Zobrazeno 1 - 10
of 12 541
pro vyhledávání: '"P. Mistry"'
Autor:
G. Tucker, K. Sztrauch, A. Bevan, Y. Muhamedsalih, S. Hawksbee, P. Shackleton, P. Mistry, B. Whitney, M. Burstow
Publikováno v:
Heliyon, Vol 9, Iss 11, Pp e21112- (2023)
Squat defects are one of the most common rail surface defects. Significant research effort has gone into understand squat defects over the last 10 years which has brought about important developments in the understanding of their initiation mechanism
Externí odkaz:
https://doaj.org/article/7063436fd0b544f4ac89316f13209a52
Autor:
N. van de Donk, M.-V. Mateos, Y.C. Cohen, P. Rodriguez-Otero, B. Paiva, A.D. Cohen, T. Martin, A. Suvannasankha, D. Madduri, C. Corsale, J.M. Schecter, K.C. De Braganca, C.C. Jackson, H. Varsos, W. Deraedt, T. Roccia, P. Mistry, X. Xu, K. Li, E. Zudaire, M. Akram, L. Pacaud, I. Avivi, J. San-Miguel
Publikováno v:
HemaSphere, Vol 7, Iss S2, Pp 25-26 (2023)
Externí odkaz:
https://doaj.org/article/1805ea76a26142d3ac7eb40eb21e5614
Autor:
A. Broijl, J. San-Miguel, K. Suzuki, A. Krishnan, N. van de Donk, G. Cook, A. Jakubowiak, D. Madduri, S. Afifi, A. Stevens, J. Schecter, W. Deraedt, S. Kuppens, P. Mistry, L. Pacaud, M. Boccadoro, F. Gay, R. Mina, L. Rasche, P. Moreau, M. Mateos, H. Einsele, P. Sonneveld
Publikováno v:
HemaSphere, Vol 7, Iss S2, Pp 22-23 (2023)
Externí odkaz:
https://doaj.org/article/2f0e5bd5d69d4a3faada27e2985b3fa5
Autor:
Mistry, Sahaj K., Saini, Sourav, Gupta, Aashray, Gupta, Aayush, Rai, Sunny, Jakhetiya, Vinit, Baid, Ujjwal, Guntuku, Sharath Chandra
Brain tumor segmentation plays a crucial role in computer-aided diagnosis. This study introduces a novel segmentation algorithm utilizing a modified nnU-Net architecture. Within the nnU-Net architecture's encoder section, we enhance conventional conv
Externí odkaz:
http://arxiv.org/abs/2409.13229
Autor:
Iyer, Kartheik G., Yunus, Mikaeel, O'Neill, Charles, Ye, Christine, Hyk, Alina, McCormick, Kiera, Ciuca, Ioana, Wu, John F., Accomazzi, Alberto, Astarita, Simone, Chakrabarty, Rishabh, Cranney, Jesse, Field, Anjalie, Ghosal, Tirthankar, Ginolfi, Michele, Huertas-Company, Marc, Jablonska, Maja, Kruk, Sandor, Liu, Huiling, Marchidan, Gabriel, Mistry, Rohit, Naiman, J. P., Peek, J. E. G., Polimera, Mugdha, Rodriguez, Sergio J., Schawinski, Kevin, Sharma, Sanjib, Smith, Michael J., Ting, Yuan-Sen, Walmsley, Mike
The exponential growth of astronomical literature poses significant challenges for researchers navigating and synthesizing general insights or even domain-specific knowledge. We present Pathfinder, a machine learning framework designed to enable lite
Externí odkaz:
http://arxiv.org/abs/2408.01556
Autor:
S. Zweegman, M. Agha, A.D. Cohen, Y.C. Cohen, S. Anguille, T. Kerre, W. Roeloffzen, D. Madduri, J.M. Schecter, K.C. De Braganca, C.C. Jackson, H. Varsos, P. Mistry, T. Roccia, X. Xu, K. Li, E. Zudaire, C. Corsale, M. Akram, D. Geng, L. Pacaud, P. Sonneveld, N. van de Donk
Publikováno v:
HemaSphere, Vol 7, Iss S2, Pp 8-8 (2023)
Externí odkaz:
https://doaj.org/article/3701c71d179848efbca0b34625e175c6
Classical models for predicting current flow in excitable cells such as axons, originally proposed by Hodgkin and Huxley, rely on empirical voltage-gating parameters that quantify ion transport across sodium and potassium ion channels. We propose a p
Externí odkaz:
http://arxiv.org/abs/2407.09474
Autor:
MicroBooNE collaboration, Abratenko, P., Alterkait, O., Aldana, D. Andrade, Arellano, L., Asaadi, J., Ashkenazi, A., Balasubramanian, S., Baller, B., Barnard, A., Barr, G., Barrow, D., Barrow, J., Basque, V., Bateman, J., Rodrigues, O. Benevides, Berkman, S., Bhanderi, A., Bhat, A., Bhattacharya, M., Bishai, M., Blake, A., Bogart, B., Bolton, T., Book, J. Y., Brunetti, M. B., Camilleri, L., Cao, Y., Caratelli, D., Cavanna, F., Cerati, G., Chappell, A., Chen, Y., Conrad, J. M., Convery, M., Cooper-Troendle, L., Crespo-Anadon, J. I., Cross, R., Del Tutto, M., Dennis, S. R., Detje, P., Diurba, R., Djurcic, Z., Dorrill, R., Duffy, K., Dytman, S., Eberly, B., Englezos, P., Ereditato, A., Evans, J. J., Fine, R., Fleming, B. T., Foreman, W., Franco, D., Furmanski, A. P., Gao, F., Garcia-Gamez, D., Gardiner, S., Ge, G., Gollapinni, S., Gramellini, E., Green, P., Greenlee, H., Gu, L., Gu, W., Guenette, R., Guzowski, P., Hagaman, L., Handley, M. D., Hen, O., Hilgenberg, C., Horton-Smith, G. A., Imani, Z., Irwin, B., Ismail, M. S., James, C., Ji, X., Jo, J. H., Johnson, R. A., Jwa, Y. J., Kalra, D., Kamp, N., Karagiorgi, G., Ketchum, W., Kirby, M., Kobilarcik, T., Kreslo, I., Lane, N., Li, J. -Y., Li, Y., Lin, K., Littlejohn, B. R., Liu, H., Louis, W. C., Luo, X., Mariani, C., Marsden, D., Marshall, J., Martinez, N., Caicedo, D. A. Martinez, Martynenko, S., Mastbaum, A., Mawby, I., McConkey, N., Meddage, V., Mendez, J., Micallef, J., Miller, K., Mistry, K., Mohayai, T., Mogan, A., Mooney, M., Moor, A. F., Moore, C. D., Lepin, L. Mora, Moudgalya, M. M., Babu, S. Mulleria, Naples, D., Navrer-Agasson, A., Nayak, N., Nebot-Guinot, M., Nguyen, C., Nowak, J., Oza, N., Palamara, O., Pallat, N., Paolone, V., Papadopoulou, A., Papavassiliou, V., Parkinson, H., Pate, S. F., Patel, N., Pavlovic, Z., Piasetzky, E., Pletcher, K., Pophale, I., Qian, X., Raaf, J. L., Radeka, V., Rafique, A., Reggiani-Guzzo, M., Ren, L., Rochester, L., Rondon, J. Rodriguez, Rosenberg, M., Ross-Lonergan, M., Safa, I., Schmitz, D. W., Schukraft, A., Seligman, W., Shaevitz, M. H., Sharankova, R., Shi, J., Snider, E. L., Soderberg, M., Soldner-Rembold, S., Spitz, J., Stancari, M., John, J. St., Strauss, T., Szelc, A. M., Tang, W., Taniuchi, N., Terao, K., Thorpe, C., Torbunov, D., Totani, D., Toups, M., Trettin, A., Tsai, Y. -T., Tyler, J., Uchida, M. A., Usher, T., Viren, B., Wang, J., Weber, M., Wei, H., White, A. J., Wolbers, S., Wongjirad, T., Wospakrik, M., Wresilo, K., Wu, W., Yandel, E., Yang, T., Yates, L. E., Yu, H. W., Zeller, G. P., Zennamo, J., Zhang, C.
A significant challenge in measurements of neutrino oscillations is reconstructing the incoming neutrino energies. While modern fully-active tracking calorimeters such as liquid argon time projection chambers in principle allow the measurement of all
Externí odkaz:
http://arxiv.org/abs/2406.10583
Autor:
MicroBooNE collaboration, Abratenko, P., Alterkait, O., Aldana, D. Andrade, Arellano, L., Asaadi, J., Ashkenazi, A., Balasubramanian, S., Baller, B., Barnard, A., Barr, G., Barrow, D., Barrow, J., Basque, V., Bateman, J., Rodrigues, O. Benevides, Berkman, S., Bhanderi, A., Bhat, A., Bhattacharya, M., Bishai, M., Blake, A., Bogart, B., Bolton, T., Book, J. Y., Brunetti, M. B., Camilleri, L., Cao, Y., Caratelli, D., Cavanna, F., Cerati, G., Chappell, A., Chen, Y., Conrad, J. M., Convery, M., Cooper-Troendle, L., Crespo-Anadon, J. I., Cross, R., Del Tutto, M., Dennis, S. R., Detje, P., Diurba, R., Djurcic, Z., Dorrill, R., Duffy, K., Dytman, S., Eberly, B., Englezos, P., Ereditato, A., Evans, J. J., Fine, R., Fleming, B. T., Foreman, W., Franco, D., Furmanski, A. P., Gao, F., Garcia-Gamez, D., Gardiner, S., Ge, G., Gollapinni, S., Gramellini, E., Green, P., Greenlee, H., Gu, L., Gu, W., Guenette, R., Guzowski, P., Hagaman, L., Hen, O., Hilgenberg, C., Horton-Smith, G. A., Imani, Z., Irwin, B., Ismail, M. S., James, C., Ji, X., Jo, J. H., Johnson, R. A., Jwa, Y. J., Kalra, D., Kamp, N., Karagiorgi, G., Ketchum, W., Kirby, M., Kobilarcik, T., Kreslo, I., Lane, N., Lepetic, I., Li, J. -Y., Li, Y., Lin, K., Littlejohn, B. R., Liu, H., Louis, W. C., Luo, X., Mariani, C., Marsden, D., Marshall, J., Martinez, N., Caicedo, D. A. Martinez, Martynenko, S., Mastbaum, A., Mawby, I., McConkey, N., Meddage, V., Mendez, J., Micallef, J., Miller, K., Mistry, K., Mohayai, T., Mogan, A., Mooney, M., Moor, A. F., Moore, C. D., Lepin, L. Mora, Moudgalya, M. M., Babu, S. Mulleria, Naples, D., Navrer-Agasson, A., Nayak, N., Nebot-Guinot, M., Nowak, J., Oza, N., Palamara, O., Pallat, N., Paolone, V., Papadopoulou, A., Papavassiliou, V., Parkinson, H., Pate, S. F., Patel, N., Pavlovic, Z., Piasetzky, E., Pletcher, K., Pophale, I., Qian, X., Raaf, J. L., Radeka, V., Rafique, A., Reggiani-Guzzo, M., Ren, L., Rochester, L., Rondon, J. Rodriguez, Rosenberg, M., Ross-Lonergan, M., Safa, I., Scanavini, G., Schmitz, D. W., Schukraft, A., Seligman, W., Shaevitz, M. H., Sharankova, R., Shi, J., Snider, E. L., Soderberg, M., Soldner-Rembold, S., Spitz, J., Stancari, M., John, J. St., Strauss, T., Szelc, A. M., Tang, W., Taniuchi, N., Terao, K., Thorpe, C., Torbunov, D., Totani, D., Toups, M., Trettin, A., Tsai, Y. -T., Tyler, J., Uchida, M. A., Usher, T., Viren, B., Weber, M., Wei, H., White, A. J., Wolbers, S., Wongjirad, T., Wospakrik, M., Wresilo, K., Wu, W., Yandel, E., Yang, T., Yates, L. E., Yu, H. W., Zeller, G. P., Zennamo, J., Zhang, C.
We present a deep learning-based method for estimating the neutrino energy of charged-current neutrino-argon interactions. We employ a recurrent neural network (RNN) architecture for neutrino energy estimation in the MicroBooNE experiment, utilizing
Externí odkaz:
http://arxiv.org/abs/2406.10123
Autor:
Contreras, T., Palmeiro, B., Almazán, H., Para, A., Martínez-Lema, G., Guenette, R., Adams, C., Álvarez, V., Aparicio, B., Aranburu, A. I., Arazi, L., Arnquist, I. J., Auria-Luna, F., Ayet, S., Azevedo, C. D. R., Bailey, K., Ballester, F., del Barrio-Torregrosa, M., Bayo, A., Benlloch-Rodríguez, J. M., Borges, F. I. G. M., Brodolin, A., Byrnes, N., Cárcel, S., Castillo, A., Cebrián, S., Church, E., Cid, L., Conde, C. A. N., Cossío, F. P., Dey, E., Díaz, G., Dickel, T., Echevarria, C., Elorza, M., Escada, J., Esteve, R., Felkai, R., Fernandes, L. M. P., Ferrario, P., Ferreira, A. L., Foss, F. W., Freixa, Z., García-Barrena, J., Gómez-Cadenas, J. J., González, R., Grocott, J. W. R., Hauptman, J., Henriques, C. A. O., Morata, J. A. Hernando, Herrero-Gómez, P., Herrero, V., Carrete, C. Hervés, Ifergan, Y., Jones, B. J. P., Kellerer, F., Larizgoitia, L., Larumbe, A., Lebrun, P., Lopez, F., López-March, N., Madigan, R., Mano, R. D. P., Marques, A. P., Martín-Albo, J., Martínez-Vara, M., Miller, R. L., Mistry, K., Molina-Canteras, J., Monrabal, F., Monteiro, C. M. B., Mora, F. J., Navarro, K. E., Novella, P., Nuñez, A., Nygren, D. R., Oblak, E., Palacio, J., Parmaksiz, I., Pazos, A., Pelegrin, J., Maneiro, M. Pérez, Querol, M., Redwine, A. B., Renner, J., Rivilla, I., Rogero, C., Rogers, L., Romeo, B., Romo-Luque, C., Santos, F. P., Santos, J. M. F. dos, Seemann, M., Shomroni, I., Silva, P. A. O. C., Simón, A., Soleti, S. R., Sorel, M., Soto-Oton, J., Teixeira, J. M. R., Teruel-Pardo, S., Toledo, J. F., Tonnelé, C., Torrent, J., Trettin, A., Usón, A., Valle, P. R. G., Veloso, J. F. C. A., Waiton, J., Yubero-Navarro, A.
The NEXT-White detector, a high-pressure gaseous xenon time projection chamber, demonstrated the excellence of this technology for future neutrinoless double beta decay searches using photomultiplier tubes (PMTs) to measure energy and silicon photomu
Externí odkaz:
http://arxiv.org/abs/2405.20427