V.; Guo, Z. J.; Arnaud, N.; Davier, M.; Derkach, D.; Grosdidier, G.; Le Diberder, F.; Lutz, A. M.; Malaescu, B.; Roudeau, P.; Schune, M. H.; Stocchi, A.; Wormser, G.; Lange, D. J.; Wright, D. M.; Bingham, I.; Chavez, C. A.; Coleman, J. P.; Fry, J. R.; Gabathuler, E.; Hutchcroft, D. E.; Payne, D. J.; Touramanis, C.; Bevan, A. J.; di Lodovico, F.; Sacco, R.; Sigamani, M.; Cowan, G.; Paramesvaran, S.; Brown, D. N.; Davis, C. L.; Denig, A. G.; Fritsch, M.; Gradl, W.; Hafner, A.; Prencipe, E.; Alwyn, K. E.; Bailey, D.; Barlow, R. J.; Jackson, G.; Lafferty, G. D.; Cenci, R.; Hamilton, B.; Jawahery, A.; Roberts, D. A.; Simi, G.; Dallapiccola, C.; Cowan, R.; Dujmic, D.; Sciolla, G.; Lindemann, D.; Patel, P. M.; Robertson, S. H.; Schram, M.; Biassoni, P.; Lazzaro, A.; Lombardo, V.; Palombo, F.; Stracka, S.; Cremaldi, L.; Godang, R.; Kroeger, R.; Sonnek, P.; Summers, D. J.; Nguyen, X.; Taras, P.; de Nardo, G.; Monorchio, D.; Onorato, G.; Sciacca, C.; Raven, G.; Snoek, H. L.; Jessop, C. P.; Knoepfel, K. J.; Losecco, J. M.; Wang, W. F.; Honscheid, K.; Kass, R.; Brau, J.; Frey, R.; Sinev, N. B.; Strom, D.; Torrence, E.; Feltresi, E.; Gagliardi, N.; Margoni, M.; Morandin, M.; Posocco, M.; Rotondo, M.; Simonetto, F.; Stroili, R.; Ben-Haim, E.; Bomben, M.; Bonneaud, G. R.; Briand, H.; Calderini, G.; Chauveau, J.; Hamon, O.; Leruste, Ph.; Marchiori, G.; Ocariz, J.; Sitt, S.; Biasini, M.; Manoni, E.; Rossi, A.; Angelini, C.; Batignani, G.; Bettarini, S.; Carpinelli, M.; Casarosa, G.; Cervelli, A.; Forti, F.; Giorgi, M. A.; Lusiani, A.; Neri, N.; Oberhof, B.; Paoloni, E.; Perez, A.; Rizzo, G.; Walsh, J. J.; Lopes Pegna, D.; Lu, C.; Olsen, J.; Smith, A. J. S.; Telnov, A. V.; Anulli, F.; Cavoto, G.; Faccini, R.; Ferrarotto, F.; Ferroni, F.; Gaspero, M.; Li Gioi, L.; Mazzoni, M. A.; Piredda, G.; Buenger, C.; Hartmann, T.; Leddig, T.; Schröder, H.; Waldi, R.; Adye, T.; Olaiya, E. O.; Wilson, F. F.; Emery, S.; Hamel de Monchenault, G.; Vasseur, G.; Yèche, Ch.; Aston, D.; Bard, D. J.; Bartoldus, R.; Benitez, J. F.; Cartaro, C.; Convery, M. R.; Dorfan, J.; Dubois-Felsmann, G. P.; Dunwoodie, W.; Field, R. C.; Franco Sevilla, M.; Fulsom, B. G.; Gabareen, A. M.; Graham, M. T.; Grenier, P.; Hast, C.; Innes, W. R.; Kelsey, M. H.; Kim, H.; Kim, P.; Kocian, M. L.; Leith, D. W. G. S.; Lewis, P.; Li, S.; Lindquist, B.; Luitz, S.; Luth, V.; Lynch, H. L.; Macfarlane, D. B.; Muller, D. R.; Neal, H.; Nelson, S.; Ofte, I.; Perl, M.; Pulliam, T.; Ratcliff, B. N.; Roodman, A.; Salnikov, A. A.; Santoro, V.; Schindler, R. H.; Snyder, A.; Su, D.; Sullivan, M. K.; Va'Vra, J.; Wagner, A. P.; Weaver, M.; Wisniewski, W. J.; Wittgen, M.; Wright, D. H.; Wulsin, H. W.; Yarritu, A. K.; Young, C. C.; Ziegler, V.; Park, W.; Purohit, M. V.; White, R. M.; Wilson, J. R.; Randle-Conde, A.; Sekula, S. J.; Bellis, M.; Burchat, P. R.; Miyashita, T. S.; Alam, M. S.; Ernst, J. A.; Gorodeisky, R.; Guttman, N.; Peimer, D. R.; Soffer, A.; Lund, P.; Spanier, S. M.; Eckmann, R.; Ritchie, J. L.; Ruland, A. M.; Schilling, C. J.; Schwitters, R. F.; Wray, B. C.; Izen, J. M.; Lou, X. C.; Bianchi, F.; Gamba, D.; Lanceri, L.; Vitale, L.; Lopez-March, N.; Martinez-Vidal, F.; Oyanguren, A.; Ahmed, H.; Albert, J.; Banerjee, Sw.; Choi, H. H. F.; King, G. J.; Kowalewski, R.; Lewczuk, M. J.; Lindsay, C.; Nugent, I. M.; Roney, J. M.; Sobie, R. J.; Gershon, T. J.; Harrison, P. F.; Latham, T. E.; Puccio, E. M. T.; Band, H. R.; Dasu, S.; Pan, Y.; Prepost, R.; Vuosalo, C. O.; Wu, S. L.

2011-07-01

We present a study of the decays B±→DK± with D mesons reconstructed in the K+π-π0 or K-π+π0 final states, where D indicates a D0 or a D¯0 meson. Using a sample of 474×106 BB¯ pairs collected with the BABAR detector at the PEP-II asymmetric-energy e+e- collider at SLAC, we measure the ratios R±≡(Γ(B±→[K∓π±π0]DK±))/(Γ(B±→[K±π∓π0]DK±)). We obtain R+=(5-10+12(stat)-4+2(syst))×10-3 and R-=(12-10+12(stat)-5+3(syst))×10-3, from which we extract the upper limits at 90% probability: R+<23×10-3 and R-<29×10-3. Using these measurements, we obtain an upper limit for the ratio rB of the magnitudes of the b→u and b→c amplitudes rB<0.13 at 90% probability.

Study of the process e + e – → π + π – η using initial state radiation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lees, J. P.; Poireau, V.; Tisserand, V.

Here, we study the process e +e –→π +π –ηγ, where the photon is radiated from the initial state. About 8000 fully reconstructed events of this process are selected from the BABAR data sample with an integrated luminosity of 469 fb –1. Using the π +π –η invariant mass spectrum, we measure the e +e –→π +π –η cross section in the e +e – center-of-mass energy range from 1.15 to 3.5 GeV. The cross section is well described by the Vector-Meson dominance model with four ρ-like states. We observe 49±9 events of the J/ψ decay to π +π –ηmore » and measure the product Γ J/Ψ→e+e–BJ/Ψ→π+π–η=2.34±0.43 stat±0.16 syst eV.« less

Study of the process e + e – → π + π – η using initial state radiation

DOE PAGES

Lees, J. P.; Poireau, V.; Tisserand, V.; ...

2018-03-21

Here, we study the process e +e –→π +π –ηγ, where the photon is radiated from the initial state. About 8000 fully reconstructed events of this process are selected from the BABAR data sample with an integrated luminosity of 469 fb –1. Using the π +π –η invariant mass spectrum, we measure the e +e –→π +π –η cross section in the e +e – center-of-mass energy range from 1.15 to 3.5 GeV. The cross section is well described by the Vector-Meson dominance model with four ρ-like states. We observe 49±9 events of the J/ψ decay to π +π –ηmore » and measure the product Γ J/Ψ→e+e–BJ/Ψ→π+π–η=2.34±0.43 stat±0.16 syst eV.« less

A study of B0-B0(bar) oscillations frequency and determination of flavor-tagging efficiency using semileptonic and hadronic B0 decays

DOE Office of Scientific and Technical Information (OSTI.GOV)

Barrera, Barbara

B{sup 0}{bar B}{sup 0} flavor oscillations are studied in e{sup +}e{sup -} annihilation data collected with the BABAR detector at center-of-mass energies near the {Upsilon}(4S) resonance. One B is reconstructed in a hadronic or semileptonic decay mode, and the flavor of the other B in the event is determined with a tagging algorithm that exploits the relation between the flavor of the heavy quark and the charges of its decay products. Tagging performance is characterized by an efficiency {epsilon}{sub i} and a probability for mis-identification, w{sub i}, for each tagging category. We report a determination of the wrong-tag probabilities, w{submore » i}, and a preliminary result for the time-dependent B{sup 0}{bar B}{sup 0} oscillation frequency, {Delta}m{sub d} = 0.512 {+-} 0.017 {+-} 0.022 {Dirac_h} ps{sup -1}.« less

Workshop on Pion-Kaon Interactions (PKI2018) Mini-Proceedings

DOE Office of Scientific and Technical Information (OSTI.GOV)

Amaryan, M; Pal, Bilas

This volume is a short summary of talks given at the PKI2018 Workshop organized to discuss current status and future prospects of pi -K interactions. The precise data on pi K interaction will have a strong impact on strange meson spectroscopy and form factors that are important ingredients in the Dalitz plot analysis of a decays of heavy mesons as well as precision measurement of Vus matrix element and therefore on a test of unitarity in the first raw of the CKM matrix. The workshop has combined the efforts of experimentalists, Lattice QCD, and phenomenology communities. Experimental data relevant tomore » the topic of the workshop were presented from the broad range of different collaborations like CLAS, GlueX, COMPASS, BaBar, BELLE, BESIII, VEPP-2000, and LHCb. One of the main goals of this workshop was to outline a need for a new high intensity and high precision secondary KL beam facility at JLab produced with the 12 GeV electron beam of CEBAF accelerator.« less

Estimation of parameters of dose volume models and their confidence limits

NASA Astrophysics Data System (ADS)

van Luijk, P.; Delvigne, T. C.; Schilstra, C.; Schippers, J. M.

2003-07-01

Predictions of the normal-tissue complication probability (NTCP) for the ranking of treatment plans are based on fits of dose-volume models to clinical and/or experimental data. In the literature several different fit methods are used. In this work frequently used methods and techniques to fit NTCP models to dose response data for establishing dose-volume effects, are discussed. The techniques are tested for their usability with dose-volume data and NTCP models. Different methods to estimate the confidence intervals of the model parameters are part of this study. From a critical-volume (CV) model with biologically realistic parameters a primary dataset was generated, serving as the reference for this study and describable by the NTCP model. The CV model was fitted to this dataset. From the resulting parameters and the CV model, 1000 secondary datasets were generated by Monte Carlo simulation. All secondary datasets were fitted to obtain 1000 parameter sets of the CV model. Thus the 'real' spread in fit results due to statistical spreading in the data is obtained and has been compared with estimates of the confidence intervals obtained by different methods applied to the primary dataset. The confidence limits of the parameters of one dataset were estimated using the methods, employing the covariance matrix, the jackknife method and directly from the likelihood landscape. These results were compared with the spread of the parameters, obtained from the secondary parameter sets. For the estimation of confidence intervals on NTCP predictions, three methods were tested. Firstly, propagation of errors using the covariance matrix was used. Secondly, the meaning of the width of a bundle of curves that resulted from parameters that were within the one standard deviation region in the likelihood space was investigated. Thirdly, many parameter sets and their likelihood were used to create a likelihood-weighted probability distribution of the NTCP. It is concluded that for the type of dose response data used here, only a full likelihood analysis will produce reliable results. The often-used approximations, such as the usage of the covariance matrix, produce inconsistent confidence limits on both the parameter sets and the resulting NTCP values.

Semantic relatedness and similarity of biomedical terms: examining the effects of recency, size, and section of biomedical publications on the performance of word2vec.

PubMed

Zhu, Yongjun; Yan, Erjia; Wang, Fei

2017-07-03

Understanding semantic relatedness and similarity between biomedical terms has a great impact on a variety of applications such as biomedical information retrieval, information extraction, and recommender systems. The objective of this study is to examine word2vec's ability in deriving semantic relatedness and similarity between biomedical terms from large publication data. Specifically, we focus on the effects of recency, size, and section of biomedical publication data on the performance of word2vec. We download abstracts of 18,777,129 articles from PubMed and 766,326 full-text articles from PubMed Central (PMC). The datasets are preprocessed and grouped into subsets by recency, size, and section. Word2vec models are trained on these subtests. Cosine similarities between biomedical terms obtained from the word2vec models are compared against reference standards. Performance of models trained on different subsets are compared to examine recency, size, and section effects. Models trained on recent datasets did not boost the performance. Models trained on larger datasets identified more pairs of biomedical terms than models trained on smaller datasets in relatedness task (from 368 at the 10% level to 494 at the 100% level) and similarity task (from 374 at the 10% level to 491 at the 100% level). The model trained on abstracts produced results that have higher correlations with the reference standards than the one trained on article bodies (i.e., 0.65 vs. 0.62 in the similarity task and 0.66 vs. 0.59 in the relatedness task). However, the latter identified more pairs of biomedical terms than the former (i.e., 344 vs. 498 in the similarity task and 339 vs. 503 in the relatedness task). Increasing the size of dataset does not always enhance the performance. Increasing the size of datasets can result in the identification of more relations of biomedical terms even though it does not guarantee better precision. As summaries of research articles, compared with article bodies, abstracts excel in accuracy but lose in coverage of identifiable relations.

VIPER: a visualisation tool for exploring inheritance inconsistencies in genotyped pedigrees

PubMed Central

2012-01-01

Background Pedigree genotype datasets are used for analysing genetic inheritance and to map genetic markers and traits. Such datasets consist of hundreds of related animals genotyped for thousands of genetic markers and invariably contain multiple errors in both the pedigree structure and in the associated individual genotype data. These errors manifest as apparent inheritance inconsistencies in the pedigree, and invalidate analyses of marker inheritance patterns across the dataset. Cleaning raw datasets of bad data points (incorrect pedigree relationships, unreliable marker assays, suspect samples, bad genotype results etc.) requires expert exploration of the patterns of exposed inconsistencies in the context of the inheritance pedigree. In order to assist this process we are developing VIPER (Visual Pedigree Explorer), a software tool that integrates an inheritance-checking algorithm with a novel space-efficient pedigree visualisation, so that reported inheritance inconsistencies are overlaid on an interactive, navigable representation of the pedigree structure. Methods and results This paper describes an evaluation of how VIPER displays the different scales and types of dataset that occur experimentally, with a description of how VIPER's display interface and functionality meet the challenges presented by such data. We examine a range of possible error types found in real and simulated pedigree genotype datasets, demonstrating how these errors are exposed and explored using the VIPER interface and we evaluate the utility and usability of the interface to the domain expert. Evaluation was performed as a two stage process with the assistance of domain experts (geneticists). The initial evaluation drove the iterative implementation of further features in the software prototype, as required by the users, prior to a final functional evaluation of the pedigree display for exploring the various error types, data scales and structures. Conclusions The VIPER display was shown to effectively expose the range of errors found in experimental genotyped pedigrees, allowing users to explore the underlying causes of reported inheritance inconsistencies. This interface will provide the basis for a full data cleaning tool that will allow the user to remove isolated bad data points, and reversibly test the effect of removing suspect genotypes and pedigree relationships. PMID:22607476

Assessment of Full and Compact Polarimetric SAR Observations for Land-Cover and Crop Classification

NASA Astrophysics Data System (ADS)

Nafari, Nima Fallah; Homayouni, Saeid; Safari, Abdolreza; Akbari, Vahid

2016-08-01

The recently developed compact polarimetric (CP) synthetic aperture radar (SAR) data tend to confer a valuable source of information -comparable to full polarimetric (FP) data- in many applications. However, this assertion still needs confirmation in practice. This paper evaluates the potential of FP and CP data in land- cover and crop classification and determines the prospects of CP data in such applications. To this end, two data sets including full polarimetric L-band data from UAVSAR, acquired over an agricultural area in Winnipeg (Canada), and full polarimetric C-band data acquired by RADARSAT-2 over San Francisco are used. CP data are simulated from the FP data of the both datasets and classified by the support vector machine (SVM) algorithm. Based on the results, CP system with a simpler design compared to FP system still has the potential to be used as an alternative when a larger swath width is required.

3-D interactive visualisation tools for Hi spectral line imaging

NASA Astrophysics Data System (ADS)

van der Hulst, J. M.; Punzo, D.; Roerdink, J. B. T. M.

2017-06-01

Upcoming HI surveys will deliver such large datasets that automated processing using the full 3-D information to find and characterize HI objects is unavoidable. Full 3-D visualization is an essential tool for enabling qualitative and quantitative inspection and analysis of the 3-D data, which is often complex in nature. Here we present SlicerAstro, an open-source extension of 3DSlicer, a multi-platform open source software package for visualization and medical image processing, which we developed for the inspection and analysis of HI spectral line data. We describe its initial capabilities, including 3-D filtering, 3-D selection and comparative modelling.

The Role of Work Experiences in College Student Leadership Development: Evidence from a National Dataset and a Text Mining Approach to Examining Beliefs about Leadership

ERIC Educational Resources Information Center

Lewis, Jonathan S.

2017-01-01

Paid employment is one of the most common extracurricular activities among full-time undergraduates, and an array of studies has attempted to measure its impact. Methodological concerns with the extant literature, however, make it difficult to draw reliable conclusions. Furthermore, the research on working college students has little to say about…

A cross-national study on the multidimensional characteristics of the five-item psychological demands scale of the Job Content Questionnaire.

PubMed

Choi, BongKyoo; Kawakami, Norito; Chang, SeiJin; Koh, SangBaek; Bjorner, Jakob; Punnett, Laura; Karasek, Robert

2008-01-01

The five-item psychological demands scale of the Job Content Questionnaire (JCQ) has been assumed to be one-dimensional in practice. To examine whether the scale has sufficient internal consistency and external validity to be treated as a single scale, using the cross-national JCQ datasets from the United States, Korea, and Japan. Exploratory factor analyses with 22 JCQ items, confirmatory factor analyses with the five psychological demands items, and correlations analyses with mental health indexes. Generally, exploratory factor analyses displayed the predicted demand/control/support structure with three and four factors extracted. However, at more detailed levels of exploratory and confirmatory factor analyses, the demands scale showed clear evidence of multi-factor structure. The correlations of items and subscales of the demands scale with mental health indexes were similar to those of the full scale in the Korean and Japanese datasets, but not in the U.S. data. In 4 out of 16 sub-samples of the U.S. data, several significant correlations of the components of the demands scale with job dissatisfaction and life dissatisfaction were obscured by the full scale. The multidimensionality of the psychological demands scale should be considered in psychometric analysis and interpretation, occupational epidemiologic studies, and future scale extension.

Hemispheric Patterns in Electric Current Helicity of Solar Magnetic Fields During Solar Cycle 24: Results from SOLIS, SDO and Hinode

NASA Astrophysics Data System (ADS)

Gusain, S.

2017-12-01

We study the hemispheric patterns in electric current helicity distribution on the Sun. Magnetic field vector in the photosphere is now routinely measured by variety of instruments. SOLIS/VSM of NSO observes full disk Stokes spectra in photospheric lines which are used to derive vector magnetograms. Hinode SP is a space based spectropolarimeter which has the same observable as SOLIS albeit with limited field-of-view (FOV) but high spatial resolution. SDO/HMI derives vector magnetograms from full disk Stokes measurements, with rather limited spectral resolution, from space in a different photospheric line. Further, these datasets now exist for several years. SOLIS/VSM from 2003, Hinode SP from 2006, and SDO HMI since 2010. Using these time series of vector magnetograms we compute the electric current density in active regions during solar cycle 24 and study the hemispheric distributions. Many studies show that the helicity parameters and proxies show a strong hemispheric bias, such that Northern hemisphere has preferentially negative and southern positive helicity, respectively. We will confirm these results for cycle 24 from three different datasets and evaluate the statistical significance of the hemispheric bias. Further, we discuss the solar cycle variation in the hemispheric helicity pattern during cycle 24 and discuss its implications in terms of solar dynamo models.

Do Photovoltaic Energy Systems Effect Residential Selling Prices? Results from a California Statewide Investigation.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hoen, Ben; Cappers, Pete; Wiser, Ryan

2011-04-12

An increasing number of homes in the U.S. have sold with photovoltaic (PV) energy systems installed at the time of sale, yet relatively little research exists that provides estimates of the marginal impacts of those PV systems on home sale prices. This research analyzes a large dataset of California homes that sold from 2000 through mid-2009 with PV installed. We find strong evidence that homes with PV systems sold for a premium over comparable homes without PV systems during this time frame. Estimates for this premium expressed in dollars per watt of installed PV range, from roughly $4 to $6.4/wattmore » across the full dataset, to approximately $2.3/watt for new homes, to more than $6/watt for existing homes. A number of ideas for further research are suggested.« less

Compression of head-related transfer function using autoregressive-moving-average models and Legendre polynomials.

PubMed

Shekarchi, Sayedali; Hallam, John; Christensen-Dalsgaard, Jakob

2013-11-01

Head-related transfer functions (HRTFs) are generally large datasets, which can be an important constraint for embedded real-time applications. A method is proposed here to reduce redundancy and compress the datasets. In this method, HRTFs are first compressed by conversion into autoregressive-moving-average (ARMA) filters whose coefficients are calculated using Prony's method. Such filters are specified by a few coefficients which can generate the full head-related impulse responses (HRIRs). Next, Legendre polynomials (LPs) are used to compress the ARMA filter coefficients. LPs are derived on the sphere and form an orthonormal basis set for spherical functions. Higher-order LPs capture increasingly fine spatial details. The number of LPs needed to represent an HRTF, therefore, is indicative of its spatial complexity. The results indicate that compression ratios can exceed 98% while maintaining a spectral error of less than 4 dB in the recovered HRTFs.

Partitioning-based mechanisms under personalized differential privacy.

PubMed

Li, Haoran; Xiong, Li; Ji, Zhanglong; Jiang, Xiaoqian

2017-05-01

Differential privacy has recently emerged in private statistical aggregate analysis as one of the strongest privacy guarantees. A limitation of the model is that it provides the same privacy protection for all individuals in the database. However, it is common that data owners may have different privacy preferences for their data. Consequently, a global differential privacy parameter may provide excessive privacy protection for some users, while insufficient for others. In this paper, we propose two partitioning-based mechanisms, privacy-aware and utility-based partitioning, to handle personalized differential privacy parameters for each individual in a dataset while maximizing utility of the differentially private computation. The privacy-aware partitioning is to minimize the privacy budget waste, while utility-based partitioning is to maximize the utility for a given aggregate analysis. We also develop a t -round partitioning to take full advantage of remaining privacy budgets. Extensive experiments using real datasets show the effectiveness of our partitioning mechanisms.

A Noise-Filtered Under-Sampling Scheme for Imbalanced Classification.

PubMed

Kang, Qi; Chen, XiaoShuang; Li, SiSi; Zhou, MengChu

2017-12-01

Under-sampling is a popular data preprocessing method in dealing with class imbalance problems, with the purposes of balancing datasets to achieve a high classification rate and avoiding the bias toward majority class examples. It always uses full minority data in a training dataset. However, some noisy minority examples may reduce the performance of classifiers. In this paper, a new under-sampling scheme is proposed by incorporating a noise filter before executing resampling. In order to verify the efficiency, this scheme is implemented based on four popular under-sampling methods, i.e., Undersampling + Adaboost, RUSBoost, UnderBagging, and EasyEnsemble through benchmarks and significance analysis. Furthermore, this paper also summarizes the relationship between algorithm performance and imbalanced ratio. Experimental results indicate that the proposed scheme can improve the original undersampling-based methods with significance in terms of three popular metrics for imbalanced classification, i.e., the area under the curve, -measure, and -mean.

On macromolecular refinement at subatomic resolution withinteratomic scatterers

DOE Office of Scientific and Technical Information (OSTI.GOV)

Afonine, Pavel V.; Grosse-Kunstleve, Ralf W.; Adams, Paul D.

2007-11-09

A study of the accurate electron density distribution in molecular crystals at subatomic resolution, better than {approx} 1.0 {angstrom}, requires more detailed models than those based on independent spherical atoms. A tool conventionally used in small-molecule crystallography is the multipolar model. Even at upper resolution limits of 0.8-1.0 {angstrom}, the number of experimental data is insufficient for the full multipolar model refinement. As an alternative, a simpler model composed of conventional independent spherical atoms augmented by additional scatterers to model bonding effects has been proposed. Refinement of these mixed models for several benchmark datasets gave results comparable in quality withmore » results of multipolar refinement and superior of those for conventional models. Applications to several datasets of both small- and macro-molecules are shown. These refinements were performed using the general-purpose macromolecular refinement module phenix.refine of the PHENIX package.« less

IM-TORNADO: a tool for comparison of 16S reads from paired-end libraries.

PubMed

Jeraldo, Patricio; Kalari, Krishna; Chen, Xianfeng; Bhavsar, Jaysheel; Mangalam, Ashutosh; White, Bryan; Nelson, Heidi; Kocher, Jean-Pierre; Chia, Nicholas

2014-01-01

16S rDNA hypervariable tag sequencing has become the de facto method for accessing microbial diversity. Illumina paired-end sequencing, which produces two separate reads for each DNA fragment, has become the platform of choice for this application. However, when the two reads do not overlap, existing computational pipelines analyze data from read separately and underutilize the information contained in the paired-end reads. We created a workflow known as Illinois Mayo Taxon Organization from RNA Dataset Operations (IM-TORNADO) for processing non-overlapping reads while retaining maximal information content. Using synthetic mock datasets, we show that the use of both reads produced answers with greater correlation to those from full length 16S rDNA when looking at taxonomy, phylogeny, and beta-diversity. IM-TORNADO is freely available at http://sourceforge.net/projects/imtornado and produces BIOM format output for cross compatibility with other pipelines such as QIIME, mothur, and phyloseq.

Partitioning-based mechanisms under personalized differential privacy

PubMed Central

Li, Haoran; Xiong, Li; Ji, Zhanglong; Jiang, Xiaoqian

2017-01-01

Differential privacy has recently emerged in private statistical aggregate analysis as one of the strongest privacy guarantees. A limitation of the model is that it provides the same privacy protection for all individuals in the database. However, it is common that data owners may have different privacy preferences for their data. Consequently, a global differential privacy parameter may provide excessive privacy protection for some users, while insufficient for others. In this paper, we propose two partitioning-based mechanisms, privacy-aware and utility-based partitioning, to handle personalized differential privacy parameters for each individual in a dataset while maximizing utility of the differentially private computation. The privacy-aware partitioning is to minimize the privacy budget waste, while utility-based partitioning is to maximize the utility for a given aggregate analysis. We also develop a t-round partitioning to take full advantage of remaining privacy budgets. Extensive experiments using real datasets show the effectiveness of our partitioning mechanisms. PMID:28932827

QuIN: A Web Server for Querying and Visualizing Chromatin Interaction Networks.

PubMed

Thibodeau, Asa; Márquez, Eladio J; Luo, Oscar; Ruan, Yijun; Menghi, Francesca; Shin, Dong-Guk; Stitzel, Michael L; Vera-Licona, Paola; Ucar, Duygu

2016-06-01

Recent studies of the human genome have indicated that regulatory elements (e.g. promoters and enhancers) at distal genomic locations can interact with each other via chromatin folding and affect gene expression levels. Genomic technologies for mapping interactions between DNA regions, e.g., ChIA-PET and HiC, can generate genome-wide maps of interactions between regulatory elements. These interaction datasets are important resources to infer distal gene targets of non-coding regulatory elements and to facilitate prioritization of critical loci for important cellular functions. With the increasing diversity and complexity of genomic information and public ontologies, making sense of these datasets demands integrative and easy-to-use software tools. Moreover, network representation of chromatin interaction maps enables effective data visualization, integration, and mining. Currently, there is no software that can take full advantage of network theory approaches for the analysis of chromatin interaction datasets. To fill this gap, we developed a web-based application, QuIN, which enables: 1) building and visualizing chromatin interaction networks, 2) annotating networks with user-provided private and publicly available functional genomics and interaction datasets, 3) querying network components based on gene name or chromosome location, and 4) utilizing network based measures to identify and prioritize critical regulatory targets and their direct and indirect interactions. QuIN's web server is available at http://quin.jax.org QuIN is developed in Java and JavaScript, utilizing an Apache Tomcat web server and MySQL database and the source code is available under the GPLV3 license available on GitHub: https://github.com/UcarLab/QuIN/.

Ontology-based meta-analysis of global collections of high-throughput public data.

PubMed

Kupershmidt, Ilya; Su, Qiaojuan Jane; Grewal, Anoop; Sundaresh, Suman; Halperin, Inbal; Flynn, James; Shekar, Mamatha; Wang, Helen; Park, Jenny; Cui, Wenwu; Wall, Gregory D; Wisotzkey, Robert; Alag, Satnam; Akhtari, Saeid; Ronaghi, Mostafa

2010-09-29

The investigation of the interconnections between the molecular and genetic events that govern biological systems is essential if we are to understand the development of disease and design effective novel treatments. Microarray and next-generation sequencing technologies have the potential to provide this information. However, taking full advantage of these approaches requires that biological connections be made across large quantities of highly heterogeneous genomic datasets. Leveraging the increasingly huge quantities of genomic data in the public domain is fast becoming one of the key challenges in the research community today. We have developed a novel data mining framework that enables researchers to use this growing collection of public high-throughput data to investigate any set of genes or proteins. The connectivity between molecular states across thousands of heterogeneous datasets from microarrays and other genomic platforms is determined through a combination of rank-based enrichment statistics, meta-analyses, and biomedical ontologies. We address data quality concerns through dataset replication and meta-analysis and ensure that the majority of the findings are derived using multiple lines of evidence. As an example of our strategy and the utility of this framework, we apply our data mining approach to explore the biology of brown fat within the context of the thousands of publicly available gene expression datasets. Our work presents a practical strategy for organizing, mining, and correlating global collections of large-scale genomic data to explore normal and disease biology. Using a hypothesis-free approach, we demonstrate how a data-driven analysis across very large collections of genomic data can reveal novel discoveries and evidence to support existing hypothesis.

Defining upper gastrointestinal bleeding from linked primary and secondary care data and the effect on occurrence and 28 day mortality

PubMed Central

2012-01-01

Background Primary care records from the UK have frequently been used to identify episodes of upper gastrointestinal bleeding in studies of drug toxicity because of their comprehensive population coverage and longitudinal recording of prescriptions and diagnoses. Recent linkage within England of primary and secondary care data has augmented this data but the timing and coding of concurrent events, and how the definition of events in linked data effects occurrence and 28 day mortality is not known. Methods We used the recently linked English Hospital Episodes Statistics and General Practice Research Database, 1997–2010, to define events by; a specific upper gastrointestinal bleed code in either dataset, a specific bleed code in both datasets, or a less specific but plausible code from the linked dataset. Results This approach resulted in 81% of secondary care defined bleeds having a corresponding plausible code within 2 months in primary care. However only 62% of primary care defined bleeds had a corresponding plausible HES admission within 2 months. The more restrictive and specific case definitions excluded severe events and almost halved the 28 day case fatality when compared to broader and more sensitive definitions. Conclusions Restrictive definitions of gastrointestinal bleeding in linked datasets fail to capture the full heterogeneity in coding possible following complex clinical events. Conversely too broad a definition in primary care introduces events not severe enough to warrant hospital admission. Ignoring these issues may unwittingly introduce selection bias into a study’s results. PMID:23148590

Experiences and lessons learned from creating a generalized workflow for data publication of field campaign datasets

NASA Astrophysics Data System (ADS)

Santhana Vannan, S. K.; Ramachandran, R.; Deb, D.; Beaty, T.; Wright, D.

2017-12-01

This paper summarizes the workflow challenges of curating and publishing data produced from disparate data sources and provides a generalized workflow solution to efficiently archive data generated by researchers. The Oak Ridge National Laboratory Distributed Active Archive Center (ORNL DAAC) for biogeochemical dynamics and the Global Hydrology Resource Center (GHRC) DAAC have been collaborating on the development of a generalized workflow solution to efficiently manage the data publication process. The generalized workflow presented here are built on lessons learned from implementations of the workflow system. Data publication consists of the following steps: Accepting the data package from the data providers, ensuring the full integrity of the data files. Identifying and addressing data quality issues Assembling standardized, detailed metadata and documentation, including file level details, processing methodology, and characteristics of data files Setting up data access mechanisms Setup of the data in data tools and services for improved data dissemination and user experience Registering the dataset in online search and discovery catalogues Preserving the data location through Digital Object Identifiers (DOI) We will describe the steps taken to automate, and realize efficiencies to the above process. The goals of the workflow system are to reduce the time taken to publish a dataset, to increase the quality of documentation and metadata, and to track individual datasets through the data curation process. Utilities developed to achieve these goal will be described. We will also share metrics driven value of the workflow system and discuss the future steps towards creation of a common software framework.

Calibration of limited-area ensemble precipitation forecasts for hydrological predictions

NASA Astrophysics Data System (ADS)

Diomede, Tommaso; Marsigli, Chiara; Montani, Andrea; Nerozzi, Fabrizio; Paccagnella, Tiziana

2015-04-01

The main objective of this study is to investigate the impact of calibration for limited-area ensemble precipitation forecasts, to be used for driving discharge predictions up to 5 days in advance. A reforecast dataset, which spans 30 years, based on the Consortium for Small Scale Modeling Limited-Area Ensemble Prediction System (COSMO-LEPS) was used for testing the calibration strategy. Three calibration techniques were applied: quantile-to-quantile mapping, linear regression, and analogs. The performance of these methodologies was evaluated in terms of statistical scores for the precipitation forecasts operationally provided by COSMO-LEPS in the years 2003-2007 over Germany, Switzerland, and the Emilia-Romagna region (northern Italy). The analog-based method seemed to be preferred because of its capability of correct position errors and spread deficiencies. A suitable spatial domain for the analog search can help to handle model spatial errors as systematic errors. However, the performance of the analog-based method may degrade in cases where a limited training dataset is available. A sensitivity test on the length of the training dataset over which to perform the analog search has been performed. The quantile-to-quantile mapping and linear regression methods were less effective, mainly because the forecast-analysis relation was not so strong for the available training dataset. A comparison between the calibration based on the deterministic reforecast and the calibration based on the full operational ensemble used as training dataset has been considered, with the aim to evaluate whether reforecasts are really worthy for calibration, given that their computational cost is remarkable. The verification of the calibration process was then performed by coupling ensemble precipitation forecasts with a distributed rainfall-runoff model. This test was carried out for a medium-sized catchment located in Emilia-Romagna, showing a beneficial impact of the analog-based method on the reduction of missed events for discharge predictions.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lopez Torres, E., E-mail: Ernesto.Lopez.Torres@cern.ch, E-mail: cerello@to.infn.it; Fiorina, E.; Pennazio, F.

Purpose: M5L, a fully automated computer-aided detection (CAD) system for the detection and segmentation of lung nodules in thoracic computed tomography (CT), is presented and validated on several image datasets. Methods: M5L is the combination of two independent subsystems, based on the Channeler Ant Model as a segmentation tool [lung channeler ant model (lungCAM)] and on the voxel-based neural approach. The lungCAM was upgraded with a scan equalization module and a new procedure to recover the nodules connected to other lung structures; its classification module, which makes use of a feed-forward neural network, is based of a small number ofmore » features (13), so as to minimize the risk of lacking generalization, which could be possible given the large difference between the size of the training and testing datasets, which contain 94 and 1019 CTs, respectively. The lungCAM (standalone) and M5L (combined) performance was extensively tested on 1043 CT scans from three independent datasets, including a detailed analysis of the full Lung Image Database Consortium/Image Database Resource Initiative database, which is not yet found in literature. Results: The lungCAM and M5L performance is consistent across the databases, with a sensitivity of about 70% and 80%, respectively, at eight false positive findings per scan, despite the variable annotation criteria and acquisition and reconstruction conditions. A reduced sensitivity is found for subtle nodules and ground glass opacities (GGO) structures. A comparison with other CAD systems is also presented. Conclusions: The M5L performance on a large and heterogeneous dataset is stable and satisfactory, although the development of a dedicated module for GGOs detection could further improve it, as well as an iterative optimization of the training procedure. The main aim of the present study was accomplished: M5L results do not deteriorate when increasing the dataset size, making it a candidate for supporting radiologists on large scale screenings and clinical programs.« less

Identification of Habitat-Specific Biomes of Aquatic Fungal Communities Using a Comprehensive Nearly Full-Length 18S rRNA Dataset Enriched with Contextual Data

PubMed Central

Panzer, Katrin; Yilmaz, Pelin; Weiß, Michael; Reich, Lothar; Richter, Michael; Wiese, Jutta; Schmaljohann, Rolf; Labes, Antje; Imhoff, Johannes F.; Glöckner, Frank Oliver; Reich, Marlis

2015-01-01

Molecular diversity surveys have demonstrated that aquatic fungi are highly diverse, and that they play fundamental ecological roles in aquatic systems. Unfortunately, comparative studies of aquatic fungal communities are few and far between, due to the scarcity of adequate datasets. We combined all publicly available fungal 18S ribosomal RNA (rRNA) gene sequences with new sequence data from a marine fungi culture collection. We further enriched this dataset by adding validated contextual data. Specifically, we included data on the habitat type of the samples assigning fungal taxa to ten different habitat categories. This dataset has been created with the intention to serve as a valuable reference dataset for aquatic fungi including a phylogenetic reference tree. The combined data enabled us to infer fungal community patterns in aquatic systems. Pairwise habitat comparisons showed significant phylogenetic differences, indicating that habitat strongly affects fungal community structure. Fungal taxonomic composition differed considerably even on phylum and class level. Freshwater fungal assemblage was most different from all other habitat types and was dominated by basal fungal lineages. For most communities, phylogenetic signals indicated clustering of sequences suggesting that environmental factors were the main drivers of fungal community structure, rather than species competition. Thus, the diversification process of aquatic fungi must be highly clade specific in some cases.The combined data enabled us to infer fungal community patterns in aquatic systems. Pairwise habitat comparisons showed significant phylogenetic differences, indicating that habitat strongly affects fungal community structure. Fungal taxonomic composition differed considerably even on phylum and class level. Freshwater fungal assemblage was most different from all other habitat types and was dominated by basal fungal lineages. For most communities, phylogenetic signals indicated clustering of sequences suggesting that environmental factors were the main drivers of fungal community structure, rather than species competition. Thus, the diversification process of aquatic fungi must be highly clade specific in some cases. PMID:26226014

Aerosol Climate Time Series Evaluation In ESA Aerosol_cci

NASA Astrophysics Data System (ADS)

Popp, T.; de Leeuw, G.; Pinnock, S.

2015-12-01

Within the ESA Climate Change Initiative (CCI) Aerosol_cci (2010 - 2017) conducts intensive work to improve algorithms for the retrieval of aerosol information from European sensors. By the end of 2015 full mission time series of 2 GCOS-required aerosol parameters are completely validated and released: Aerosol Optical Depth (AOD) from dual view ATSR-2 / AATSR radiometers (3 algorithms, 1995 - 2012), and stratospheric extinction profiles from star occultation GOMOS spectrometer (2002 - 2012). Additionally, a 35-year multi-sensor time series of the qualitative Absorbing Aerosol Index (AAI) together with sensitivity information and an AAI model simulator is available. Complementary aerosol properties requested by GCOS are in a "round robin" phase, where various algorithms are inter-compared: fine mode AOD, mineral dust AOD (from the thermal IASI spectrometer), absorption information and aerosol layer height. As a quasi-reference for validation in few selected regions with sparse ground-based observations the multi-pixel GRASP algorithm for the POLDER instrument is used. Validation of first dataset versions (vs. AERONET, MAN) and inter-comparison to other satellite datasets (MODIS, MISR, SeaWIFS) proved the high quality of the available datasets comparable to other satellite retrievals and revealed needs for algorithm improvement (for example for higher AOD values) which were taken into account for a reprocessing. The datasets contain pixel level uncertainty estimates which are also validated. The paper will summarize and discuss the results of major reprocessing and validation conducted in 2015. The focus will be on the ATSR, GOMOS and IASI datasets. Pixel level uncertainties validation will be summarized and discussed including unknown components and their potential usefulness and limitations. Opportunities for time series extension with successor instruments of the Sentinel family will be described and the complementarity of the different satellite aerosol products (e.g. dust vs. total AOD, ensembles from different algorithms for the same sensor) will be discussed.

A Spatially Distinct History of the Development of California Groundfish Fisheries

PubMed Central

Miller, Rebecca R.; Field, John C.; Santora, Jarrod A.; Schroeder, Isaac D.; Huff, David D.; Key, Meisha; Pearson, Don E.; MacCall, Alec D.

2014-01-01

During the past century, commercial fisheries have expanded from small vessels fishing in shallow, coastal habitats to a broad suite of vessels and gears that fish virtually every marine habitat on the globe. Understanding how fisheries have developed in space and time is critical for interpreting and managing the response of ecosystems to the effects of fishing, however time series of spatially explicit data are typically rare. Recently, the 1933–1968 portion of the commercial catch dataset from the California Department of Fish and Wildlife was recovered and digitized, completing the full historical series for both commercial and recreational datasets from 1933–2010. These unique datasets include landing estimates at a coarse 10 by 10 minute “grid-block” spatial resolution and extends the entire length of coastal California up to 180 kilometers from shore. In this study, we focus on the catch history of groundfish which were mapped for each grid-block using the year at 50% cumulative catch and total historical catch per habitat area. We then constructed generalized linear models to quantify the relationship between spatiotemporal trends in groundfish catches, distance from ports, depth, percentage of days with wind speed over 15 knots, SST and ocean productivity. Our results indicate that over the history of these fisheries, catches have taken place in increasingly deeper habitat, at a greater distance from ports, and in increasingly inclement weather conditions. Understanding spatial development of groundfish fisheries and catches in California are critical for improving population models and for evaluating whether implicit stock assessment model assumptions of relative homogeneity of fisheries removals over time and space are reasonable. This newly reconstructed catch dataset and analysis provides a comprehensive appreciation for the development of groundfish fisheries with respect to commonly assumed trends of global fisheries patterns that are typically constrained by a lack of long-term spatial datasets. PMID:24967973

Chapter 11: Web-based Tools - VO Region Inventory Service

NASA Astrophysics Data System (ADS)

Good, J. C.

As the size and number of datasets available through the VO grows, it becomes increasingly critical to have services that aid in locating and characterizing data pertinent to a particular scientific problem. At the same time, this same increase makes that goal more and more difficult to achieve. With a small number of datasets, it is feasible to simply retrieve the data itself (as the NVO DataScope service does). At intermediate scales, "count" DBMS searches (searches of the actual datasets which return record counts rather than full data subsets) sent to each data provider will work. However, neither of these approaches scale as the number of datasets expands into the hundreds or thousands. Dealing with the same problem internally, IRSA developed a compact and extremely fast scheme for determining source counts for positional catalogs (and in some cases image metadata) over arbitrarily large regions for multiple catalogs in a fraction of a second. To show applicability to the VO in general, this service has been extended with indices for all 4000+ catalogs in CDS Vizier (essentially all published catalogs and source tables). In this chapter, we will briefly describe the architecture of this service, and then describe how this can be used in a distributed system to retrieve rapid inventories of all VO holdings in a way that places an insignificant load on any data supplier. Further, we show and this tool can be used in conjunction with VO Registries and catalog services to zero in on those datasets that are appropriate to the user's needs. The initial implementation of this service consolidates custom binary index file structures (external to any DBMS and therefore portable) at a single site to minimize search times and implements the search interface as a simple CGI program. However, the architecture is amenable to distribution. The next phase of development will focus on metadata harvesting from data archives through a standard program interface and distribution of the search processing across multiple service providers for redundancy and parallelization.

A learning-based markerless approach for full-body kinematics estimation in-natura from a single image.

PubMed

Drory, Ami; Li, Hongdong; Hartley, Richard

2017-04-11

We present a supervised machine learning approach for markerless estimation of human full-body kinematics for a cyclist from an unconstrained colour image. This approach is motivated by the limitations of existing marker-based approaches restricted by infrastructure, environmental conditions, and obtrusive markers. By using a discriminatively learned mixture-of-parts model, we construct a probabilistic tree representation to model the configuration and appearance of human body joints. During the learning stage, a Structured Support Vector Machine (SSVM) learns body parts appearance and spatial relations. In the testing stage, the learned models are employed to recover body pose via searching in a test image over a pyramid structure. We focus on the movement modality of cycling to demonstrate the efficacy of our approach. In natura estimation of cycling kinematics using images is challenging because of human interaction with a bicycle causing frequent occlusions. We make no assumptions in relation to the kinematic constraints of the model, nor the appearance of the scene. Our technique finds multiple quality hypotheses for the pose. We evaluate the precision of our method on two new datasets using loss functions. Our method achieves a score of 91.1 and 69.3 on mean Probability of Correct Keypoint (PCK) measure and 88.7 and 66.1 on the Average Precision of Keypoints (APK) measure for the frontal and sagittal datasets respectively. We conclude that our method opens new vistas to robust user-interaction free estimation of full body kinematics, a prerequisite to motion analysis. Copyright © 2017 Elsevier Ltd. All rights reserved.

Approximations of noise covariance in multi-slice helical CT scans: impact on lung nodule size estimation.

PubMed

Zeng, Rongping; Petrick, Nicholas; Gavrielides, Marios A; Myers, Kyle J

2011-10-07

Multi-slice computed tomography (MSCT) scanners have become popular volumetric imaging tools. Deterministic and random properties of the resulting CT scans have been studied in the literature. Due to the large number of voxels in the three-dimensional (3D) volumetric dataset, full characterization of the noise covariance in MSCT scans is difficult to tackle. However, as usage of such datasets for quantitative disease diagnosis grows, so does the importance of understanding the noise properties because of their effect on the accuracy of the clinical outcome. The goal of this work is to study noise covariance in the helical MSCT volumetric dataset. We explore possible approximations to the noise covariance matrix with reduced degrees of freedom, including voxel-based variance, one-dimensional (1D) correlation, two-dimensional (2D) in-plane correlation and the noise power spectrum (NPS). We further examine the effect of various noise covariance models on the accuracy of a prewhitening matched filter nodule size estimation strategy. Our simulation results suggest that the 1D longitudinal, 2D in-plane and NPS prewhitening approaches can improve the performance of nodule size estimation algorithms. When taking into account computational costs in determining noise characterizations, the NPS model may be the most efficient approximation to the MSCT noise covariance matrix.

Trace: a high-throughput tomographic reconstruction engine for large-scale datasets

DOE PAGES

Bicer, Tekin; Gursoy, Doga; Andrade, Vincent De; ...

2017-01-28

Here, synchrotron light source and detector technologies enable scientists to perform advanced experiments. These scientific instruments and experiments produce data at such scale and complexity that large-scale computation is required to unleash their full power. One of the widely used data acquisition technique at light sources is Computed Tomography, which can generate tens of GB/s depending on x-ray range. A large-scale tomographic dataset, such as mouse brain, may require hours of computation time with a medium size workstation. In this paper, we present Trace, a data-intensive computing middleware we developed for implementation and parallelization of iterative tomographic reconstruction algorithms. Tracemore » provides fine-grained reconstruction of tomography datasets using both (thread level) shared memory and (process level) distributed memory parallelization. Trace utilizes a special data structure called replicated reconstruction object to maximize application performance. We also present the optimizations we have done on the replicated reconstruction objects and evaluate them using a shale and a mouse brain sinogram. Our experimental evaluations show that the applied optimizations and parallelization techniques can provide 158x speedup (using 32 compute nodes) over single core configuration, which decreases the reconstruction time of a sinogram (with 4501 projections and 22400 detector resolution) from 12.5 hours to less than 5 minutes per iteration.« less

Condensing Massive Satellite Datasets For Rapid Interactive Analysis

NASA Astrophysics Data System (ADS)

Grant, G.; Gallaher, D. W.; Lv, Q.; Campbell, G. G.; Fowler, C.; LIU, Q.; Chen, C.; Klucik, R.; McAllister, R. A.

2015-12-01

Our goal is to enable users to interactively analyze massive satellite datasets, identifying anomalous data or values that fall outside of thresholds. To achieve this, the project seeks to create a derived database containing only the most relevant information, accelerating the analysis process. The database is designed to be an ancillary tool for the researcher, not an archival database to replace the original data. This approach is aimed at improving performance by reducing the overall size by way of condensing the data. The primary challenges of the project include: - The nature of the research question(s) may not be known ahead of time. - The thresholds for determining anomalies may be uncertain. - Problems associated with processing cloudy, missing, or noisy satellite imagery. - The contents and method of creation of the condensed dataset must be easily explainable to users. The architecture of the database will reorganize spatially-oriented satellite imagery into temporally-oriented columns of data (a.k.a., "data rods") to facilitate time-series analysis. The database itself is an open-source parallel database, designed to make full use of clustered server technologies. A demonstration of the system capabilities will be shown. Applications for this technology include quick-look views of the data, as well as the potential for on-board satellite processing of essential information, with the goal of reducing data latency.

Spark and HPC for High Energy Physics Data Analyses

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sehrish, Saba; Kowalkowski, Jim; Paterno, Marc

A full High Energy Physics (HEP) data analysis is divided into multiple data reduction phases. Processing within these phases is extremely time consuming, therefore intermediate results are stored in files held in mass storage systems and referenced as part of large datasets. This processing model limits what can be done with interactive data analytics. Growth in size and complexity of experimental datasets, along with emerging big data tools are beginning to cause changes to the traditional ways of doing data analyses. Use of big data tools for HEP analysis looks promising, mainly because extremely large HEP datasets can be representedmore » and held in memory across a system, and accessed interactively by encoding an analysis using highlevel programming abstractions. The mainstream tools, however, are not designed for scientific computing or for exploiting the available HPC platform features. We use an example from the Compact Muon Solenoid (CMS) experiment at the Large Hadron Collider (LHC) in Geneva, Switzerland. The LHC is the highest energy particle collider in the world. Our use case focuses on searching for new types of elementary particles explaining Dark Matter in the universe. We use HDF5 as our input data format, and Spark to implement the use case. We show the benefits and limitations of using Spark with HDF5 on Edison at NERSC.« less

Trace: a high-throughput tomographic reconstruction engine for large-scale datasets

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bicer, Tekin; Gursoy, Doga; Andrade, Vincent De

Here, synchrotron light source and detector technologies enable scientists to perform advanced experiments. These scientific instruments and experiments produce data at such scale and complexity that large-scale computation is required to unleash their full power. One of the widely used data acquisition technique at light sources is Computed Tomography, which can generate tens of GB/s depending on x-ray range. A large-scale tomographic dataset, such as mouse brain, may require hours of computation time with a medium size workstation. In this paper, we present Trace, a data-intensive computing middleware we developed for implementation and parallelization of iterative tomographic reconstruction algorithms. Tracemore » provides fine-grained reconstruction of tomography datasets using both (thread level) shared memory and (process level) distributed memory parallelization. Trace utilizes a special data structure called replicated reconstruction object to maximize application performance. We also present the optimizations we have done on the replicated reconstruction objects and evaluate them using a shale and a mouse brain sinogram. Our experimental evaluations show that the applied optimizations and parallelization techniques can provide 158x speedup (using 32 compute nodes) over single core configuration, which decreases the reconstruction time of a sinogram (with 4501 projections and 22400 detector resolution) from 12.5 hours to less than 5 minutes per iteration.« less

Using nearly full-genome HIV sequence data improves phylogeny reconstruction in a simulated epidemic

PubMed Central

Yebra, Gonzalo; Hodcroft, Emma B.; Ragonnet-Cronin, Manon L.; Pillay, Deenan; Brown, Andrew J. Leigh; Fraser, Christophe; Kellam, Paul; de Oliveira, Tulio; Dennis, Ann; Hoppe, Anne; Kityo, Cissy; Frampton, Dan; Ssemwanga, Deogratius; Tanser, Frank; Keshani, Jagoda; Lingappa, Jairam; Herbeck, Joshua; Wawer, Maria; Essex, Max; Cohen, Myron S.; Paton, Nicholas; Ratmann, Oliver; Kaleebu, Pontiano; Hayes, Richard; Fidler, Sarah; Quinn, Thomas; Novitsky, Vladimir; Haywards, Andrew; Nastouli, Eleni; Morris, Steven; Clark, Duncan; Kozlakidis, Zisis

2016-01-01

HIV molecular epidemiology studies analyse viral pol gene sequences due to their availability, but whole genome sequencing allows to use other genes. We aimed to determine what gene(s) provide(s) the best approximation to the real phylogeny by analysing a simulated epidemic (created as part of the PANGEA_HIV project) with a known transmission tree. We sub-sampled a simulated dataset of 4662 sequences into different combinations of genes (gag-pol-env, gag-pol, gag, pol, env and partial pol) and sampling depths (100%, 60%, 20% and 5%), generating 100 replicates for each case. We built maximum-likelihood trees for each combination using RAxML (GTR + Γ), and compared their topologies to the corresponding true tree’s using CompareTree. The accuracy of the trees was significantly proportional to the length of the sequences used, with the gag-pol-env datasets showing the best performance and gag and partial pol sequences showing the worst. The lowest sampling depths (20% and 5%) greatly reduced the accuracy of tree reconstruction and showed high variability among replicates, especially when using the shortest gene datasets. In conclusion, using longer sequences derived from nearly whole genomes will improve the reliability of phylogenetic reconstruction. With low sample coverage, results can be highly variable, particularly when based on short sequences. PMID:28008945

Using nearly full-genome HIV sequence data improves phylogeny reconstruction in a simulated epidemic.

PubMed

Yebra, Gonzalo; Hodcroft, Emma B; Ragonnet-Cronin, Manon L; Pillay, Deenan; Brown, Andrew J Leigh

2016-12-23

HIV molecular epidemiology studies analyse viral pol gene sequences due to their availability, but whole genome sequencing allows to use other genes. We aimed to determine what gene(s) provide(s) the best approximation to the real phylogeny by analysing a simulated epidemic (created as part of the PANGEA_HIV project) with a known transmission tree. We sub-sampled a simulated dataset of 4662 sequences into different combinations of genes (gag-pol-env, gag-pol, gag, pol, env and partial pol) and sampling depths (100%, 60%, 20% and 5%), generating 100 replicates for each case. We built maximum-likelihood trees for each combination using RAxML (GTR + Γ), and compared their topologies to the corresponding true tree's using CompareTree. The accuracy of the trees was significantly proportional to the length of the sequences used, with the gag-pol-env datasets showing the best performance and gag and partial pol sequences showing the worst. The lowest sampling depths (20% and 5%) greatly reduced the accuracy of tree reconstruction and showed high variability among replicates, especially when using the shortest gene datasets. In conclusion, using longer sequences derived from nearly whole genomes will improve the reliability of phylogenetic reconstruction. With low sample coverage, results can be highly variable, particularly when based on short sequences.

Biotea: RDFizing PubMed Central in support for the paper as an interface to the Web of Data

PubMed Central

2013-01-01

Background The World Wide Web has become a dissemination platform for scientific and non-scientific publications. However, most of the information remains locked up in discrete documents that are not always interconnected or machine-readable. The connectivity tissue provided by RDF technology has not yet been widely used to support the generation of self-describing, machine-readable documents. Results In this paper, we present our approach to the generation of self-describing machine-readable scholarly documents. We understand the scientific document as an entry point and interface to the Web of Data. We have semantically processed the full-text, open-access subset of PubMed Central. Our RDF model and resulting dataset make extensive use of existing ontologies and semantic enrichment services. We expose our model, services, prototype, and datasets at http://biotea.idiginfo.org/ Conclusions The semantic processing of biomedical literature presented in this paper embeds documents within the Web of Data and facilitates the execution of concept-based queries against the entire digital library. Our approach delivers a flexible and adaptable set of tools for metadata enrichment and semantic processing of biomedical documents. Our model delivers a semantically rich and highly interconnected dataset with self-describing content so that software can make effective use of it. PMID:23734622

Argo_CUDA: Exhaustive GPU based approach for motif discovery in large DNA datasets.

PubMed

Vishnevsky, Oleg V; Bocharnikov, Andrey V; Kolchanov, Nikolay A

2018-02-01

The development of chromatin immunoprecipitation sequencing (ChIP-seq) technology has revolutionized the genetic analysis of the basic mechanisms underlying transcription regulation and led to accumulation of information about a huge amount of DNA sequences. There are a lot of web services which are currently available for de novo motif discovery in datasets containing information about DNA/protein binding. An enormous motif diversity makes their finding challenging. In order to avoid the difficulties, researchers use different stochastic approaches. Unfortunately, the efficiency of the motif discovery programs dramatically declines with the query set size increase. This leads to the fact that only a fraction of top "peak" ChIP-Seq segments can be analyzed or the area of analysis should be narrowed. Thus, the motif discovery in massive datasets remains a challenging issue. Argo_Compute Unified Device Architecture (CUDA) web service is designed to process the massive DNA data. It is a program for the detection of degenerate oligonucleotide motifs of fixed length written in 15-letter IUPAC code. Argo_CUDA is a full-exhaustive approach based on the high-performance GPU technologies. Compared with the existing motif discovery web services, Argo_CUDA shows good prediction quality on simulated sets. The analysis of ChIP-Seq sequences revealed the motifs which correspond to known transcription factor binding sites.

Impact of sequencing depth and read length on single cell RNA sequencing data of T cells.

PubMed

Rizzetto, Simone; Eltahla, Auda A; Lin, Peijie; Bull, Rowena; Lloyd, Andrew R; Ho, Joshua W K; Venturi, Vanessa; Luciani, Fabio

2017-10-06

Single cell RNA sequencing (scRNA-seq) provides great potential in measuring the gene expression profiles of heterogeneous cell populations. In immunology, scRNA-seq allowed the characterisation of transcript sequence diversity of functionally relevant T cell subsets, and the identification of the full length T cell receptor (TCRαβ), which defines the specificity against cognate antigens. Several factors, e.g. RNA library capture, cell quality, and sequencing output affect the quality of scRNA-seq data. We studied the effects of read length and sequencing depth on the quality of gene expression profiles, cell type identification, and TCRαβ reconstruction, utilising 1,305 single cells from 8 publically available scRNA-seq datasets, and simulation-based analyses. Gene expression was characterised by an increased number of unique genes identified with short read lengths (<50 bp), but these featured higher technical variability compared to profiles from longer reads. Successful TCRαβ reconstruction was achieved for 6 datasets (81% - 100%) with at least 0.25 millions (PE) reads of length >50 bp, while it failed for datasets with <30 bp reads. Sufficient read length and sequencing depth can control technical noise to enable accurate identification of TCRαβ and gene expression profiles from scRNA-seq data of T cells.

VizieR Online Data Catalog: Orion Integral Filament ALMA+IRAM30m N2H+(1-0) data (Hacar+, 2018)

NASA Astrophysics Data System (ADS)

Hacar, A.; Tafalla, M.; Forbrich, J.; Alves, J.; Meingast, S.; Grossschedl, J.; Teixeira, P. S.

2018-01-01

Combined ALMA+IRAM30m large-scale N2H+(1-0) emission in the Orion ISF. Two datasets are presented here in FITS format: 1.- Full data cube: spectral resolution = 0.1 kms-1 2.- Total integrated line intensity (moment 0) map Units are in Jy/beam See also: https://sites.google.com/site/orion4dproject/home (2 data files).

X3D-Earth: Full Globe Coverage Utilizing Multiple Dataset

DTIC Science & Technology

2010-09-01

DtedNvtProcessor Class ..................................................128 Figure 63. Subversion Checkout in Netbeans ...to the Ant build.xml file within a NetBeans Project: <target name=“moveToHamming” depends=““> <scp todir=“user@hamming.uc.nps.edu:/work/user/DTED...This task was generated using the NetBeans IDE (can be downloaded at www.netbeans.org). The task was then executed within NetBeans . This type of

POPE: Partial Order Preserving Encoding

DTIC Science & Technology

2016-09-09

Alex X. Liu, Ann L. Wang, and Bezawada Bruhadeshwar. Fast range query processing with strong privacy protection for cloud computing . Proc. VLDB...States government. As such, the Government retains a nonexclusive, royalty-free right to publish or reproduce this article , or to allow others to do so...of these schemes the direc- tory in the persistent client storage depends on the full dataset. Thus 1We abuse notation and use OPE to refer to both

Neutrino constraints: what large-scale structure and CMB data are telling us?

DOE Office of Scientific and Technical Information (OSTI.GOV)

Costanzi, Matteo; Sartoris, Barbara; Borgani, Stefano

We discuss the reliability of neutrino mass constraints, either active or sterile, from the combination of different low redshift Universe probes with measurements of CMB anisotropies. In our analyses we consider WMAP 9-year or Planck Cosmic Microwave Background (CMB) data in combination with Baryonic Acoustic Oscillations (BAO) measurements from BOSS DR11, galaxy shear measurements from CFHTLenS, SDSS Ly α forest constraints and galaxy cluster mass function from Chandra observations. At odds with recent similar studies, to avoid model dependence of the constraints we perform a full likelihood analysis for all the datasets employed. As for the cluster data analysis wemore » rely on to the most recent calibration of massive neutrino effects in the halo mass function and we explore the impact of the uncertainty in the mass bias and re-calibration of the halo mass function due to baryonic feedback processes on cosmological parameters. We find that none of the low redshift probes alone provide evidence for massive neutrino in combination with CMB measurements, while a larger than 2σ detection of non zero neutrino mass, either active or sterile, is achieved combining cluster or shear data with CMB and BAO measurements. Yet, the significance of the detection exceeds 3σ if we combine all four datasets. For a three active neutrino scenario, from the joint analysis of CMB, BAO, shear and cluster data including the uncertainty in the mass bias we obtain ∑ m{sub ν} =0.29{sup +0.18}{sub -0.21} eV and ∑ m{sub ν} =0.22{sup +0.17}{sub -0.18} eV 95%CL) using WMAP9 or Planck as CMB dataset, respectively. The preference for massive neutrino is even larger in the sterile neutrino scenario, for which we get m{sub s}{sup eff}=0.44{sup +0.28}{sub -0.26} eV and Δ N{sub eff}=0.78{sup +0.60}{sub -0.59} 95%CL) from the joint analysis of Planck, BAO, shear and cluster datasets. For this data combination the vanilla ΛCDM model is rejected at more than 3σ and a sterile neutrino mass as motivated by accelerator anomaly is within the 2σ errors. Conversely, the Ly α data favour vanishing neutrino masses and from the data combination Planck+BAO+Ly α we get the tight upper limits ∑ m{sub ν} <0.14 eV and m{sub s}{sup eff}<0.22 eV—Δ N{sub eff}<1.11 95%CL) for the active and sterile neutrino model, respectively. Finally, results from the full data combination reflect the tension between the σ{sub 8} constraints obtained from cluster and shear data and that inferred from Ly α forest measurements; in the active neutrino scenario for both CMB datasets employed, the full data combination yields only an upper limits on ∑ m{sub ν}, while assuming an extra sterile neutrino we still get preference for non-vanishing mass, m{sub s}{sup eff}=0.26{sup +0.22}{sub -0.24} eV, and dark contribution to the radiation content, Δ N{sub eff}=0.82±0.55.« less

DOE Office of Scientific and Technical Information (OSTI.GOV)

Thomas, S; Yuen, C; Huang, V

Purpose: In this abstract we implement and validate a 4D VMAT Acuros XB dose calculation using Gafchromic film. Special attention is paid to the physical material assignment in the CT dataset and to reported dose to water and dose to medium. Methods: A QUASAR phantom with a 3 cm sinusoidal tumor motion and 5 second period was scanned using 4D computed tomography. A CT was also obtained of the static QUASAR phantom with the tumor at the central position. A VMAT plan was created on the average CT dataset and was delivered on a Varian TrueBeam linear accelerator. The trajectorymore » log file from this treatment was acquired and used to create 10 VMAT subplans (one for each portion of the breathing cycle). Motion for each subplan was simulated by moving the beam isocentre in the superior/inferior direction in the Treatment Planning System on the static CT scan. The 10 plans were calculated (both dose to medium and dose to water) and summed for 1) the original HU values from the static CT scan and 2) the correct physical material assignment in the CT dataset. To acquire a breathing phase synchronized film measurements the trajectory log was used to create a VMAT delivery plan which includes dynamic couch motion using the Developer Mode. Three different treatment start phases were investigated (mid inhalation, full inhalation and full exhalation). Results: For each scenario the coronal dose distributions were measured using Gafchromic film and compared to the corresponding calculation with Film QA Pro Software using a Gamma test with a 3%/3mm distance to agreement criteria. Good agreement was found between calculation and measurement. No statistically significant difference in agreement was found between calculations to original HU values vs calculations to over-written (material-assigned) HU values. Conclusion: The investigated 4D dose calculation method agrees well with measurement.« less

A Comparison Study of Classifier Algorithms for Cross-Person Physical Activity Recognition

PubMed Central

Saez, Yago; Baldominos, Alejandro; Isasi, Pedro

2016-01-01

Physical activity is widely known to be one of the key elements of a healthy life. The many benefits of physical activity described in the medical literature include weight loss and reductions in the risk factors for chronic diseases. With the recent advances in wearable devices, such as smartwatches or physical activity wristbands, motion tracking sensors are becoming pervasive, which has led to an impressive growth in the amount of physical activity data available and an increasing interest in recognizing which specific activity a user is performing. Moreover, big data and machine learning are now cross-fertilizing each other in an approach called “deep learning”, which consists of massive artificial neural networks able to detect complicated patterns from enormous amounts of input data to learn classification models. This work compares various state-of-the-art classification techniques for automatic cross-person activity recognition under different scenarios that vary widely in how much information is available for analysis. We have incorporated deep learning by using Google’s TensorFlow framework. The data used in this study were acquired from PAMAP2 (Physical Activity Monitoring in the Ageing Population), a publicly available dataset containing physical activity data. To perform cross-person prediction, we used the leave-one-subject-out (LOSO) cross-validation technique. When working with large training sets, the best classifiers obtain very high average accuracies (e.g., 96% using extra randomized trees). However, when the data volume is drastically reduced (where available data are only 0.001% of the continuous data), deep neural networks performed the best, achieving 60% in overall prediction accuracy. We found that even when working with only approximately 22.67% of the full dataset, we can statistically obtain the same results as when working with the full dataset. This finding enables the design of more energy-efficient devices and facilitates cold starts and big data processing of physical activity records. PMID:28042838

FluReF, an automated flu virus reassortment finder based on phylogenetic trees.

PubMed

Yurovsky, Alisa; Moret, Bernard M E

2011-01-01

Reassortments are events in the evolution of the genome of influenza (flu), whereby segments of the genome are exchanged between different strains. As reassortments have been implicated in major human pandemics of the last century, their identification has become a health priority. While such identification can be done "by hand" on a small dataset, researchers and health authorities are building up enormous databases of genomic sequences for every flu strain, so that it is imperative to develop automated identification methods. However, current methods are limited to pairwise segment comparisons. We present FluReF, a fully automated flu virus reassortment finder. FluReF is inspired by the visual approach to reassortment identification and uses the reconstructed phylogenetic trees of the individual segments and of the full genome. We also present a simple flu evolution simulator, based on the current, source-sink, hypothesis for flu cycles. On synthetic datasets produced by our simulator, FluReF, tuned for a 0% false positive rate, yielded false negative rates of less than 10%. FluReF corroborated two new reassortments identified by visual analysis of 75 Human H3N2 New York flu strains from 2005-2008 and gave partial verification of reassortments found using another bioinformatics method. FluReF finds reassortments by a bottom-up search of the full-genome and segment-based phylogenetic trees for candidate clades--groups of one or more sampled viruses that are separated from the other variants from the same season. Candidate clades in each tree are tested to guarantee confidence values, using the lengths of key edges as well as other tree parameters; clades with reassortments must have validated incongruencies among segment trees. FluReF demonstrates robustness of prediction for geographically and temporally expanded datasets, and is not limited to finding reassortments with previously collected sequences. The complete source code is available from http://lcbb.epfl.ch/software.html.

A Comparison Study of Classifier Algorithms for Cross-Person Physical Activity Recognition.

PubMed

Saez, Yago; Baldominos, Alejandro; Isasi, Pedro

2016-12-30

Physical activity is widely known to be one of the key elements of a healthy life. The many benefits of physical activity described in the medical literature include weight loss and reductions in the risk factors for chronic diseases. With the recent advances in wearable devices, such as smartwatches or physical activity wristbands, motion tracking sensors are becoming pervasive, which has led to an impressive growth in the amount of physical activity data available and an increasing interest in recognizing which specific activity a user is performing. Moreover, big data and machine learning are now cross-fertilizing each other in an approach called "deep learning", which consists of massive artificial neural networks able to detect complicated patterns from enormous amounts of input data to learn classification models. This work compares various state-of-the-art classification techniques for automatic cross-person activity recognition under different scenarios that vary widely in how much information is available for analysis. We have incorporated deep learning by using Google's TensorFlow framework. The data used in this study were acquired from PAMAP2 (Physical Activity Monitoring in the Ageing Population), a publicly available dataset containing physical activity data. To perform cross-person prediction, we used the leave-one-subject-out (LOSO) cross-validation technique. When working with large training sets, the best classifiers obtain very high average accuracies (e.g., 96% using extra randomized trees). However, when the data volume is drastically reduced (where available data are only 0.001% of the continuous data), deep neural networks performed the best, achieving 60% in overall prediction accuracy. We found that even when working with only approximately 22.67% of the full dataset, we can statistically obtain the same results as when working with the full dataset. This finding enables the design of more energy-efficient devices and facilitates cold starts and big data processing of physical activity records.

How Many Measurements Are Needed to Estimate Blood Pressure Variability Without Loss of Prognostic Information?

PubMed Central

2014-01-01

BACKGROUND Average real variability (ARV) is a recently proposed index for short-term blood pressure (BP) variability. We aimed to determine the minimum number of BP readings required to compute ARV without loss of prognostic information. METHODS ARV was calculated from a discovery dataset that included 24-hour ambulatory BP measurements for 1,254 residents (mean age = 56.6 years; 43.5% women) of Copenhagen, Denmark. Concordance between ARV from full (≥80 BP readings) and randomly reduced 24-hour BP recordings was examined, as was prognostic accuracy. A test dataset that included 5,353 subjects (mean age = 54.0 years; 45.6% women) with at least 48 BP measurements from 11 randomly recruited population cohorts was used to validate the results. RESULTS In the discovery dataset, a minimum of 48 BP readings allowed an accurate assessment of the association between cardiovascular risk and ARV. In the test dataset, over 10.2 years (median), 806 participants died (335 cardiovascular deaths, 206 cardiac deaths) and 696 experienced a major fatal or nonfatal cardiovascular event. Standardized multivariable-adjusted hazard ratios (HRs) were computed for associations between outcome and BP variability. Higher diastolic ARV in 24-hour ambulatory BP recordings predicted (P < 0.01) total (HR = 1.12), cardiovascular (HR = 1.19), and cardiac (HR = 1.19) mortality and fatal combined with nonfatal cerebrovascular events (HR = 1.16). Higher systolic ARV in 24-hour ambulatory BP recordings predicted (P < 0.01) total (HR = 1.12), cardiovascular (HR = 1.17), and cardiac (HR = 1.24) mortality. CONCLUSIONS Forty-eight BP readings over 24 hours were observed to be adequate to compute ARV without meaningful loss of prognostic information. PMID:23955605

Development of water level estimation algorithms using SARAL/Altika dataset and validation over the Ukai reservoir, India

NASA Astrophysics Data System (ADS)

Chander, Shard; Ganguly, Debojyoti

2017-01-01

Water level was estimated, using AltiKa radar altimeter onboard the SARAL satellite, over the Ukai reservoir using modified algorithms specifically for inland water bodies. The methodology was based on waveform classification, waveform retracking, and dedicated inland range corrections algorithms. The 40-Hz waveforms were classified based on linear discriminant analysis and Bayesian classifier. Waveforms were retracked using Brown, Ice-2, threshold, and offset center of gravity methods. Retracking algorithms were implemented on full waveform and subwaveforms (only one leading edge) for estimating the improvement in the retrieved range. European Centre for Medium-Range Weather Forecasts (ECMWF) operational, ECMWF re-analysis pressure fields, and global ionosphere maps were used to exactly estimate the range corrections. The microwave and optical images were used for estimating the extent of the water body and altimeter track location. Four global positioning system (GPS) field trips were conducted on same day as the SARAL pass using two dual frequency GPS. One GPS was mounted close to the dam in static mode and the other was used on a moving vehicle within the reservoir in Kinematic mode. In situ gauge dataset was provided by the Ukai dam authority for the time period January 1972 to March 2015. The altimeter retrieved water level results were then validated with the GPS survey and in situ gauge dataset. With good selection of virtual station (waveform classification, back scattering coefficient), Ice-2 retracker and subwaveform retracker both work better with an overall root-mean-square error <15 cm. The results support that the AltiKa dataset, due to a smaller foot-print and sharp trailing edge of the Ka-band waveform, can be utilized for more accurate water level information over inland water bodies.

A Metastatistical Approach to Satellite Estimates of Extreme Rainfall Events

NASA Astrophysics Data System (ADS)

Zorzetto, E.; Marani, M.

2017-12-01

The estimation of the average recurrence interval of intense rainfall events is a central issue for both hydrologic modeling and engineering design. These estimates require the inference of the properties of the right tail of the statistical distribution of precipitation, a task often performed using the Generalized Extreme Value (GEV) distribution, estimated either from a samples of annual maxima (AM) or with a peaks over threshold (POT) approach. However, these approaches require long and homogeneous rainfall records, which often are not available, especially in the case of remote-sensed rainfall datasets. We use here, and tailor it to remotely-sensed rainfall estimates, an alternative approach, based on the metastatistical extreme value distribution (MEVD), which produces estimates of rainfall extreme values based on the probability distribution function (pdf) of all measured `ordinary' rainfall event. This methodology also accounts for the interannual variations observed in the pdf of daily rainfall by integrating over the sample space of its random parameters. We illustrate the application of this framework to the TRMM Multi-satellite Precipitation Analysis rainfall dataset, where MEVD optimally exploits the relatively short datasets of satellite-sensed rainfall, while taking full advantage of its high spatial resolution and quasi-global coverage. Accuracy of TRMM precipitation estimates and scale issues are here investigated for a case study located in the Little Washita watershed, Oklahoma, using a dense network of rain gauges for independent ground validation. The methodology contributes to our understanding of the risk of extreme rainfall events, as it allows i) an optimal use of the TRMM datasets in estimating the tail of the probability distribution of daily rainfall, and ii) a global mapping of daily rainfall extremes and distributional tail properties, bridging the existing gaps in rain gauges networks.

Population Pharmacokinetics of Intravenous Paracetamol (Acetaminophen) in Preterm and Term Neonates: Model Development and External Evaluation.

PubMed

Cook, Sarah F; Roberts, Jessica K; Samiee-Zafarghandy, Samira; Stockmann, Chris; King, Amber D; Deutsch, Nina; Williams, Elaine F; Allegaert, Karel; Wilkins, Diana G; Sherwin, Catherine M T; van den Anker, John N

2016-01-01

The aims of this study were to develop a population pharmacokinetic model for intravenous paracetamol in preterm and term neonates and to assess the generalizability of the model by testing its predictive performance in an external dataset. Nonlinear mixed-effects models were constructed from paracetamol concentration-time data in NONMEM 7.2. Potential covariates included body weight, gestational age, postnatal age, postmenstrual age, sex, race, total bilirubin, and estimated glomerular filtration rate. An external dataset was used to test the predictive performance of the model through calculation of bias, precision, and normalized prediction distribution errors. The model-building dataset included 260 observations from 35 neonates with a mean gestational age of 33.6 weeks [standard deviation (SD) 6.6]. Data were well-described by a one-compartment model with first-order elimination. Weight predicted paracetamol clearance and volume of distribution, which were estimated as 0.348 L/h (5.5 % relative standard error; 30.8 % coefficient of variation) and 2.46 L (3.5 % relative standard error; 14.3 % coefficient of variation), respectively, at the mean subject weight of 2.30 kg. An external evaluation was performed on an independent dataset that included 436 observations from 60 neonates with a mean gestational age of 35.6 weeks (SD 4.3). The median prediction error was 10.1 % [95 % confidence interval (CI) 6.1-14.3] and the median absolute prediction error was 25.3 % (95 % CI 23.1-28.1). Weight predicted intravenous paracetamol pharmacokinetics in neonates ranging from extreme preterm to full-term gestational status. External evaluation suggested that these findings should be generalizable to other similar patient populations.

Population Pharmacokinetics of Intravenous Paracetamol (Acetaminophen) in Preterm and Term Neonates: Model Development and External Evaluation

PubMed Central

Cook, Sarah F.; Roberts, Jessica K.; Samiee-Zafarghandy, Samira; Stockmann, Chris; King, Amber D.; Deutsch, Nina; Williams, Elaine F.; Allegaert, Karel; Sherwin, Catherine M. T.; van den Anker, John N.

2017-01-01

Objectives The aims of this study were to develop a population pharmacokinetic model for intravenous paracetamol in preterm and term neonates and to assess the generalizability of the model by testing its predictive performance in an external dataset. Methods Nonlinear mixed-effects models were constructed from paracetamol concentration–time data in NONMEM 7.2. Potential covariates included body weight, gestational age, postnatal age, postmenstrual age, sex, race, total bilirubin, and estimated glomerular filtration rate. An external dataset was used to test the predictive performance of the model through calculation of bias, precision, and normalized prediction distribution errors. Results The model-building dataset included 260 observations from 35 neonates with a mean gestational age of 33.6 weeks [standard deviation (SD) 6.6]. Data were well-described by a one-compartment model with first-order elimination. Weight predicted paracetamol clearance and volume of distribution, which were estimated as 0.348 L/h (5.5 % relative standard error; 30.8 % coefficient of variation) and 2.46 L (3.5 % relative standard error; 14.3 % coefficient of variation), respectively, at the mean subject weight of 2.30 kg. An external evaluation was performed on an independent dataset that included 436 observations from 60 neonates with a mean gestational age of 35.6 weeks (SD 4.3). The median prediction error was 10.1 % [95 % confidence interval (CI) 6.1–14.3] and the median absolute prediction error was 25.3 % (95 % CI 23.1–28.1). Conclusions Weight predicted intravenous paracetamol pharmacokinetics in neonates ranging from extreme preterm to full-term gestational status. External evaluation suggested that these findings should be generalizable to other similar patient populations. PMID:26201306

Who shares? Who doesn't? Factors associated with openly archiving raw research data.

PubMed

Piwowar, Heather A

2011-01-01

Many initiatives encourage investigators to share their raw datasets in hopes of increasing research efficiency and quality. Despite these investments of time and money, we do not have a firm grasp of who openly shares raw research data, who doesn't, and which initiatives are correlated with high rates of data sharing. In this analysis I use bibliometric methods to identify patterns in the frequency with which investigators openly archive their raw gene expression microarray datasets after study publication. Automated methods identified 11,603 articles published between 2000 and 2009 that describe the creation of gene expression microarray data. Associated datasets in best-practice repositories were found for 25% of these articles, increasing from less than 5% in 2001 to 30%-35% in 2007-2009. Accounting for sensitivity of the automated methods, approximately 45% of recent gene expression studies made their data publicly available. First-order factor analysis on 124 diverse bibliometric attributes of the data creation articles revealed 15 factors describing authorship, funding, institution, publication, and domain environments. In multivariate regression, authors were most likely to share data if they had prior experience sharing or reusing data, if their study was published in an open access journal or a journal with a relatively strong data sharing policy, or if the study was funded by a large number of NIH grants. Authors of studies on cancer and human subjects were least likely to make their datasets available. These results suggest research data sharing levels are still low and increasing only slowly, and data is least available in areas where it could make the biggest impact. Let's learn from those with high rates of sharing to embrace the full potential of our research output.

Statistical and population genetics issues of two Hungarian datasets from the aspect of DNA evidence interpretation.

PubMed

Szabolcsi, Zoltán; Farkas, Zsuzsa; Borbély, Andrea; Bárány, Gusztáv; Varga, Dániel; Heinrich, Attila; Völgyi, Antónia; Pamjav, Horolma

2015-11-01

When the DNA profile from a crime-scene matches that of a suspect, the weight of DNA evidence depends on the unbiased estimation of the match probability of the profiles. For this reason, it is required to establish and expand the databases that reflect the actual allele frequencies in the population applied. 21,473 complete DNA profiles from Databank samples were used to establish the allele frequency database to represent the population of Hungarian suspects. We used fifteen STR loci (PowerPlex ESI16) including five, new ESS loci. The aim was to calculate the statistical, forensic efficiency parameters for the Databank samples and compare the newly detected data to the earlier report. The population substructure caused by relatedness may influence the frequency of profiles estimated. As our Databank profiles were considered non-random samples, possible relationships between the suspects can be assumed. Therefore, population inbreeding effect was estimated using the FIS calculation. The overall inbreeding parameter was found to be 0.0106. Furthermore, we tested the impact of the two allele frequency datasets on 101 randomly chosen STR profiles, including full and partial profiles. The 95% confidence interval estimates for the profile frequencies (pM) resulted in a tighter range when we used the new dataset compared to the previously published ones. We found that the FIS had less effect on frequency values in the 21,473 samples than the application of minimum allele frequency. No genetic substructure was detected by STRUCTURE analysis. Due to the low level of inbreeding effect and the high number of samples, the new dataset provides unbiased and precise estimates of LR for statistical interpretation of forensic casework and allows us to use lower allele frequencies. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

QuIN: A Web Server for Querying and Visualizing Chromatin Interaction Networks

PubMed Central

Thibodeau, Asa; Márquez, Eladio J.; Luo, Oscar; Ruan, Yijun; Shin, Dong-Guk; Stitzel, Michael L.; Ucar, Duygu

2016-01-01

Recent studies of the human genome have indicated that regulatory elements (e.g. promoters and enhancers) at distal genomic locations can interact with each other via chromatin folding and affect gene expression levels. Genomic technologies for mapping interactions between DNA regions, e.g., ChIA-PET and HiC, can generate genome-wide maps of interactions between regulatory elements. These interaction datasets are important resources to infer distal gene targets of non-coding regulatory elements and to facilitate prioritization of critical loci for important cellular functions. With the increasing diversity and complexity of genomic information and public ontologies, making sense of these datasets demands integrative and easy-to-use software tools. Moreover, network representation of chromatin interaction maps enables effective data visualization, integration, and mining. Currently, there is no software that can take full advantage of network theory approaches for the analysis of chromatin interaction datasets. To fill this gap, we developed a web-based application, QuIN, which enables: 1) building and visualizing chromatin interaction networks, 2) annotating networks with user-provided private and publicly available functional genomics and interaction datasets, 3) querying network components based on gene name or chromosome location, and 4) utilizing network based measures to identify and prioritize critical regulatory targets and their direct and indirect interactions. AVAILABILITY: QuIN’s web server is available at http://quin.jax.org QuIN is developed in Java and JavaScript, utilizing an Apache Tomcat web server and MySQL database and the source code is available under the GPLV3 license available on GitHub: https://github.com/UcarLab/QuIN/. PMID:27336171

MRL and SuperFine+MRL: new supertree methods

PubMed Central

2012-01-01

Background Supertree methods combine trees on subsets of the full taxon set together to produce a tree on the entire set of taxa. Of the many supertree methods, the most popular is MRP (Matrix Representation with Parsimony), a method that operates by first encoding the input set of source trees by a large matrix (the "MRP matrix") over {0,1, ?}, and then running maximum parsimony heuristics on the MRP matrix. Experimental studies evaluating MRP in comparison to other supertree methods have established that for large datasets, MRP generally produces trees of equal or greater accuracy than other methods, and can run on larger datasets. A recent development in supertree methods is SuperFine+MRP, a method that combines MRP with a divide-and-conquer approach, and produces more accurate trees in less time than MRP. In this paper we consider a new approach for supertree estimation, called MRL (Matrix Representation with Likelihood). MRL begins with the same MRP matrix, but then analyzes the MRP matrix using heuristics (such as RAxML) for 2-state Maximum Likelihood. Results We compared MRP and SuperFine+MRP with MRL and SuperFine+MRL on simulated and biological datasets. We examined the MRP and MRL scores of each method on a wide range of datasets, as well as the resulting topological accuracy of the trees. Our experimental results show that MRL, coupled with a very good ML heuristic such as RAxML, produced more accurate trees than MRP, and MRL scores were more strongly correlated with topological accuracy than MRP scores. Conclusions SuperFine+MRP, when based upon a good MP heuristic, such as TNT, produces among the best scores for both MRP and MRL, and is generally faster and more topologically accurate than other supertree methods we tested. PMID:22280525

Pooled solifenacin overactive bladder trial data: Creation, validation and analysis of an integrated database.

PubMed

Chapple, Christopher R; Cardozo, Linda; Snijder, Robert; Siddiqui, Emad; Herschorn, Sender

2016-12-15

Patient-level data are available for 11 randomized, controlled, Phase III/Phase IV solifenacin clinical trials. Meta-analyses were conducted to interrogate the data, to broaden knowledge about solifenacin and overactive bladder (OAB) in general. Before integrating data, datasets from individual studies were mapped to a single format using methodology developed by the Clinical Data Interchange Standards Consortium (CDISC). Initially, the data structure was harmonized, to ensure identical categorization, using the CDISC Study Data Tabulation Model (SDTM). To allow for patient level meta-analysis, data were integrated and mapped to analysis datasets. Mapping included adding derived and categorical variables and followed standards described as the Analysis Data Model (ADaM). Mapping to both SDTM and ADaM was performed twice by two independent programming teams, results compared, and inconsistencies corrected in the final output. ADaM analysis sets included assignments of patients to the Safety Analysis Set and the Full Analysis Set. There were three analysis groupings: Analysis group 1 (placebo-controlled, monotherapy, fixed-dose studies, n = 3011); Analysis group 2 (placebo-controlled, monotherapy, pooled, fixed- and flexible-dose, n = 5379); Analysis group 3 (all solifenacin monotherapy-treated patients, n = 6539). Treatment groups were: solifenacin 5 mg fixed dose, solifenacin 5/10 mg flexible dose, solifenacin 10 mg fixed dose and overall solifenacin. Patient were similar enough for data pooling to be acceptable. Creating ADaM datasets provided significant information about individual studies and the derivation decisions made in each study; validated ADaM datasets now exist for medical history, efficacy and AEs. Results from these meta-analyses were similar over time.

EFEHR - the European Facilities for Earthquake Hazard and Risk: beyond the web-platform

NASA Astrophysics Data System (ADS)

Danciu, Laurentiu; Wiemer, Stefan; Haslinger, Florian; Kastli, Philipp; Giardini, Domenico

2017-04-01

European Facilities for Earthquake Hazard and Risk (EEFEHR) represents the sustainable community resource for seismic hazard and risk in Europe. The EFEHR web platform is the main gateway to access data, models and tools as well as provide expertise relevant for assessment of seismic hazard and risk. The main services (databases and web-platform) are hosted at ETH Zurich and operated by the Swiss Seismological Service (Schweizerischer Erdbebendienst SED). EFEHR web-portal (www.efehr.org) collects and displays (i) harmonized datasets necessary for hazard and risk modeling, e.g. seismic catalogues, fault compilations, site amplifications, vulnerabilities, inventories; (ii) extensive seismic hazard products, namely hazard curves, uniform hazard spectra and maps for national and regional assessments. (ii) standardized configuration files for re-computing the regional seismic hazard models; (iv) relevant documentation of harmonized datasets, models and web-services. Today, EFEHR distributes full output of the 2013 European Seismic Hazard Model, ESHM13, as developed within the SHARE project (http://www.share-eu.org/); the latest results of the 2014 Earthquake Model of the Middle East (EMME14), derived within the EMME Project (www.emme-gem.org); the 2001 Global Seismic Hazard Assessment Project (GSHAP) results and the 2015 updates of the Swiss Seismic Hazard. New datasets related to either seismic hazard or risk will be incorporated as they become available. We present the currents status of the EFEHR platform, with focus on the challenges, summaries of the up-to-date datasets, user experience and feedback, as well as the roadmap to future technological innovation beyond the web-platform development. We also show the new services foreseen to fully integrate with the seismological core services of European Plate Observing System (EPOS).

Deep learning in breast cancer risk assessment: evaluation of fine-tuned convolutional neural networks on a clinical dataset of FFDMs

NASA Astrophysics Data System (ADS)

Li, Hui; Mendel, Kayla R.; Lee, John H.; Lan, Li; Giger, Maryellen L.

2018-02-01

We evaluated the potential of deep learning in the assessment of breast cancer risk using convolutional neural networks (CNNs) fine-tuned on full-field digital mammographic (FFDM) images. This study included 456 clinical FFDM cases from two high-risk datasets: BRCA1/2 gene-mutation carriers (53 cases) and unilateral cancer patients (75 cases), and a low-risk dataset as the control group (328 cases). All FFDM images (12-bit quantization and 100 micron pixel) were acquired with a GE Senographe 2000D system and were retrospectively collected under an IRB-approved, HIPAA-compliant protocol. Regions of interest of 256x256 pixels were selected from the central breast region behind the nipple in the craniocaudal projection. VGG19 pre-trained on the ImageNet dataset was used to classify the images either as high-risk or as low-risk subjects. The last fully-connected layer of pre-trained VGG19 was fine-tuned on FFDM images for breast cancer risk assessment. Performance was evaluated using the area under the receiver operating characteristic (ROC) curve (AUC) in the task of distinguishing between high-risk and low-risk subjects. AUC values of 0.84 (SE=0.05) and 0.72 (SE=0.06) were obtained in the task of distinguishing between the BRCA1/2 gene-mutation carriers and low-risk women and between unilateral cancer patients and low-risk women, respectively. Deep learning with CNNs appears to be able to extract parenchymal characteristics directly from FFDMs which are relevant to the task of distinguishing between cancer risk populations, and therefore has potential to aid clinicians in assessing mammographic parenchymal patterns for cancer risk assessment.

Earth History databases and visualization - the TimeScale Creator system

NASA Astrophysics Data System (ADS)

Ogg, James; Lugowski, Adam; Gradstein, Felix

2010-05-01

The "TimeScale Creator" team (www.tscreator.org) and the Subcommission on Stratigraphic Information (stratigraphy.science.purdue.edu) of the International Commission on Stratigraphy (www.stratigraphy.org) has worked with numerous geoscientists and geological surveys to prepare reference datasets for global and regional stratigraphy. All events are currently calibrated to Geologic Time Scale 2004 (Gradstein et al., 2004, Cambridge Univ. Press) and Concise Geologic Time Scale (Ogg et al., 2008, Cambridge Univ. Press); but the array of intercalibrations enable dynamic adjustment to future numerical age scales and interpolation methods. The main "global" database contains over 25,000 events/zones from paleontology, geomagnetics, sea-level and sequence stratigraphy, igneous provinces, bolide impacts, plus several stable isotope curves and image sets. Several regional datasets are provided in conjunction with geological surveys, with numerical ages interpolated using a similar flexible inter-calibration procedure. For example, a joint program with Geoscience Australia has compiled an extensive Australian regional biostratigraphy and a full array of basin lithologic columns with each formation linked to public lexicons of all Proterozoic through Phanerozoic basins - nearly 500 columns of over 9,000 data lines plus hot-curser links to oil-gas reference wells. Other datapacks include New Zealand biostratigraphy and basin transects (ca. 200 columns), Russian biostratigraphy, British Isles regional stratigraphy, Gulf of Mexico biostratigraphy and lithostratigraphy, high-resolution Neogene stable isotope curves and ice-core data, human cultural episodes, and Circum-Arctic stratigraphy sets. The growing library of datasets is designed for viewing and chart-making in the free "TimeScale Creator" JAVA package. This visualization system produces a screen display of the user-selected time-span and the selected columns of geologic time scale information. The user can change the vertical-scale, column widths, fonts, colors, titles, ordering, range chart options and many other features. Mouse-activated pop-ups provide additional information on columns and events; including links to external Internet sites. The graphics can be saved as SVG (scalable vector graphics) or PDF files for direct import into Adobe Illustrator or other common drafting software. Users can load additional regional datapacks, and create and upload their own datasets. The "Pro" version has additional dataset-creation tools, output options and the ability to edit and re-save merged datasets. The databases and visualization package are envisioned as a convenient reference tool, chart-production assistant, and a window into the geologic history of our planet.

Online Visualization and Analysis of Merged Global Geostationary Satellite Infrared Dataset

NASA Technical Reports Server (NTRS)

Liu, Zhong; Ostrenga, D.; Leptoukh, G.; Mehta, A.

2008-01-01

The NASA Goddard Earth Sciences Data Information Services Center (GES DISC) is home of Tropical Rainfall Measuring Mission (TRMM) data archive. The global merged IR product also known as the NCEP/CPC 4-km Global (60 degrees N - 60 degrees S) IR Dataset, is one of TRMM ancillary datasets. They are globally merged (60 degrees N - 60 degrees S) pixel-resolution (4 km) IR brightness temperature data (equivalent blackbody temperatures), merged from all available geostationary satellites (GOES-8/10, METEOSAT-7/5 and GMS). The availability of data from METEOSAT-5, which is located at 63E at the present time, yields a unique opportunity for total global (60 degrees N- 60 degrees S) coverage. The GES DISC has collected over 8 years of the data beginning from February of 2000. This high temporal resolution dataset can not only provide additional background information to TRMM and other satellite missions, but also allow observing a wide range of meteorological phenomena from space, such as, mesoscale convection systems, tropical cyclones, hurricanes, etc. The dataset can also be used to verify model simulations. Despite that the data can be downloaded via ftp, however, its large volume poses a challenge for many users. A single file occupies about 70 MB disk space and there is a total of approximately 73,000 files (approximately 4.5 TB) for the past 8 years. In order to facilitate data access, we have developed a web prototype to allow users to conduct online visualization and analysis of this dataset. With a web browser and few mouse clicks, users can have a full access to over 8 year and over 4.5 TB data and generate black and white IR imagery and animation without downloading any software and data. In short, you can make your own images! Basic functions include selection of area of interest, single imagery or animation, a time skip capability for different temporal resolution and image size. Users can save an animation as a file (animated gif) and import it in other presentation software, such as, Microsoft PowerPoint. The prototype will be integrated into GIOVANNI and existing GIOVANNI capabilities, such as, data download, Google Earth KMZ, etc will be available. Users will also be able to access other data products in the GIOVANNI family.

Machine learning methods can replace 3D profile method in classification of amyloidogenic hexapeptides.

PubMed

Stanislawski, Jerzy; Kotulska, Malgorzata; Unold, Olgierd

2013-01-17

Amyloids are proteins capable of forming fibrils. Many of them underlie serious diseases, like Alzheimer disease. The number of amyloid-associated diseases is constantly increasing. Recent studies indicate that amyloidogenic properties can be associated with short segments of aminoacids, which transform the structure when exposed. A few hundreds of such peptides have been experimentally found. Experimental testing of all possible aminoacid combinations is currently not feasible. Instead, they can be predicted by computational methods. 3D profile is a physicochemical-based method that has generated the most numerous dataset - ZipperDB. However, it is computationally very demanding. Here, we show that dataset generation can be accelerated. Two methods to increase the classification efficiency of amyloidogenic candidates are presented and tested: simplified 3D profile generation and machine learning methods. We generated a new dataset of hexapeptides, using more economical 3D profile algorithm, which showed very good classification overlap with ZipperDB (93.5%). The new part of our dataset contains 1779 segments, with 204 classified as amyloidogenic. The dataset of 6-residue sequences with their binary classification, based on the energy of the segment, was applied for training machine learning methods. A separate set of sequences from ZipperDB was used as a test set. The most effective methods were Alternating Decision Tree and Multilayer Perceptron. Both methods obtained area under ROC curve of 0.96, accuracy 91%, true positive rate ca. 78%, and true negative rate 95%. A few other machine learning methods also achieved a good performance. The computational time was reduced from 18-20 CPU-hours (full 3D profile) to 0.5 CPU-hours (simplified 3D profile) to seconds (machine learning). We showed that the simplified profile generation method does not introduce an error with regard to the original method, while increasing the computational efficiency. Our new dataset proved representative enough to use simple statistical methods for testing the amylogenicity based only on six letter sequences. Statistical machine learning methods such as Alternating Decision Tree and Multilayer Perceptron can replace the energy based classifier, with advantage of very significantly reduced computational time and simplicity to perform the analysis. Additionally, a decision tree provides a set of very easily interpretable rules.

8D.07: GENE EXPRESSION ANALYSIS AND BIOINFORMATICS REVEALED POTENTIAL TRANSCRIPTION FACTORS ASSOCIATED WITH RENIN-ANGIOTENSIN-ALDOSTERONE SYSTEM IN ATHEROMA.

PubMed

Nehme, A; Zibara, K; Cerutti, C; Bricca, G

2015-06-01

The implication of the renin-angiotensin-aldosterone system (RAAS) in atheroma development is well described. However, a complete view of the local RAAS in atheroma is still missing. In this study we aimed to reveal the organization of RAAS in atheroma at the transcriptomic level and identify the transcriptional regulators behind it. Extended RAAS (extRAAS) was defined as the set of 37 genes coding for classical and novel RAAS participants (Figure 1). Five microarray datasets containing overall 590 samples representing carotid and peripheral atheroma were downloaded from the GEO database. Correlation-based hierarchical clustering (R software) of extRAAS genes within each dataset allowed the identification of modules of co-expressed genes. Reproducible co-expression modules across datasets were then extracted. Transcription factors (TFs) having common binding sites (TFBSs) in the promoters of coordinated genes were identified using the Genomatix database tools and analyzed for their correlation with extRAAS genes in the microarray datasets. Expression data revealed the expressed extRAAS components and their relative abundance displaying the favored pathways in atheroma. Three co-expression modules with more than 80% reproducibility across datasets were extracted. Two of them (M1 and M2) contained genes coding for angiotensin metabolizing enzymes involved in different pathways: M1 included ACE, MME, RNPEP, and DPP3, in addition to 7 other genes; and M2 included CMA1, CTSG, and CPA3. The third module (M3) contained genes coding for receptors known to be implicated in atheroma (AGTR1, MR, GR, LNPEP, EGFR and GPER). M1 and M3 were negatively correlated in 3 of 5 datasets. We identified 19 TFs that have enriched TFBSs in the promoters of genes of M1, and two for M3, but none was found for M2. Among the extracted TFs, ELF1, MAX, and IRF5 showed significant positive correlations with peptidase-coding genes from M1 and negative correlations with receptors-coding genes from M3 (p < 0.05). The identified co-expression modules display the transcriptional organization of local extRAAS in human carotid atheroma. The identification of several TFs potentially associated to extRAAS genes may provide a frame for the discovery of atheroma-specific modulators of extRAAS activity.(Figure is included in full-text article.).

Fear of darkness, the full moon and the nocturnal ecology of African lions.

PubMed

Packer, Craig; Swanson, Alexandra; Ikanda, Dennis; Kushnir, Hadas

2011-01-01

Nocturnal carnivores are widely believed to have played an important role in human evolution, driving the need for night-time shelter, the control of fire and our innate fear of darkness. However, no empirical data are available on the effects of darkness on the risks of predation in humans. We performed an extensive analysis of predatory behavior across the lunar cycle on the largest dataset of lion attacks ever assembled and found that African lions are as sensitive to moonlight when hunting humans as when hunting herbivores and that lions are most dangerous to humans when the moon is faint or below the horizon. At night, people are most active between dusk and 10:00 pm, thus most lion attacks occur in the first weeks following the full moon (when the moon rises at least an hour after sunset). Consequently, the full moon is a reliable indicator of impending danger, perhaps helping to explain why the full moon has been the subject of so many myths and misconceptions.

Study of B to pi l nu and B to rho l nu Decays and Determination of |V_ub|

DOE Office of Scientific and Technical Information (OSTI.GOV)

del Amo Sanchez, P.; Lees, J.P.; Poireau, V.

2011-12-09

We present an analysis of exclusive charmless semileptonic B-meson decays based on 377 million B{bar B} pairs recorded with the BABAR detector at the {Upsilon} (4S) resonance. We select four event samples corresponding to the decay modes B{sup 0} {yields} {pi}{sup -}{ell}{sup +}{nu}, B{sup +} {yields} {pi}{sup 0}{ell}{sup +}{nu}, B{sup 0} {yields} {rho}{sup -}{ell}{sup +}{nu}, and B{sup +} {yields} {rho}{sup 0}{ell}{sup +}{nu}, and find the measured branching fractions to be consistent with isospin symmetry. Assuming isospin symmetry, we combine the two B {yields} {pi}{ell}{nu} samples, and similarly the two B {yields} {rho}{ell}{nu} samples, and measure the branching fractions {Beta}(B{sup 0}more » {yields} {pi}{sup -}{ell}{sup +}{nu}) = (1.41 {+-} 0.05 {+-} 0.07) x 10{sup -4} and {Beta}(B{sup 0} {yields} {rho}{sup 0}{ell}{sup +}{nu}) = (1.75 {+-} 0.15 {+-} 0.27) x 10{sup -4}, where the errors are statistical and systematic. We compare the measured distribution in q{sup 2}, the momentum transfer squared, with predictions for the form factors from QCD calculations and determine the CKM matrix element |V{sub ub}|. Based on the measured partial branching fraction for B {yields} {pi}{ell}{nu} in the range q{sup 2} < 12 GeV{sup 2} and the most recent LCSR calculations we obtain |V{sub ub}| = (3.78 {+-} 0.13{sub -0.40}{sup +0.55}) x 10{sup -3}, where the errors refer to the experimental and theoretical uncertainties. From a simultaneous fit to the data over the full q{sup 2} range and the FNAL/MILC lattice QCD results, we obtain |V{sub ub}| = (2.95 {+-} 0.31) x 10{sup -3} from B {yields} {pi}{ell}{nu}, where the error is the combined experimental and theoretical uncertainty.« less

Measurement of inclusive radiative B-meson decay B decaying to X(S) meson-gamma

NASA Astrophysics Data System (ADS)

Ozcan, Veysi Erkcan

Radiative decays of the B meson, B→ Xsgamma, proceed via virtual flavor changing neutral current processes that are sensitive to contributions from high mass scales, either within the Standard Model of electroweak interactions or beyond. In the Standard Model, these transitions are sensitive to the weak interactions of the top quark, and relatively robust predictions of the inclusive decay rate exist. Significant deviation from these predictions could be interpreted as indications for processes not included in the minimal Standard Model, like interactions of charged Higgs or SUSY particles. The analysis of the inclusive photon spectrum from B→ Xsgamma decays is rather challenging due to high backgrounds from photons emitted in the decay of mesons in B decays as well as e+e- annihilation to low mass quark and lepton pairs. Based on 88.5 million BB events collected by the BABAR detector, the photon spectrum above 1.9 GeV is presented. By comparison of the first and second moments of the photon spectrum with QCD predictions (calculated in the kinetic scheme), QCD parameters describing the bound state of the b quark in the B meson are extracted: mb=4.45+/-0.16 GeV/c2m2 p=0.65+/-0.29 GeV2 These parameters are useful input to non-perturbative QCD corrections to the semileptonic B decay rate and the determination of the CKM parameter Vub. Based on these parameters and heavy quark expansion, the full branching fraction is obtained as: BRB→X sgEg >1.6GeV=4.050.32 stat+/-0.38syst +/-0.29model x10-4. This result is in good agreement with previous measurements, the statistical and systematic errors are comparable. It is also in good agreement with the theoretical Standard Model predictions, and thus within the present errors there is no indication of any interactions not accounted for in the Standard Model. This finding implies strong constraints on physics beyond the Standard Model.

Genome-Wide Association Study of a Validated Case Definition of Gulf War Illness in a Population-Representative Sample

DTIC Science & Technology

2013-09-01

sequence dataset. All procedures were performed by personnel in the IIMT UT Southwestern Genomics and Microarray Core using standard protocols. More... sequencing run, samples were demultiplexed using standard algorithms in the Genomics and Microarray Core and processed into individual sample Illumina single... Sequencing (RNA-Seq), using Illumina’s multiplexing mRNA-Seq to generate full sequence libraries from the poly-A tailed RNA to a read depth of 30

Using smart card technology to monitor the eating habits of children in a school cafeteria: 1. Developing and validating the methodology.

PubMed

Lambert, N; Plumb, J; Looise, B; Johnson, I T; Harvey, I; Wheeler, C; Robinson, M; Rolfe, P

2005-08-01

The aim of the study was to test the feasibility of using smart card technology to track the eating behaviours of nearly a thousand children in a school cafeteria. Within a large boys' school a smart card based system was developed that was capable of providing a full electronic audit of all the individual transactions that occurred within the cafeteria. This dataset was interfaced to an electronic version of the McCance and Widdowson composition of foods dataset. The accuracy of the smart card generated data and the influence of portion size and wastage were determined empirically during two 5-day trials. The smart card system created succeeded in generating precise data on the food choices made by hundreds of children over an indefinite time period. The data was expanded to include a full nutrient analysis of all the foods chosen. The accuracy of this information was only constrained by the limitations facing all food composition research, e.g. variations in recipes, portion sizes, cooking practices, etc. Although technically possible to introduce wastage correction factors into the software, thereby providing information upon foods consumed, this was not seen as universally practical. The study demonstrated the power of smart card technology for monitoring food/nutrient choice over limitless time in environments such as school cafeterias. The strengths, limitations and applications of such technology are discussed.

Xander: employing a novel method for efficient gene-targeted metagenomic assembly

DOE PAGES

Wang, Qiong; Fish, Jordan A.; Gilman, Mariah; ...

2015-08-05

Here, metagenomics can provide important insight into microbial communities. However, assembling metagenomic datasets has proven to be computationally challenging. Current methods often assemble only fragmented partial genes. We present a novel method for targeting assembly of specific protein-coding genes. This method combines a de Bruijn graph, as used in standard assembly approaches, and a protein profile hidden Markov model (HMM) for the gene of interest, as used in standard annotation approaches. These are used to create a novel combined weighted assembly graph. Xander performs both assembly and annotation concomitantly using information incorporated in this graph. We demonstrate the utility ofmore » this approach by assembling contigs for one phylogenetic marker gene and for two functional marker genes, first on Human Microbiome Project (HMP)-defined community Illumina data and then on 21 rhizosphere soil metagenomic datasets from three different crops totaling over 800 Gbp of unassembled data. We compared our method to a recently published bulk metagenome assembly method and a recently published gene-targeted assembler and found our method produced more, longer, and higher quality gene sequences. In conclusion, xander combines gene assignment with the rapid assembly of full-length or near full-length functional genes from metagenomic data without requiring bulk assembly or post-processing to find genes of interest. HMMs used for assembly can be tailored to the targeted genes, allowing flexibility to improve annotation over generic annotation pipelines.« less

Kubo-Greenwood electrical conductivity formulation and implementation for projector augmented wave datasets

NASA Astrophysics Data System (ADS)

Calderín, L.; Karasiev, V. V.; Trickey, S. B.

2017-12-01

As the foundation for a new computational implementation, we survey the calculation of the complex electrical conductivity tensor based on the Kubo-Greenwood (KG) formalism (Kubo, 1957; Greenwood, 1958), with emphasis on derivations and technical aspects pertinent to use of projector augmented wave datasets with plane wave basis sets (Blöchl, 1994). New analytical results and a full implementation of the KG approach in an open-source Fortran 90 post-processing code for use with Quantum Espresso (Giannozzi et al., 2009) are presented. Named KGEC ([K]ubo [G]reenwood [E]lectronic [C]onductivity), the code calculates the full complex conductivity tensor (not just the average trace). It supports use of either the original KG formula or the popular one approximated in terms of a Dirac delta function. It provides both Gaussian and Lorentzian representations of the Dirac delta function (though the Lorentzian is preferable on basic grounds). KGEC provides decomposition of the conductivity into intra- and inter-band contributions as well as degenerate state contributions. It calculates the dc conductivity tensor directly. It is MPI parallelized over k-points, bands, and plane waves, with an option to recover the plane wave processes for their use in band parallelization as well. It is designed to provide rapid convergence with respect to k-point density. Examples of its use are given.

Assessing Variations in Areal Organization for the Intrinsic Brain: From Fingerprints to Reliability

PubMed Central

Xu, Ting; Opitz, Alexander; Craddock, R. Cameron; Wright, Margaret J.; Zuo, Xi-Nian; Milham, Michael P.

2016-01-01

Resting state fMRI (R-fMRI) is a powerful in-vivo tool for examining the functional architecture of the human brain. Recent studies have demonstrated the ability to characterize transitions between functionally distinct cortical areas through the mapping of gradients in intrinsic functional connectivity (iFC) profiles. To date, this novel approach has primarily been applied to iFC profiles averaged across groups of individuals, or in one case, a single individual scanned multiple times. Here, we used a publically available R-fMRI dataset, in which 30 healthy participants were scanned 10 times (10 min per session), to investigate differences in full-brain transition profiles (i.e., gradient maps, edge maps) across individuals, and their reliability. 10-min R-fMRI scans were sufficient to achieve high accuracies in efforts to “fingerprint” individuals based upon full-brain transition profiles. Regarding test–retest reliability, the image-wise intraclass correlation coefficient (ICC) was moderate, and vertex-level ICC varied depending on region; larger durations of data yielded higher reliability scores universally. Initial application of gradient-based methodologies to a recently published dataset obtained from twins suggested inter-individual variation in areal profiles might have genetic and familial origins. Overall, these results illustrate the utility of gradient-based iFC approaches for studying inter-individual variation in brain function. PMID:27600846

DOE Office of Scientific and Technical Information (OSTI.GOV)

Becker, M. R.

We present the first constraints on cosmology from the Dark Energy Survey (DES), using weak lensing measurements from the preliminary Science Verification (SV) data. We use 139 square degrees of SV data, which is less than 3% of the full DES survey area. Using cosmic shear 2-point measurements over three redshift bins we find σ 8(m=0.3) 0.5 = 0:81 ± 0:06 (68% confidence), after marginalising over 7 systematics parameters and 3 other cosmological parameters. Furthermore, we examine the robustness of our results to the choice of data vector and systematics assumed, and find them to be stable. About 20% ofmore » our error bar comes from marginalising over shear and photometric redshift calibration uncertainties. The current state-of-the-art cosmic shear measurements from CFHTLenS are mildly discrepant with the cosmological constraints from Planck CMB data. Our results are consistent with both datasets. Our uncertainties are ~30% larger than those from CFHTLenS when we carry out a comparable analysis of the two datasets, which we attribute largely to the lower number density of our shear catalogue. We investigate constraints on dark energy and find that, with this small fraction of the full survey, the DES SV constraints make negligible impact on the Planck constraints. The moderate disagreement between the CFHTLenS and Planck values of σ 8(Ω m=0.3) 0.5 is present regardless of the value of w.« less

Using the Full Cycle of GOCE Data in the Quasi-Geoid Modelling of Finland

NASA Astrophysics Data System (ADS)

Saari, Timo; Bilker-Koivula, Mirjam; Poutanen, Markku

2016-08-01

In the Dragon 3 project 10519 "Case study on heterogeneous geoid/quasigeoid based on space borne and terrestrial data combination with special consideration of GOCE mission data impact" we combined the latest GOCE models with the terrestrial gravity data of Finland and surrounding areas to calculate a quasi-geoid model for Finland. Altogether 249 geoid models with different modifications were calculated using the GOCE DIR5 models up to spherical harmonic degree and order 240 and 300 and the EIGEN-6C4 up to degree and order 1000 and 2190.The calculated quasi-geoid models were compared against the ground truth in Finland with two independent GPS-levelling datasets. The best GOCE- only models gave standard deviations of 2.8 cm, 2.6 cm (DIR5 d/o 240) and 2.7 cm, 2.3 cm (DIR5 d/o 300) in Finnish territory for NLS-FIN and EUVN-DA datasets, respectively. For the high resolution model EIGEN-6C4 (which includes the full cycle of the GOCE data), the results were 2.4 cm, 1.8 cm (d/o 1000) and 2.5 cm, 1.7 (d/o 2190). The sub-2-centimetre (and near 2 cm with GOCE-only) accuracy is an improvement over the previous and current Finnish geoid models, thus leading to a conclusion of the great impact of the GOCE- mission on regional geoid modelling.

Coupled Harmonic Bases for Longitudinal Characterization of Brain Networks

PubMed Central

Hwang, Seong Jae; Adluru, Nagesh; Collins, Maxwell D.; Ravi, Sathya N.; Bendlin, Barbara B.; Johnson, Sterling C.; Singh, Vikas

2016-01-01

There is a great deal of interest in using large scale brain imaging studies to understand how brain connectivity evolves over time for an individual and how it varies over different levels/quantiles of cognitive function. To do so, one typically performs so-called tractography procedures on diffusion MR brain images and derives measures of brain connectivity expressed as graphs. The nodes correspond to distinct brain regions and the edges encode the strength of the connection. The scientific interest is in characterizing the evolution of these graphs over time or from healthy individuals to diseased. We pose this important question in terms of the Laplacian of the connectivity graphs derived from various longitudinal or disease time points — quantifying its progression is then expressed in terms of coupling the harmonic bases of a full set of Laplacians. We derive a coupled system of generalized eigenvalue problems (and corresponding numerical optimization schemes) whose solution helps characterize the full life cycle of brain connectivity evolution in a given dataset. Finally, we show a set of results on a diffusion MR imaging dataset of middle aged people at risk for Alzheimer’s disease (AD), who are cognitively healthy. In such asymptomatic adults, we find that a framework for characterizing brain connectivity evolution provides the ability to predict cognitive scores for individual subjects, and for estimating the progression of participant’s brain connectivity into the future. PMID:27812274

EarthServer: Visualisation and use of uncertainty as a data exploration tool

NASA Astrophysics Data System (ADS)

Walker, Peter; Clements, Oliver; Grant, Mike

2013-04-01

The Ocean Science/Earth Observation community generates huge datasets from satellite observation. Until recently it has been difficult to obtain matching uncertainty information for these datasets and to apply this to their processing. In order to make use of uncertainty information when analysing "Big Data" we need both the uncertainty itself (attached to the underlying data) and a means of working with the combined product without requiring the entire dataset to be downloaded. The European Commission FP7 project EarthServer (http://earthserver.eu) is addressing the problem of accessing and ad-hoc analysis of extreme-size Earth Science data using cutting-edge Array Database technology. The core software (Rasdaman) and web services wrapper (Petascope) allow huge datasets to be accessed using Open Geospatial Consortium (OGC) standard interfaces including the well established standards, Web Coverage Service (WCS) and Web Map Service (WMS) as well as the emerging standard, Web Coverage Processing Service (WCPS). The WCPS standard allows the running of ad-hoc queries on any of the data stored within Rasdaman, creating an infrastructure where users are not restricted by bandwidth when manipulating or querying huge datasets. The ESA Ocean Colour - Climate Change Initiative (OC-CCI) project (http://www.esa-oceancolour-cci.org/), is producing high-resolution, global ocean colour datasets over the full time period (1998-2012) where high quality observations were available. This climate data record includes per-pixel uncertainty data for each variable, based on an analytic method that classifies how much and which types of water are present in a pixel, and assigns uncertainty based on robust comparisons to global in-situ validation datasets. These uncertainty values take two forms, Root Mean Square (RMS) and Bias uncertainty, respectively representing the expected variability and expected offset error. By combining the data produced through the OC-CCI project with the software from the EarthServer project we can produce a novel data offering that allows the use of traditional exploration and access mechanisms such as WMS and WCS. However the real benefits can be seen when utilising WCPS to explore the data . We will show two major benefits to this infrastructure. Firstly we will show that the visualisation of the combined chlorophyll and uncertainty datasets through a web based GIS portal gives users the ability to instantaneously assess the quality of the data they are exploring using traditional web based plotting techniques as well as through novel web based 3 dimensional visualisation. Secondly we will showcase the benefits available when combining these data with the WCPS standard. The uncertainty data can be utilised in queries using the standard WCPS query language. This allows selection of data either for download or use within the query, based on the respective uncertainty values as well as the possibility of incorporating both the chlorophyll data and uncertainty data into complex queries to produce additional novel data products. By filtering with uncertainty at the data source rather than the client we can minimise traffic over the network allowing huge datasets to be worked on with a minimal time penalty.

PAIR Comparison between Two Within-Group Conditions of Resting-State fMRI Improves Classification Accuracy

PubMed Central

Zhou, Zhen; Wang, Jian-Bao; Zang, Yu-Feng; Pan, Gang

2018-01-01

Classification approaches have been increasingly applied to differentiate patients and normal controls using resting-state functional magnetic resonance imaging data (RS-fMRI). Although most previous classification studies have reported promising accuracy within individual datasets, achieving high levels of accuracy with multiple datasets remains challenging for two main reasons: high dimensionality, and high variability across subjects. We used two independent RS-fMRI datasets (n = 31, 46, respectively) both with eyes closed (EC) and eyes open (EO) conditions. For each dataset, we first reduced the number of features to a small number of brain regions with paired t-tests, using the amplitude of low frequency fluctuation (ALFF) as a metric. Second, we employed a new method for feature extraction, named the PAIR method, examining EC and EO as paired conditions rather than independent conditions. Specifically, for each dataset, we obtained EC minus EO (EC—EO) maps of ALFF from half of subjects (n = 15 for dataset-1, n = 23 for dataset-2) and obtained EO—EC maps from the other half (n = 16 for dataset-1, n = 23 for dataset-2). A support vector machine (SVM) method was used for classification of EC RS-fMRI mapping and EO mapping. The mean classification accuracy of the PAIR method was 91.40% for dataset-1, and 92.75% for dataset-2 in the conventional frequency band of 0.01–0.08 Hz. For cross-dataset validation, we applied the classifier from dataset-1 directly to dataset-2, and vice versa. The mean accuracy of cross-dataset validation was 94.93% for dataset-1 to dataset-2 and 90.32% for dataset-2 to dataset-1 in the 0.01–0.08 Hz range. For the UNPAIR method, classification accuracy was substantially lower (mean 69.89% for dataset-1 and 82.97% for dataset-2), and was much lower for cross-dataset validation (64.69% for dataset-1 to dataset-2 and 64.98% for dataset-2 to dataset-1) in the 0.01–0.08 Hz range. In conclusion, for within-group design studies (e.g., paired conditions or follow-up studies), we recommend the PAIR method for feature extraction. In addition, dimensionality reduction with strong prior knowledge of specific brain regions should also be considered for feature selection in neuroimaging studies. PMID:29375288

Applicability of the iterative technique for cardiac resynchronization therapy optimization: full-disclosure, 50-sequential-patient dataset of transmitral Doppler traces, with implications for future research design and guidelines.

PubMed

Jones, Siana; Shun-Shin, Matthew J; Cole, Graham D; Sau, Arunashis; March, Katherine; Williams, Suzanne; Kyriacou, Andreas; Hughes, Alun D; Mayet, Jamil; Frenneaux, Michael; Manisty, Charlotte H; Whinnett, Zachary I; Francis, Darrel P

2014-04-01

Full-disclosure study describing Doppler patterns during iterative atrioventricular delay (AVD) optimization of biventricular pacemakers (cardiac resynchronization therapy, CRT). Doppler traces of the first 50 eligible patients undergoing iterative Doppler AVD optimization in the BRAVO trial were examined. Three experienced observers classified conformity to guideline-described patterns. Each observer then selected the optimum AVD on two separate occasions: blinded and unblinded to AVD. Four Doppler E-A patterns occurred: A (always merged, 18% of patients), B (incrementally less fusion at short AVDs, 12%), C (full separation at short AVDs, as described by the guidelines, 28%), and D (always separated, 42%). In Groups A and D (60%), the iterative guidelines therefore cannot specify one single AVD. On the kappa scale (0 = chance alone; 1 = perfect agreement), observer agreement for the ideal AVD in Classes B and C was poor (0.32) and appeared worse in Groups A and D (0.22). Blinding caused the scattering of the AVD selected as optimal to widen (standard deviation rising from 37 to 49 ms, P < 0.001). By blinding 28% of the selected optimum AVDs were ≤60 or ≥200 ms. All 50 Doppler datasets are presented, to support future methodological testing. In most patients, the iterative method does not clearly specify one AVD. In all the patients, agreement on the ideal AVD between skilled observers viewing identical images is poor. The iterative protocol may successfully exclude some extremely unsuitable AVDs, but so might simply accepting factory default. Irreproducibility of the gold standard also prevents alternative physiological optimization methods from being validated honestly.

Automated retinal image quality assessment on the UK Biobank dataset for epidemiological studies.

PubMed

Welikala, R A; Fraz, M M; Foster, P J; Whincup, P H; Rudnicka, A R; Owen, C G; Strachan, D P; Barman, S A

2016-04-01

Morphological changes in the retinal vascular network are associated with future risk of many systemic and vascular diseases. However, uncertainty over the presence and nature of some of these associations exists. Analysis of data from large population based studies will help to resolve these uncertainties. The QUARTZ (QUantitative Analysis of Retinal vessel Topology and siZe) retinal image analysis system allows automated processing of large numbers of retinal images. However, an image quality assessment module is needed to achieve full automation. In this paper, we propose such an algorithm, which uses the segmented vessel map to determine the suitability of retinal images for use in the creation of vessel morphometric data suitable for epidemiological studies. This includes an effective 3-dimensional feature set and support vector machine classification. A random subset of 800 retinal images from UK Biobank (a large prospective study of 500,000 middle aged adults; where 68,151 underwent retinal imaging) was used to examine the performance of the image quality algorithm. The algorithm achieved a sensitivity of 95.33% and a specificity of 91.13% for the detection of inadequate images. The strong performance of this image quality algorithm will make rapid automated analysis of vascular morphometry feasible on the entire UK Biobank dataset (and other large retinal datasets), with minimal operator involvement, and at low cost. Copyright © 2016 Elsevier Ltd. All rights reserved.

Assessing the accuracy and stability of variable selection ...

EPA Pesticide Factsheets

Random forest (RF) modeling has emerged as an important statistical learning method in ecology due to its exceptional predictive performance. However, for large and complex ecological datasets there is limited guidance on variable selection methods for RF modeling. Typically, either a preselected set of predictor variables are used, or stepwise procedures are employed which iteratively add/remove variables according to their importance measures. This paper investigates the application of variable selection methods to RF models for predicting probable biological stream condition. Our motivating dataset consists of the good/poor condition of n=1365 stream survey sites from the 2008/2009 National Rivers and Stream Assessment, and a large set (p=212) of landscape features from the StreamCat dataset. Two types of RF models are compared: a full variable set model with all 212 predictors, and a reduced variable set model selected using a backwards elimination approach. We assess model accuracy using RF's internal out-of-bag estimate, and a cross-validation procedure with validation folds external to the variable selection process. We also assess the stability of the spatial predictions generated by the RF models to changes in the number of predictors, and argue that model selection needs to consider both accuracy and stability. The results suggest that RF modeling is robust to the inclusion of many variables of moderate to low importance. We found no substanti

A Preliminary Investigation of Reversing RML: From an RDF dataset to its Column-Based data source

PubMed Central

Gougousis, Alexandros

2015-01-01

Abstract Background A large percentage of scientific data with tabular structure are published on the Web of Data as interlinked RDF datasets. When we come to the issue of long-term preservation of such RDF-based digital objects, it is important to provide full support for reusing them in the future. In particular, it should include means for both players who have no familiarity with RDF data model and, at the same time, who by working only with the native format of the data still provide sufficient information. To achieve this, we need mechanisms to bring the data back to their original format and structure. New information In this paper, we investigate how to perform the reverse process for column-based data sources. In particular, we devise an algorithm, RML2CSV, and exemplify its implementation in transforming an RDF dataset into its CSV tabular structure, through the use of the same RML mapping document that was used to generate the set of RDF triples. Through a set of content-based criteria, we attempt a comparative evaluation to measure the similarity between the rebuilt CSV and the original one. The results are promising and show that, under certain assumptions, RML2CSV reconstructs the same data with the same structure, offering more advanced digital preservation services. PMID:26312054

A generalized framework unifying image registration and respiratory motion models and incorporating image reconstruction, for partial image data or full images

NASA Astrophysics Data System (ADS)

McClelland, Jamie R.; Modat, Marc; Arridge, Simon; Grimes, Helen; D'Souza, Derek; Thomas, David; O' Connell, Dylan; Low, Daniel A.; Kaza, Evangelia; Collins, David J.; Leach, Martin O.; Hawkes, David J.

2017-06-01

Surrogate-driven respiratory motion models relate the motion of the internal anatomy to easily acquired respiratory surrogate signals, such as the motion of the skin surface. They are usually built by first using image registration to determine the motion from a number of dynamic images, and then fitting a correspondence model relating the motion to the surrogate signals. In this paper we present a generalized framework that unifies the image registration and correspondence model fitting into a single optimization. This allows the use of ‘partial’ imaging data, such as individual slices, projections, or k-space data, where it would not be possible to determine the motion from an individual frame of data. Motion compensated image reconstruction can also be incorporated using an iterative approach, so that both the motion and a motion-free image can be estimated from the partial image data. The framework has been applied to real 4DCT, Cine CT, multi-slice CT, and multi-slice MR data, as well as simulated datasets from a computer phantom. This includes the use of a super-resolution reconstruction method for the multi-slice MR data. Good results were obtained for all datasets, including quantitative results for the 4DCT and phantom datasets where the ground truth motion was known or could be estimated.

A generalized framework unifying image registration and respiratory motion models and incorporating image reconstruction, for partial image data or full images.

PubMed

McClelland, Jamie R; Modat, Marc; Arridge, Simon; Grimes, Helen; D'Souza, Derek; Thomas, David; Connell, Dylan O'; Low, Daniel A; Kaza, Evangelia; Collins, David J; Leach, Martin O; Hawkes, David J

2017-06-07

Surrogate-driven respiratory motion models relate the motion of the internal anatomy to easily acquired respiratory surrogate signals, such as the motion of the skin surface. They are usually built by first using image registration to determine the motion from a number of dynamic images, and then fitting a correspondence model relating the motion to the surrogate signals. In this paper we present a generalized framework that unifies the image registration and correspondence model fitting into a single optimization. This allows the use of 'partial' imaging data, such as individual slices, projections, or k-space data, where it would not be possible to determine the motion from an individual frame of data. Motion compensated image reconstruction can also be incorporated using an iterative approach, so that both the motion and a motion-free image can be estimated from the partial image data. The framework has been applied to real 4DCT, Cine CT, multi-slice CT, and multi-slice MR data, as well as simulated datasets from a computer phantom. This includes the use of a super-resolution reconstruction method for the multi-slice MR data. Good results were obtained for all datasets, including quantitative results for the 4DCT and phantom datasets where the ground truth motion was known or could be estimated.

A generalized framework unifying image registration and respiratory motion models and incorporating image reconstruction, for partial image data or full images

PubMed Central

McClelland, Jamie R; Modat, Marc; Arridge, Simon; Grimes, Helen; D’Souza, Derek; Thomas, David; Connell, Dylan O’; Low, Daniel A; Kaza, Evangelia; Collins, David J; Leach, Martin O; Hawkes, David J

2017-01-01

Abstract Surrogate-driven respiratory motion models relate the motion of the internal anatomy to easily acquired respiratory surrogate signals, such as the motion of the skin surface. They are usually built by first using image registration to determine the motion from a number of dynamic images, and then fitting a correspondence model relating the motion to the surrogate signals. In this paper we present a generalized framework that unifies the image registration and correspondence model fitting into a single optimization. This allows the use of ‘partial’ imaging data, such as individual slices, projections, or k-space data, where it would not be possible to determine the motion from an individual frame of data. Motion compensated image reconstruction can also be incorporated using an iterative approach, so that both the motion and a motion-free image can be estimated from the partial image data. The framework has been applied to real 4DCT, Cine CT, multi-slice CT, and multi-slice MR data, as well as simulated datasets from a computer phantom. This includes the use of a super-resolution reconstruction method for the multi-slice MR data. Good results were obtained for all datasets, including quantitative results for the 4DCT and phantom datasets where the ground truth motion was known or could be estimated. PMID:28195833

Progeny Clustering: A Method to Identify Biological Phenotypes

PubMed Central

Hu, Chenyue W.; Kornblau, Steven M.; Slater, John H.; Qutub, Amina A.

2015-01-01

Estimating the optimal number of clusters is a major challenge in applying cluster analysis to any type of dataset, especially to biomedical datasets, which are high-dimensional and complex. Here, we introduce an improved method, Progeny Clustering, which is stability-based and exceptionally efficient in computing, to find the ideal number of clusters. The algorithm employs a novel Progeny Sampling method to reconstruct cluster identity, a co-occurrence probability matrix to assess the clustering stability, and a set of reference datasets to overcome inherent biases in the algorithm and data space. Our method was shown successful and robust when applied to two synthetic datasets (datasets of two-dimensions and ten-dimensions containing eight dimensions of pure noise), two standard biological datasets (the Iris dataset and Rat CNS dataset) and two biological datasets (a cell phenotype dataset and an acute myeloid leukemia (AML) reverse phase protein array (RPPA) dataset). Progeny Clustering outperformed some popular clustering evaluation methods in the ten-dimensional synthetic dataset as well as in the cell phenotype dataset, and it was the only method that successfully discovered clinically meaningful patient groupings in the AML RPPA dataset. PMID:26267476

Web services in the U.S. geological survey streamstats web application

USGS Publications Warehouse

Guthrie, J.D.; Dartiguenave, C.; Ries, Kernell G.

2009-01-01

StreamStats is a U.S. Geological Survey Web-based GIS application developed as a tool for waterresources planning and management, engineering design, and other applications. StreamStats' primary functionality allows users to obtain drainage-basin boundaries, basin characteristics, and streamflow statistics for gaged and ungaged sites. Recently, Web services have been developed that provide the capability to remote users and applications to access comprehensive GIS tools that are available in StreamStats, including delineating drainage-basin boundaries, computing basin characteristics, estimating streamflow statistics for user-selected locations, and determining point features that coincide with a National Hydrography Dataset (NHD) reach address. For the state of Kentucky, a web service also has been developed that provides users the ability to estimate daily time series of drainage-basin average values of daily precipitation and temperature. The use of web services allows the user to take full advantage of the datasets and processes behind the Stream Stats application without having to develop and maintain them. ?? 2009 IEEE.

TXM-Wizard: a program for advanced data collection and evaluation in full-field transmission X-ray microscopy

PubMed Central

Liu, Yijin; Meirer, Florian; Williams, Phillip A.; Wang, Junyue; Andrews, Joy C.; Pianetta, Piero

2012-01-01

Transmission X-ray microscopy (TXM) has been well recognized as a powerful tool for non-destructive investigation of the three-dimensional inner structure of a sample with spatial resolution down to a few tens of nanometers, especially when combined with synchrotron radiation sources. Recent developments of this technique have presented a need for new tools for both system control and data analysis. Here a software package developed in MATLAB for script command generation and analysis of TXM data is presented. The first toolkit, the script generator, allows automating complex experimental tasks which involve up to several thousand motor movements. The second package was designed to accomplish computationally intense tasks such as data processing of mosaic and mosaic tomography datasets; dual-energy contrast imaging, where data are recorded above and below a specific X-ray absorption edge; and TXM X-ray absorption near-edge structure imaging datasets. Furthermore, analytical and iterative tomography reconstruction algorithms were implemented. The compiled software package is freely available. PMID:22338691

POCS-enhanced correction of motion artifacts in parallel MRI.

PubMed

Samsonov, Alexey A; Velikina, Julia; Jung, Youngkyoo; Kholmovski, Eugene G; Johnson, Chris R; Block, Walter F

2010-04-01

A new method for correction of MRI motion artifacts induced by corrupted k-space data, acquired by multiple receiver coils such as phased arrays, is presented. In our approach, a projections onto convex sets (POCS)-based method for reconstruction of sensitivity encoded MRI data (POCSENSE) is employed to identify corrupted k-space samples. After the erroneous data are discarded from the dataset, the artifact-free images are restored from the remaining data using coil sensitivity profiles. The error detection and data restoration are based on informational redundancy of phased-array data and may be applied to full and reduced datasets. An important advantage of the new POCS-based method is that, in addition to multicoil data redundancy, it can use a priori known properties about the imaged object for improved MR image artifact correction. The use of such information was shown to improve significantly k-space error detection and image artifact correction. The method was validated on data corrupted by simulated and real motion such as head motion and pulsatile flow.

Ancestral haplotype-based association mapping with generalized linear mixed models accounting for stratification.

PubMed

Zhang, Z; Guillaume, F; Sartelet, A; Charlier, C; Georges, M; Farnir, F; Druet, T

2012-10-01

In many situations, genome-wide association studies are performed in populations presenting stratification. Mixed models including a kinship matrix accounting for genetic relatedness among individuals have been shown to correct for population and/or family structure. Here we extend this methodology to generalized linear mixed models which properly model data under various distributions. In addition we perform association with ancestral haplotypes inferred using a hidden Markov model. The method was shown to properly account for stratification under various simulated scenari presenting population and/or family structure. Use of ancestral haplotypes resulted in higher power than SNPs on simulated datasets. Application to real data demonstrates the usefulness of the developed model. Full analysis of a dataset with 4600 individuals and 500 000 SNPs was performed in 2 h 36 min and required 2.28 Gb of RAM. The software GLASCOW can be freely downloaded from www.giga.ulg.ac.be/jcms/prod_381171/software. francois.guillaume@jouy.inra.fr Supplementary data are available at Bioinformatics online.

IM-TORNADO: A Tool for Comparison of 16S Reads from Paired-End Libraries

PubMed Central

Jeraldo, Patricio; Kalari, Krishna; Chen, Xianfeng; Bhavsar, Jaysheel; Mangalam, Ashutosh; White, Bryan; Nelson, Heidi; Kocher, Jean-Pierre; Chia, Nicholas

2014-01-01

Motivation 16S rDNA hypervariable tag sequencing has become the de facto method for accessing microbial diversity. Illumina paired-end sequencing, which produces two separate reads for each DNA fragment, has become the platform of choice for this application. However, when the two reads do not overlap, existing computational pipelines analyze data from read separately and underutilize the information contained in the paired-end reads. Results We created a workflow known as Illinois Mayo Taxon Organization from RNA Dataset Operations (IM-TORNADO) for processing non-overlapping reads while retaining maximal information content. Using synthetic mock datasets, we show that the use of both reads produced answers with greater correlation to those from full length 16S rDNA when looking at taxonomy, phylogeny, and beta-diversity. Availability and Implementation IM-TORNADO is freely available at http://sourceforge.net/projects/imtornado and produces BIOM format output for cross compatibility with other pipelines such as QIIME, mothur, and phyloseq. PMID:25506826

Gender classification of running subjects using full-body kinematics

NASA Astrophysics Data System (ADS)

Williams, Christina M.; Flora, Jeffrey B.; Iftekharuddin, Khan M.

2016-05-01

This paper proposes novel automated gender classification of subjects while engaged in running activity. The machine learning techniques include preprocessing steps using principal component analysis followed by classification with linear discriminant analysis, and nonlinear support vector machines, and decision-stump with AdaBoost. The dataset consists of 49 subjects (25 males, 24 females, 2 trials each) all equipped with approximately 80 retroreflective markers. The trials are reflective of the subject's entire body moving unrestrained through a capture volume at a self-selected running speed, thus producing highly realistic data. The classification accuracy using leave-one-out cross validation for the 49 subjects is improved from 66.33% using linear discriminant analysis to 86.74% using the nonlinear support vector machine. Results are further improved to 87.76% by means of implementing a nonlinear decision stump with AdaBoost classifier. The experimental findings suggest that the linear classification approaches are inadequate in classifying gender for a large dataset with subjects running in a moderately uninhibited environment.

Revisiting Hansen Solubility Parameters by Including Thermodynamics.

PubMed

Louwerse, Manuel J; Maldonado, Ana; Rousseau, Simon; Moreau-Masselon, Chloe; Roux, Bernard; Rothenberg, Gadi

2017-11-03

The Hansen solubility parameter approach is revisited by implementing the thermodynamics of dissolution and mixing. Hansen's pragmatic approach has earned its spurs in predicting solvents for polymer solutions, but for molecular solutes improvements are needed. By going into the details of entropy and enthalpy, several corrections are suggested that make the methodology thermodynamically sound without losing its ease of use. The most important corrections include accounting for the solvent molecules' size, the destruction of the solid's crystal structure, and the specificity of hydrogen-bonding interactions, as well as opportunities to predict the solubility at extrapolated temperatures. Testing the original and the improved methods on a large industrial dataset including solvent blends, fit qualities improved from 0.89 to 0.97 and the percentage of correct predictions rose from 54 % to 78 %. Full Matlab scripts are included in the Supporting Information, allowing readers to implement these improvements on their own datasets. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Recent development in preparation of European soil hydraulic maps

NASA Astrophysics Data System (ADS)

Toth, B.; Weynants, M.; Pasztor, L.; Hengl, T.

2017-12-01

Reliable quantitative information on soil hydraulic properties is crucial for modelling hydrological, meteorological, ecological and biological processes of the Critical Zone. Most of the Earth system models need information on soil moisture retention capacity and hydraulic conductivity in the full matric potential range. These soil hydraulic properties can be quantified, but their measurement is expensive and time consuming, therefore measurement-based catchment scale mapping of these soil properties is not possible. The increasing availability of soil information and methods describing relationships between simple soil characteristics and soil hydraulic properties provide the possibility to derive soil hydraulic maps based on spatial soil datasets and pedotransfer functions (PTFs). Over the last decade there has been a significant development in preparation of soil hydraulic maps. Spatial datasets on model parameters describing the soil hydraulic processes have become available for countries, continents and even for the whole globe. Our aim is to present European soil hydraulic maps, show their performance, highlight their advantages and drawbacks, and propose possible ways to further improve the performance of those.

Predictive process simulation of cryogenic implants for leading edge transistor design

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gossmann, Hans-Joachim; Zographos, Nikolas; Park, Hugh

2012-11-06

Two cryogenic implant TCAD-modules have been developed: (i) A continuum-based compact model targeted towards a TCAD production environment calibrated against an extensive data-set for all common dopants. Ion-specific calibration parameters related to damage generation and dynamic annealing were used and resulted in excellent fits to the calibration data-set. (ii) A Kinetic Monte Carlo (kMC) model including the full time dependence of ion-exposure that a particular spot on the wafer experiences, as well as the resulting temperature vs. time profile of this spot. It was calibrated by adjusting damage generation and dynamic annealing parameters. The kMC simulations clearly demonstrate the importancemore » of the time-structure of the beam for the amorphization process: Assuming an average dose-rate does not capture all of the physics and may lead to incorrect conclusions. The model enables optimization of the amorphization process through tool parameters such as scan speed or beam height.« less

Measurements of branching fractions and CP-violating asymmetries in B meson decays to charmless two-body states containing a K(0).

PubMed

Aubert, B; Barate, R; Boutigny, D; Couderc, F; Gaillard, J-M; Hicheur, A; Karyotakis, Y; Lees, J P; Robbe, P; Tisserand, V; Zghiche, A; Palano, A; Pompili, A; Chen, J C; Qi, N D; Rong, G; Wang, P; Zhu, Y S; Eigen, G; Ofte, I; Stugu, B; Abrams, G S; Borgland, A W; Breon, A B; Brown, D N; Button-Shafer, J; Cahn, R N; Charles, E; Day, C T; Gill, M S; Gritsan, A V; Groysman, Y; Jacobsen, R G; Kadel, R W; Kadyk, J; Kerth, L T; Kolomensky, Yu G; Kukartsev, G; LeClerc, C; Levi, M E; Lynch, G; Mir, L M; Oddone, P J; Orimoto, T J; Pripstein, M; Roe, N A; Romosan, A; Ronan, M T; Shelkov, V G; Telnov, A V; Wenzel, W A; Ford, K; Harrison, T J; Hawkes, C M; Knowles, D J; Morgan, S E; Penny, R C; Watson, A T; Watson, N K; Goetzen, K; Held, T; Koch, H; Lewandowski, B; Pelizaeus, M; Peters, K; Schmuecker, H; Steinke, M; Boyd, J T; Chevalier, N; Cottingham, W N; Kelly, M P; Latham, T E; Mackay, C; Wilson, F F; Abe, K; Cuhadar-Donszelmann, T; Hearty, C; Mattison, T S; McKenna, J A; Thiessen, D; Kyberd, P; McKemey, A K; Teodorescu, L; Blinov, V E; Bukin, A D; Golubev, V B; Ivanchenko, V N; Kravchenko, E A; Onuchin, A P; Serednyakov, S I; Skovpen, Yu I; Solodov, E P; Yushkov, A N; Best, D; Bruinsma, M; Chao, M; Eschrich, I; Kirkby, D; Lankford, A J; Mandelkern, M; Mommsen, R K; Roethel, W; Stoker, D P; Buchanan, C; Hartfiel, B L; Gary, J W; Layter, J; Shen, B C; Wang, K; del Re, D; Hadavand, H K; Hill, E J; MacFarlane, D B; Paar, H P; Rahatlou, Sh; Sharma, V; Berryhill, J W; Campagnari, C; Dahmes, B; Levy, S L; Long, O; Lu, A; Mazur, M A; Richman, J D; Verkerke, W; Beck, T W; Beringer, J; Eisner, A M; Heusch, C A; Lockman, W S; Schalk, T; Schmitz, R E; Schumm, B A; Seiden, A; Spradlin, P; Turri, M; Walkowiak, W; Williams, D C; Wilson, M G; Albert, J; Chen, E; Dubois-Felsmann, G P; Dvoretskii, A; Erwin, R J; Hitlin, D G; Narsky, I; Piatenko, T; Porter, F C; Ryd, A; Samuel, A; Yang, S; Jayatilleke, S; Mancinelli, G; Meadows, B T; Sokoloff, M D; Abe, T; Blanc, F; Bloom, P; Chen, S; Clark, P J; Ford, W T; Nauenberg, U; Olivas, A; Rankin, P; Roy, J; Smith, J G; van Hoek, W C; Zhang, L; Harton, J L; Hu, T; Soffer, A; Toki, W H; Wilson, R J; Zhang, J; Aleksan, R; Emery, S; Gaidot, A; Ganzhur, S F; Giraud, P-F; Hamelde Monchenault, G; Kozanecki, W; Langer, M; Legendre, M; London, G W; Mayer, B; Schott, G; Vasseur, G; Yeche, Ch; Zito, M; Altenburg, D; Brandt, T; Brose, J; Colberg, T; Dickopp, M; Hauke, A; Lacker, H M; Maly, E; Müller-Pfefferkorn, R; Nogowski, R; Otto, S; Schubert, J; Schubert, K R; Schwierz, R; Spaan, B; Wilden, L; Bernard, D; Bonneaud, G R; Brochard, F; Cohen-Tanugi, J; Grenier, P; Thiebaux, Ch; Vasileiadis, G; Verderi, M; Khan, A; Lavin, D; Muheim, F; Playfer, S; Swain, J E; Andreotti, M; Azzolini, V; Bettoni, D; Bozzi, C; Calabrese, R; Cibinetto, G; Luppi, E; Negrini, M; Piemontese, L; Sarti, A; Treadwell, E; Anulli, F; Baldini-Ferroli, R; Calcaterra, A; De Sangro, R; Falciai, D; Finocchiaro, G; Patteri, P; Peruzzi, I M; Piccolo, M; Zallo, A; Buzzo, A; Capra, R; Contri, R; Crosetti, G; Lo Vetere, M; Macri, M; Monge, M R; Passaggio, S; Patrignani, C; Robutti, E; Santroni, A; Tosi, S; Bailey, S; Morii, M; Won, E; Dubitzky, R S; Bhimji, W; Bowerman, D A; Dauncey, P D; Egede, U; Gaillard, J R; Morton, G W; Nash, J A; Taylor, G P; Grenier, G J; Lee, S-J; Mallik, U; Cochran, J; Crawley, H B; Lamsa, J; Meyer, W T; Prell, S; Rosenberg, E I; Yi, J; Biasini, M; Pioppi, M; Davier, M; Grosdidier, G; Höcker, A; Laplace, S; Diberder, F Le; Lepeltier, V; Lutz, A M; Petersen, T C; Plaszczynski, S; Schune, M H; Tantot, L; Wormser, G; Brigljević, V; Cheng, C H; Lange, D J; Simani, M C; Wright, D M; Bevan, A J; Coleman, J P; Fry, J R; Gabathuler, E; Gamet, R; Kay, M; Parry, R J; Payne, D J; Sloane, R J; Touramanis, C; Back, J J; Cormack, C M; Harrison, P F; Shorthouse, H W; Vidal, P B; Brown, C L; Cowan, G; Flack, R L; Flaecher, H U; George, S; Green, M G; Kurup, A; Marker, C E; McMahon, T R; Ricciardi, S; Salvatore, F; Vaitsas, G; Winter, M A; Brown, D; Davis, C L; Allison, J; Barlow, N R; Barlow, R J; Hart, P A; Hodgkinson, M C; Jackson, F; Lafferty, G D; Lyon, A J; Weatherall, J H; Williams, J C; Farbin, A; Hulsbergen, W D; Jawahery, A; Kovalskyi, D; Lae, C K; Lillard, V; Roberts, D A; Blaylock, G; Dallapiccola, C; Flood, K T; Hertzbach, S S; Kofler, R; Koptchev, V B; Moore, T B; Saremi, S; Staengle, H; Willocq, S; Cowan, R; Sciolla, G; Taylor, F; Yamamoto, R K; Mangeol, D J J; Patel, P M; Robertson, S H; Lazzaro, A; Palombo, F; Bauer, J M; Cremaldi, L; Eschenburg, V; Godang, R; Kroeger, R; Reidy, J; Sanders, D A; Summers, D J; Zhao, H W; Brunet, S; Cote-Ahern, D; Taras, P; Nicholson, H; Raven, G; Cartaro, C; Cavallo, N; De Nardo, G; Fabozzi, F; Gatto, C; Lista, L; Paolucci, P; Piccolo, D; Sciacca, C; Jessop, C P; LoSecco, J M; Gabriel, T A; Brau, B; Gan, K K; Honscheid, K; Hufnagel, D; Kagan, H; Kass, R; Pulliam, T; Ter-Antonyan, R; Wong, Q K; Brau, J; Frey, R; Igonkina, O; Potter, C T; Sinev, N B; Strom, D; Torrence, E; Colecchia, F; Dorigo, A; Galeazzi, F; Margoni, M; Morandin, M; Posocco, M; Rotondo, M; Simonetto, F; Stroili, R; Tiozzo, G; Voci, C; Benayoun, M; Briand, H; Chauveau, J; David, P; De la Vaissière, Ch; Del Buono, L; Hamon, O; John, M J J; Leruste, Ph; Ocariz, J; Pivk, M; Roos, L; Stark, J; T'Jampens, S; Therin, G; Manfredi, P F; Re, V; Behera, P K; Gladney, L; Guo, Q H; Panetta, J; Angelini, C; Batignani, G; Bettarini, S; Bondioli, M; Bucci, F; Calderini, G; Carpinelli, M; Del Gamba, V; Forti, F; Giorgi, M A; Lusiani, A; Marchiori, G; Martinez-Vidal, F; Morganti, M; Neri, N; Paoloni, E; Rama, M; Rizzo, G; Sandrelli, F; Walsh, J; Haire, M; Judd, D; Paick, K; Wagoner, D E; Cavoto, G; Danielson, N; Elmer, P; Lu, C; Miftakov, V; Olsen, J; Smith, A J S; Bellini, F; Faccini, R; Ferrarotto, F; Ferroni, F; Gaspero, M; Mazzoni, M A; Morganti, S; Pierini, M; Piredda, G; Safai Tehrani, F; Voena, C; Christ, S; Wagner, G; Waldi, R; Adye, T; De Groot, N; Franek, B; Geddes, N I; Gopal, G P; Olaiya, E O; Xella, S M; Purohit, M V; Weidemann, A W; Yumiceva, F X; Aston, D; Bartoldus, R; Berger, N; Boyarski, A M; Buchmueller, O L; Convery, M R; Cristinziani, M; Dong, D; Dorfan, J; Dujmic, D; Dunwoodie, W; Elsen, E E; Field, R C; Glanzman, T; Gowdy, S J; Hadig, T; Halyo, V; Hryn'ova, T; Innes, W R; Kelsey, M H; Kim, P; Kocian, M L; Langenegger, U; Leith, D W G S; Libby, J; Luitz, S; Luth, V; Lynch, H L; Marsiske, H; Messner, R; Muller, D R; O'Grady, C P; Ozcan, V E; Perazzo, A; Perl, M; Petrak, S; Ratcliff, B N; Roodman, A; Salnikov, A A; Schindler, R H; Schwiening, J; Simi, G; Snyder, A; Soha, A; Stelzer, J; Su, D; Sullivan, M K; Va'vra, J; Wagner, S R; Weaver, M; Weinstein, A J R; Wisniewski, W J; Wright, D H; Young, C C; Burchat, P R; Edwards, A J; Meyer, T I; Petersen, B A; Roat, C; Ahmed, M; Ahmed, S; Alam, M S; Ernst, J A; Saeed, M A; Saleem, M; Wappler, F R; Bugg, W; Krishnamurthy, M; Spanier, S M; Eckmann, R; Kim, H; Ritchie, J L; Satpathy, A; Schwitters, R F; Izen, J M; Kitayama, I; Lou, X C; Ye, S; Bianchi, F; Bona, M; Gallo, F; Gamba, D; Borean, C; Bosisio, L; Della Ricca, G; Dittongo, S; Grancagnolo, S; Lanceri, L; Poropat, P; Vitale, L; Vuagnin, G; Panvini, R S; Banerjee, Sw; Brown, C M; Fortin, D; Jackson, P D; Kowalewski, R; Roney, J M; Band, H R; Dasu, S; Datta, M; Eichenbaum, A M; Johnson, J R; Kutter, P E; Li, H; Liu, R; Lodovico, F Di; Mihalyi, A; Mohapatra, A K; Pan, Y; Prepost, R; Sekula, S J; von Wimmersperg-Toeller, J H; Wu, J; Wu, S L; Yu, Z; Neal, H

2004-05-21

We present measurements of branching fractions and CP-violating asymmetries in decays of B mesons to two-body final states containing a K0. The results are based on a data sample of approximately 88 x 10(6) Upsilon(4S)-->BB decays collected with the BABAR detector at the PEP-II asymmetric-energy B Factory at SLAC. We measure B(B+-->K(0)pi(+))=(22.3+/-1.7+/-1.1)x10(-6), B(B0-->K(0)pi(0)=(11.4+/-1.7+/-0.8)x10(-6), B(B+-->K(0)K+)<2.5 x 10(-6), and B(B0-->K(0)K(0)<1.8 x 10(-6), where the first uncertainty is statistical and the second is systematic, and the upper limits are at the 90% confidence level. In addition, the following CP-violating asymmetries have been measured: A(CP)(B+-->K(0)pi(+))=-0.05+/-0.08+/-0.01 and A(CP)(B0-->K(0)pi(0)=0.03+/-0.36+/-0.11.

Search for Long-Lived Particles in e+e- Collisions

NASA Astrophysics Data System (ADS)

Lees, J. P.; Poireau, V.; Tisserand, V.; Grauges, E.; Palano, A.; Eigen, G.; Stugu, B.; Brown, D. N.; Kerth, L. T.; Kolomensky, Yu. G.; Lee, M. J.; Lynch, G.; Koch, H.; Schroeder, T.; Hearty, C.; Mattison, T. S.; McKenna, J. A.; So, R. Y.; Khan, A.; Blinov, V. E.; Buzykaev, A. R.; Druzhinin, V. P.; Golubev, V. B.; Kravchenko, E. A.; Onuchin, A. P.; Serednyakov, S. I.; Skovpen, Yu. I.; Solodov, E. P.; Todyshev, K. Yu.; Lankford, A. J.; Dey, B.; Gary, J. W.; Long, O.; Campagnari, C.; Franco Sevilla, M.; Hong, T. M.; Kovalskyi, D.; Richman, J. D.; West, C. A.; Eisner, A. M.; Lockman, W. S.; Panduro Vazquez, W.; Schumm, B. A.; Seiden, A.; Chao, D. S.; Cheng, C. H.; Echenard, B.; Flood, K. T.; Hitlin, D. G.; Miyashita, T. S.; Ongmongkolkul, P.; Porter, F. C.; Röhrken, M.; Andreassen, R.; Huard, Z.; Meadows, B. T.; Pushpawela, B. G.; Sokoloff, M. D.; Sun, L.; Bloom, P. C.; Ford, W. T.; Gaz, A.; Smith, J. G.; Wagner, S. R.; Ayad, R.; Toki, W. H.; Spaan, B.; Bernard, D.; Verderi, M.; Playfer, S.; Bettoni, D.; Bozzi, C.; Calabrese, R.; Cibinetto, G.; Fioravanti, E.; Garzia, I.; Luppi, E.; Piemontese, L.; Santoro, V.; Calcaterra, A.; de Sangro, R.; Finocchiaro, G.; Martellotti, S.; Patteri, P.; Peruzzi, I. M.; Piccolo, M.; Rama, M.; Zallo, A.; Contri, R.; Lo Vetere, M.; Monge, M. R.; Passaggio, S.; Patrignani, C.; Robutti, E.; Bhuyan, B.; Prasad, V.; Adametz, A.; Uwer, U.; Lacker, H. M.; Mallik, U.; Chen, C.; Cochran, J.; Prell, S.; Ahmed, H.; Gritsan, A. V.; Arnaud, N.; Davier, M.; Derkach, D.; Grosdidier, G.; Le Diberder, F.; Lutz, A. M.; Malaescu, B.; Roudeau, P.; Stocchi, A.; Wormser, G.; Lange, D. J.; Wright, D. M.; Coleman, J. P.; Fry, J. R.; Gabathuler, E.; Hutchcroft, D. E.; Payne, D. J.; Touramanis, C.; Bevan, A. J.; di Lodovico, F.; Sacco, R.; Cowan, G.; Brown, D. N.; Davis, C. L.; Denig, A. G.; Fritsch, M.; Gradl, W.; Griessinger, K.; Hafner, A.; Schubert, K. R.; Barlow, R. J.; Lafferty, G. D.; Cenci, R.; Hamilton, B.; Jawahery, A.; Roberts, D. A.; Cowan, R.; Sciolla, G.; Cheaib, R.; Patel, P. M.; Robertson, S. H.; Neri, N.; Palombo, F.; Cremaldi, L.; Godang, R.; Sonnek, P.; Summers, D. J.; Simard, M.; Taras, P.; de Nardo, G.; Onorato, G.; Sciacca, C.; Martinelli, M.; Raven, G.; Jessop, C. P.; Losecco, J. M.; Honscheid, K.; Kass, R.; Feltresi, E.; Margoni, M.; Morandin, M.; Posocco, M.; Rotondo, M.; Simi, G.; Simonetto, F.; Stroili, R.; Akar, S.; Ben-Haim, E.; Bomben, M.; Bonneaud, G. R.; Briand, H.; Calderini, G.; Chauveau, J.; Leruste, Ph.; Marchiori, G.; Ocariz, J.; Biasini, M.; Manoni, E.; Pacetti, S.; Rossi, A.; Angelini, C.; Batignani, G.; Bettarini, S.; Carpinelli, M.; Casarosa, G.; Cervelli, A.; Chrzaszcz, M.; Forti, F.; Giorgi, M. A.; Lusiani, A.; Oberhof, B.; Paoloni, E.; Perez, A.; Rizzo, G.; Walsh, J. J.; Lopes Pegna, D.; Olsen, J.; Smith, A. J. S.; Anulli, F.; Faccini, R.; Ferrarotto, F.; Ferroni, F.; Gaspero, M.; Li Gioi, L.; Pilloni, A.; Piredda, G.; Bünger, C.; Dittrich, S.; Grünberg, O.; Hess, M.; Leddig, T.; Voß, C.; Waldi, R.; Adye, T.; Olaiya, E. O.; Wilson, F. F.; Emery, S.; Vasseur, G.; Aston, D.; Bard, D. J.; Cartaro, C.; Convery, M. R.; Dorfan, J.; Dubois-Felsmann, G. P.; Dunwoodie, W.; Ebert, M.; Field, R. C.; Fulsom, B. G.; Graham, M. T.; Hast, C.; Innes, W. R.; Kim, P.; Leith, D. W. G. S.; Lindemann, D.; Luitz, S.; Luth, V.; Lynch, H. L.; Macfarlane, D. B.; Muller, D. R.; Neal, H.; Perl, M.; Pulliam, T.; Ratcliff, B. N.; Roodman, A.; Salnikov, A. A.; Schindler, R. H.; Snyder, A.; Su, D.; Sullivan, M. K.; Va'Vra, J.; Wisniewski, W. J.; Wulsin, H. W.; Purohit, M. V.; White, R. M.; Wilson, J. R.; Randle-Conde, A.; Sekula, S. J.; Bellis, M.; Burchat, P. R.; Puccio, E. M. T.; Alam, M. S.; Ernst, J. A.; Gorodeisky, R.; Guttman, N.; Peimer, D. R.; Soffer, A.; Spanier, S. M.; Ritchie, J. L.; Schwitters, R. F.; Wray, B. C.; Izen, J. M.; Lou, X. C.; Bianchi, F.; de Mori, F.; Filippi, A.; Gamba, D.; Lanceri, L.; Vitale, L.; Martinez-Vidal, F.; Oyanguren, A.; Villanueva-Perez, P.; Albert, J.; Banerjee, Sw.; Beaulieu, A.; Bernlochner, F. U.; Choi, H. H. F.; King, G. J.; Kowalewski, R.; Lewczuk, M. J.; Lueck, T.; Nugent, I. M.; Roney, J. M.; Sobie, R. J.; Tasneem, N.; Gershon, T. J.; Harrison, P. F.; Latham, T. E.; Band, H. R.; Dasu, S.; Pan, Y.; Prepost, R.; Wu, S. L.; Babar Collaboration

2015-05-01

We present a search for a neutral, long-lived particle L that is produced in e+e- collisions and decays at a significant distance from the e+e- interaction point into various flavor combinations of two oppositely charged tracks. The analysis uses an e+e- data sample with a luminosity of 489.1 fb-1 collected by the BABAR detector at the ϒ (4 S ) , ϒ (3 S ) , and ϒ (2 S ) resonances and just below the ϒ (4 S ) . Fitting the two-track mass distribution in search of a signal peak, we do not observe a significant signal, and set 90% confidence level upper limits on the product of the L production cross section, branching fraction, and reconstruction efficiency for six possible two-body L decay modes as a function of the L mass. The efficiency is given for each final state as a function of the mass, lifetime, and transverse momentum of the candidate, allowing application of the upper limits to any production model. In addition, upper limits are provided on the branching fraction B (B →XsL ) , where Xs is a strange hadronic system.

Virtuality Distributions and γγ * -> π 0 Transition at Handbag Level

DOE Office of Scientific and Technical Information (OSTI.GOV)

Radyushkin, Anatoly V.

2015-09-01

We outline a new approach to transverse momentum dependence in hard processes using as an example the exclusive transitionmore » $${\\gamma^{*}\\gamma \\to \\pi^{0}}$$ at the handbag level. We start with the coordinate representation for a matrix element $${\\langle p |{\\cal O}(0,z) |0 \\rangle}$$ of a bilocal operator $${{\\cal O} (0,z)}$$ describing a hadron with momentum p. Treated as a function of (pz) and z$$^{2}$$, it is parametrized through virtuality distribution amplitude (VDA) Φ (x, σ), with x being Fourier-conjugate to (pz) and σ Laplace-conjugate to z$$^{2}$$. For intervals with z$$^{+}$$ = 0, we introduce the transverse momentum distribution amplitude (TMDA) $${\\Ψ (x,k_{\\perp})}$$ , and write it in terms of VDA Φ (x, σ). The results of covariant calculations, written in terms of Φ (x, σ) are converted into expressions involving $${\\Ψ (x,k_{\\perp})}$$ . We propose simple models for soft VDAs/TMDAs, and use them for comparison of handbag results with experimental (BaBar and BELLE) data on the pion transition form factor.« less

Search for Long-Lived Particles in e+ e- Collisions.

PubMed

Lees, J P; Poireau, V; Tisserand, V; Grauges, E; Palano, A; Eigen, G; Stugu, B; Brown, D N; Kerth, L T; Kolomensky, Yu G; Lee, M J; Lynch, G; Koch, H; Schroeder, T; Hearty, C; Mattison, T S; McKenna, J A; So, R Y; Khan, A; Blinov, V E; Buzykaev, A R; Druzhinin, V P; Golubev, V B; Kravchenko, E A; Onuchin, A P; Serednyakov, S I; Skovpen, Yu I; Solodov, E P; Todyshev, K Yu; Lankford, A J; Dey, B; Gary, J W; Long, O; Campagnari, C; Franco Sevilla, M; Hong, T M; Kovalskyi, D; Richman, J D; West, C A; Eisner, A M; Lockman, W S; Panduro Vazquez, W; Schumm, B A; Seiden, A; Chao, D S; Cheng, C H; Echenard, B; Flood, K T; Hitlin, D G; Miyashita, T S; Ongmongkolkul, P; Porter, F C; Röhrken, M; Andreassen, R; Huard, Z; Meadows, B T; Pushpawela, B G; Sokoloff, M D; Sun, L; Bloom, P C; Ford, W T; Gaz, A; Smith, J G; Wagner, S R; Ayad, R; Toki, W H; Spaan, B; Bernard, D; Verderi, M; Playfer, S; Bettoni, D; Bozzi, C; Calabrese, R; Cibinetto, G; Fioravanti, E; Garzia, I; Luppi, E; Piemontese, L; Santoro, V; Calcaterra, A; de Sangro, R; Finocchiaro, G; Martellotti, S; Patteri, P; Peruzzi, I M; Piccolo, M; Rama, M; Zallo, A; Contri, R; Lo Vetere, M; Monge, M R; Passaggio, S; Patrignani, C; Robutti, E; Bhuyan, B; Prasad, V; Adametz, A; Uwer, U; Lacker, H M; Mallik, U; Chen, C; Cochran, J; Prell, S; Ahmed, H; Gritsan, A V; Arnaud, N; Davier, M; Derkach, D; Grosdidier, G; Le Diberder, F; Lutz, A M; Malaescu, B; Roudeau, P; Stocchi, A; Wormser, G; Lange, D J; Wright, D M; Coleman, J P; Fry, J R; Gabathuler, E; Hutchcroft, D E; Payne, D J; Touramanis, C; Bevan, A J; Di Lodovico, F; Sacco, R; Cowan, G; Brown, D N; Davis, C L; Denig, A G; Fritsch, M; Gradl, W; Griessinger, K; Hafner, A; Schubert, K R; Barlow, R J; Lafferty, G D; Cenci, R; Hamilton, B; Jawahery, A; Roberts, D A; Cowan, R; Sciolla, G; Cheaib, R; Patel, P M; Robertson, S H; Neri, N; Palombo, F; Cremaldi, L; Godang, R; Sonnek, P; Summers, D J; Simard, M; Taras, P; De Nardo, G; Onorato, G; Sciacca, C; Martinelli, M; Raven, G; Jessop, C P; LoSecco, J M; Honscheid, K; Kass, R; Feltresi, E; Margoni, M; Morandin, M; Posocco, M; Rotondo, M; Simi, G; Simonetto, F; Stroili, R; Akar, S; Ben-Haim, E; Bomben, M; Bonneaud, G R; Briand, H; Calderini, G; Chauveau, J; Leruste, Ph; Marchiori, G; Ocariz, J; Biasini, M; Manoni, E; Pacetti, S; Rossi, A; Angelini, C; Batignani, G; Bettarini, S; Carpinelli, M; Casarosa, G; Cervelli, A; Chrzaszcz, M; Forti, F; Giorgi, M A; Lusiani, A; Oberhof, B; Paoloni, E; Perez, A; Rizzo, G; Walsh, J J; Lopes Pegna, D; Olsen, J; Smith, A J S; Anulli, F; Faccini, R; Ferrarotto, F; Ferroni, F; Gaspero, M; Li Gioi, L; Pilloni, A; Piredda, G; Bünger, C; Dittrich, S; Grünberg, O; Hess, M; Leddig, T; Voß, C; Waldi, R; Adye, T; Olaiya, E O; Wilson, F F; Emery, S; Vasseur, G; Aston, D; Bard, D J; Cartaro, C; Convery, M R; Dorfan, J; Dubois-Felsmann, G P; Dunwoodie, W; Ebert, M; Field, R C; Fulsom, B G; Graham, M T; Hast, C; Innes, W R; Kim, P; Leith, D W G S; Lindemann, D; Luitz, S; Luth, V; Lynch, H L; MacFarlane, D B; Muller, D R; Neal, H; Perl, M; Pulliam, T; Ratcliff, B N; Roodman, A; Salnikov, A A; Schindler, R H; Snyder, A; Su, D; Sullivan, M K; Va'vra, J; Wisniewski, W J; Wulsin, H W; Purohit, M V; White, R M; Wilson, J R; Randle-Conde, A; Sekula, S J; Bellis, M; Burchat, P R; Puccio, E M T; Alam, M S; Ernst, J A; Gorodeisky, R; Guttman, N; Peimer, D R; Soffer, A; Spanier, S M; Ritchie, J L; Schwitters, R F; Wray, B C; Izen, J M; Lou, X C; Bianchi, F; De Mori, F; Filippi, A; Gamba, D; Lanceri, L; Vitale, L; Martinez-Vidal, F; Oyanguren, A; Villanueva-Perez, P; Albert, J; Banerjee, Sw; Beaulieu, A; Bernlochner, F U; Choi, H H F; King, G J; Kowalewski, R; Lewczuk, M J; Lueck, T; Nugent, I M; Roney, J M; Sobie, R J; Tasneem, N; Gershon, T J; Harrison, P F; Latham, T E; Band, H R; Dasu, S; Pan, Y; Prepost, R; Wu, S L

2015-05-01

We present a search for a neutral, long-lived particle L that is produced in e+ e- collisions and decays at a significant distance from the e+ e- interaction point into various flavor combinations of two oppositely charged tracks. The analysis uses an e+ e- data sample with a luminosity of 489.1  fb(-1) collected by the BABAR detector at the ϒ(4S), ϒ(3S), and ϒ(2S) resonances and just below the ϒ(4S). Fitting the two-track mass distribution in search of a signal peak, we do not observe a significant signal, and set 90% confidence level upper limits on the product of the L production cross section, branching fraction, and reconstruction efficiency for six possible two-body L decay modes as a function of the L mass. The efficiency is given for each final state as a function of the mass, lifetime, and transverse momentum of the candidate, allowing application of the upper limits to any production model. In addition, upper limits are provided on the branching fraction B(B→XsL), where Xs is a strange hadronic system.

Evidence for Direct CP Violation in the Measurement of the Cabbibo-Kobayashi-Maskawa Angle {gamma} with B{sup {+-}}{yields}D(*)K{sup (*){+-}} Decays

DOE Office of Scientific and Technical Information (OSTI.GOV)

Amo Sanchez, P. del; Lees, J. P.; Poireau, V.

2010-09-17

We report the measurement of the Cabibbo-Kobayashi-Maskawa CP-violating angle {gamma} through a Dalitz plot analysis of neutral D-meson decays to K{sub S}{sup 0}{pi}{sup +}{pi}{sup -} and K{sub S}{sup 0}K{sup +}K{sup -} produced in the processes B{sup {+-}}{yields}DK{sup {+-}}, B{sup {+-}}{yields}D*K{sup {+-}} with D*{yields}D{pi}{sup 0}, D{gamma}, and B{sup {+-}}{yields}DK*{sup {+-}} with K*{sup {+-}}{yields}K{sub S}{sup 0}{pi}{+-}, using 468 million BB pairs collected by the BABAR detector at the PEP-II asymmetric-energy e{sup +}e{sup -} collider at SLAC. We measure {gamma}=(68{+-}14{+-}4{+-}3) deg. (modulo 180 deg.), where the first error is statistical, the second is the experimental systematic uncertainty, and the third reflects the uncertaintymore » in the description of the neutral D decay amplitudes. This result is inconsistent with {gamma}=0 (no direct CP violation) with a significance of 3.5 standard deviations.« less

Evidence for Direct CP Violation in the Measurement of the Cabibbo-Kobayashi-Maskawa Angle gamma with B-+ to D(*) K(*)-+ Decays

DOE Office of Scientific and Technical Information (OSTI.GOV)

del Amo Sanchez, P.; Lees, J.P.; Poireau, V.

2011-08-19

We report the measurement of the Cabibbo-Kobayashi-Maskawa CP-violating angle {gamma} through a Dalitz plot analysis of neutral D meson decays to K{sub S}{sup 0}{pi}{sup +}{pi}{sup -} and K{sub S}{sup 0} K{sup +}K{sup -} produced in the processes B{sup {-+}} {yields} DK{sup {-+}}, B{sup {-+}} {yields} D* K{sup {-+}} with D* {yields} D{pi}{sup 0}, D{gamma}, and B{sup {-+}} {yields} DK*{sup {-+}} with K*{sup {-+}} {yields} K{sub S}{sup 0}{pi}{sup {-+}}, using 468 million B{bar B} pairs collected by the BABAR detector at the PEP-II asymmetric-energy e{sup +}e{sup -} collider at SLAC. We measure {gamma} = (68 {+-} 14 {+-} 4 {+-} 3){supmore » o} (modulo 180{sup o}), where the first error is statistical, the second is the experimental systematic uncertainty and the third reflects the uncertainty in the description of the neutral D decay amplitudes. This result is inconsistent with {gamma} = 0 (no direct CP violation) with a significance of 3.5 standard deviations.« less

Double Collins effect in e+e-→Λ Λ ¯ X and e+e-→Λ π X processes in a diquark spectator model

NASA Astrophysics Data System (ADS)

Wang, Xiaoyu; Yang, Yongliang; Lu, Zhun

2018-06-01

We study the Collins function H1⊥ of the Λ hyperon, which describes the fragmentation of a transversely polarized quark into an unpolarized Λ hyperon. We calculate H1⊥ for light quarks of the Λ hyperon, in the diquark spectator model with a Gaussian form factor for the hyperon-quark-diquark vertex. The model calculation includes contributions from both the scalar diquark and vector diquark spectators. Using the model result, we estimate the azimuthal asymmetry A12, which appears in the ratio of unlike-sign events to like-sign events contributed by double Collins effects, in the processes e+e-→Λ Λ ¯X and e+e-→Λ π X . The QCD evolution effects for the half kT moment of the Collins function and the unpolarized fragmentation function D1(z ) are also included. The results show that the asymmetries are sizable and measurable at the kinematical configurations of Belle and BABAR experiments. We also find that the evolution effects play an important role in the phenomenological analysis.

Search for mixing-induced C P violation using partial reconstruction of B ¯ 0 → D * + X ℓ - ν ¯ ℓ and kaon tagging

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lees, J. P.; Poireau, V.; Tisserand, V.

We describe in detail a previously published measurement of CP violation in B0-B¯0 oscillations, based on an integrated luminosity of 425.7 fb-1 collected by the BABAR experiment at the PEPII collider. We apply a novel technique to a sample of about 6 million B¯0→D*+-ν¯ decays selected with partial reconstruction of the D*+ meson. The charged lepton identifies the flavor of one B meson at its decay time, the flavor of the other B is determined by kaon tagging. We determine a CP violating asymmetry ACP=(N(B0B0)-N(B¯0B¯0))/(N(B0B0)+N(B¯0B¯0))=(0.06±0.17-0.32+0.38)% corresponding to ΔCP=1-|q/p|=(0.29±0.84-1.61+1.88)×10-3. This measurement is consistent and competitive with those obtained at the Bmore » factories with dilepton events.« less

Search for mixing-induced C P violation using partial reconstruction of B ¯ 0 → D * + X ℓ - ν ¯ ℓ and kaon tagging

DOE Office of Scientific and Technical Information (OSTI.GOV)

J. P. Lees

We describe in detail a previously published measurement of CP violation in B 0-B¯ 0 oscillations, based on an integrated luminosity of 425.7 fb -1 collected by the BABAR experiment at the PEPII collider. We apply a novel technique to a sample of about 6 million B¯ 0→D* +ℓ -ν ℓ¯ decays selected with partial reconstruction of the D*+ meson. The charged lepton identifies the flavor of one B meson at its decay time, the flavor of the other B is determined by kaon tagging. We determine a CP violating asymmetry ACP=(N(B0B0)-N(B¯ 0B¯ 0))/(N(B 0B 0)+N(B¯ 0B¯ 0))=(0.06±0.17 +0.38 -0.32)%more » corresponding to Δ CP=1-|q/p|=(0.29±0.84 +1.88 -1.61)×10 -3. This measurement is consistent and competitive with those obtained at the B factories with dilepton events.« less

Search for the rare decay B→Kνν¯

NASA Astrophysics Data System (ADS)

Del Amo Sanchez, P.; Lees, J. P.; Poireau, V.; Prencipe, E.; Tisserand, V.; Garra Tico, J.; Grauges, E.; Martinelli, M.; Palano, A.; Pappagallo, M.; Eigen, G.; Stugu, B.; Sun, L.; Battaglia, M.; Brown, D. N.; Hooberman, B.; Kerth, L. T.; Kolomensky, Yu. G.; Lynch, G.; Osipenkov, I. L.; Tanabe, T.; Hawkes, C. M.; Watson, A. T.; Koch, H.; Schroeder, T.; Asgeirsson, D. J.; Hearty, C.; Mattison, T. S.; McKenna, J. A.; Khan, A.; Randle-Conde, A.; Blinov, V. E.; Buzykaev, A. R.; Druzhinin, V. P.; Golubev, V. B.; Onuchin, A. P.; Serednyakov, S. I.; Skovpen, Yu. I.; Solodov, E. P.; Todyshev, K. Yu.; Yushkov, A. N.; Bondioli, M.; Curry, S.; Kirkby, D.; Lankford, A. J.; Mandelkern, M.; Martin, E. C.; Stoker, D. P.; Atmacan, H.; Gary, J. W.; Liu, F.; Long, O.; Vitug, G. M.; Campagnari, C.; Hong, T. M.; Kovalskyi, D.; Richman, J. D.; Eisner, A. M.; Heusch, C. A.; Kroseberg, J.; Lockman, W. S.; Martinez, A. J.; Schalk, T.; Schumm, B. A.; Seiden, A.; Winstrom, L. O.; Cheng, C. H.; Doll, D. A.; Echenard, B.; Hitlin, D. G.; Ongmongkolkul, P.; Porter, F. C.; Rakitin, A. Y.; Andreassen, R.; Dubrovin, M. S.; Mancinelli, G.; Meadows, B. T.; Sokoloff, M. D.; Bloom, P. C.; Ford, W. T.; Gaz, A.; Nagel, M.; Nauenberg, U.; Smith, J. G.; Wagner, S. R.; Ayad, R.; Toki, W. H.; Jasper, H.; Karbach, T. M.; Merkel, J.; Petzold, A.; Spaan, B.; Wacker, K.; Kobel, M. J.; Schubert, K. R.; Schwierz, R.; Bernard, D.; Verderi, M.; Clark, P. J.; Playfer, S.; Watson, J. E.; Andreotti, M.; Bettoni, D.; Bozzi, C.; Calabrese, R.; Cecchi, A.; Cibinetto, G.; Fioravanti, E.; Franchini, P.; Luppi, E.; Munerato, M.; Negrini, M.; Petrella, A.; Piemontese, L.; Baldini-Ferroli, R.; Calcaterra, A.; de Sangro, R.; Finocchiaro, G.; Nicolaci, M.; Pacetti, S.; Patteri, P.; Peruzzi, I. M.; Piccolo, M.; Rama, M.; Zallo, A.; Contri, R.; Guido, E.; Lo Vetere, M.; Monge, M. R.; Passaggio, S.; Patrignani, C.; Robutti, E.; Tosi, S.; Bhuyan, B.; Prasad, V.; Lee, C. L.; Morii, M.; Adametz, A.; Marks, J.; Uwer, U.; Bernlochner, F. U.; Ebert, M.; Lacker, H. M.; Lueck, T.; Volk, A.; Dauncey, P. D.; Tibbetts, M.; Behera, P. K.; Mallik, U.; Chen, C.; Cochran, J.; Crawley, H. B.; Dong, L.; Meyer, W. T.; Prell, S.; Rosenberg, E. I.; Rubin, A. E.; Gao, Y. Y.; Gritsan, A. V.; Guo, Z. J.; Arnaud, N.; Davier, M.; Derkach, D.; Firmino da Costa, J.; Grosdidier, G.; Le Diberder, F.; Lutz, A. M.; Malaescu, B.; Perez, A.; Roudeau, P.; Schune, M. H.; Serrano, J.; Sordini, V.; Stocchi, A.; Wang, L.; Wormser, G.; Lange, D. J.; Wright, D. M.; Bingham, I.; Chavez, C. A.; Coleman, J. P.; Fry, J. R.; Gabathuler, E.; Gamet, R.; Hutchcroft, D. E.; Payne, D. J.; Touramanis, C.; Bevan, A. J.; di Lodovico, F.; Sacco, R.; Sigamani, M.; Cowan, G.; Paramesvaran, S.; Wren, A. C.; Brown, D. N.; Davis, C. L.; Denig, A. G.; Fritsch, M.; Gradl, W.; Hafner, A.; Alwyn, K. E.; Bailey, D.; Barlow, R. J.; Jackson, G.; Lafferty, G. D.; West, T. J.; Anderson, J.; Cenci, R.; Jawahery, A.; Roberts, D. A.; Simi, G.; Tuggle, J. M.; Dallapiccola, C.; Salvati, E.; Cowan, R.; Dujmic, D.; Fisher, P. H.; Sciolla, G.; Zhao, M.; Lindemann, D.; Patel, P. M.; Robertson, S. H.; Schram, M.; Biassoni, P.; Lazzaro, A.; Lombardo, V.; Palombo, F.; Stracka, S.; Cremaldi, L.; Godang, R.; Kroeger, R.; Sonnek, P.; Summers, D. J.; Nguyen, X.; Simard, M.; Taras, P.; de Nardo, G.; Monorchio, D.; Onorato, G.; Sciacca, C.; Raven, G.; Snoek, H. L.; Jessop, C. P.; Knoepfel, K. J.; Losecco, J. M.; Wang, W. F.; Corwin, L. A.; Honscheid, K.; Kass, R.; Morris, J. P.; Blount, N. L.; Brau, J.; Frey, R.; Igonkina, O.; Kolb, J. A.; Rahmat, R.; Sinev, N. B.; Strom, D.; Strube, J.; Torrence, E.; Castelli, G.; Feltresi, E.; Gagliardi, N.; Margoni, M.; Morandin, M.; Posocco, M.; Rotondo, M.; Simonetto, F.; Stroili, R.; Ben-Haim, E.; Bonneaud, G. R.; Briand, H.; Calderini, G.; Chauveau, J.; Hamon, O.; Leruste, Ph.; Marchiori, G.; Ocariz, J.; Prendki, J.; Sitt, S.; Biasini, M.; Manoni, E.; Rossi, A.; Angelini, C.; Batignani, G.; Bettarini, S.; Carpinelli, M.; Casarosa, G.; Cervelli, A.; Forti, F.; Giorgi, M. A.; Lusiani, A.; Neri, N.; Paoloni, E.; Rizzo, G.; Walsh, J. J.; Lopes Pegna, D.; Lu, C.; Olsen, J.; Smith, A. J. S.; Telnov, A. V.; Anulli, F.; Baracchini, E.; Cavoto, G.; Faccini, R.; Ferrarotto, F.; Ferroni, F.; Gaspero, M.; Li Gioi, L.; Mazzoni, M. A.; Piredda, G.; Renga, F.; Hartmann, T.; Leddig, T.; Schröder, H.; Waldi, R.; Adye, T.; Franek, B.; Olaiya, E. O.; Wilson, F. F.; Emery, S.; Hamel de Monchenault, G.; Vasseur, G.; Yèche, Ch.; Zito, M.; Allen, M. T.; Aston, D.; Bard, D. J.; Bartoldus, R.; Benitez, J. F.; Cartaro, C.; Convery, M. R.; Dorfan, J.; Dubois-Felsmann, G. P.; Dunwoodie, W.; Field, R. C.; Franco Sevilla, M.; Fulsom, B. G.; Gabareen, A. M.; Graham, M. T.; Grenier, P.; Hast, C.; Innes, W. R.; Kelsey, M. H.; Kim, H.; Kim, P.; Kocian, M. L.; Leith, D. W. G. S.; Li, S.; Lindquist, B.; Luitz, S.; Luth, V.; Lynch, H. L.; Macfarlane, D. B.; Marsiske, H.; Muller, D. R.; Neal, H.; Nelson, S.; O'Grady, C. P.; Ofte, I.; Perl, M.; Pulliam, T.; Ratcliff, B. N.; Roodman, A.; Salnikov, A. A.; Santoro, V.; Schindler, R. H.; Schwiening, J.; Snyder, A.; Su, D.; Sullivan, M. K.; Sun, S.; Suzuki, K.; Thompson, J. M.; Va'Vra, J.; Wagner, A. P.; Weaver, M.; West, C. A.; Wisniewski, W. J.; Wittgen, M.; Wright, D. H.; Wulsin, H. W.; Yarritu, A. K.; Young, C. C.; Ziegler, V.; Chen, X. R.; Park, W.; Purohit, M. V.; White, R. M.; Wilson, J. R.; Sekula, S. J.; Bellis, M.; Burchat, P. R.; Edwards, A. J.; Miyashita, T. S.; Ahmed, S.; Alam, M. S.; Ernst, J. A.; Pan, B.; Saeed, M. A.; Zain, S. B.; Guttman, N.; Soffer, A.; Lund, P.; Spanier, S. M.; Eckmann, R.; Ritchie, J. L.; Ruland, A. M.; Schilling, C. J.; Schwitters, R. F.; Wray, B. C.; Izen, J. M.; Lou, X. C.; Bianchi, F.; Gamba, D.; Pelliccioni, M.; Bomben, M.; Lanceri, L.; Vitale, L.; Lopez-March, N.; Martinez-Vidal, F.; Milanes, D. A.; Oyanguren, A.; Albert, J.; Banerjee, Sw.; Choi, H. H. F.; Hamano, K.; King, G. J.; Kowalewski, R.; Lewczuk, M. J.; Nugent, I. M.; Roney, J. M.; Sobie, R. J.; Gershon, T. J.; Harrison, P. F.; Latham, T. E.; Puccio, E. M. T.; Band, H. R.; Dasu, S.; Flood, K. T.; Pan, Y.; Prepost, R.; Vuosalo, C. O.; Wu, S. L.

2010-12-01

We present a search for the rare decays B+→K+νν¯ and B0→K0νν¯ using 459×106 BB¯ pairs collected with the BABAR detector at the SLAC National Accelerator Laboratory. Flavor-changing neutral-current decays such as these are forbidden at tree level but can occur through one-loop diagrams in the standard model (SM), with possible contributions from new physics at the same order. The presence of two neutrinos in the final state makes identification of signal events challenging, so reconstruction in the semileptonic decay channels B→D(*)lν of the B meson recoiling from the signal B is used to suppress backgrounds. We set an upper limit at the 90% confidence level (CL) of 1.3×10-5 on the total branching fraction for B+→K+νν¯, and 5.6×10-5 for B0→K0νν¯. We additionally report 90% CL upper limits on partial branching fractions in two ranges of dineutrino mass squared for B+→K+νν¯.

Search for mixing-induced C P violation using partial reconstruction of B ¯ 0 → D * + X ℓ - ν ¯ ℓ and kaon tagging

DOE PAGES

Lees, J. P.; Poireau, V.; Tisserand, V.; ...

2016-02-08

We describe in detail a previously published measurement of CP violation in B0-B¯0 oscillations, based on an integrated luminosity of 425.7 fb-1 collected by the BABAR experiment at the PEPII collider. We apply a novel technique to a sample of about 6 million B¯0→D*+-ν¯ decays selected with partial reconstruction of the D*+ meson. The charged lepton identifies the flavor of one B meson at its decay time, the flavor of the other B is determined by kaon tagging. We determine a CP violating asymmetry ACP=(N(B0B0)-N(B¯0B¯0))/(N(B0B0)+N(B¯0B¯0))=(0.06±0.17-0.32+0.38)% corresponding to ΔCP=1-|q/p|=(0.29±0.84-1.61+1.88)×10-3. This measurement is consistent and competitive with those obtained at the Bmore » factories with dilepton events.« less

PREFACE: International Workshop on Discovery Physics at the LHC (Kruger2012)

NASA Astrophysics Data System (ADS)

Cleymans, Jean

2013-08-01

The second conference on 'Discovery Physics at the LHC' was held on 3-7 December 2012 at the Kruger Gate Hotel in South Africa. In total there were 110 participants from Armenia, Belgium, Brazil, Canada, Czech Republic, France, Germany, Greece, Israel, Italy, Norway, Poland, USA, Russia, Slovakia, Spain, Sweden, United Kingdom, Switzerland and South Africa. The latest results from the Large Hadron Collider, Brookhaven National Laboratory, Jefferson Laboratory and BABAR experiments, as well as the latest theoretical insights were presented. Set against the backdrop of the majestic Kruger National Park a very stimulating conference with many exchanges took place. The proceedings reflect the high standard of the conference. The financial contributions from the National Institute for Theoretical Physics (NITHeP), the SA-CERN programme, the UCT-CERN Research Centre, the University of Johannesburg, the University of the Witwatersrand and iThemba Labs—Laboratory for Accelerator Based Science are gratefully acknowledged. Jean Cleymans Chair of the Local Organizing Committee Local Organizing Committee Oana Boeriu Jean Cleymans Simon H Connell Alan S Cornell William A Horowitz Andre Peshier Trevor Vickey Zeblon Z Vilakazi Group picture

Search for the decay modes D⁰→e⁺e⁻, D⁰→μ⁺μ⁻, and D⁰→e ±μ∓

DOE PAGES

Lees, J. P.; Poireau, V.; Tisserand, V.; ...

2012-08-01

We present searches for the rare decay modes D⁰→e⁺e⁻, D0→μ⁺μ⁻, and D⁰→e ±μ ∓ in continuum e⁺e⁻→cc¯ events recorded by the BABAR detector in a data sample that corresponds to an integrated luminosity of 468 fb⁻¹. These decays are highly Glashow–Iliopoulos–Maiani suppressed but may be enhanced in several extensions of the standard model. Our observed event yields are consistent with the expected backgrounds. An excess is seen in the D⁰→μ⁺μ⁻ channel, although the observed yield is consistent with an upward background fluctuation at the 5% level. Using the Feldman–Cousins method, we set the following 90% confidence level intervals on themore » branching fractions: B(D⁰→e⁺e⁻)<1.7×10⁻⁷, B(D⁰→μ⁺μ⁻) within [0.6,8.1]×10⁻⁷, and B(D⁰→e ±μ ∓)<3.3×10⁻⁷.« less

Search for Strange Pentaquark Production in e{sup +}e{sup -} Annihilations at {radical}s=10.5 GeV and in {Upsilon}(4S) Decays

DOE Office of Scientific and Technical Information (OSTI.GOV)

Aubert, B

2004-08-16

The authors present a preliminary inclusive search for strange pentaquark production in e{sup +}e{sup -} interactions at a center-of-mass energy of 10.58 GeV using 123 fb{sup -1} of data collected with the BABAR detector. They look for the states that have been reported previously: the {Theta}{sup +}(1540), interpreted as a udud{bar s} state; and the {Xi}{sup --}(1860) and {Xi}{sup 0}(1860), candidate dsds{bar u} and uss(u{bar u} + d{bar d}) states, respectively. In addition they search for other members of the antidecuplet and corresponding octet to which these states are thought to belong. They find no evidence for the production ofmore » such states and set preliminary limits on their production cross sections as functions of c.m. momentum. The corresponding limits on the {Theta}{sup +}(1540) and {Xi}{sup --}(1860) rates per e{sup +}e{sup -} --> q{bar q} event are well below the rates measured for ordinary baryons of similar mass.« less

Final Report for U.S. DOE GRANT No. DEFG02-96ER41015 November 1, 2010 - April 30, 2013 entitled HIGH ENERGY ACCELERATOR AND COLLIDING BEAM USER GROUP at the UNIVERSITY of MARYLAND

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hadley, Nicholas; Jawahery, Abolhassan; Eno, Sarah C

2013-07-26

We have finished the third year of a three year grant cycle with the U.S. Department of Energy for which we were given a five month extension (U.S. D.O.E. Grant No. DEFG02-96ER41015). This document is the fi nal report for this grant and covers the period from November 1, 2010 to April 30, 2013. The Maryland program is administered as a single task with Professor Nicholas Hadley as Principal Investigator. The Maryland experimental HEP group is focused on two major research areas. We are members of the CMS experiment at the LHC at CERN working on the physics of themore » Energy Frontier. We are also analyzing the data from the Babar experiment at SLAC while doing design work and R&D towards a Super B experiment as part of the Intensity Frontier. We have recently joined the LHCb experiment at CERN. We concluded our activities on the D experiment at Fermilab in 2009.« less

Search for B{sup +} --> K{sup +} lepton-plus-lepton-minus and B{sup 0} --> K*{sup 0} lepton-plus-lepton-minus

DOE Office of Scientific and Technical Information (OSTI.GOV)

Barrera, Barbara

Using a sample of 3.7 x 10{sup 6} upsilon(4S) --> B anti-B events collected with the BaBar detector at the PEP-II storage ring, the authors search for the electroweak penguin decays B{sup +} --> K{sup +}e{sup +}e{sup {minus}}, B{sup +} --> K{sup +}mu{sup +}mu{sup {minus}},B{sup 0} --> K*{sup 0} e{sup +}e{sup {minus}}, and B{sup 0} --> K*{sup 0}mu{sup +}mu{sup {minus}}. The authors observe no significant signals for these modes and set preliminary 90% C.L. upper limits of: beta(B{sup +} --> K{sup +}e{sup +}e{sup {minus}}) < 12.5 x 10{sup {minus}6}; beta(B{sup +} --> K{sup +}mu{sup +}mu{sup {minus}}) < 8.3 x 10{supmore » {minus}6}; beta(B{sup 0} --> K*{sup 0}e{sup +}e{sup {minus}}) < 24.1 x 10{sup {minus}6}; and beta(B{sup 0} --> K*{sup 0}mu{sup +}mu{sup {minus}}) < 24.5 x 10{sup {minus}6}.« less

Closeout Report: Experimental High Energy Physics Group at the University of South Alabama

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jenkins, Charles M; Godang, Romulus

The High Energy Physics group at the University of South Alabama has been supported by this research grant (DE-FG02-96ER40970) since 1996. One researcher, Dr. Merrill Jenkins, has been supported on this grant during this time worked on fixed target experiments at the Fermi National Accelerator Laboratory, west of Chicago, Illinois. These experiments have been E-705, E-771, E-871 (HyperCP) and E-921 (CKM) before it was canceled for budgetary reasons. After the cancellation of CKM, Dr. Jenkins joined the Compact Muon Solenoid (CMS) experiment as an associate member via the High Energy Physics Group at the Florida State University. A second, recentlymore » tenured faculty member, Dr. Romulus Godang joined the group in 2009 and has been supported by this grant since then. Dr. Godang is working on the BaBaR experiment at SLAC and has joined the Belle-II experiment located in Japan at KEK. According to the instructions sent to us by our grant monitor, we are to concentrate on the activities over the last three years in this closeout report.« less

Extraction of quark transversity distribution and Collins fragmentation functions with QCD evolution

NASA Astrophysics Data System (ADS)

Kang, Zhong-Bo; Prokudin, Alexei; Sun, Peng; Yuan, Feng

2016-01-01

We study the transverse-momentum-dependent (TMD) evolution of the Collins azimuthal asymmetries in e+e- annihilations and semi-inclusive hadron production in deep inelastic scattering processes. All the relevant coefficients are calculated up to the next-to-leading-logarithmic-order accuracy. By applying the TMD evolution at the approximate next-to-leading-logarithmic order in the Collins-Soper-Sterman formalism, we extract transversity distributions for u and d quarks and Collins fragmentation functions from current experimental data by a global analysis of the Collins asymmetries in back-to-back dihadron productions in e+e- annihilations measured by BELLE and BABAR collaborations and semi-inclusive hadron production in deep inelastic scattering data from HERMES, COMPASS, and JLab HALL A experiments. The impact of the evolution effects and the relevant theoretical uncertainties are discussed. We further discuss the TMD interpretation for our results and illustrate the unpolarized quark distribution, transversity distribution, unpolarized quark fragmentation, and Collins fragmentation functions depending on the transverse momentum and the hard momentum scale. We make detailed predictions for future experiments and discuss their impact.

Phenomenology from SIDIS and e+e- multiplicities: multiplicities and phenomenology - part I

NASA Astrophysics Data System (ADS)

Bacchetta, Alessandro; Echevarria, Miguel G.; Radici, Marco; Signori, Andrea

2015-01-01

This study is part of a project to investigate the transverse momentum dependence in parton distribution and fragmentation functions, analyzing (semi-)inclusive high-energy processes within a proper QCD framework. We calculate the transverse-momentum-dependent (TMD) multiplicities for e+e- annihilation into two hadrons (considering different combinations of pions and kaons) aiming to investigate the impact of intrinsic and radiative partonic transverse momentum and their mixing with flavor. Different descriptions of the non-perturbative evolution kernel (see, e.g., Refs. [1-5]) are available on the market and there are 200 sets of flavor configurations for the unpolarized TMD fragmentation functions (FFs) resulting from a Monte Carlo fit of Semi-Inclusive Deep-Inelastic Scattering (SIDIS) data at Hermes (see Ref. [6]). We build our predictions of e+e- multiplicities relying on this rich phenomenology. The comparison of these calculations with future experimental data (from Belle and BaBar collaborations) will shed light on non-perturbative aspects of hadron structure, opening important insights into the physics of spin, flavor and momentum structure of hadrons.

Interplay of threshold resummation and hadron mass corrections in deep inelastic processes

DOE PAGES

Accardi, Alberto; Anderle, Daniele P.; Ringer, Felix

2015-02-01

We discuss hadron mass corrections and threshold resummation for deep-inelastic scattering lN-->l'X and semi-inclusive annihilation e +e - → hX processes, and provide a prescription how to consistently combine these two corrections respecting all kinematic thresholds. We find an interesting interplay between threshold resummation and target mass corrections for deep-inelastic scattering at large values of Bjorken x B. In semi-inclusive annihilation, on the contrary, the two considered corrections are relevant in different kinematic regions and do not affect each other. A detailed analysis is nonetheless of interest in the light of recent high precision data from BaBar and Belle onmore » pion and kaon production, with which we compare our calculations. For both deep inelastic scattering and single inclusive annihilation, the size of the combined corrections compared to the precision of world data is shown to be large. Therefore, we conclude that these theoretical corrections are relevant for global QCD fits in order to extract precise parton distributions at large Bjorken x B, and fragmentation functions over the whole kinematic range.« less

Dataset reporting the perceiver identification rates of basic emotions expressed by male, female and ambiguous gendered walkers in full-light, point-light and synthetically modelled point-light walkers.

PubMed

Halovic, Shaun; Kroos, Christian

2017-12-01

This data set describes the experimental data collected and reported in the research article "Walking my way? Walker gender and display format confounds the perception of specific emotions" (Halovic and Kroos, in press) [1]. The data set represent perceiver identification rates for different emotions (happiness, sadness, anger, fear and neutral), as displayed by full-light, point-light and synthetic point-light walkers. The perceiver identification scores have been transformed into H t rates, which represent proportions/percentages of correct identifications above what would be expected by chance. This data set also provides H t rates separately for male, female and ambiguously gendered walkers.

Large-scale benchmarking reveals false discoveries and count transformation sensitivity in 16S rRNA gene amplicon data analysis methods used in microbiome studies.

PubMed

Thorsen, Jonathan; Brejnrod, Asker; Mortensen, Martin; Rasmussen, Morten A; Stokholm, Jakob; Al-Soud, Waleed Abu; Sørensen, Søren; Bisgaard, Hans; Waage, Johannes

2016-11-25

There is an immense scientific interest in the human microbiome and its effects on human physiology, health, and disease. A common approach for examining bacterial communities is high-throughput sequencing of 16S rRNA gene hypervariable regions, aggregating sequence-similar amplicons into operational taxonomic units (OTUs). Strategies for detecting differential relative abundance of OTUs between sample conditions include classical statistical approaches as well as a plethora of newer methods, many borrowing from the related field of RNA-seq analysis. This effort is complicated by unique data characteristics, including sparsity, sequencing depth variation, and nonconformity of read counts to theoretical distributions, which is often exacerbated by exploratory and/or unbalanced study designs. Here, we assess the robustness of available methods for (1) inference in differential relative abundance analysis and (2) beta-diversity-based sample separation, using a rigorous benchmarking framework based on large clinical 16S microbiome datasets from different sources. Running more than 380,000 full differential relative abundance tests on real datasets with permuted case/control assignments and in silico-spiked OTUs, we identify large differences in method performance on a range of parameters, including false positive rates, sensitivity to sparsity and case/control balances, and spike-in retrieval rate. In large datasets, methods with the highest false positive rates also tend to have the best detection power. For beta-diversity-based sample separation, we show that library size normalization has very little effect and that the distance metric is the most important factor in terms of separation power. Our results, generalizable to datasets from different sequencing platforms, demonstrate how the choice of method considerably affects analysis outcome. Here, we give recommendations for tools that exhibit low false positive rates, have good retrieval power across effect sizes and case/control proportions, and have low sparsity bias. Result output from some commonly used methods should be interpreted with caution. We provide an easily extensible framework for benchmarking of new methods and future microbiome datasets.

Measurement properties of comorbidity indices in maternal health research: a systematic review.

PubMed

Aoyama, Kazuyoshi; D'Souza, Rohan; Inada, Eiichi; Lapinsky, Stephen E; Fowler, Robert A

2017-11-13

Maternal critical illness occurs in 1.2 to 4.7 of every 1000 live births in the United States and approximately 1 in 100 women who become critically ill will die. Patient characteristics and comorbid conditions are commonly summarized as an index or score for the purpose of predicting the likelihood of dying; however, most such indices have arisen from non-pregnant patient populations. We sought to systematically review comorbidity indices used in health administrative datasets of pregnant women, in order to critically appraise their measurement properties and recommend optimal tools for clinicians and maternal health researchers. We conducted a systematic search of MEDLINE and EMBASE to identify studies published from 1946 and 1947, respectively, to May 2017 that describe predictive validity of comorbidity indices using health administrative datasets in the field of maternal health research. We applied a methodological PubMed search filter to identify all studies of measurement properties for each index. Our initial search retrieved 8944 citations. The full text of 61 articles were identified and assessed for final eligibility. Finally, two eligible articles, describing three comorbidity indices appropriate for health administrative data remained: The Maternal comorbidity index, the Charlson comorbidity index and the Elixhauser Comorbidity Index. These studies of identified indices had a low risk of bias. The lack of an established consensus-building methodology in generating each index resulted in marginal sensibility for all indices. Only the Maternal Comorbidity Index was derived and validated specifically from a cohort of pregnant and postpartum women, using an administrative dataset, and had an associated c-statistic of 0.675 (95% Confidence Interval 0.647-0.666) in predicting mortality. Only the Maternal Comorbidity Index directly evaluated measurement properties relevant to pregnant women in health administrative datasets; however, it has only modest predictive ability for mortality among development and validation studies. Further research to investigate the feasibility of applying this index in clinical research, and its reliability across a variety of health administrative datasets would be incrementally helpful. Evolution of this and other tools for risk prediction and risk adjustment in pregnant and post-partum patients is an important area for ongoing study.

Displaying Planetary and Geophysical Datasets on NOAAs Science On a Sphere (TM)

NASA Astrophysics Data System (ADS)

Albers, S. C.; MacDonald, A. E.; Himes, D.

2005-12-01

NOAAs Science On a Sphere(TM)(SOS)was developed to educate current and future generations about the changing Earth and its processes. This system presents NOAAs global science through a 3D representation of our planet as if the viewer were looking at the Earth from outer space. In our presentation, we will describe the preparation of various global datasets for display on Science On a Sphere(TM), a 1.7-m diameter spherical projection system developed and patented at the Forecast Systems Laboratory (FSL) in Boulder, Colorado. Four projectors cast rotating images onto a spherical projection screen to create the effect of Earth, planet, or satellite floating in space. A static dataset can be prepared for display using popular image formats such as JPEG, usually sized at 1024x2048 or 2048x4096 pixels. A set of static images in a directory will comprise a movie. Imagery and data for SOS are obtained from a variety of government organizations, sometimes post-processed by various individuals, including the authors. Some datasets are already available in the required cylindrical projection. Readily available planetary maps can often be improved in coverage and/or appearance by reprojecting and combining additional images and mosaics obtained by various spacecraft, such as Voyager, Galileo, and Cassini. A map of Mercury was produced by blending some Mariner 10 photo-mosaics with a USGS shaded-relief map. An improved high-resolution map of Venus was produced by combining several Magellan mosaics, supplied by The Planetary Society, along with other spacecraft data. We now have a full set of Jupiter's Galilean satellite imagery that we can display on Science On a Sphere(TM). Photo-mosaics of several Saturnian satellites were updated by reprojecting and overlaying recently taken Cassini flyby images. Maps of imagery from five Uranian satellites were added, as well as one for Neptune. More image processing was needed to add a high-resolution Voyager mosaic to a pre-existing map of Neptune's moon Triton. A map of the cosmic background radiation was produced that shows the early universe from an external perspective. Full details and credits for these maps may be viewed online at http://laps.fsl.noaa.gov/albers/sos/sos.html. Geophysical imagery recently added to SOS includes a real-time global infrared weather satellite animation of Earth. This is a 15-minute, quality controlled animation spanning the most recent month, which draws on a number of geosynchronous and polar-orbiting weather satellites for data. Other meteorological and oceanographic datasets can be displayed, such as animations depicting the three-dimensional drifting of the ARGO buoy network through the oceans. Oceanic buoy observations were overlaid on the "Blue Marble" Earth imagery displayed on Science On a Sphere(TM). A static image shows locations for five different global buoy networks. We also produced two movies that show the drift of >1000 ARGO buoys over a period of several months. The first movie shows only the horizontal buoy drift, and the second modulates the intensities to represent the timing of each buoy dive cycle. Animations in real time are also being produced for sea surface temperatures (and anomalies). These analyses are obtained from web displays provided by the DOD Fleet Numerical Operations Center. With advanced technologies, the possibilities are limitless for displaying additional global datasets on Science On a Sphere(TM) and other spherical projection screens.

Over 10 million seawater temperature records for the United Kingdom Continental Shelf between 1880 and 2014 from 17 Cefas (United Kingdom government) marine data systems

NASA Astrophysics Data System (ADS)

Morris, David J.; Pinnegar, John K.; Maxwell, David L.; Dye, Stephen R.; Fernand, Liam J.; Flatman, Stephen; Williams, Oliver J.; Rogers, Stuart I.

2018-01-01

The datasets described here bring together quality-controlled seawater temperature measurements from over 130 years of departmental government-funded marine science investigations in the UK (United Kingdom). Since before the foundation of a Marine Biological Association fisheries laboratory in 1902 and through subsequent evolutions as the Directorate of Fisheries Research and the current Centre for Environment Fisheries & Aquaculture Science, UK government marine scientists and observers have been collecting seawater temperature data as part of oceanographic, chemical, biological, radiological, and other policy-driven research and observation programmes in UK waters. These datasets start with a few tens of records per year, rise to hundreds from the early 1900s, thousands by 1959, and hundreds of thousands by the 1980s, peaking with > 1 million for some years from 2000 onwards. The data source systems vary from time series at coastal monitoring stations or offshore platforms (buoys), through repeated research cruises or opportunistic sampling from ferry routes, to temperature extracts from CTD (conductivity, temperature, depth) profiles, oceanographic, fishery and plankton tows, and data collected from recreational scuba divers or electronic devices attached to marine animals. The datasets described have not been included in previous seawater temperature collation exercises (e.g. International Comprehensive Ocean-Atmosphere Data Set, Met Office Hadley Centre sea surface temperature data set, the centennial in situ observation-based estimates of sea surface temperatures), although some summary data reside in the British Oceanographic Data Centre (BODC) archive, the Marine Environment Monitoring and Assessment National (MERMAN) database and the International Council for the Exploration of the Sea (ICES) data centre. We envisage the data primarily providing a biologically and ecosystem-relevant context for regional assessments of changing hydrological conditions around the British Isles, although cross-matching with satellite-derived data for surface temperatures at specific times and in specific areas is another area in which the data could be of value (see e.g. Smit et al., 2013). Maps are provided indicating geographical coverage, which is generally within and around the UK Continental Shelf area, but occasionally extends north from Labrador and Greenland to east of Svalbard and southward to the Bay of Biscay. Example potential uses of the data are described using plots of data in four selected groups of four ICES rectangles covering areas of particular fisheries interest. The full dataset enables extensive data synthesis, for example in the southern North Sea where issues of spatial and numerical bias from a data source are explored. The full dataset also facilitates the construction of long-term temperature time series and an examination of changes in the phenology (seasonal timing) of ecosystem processes. This is done for a wide geographic area with an exploration of the limitations of data coverage over long periods. Throughout, we highlight and explore potential issues around the simple combination of data from the diverse and disparate sources collated here. The datasets are available on the Cefas Data Hub (https://www.cefas.co.uk/cefas-data-hub/). The referenced data sources are listed in Sect. 5.

Correlative Feature Analysis for Multimodality Breast CAD

DTIC Science & Technology

2009-09-01

Imaging 20, 1275–1284 2001. 22V. Caselles, R . Kimmel, and G. Sapiro, “Geodesic active contours,” Int. J. Comput. Vis. 22, 61–79 1997. 23R. Malladi , J...A. R . Jamieson, C. A. Sennett, and S. A. Jensen, “Evaluation of computer-aided diagnosis on a large clinical full-field digital mammographic dataset...Academic Radiology, 15, 1437-1445 (2008). Conference Proceeding Papers [1] Y. Yuan, M. L. Giger, K. Suzuki, H. Li, and A. R . Jamieson, “A

Development, Validation, and Fairness of a Biographical Data Questionnaire for the Air Traffic Control Specialist Occupation

DTIC Science & Technology

2012-12-01

Development and validation. ABA, BQ , and criterion data were extracted from AT- SAT concurrent, criterion- related validation database. Overall, 1,232...dependent on responses to the other instrument. 3 A subset of 260 controllers in the AT- SAT dataset had full and complete ABA, BQ , and criterion data (i.e... SAT cases with ABA, BQ , and criterion data (n=260) was very small, making fairness analyses with the validation sample impractical. However, the

Use of Persistent Identifiers to link Heterogeneous Data Systems in the Integrated Earth Data Applications (IEDA) Facility

NASA Astrophysics Data System (ADS)

Hsu, L.; Lehnert, K. A.; Carbotte, S. M.; Arko, R. A.; Ferrini, V.; O'hara, S. H.; Walker, J. D.

2012-12-01

The Integrated Earth Data Applications (IEDA) facility maintains multiple data systems with a wide range of solid earth data types from the marine, terrestrial, and polar environments. Examples of the different data types include syntheses of ultra-high resolution seafloor bathymetry collected on large collaborative cruises and analytical geochemistry measurements collected by single investigators in small, unique projects. These different data types have historically been channeled into separate, discipline-specific databases with search and retrieval tailored for the specific data type. However, a current major goal is to integrate data from different systems to allow interdisciplinary data discovery and scientific analysis. To increase discovery and access across these heterogeneous systems, IEDA employs several unique IDs, including sample IDs (International Geo Sample Number, IGSN), person IDs (GeoPass ID), funding award IDs (NSF Award Number), cruise IDs (from the Marine Geoscience Data System Expedition Metadata Catalog), dataset IDs (DOIs), and publication IDs (DOIs). These IDs allow linking of a sample registry (System for Earth SAmple Registration), data libraries and repositories (e.g. Geochemical Research Library, Marine Geoscience Data System), integrated synthesis databases (e.g. EarthChem Portal, PetDB), and investigator services (IEDA Data Compliance Tool). The linked systems allow efficient discovery of related data across different levels of granularity. In addition, IEDA data systems maintain links with several external data systems, including digital journal publishers. Links have been established between the EarthChem Portal and ScienceDirect through publication DOIs, returning sample-level objects and geochemical analyses for a particular publication. Linking IEDA-hosted data to digital publications with IGSNs at the sample level and with IEDA-allocated dataset DOIs are under development. As an example, an individual investigator could sign up for a GeoPass account ID, write a proposal to NSF and create a data plan using the IEDA Data Management Plan Tool. Having received the grant, the investigator then collects rock samples on a scientific cruise from dredges and registers the samples with IGSNs. The investigator then performs analytical geochemistry on the samples, and submits the full dataset to the Geochemical Resource Library for a dataset DOI. Finally, the investigator writes an article that is published in Science Direct. Knowing any of the following IDs: Investigator GeoPass ID, NSF Award Number, Cruise ID, Sample IGSNs, dataset DOI, or publication DOI, a user would be able to navigate to all samples, datasets, and publications in IEDA and external systems. Use of persistent identifiers to link heterogeneous data systems in IEDA thus increases access, discovery, and proper citation of hard-earned investigator datasets.

The experience of linking Victorian emergency medical service trauma data

PubMed Central

Boyle, Malcolm J

2008-01-01

Background The linking of a large Emergency Medical Service (EMS) dataset with the Victorian Department of Human Services (DHS) hospital datasets and Victorian State Trauma Outcome Registry and Monitoring (VSTORM) dataset to determine patient outcomes has not previously been undertaken in Victoria. The objective of this study was to identify the linkage rate of a large EMS trauma dataset with the Department of Human Services hospital datasets and VSTORM dataset. Methods The linking of an EMS trauma dataset to the hospital datasets utilised deterministic and probabilistic matching. The linking of three EMS trauma datasets to the VSTORM dataset utilised deterministic, probabilistic and manual matching. Results There were 66.7% of patients from the EMS dataset located in the VEMD. There were 96% of patients located in the VAED who were defined in the VEMD as being admitted to hospital. 3.7% of patients located in the VAED could not be found in the VEMD due to hospitals not reporting to the VEMD. For the EMS datasets, there was a 146% increase in successful links with the trauma profile dataset, a 221% increase in successful links with the mechanism of injury only dataset, and a 46% increase with sudden deterioration dataset, to VSTORM when using manual compared to deterministic matching. Conclusion This study has demonstrated that EMS data can be successfully linked to other health related datasets using deterministic and probabilistic matching with varying levels of success. The quality of EMS data needs to be improved to ensure better linkage success rates with other health related datasets. PMID:19014622