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263 results on '"HERRERA R P"'

4. Measurement of the background in the CMS muon detector in pps=13TeV-collisions at pps=13TeV pps=13TeV

Author

Tytgat, M., Muhammad, A., De Lentdecker, G., Jaramillo, J., Moureaux, L., Pétré, L., Yang, Y., Rendón, C., Gokbulut, G., Hong, Y., Samalan, A., Alves, G. A., Marujo da Silva, F., Alves Coelho, E., Barroso Ferreira Filho, M., Da Costa, E. M., De Jesus Damiao, D., Ferreira, B. C., Fonseca De Souza, S., Mota Amarilo, K., Nogima, H., Santoro, A., Thiel, M., Aleksandrov, A., Dimitrov, L., Hadjiiska, R., Iaydjiev, P., Misheva, M., Mitev, G., Ratchev, L., Rashevski, G., Shopova, M., Sultanov, G., Dimitrov, A., Litov, L., Pavlov, B., Petkov, P., Petrov, A., Shumka, E., Keshri, S., Thakur, S., Chen, M., Dong, X., Gong, W., Hou, Q., Jiang, C., Kou, H., Liu, Z.-A., Luo, W., Song, J., Sun, L., Wang, N., Wang, Y., Wang, Z., Zhang, C., Zhang, Y., Zhang, H., Zhao, J., Agapitos, A., Ban, Y., Levin, A., Li, Q., Qian, S. J., Wang, D., Wang, K., You, Z., Avila, C., Barbosa Trujillo, D. A., Cabrera, A., Florez, C. A., Fraga, J., Reyes Vega, J. A., Ramirez, F., Rodriguez, M., Ruiz, J. D., Vanegas, N., Abdalla, H., Abdelalim, A. A., Assran, Y., Radi, A., Crotty, I., Mahmoud, M. A., Balleyguier, L., Chen, X., Combaret, C., Galbit, G., Gouzevitch, M., Grenier, G., Laktineh, I. B., Luciol, A., Mirabito, L., Tromeur, W., Bagaturia, I., Lomidze, I., Kemularia, O., Tsamalaidze, Z., Böttger, U., Eliseev, D., Hebbeker, T., Hoepfner, K., Merschmeyer, M., Ivone, F., Mukherjee, S., Nowotny, F., Philipps, B., Reithler, H., Sharma, A., Torres Da Silva De Araujo, F., Wiedenbeck, S., Zaleski, S., Zantis, F. P., Abbas, M., Mallows, S., Bencze, G., Beni, N., Molnar, J., Szillasi, Z., Teyssier, D., Ujvari, B., Zilizi, G., Babbar, J., Bansal, S., Bhatnagar, V., Chauhan, S., Kaur, A., Kaur, H., Kaur Sahota, A., Kumar, S., Sheokand, T., Singh, J., Choudhary, B. C., Kumar, A., Kumar Saini, M., Naimuddin, M., Majumdar, N., Mukhopadhyay, S., Rout, P., Amoozegar, V., Boghrati, B., Ebraimi, M., Mohammadi Najafabadi, M., Zareian, E., Abbrescia, M., Aly, R., Buonsante, M., Colaleo, A., De Filippis, N., Dell’Olio, D., De Robertis, G., Elmetenawee, W., Ferrara, N., Franco, M., Iaselli, G., Lacalamita, N., Licciulli, F., Loddo, F., Maggi, M., Martiradonna, S., Nuzzo, S., Longo, L., Pellecchia, A., Pugliese, G., Radogna, R., Ramos, D., Ranieri, A., Simone, F. M., Stamerra, A., Troiano, D., Venditti, R., Verwilligen, P., Zaza, A., Abbiendi, G., Baldanza, C., Battilana, C., Benvenuti, A., Borgonovi, L., Cafaro, V., Cavallo, F. R., Crupano, A., Cuffiani, M., Dallavalle, G. M., Fabbri, F., Fanfani, A., Fasanella, D., Giacomelli, P., Giordano, V., Guandalini, C., Guiducci, L., Lo Meo, S., Lunerti, L., Marcellini, S., Masetti, G., Navarria, F. L., Paggi, G., Perrotta, A., Primavera, F., Rossi, A. M., Rovelli, T., Torromeo, G., Benussi, L., Bianco, S., Campagnola, R., Caponero, M., Colafranceschi, S., Meola, S., Passamonti, L., Piccolo, D., Pierluigi, D., Raffone, G., Russo, A., Saviano, G., Buontempo, S., Cagnotta, A., Carnevali, F., Cassese, F., Cavallo, N., De Iorio, A., Fabozzi, F., Iorio, A. O. M., Lista, L., Paolucci, P., Passeggio, G., Rossi, B., Barcellan, L., Bellato, M., Benettoni, M., Bergnoli, A., Bragagnolo, A., Carlin, R., Castellani, L., Checchia, P., Ciano, L., Colombo, A., Corti, D., Gasparini, F., Gasparini, U., Gonella, F., Gozzelino, A., Griggio, A., Grosso, G., Gulmini, M., Isocrate, R., Lusiani, E., Maron, G., Margoni, M., Meneguzzo, A. T., Migliorini, M., Modenese, L., Montecassiano, F., Negrello, M., Passaseo, M., Pazzini, J., Ramina, L., Rampazzo, M., Rebeschini, M., Ronchese, P., Rossin, R., Simonetto, F., Toffano, M., Toniolo, N., Triossi, A., Ventura, S., Zanetti, M., Zatti, P. G., Zotto, P., Zucchetta, A., AbuZeid, S., Aimè, C., Braghieri, A., Calzaferri, S., Fiorina, D., Gigli, S., Montagna, P., Riccardi, C., Salvini, P., Vai, I., Vitulo, P., Amapane, N., Cotto, G., Dattola, D., De Remigis, P., Kiani, B., Mariotti, C., Maselli, S., Pelliccioni , M., Rotondo, F., Staiano, A., Trocino, D., Umoret, G., Asilar, E., Kim, T. J., Merlin, J. A., Choi, S., Hong, B., Lee, K. S., Goh, J., Choi, J., Kim, J., Yang, U., Yoon, I., Jang, W., Heo, J., Kang, D., Kang, Y., Kim, D., Kim, S., Ko, B., Lee, J. S. H., Park, I. C., Watson, I. J., Yang, S., Jeong, Y., Lee, Y., Yu, I., Alasfour, G., Beyrouthy, T., Gharbia, Y., Maghrbi, Y., Otkur, M., Castilla-Valdez, H., Crotte Ledesma, H., Lopez-Fernandez, R., Sánchez Hernández, A., Ramírez García, M., Vazquez, E., Shah, M. A., Zaganidis, N., Pedraza, I., Uribe Estrada, C., Ahmad, A., Ahmed, W., Asghar, M. I., Hoorani, H. R., Muhammad, S., Wajid, A., Alcaraz Maestre, J., Álvarez Fernández, A., Fernandez Bedoya, Cristina F., Blanco Ramos, L. C., Calvo, E., Carrillo Montoya, C. A., Cela Ruiz, J. M., Cepeda, M., Cerrada, M., Colino, N., Cuadrado Calzada, S., Cuchillo Ortega, J., De La Cruz, B., de Lara Rodríguez, C. I., Fernández Del Val, D., Fernández Ramos, J. P., Fouz, M. C., Francia Ferrero, D., García Romero, J., Gonzalez Lopez, O., Goy Lopez, S., Josa, M. I., León Holgado, J., Manzanilla Carretero, O., Martín Martín, I., Martínez Morales, J. J., Martín Viscasillas, E., Moran, D., Navarro Tobar, Á., Paz Herrera, R., Puras Sánchez, J. C., Puerta Pelayo, J., Pulido Ferrero, S., Redondo, I., Redondo Ferrero, D. D., Salto Parra, V., Sánchez Navas, S., Sastre, J., Urda Gómez, L., Vazquez Escobar, J., de Trocóniz, J. F., Frias Garcia-Lago, F., Reyes-Almanza, R., Alvarez Gonzalez, B., Cuevas, J., Fernandez Menendez, J., Folgueras, S., Gonzalez Caballero, I., Leguina López, P., Palencia Cortezon, E., Ramón Álvarez, C., Prado Pico, J., Rodríguez Bouza, V., Soto Rodríguez, A., Trapote, A., Villalba, C. Vico, Kailasapathy, B., Malagalage, K., Sonnadara, D. U. J., Wickramarathna, D. D. C., Dharmaratna, W. G. D., Liyanage, K., Perera, N., Wickramage, N., Aspell, P., Bianco, M., Bozzato, D., Brachet, S., Conde Garcia, A., Dabrowski, A., De Oliveira, R., Fallavollita, F., Kicsiny, P., Sharma, A., Hazen, E., May, S., Peck, A., Salyer, K., Suarez, I., Abbott, S., Bonilla, J., Breedon, R., Cai, H., Cox, P. T., Erbacher, R., Kukral, O., McLean, C., Mocellin, G., Mulhearn, M., Regnery, B., Tripathi, M., Waegel, G., Yao, Y., Carlson, J., Cousins, R., Dasgupta, A., Datta, A., Hauser, J., Ignatenko, M., Iqbal, M. A., Lo, C., Saltzberg, D., Schnaible, C., Valuev, V., Clare, R., Gordon, M., Hanson, G., Amin, N., Bradmiller-Feld, J., Campagnari, C., Danielson, T., Dishaw, A., Dorsett, A., Kim, J., Marsh, B., Mei, H., Oshiro, M., Richman, J., Setti, F., Sevilla, M. F., Siddireddy, P., Wang, S., Aruta, C., Barashko, V., Cherepanov, V., Dittrich, M., Korytov, A., Kuznetsova, E., Madorsky, A., Mitselmakher, G., Muthirakalayil Madhu, A., Rawal, N., Terentyev, N., Wang, J., Alsufyani, B., Butalla, S., Elkafrawy, T., Hohlmann, M., Yanes, E., Eysermans, J., Barberis, E., Haddad, Y., Han, Y., Madigan, G., Morse, D. M., Nguyen, V., Wood, D., Bhattacharya, S., Bueghly, J., Chen, Z., Hahn, K. A., Liu, Y., Miao, Y., Monk, D. G., Schmitt, M. H., Taliercio, A., Velasco, M., Bylsma, B., Carrigan, M., De Los Santos, R., Durkin, L. S., Hill, C., Banicz, K., Liu, J., Matveev, M., Padley, B. P., Aebi, D., Ahmad, M., Akhter, T., Bolshov, A., Bouhali, O., Eusebi, R., Gilmore, J., Huang, T., Juska, E., Kamon, T., Kim, H., Kizlov, M., Malhotra, S., Mueller, R., Rabadan, R., Rathjens, D., Safonov, A., Karchin, P. E., Aravind, A., Black, K., De Bruyn, I., Everaerts, P., Galloni, C., Herndon, M., Lanaro, A., Loveless, R., Madhusudanan Sreekala, J., Mondal, S., Teague, D., Vetens, W., Warden, A., Azhgirey, I., Borshch, V., Chtchipunov, L., Egorov, A., Gavrilov, G., Golovtcov, V., Ivanov, M., Ivantchenko, V., Ivanov, Y., Karjavine, V., Khodinov, A., Kim, V., Kurochkin, I. A., Levchenko, P., Murzin, V., Nasybulin, S., Oreshkin, V., Palichik, V., Perelygin, V., Riabchikova, A., Sosnov, D., Sulimov, V., Uvarov, L., Vavilov, S., and Vorobyev, A.

Published
2024
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6. Optimization of the JUNO liquid scintillator composition using a Daya Bay antineutrino detector

Author

Bay, Daya, collaborations, JUNO, Abusleme, A., Adam, T., Ahmad, S., Aiello, S., Akram, M., Ali, N., An, F. P., An, G. P., An, Q., Andronico, G., Anfimov, N., Antonelli, V., Antoshkina, T., Asavapibhop, B., de André, J. P. A. M., Babic, A., Balantekin, A. B., Baldini, W., Baldoncini, M., Band, H. R., Barresi, A., Baussan, E., Bellato, M., Bernieri, E., Biare, D., Birkenfeld, T., Bishai, M., Blin, S., Blum, D., Blyth, S., Bordereau, C., Brigatti, A., Brugnera, R., Budano, A., Burgbacher, P., Buscemi, M., Bussino, S., Busto, J., Butorov, I., Cabrera, A., Cai, H., Cai, X., Cai, Y. K., Cai, Z. Y., Cammi, A., Campeny, A., Cao, C. Y., Cao, G. F., Cao, J., Caruso, R., Cerna, C., Chakaberia, I., Chang, J. F., Chang, Y., Chen, H. S., Chen, P. A., Chen, P. P., Chen, S. M., Chen, S. J., Chen, X. R., Chen, Y. W., Chen, Y. X., Chen, Y., Chen, Z., Cheng, J., Cheng, Y. P., Cheng, Z. K., Chepurnov, A., Cherwinka, J. J., Chiarello, F., Chiesa, D., Chimenti, P., Chu, M. C., Chukanov, A., Chuvashova, A., Clementi, ., Clerbaux, B., Di Lorenzo, S. Conforti, Corti, D., Costa, S., Corso, F. D., Cummings, J. P., Dalager, O., De La Taille, C., Deng, F. S., Deng, J. W., Deng, Z., Deng, Z. Y., Depnering, W., Diaz, M., Ding, X. F., Ding, Y. Y., Dirgantara, B., Dmitrievsky, S., Diwan, M. V., Dohnal, T., Donchenko, G., Dong, J. M., Dornic, D., Doroshkevich, E., Dove, J., Dracos, M., Druillole, F., Du, S. X., Dusini, S., Dvorak, M., Dwyer, D. A., Enqvist, T., Enzmann, H., Fabbri, A., Fajt, L., Fan, D. H., Fan, L., Fang, C., Fang, J., Fatkina, A., Fedoseev, D., Fekete, V., Feng, L. C., Feng, Q. C., Fiorentini, G., Ford, R., Formozov, A., Fournier, A., Franke, S., Gallo, J. P., Gan, H. N., Gao, F., Garfagnini, A., Göttel, A., Genster, C., Giammarchi, M., Giaz, A., Giudice, N., Giuliani, F., Gonchar, M., Gong, G. H., Gong, H., Gorchakov, O., Gornushkin, Y., Grassi, M., Grewing, C., Gromov, M., Gromov, V., Gu, M. H., Gu, W. Q., Gu, X. F., Gu, Y., Guan, M. Y., Guardone, N., Gul, M., Guo, C., Guo, J. Y., Guo, L., Guo, W. L., Guo, X. H., Guo, Y. H., Guo, Z., Haacke, M., Hackenburg, R. W., Hackspacher, P., Hagner, C., Han, R., Han, Y., Hans, S., He, M., He, W., Heeger, K. M., Heinz, T., Heng, Y. K., Herrera, R., Higuera, A., Hong, D. J., Hor, Y. K., Hou, S. J., Hsiung, Y. B., Hu, B. Z., Hu, H., Hu, J. R., Hu, J., Hu, S. Y., Hu, T., Hu, Z. J., Huang, C. H., Huang, G. H., Huang, H. X., Huang, Q. H., Huang, W. H., Huang, X. T., Huang, Y. B., Huber, P., Hui, J. Q., Huo, L., Huo, W. J., Huss, C., Hussain, S., Insolia, A., Ioannisian, A., Ioannisyan, D., Isocrate, R., Jaffe, D. E., Jen, K. L., Ji, X. L., Ji, X. P., Ji, X. Z., Jia, H. H., Jia, J. J., Jian, S. Y., Jiang, D., Jiang, X. S., Jin, R. Y., Jing, X. P., Johnson, R. A., Jollet, C., Jones, D., Joutsenvaara, J., Jungthawan, S., Kalousis, L., Kampmann, P., Kang, L., Karagounis, M., Kazarian, N., Kettell, S. H., Khan, A., Khan, W., Khosonthongkee, K., Kinz, P., Kohn, S., Korablev, D., Kouzakov, K., Kramer, M., Krasnoperov, A., Krokhaleva, S., Krumshteyn, Z., Kruth, A., Kutovskiy, N., Kuusiniemi, P., Lachacinski, B., Lachenmaier, T., Langford, T. J., Lee, J., Lee, J. H. C., Lefevre, F., Lei, L., Lei, R., Leitner, R., Leung, J., Li, C., Li, D. M., Li, F., Li, H. T., Li, H. L., Li, J., Li, J. J., Li, J. Q., Li, K. J., Li, M. Z., Li, N., Li, Q. J., Li, R. H., Li, S. C., Li, S. F., Li, S. J., Li, T., Li, W. D., Li, W. G., Li, X. M., Li, X. N., Li, X. L., Li, X. Q., Li, Y., Li, Y. F., Li, Z. B., Li, Z. Y., Liang, H., Liang, J. J., Liebau, D., Limphirat, A., Limpijumnong, S., Lin, C. J., Lin, G. L., Lin, S. X., Lin, T., Lin, Y. H., Ling, J. J., Link, J. M., Lippi, I., Littenberg, L., Littlejohn, B. R., Liu, F., Liu, H., Liu, H. B., Liu, H. D., Liu, H. J., Liu, H. T., Liu, J. C., Liu, J. L., Liu, M., Liu, Q., Liu, R. X., Liu, S. Y., Liu, S. B., Liu, S. L., Liu, X. W., Liu, Y., Lokhov, A., Lombardi, P., Loo, K., Lorenz, S., Lu, C., Lu, H. Q., Lu, J. B., Lu, J. G., Lu, S. X., Lu, X. X., Lubsandorzhiev, B., Lubsandorzhiev, S., Ludhova, L., Luk, K. B., Luo, F. J., Luo, G., Luo, P. W., Luo, S., Luo, W. M., Lyashuk, V., Ma, Q. M., Ma, S., Ma, X. B., Ma, X. Y., Ma, Y. Q., Malyshkin, Y., Mantovani, F., Mao, Y. J., Mari, S. M., Marini, F., Marium, S., Marshall, C., Martellini, C., Martin-Chassard, G., Caicedo, D. A. Martinez, Martini, A., Martino, J., Mayilyan, D., McDonald, K. T., McKeown, R. D., Müller, A., Meng, G., Meng, Y., Meregaglia, A., Meroni, E., Meyhöfer, D., Mezzetto, M., Miller, J., Miramonti, L., Monforte, S., Montini, P., Montuschi, M., Morozov, N., Muralidharan, P., Napolitano, J., Nastasi, M., Naumov, D. V., Naumova, E., Nemchenok, I., Nikolaev, A., Ning, F. P., Ning, Z., Nunokawa, H., Oberauer, L., Ochoa-Ricoux, J. P., Olshevskiy, A., Ortica, F., Pan, H. R., Paoloni, A., Park, J., Parkalian, N., Parmeggiano, S., Patton, S., Payupol, T., Pec, V., Pedretti, D., Pei, Y. T., Pelliccia, N., Peng, A. G., Peng, H. P., Peng, J. C., Perrot, F., Petitjean, P. A., Rico, L. F. Pineres, Popov, A., Poussot, P., Pratumwan, W., Previtali, E., Pun, C. S. J., Qi, F. Z., Qi, M., Qian, S., Qian, X., Qian, X. H., Qiao, H., Qin, Z. H., Qiu, S. K., Rajput, M., Ranucci, G., Raper, N., Re, A., Rebber, H., Rebii, A., Ren, B., Ren, J., Reveco, C. M., Rezinko, T., Ricci, B., Robens, M., Roche, M., Rodphai, N., Rohwer, L., Romani, A., Rosero, R., Roskovec, B., Roth, C., Ruan, X. C., Ruan, X. D., Rujirawat, S., Rybnikov, A., Sadovsky, A., Saggese, P., Salamanna, G., Sangka, A., Sanguansak, N., Sawangwit, U., Sawatzki, J., Sawy, F., Schever, M., Schuler, J., Schwab, C., Schweizer, K., Selivanov, D., Selyunin, A., Serafini, A., Settanta, G., Settimo, M., Shahzad, M., Shi, G., Shi, J. Y., Shi, Y. J., Shutov, V., Sidorenkov, A., Simkovic, F., Sirignano, C., Siripak, J., Sisti, M., Slupecki, M., Smirnov, M., Smirnov, O., Sogo-Bezerra, T., Songwadhana, J., Soonthornthum, B., Sotnikov, A., Sramek, O., Sreethawong, W., Stahl, A., Stanco, L., Stankevich, K., Stefanik, D., Steiger, H., Steiner, H., Steinmann, J., Stender, M., Strati, V., Studenikin, A., Sun, G. X., Sun, L. T., Sun, J. L., Sun, S. F., Sun, X. L., Sun, Y. J., Sun, Y. Z., Suwonjandee, N., Szelezniak, M., Tang, J., Tang, Q., Tang, X., Tietzsch, A., Tkachev, I., Tmej, T., Treskov, K., Troni, G., Trzaska, W., Tse, W. -H., Tull, C. E., Tuve, C., van Waasen, S., Boom, J. Vanden, Vassilopoulos, N., Vedin, V., Verde, G., Vialkov, M., Viaud, B., Viren, B., Volpe, C., Vorobel, V., Votano, L., Walker, P., Wang, C., Wang, C. H., Wang, E., Wang, G. L., Wang, J., Wang, K. Y., Wang, L., Wang, M. F., Wang, M., Wang, N. Y., Wang, R. G., Wang, S. G., Wang, W., Wang, W. S., Wang, X., Wang, X. Y., Wang, Y., Wang, Y. F., Wang, Y. G., Wang, Y. M., Wang, Y. Q., Wang, Z., Wang, Z. M., Wang, Z. Y., Watcharangkool, A., Wei, H. Y., Wei, L. H., Wei, W., Wei, Y. D., Wen, L. J., Whisnant, K., White, C. G., Wiebusch, C., Wong, S. C. F., Wong, H. L. H., Wonsak, B., Worcester, E., Wu, C. H., Wu, D. R., Wu, F. L., Wu, Q., Wu, W. J., Wu, Z., Wurm, M., Wurtz, J., Wysotzki, C., Xi, Y. F., Xia, D. M., Xie, Y. G., Xie, Z. Q., Xing, Z. Z., Xu, D. L., Xu, F. R., Xu, H. K., Xu, J. L., Xu, J., Xu, M. H., Xu, T., Xu, Y., Xue, T., Yan, B. J., Yan, X. B., Yan, Y. P., Yang, A. B., Yang, C. G., Yang, H., Yang, J., Yang, L., Yang, X. Y., Yang, Y. F., Yang, Y. Z., Yao, H. F., Yasin, Z., Ye, J. X., Ye, M., Yegin, U., Yeh, M., Yermia, F., Yi, P. H., You, Z. Y., Young, B. L., Yu, B. X., Yu, C. X., Yu, C. Y., Yu, H. Z., Yu, M., Yu, X. H., Yu, Z. Y., Yuan, C. Z., Yuan, Y., Yuan, Z. X., Yuan, Z. Y., Yue, B. B., Zafar, N., Zambanini, A., Zeng, P., Zeng, S., Zeng, T. X., Zeng, Y. D., Zhan, L., Zhang, C., Zhang, F. Y., Zhang, G. Q., Zhang, H. H., Zhang, H. Q., Zhang, J., Zhang, J. B., Zhang, J. W., Zhang, P., Zhang, Q. M., Zhang, T., Zhang, X. M., Zhang, X. T., Zhang, Y., Zhang, Y. H., Zhang, Y. M., Zhang, Y. P., Zhang, Y. X., Zhang, Y. Y., Zhang, Z. J., Zhang, Z. P., Zhang, Z. Y., Zhao, F. Y., Zhao, J., Zhao, R., Zhao, S. J., Zhao, T. C., Zheng, D. Q., Zheng, H., Zheng, M. S., Zheng, Y. H., Zhong, W. R., Zhou, J., Zhou, L., Zhou, N., Zhou, S., Zhou, X., Zhu, J., Zhu, K. J., Zhuang, H. L., Zong, L., and Zou, J. H.

Subjects
Physics - Instrumentation and Detectors, High Energy Physics - Experiment
Abstract

To maximize the light yield of the liquid scintillator (LS) for the Jiangmen Underground Neutrino Observatory (JUNO), a 20 t LS sample was produced in a pilot plant at Daya Bay. The optical properties of the new LS in various compositions were studied by replacing the gadolinium-loaded LS in one antineutrino detector. The concentrations of the fluor, PPO, and the wavelength shifter, bis-MSB, were increased in 12 steps from 0.5 g/L and <0.01 mg/L to 4 g/L and 13 mg/L, respectively. The numbers of total detected photoelectrons suggest that, with the optically purified solvent, the bis-MSB concentration does not need to be more than 4 mg/L. To bridge the one order of magnitude in the detector size difference between Daya Bay and JUNO, the Daya Bay data were used to tune the parameters of a newly developed optical model. Then, the model and tuned parameters were used in the JUNO simulation. This enabled to determine the optimal composition for the JUNO LS: purified solvent LAB with 2.5 g/L PPO, and 1 to 4 mg/L bis-MSB., Comment: 13 pages, 8 figures

Published
2020

10. Is the cosmological dark sector better modeled by a generalized Chaplygin gas or by a scalar field?

Author

del Campo, S., Fabris, J. C., Herrera, R., and Zimdahl, W.

Subjects
Astrophysics - Cosmology and Nongalactic Astrophysics, General Relativity and Quantum Cosmology
Abstract

Both scalar fields and (generalized) Chaplygin gases have been widely used separately to characterize the dark sector of the Universe. Here we investigate the cosmological background dynamics for a mixture of both these components and quantify the fractional abundances that are admitted by observational data from supernovae of type Ia and from the evolution of the Hubble rate. Moreover, we study how the growth rate of (baryonic) matter perturbations is affected by the dark-sector perturbations., Comment: 20 pages, 9 figures, substantially revised, section on matter perturbations added, accepted for publication in EPJC

Published
2017
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12. The role of master regulators in gene regulatory networks

Author

Hernández-Lemus, E., Baca-López, K., Lemus, R., and García-Herrera, R.

Subjects
Quantitative Biology - Molecular Networks, Nonlinear Sciences - Adaptation and Self-Organizing Systems
Abstract

Gene regulatory networks present a wide variety of dynamical responses to intrinsic and extrinsic perturbations. Arguably, one of the most important of such coordinated responses is the one of amplification cascades, in which activation of a few key-responsive transcription factors (termed master regulators, MRs) lead to a large series of transcriptional activation events. This is so since master regulators are transcription factors controlling the expression of other transcription factor molecules and so on. MRs hold a central position related to transcriptional dynamics and control of gene regulatory networks and are often involved in complex feedback and feedforward loops inducing non-trivial dynamics. Recent studies have pointed out to the myocyte enhancing factor 2C (MEF2C, also known as MADS box transcription enhancer factor 2, polypeptide C) as being one of such master regulators involved in the pathogenesis of primary breast cancer. In this work, we perform an integrative genomic analysis of the transcriptional regulation activity of MEF2C and its target genes to evaluate to what extent are these molecules inducing collective responses leading to gene expression deregulation and carcinogenesis. We also analyzed a number of induced dynamic responses, in particular those associated with transcriptional bursts, and nonlinear cascading to evaluate the influence they may have in malignant phenotypes and cancer., Comment: 8 pages, 4 figures

Published
2015
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13. Cosmology with Ricci-type dark energy

Author

Zimdahl, W., Fabris, J. C., del Campo, S., and Herrera, R.

Subjects
Astrophysics - Cosmology and Nongalactic Astrophysics, General Relativity and Quantum Cosmology, High Energy Physics - Theory
Abstract

We consider the dynamics of a cosmological substratum of pressureless matter and holographic dark energy with a cutoff length proportional to the Ricci scale. Stability requirements for the matter perturbations are shown to single out a model with a fixed relation between the present matter fraction $\Omega_{m0}$ and the present value $\omega_{0}$ of the equation-of-state parameter of the dark energy. This model has the same number of free parameters as the $\Lambda$CDM model but it has no $\Lambda$CDM limit. We discuss the consistency between background observations and the mentioned stability-guaranteeing parameter combination., Comment: 6 pages, 3 figures, submitted to the Proceedings of the CosmoSurII conference, Valpara\'iso, Chile, 27 - 31 May 2013

Published
2014
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22. Application of Fractional Fourier Transform in Cepstrum Analysis

Author

Miah, K. H., Herrera, R. H., van der Baan, M., and Sacchi, M. D.

Subjects
Computer Science - Information Theory, Physics - Geophysics
Abstract

Source wavelet estimation is the key in seismic signal processing for resolving subsurface structural properties. Homomorphic deconvolution using cepstrum analysis has been an effective method for wavelet estimation for decades. In general, the inverse of the Fourier transform of the logarithm of a signal's Fourier transform is the cepstral domain representation of that signal. The convolution operation of two signals in the time domain becomes an addition in the cepstral domain. The fractional Fourier transform (FRFT) is the generalization of the standard Fourier transform (FT). In an FRFT, the transformation kernel is a set of linear chirps whereas the kernel is composed of complex sinusoids for the FT. Depending on the fractional order, signals can be represented in multiple domains. This gives FRFT an extra degree of freedom in signal analysis over the standard FT. In this paper, we have taken advantage of the multidomain nature of the FRFT and applied it to cepstral analysis. We term this combination the Fractional-Cepstrum (FC). We derive the real FC formulation, and give an example using wavelets to show the multidomain representation of the traditional cepstrum with different fractional orders of the FRFT., Comment: 4 pages, Conference: Recovery - 2011 CSPG CSEG CWLS Convention

Published
2012

23. Tachyon warm inflationary universe models

Author

Herrera, R., del Campo, S., and Campuzano, C.

Subjects
Astrophysics, General Relativity and Quantum Cosmology, High Energy Physics - Phenomenology, High Energy Physics - Theory
Abstract

Warm inflationary universe models in a tachyon field theory are studied. General conditions required for these models to be realizable are derived and discussed. We describe scalar perturbations (in the longitudinal gauge) and tensor perturbations for these scenarios. We develop our models for a constant dissipation parameter $\Gamma$ in one case and one dependent on $\phi$ in the other case. We have been successful in describing such of inflationary universe models. We use recent astronomical observations for constraining the parameters appearing in our model. Also, our results are compared with their analogous found in the cool inflationary case., Comment: 21 pages, Accepted by JCAP

Published
2006
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24. Curvaton reheating in tachyonic inflationary models

Author

Campuzano, C., del Campo, S., and Herrera, R.

Subjects
General Relativity and Quantum Cosmology, Astrophysics, High Energy Physics - Theory
Abstract

The curvaton reheating in a tachyonic inflationary universe model with an exponential potential is studied. We have found that the energy density in the kinetic epoch, has a complicated dependencies of the scale factor. For different scenarios, the temperature of reheating is computed. These temperature result to be analogous to those obtained in the standard case of the curvaton scenario., Comment: 9 pages, Accepted for publication in Phys. Letter B

Published
2005
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25. Basin-wide variations in Amazon forest structure and function are mediated by both soils and climate

Author

Quesada, C. A, Phillips, O. L, Schwarz, M., Czimczik, C. I, Baker, T. R, Patiño, S., Fyllas, N. M, Hodnett, M. G, Herrera, R., Almeida, S., Alvarez Dávila, E., Arneth, A., Arroyo, L., Chao, K. J, Dezzeo, N., Erwin, T., di Fiore, A., Higuchi, N., Honorio Coronado, E., Jimenez, E. M, Killeen, T., Lezama, A. T, Lloyd, G., López-González, G., Luizão, F. J, Malhi, Y., Monteagudo, A., Neill, D. A, Núñez Vargas, P., Paiva, R., Peacock, J., Peñuela, M. C, Peña Cruz, A., Pitman, N., Priante Filho, N., Prieto, A., Ramírez, H., Rudas, A., Salomão, R., Santos, A. J. B, Schmerler, J., Silva, N., Silveira, M., Vásquez, R., Vieira, I., Terborgh, J., and Lloyd, J.

Subjects
tropical rain-forest, plant-growth responses, ecological field experiments, net primary productivity, wood specific-gravity, branch xylem density, stem water storage, long term plots, geographical ecology, use efficiency
Abstract

Forest structure and dynamics vary across the Amazon Basin in an east-west gradient coincident with variations in soil fertility and geology. This has resulted in the hypothesis that soil fertility may play an important role in explaining Basin-wide variations in forest biomass, growth and stem turnover rates. Soil samples were collected in a total of 59 different forest plots across the Amazon Basin and analysed for exchangeable cations, carbon, nitrogen and pH, with several phosphorus fractions of likely different plant availability also quantified. Physical properties were additionally examined and an index of soil physical quality developed. Bivariate relationships of soil and climatic properties with above-ground wood productivity, stand-level tree turnover rates, above-ground wood biomass and wood density were first examined with multivariate regression models then applied. Both forms of analysis were undertaken with and without considerations regarding the underlying spatial structure of the dataset. Despite the presence of autocorrelated spatial structures complicating many analyses, forest structure and dynamics were found to be strongly and quantitatively related to edaphic as well as climatic conditions. Basin-wide differences in stand-level turnover rates are mostly influenced by soil physical properties with variations in rates of coarse wood production mostly related to soil phosphorus status. Total soil P was a better predictor of wood production rates than any of the fractionated organic- or inorganic-P pools. This suggests that it is not only the immediately available P forms, but probably the entire soil phosphorus pool that is interacting with forest growth on longer timescales. A role for soil potassium in modulating Amazon forest dynamics through its effects on stand-level wood density was also detected. Taking this into account, otherwise enigmatic variations in stand-level biomass across the Basin were then accounted for through the interacting effects of soil physical and chemical properties with climate. A hypothesis of self-maintaining forest dynamic feedback mechanisms initiated by edaphic conditions is proposed. It is further suggested that this is a major factor determining endogenous disturbance levels, species composition, and forest productivity across the Amazon Basin.

Published
2012

26. Variations in chemical and physical properties of Amazon forest soils in relation to their genesis

Author

Quesada, C. A, Lloyd, J., Schwarz, M., Patiño, S., Baker, T. R, Czimczik, C., Fyllas, N. M, Martinelli, L., Nardoto, G. B, Schmerler, J., Santos, A. J. B, Hodnett, M. G, Herrera, R., Luizão, F. J, Arneth, A., Lloyd, G., Dezzeo, N., Hilke, I., Kuhlmann, I., Raessler, M., Brand, W. A, Geilmann, H., Moraes Filho, J. O, Carvalho, F. P, Araujo Filho, R. N, Chaves, J. E, Cruz Junior, O. F, Pimentel, T. P, and Paiva, R.

Subjects
tropical rain-forests, plant-available phosphorus, litter decomposition, organic phosphorus, hedley fractionation, phosphate rock, rhizosphere, nitrogen, dynamics, ecosystems
Abstract

Soil samples were collected in six South American countries in a total of 71 different 1 ha forest plots across the Amazon Basin as part of the RAINFOR project. They were analysed for total and exchangeable cations, C, N, pH with various P fractions also determined. Physical properties were also examined and an index of soil physical quality proposed. A diverse range of soils was found. For the western areas near the Andean cordillera and the southern and northern fringes, soils tend to be distributed among the lower pedogenetic levels, while the central and eastern areas of Amazonia have more intensely weathered soils. This gives rise to a large variation of soil chemical and physical properties across the Basin, with soil properties varying predictably along a gradient of pedogenic development. Nutrient pools generally increased slightly in concentration from the youngest to the intermediate aged soils after which a gradual decline was observed with the lowest values found in the most weathered soils. Soil physical properties were strongly correlated with soil fertility, with favourable physical properties occurring in highly weathered and nutrient depleted soils and with the least weathered, more fertile soils having higher incidence of limiting physical properties. Soil phosphorus concentrations varied markedly in accordance with weathering extent and appear to exert an important influence on the nitrogen cycle of Amazon forest soils.

Published
2010

27. Branch xylem density variations across the Amazon Basin

Author

Patiño, S., Lloyd, J., Paiva, R., Baker, T. R, Quesada, C. A, Mercado, L. M, Schmerler, J., Schwarz, M., Santos, A. J. B, Aguilar, A., Czimczik, C. I, Gallo, J., Horna, V., Hoyos, E. J, Jimenez, E. M, Palomino, W., Peacock, J., Peña-Cruz, A., Sarmiento, C., Sota, A., Turriago, J. D, Villanueva, B., Vitzthum, P., Alvarez, E., Arroyo, L., Baraloto, C., Bonal, D., Chave, J., Costa, A. C. L, Herrera, R., Higuchi, N., Killeen, T., Leal, E., Luizão, F., Meir, P., Monteagudo, A., Neil, D., Núñez-Vargas, P., Peñuela, M. C, Pitman, N., Priante Filho, N., Prieto, A., Panfil, S. N, Rudas, A., Salomão, R., Silva, N., Silveira, M., Soares deAlmeida, S., Torres-Lezama, A., Vásquez-Martínez, R., Vieira, I., Malhi, Y., and Phillips, O. L

Subjects
wood specific-gravity, tropical rain-forest, long-term plots, hydraulic architecture, cavitation resistance, carbon gain, functional-significance, water transport, savanna trees, canopy trees
Abstract

Xylem density is a physical property of wood that varies between individuals, species and environments. It reflects the physiological strategies of trees that lead to growth, survival and reproduction. Measurements of branch xylem density, ρx, were made for 1653 trees representing 598 species, sampled from 87 sites across the Amazon basin. Measured values ranged from 218 kg m−3for a Cordia sagotii (Boraginaceae) from Mountagne de Tortue, French Guiana to 1130 kg m−3 for an Aiouea sp. (Lauraceae) from Caxiuana, Central Pará, Brazil. Analysis of variance showed significant differences in average ρx across regions and sampled plots as well as significant differences between families, genera and species. A partitioning of the total variance in the dataset showed that species identity (family, genera and species) accounted for 33% with environment (geographic location and plot) accounting for an additional 26%; the remaining "residual" variance accounted for 41% of the total variance. Variations in plot means, were, however, not only accountable by differences in species composition because xylem density of the most widely distributed species in our dataset varied systematically from plot to plot. Thus, as well as having a genetic component, branch xylem density is a plastic trait that, for any given species, varies according to where the tree is growing in a predictable manner. Within the analysed taxa, exceptions to this general rule seem to be pioneer species belonging for example to the Urticaceae whose branch xylem density is more constrained than most species sampled in this study. These patterns of variation of branch xylem density across Amazonia suggest a large functional diversity amongst Amazonian trees which is not well understood.

Published
2009

49. How Well do Polygenic Risk Scores Identify Men at High Risk for Prostate Cancer? Systematic Review and Meta-Analysis

Author

Siltari, Aino, Lönnerbro, Ragnar, Pang, Karl, Shiranov, Kirill, Asiimwe, Alex, Evans-Axelsson, Susan, Franks, Billy, Kiran, Amit, Murtola, Teemu J., Schalken, Jack, Steinbeisser, Carl, Bjartell, Anders, Auvinen, Anssi, N’Dow, J., Smith, E.J., Shepherd, R., Ribal, M., Mottet, N., Moris, L., Lardas, M., Willemse, P-P., Gandaglia, G., Campi, R., Nicoletti, Rossella, Gacci, M., Briganti, A., Ratti, M.M., Alleva, E., Leardini, L., Sisca, E.S., Bangma, R., Roobol, M., Remmers, S., Tilki, D., Visakorpi, T., Talala, K., Tammela, T., van Hemelrijck, M., Bayer, K., Lejeune, S., Byrne, S., Fialho, L., De Meulder, P. Palaiologou B., Auffray, C., Hijazy, A., Power, S., Kermani, N. Zounemat, van Bochove, K., Kalafati, M., Moinat, M., Voss, E., Horgan, D., Fullwood, L., Holtorf, M., Lancet, D., Bernstein, G., Omar, I., MacLennan, S., Maclennan, S., Tripathee, S., Wirth, M., Froehner, M., Brenner, B., Borkowetz, A., Thomas, C., Horn, F., Reiche, K., Kreux, M., Josefsson, A., Tandefekt, D. Gasi, Hugosson, J., Huisman, H., Schalken, J., Hofmacher, T., Lindgren, P., Andersson, E., Fridhammar, A., Zong, J., Butler-Ransohoff, J-E., Herrera, R., Maass, M., Torremante, P., Voss, M.D., Devecseri, Z., Abbott, T., Dau, C., Papineni, K., Snijder, R., Lambrecht, M., Wolfinger, R., Rogiers, S., Servan, A., Antoni, L., Pacoe, K., Robinson, P., Jaton, B., Bakkard, D., Turunen, H., Kilkku, O., Pohjanjousi, P., Voima, O., Nevalaita, L., Reich, C., Araujo, S., Longden-Chapman, E., Burke, D., Agapow, P., Derkits, S., Licour, M., McCrea, C., Payne, S., Yong, A., Thompson, L., Mare, S. Le, Bussmann, M, and Kotik, D.

Abstract

•Polygenic risk scores (PRS) can be used to predict risk of prostate cancer (PCa).•Based on meta-analysis, the ability of PRS to identify PCa was modest (AUC 0.63).•Combining PRS with clinical variables increased the pooled AUC to 0.74 (0.68-0.81).•PRS accuracy is comparable to PSA or family history.

Published
2023
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