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6,820 results on '"Bench, A."'

1. Hippocrates: An Open-Source Framework for Advancing Large Language Models in Healthcare

Author: Acikgoz, Emre Can, İnce, Osman Batur, Bench, Rayene, Boz, Arda Anıl, Kesen, İlker, Erdem, Aykut, and Erdem, Erkut
Subjects: Computer Science - Machine Learning, Computer Science - Artificial Intelligence, Computer Science - Computation and Language
Abstract: The integration of Large Language Models (LLMs) into healthcare promises to transform medical diagnostics, research, and patient care. Yet, the progression of medical LLMs faces obstacles such as complex training requirements, rigorous evaluation demands, and the dominance of proprietary models that restrict academic exploration. Transparent, comprehensive access to LLM resources is essential for advancing the field, fostering reproducibility, and encouraging innovation in healthcare AI. We present Hippocrates, an open-source LLM framework specifically developed for the medical domain. In stark contrast to previous efforts, it offers unrestricted access to its training datasets, codebase, checkpoints, and evaluation protocols. This open approach is designed to stimulate collaborative research, allowing the community to build upon, refine, and rigorously evaluate medical LLMs within a transparent ecosystem. Also, we introduce Hippo, a family of 7B models tailored for the medical domain, fine-tuned from Mistral and LLaMA2 through continual pre-training, instruction tuning, and reinforcement learning from human and AI feedback. Our models outperform existing open medical LLMs models by a large-margin, even surpassing models with 70B parameters. Through Hippocrates, we aspire to unlock the full potential of LLMs not just to advance medical knowledge and patient care but also to democratize the benefits of AI research in healthcare, making them available across the globe.
Published: 2024

2. Intermediate factors and precedential constraint

Author: Bench-Capon, Trevor
Published: 2024
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3. Limitations of effective medium models for tissue phantoms in the THz frequency range

Author: Sonal Saxena, Ciaran Bench, Diksha Garg, Patric Boardman, Michal Mrnka, Harry Penketh, Nicholas Stone, and Euan Hendry
Subjects: Gelatine hydrogel, THz permittivity, Biological application of THz, Bound water, Raman spectra, Medicine, Science
Abstract: Abstract The absorption of terahertz (THz) radiation by water molecules facilitates its application to several biomedical applications such as cancer detection. Therefore, it is critical for the THz technologies to be characterised with water content in a sample. In this paper, we analyse gelatine phantoms in the THz frequency range, with continuously varying hydration levels as they dry over time. Water molecules in close proximity to the protein molecule, termed ‘bound water’, feature properties different from the ‘free water’ molecules at larger distances. We find that a common model for predicting electromagnetic properties of phantoms and tissue samples, which assumes that only the free water varies with hydration while the bound water remains constant, does not agree well with measured results. To gain insight into this behaviour, we simultaneously measured the phantom in Raman spectroscopy, which shows a continuously varying concentration of bound water with hydration level. It follows from this investigation, that the permittivity contributions of neither the biomolecules nor water are expected to be linear with water density. This means that the often used, simple effective medium model will not be accurate for many biological tissues or phantoms.
Published: 2024
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4. Oral Health Screening by MassHealth Accountable Care Organizations: An opportunity for equity-focused interventions

Author: Ahern, John, Sullivan, Laura, Tam, Caleb, Bench, Kara Keating, and Cook, Benjamin Le
Subjects: Oral health -- Evaluation, Medical screening -- Methods, Health
Abstract: Establishing reliable access to dental services for publicly insured patients is an important part of achieving equitable oral health care. In 2023, an oral health screening requirement was added to the MassHealth Accountable Care Organization contract, which has the capacity to affect over 1.3 million members enrolled in MassHealth Accountable Care Organizations throughout the state. The goal of the oral health screening requirement is to identify MassHealth-insured patients who do not have reliable access to dental services and to provide them with resources to establish a dental home with a MassHealth-participating dentist. Primary care providers were surveyed, and results indicate a need for a care coordination mechanism to assist MassHealthinsured patients with establishing a dental home, in addition to an option to request telehealth-enabled and/ or urgent dental appointments. This report describes the oral health screening program at one MassHealth Accountable Care Organization and presents some of the data collected during the first year of its implementation, in addition to discussing how this data is being used to guide equity-focused interventions with the potential for policy implications. Keywords access to care, oral health services, dental home, teledentistry, oral health equity, INTRODUCTION The 2021 National Institutes of Health (NIH) report 'Oral Health in America: Advances and Challenges' described promising advancements in the delivery of oral health care, emphasizing the importance of [...]
Published: 2024

5. Unsupervised denoising of Raman spectra with cycle-consistent generative adversarial networks

Author: Bench, Ciaran, Bergholt, Mads S., and al-Badri, Mohamed Ali
Subjects: Physics - Medical Physics
Abstract: Raman spectroscopy can provide insight into the molecular composition of cells and tissue. Consequently, it can be used as a powerful diagnostic tool, e.g. to help identify changes in molecular contents with the onset of disease. But robust information about sample composition may only be recovered with long acquisition times that produce spectra with a high signal to noise ratio. This acts as a bottleneck on experimental workflows, driving a desire for effective spectral denoising techniques. Denoising algorithms based on deep neural networks have been shown superior to `classical' approaches, but require the use of bespoke paired datasets (i.e. spectra acquired from the same set of samples acquired with both long and short acquisition times) that require significant effort to generate. Here, we propose an unsupervised denoising approach that does not require paired data. We cast the problem of spectral denoising as a style transfer task and show how cycle-consistent generative adversarial networks can provide significant performance benefits over classical denoising techniques., Comment: Added HSI evaluation, and changed formatting of some figures
Published: 2023

6. Updated T2K measurements of muon neutrino and antineutrino disappearance using 3.6 $\times$ 10$^{21}$ protons on target

Author: Abe, K., Akhlaq, N., Akutsu, R., Alarakia-Charles, H., Ali, A., Hakim, Y. I. Alj, Monsalve, S. Alonso, Alt, C., Andreopoulos, C., Antonova, M., Aoki, S., Arihara, T., Asada, Y., Ashida, Y., Atkin, E. T., Barbi, M., Barker, G. J., Barr, G., Barrow, D., Batkiewicz-Kwasniak, M., Bench, F., Berardi, V., Berns, L., Bhadra, S., Blanchet, A., Blondel, A., Bolognesi, S., Bonus, T., Bordoni, S., Boyd, S. B., Bravar, A., Bronner, C., Bron, S., Bubak, A., Avanzini, M. Buizza, Caballero, J. A., Calabria, N. F., Cao, S., Carabadjac, D., Carter, A. J., Cartwright, S. L., Casado, M. P., Catanesi, M. G., Cervera, A., Chakrani, J., Cherdack, D., Chong, P. S., Christodoulou, G., Chvirova, A., Cicerchia, M., Coleman, J., Collazuol, G., Cook, L., Cudd, A., Dalmazzone, C., Daret, T., Dasgupta, P., Davydov, Yu. I., De Roeck, A., De Rosa, G., Dealtry, T., Delogu, C. C., Densham, C., Dergacheva, A., Di Lodovico, F., Dolan, S., Douqa, D., Doyle, T. A., Drapier, O., Dumarchez, J., Dunne, P., Dygnarowicz, K., Eguchi, A., Emery-Schrenk, S., Erofeev, G., Ershova, A., Eurin, G., Fedorova, D., Fedotov, S., Feltre, M., Finch, A. J., Aguirre, G. A. Fiorentini, Fiorillo, G., Fitton, M. D., Patiño, J. M. Franco, Friend, M., Fujii, Y., Fukuda, Y., Furui, Y., Fusshoeller, K., Giannessi, L., Giganti, C., Glagolev, V., Gonin, M., Rosa, J. González, Goodman, E. A. G., Gorin, A., Grassi, M., Guigue, M., Hadley, D. R., Haigh, J. T., Hamacher-Baumann, P., Harris, D. A., Hartz, M., Hasegawa, T., Hassani, S., Hastings, N. C., Hayato, Y., Henaff, D., Hiramoto, A., Hogan, M., Holeczek, J., Holin, A., Holvey, T., Van, N. T. Hong, Honjo, T., Iacob, F., Ichikawa, A. K., Ikeda, M., Ishida, T., Ishitsuka, M., Israel, H. T., Iwamoto, K., Izmaylov, A., Izumi, N., Jakkapu, M., Jamieson, B., Jenkins, S. J., Jesús-Valls, C., Jiang, J. J., Ji, J. Y., Jonsson, P., Joshi, S., Jung, C. K., Jurj, P. B., Kabirnezhad, M., Kaboth, A. C., Kajita, T., Kakuno, H., Kameda, J., Kasetti, S. P., Kataoka, Y., Katayama, Y., Katori, T., Kawaue, M., Kearns, E., Khabibullin, M., Khotjantsev, A., Kikawa, T., Kikutani, H., King, S., Kiseeva, V., Kisiel, J., Kobata, T., Kobayashi, H., Kobayashi, T., Koch, L., Kodama, S., Konaka, A., Kormos, L. L., Koshio, Y., Kostin, A., Koto, T., Kowalik, K., Kudenko, Y., Kudo, Y., Kuribayashi, S., Kurjata, R., Kutter, T., Kuze, M., La Commara, M., Labarga, L., Lachner, K., Lagoda, J., Lakshmi, S. M., James, M. Lamers, Lamoureux, M., Langella, A., Laporte, J. -F., Last, D., Latham, N., Laveder, M., Lavitola, L., Lawe, M., Lee, Y., Lin, C., Lin, S. -K., Litchfield, R. P., Liu, S. L., Li, W., Longhin, A., Long, K. R., Moreno, A. Lopez, Ludovici, L., Lu, X., Lux, T., Machado, L. N., Magaletti, L., Mahn, K., Malek, M., Mandal, M., Manly, S., Marino, A. D., Marti-Magro, L., Martin, D. G. R., Martini, M., Martin, J. F., Maruyama, T., Matsubara, T., Matveev, V., Mauger, C., Mavrokoridis, K., Mazzucato, E., McCauley, N., McElwee, J., McFarland, K. S., McGrew, C., McKean, J., Mefodiev, A., Megias, G. D., Mehta, P., Mellet, L., Metelko, C., Mezzetto, M., Miller, E., Minamino, A., Mineev, O., Mine, S., Miura, M., Bueno, L. Molina, Moriyama, S., Morrison, P., Mueller, Th. A., Munford, D., Munteanu, L., Nagai, K., Nagai, Y., Nakadaira, T., Nakagiri, K., Nakahata, M., Nakajima, Y., Nakamura, A., Nakamura, H., Nakamura, K., Nakamura, K. D., Nakano, Y., Nakayama, S., Nakaya, T., Nakayoshi, K., Naseby, C. E. R., Ngoc, T. V., Nguyen, V. Q., Niewczas, K., Nishimori, S., Nishimura, Y., Nishizaki, K., Nosek, T., Nova, F., Novella, P., Nugent, J. C., O'Keeffe, H. M., O'Sullivan, L., Odagawa, T., Ogawa, T., Okada, R., Okinaga, W., Okumura, K., Okusawa, T., Ospina, N., Osu, L., Owen, R. A., Oyama, Y., Palladino, V., Paolone, V., Pari, M., Parlone, J., Parsa, S., Pasternak, J., Pavin, M., Payne, D., Penn, G. C., Pershey, D., Pickering, L., Pidcott, C., Pintaudi, G., Pistillo, C., Popov, B., Yrey, A. J. Portocarrero, Porwit, K., Posiadala-Zezula, M., Prabhu, Y. S., Pupilli, F., Quilain, B., Radermacher, T., Radicioni, E., Radics, B., Ramírez, M. A., Ratoff, P. N., Reh, M., Riccio, C., Rondio, E., Roth, S., Roy, N., Rubbia, A., Ruggeri, A. C., Ruggles, C. A., Rychter, A., Sakashita, K., Sánchez, F., Santucci, G., Schefke, T., Schloesser, C. M., Scholberg, K., Scott, M., Seiya, Y., Sekiguchi, T., Sekiya, H., Sgalaberna, D., Shaikhiev, A., Shaker, F., Shiozawa, M., Shorrock, W., Shvartsman, A., Skrobova, N., Skwarczynski, K., Smyczek, D., Smy, M., Sobczyk, J. T., Sobel, H., Soler, F. J. P., Sonoda, Y., Speers, A. J., Spina, R., Suslov, I. A., Suvorov, S., Suzuki, A., Suzuki, S. Y., Suzuki, Y., Sztuc, A. A., Tada, M., Tairafune, S., Takayasu, S., Takeda, A., Takeuchi, Y., Takifuji, K., Tanaka, H. K., Tanigawa, H., Tanihara, Y., Tani, M., Teklu, A., Tereshchenko, V. V., Teshima, N., Thamm, N., Thompson, L. F., Toki, W., Touramanis, C., Towstego, T., Tsui, K. M., Tsukamoto, T., Tzanov, M., Uchida, Y., Vagins, M., Vargas, D., Varghese, M., Vasseur, G., Vilela, C., Villa, E., Vinning, W. G. S., Virginet, U., Vladisavljevic, T., Wachala, T., Wakabayashi, D., Walsh, J. G., Wang, Y., Wan, L., Wark, D., Wascko, M. O., Weber, A., Wendell, R., Wilking, M. J., Wilkinson, C., Wilson, J. R., Wood, K., Wret, C., Xia, J., Xu, Y. -h., Yamamoto, K., Yamamoto, T., Yanagisawa, C., Yang, G., Yano, T., Yasutome, K., Yershov, N., Yevarouskaya, U., Yokoyama, M., Yoshimoto, Y., Yoshimura, N., Yu, M., Zaki, R., Zalewska, A., Zalipska, J., Zaremba, K., Zarnecki, G., Zhao, X., Zhu, T., Ziembicki, M., Zimmerman, E. D., Zito, M., and Zsoldos, S.
Subjects: High Energy Physics - Experiment
Abstract: Muon neutrino and antineutrino disappearance probabilities are identical in the standard three-flavor neutrino oscillation framework, but CPT violation and non-standard interactions can violate this symmetry. In this work we report the measurements of $\sin^{2} \theta_{23}$ and $\Delta m_{32}^2$ independently for neutrinos and antineutrinos. The aforementioned symmetry violation would manifest as an inconsistency in the neutrino and antineutrino oscillation parameters. The analysis discussed here uses a total of 1.97$\times$10$^{21}$ and 1.63$\times$10$^{21}$ protons on target taken with a neutrino and antineutrino beam respectively, and benefits from improved flux and cross-section models, new near detector samples and more than double the data reducing the overall uncertainty of the result. No significant deviation is observed, consistent with the standard neutrino oscillation picture.
Published: 2023

7. Enhancing synthetic training data for quantitative photoacoustic tomography with generative deep learning

Author: Bench, Ciaran and Cox, Ben T.
Subjects: Physics - Medical Physics
Abstract: Multiwavelength photoacoustic images encode information about a tissue's optical absorption distribution. This can be used to estimate its blood oxygen saturation distribution (sO2), an important physiological indicator of tissue health and pathology. However the wavelength dependence of the light fluence distribution complicates the recovery of accurate estimates, in particular, preventing the use of a straightforward spectroscopic inversion. Deep learning approaches have been shown effective at producing accurate estimates of sO2 from simulated data. Though, the translation of generic supervised learning approaches to real tissues is prevented by the lack of real `paired' training data (multiwavelength PA images of in vivo tissues with their corresponding sO2 distributions). Here, we discuss i) why networks trained on images simulated using conventional means are unlikely to generalise their performance on real tissues, and ii) the prospects of using two generative adversarial network based strategies to improve the generalisability of sO2-estimating networks trained on synthetic data: a) CycleGAN-driven unsupervised domain adaptation of conventionally simulated images, and b) the generation of paired training data using AmbientGANs.
Published: 2023

8. Limitations of effective medium models for tissue phantoms in the THz frequency range

Author: Saxena, Sonal, Bench, Ciaran, Garg, Diksha, Boardman, Patric, Mrnka, Michal, Penketh, Harry, Stone, Nicholas, and Hendry, Euan
Published: 2024
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9. Understanding the process of adolescent assent for voluntary male medical circumcision in Zimbabwe: findings from a cross-sectional study

Author: West, Rebecca L., Sharma, Sunny, Hurst, Nisa, Bench, Will, Nhando, Nehemiah, Maponga, Brian, Bullock, Lucy, Egualeonan, Darius, Reast, Jemma, Xaba, Sinokuthemba, Hatzold, Karin, and Gumede-Moyo, Sehlulekile
Published: 2024
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10. First measurement of muon neutrino charged-current interactions on hydrocarbon without pions in the final state using multiple detectors with correlated energy spectra at T2K

Author: Abe, K., Akhlaq, N., Akutsu, R., Alarakia-Charles, H., Ali, A., Hakim, Y. I. Alj, Monsalve, S. Alonso, Alt, C., Andreopoulos, C., Antonova, M., Aoki, S., Arihara, T., Asada, Y., Ashida, Y., Atkin, E. T., Barbi, M., Barker, G. J., Barr, G., Barrow, D., Batkiewicz-Kwasniak, M., Bench, F., Berardi, V., Berns, L., Bhadra, S., Blanchet, A., Blondel, A., Bolognesi, S., Bonus, T., Bordoni, S., Boyd, S. B., Bravar, A., Bronner, C., Bron, S., Bubak, A., Avanzini, M. Buizza, Caballero, J. A., Calabria, N. F., Cao, S., Carabadjac, D., Carter, A. J., Cartwright, S. L., Casado, M. P., Catanesi, M. G., Cervera, A., Chakrani, J., Cherdack, D., Chong, P. S., Christodoulou, G., Chvirova, A., Cicerchia, M., Coleman, J., Collazuol, G., Cook, L., Cudd, A., Dalmazzone, C., Daret, T., Dasgupta, P., Davydov, Yu. I., De Roeck, A., De Rosa, G., Dealtry, T., Delogu, C. C., Densham, C., Dergacheva, A., Di Lodovico, F., Dolan, S., Douqa, D., Doyle, T. A., Drapier, O., Dumarchez, J., Dunne, P., Dygnarowicz, K., Eguchi, A., Emery-Schrenk, S., Erofeev, G., Ershova, A., Eurin, G., Fedorova, D., Fedotov, S., Feltre, M., Finch, A. J., Aguirre, G. A. Fiorentini, Fiorillo, G., Fitton, M. D., Patiño, J. M. Franco, Friend, M., Fujii, Y., Fukuda, Y., Furui, Y., Fusshoeller, K., Giannessi, L., Giganti, C., Glagolev, V., Gonin, M., Rosa, J. González, Goodman, E. A. G., Gorin, A., Grassi, M., Guigue, M., Hadley, D. R., Haigh, J. T., Hamacher-Baumann, P., Harris, D. A., Hartz, M., Hasegawa, T., Hassani, S., Hastings, N. C., Hayato, Y., Henaff, D., Hiramoto, A., Hogan, M., Holeczek, J., Holin, A., Holvey, T., Van, N. T. Hong, Honjo, T., Iacob, F., Ichikawa, A. K., Ikeda, M., Ishida, T., Ishitsuka, M., Israel, H. T., Izmaylov, A., Izumi, N., Jakkapu, M., Jamieson, B., Jenkins, S. J., Jesús-Valls, C., Jiang, J. J., Ji, J. Y., Jonsson, P., Joshi, S., Jung, C. K., Jurj, P. B., Kabirnezhad, M., Kaboth, A. C., Kajita, T., Kakuno, H., Kameda, J., Kasetti, S. P., Kataoka, Y., Katori, T., Kawaue, M., Kearns, E., Khabibullin, M., Khotjantsev, A., Kikawa, T., King, S., Kiseeva, V., Kisiel, J., Kobata, T., Kobayashi, H., Kobayashi, T., Koch, L., Kodama, S., Konaka, A., Kormos, L. L., Koshio, Y., Kostin, A., Koto, T., Kowalik, K., Kudenko, Y., Kudo, Y., Kuribayashi, S., Kurjata, R., Kutter, T., Kuze, M., La Commara, M., Labarga, L., Lachner, K., Lagoda, J., Lakshmi, S. M., James, M. Lamers, Lamoureux, M., Langella, A., Laporte, J. -F., Last, D., Latham, N., Laveder, M., Lavitola, L., Lawe, M., Lee, Y., Lin, C., Lin, S. -K., Litchfield, R. P., Liu, S. L., Li, W., Longhin, A., Long, K. R., Moreno, A. Lopez, Ludovici, L., Lu, X., Lux, T., Machado, L. N., Magaletti, L., Mahn, K., Malek, M., Mandal, M., Manly, S., Marino, A. D., Marti-Magro, L., Martin, D. G. R., Martini, M., Martin, J. F., Maruyama, T., Matsubara, T., Matveev, V., Mauger, C., Mavrokoridis, K., Mazzucato, E., McCauley, N., McElwee, J., McFarland, K. S., McGrew, C., McKean, J., Mefodiev, A., Megias, G. D., Mehta, P., Mellet, L., Metelko, C., Mezzetto, M., Miller, E., Minamino, A., Mineev, O., Mine, S., Miura, M., Bueno, L. Molina, Moriyama, S., Morrison, P., Mueller, Th. A., Munford, D., Munteanu, L., Nagai, K., Nagai, Y., Nakadaira, T., Nakagiri, K., Nakahata, M., Nakajima, Y., Nakamura, A., Nakamura, H., Nakamura, K., Nakamura, K. D., Nakano, Y., Nakayama, S., Nakaya, T., Nakayoshi, K., Naseby, C. E. R., Ngoc, T. V., Nguyen, V. Q., Niewczas, K., Nishimori, S., Nishimura, Y., Nishizaki, K., Nosek, T., Nova, F., Novella, P., Nugent, J. C., O'Keeffe, H. M., O'Sullivan, L., Odagawa, T., Ogawa, T., Okinaga, W., Okumura, K., Okusawa, T., Ospina, N., Osu, L., Owen, R. A., Oyama, Y., Palladino, V., Paolone, V., Pari, M., Parlone, J., Parsa, S., Pasternak, J., Pavin, M., Payne, D., Penn, G. C., Pershey, D., Pickering, L., Pidcott, C., Pintaudi, G., Pistillo, C., Popov, B., Yrey, A. J. Portocarrero, Porwit, K., Posiadala-Zezula, M., Prabhu, Y. S., Pupilli, F., Quilain, B., Radermacher, T., Radicioni, E., Radics, B., Ramírez, M. A., Ratoff, P. N., Reh, M., Riccio, C., Rondio, E., Roth, S., Roy, N., Rubbia, A., Ruggeri, A. C., Ruggles, C. A., Rychter, A., Sakashita, K., Sánchez, F., Santucci, G., Schefke, T., Schloesser, C. M., Scholberg, K., Scott, M., Seiya, Y., Sekiguchi, T., Sekiya, H., Sgalaberna, D., Shaikhiev, A., Shaker, F., Shiozawa, M., Shorrock, W., Shvartsman, A., Skrobova, N., Skwarczynski, K., Smyczek, D., Smy, M., Sobczyk, J. T., Sobel, H., Soler, F. J. P., Sonoda, Y., Speers, A. J., Spina, R., Suslov, I. A., Suvorov, S., Suzuki, A., Suzuki, S. Y., Suzuki, Y., Sztuc, A. A., Tada, M., Tairafune, S., Takayasu, S., Takeda, A., Takeuchi, Y., Takifuji, K., Tanaka, H. K., Tanigawa, H., Tani, M., Teklu, A., Tereshchenko, V. V., Teshima, N., Thamm, N., Thompson, L. F., Toki, W., Touramanis, C., Towstego, T., Tsui, K. M., Tsukamoto, T., Tzanov, M., Uchida, Y., Vagins, M., Vargas, D., Varghese, M., Vasseur, G., Vilela, C., Villa, E., Vinning, W. G. S., Virginet, U., Vladisavljevic, T., Wachala, T., Wakabayashi, D., Walsh, J. G., Wang, Y., Wan, L., Wark, D., Wascko, M. O., Weber, A., Wendell, R., Wilking, M. J., Wilkinson, C., Wilson, J. R., Wood, K., Wret, C., Xia, J., Xu, Y. -h., Yamamoto, K., Yamamoto, T., Yanagisawa, C., Yang, G., Yano, T., Yasutome, K., Yershov, N., Yevarouskaya, U., Yokoyama, M., Yoshimoto, Y., Yoshimura, N., Yu, M., Zaki, R., Zalewska, A., Zalipska, J., Zaremba, K., Zarnecki, G., Zhao, X., Zhu, T., Ziembicki, M., Zimmerman, E. D., Zito, M., and Zsoldos, S.
Subjects: High Energy Physics - Experiment
Abstract: This paper reports the first measurement of muon neutrino charged-current interactions without pions in the final state using multiple detectors with correlated energy spectra at T2K. The data was collected on hydrocarbon targets using the off-axis T2K near detector (ND280) and the on-axis T2K near detector (INGRID) with neutrino energy spectra peaked at 0.6 GeV and 1.1 GeV respectively. The correlated neutrino flux presents an opportunity to reduce the impact of the flux uncertainty and to study the energy dependence of neutrino interactions. The extracted double-differential cross sections are compared to several Monte Carlo neutrino-nucleus interaction event generators showing the agreement between both detectors individually and with the correlated result., Comment: Updated discussion in Sec. V-A; Updated author list
Published: 2023
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11. Measurements of neutrino oscillation parameters from the T2K experiment using $3.6\times10^{21}$ protons on target

Author: The T2K Collaboration, Abe, K., Akhlaq, N., Akutsu, R., Ali, A., Monsalve, S. Alonso, Alt, C., Andreopoulos, C., Antonova, M., Aoki, S., Arihara, T., Asada, Y., Ashida, Y., Atkin, E. T., Barbi, M., Barker, G. J., Barr, G., Barrow, D., Batkiewicz-Kwasniak, M., Bench, F., Berardi, V., Berns, L., Bhadra, S., Blanchet, A., Blondel, A., Bolognesi, S., Bonus, T., Bordoni, S., Boyd, S. B., Bravar, A., Bronner, C., Bron, S., Bubak, A., Avanzini, M. Buizza, Caballero, J. A., Calabria, N. F., Cao, S., Carabadjac, D., Carter, A. J., Cartwright, S. L., Catanesi, M. G., Cervera, A., Chakrani, J., Cherdack, D., Chong, P. S., Christodoulou, G., Chvirova, A., Cicerchia, M., Coleman, J., Collazuol, G., Cook, L., Cudd, A., Dalmazzone, C., Daret, T., Davydov, Yu. I., De Roeck, A., De Rosa, G., Dealtry, T., Delogu, C. C., Densham, C., Dergacheva, A., Di Lodovico, F., Dolan, S., Douqa, D., Doyle, T. A., Drapier, O., Dumarchez, J., Dunne, P., Dygnarowicz, K., Eguchi, A., Emery-Schrenk, S., Erofeev, G., Ershova, A., Eurin, G., Fedorova, D., Fedotov, S., Feltre, M., Finch, A. J., Aguirre, G. A. Fiorentini, Fiorillo, G., Fitton, M. D., Patiño, J. M. Franco, Friend, M., Fujii, Y., Fukuda, Y., Fusshoeller, K., Giannessi, L., Giganti, C., Glagolev, V., Gonin, M., Rosa, J. González, Goodman, E. A. G., Gorin, A., Grassi, M., Guigue, M., Hadley, D. R., Haigh, J. T., Hamacher-Baumann, P., Harris, D. A., Hartz, M., Hasegawa, T., Hassani, S., Hastings, N. C., Hayato, Y., Henaff, D., Hiramoto, A., Hogan, M., Holeczek, J., Holin, A., Holvey, T., Van, N. T. Hong, Honjo, T., Iacob, F., Ichikawa, A. K., Ikeda, M., Ishida, T., Ishitsuka, M., Israel, H. T., Iwamoto, K., Izmaylov, A., Izumi, N., Jakkapu, M., Jamieson, B., Jenkins, S. J., Jesús-Valls, C., Jiang, J. J., Jonsson, P., Joshi, S., Jung, C. K., Jurj, P. B., Kabirnezhad, M., Kaboth, A. C., Kajita, T., Kakuno, H., Kameda, J., Kasetti, S. P., Kataoka, Y., Katayama, Y., Katori, T., Kawaue, M., Kearns, E., Khabibullin, M., Khotjantsev, A., Kikawa, T., Kikutani, H., King, S., Kiseeva, V., Kisiel, J., Kobata, T., Kobayashi, H., Kobayashi, T., Koch, L., Kodama, S., Konaka, A., Kormos, L. L., Koshio, Y., Kostin, A., Koto, T., Kowalik, K., Kudenko, Y., Kudo, Y., Kuribayashi, S., Kurjata, R., Kutter, T., Kuze, M., La Commara, M., Labarga, L., Lachner, K., Lagoda, J., Lakshmi, S. M., James, M. Lamers, Lamoureux, M., Langella, A., Laporte, J. -F., Last, D., Latham, N., Laveder, M., Lavitola, L., Lawe, M., Lee, Y., Lin, C., Lin, S. -K., Litchfield, R. P., Liu, S. L., Li, W., Longhin, A., Long, K. R., Moreno, A. Lopez, Ludovici, L., Lu, X., Lux, T., Machado, L. N., Magaletti, L., Mahn, K., Malek, M., Mandal, M., Manly, S., Marino, A. D., Marti-Magro, L., Martin, D. G. R., Martini, M., Martin, J. F., Maruyama, T., Matsubara, T., Matveev, V., Mauger, C., Mavrokoridis, K., Mazzucato, E., McCauley, N., McElwee, J., McFarland, K. S., McGrew, C., McKean, J., Mefodiev, A., Megias, G. D., Mehta, P., Mellet, L., Metelko, C., Mezzetto, M., Miller, E., Minamino, A., Mineev, O., Mine, S., Miura, M., Bueno, L. Molina, Moriyama, S., Morrison, P., Mueller, Th. A., Munford, D., Munteanu, L., Nagai, K., Nagai, Y., Nakadaira, T., Nakagiri, K., Nakahata, M., Nakajima, Y., Nakamura, A., Nakamura, H., Nakamura, K., Nakamura, K. D., Nakano, Y., Nakayama, S., Nakaya, T., Nakayoshi, K., Naseby, C. E. R., Ngoc, T. V., Nguyen, V. Q., Niewczas, K., Nishimori, S., Nishimura, Y., Nishizaki, K., Nosek, T., Nova, F., Novella, P., Nugent, J. C., O'Keeffe, H. M., O'Sullivan, L., Odagawa, T., Ogawa, T., Okada, R., Okinaga, W., Okumura, K., Okusawa, T., Ospina, N., Owen, R. A., Oyama, Y., Palladino, V., Paolone, V., Pari, M., Parlone, J., Parsa, S., Pasternak, J., Pavin, M., Payne, D., Penn, G. C., Pershey, D., Pickering, L., Pidcott, C., Pintaudi, G., Pistillo, C., Popov, B., Porwit, K., Posiadala-Zezula, M., Prabhu, Y. S., Pupilli, F., Quilain, B., Radermacher, T., Radicioni, E., Radics, B., Ramírez, M. A., Ratoff, P. N., Reh, M., Riccio, C., Rondio, E., Roth, S., Roy, N., Rubbia, A., Ruggeri, A. C., Ruggles, C. A., Rychter, A., Sakashita, K., Sánchez, F., Santucci, G., Schloesser, C. M., Scholberg, K., Scott, M., Seiya, Y., Sekiguchi, T., Sekiya, H., Sgalaberna, D., Shaikhiev, A., Shaker, F., Shaykina, A., Shiozawa, M., Shorrock, W., Shvartsman, A., Skrobova, N., Skwarczynski, K., Smyczek, D., Smy, M., Sobczyk, J. T., Sobel, H., Soler, F. J. P., Sonoda, Y., Speers, A. J., Spina, R., Suslov, I. A., Suvorov, S., Suzuki, A., Suzuki, S. Y., Suzuki, Y., Sztuc, A. A., Tada, M., Tairafune, S., Takayasu, S., Takeda, A., Takeuchi, Y., Takifuji, K., Tanaka, H. K., Tanihara, Y., Tani, M., Teklu, A., Tereshchenko, V. V., Teshima, N., Thamm, N., Thompson, L. F., Toki, W., Touramanis, C., Towstego, T., Tsui, K. M., Tsukamoto, T., Tzanov, M., Uchida, Y., Vagins, M., Vargas, D., Varghese, M., Vasseur, G., Vilela, C., Villa, E., Vinning, W. G. S., Virginet, U., Vladisavljevic, T., Wachala, T., Walsh, J. G., Wang, Y., Wan, L., Wark, D., Wascko, M. O., Weber, A., Wendell, R., Wilking, M. J., Wilkinson, C., Wilson, J. R., Wood, K., Wret, C., Xia, J., Xu, Y. -h., Yamamoto, K., Yamamoto, T., Yanagisawa, C., Yang, G., Yano, T., Yasutome, K., Yershov, N., Yevarouskaya, U., Yokoyama, M., Yoshimoto, Y., Yoshimura, N., Yu, M., Zaki, R., Zalewska, A., Zalipska, J., Zaremba, K., Zarnecki, G., Zhao, X., Zhu, T., Ziembicki, M., Zimmerman, E. D., Zito, M., and Zsoldos, S.
Subjects: High Energy Physics - Experiment
Abstract: The T2K experiment presents new measurements of neutrino oscillation parameters using $19.7(16.3)\times10^{20}$ protons on target (POT) in (anti-)neutrino mode at the far detector (FD). Compared to the previous analysis, an additional $4.7\times10^{20}$ POT neutrino data was collected at the FD. Significant improvements were made to the analysis methodology, with the near-detector analysis introducing new selections and using more than double the data. Additionally, this is the first T2K oscillation analysis to use NA61/SHINE data on a replica of the T2K target to tune the neutrino flux model, and the neutrino interaction model was improved to include new nuclear effects and calculations. Frequentist and Bayesian analyses are presented, including results on $\sin^2\theta_{13}$ and the impact of priors on the $\delta_\mathrm{CP}$ measurement. Both analyses prefer the normal mass ordering and upper octant of $\sin^2\theta_{23}$ with a nearly maximally CP-violating phase. Assuming the normal ordering and using the constraint on $\sin^2\theta_{13}$ from reactors, $\sin^2\theta_{23}=0.561^{+0.021}_{-0.032}$ using Feldman--Cousins corrected intervals, and $\Delta{}m^2_{32}=2.494_{-0.058}^{+0.041}\times10^{-3}~\mathrm{eV^2}$ using constant $\Delta\chi^{2}$ intervals. The CP-violating phase is constrained to $\delta_\mathrm{CP}=-1.97_{-0.70}^{+0.97}$ using Feldman--Cousins corrected intervals, and $\delta_\mathrm{CP}=0,\pi$ is excluded at more than 90% confidence level. A Jarlskog invariant of zero is excluded at more than $2\sigma$ credible level using a flat prior in $\delta_\mathrm{CP}$, and just below $2\sigma$ using a flat prior in $\sin\delta_\mathrm{CP}$. When the external constraint on $\sin^2\theta_{13}$ is removed, $\sin^2\theta_{13}=28.0^{+2.8}_{-6.5}\times10^{-3}$, in agreement with measurements from reactor experiments. These results are consistent with previous T2K analyses.
Published: 2023
Full Text: View/download PDF

12. Friendship Bench Adaptation to Improve Mental Health & HIV Care Engagement Outcomes Among PLWH and PWID in Vietnam (VITAL)

Author: Hanoi Medical University, The Friendship Bench Trust, and National Institute on Drug Abuse (NIDA)
Published: 2023

13. Using Argumentation Schemes to Model Legal Reasoning

Author: Bench-Capon, Trevor and Atkinson, Katie
Subjects: Computer Science - Artificial Intelligence
Abstract: We present argumentation schemes to model reasoning with legal cases. We provide schemes for each of the three stages that take place after the facts are established: factor ascription, issue resolution and outcome determination. The schemes are illustrated with examples from a specific legal domain, US Trade Secrets law, and the wider applicability of these schemes is discussed.
Published: 2022

14. Unsupervised segmentation of biomedical hyperspectral image data: tackling high dimensionality with convolutional autoencoders

Author: Bench, Ciaran, Nallala, Jayakrupakar, Wang, Chun-Chin, Sheridan, Hannah, and Stone, Nicholas
Subjects: Physics - Medical Physics, Electrical Engineering and Systems Science - Image and Video Processing
Abstract: Information about the structure and composition of biopsy specimens can assist in disease monitoring and diagnosis. In principle, this can be acquired from Raman and infrared (IR) hyperspectral images (HSIs) that encode information about how a sample's constituent molecules are arranged in space. Each tissue section/component is defined by a unique combination of spatial and spectral features, but given the high dimensionality of HSI datasets, extracting and utilising them to segment images is non-trivial. Here, we show how networks based on deep convolutional autoencoders (CAEs) can perform this task in an end-to-end fashion by first detecting and compressing relevant features from patches of the HSI into low-dimensional latent vectors, and then performing a clustering step that groups patches containing similar spatio-spectral features together. We showcase the advantages of using this end-to-end spatio-spectral segmentation approach compared to i) the same spatio-spectral technique not trained in an end-to-end manner, and ii) a method that only utilises spectral features (spectral k-means) using simulated HSIs of porcine tissue as test examples. Secondly, we describe the potential advantages/limitations of using three different CAE architectures: a generic 2D CAE, a generic 3D CAE, and a 2D CNN architecture inspired by the recently proposed UwU-net that is specialised for extracting features from HSI data. We assess their performance on IR HSIs of real colon samples. We find that all architectures are capable of producing segmentations that show good correspondence with HE stained adjacent tissue slices used as approximate ground truths, indicating the robustness of the CAE-driven approach for segmenting biomedical HSI data. Additionally, we stress the need for more accurate ground truth information to rigorously compare the advantages offered by each architecture.
Published: 2022

15. Scintillator ageing of the T2K near detectors from 2010 to 2021

Author: The T2K Collaboration, Abe, K., Akhlaq, N., Akutsu, R., Ali, A., Alt, C., Andreopoulos, C., Antonova, M., Aoki, S., Arihara, T., Asada, Y., Ashida, Y., Atkin, E. T., Ban, S., Barbi, M., Barker, G. J., Barr, G., Barrow, D., Batkiewicz-Kwasniak, M., Bench, F., Berardi, V., Berns, L., Bhadra, S., Blanchet, A., Blondel, A., Bolognesi, S., Bonus, T., Bordoni, S., Boyd, S. B., Bravar, A., Bronner, C., Bron, S., Bubak, A., Avanzini, M. Buizza, Calabria, N. F., Cao, S., Carter, A. J., Cartwright, S. L., Catanesi, M. G., Cervera, A., Chakrani, J., Cherdack, D., Christodoulou, G., Cicerchia, M., Coleman, J., Collazuol, G., Cook, L., Cudd, A., Davydov, Yu. I., De Roeck, A., De Rosa, G., Dealtry, T., Delogu, C. C., Densham, C., Dergacheva, A., Di Lodovico, F., Dolan, S., Douqa, D., Doyle, T. A., Drapier, O., Duffy, K. E., Dumarchez, J., Dunne, P., Dygnarowicz, K., Eguchi, A., Emery-Schrenk, S., Ershova, A., Fedotov, S., Fernandez, P., Finch, A. J., Aguirre, G. A. Fiorentini, Fiorillo, G., Friend, M., Fujii, Y., Fukuda, Y., Fusshoeller, K., Giganti, C., Glagolev, V., Gonin, M., Goodman, E. A. G., Gorin, A., Grassi, M., Guigue, M., Hadley, D. R., Haigh, J. T., Hamacher-Baumann, P., Harris, D. A., Hartz, M., Hasegawa, T., Hassani, S., Hastings, N. C., Hatzikoutelis, A., Hayato, Y., Hiramoto, A., Hogan, M., Holeczek, J., Holin, A., Holvey, T. J., Van, N. T. Hong, Honjo, T., Iacob, F., Ichikawa, A. K., Ikeda, M., Ishida, T., Ishitsuka, M., Israel, H. T., Iwamoto, K., Izmaylov, A., Izumi, N., Jakkapu, M., Jamieson, B., Jenkins, S. J., Jesús-Valls, C., Jiang, J. J., Jonsson, P., Jung, C. K., Jurj, P. B., Kabirnezhad, M., Kaboth, A. C., Kajita, T., Kakuno, H., Kameda, J., Kasetti, S. P., Kataoka, Y., Katayama, Y., Katori, T., Kawaue, M., Kearns, E., Khabibullin, M., Khotjantsev, A., Kikawa, T., Kikutani, H., King, S., Kisiel, J., Knight, A., Kobata, T., Kobayashi, T., Koch, L., Kogan, G., Konaka, A., Kormos, L. L., Koshio, Y., Kostin, A., Kowalik, K., Kudenko, Y., Kuribayashi, S., Kurjata, R., Kutter, T., Kuze, M., La Commara, M., Labarga, L., Lagoda, J., Lakshmi, S. M., James, M. Lamers, Lamont, I., Lamoureux, M., Last, D., Latham, N., Laveder, M., Lawe, M., Lee, Y., Lin, C., Lindner, T., Lin, S. -K., Litchfield, R. P., Liu, S. L., Longhin, A., Long, K. R., Ludovici, L., Lu, X., Lux, T., Machado, L. N., Magaletti, L., Mahn, K., Malek, M., Mandal, M., Manly, S., Marino, A. D., Marti-Magro, L., Martin, D. G. R., Martini, M., Martin, J. F., Maruyama, T., Matsubara, T., Matveev, V., Mauger, C., Mavrokoridis, K., Mazzucato, E., McCauley, N., McElwee, J., McFarland, K. S., McGrew, C., Mefodiev, A., Megias, G. D., Mellet, L., Metelko, C., Mezzetto, M., Minamino, A., Mineev, O., Mine, S., Miura, M., Bueno, L. Molina, Moriyama, S., Mueller, Th. A., Munford, D., Munteanu, L., Nagai, K., Nagai, Y., Nakadaira, T., Nakagiri, K., Nakahata, M., Nakajima, Y., Nakamura, A., Nakamura, H., Nakamura, K., Nakano, Y., Nakayama, S., Nakaya, T., Nakayoshi, K., Naseby, C. E. R., Ngoc, T. V., Nguyen, V. Q., Niewczas, K., Nishimura, Y., Nishizaki, K., Nova, F., Novella, P., Nugent, J. C., O'Keeffe, H. M., O'Sullivan, L., Odagawa, T., Ogawa, T., Okada, R., Okumura, K., Okusawa, T., Owen, R. A., Oyama, Y., Palladino, V., Paolone, V., Pari, M., Parlone, J., Parsa, S., Pasternak, J., Pavin, M., Payne, D., Penn, G. C., Pershey, D., Pickering, L., Pidcott, C., Pintaudi, G., Pistillo, C., Popov, B., Porwit, K., Posiadala-Zezula, M., Prabhu, Y. S., Quilain, B., Radermacher, T., Radicioni, E., Radics, B., Ratoff, P. N., Reh, M., Riccio, C., Rondio, E., Roth, S., Rubbia, A., Ruggeri, A. C., Ruggles, C. A., Rychter, A., Sakashita, K., Sánchez, F., Santucci, G., Schloesser, C. M., Scholberg, K., Scott, M., Seiya, Y., Sekiguchi, T., Sekiya, H., Sgalaberna, D., Shaikhiev, A., Shaykina, A., Shiozawa, M., Shorrock, W., Shvartsman, A., Skwarczynski, K., Smy, M., Sobczyk, J. T., Sobel, H., Soler, F. J. P., Sonoda, Y., Spina, R., Su, H., Suslov, I. A., Suvorov, S., Suzuki, A., Suzuki, S. Y., Suzuki, Y., Sztuc, A. A., Tada, M., Takayasu, S., Takeda, A., Takeuchi, Y., Tanaka, H. K., Tanihara, Y., Tani, M., Tereshchenko, V. V., Teshima, N., Thamm, N., Thompson, L. F., Toki, W., Touramanis, C., Towstego, T., Tsui, K. M., Tsukamoto, T., Tzanov, M., Uchida, Y., Vacheret, A., Vagins, M., Vargas, D., Vasseur, G., Vilela, C., Vinning, W. G. S., Vladisavljevic, T., Wachala, T., Walsh, J. G., Wang, Y., Wan, L., Wark, D., Wascko, M. O., Weber, A., Wendell, R., Wilking, M. J., Wilkinson, C., Wilson, J. R., Wood, K., Wret, C., Xia, J., Xu, Y. -h., Yamamoto, K., Yanagisawa, C., Yang, G., Yano, T., Yasutome, K., Yershov, N., Yevarouskaya, U., Yokoyama, M., Yoshimoto, Y., Yu, M., Zaki, R., Zalewska, A., Zalipska, J., Zaremba, K., Zarnecki, G., Zhao, X., Zhu, T., Ziembicki, M., Zimmerman, E. D., Zito, M., and Zsoldos, S.
Subjects: Physics - Instrumentation and Detectors, High Energy Physics - Experiment
Abstract: The T2K experiment widely uses plastic scintillator as a target for neutrino interactions and an active medium for the measurement of charged particles produced in neutrino interactions at its near detector complex. Over 10 years of operation the measured light yield recorded by the scintillator based subsystems has been observed to degrade by 0.9--2.2\% per year. Extrapolation of the degradation rate through to 2040 indicates the recorded light yield should remain above the lower threshold used by the current reconstruction algorithms for all subsystems. This will allow the near detectors to continue contributing to important physics measurements during the T2K-II and Hyper-Kamiokande eras. Additionally, work to disentangle the degradation of the plastic scintillator and wavelength shifting fibres shows that the reduction in light yield can be attributed to the ageing of the plastic scintillator., Comment: 29 pages, 18 figures. Prepared for submission to JINST
Published: 2022

16. Measurements of neutrino oscillation parameters from the T2K experiment using 3.6×1021 protons on target

Author: Abe, K, Akhlaq, N, Akutsu, R, Ali, A, Alonso Monsalve, S, Alt, C, Andreopoulos, C, Antonova, M, Aoki, S, Arihara, T, Asada, Y, Ashida, Y, Atkin, ET, Barbi, M, Barker, GJ, Barr, G, Barrow, D, Batkiewicz-Kwasniak, M, Bench, F, Berardi, V, Berns, L, Bhadra, S, Blanchet, A, Blondel, A, Bolognesi, S, Bonus, T, Bordoni, S, Boyd, SB, Bravar, A, Bronner, C, Bron, S, Bubak, A, Buizza Avanzini, M, Caballero, JA, Calabria, NF, Cao, S, Carabadjac, D, Carter, AJ, Cartwright, SL, Catanesi, MG, Cervera, A, Chakrani, J, Cherdack, D, Chong, PS, Christodoulou, G, Chvirova, A, Cicerchia, M, Coleman, J, Collazuol, G, Cook, L, Cudd, A, Dalmazzone, C, Daret, T, Davydov, Yu I, De Roeck, A, De Rosa, G, Dealtry, T, Delogu, CC, Densham, C, Dergacheva, A, Di Lodovico, F, Dolan, S, Douqa, D, Doyle, TA, Drapier, O, Dumarchez, J, Dunne, P, Dygnarowicz, K, Eguchi, A, Emery-Schrenk, S, Erofeev, G, Ershova, A, Eurin, G, Fedorova, D, Fedotov, S, Feltre, M, Finch, AJ, Fiorentini Aguirre, GA, Fiorillo, G, Fitton, MD, Franco Patiño, JM, Friend, M, Fujii, Y, Fukuda, Y, Fusshoeller, K, Giannessi, L, Giganti, C, Glagolev, V, Gonin, M, González Rosa, J, Goodman, EAG, Gorin, A, Grassi, M, Guigue, M, Hadley, DR, Haigh, JT, Hamacher-Baumann, P, Harris, DA, Hartz, M, and Hasegawa, T
Subjects: Nuclear and Plasma Physics, Particle and High Energy Physics, Physical Sciences, T2K Collaboration, Atomic, Molecular, Nuclear, Particle and Plasma Physics, Quantum Physics, Nuclear & Particles Physics, Astronomical sciences, Atomic, molecular and optical physics, Particle and high energy physics
Abstract: The T2K experiment presents new measurements of neutrino oscillation parameters using 19.7(16.3)×1020 protons on target (POT) in (anti-)neutrino mode at the far detector (FD). Compared to the previous analysis, an additional 4.7×1020 POT neutrino data was collected at the FD. Significant improvements were made to the analysis methodology, with the near-detector analysis introducing new selections and using more than double the data. Additionally, this is the first T2K oscillation analysis to use NA61/SHINE data on a replica of the T2K target to tune the neutrino flux model, and the neutrino interaction model was improved to include new nuclear effects and calculations. Frequentist and Bayesian analyses are presented, including results on sin2θ13 and the impact of priors on the δCP measurement. Both analyses prefer the normal mass ordering and upper octant of sin2θ23 with a nearly maximally CP-violating phase. Assuming the normal ordering and using the constraint on sin2θ13 from reactors, sin2θ23=0.561-0.032+0.021 using Feldman-Cousins corrected intervals, and Δm322=2.494-0.058+0.041×10-3eV2 using constant Δχ2 intervals. The CP-violating phase is constrained to δCP=-1.97-0.70+0.97 using Feldman-Cousins corrected intervals, and δCP=0,π is excluded at more than 90% confidence level. A Jarlskog invariant of zero is excluded at more than 2σ credible level using a flat prior in δCP, and just below 2σ using a flat prior in sinδCP. When the external constraint on sin2θ13 is removed, sin2θ13=28.0-6.5+2.8×10-3, in agreement with measurements from reactor experiments. These results are consistent with previous T2K analyses.
Published: 2023

17. Characterizing manufacturing sector disruptions with targeted mitigation strategies

Author: Elimbi Moudio, Marie Pelagie, Bolin, Richard, Carpenter, Alberta, Reese, Samantha Bench, Shehabi, Arman, and Rao, Prakash
Subjects: Transportation, Logistics and Supply Chains, Commerce, Management, Tourism and Services, Industry, Innovation and Infrastructure
Abstract: It has become clear in recent decades that manufacturing supply chains are increasingly vulnerable to disruptions of varying geographical scales and intensities. These disruptions—whether intentional, accidental, or resulting from natural disasters—cause failures and capacity reductions to manufacturing infrastructure, with lasting effects that can cascade throughout the manufacturing network. An overall lack of understanding of solutions to mitigate disturbances has rendered the challenge of reducing manufacturing supply chain vulnerability even more difficult. Additionally, the variability of disruptions and their impacts complicates policy maker and stakeholder efforts to plan for specific disruptive scenarios. It is necessary to comprehend different kinds of disturbances and group them based on stakeholder-provided metrics to support planning processes and modeling efforts that promote adaptable, resilient manufacturing supply chains. This paper reviews existing methods for risk management in manufacturing supply chains and the economic and environmental impacts of disruptions. In addition, we develop a framework using agglomerative hierarchical clustering to classify disruptions using U.S. manufacturing network data between 2000 and 2021 and characteristic metrics defined in the literature. Our review identifies five groups of disruptions and discusses both general mitigation methods and strategies targeting each identified group. Further, we highlight gaps in the literature related to estimating and including environmental costs in disaster preparedness and mitigation planning. We also discuss the lack of easily available metrics to quantify environmental impacts of disruptions and how such metrics could be included into our methodology.
Published: 2022

18. Annotated insights into legal reasoning: A dataset of Article 6 ECHR cases.

Author: Jack Mumford, Katie Atkinson, and Trevor J. M. Bench-Capon
Published: 2024
Full Text: View/download PDF

19. A Note on Hierarchical Constraints

Author: Bench-Capon, Trevor, primary
Published: 2023
Full Text: View/download PDF

20. Dimensions and Precedential Constraint: Factors Deriving from Multiple Dimensions

Author: Bench-Capon, Trevor, primary and Atkinson, Katie, additional
Published: 2023
Full Text: View/download PDF

21. Human Performance on the AI Legal Case Verdict Classification Task

Author: Mumford, Jack, primary, Atkinson, Katie, additional, and Bench-Capon, Trevor, additional
Published: 2023
Full Text: View/download PDF

22. Observing impacts on luminescence depth profile evolutions from surface altered quartzite using OSL laser scanning and controlled light exposed rock sampling techniques

Author: Bench, Tristan, Sanderson, David, and Feathers, James
Published: 2024
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23. The relationship between clinicopathological variables, systemic inflammation, and CT‐derived body composition with survival in patients with advanced non‐small cell lung cancer receiving nivolumab as a second‐line treatment

Author: Randa Saeed, Josh McGovern, Hugo Bench, Ross D. Dolan, Donald C. McMillan, and Almudena Cascales
Subjects: body composition, ECOG‐PS, hypoalbuminemia, immunotherapy, Nivolumab, NSCLC, Neoplasms. Tumors. Oncology. Including cancer and carcinogens, RC254-282
Abstract: Abstract Background Second‐line immunotherapy is currently recognized to help only a subset of patients with advanced forms of non‐small cell lung cancer (NSCLC). The current study analyzes the connection between prior treatment host/tumor characteristics and survival in advanced NSCLC patients receiving nivolumab as a second‐line therapy. Methods A retrospective cohort analysis was carried out on individuals with advanced NSCLC receiving second‐line Nivolumab with palliative intent between February 2016 and May 2019 across three health boards in NHS Greater Glasgow and Clyde, Lanarkshire, Ayrshire, and Arran in Scotland to examine the association between systemic inflammation, body composition, and survival were determined using computed tomography (CT). Results The current study investigates the connection between prior treatment host/tumor characteristics and survival in advanced NSCLC patients receiving nivolumab as a second‐line therapy. The majority were 65 years of age or older (51%), female (53%), had adenocarcinoma (53%), and had good performance status (ECOG 0/1) (86%). Most patients had high SFI (70%) or VFA (54%). The median overall survival after starting Nivolumab was 15 months. ECOG‐PS and hypoalbuminemia were significant predictors of 12‐month survival in patients with advanced NSCLC following Nivolumab treatment, according to Cox regression (p‐value = 0.047 and 0.014, respectively). Conclusion In patients with advanced NSCLC receiving Nivolumab as a second‐line therapy, ECOG‐PS and hypoalbuminemia were strongly associated with survival. Systemic inflammation and hypoalbuminemia measurements may enhance the ECOG‐PS stratification of expected outcomes.
Published: 2023
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24. Challenges Encountered by Indigenous Children in Self-Learning Module during New Normal Education

Author: Bench G. Fabros, Janine T. Ancheta, Audley Jan R. Balanay, Mharey D. Bellen, Alexandria Shane S. Cuario, and Ma. Isabel B. Marzan
Subjects: indigenous children, indigenous people, self-learning module, new normal education, Theory and practice of education, LB5-3640
Abstract: The impoverished and indigenous peoples are the most seriously affected groups in the Philippines' abrupt shift in curriculum due to the risk of the COVID-19 outbreak who reside in rural areas where the provision of basic services has been challenging. This study aims to determine the challenges faced by indigenous children in the self-learning module. Using a researcher-made validated semi-structured interview, the study implemented a qualitative narrative research method design wherein responses were gathered from participants' interviews, experiences, and challenges encountered in the self-learning module. The participants of the study were two (2) kindergarten parents and one (1) grade 3 parent from Sitio Poquiz Maasin, San Clemente, Tarlac, Philippines. As an outcome, the pandemic affects the learning of indigenous children. Loss of motivation showed that learners were becoming lazy when answering and completing their modules. The learners also showed they had challenges in concentrating, which has an effect on the learning and teaching experiences. Because of their parents' limited education, challenges in understanding the module were noted, and unclear instructions in the modules made it challenging for students to answer. Despite these challenges, the researchers lay out some alternative ways and interventions that can be utilized to cope up with the new normal education.
Published: 2023
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25. Fatigue after CriTical illness (FACT): Co-production of a self-management intervention to support people with fatigue after critical illness

Author: Brown, Sophie Eleanor, Shah, Akshay, Czuber-Dochan, Wladyslawa, Bench, Suzanne, and Stayt, Louise
Published: 2024
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26. Data-driven quantitative photoacoustic tomography

Author: Bench, Ciaran
Abstract: Spatial information about the 3D distribution of blood oxygen saturation (sO2) in vivo is of clinical interest as it encodes important physiological information about tissue health/pathology. Photoacoustic tomography (PAT) is a biomedical imaging modality that, in principle, can be used to acquire this information. Images are formed by illuminating the sample with a laser pulse where, after multiple scattering events, the optical energy is absorbed. A subsequent rise in temperature induces an increase in pressure (the photoacoustic initial pressure p0) that propagates to the sample surface as an acoustic wave. These acoustic waves are detected as pressure time series by sensor arrays and used to reconstruct images of sample's p0 distribution. This encodes information about the sample's absorption distribution, and can be used to estimate sO2. However, an ill-posed nonlinear inverse problem stands in the way of acquiring estimates in vivo. Current approaches to solving this problem fall short of being widely and successfully applied to in vivo tissues due to their reliance on simplifying assumptions about the tissue, prior knowledge of its optical properties, or the formulation of a forward model accurately describing image acquisition with a specific imaging system. Here, we investigate the use of data-driven approaches (deep convolutional networks) to solve this problem. Networks only require a dataset of examples to learn a mapping from PAT data to images of the sO2 distribution. We show the results of training a 3D convolutional network to estimate the 3D sO2 distribution within model tissues from 3D multiwavelength simulated images. However, acquiring a realistic training set to enable successful in vivo application is non-trivial given the challenges associated with estimating ground truth sO2 distributions and the current limitations of simulating training data. We suggest/test several methods to 1) acquire more realistic training data or 2) improve network performance in the absence of adequate quantities of realistic training data. For 1) we describe how training data may be acquired from an organ perfusion system and outline a possible design. Separately, we describe how training data may be generated synthetically using a variant of generative adversarial networks called ambientGANs. For 2), we show how the accuracy of networks trained with limited training data can be improved with self-training. We also demonstrate how the domain gap between training and test sets can be minimised with unsupervised domain adaption to improve quantification accuracy. Overall, this thesis clarifies the advantages of data-driven approaches, and suggests concrete steps towards overcoming the challenges with in vivo application.
Published: 2022

27. Use of fidget and drinking behaviour in combination with facial infrared thermography for diagnosis of bovine respiratory disease in a spontaneous model

Author: H.J. Perez Marquez, A.L. Schaefer, and C.J Bench
Subjects: Cattle, Facial-temperature, Lung-illness, Micro-movement, Non-invasive, Animal culture, SF1-1100
Abstract: Bovine respiratory disease (BRD) is a highly prevalent multi pathogen infectious disease (70–80%) in newly received feedlot cattle, causing significant economic losses and reduced animal welfare. Current BRD diagnosis involves stressful and invasive methods that can increase the incidence and transmission of BRD. An alternative is the use of an automated infrared thermography (IR) platform that can monitor facial temperature and behaviour traits to diagnose BRD in a non-invasive manner. The objective of this study was to investigate the use of fidget and drinking behaviours in conjunction with facial temperature as method of BRD diagnosis in beef calves. Sixty-five weaned calves (N = 65) were monitored over a 21-d period after 6 h transportation to predispose calves to BRD infection. Data collected from an automated IR platform placed at a water station included the number of IR frames during drinking (Fidget), number of drinking visits (Drinking bouts), total drinking duration, average drinking duration, average cheek temperature (AVG temp), and maximum orbital temperature (Max temp). Fidget, drinking behaviours, and IR were compared to a clinical score assessment based on respiratory, digestive, and lethargy signs (visual observation) and haematology analysis using a receiver operating characteristics curve analysis to identify the accuracy of each metric and combinations of metrics for BRD diagnosis. The greater accuracies observed were Fidget, Youden’s index (J): 0.25 J), Drinking bout (0.28 J), and Total drinking duration (0.22 J). The average IR temperature accuracy resulted in 0.88 J and Max temp 0.77 J. Thirty-five combinations of drinking behaviour and facial IR metrics were evaluated to identify BRD calves. Optimum accuracy (100%) was achieved when combining Fidget, Drinking bout, Average drinking duration, AVG temp, and Max temp 1.00 J. Similar evaluations were performed at 48 and 24 h before d 0 using the most accurate Fidget, Drinking behaviour, and IR combination, resulting in 0.44 J 48 h prior to d 0 and 0.45 J 24 h prior to d 0. Combining fidget and drinking behaviour metrics increased the sensitivity to detect the onset of BRD infection and the specificity to discriminate true positive BRD calves from true negative BRD calves.
Published: 2024
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28. Using Issues to Explain Legal Decisions

Author: Bench-Capon, Trevor
Subjects: Computer Science - Artificial Intelligence, Computer Science - Machine Learning
Abstract: The need to explain the output from Machine Learning systems designed to predict the outcomes of legal cases has led to a renewed interest in the explanations offered by traditional AI and Law systems, especially those using factor based reasoning and precedent cases. In this paper we consider what sort of explanations we should expect from such systems, with a particular focus on the structure that can be provided by the use of issues in cases., Comment: Presented at the XAILA workshop 2021
Published: 2021

29. Measurements of neutrino oscillation parameters from the T2K experiment using $$3.6\times 10^{21}$$ 3.6 × 10 21 protons on target

Author: K. Abe, N. Akhlaq, R. Akutsu, A. Ali, S. Alonso Monsalve, C. Alt, C. Andreopoulos, M. Antonova, S. Aoki, T. Arihara, Y. Asada, Y. Ashida, E. T. Atkin, M. Barbi, G. J. Barker, G. Barr, D. Barrow, M. Batkiewicz-Kwasniak, F. Bench, V. Berardi, L. Berns, S. Bhadra, A. Blanchet, A. Blondel, S. Bolognesi, T. Bonus, S. Bordoni, S. B. Boyd, A. Bravar, C. Bronner, S. Bron, A. Bubak, M. Buizza Avanzini, J. A. Caballero, N. F. Calabria, S. Cao, D. Carabadjac, A. J. Carter, S. L. Cartwright, M. G. Catanesi, A. Cervera, J. Chakrani, D. Cherdack, P. S. Chong, G. Christodoulou, A. Chvirova, M. Cicerchia, J. Coleman, G. Collazuol, L. Cook, A. Cudd, C. Dalmazzone, T. Daret, Yu. I. Davydov, A. De Roeck, G. De Rosa, T. Dealtry, C. C. Delogu, C. Densham, A. Dergacheva, F. Di Lodovico, S. Dolan, D. Douqa, T. A. Doyle, O. Drapier, J. Dumarchez, P. Dunne, K. Dygnarowicz, A. Eguchi, S. Emery-Schrenk, G. Erofeev, A. Ershova, G. Eurin, D. Fedorova, S. Fedotov, M. Feltre, A. J. Finch, G. A. Fiorentini Aguirre, G. Fiorillo, M. D. Fitton, J. M. Franco Patiño, M. Friend, Y. Fujii, Y. Fukuda, K. Fusshoeller, L. Giannessi, C. Giganti, V. Glagolev, M. Gonin, J. González Rosa, E. A. G. Goodman, A. Gorin, M. Grassi, M. Guigue, D. R. Hadley, J. T. Haigh, P. Hamacher-Baumann, D. A. Harris, M. Hartz, T. Hasegawa, S. Hassani, N. C. Hastings, Y. Hayato, D. Henaff, A. Hiramoto, M. Hogan, J. Holeczek, A. Holin, T. Holvey, N. T. Hong Van, T. Honjo, F. Iacob, A. K. Ichikawa, M. Ikeda, T. Ishida, M. Ishitsuka, H. T. Israel, K. Iwamoto, A. Izmaylov, N. Izumi, M. Jakkapu, B. Jamieson, S. J. Jenkins, C. Jesús-Valls, J. J. Jiang, P. Jonsson, S. Joshi, C. K. Jung, P. B. Jurj, M. Kabirnezhad, A. C. Kaboth, T. Kajita, H. Kakuno, J. Kameda, S. P. Kasetti, Y. Kataoka, Y. Katayama, T. Katori, M. Kawaue, E. Kearns, M. Khabibullin, A. Khotjantsev, T. Kikawa, H. Kikutani, S. King, V. Kiseeva, J. Kisiel, T. Kobata, H. Kobayashi, T. Kobayashi, L. Koch, S. Kodama, A. Konaka, L. L. Kormos, Y. Koshio, A. Kostin, T. Koto, K. Kowalik, Y. Kudenko, Y. Kudo, S. Kuribayashi, R. Kurjata, T. Kutter, M. Kuze, M. La Commara, L. Labarga, K. Lachner, J. Lagoda, S. M. Lakshmi, M. Lamers James, M. Lamoureux, A. Langella, J.-F. Laporte, D. Last, N. Latham, M. Laveder, L. Lavitola, M. Lawe, Y. Lee, C. Lin, S.-K. Lin, R. P. Litchfield, S. L. Liu, W. Li, A. Longhin, K. R. Long, A. Lopez Moreno, L. Ludovici, X. Lu, T. Lux, L. N. Machado, L. Magaletti, K. Mahn, M. Malek, M. Mandal, S. Manly, A. D. Marino, L. Marti-Magro, D. G. R. Martin, M. Martini, J. F. Martin, T. Maruyama, T. Matsubara, V. Matveev, C. Mauger, K. Mavrokoridis, E. Mazzucato, N. McCauley, J. McElwee, K. S. McFarland, C. McGrew, J. McKean, A. Mefodiev, G. D. Megias, P. Mehta, L. Mellet, C. Metelko, M. Mezzetto, E. Miller, A. Minamino, O. Mineev, S. Mine, M. Miura, L. Molina Bueno, S. Moriyama, P. Morrison, Th. A. Mueller, D. Munford, L. Munteanu, K. Nagai, Y. Nagai, T. Nakadaira, K. Nakagiri, M. Nakahata, Y. Nakajima, A. Nakamura, H. Nakamura, K. Nakamura, K. D. Nakamura, Y. Nakano, S. Nakayama, T. Nakaya, K. Nakayoshi, C. E. R. Naseby, T. V. Ngoc, V. Q. Nguyen, K. Niewczas, S. Nishimori, Y. Nishimura, K. Nishizaki, T. Nosek, F. Nova, P. Novella, J. C. Nugent, H. M. O’Keeffe, L. O’Sullivan, T. Odagawa, T. Ogawa, R. Okada, W. Okinaga, K. Okumura, T. Okusawa, N. Ospina, R. A. Owen, Y. Oyama, V. Palladino, V. Paolone, M. Pari, J. Parlone, S. Parsa, J. Pasternak, M. Pavin, D. Payne, G. C. Penn, D. Pershey, L. Pickering, C. Pidcott, G. Pintaudi, C. Pistillo, B. Popov, K. Porwit, M. Posiadala-Zezula, Y. S. Prabhu, F. Pupilli, B. Quilain, T. Radermacher, E. Radicioni, B. Radics, M. A. Ramírez, P. N. Ratoff, M. Reh, C. Riccio, E. Rondio, S. Roth, N. Roy, A. Rubbia, A. C. Ruggeri, C. A. Ruggles, A. Rychter, K. Sakashita, F. Sánchez, G. Santucci, C. M. Schloesser, K. Scholberg, M. Scott, Y. Seiya, T. Sekiguchi, H. Sekiya, D. Sgalaberna, A. Shaikhiev, F. Shaker, A. Shaykina, M. Shiozawa, W. Shorrock, A. Shvartsman, N. Skrobova, K. Skwarczynski, D. Smyczek, M. Smy, J. T. Sobczyk, H. Sobel, F. J. P. Soler, Y. Sonoda, A. J. Speers, R. Spina, I. A. Suslov, S. Suvorov, A. Suzuki, S. Y. Suzuki, Y. Suzuki, A. A. Sztuc, M. Tada, S. Tairafune, S. Takayasu, A. Takeda, Y. Takeuchi, K. Takifuji, H. K. Tanaka, Y. Tanihara, M. Tani, A. Teklu, V. V. Tereshchenko, N. Teshima, N. Thamm, L. F. Thompson, W. Toki, C. Touramanis, T. Towstego, K. M. Tsui, T. Tsukamoto, M. Tzanov, Y. Uchida, M. Vagins, D. Vargas, M. Varghese, G. Vasseur, C. Vilela, E. Villa, W. G. S. Vinning, U. Virginet, T. Vladisavljevic, T. Wachala, J. G. Walsh, Y. Wang, L. Wan, D. Wark, M. O. Wascko, A. Weber, R. Wendell, M. J. Wilking, C. Wilkinson, J. R. Wilson, K. Wood, C. Wret, J. Xia, Y.-H. Xu, K. Yamamoto, T. Yamamoto, C. Yanagisawa, G. Yang, T. Yano, K. Yasutome, N. Yershov, U. Yevarouskaya, M. Yokoyama, Y. Yoshimoto, N. Yoshimura, M. Yu, R. Zaki, A. Zalewska, J. Zalipska, K. Zaremba, G. Zarnecki, X. Zhao, T. Zhu, M. Ziembicki, E. D. Zimmerman, M. Zito, S. Zsoldos, and T2K Collaboration
Subjects: Astrophysics, QB460-466, Nuclear and particle physics. Atomic energy. Radioactivity, QC770-798
Abstract: Abstract The T2K experiment presents new measurements of neutrino oscillation parameters using $$19.7(16.3)\times 10^{20}$$ 19.7 ( 16.3 ) × 10 20 protons on target (POT) in (anti-)neutrino mode at the far detector (FD). Compared to the previous analysis, an additional $$4.7\times 10^{20}$$ 4.7 × 10 20 POT neutrino data was collected at the FD. Significant improvements were made to the analysis methodology, with the near-detector analysis introducing new selections and using more than double the data. Additionally, this is the first T2K oscillation analysis to use NA61/SHINE data on a replica of the T2K target to tune the neutrino flux model, and the neutrino interaction model was improved to include new nuclear effects and calculations. Frequentist and Bayesian analyses are presented, including results on $$\sin ^2\theta _{13}$$ sin 2 θ 13 and the impact of priors on the $$\delta _{\textrm{CP}}$$ δ CP measurement. Both analyses prefer the normal mass ordering and upper octant of $$\sin ^2\theta _{23}$$ sin 2 θ 23 with a nearly maximally CP-violating phase. Assuming the normal ordering and using the constraint on $$\sin ^2\theta _{13}$$ sin 2 θ 13 from reactors, $$\sin ^2\theta _{23}=0.561^{+0.021}_{-0.032}$$ sin 2 θ 23 = 0 . 561 - 0.032 + 0.021 using Feldman–Cousins corrected intervals, and $$\varDelta {}m^2_{32}=2.494_{-0.058}^{+0.041}\times 10^{-3}~\text {eV}^2$$ Δ m 32 2 = 2 . 494 - 0.058 + 0.041 × 10 - 3 eV 2 using constant $$\varDelta \chi ^{2}$$ Δ χ 2 intervals. The CP-violating phase is constrained to $$\delta _{\textrm{CP}}=-1.97_{-0.70}^{+0.97}$$ δ CP = - 1 . 97 - 0.70 + 0.97 using Feldman–Cousins corrected intervals, and $$\delta _{\textrm{CP}}=0,\pi $$ δ CP = 0 , π is excluded at more than 90% confidence level. A Jarlskog invariant of zero is excluded at more than $$2\sigma $$ 2 σ credible level using a flat prior in $$\delta _{\textrm{CP}},$$ δ CP , and just below $$2\sigma $$ 2 σ using a flat prior in $$\sin \delta _{\textrm{CP}}.$$ sin δ CP . When the external constraint on $$\sin ^2\theta _{13}$$ sin 2 θ 13 is removed, $$\sin ^2\theta _{13}=28.0^{+2.8}_{-6.5}\times 10^{-3},$$ sin 2 θ 13 = 28 . 0 - 6.5 + 2.8 × 10 - 3 , in agreement with measurements from reactor experiments. These results are consistent with previous T2K analyses.
Published: 2023
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30. Fiscal Rules in Ensuring the Debt Security of Ukraine

Author: Koliada Tetiana A., Bench Liliia Ya., and Pozhytkova Polina A.
Subjects: fiscal rules, debt security, fiscal policy, public debt management, government borrowing, debt burden, budget process., Business, HF5001-6182
Abstract: The aim of the article is to deepen and develop the scientific foundations of disclosure of the essence and significance of fiscal rules in the budget process, the features of their practical application in the countries of the world in the context of strengthening the debt security of Ukraine. The article systematizes fiscal rules by kinds, provides an essential characterization, identifies the disadvantages and advantages of their practical application in order to manage the debt security of the State. The popularity and frequency of application of various kinds of fiscal rules in the budget process of 106 countries of the world for the period from 1990 to 2021 are determined, some visual graphs are built. The distribution of fiscal rules by kinds in the context of economic groups of the countries of the world is carried out, an assessment of their effectiveness in the implementation of counter-cyclical fiscal policy is provided. The practice of using fiscal rules in the budget process of Ukraine is disclosed, the reasons for violation of their marginal indicators during military aggression are determined. The need to use a combination of different kinds of fiscal rules in order to achieve positive effects on debt security and level the cyclical nature of fiscal policy is emphasized. Proposals for improving the process of public debt management in the context of ensuring the optimal level of debt security of Ukraine are substantiated. Prospect for further research in this direction is to prove the need to restore the system of fiscal rules after the end of the war and bring it to the requirements of the European Union, taking into account the European integration vector of Ukraine’s development.
Published: 2023
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31. Interventions to support critical care nurse wellbeing: A scoping review

Author: Stewart, Carolyne, Bench, Suzanne, and Malone, Mary
Published: 2024
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32. Use of fidget and drinking behaviour in combination with facial infrared thermography for diagnosis of bovine respiratory disease in a spontaneous model

Author: Perez Marquez, H.J., Schaefer, A.L., and Bench, C.J
Published: 2024
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33. Effect of pullet rearing environment, strain and perch shape on perching behaviour, perching biomechanics, and keel bone damage in enriched-housed laying hens

Author: DePaoli, Emily, Korver, Doug, and Bench, Clover
Published: 2024
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34. Training Leaders in Trauma Resuscitation: Teacher and Learner Perspectives on Ideal Methods

Author: Quon, Samantha, Riddell, Jeffrey, Ford Bench, Kelsey, Roepke, Clare, and Burner, Elizabeth
Abstract: Introduction: Effective leadership improves patient care during medical and trauma resuscitations. While dedicated training programs can improve leadership in trauma resuscitation, we have a limited understanding of the optimal training methods. Our objective was to explore learners’ and teachers’ perceptions of effective methods of leadership training for trauma resuscitation.Methods: We performed a qualitative exploration of learner and teacher perceptions of leadership training methods using a modified grounded theory approach. We interviewed 28 participants, including attending physicians, residents, fellows, and nurses who regularly participated in trauma team activations. We then analyzed transcripts in an iterative manner to form codes, identify themes, and explore relationships between themes.Results: Based on interviewees’ perceptions, we identified seven methods used to train leadership in trauma resuscitation: reflection; feedback; hands-on learning; role modeling; simulation; group reflection; and didactic. We also identified three major themes in perceived best practices in training leaders in trauma resuscitation: formal vs informal curriculum; training techniques for novice vs more senior learner; and interprofessional training. Participants felt that informal training methods were the most important part of training, and that a significant part of a training program for leaders in trauma resuscitation should use informal methods. Learners who were earlier in their training preferred more supervision and guidance, while learners who were more advanced in their training preferred a greater degree of autonomy. Finally, participants believed leadership training for trauma resuscitation should be multidisciplinary and interprofessional.Conclusion: We identified several important themes for training leaders in trauma resuscitation, including using a variety of different training methods, adapting the methods used based on the learner’s level of training, and incorporating opportunities for multidisciplinary and interprofessional training. More research is needed to determine the optimal balance of informal and formal training, how to standardize and increase consistency in informal training, and the optimal way to incorporate multidisciplinary and interprofessional learning into a leadership in trauma resuscitation training program.
Published: 2022

35. First T2K measurement of transverse kinematic imbalance in the muon-neutrino charged-current single-$\pi^+$ production channel containing at least one proton

Author: Abe, K., Akhlaq, N., Akutsu, R., Ali, A., Alt, C., Andreopoulos, C., Antonova, M., Aoki, S., Arihara, T., Asada, Y., Ashida, Y., Atkin, E. T., Awataguchi, Y., Barker, G. J., Barr, G., Barrow, D., Batkiewicz-Kwasniak, M., Beloshapkin, A., Bench, F., Berardi, V., Berns, L., Bhadra, S., Blanchet, A., Blondel, A., Bolognesi, S., Bonus, T., Bourguille, B., Boyd, S. B., Bravar, A., Berguño, D. Bravo, Bronner, C., Bron, S., Bubak, A., Avanzini, M. Buizza, Cao, S., Cartwright, S. L., Catanesi, M. G., Cervera, A., Cherdack, D., Christodoulou, G., Cicerchia, M., Coleman, J., Collazuol, G., Cook, L., Coplowe, D., Cudd, A., De Rosa, G., Dealtry, T., Delogu, C. C., Dennis, S. R., Densham, C., Dergacheva, A., Di Lodovico, F., Dolan, S., Douqa, D., Doyle, T. A., Dumarchez, J., Dunne, P., Eguchi, A., Eklund, L., Emery-Schrenk, S., Ereditato, A., Finch, A. J., Fiorillo, G., Francois, C., Friend, M., Fujii, Y., Fukuda, R., Fukuda, Y., Fusshoeller, K., Giganti, C., Gonin, M., Gorin, A., Grassi, M., Guigue, M., Hadley, D. R., Hamacher-Baumann, P., Harris, D. A., Hartz, M., Hasegawa, T., Hassani, S., Hastings, N. C., Hayato, Y., Hiramoto, A., Hogan, M., Holeczek, J., Van, N. T. Hong, Honjo, T., Iacob, F., Ichikawa, A. K., Ikeda, M., Ishida, T., Ishitsuka, M., Iwamoto, K., Izmaylov, A., Izumi, N., Jakkapu, M., Jamieson, B., Jenkins, S. J., Jesús-Valls, C., Jonsson, P., Jung, C. K., Jurj, P. B., Kabirnezhad, M., Kakuno, H., Kameda, J., Kasetti, S. P., Kataoka, Y., Katayama, Y., Katori, T., Kearns, E., Khabibullin, M., Khotjantsev, A., Kikawa, T., Kikutani, H., King, S., Kisiel, J., Kobata, T., Kobayashi, T., Koch, L., Konaka, A., Kormos, L. L., Koshio, Y., Kostin, A., Kowalik, K., Kudenko, Y., Kuribayashi, S., Kurjata, R., Kutter, T., Kuze, M., Labarga, L., Lagoda, J., Lamoureux, M., Last, D., Laveder, M., Lawe, M., Litchfield, R. P., Liu, S. L., Longhin, A., Ludovici, L., Lu, X., Lux, T., Machado, L. N., Magaletti, L., Mahn, K., Malek, M., Manly, S., Maret, L., Marino, A. D., Marti-Magro, L., Maruyama, T., Matsubara, T., Matsushita, K., Mauger, C., Mavrokoridis, K., Mazzucato, E., McCauley, N., McElwee, J., McFarland, K. S., McGrew, C., Mefodiev, A., Mezzetto, M., Minamino, A., Mineev, O., Mine, S., Miura, M., Bueno, L. Molina, Moriyama, S., Mueller, Th. A., Munteanu, L., Nagai, Y., Nakadaira, T., Nakahata, M., Nakajima, Y., Nakamura, A., Nakamura, K., Nakano, Y., Nakayama, S., Nakaya, T., Nakayoshi, K., Naseby, C. E. R., Ngoc, T. V., Nguyen, V. Q., Niewczas, K., Nishimura, Y., Noah, E., Nonnenmacher, T. S., Nova, F., Nowak, J., Nugent, J. C., O'Keeffe, H. M., O'Sullivan, L., Odagawa, T., Ogawa, T., Okada, R., Okumura, K., Okusawa, T., Owen, R. A., Oyama, Y., Palladino, V., Paolone, V., Pari, M., Parker, W. C., Parsa, S., Pasternak, J., Pavin, M., Payne, D., Penn, G. C., Pershey, D., Pickering, L., Pidcott, C., Pintaudi, G., Pistillo, C., Popov, B., Porwit, K., Posiadala-Zezula, M., Quilain, B., Radermacher, T., Radicioni, E., Radics, B., Ratoff, P. N., Riccio, C., Rondio, E., Roth, S., Rubbia, A., Ruggeri, A. C., Ruggles, C., Rychter, A., Sakashita, K., Sánchez, F., Santucci, G., Schloesser, C. M., Scholberg, K., Scott, M., Seiya, Y., Sekiguchi, T., Sekiya, H., Sgalaberna, D., Shaikhiev, A., Shaykina, A., Shiozawa, M., Shorrock, W., Shvartsman, A., Skwarczynski, K., Smy, M., Sobczyk, J. T., Sobel, H., Soler, F. J. P., Sonoda, Y., Spina, R., Suvorov, S., Suzuki, A., Suzuki, S. Y., Suzuki, Y., Sztuc, A. A., Tada, M., Tajima, M., Takeda, A., Takeuchi, Y., Tanaka, H. K., Tanihara, Y., Tani, M., Teshima, N., Thompson, L. F., Toki, W., Touramanis, C., Towstego, T., Tsui, K. M., Tsukamoto, T., Tzanov, M., Uchida, Y., Vagins, M., Valder, S., Vargas, D., Vasseur, G., Vilela, C., Vinning, W. G. S., Vladisavljevic, T., Wachala, T., Walker, J., Walsh, J. G., Wang, Y., Wan, L., Wark, D., Wascko, M. O., Weber, A., Wendell, R., Wilking, M. J., Wilkinson, C., Wilson, J. R., Wood, K., Wret, C., Xia, J., Xu, Y. -h., Yamamoto, K., Yanagisawa, C., Yang, G., Yano, T., Yasutome, K., Yershov, N., Yokoyama, M., Yoshida, T., Yoshimoto, Y., Yu, M., Zalewska, A., Zalipska, J., Zaremba, K., Zarnecki, G., Ziembicki, M., Zito, M., and Zsoldos, S.
Subjects: High Energy Physics - Experiment
Abstract: This paper reports the first T2K measurement of the transverse kinematic imbalance in the single-$\pi^+$ production channel of neutrino interactions. We measure the differential cross sections in the muon-neutrino charged-current interaction on hydrocarbon with a single $\pi^+$ and at least one proton in the final state, at the ND280 off-axis near detector of the T2K experiment. The extracted cross sections are compared to the predictions from different neutrino-nucleus interaction event generators. Overall, the results show a preference for models which have a more realistic treatment of nuclear medium effects including the initial nuclear state and final-state interactions.
Published: 2021
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36. Improved constraints on neutrino mixing from the T2K experiment with $\mathbf{3.13\times10^{21}}$ protons on target

Author: T2K Collaboration, Abe, K., Akhlaq, N., Akutsu, R., Ali, A., Alt, C., Andreopoulos, C., Antonova, M., Aoki, S., Arihara, T., Asada, Y., Ashida, Y., Atkin, E. T., Awataguchi, Y., Barker, G. J., Barr, G., Barrow, D., Batkiewicz-Kwasniak, M., Beloshapkin, A., Bench, F., Berardi, V., Berns, L., Bhadra, S., Blanchet, A., Blondel, A., Bolognesi, S., Bonus, T., Bourguille, B., Boyd, S. B., Bravar, A., Bergu, D. Bravo, Bronner, C., Bron, S., Bubak, A., Avanzini, M. Buizza, Cao, S., Cartwright, S. L., Catanesi, M. G., Cervera, A., Cherdack, D., Christodoulou, G., Cicerchia, M., Coleman, J., Collazuol, G., Cook, L., Coplowe, D., Cudd, A., De Rosa, G., Dealtry, T., Delogu, C. C., Dennis, S. R., Densham, C., Dergacheva, A., Di Lodovico, F., Dolan, S., Douqa, D., Doyle, T. A., Dumarchez, J., Dunne, P., Eguchi, A., Eklund, L., Emery-Schrenk, S., Ereditato, A., Finch, A. J., Fiorillo, G., Francois, C., Friend, M., Fujii, Y., Fukuda, R., Fukuda, Y., Fusshoeller, K., Giganti, C., Gonin, M., Gorin, A., Grassi, M., Guigue, M., Hadley, D. R., Hamacher-Baumann, P., Harris, D. A., Hartz, M., Hasegawa, T., Hassani, S., Hastings, N. C., Hayato, Y., Hiramoto, A., Hogan, M., Holeczek, J., Van, N. T. Hong, Honjo, T., Iacob, F., Ichikawa, A. K., Ikeda, M., Ishida, T., Ishitsuka, M., Iwamoto, K., Izmaylov, A., Izumi, N., Jakkapu, M., Jamieson, B., Jenkins, S. J., Jes, C., Jonsson, P., Jung, C. K., Jurj, P. B., Kabirnezhad, M., Kakuno, H., Kameda, J., Kasetti, S. P., Kataoka, Y., Katayama, Y., Katori, T., Kearns, E., Khabibullin, M., Khotjantsev, A., Kikawa, T., Kikutani, H., King, S., Kisiel, J., Kobata, T., Kobayashi, T., Koch, L., Konaka, A., Kormos, L. L., Koshio, Y., Kostin, A., Kowalik, K., Kudenko, Y., Kuribayashi, S., Kurjata, R., Kutter, T., Kuze, M., Labarga, L., Lagoda, J., Lamoureux, M., Last, D., Laveder, M., Lawe, M., Litchfield, R. P., Liu, S. L., Longhin, A., Ludovici, L., Lu, X., Lux, T., Machado, L. N., Magaletti, L., Mahn, K., Malek, M., Manly, S., Maret, L., Marino, A. D., Marti-Magro, L., Maruyama, T., Matsubara, T., Matsushita, K., Mauger, C., Mavrokoridis, K., Mazzucato, E., McCauley, N., McElwee, J., McFarland, K. S., McGrew, C., Mefodiev, A., Mezzetto, M., Minamino, A., Mineev, O., Mine, S., Miura, M., Bueno, L. Molina, Moriyama, S., Mueller, Th. A., Munteanu, L., Nagai, Y., Nakadaira, T., Nakahata, M., Nakajima, Y., Nakamura, A., Nakamura, K., Nakano, Y., Nakayama, S., Nakaya, T., Nakayoshi, K., Naseby, C. E. R., Ngoc, T. V., Nguyen, V. Q., Niewczas, K., Nishimura, Y., Noah, E., Nonnenmacher, T. S., Nova, F., Nowak, J., Nugent, J. C., O'Keeffe, H. M., O'Sullivan, L., Odagawa, T., Ogawa, T., Okada, R., Okumura, K., Okusawa, T., Owen, R. A., Oyama, Y., Palladino, V., Paolone, V., Pari, M., Parker, W. C., Parsa, S., Pasternak, J., Pavin, M., Payne, D., Penn, G. C., Pickering, L., Pidcott, C., Pintaudi, G., Pistillo, C., Popov, B., Porwit, K., Posiadala-Zezula, M., Pritchard, A., Quilain, B., Radermacher, T., Radicioni, E., Radics, B., Ratoff, P. N., Riccio, C., Rondio, E., Roth, S., Rubbia, A., Ruggeri, A. C., Ruggles, C., Rychter, A., Sakashita, K., S, F., Santucci, G., Schloesser, C. M., Scholberg, K., Scott, M., Seiya, Y., Sekiguchi, T., Sekiya, H., Sgalaberna, D., Shaikhiev, A., Shaykina, A., Shiozawa, M., Shorrock, W., Shvartsman, A., Skwarczynski, K., Smy, M., Sobczyk, J. T., Sobel, H., Soler, F. J. P., Sonoda, Y., Spina, R., Suvorov, S., Suzuki, A., Suzuki, S. Y., Suzuki, Y., Sztuc, A. A., Tada, M., Tajima, M., Takeda, A., Takeuchi, Y., Tanaka, H. K., Tanihara, Y., Tani, M., Teshima, N., Thompson, L. F., Toki, W., Touramanis, C., Towstego, T., Tsui, K. M., Tsukamoto, T., Tzanov, M., Uchida, Y., Vagins, M., Valder, S., Vargas, D., Vasseur, G., Vilela, C., Vinning, W. G. S., Vladisavljevic, T., Wachala, T., Walker, J., Walsh, J. G., Wang, Y., Wark, D., Wascko, M. O., Weber, A., Wendell, R., Wilking, M. J., Wilkinson, C., Wilson, J. R., Wood, K., Wret, C., Xia, J., Yamamoto, K., Yanagisawa, C., Yang, G., Yano, T., Yasutome, K., Yershov, N., Yokoyama, M., Yoshida, T., Yoshimoto, Y., Yu, M., Zalewska, A., Zalipska, J., Zaremba, K., Zarnecki, G., Ziembicki, M., Zito, M., and Zsoldos, S.
Subjects: High Energy Physics - Experiment
Abstract: The T2K experiment reports updated measurements of neutrino and antineutrino oscillations using both appearance and disappearance channels. This result comes from an exposure of $14.9~(16.4) \times 10^{20}$ protons on target in neutrino (antineutrino) mode. Significant improvements have been made to the neutrino interaction model and far detector reconstruction. An extensive set of simulated data studies have also been performed to quantify the effect interaction model uncertainties have on the T2K oscillation parameter sensitivity. T2K performs multiple oscillation analyses that present both frequentist and Bayesian intervals for the PMNS parameters. For fits including a constraint on \ssqthonethree from reactor data and assuming normal mass ordering T2K measures $\sin^2\theta_{23} = 0.53^{+0.03}_{-0.04}$ and $\Delta{}m^2_{32} = (2.45 \pm 0.07) \times 10^{-3}$ eV$^{2}$c$^{-4}$. The Bayesian analyses show a weak preference for normal mass ordering (89% posterior probability) and the upper $\sin^2\theta_{23}$ octant (80% posterior probability), with a uniform prior probability assumed in both cases. The T2K data exclude CP conservation in neutrino oscillations at the $2\sigma$ level., Comment: Update figure formatting
Published: 2021
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37. Hippocrates: An Open-Source Framework for Advancing Large Language Models in Healthcare.

Author: Emre Can Acikgoz, Osman Batur Ince, Rayene Bench, Arda Anil Boz, Ilker Kesen, Aykut Erdem, and Erkut Erdem
Published: 2024
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38. Human Performance on the AI Legal Case Verdict Classification Task.

Author: Jack Mumford, Katie Atkinson, and Trevor J. M. Bench-Capon
Published: 2023
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39. A Note on Hierarchical Constraints.

Author: Trevor J. M. Bench-Capon
Published: 2023
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40. Dimensions and Precedential Constraint: Factors Deriving from Multiple Dimensions.

Author: Trevor J. M. Bench-Capon and Katie Atkinson
Published: 2023
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41. ANGELIC II: An Improved Methodology for Representing Legal Domain Knowledge.

Author: Katie Atkinson and Trevor J. M. Bench-Capon
Published: 2023
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42. Combining a Legal Knowledge Model with Machine Learning for Reasoning with Legal Cases.

Author: Jack Mumford, Katie Atkinson, and Trevor J. M. Bench-Capon
Published: 2023
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43. Whatever Happened to Hypotheticals?

Author: Trevor J. M. Bench-Capon
Published: 2023
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44. The Role of Intermediate Factors in Explaining Precedential Constraint.

Author: Trevor J. M. Bench-Capon
Published: 2023

45. Safety and utility of mechanical circulatory support in patients with acute myocardial infarction complicated by cardiogenic shock: A systematic review and meta-analysis

Author: Frye, Jesse, Tao, Michael, Gupta, Shivani, Gier, Chad, Masson, Ravi, Rahman, Tahmid, Bench, Travis, Mann, Noelle, and Tam, Edlira
Published: 2024
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46. T2K measurements of muon neutrino and antineutrino disappearance using $3.13\times 10^{21}$ protons on target

Author: Abe, K., Akhlaq, N., Akutsu, R., Ali, A., Alt, C., Andreopoulos, C., Antonova, M., Aoki, S., Arihara, T., Asada, Y., Ashida, Y., Atkin, E. T., Awataguchi, Y., Barker, G. J., Barr, G., Barrow, D., Batkiewicz-Kwasniak, M., Beloshapkin, A., Bench, F., Berardi, V., Berns, L., Bhadra, S., Bolognesi, S., Bonus, T., Bourguille, B., Boyd, S. B., Bravar, A., BravoBerguno, D., Bronner, C., Bron, S., Bubak, A., BuizzaAvanzini, M., Cao, S., Cartwright, S. L., Catanesi, M. G., Cervera, A., Cherdack, D., Christodoulou, G., Cicerchia, M., Coleman, J., Collazuol, G., Cook, L., Coplowe, D., Cudd, A., DeRosa, G., Dealtry, T., Delogu, C. C., Dennis, S. R., Densham, C., DiLodovico, F., Dolan, S., Doyle, T. A., Dumarchez, J., Dunne, P., Eguchi, A., Eklund, L., Emery-Schrenk, S., Ereditato, A., Finch, A. J., Fiorentini, G. A., Francois, C., Friend, M., Fujii, Y., Fukuda, R., Fukuda, Y., Fusshoeller, K., Giganti, C., Gonin, M., Gorin, A., Guigue, M., Hadley, D. R., Hamacher-Baumann, P., Hartz, M., Hasegawa, T., Hassani, S., Hastings, N. C., Hayato, Y., Hiramoto, A., Hogan, M., Holeczek, J., HongVan, N. T., Honjo, T., Iacob, F., Ichikawa, A. K., Ikeda, M., Ishida, T., Ishitsuka, M., Iwamoto, K., Izmaylov, A., Izumi, N., Jakkapu, M., Jamieson, B., Jenkins, S. J., Jesus-Valls, C., Jonsson, P., Junjie, X., Jurj, P. B., Kabirnezhad, M., Kakuno, H., Kameda, J., Abe, S. P. K., Blondel, A., Berguño, D. Bravo, Avanzini, M. Buizza, De Rosa, G., Dergacheva, A., Di Lodovico, F., Harris, D. A., Van, N. T. Hong, Jesús-Valls, C., Jung, C. K., Kasetti, S. P., Kataoka, Y., Katayama, Y., Katori, T., Kearns, E., Khabibullin, M., Khotjantsev, A., Kikawa, T., Kikutani, H., King, S., Kisiel, J., Kobata, T., Kobayashi, T., Koch, L., Konaka, A., Kormos, L. L., Koshio, Y., Kostin, A., Kowalik, K., Kudenko, Y., Kuribayashi, S., Kurjata, R., Kutter, T., Kuze, M., Labarga, L., Lagoda, J., Lamoureux, M., Last, D., Laveder, M., Lawe, M., Litchfield, R. P., Liu, S. L., Longhin, A., Ludovici, L., Lu, X., Lux, T., Machado, L. N., Magaletti, L., Mahn, K., Malek, M., Manly, S., Maret, L., Marino, A. D., Marti-Magro, L., Maruyama, T., Matsubara, T., Matsushita, K., Mauger, C., Mavrokoridis, K., Mazzucato, E., McCauley, N., McElwee, J., McFarland, K. S., McGrew, C., Mefodiev, A., Mezzetto, M., Minamino, A., Mineev, O., Mine, S., Miura, M., Bueno, L. Molina, Moriyama, S., Mueller, Th. A., Munteanu, L., Nagai, Y., Nakadaira, T., Nakahata, M., Nakajima, Y., Nakamura, A., Nakamura, K., Nakano, Y., Nakayama, S., Nakaya, T., Nakayoshi, K., Naseby, C. E. R., Ngoc, T. V., Nguyen, V. Q., Niewczas, K., Nishimura, Y., Noah, E., Nonnenmacher, T. S., Nova, F., Nowak, J., Nugent, J. C., O'Keeffe, H. M., O'Sullivan, L., Odagawa, T., Ogawa, T., Okada, R., Okumura, K., Okusawa, T., Owen, R. A., Oyama, Y., Palladino, V., Paolone, V., Pari, M., Parker, W. C., Parsa, S., Pasternak, J., Pavin, M., Payne, D., Penn, G. C., Pickering, L., Pidcott, C., Pintaudi, G., Pistillo, C., Popov, B., Porwit, K., Posiadala-Zezula, M., Pritchard, A., Quilain, B., Radermacher, T., Radicioni, E., Radics, B., Ratoff, P. N., Riccio, C., Rondio, E., Roth, S., Rubbia, A., Ruggeri, A. C., Ruggles, C., Rychter, A., Sakashita, K., Sánchez, F., Santucci, G., Schloesser, C. M., Scholberg, K., Scott, M., Seiya, Y., Sekiguchi, T., Sekiya, H., Sgalaberna, D., Shaikhiev, A., Shaykina, A., Shiozawa, M., Shorrock, W., Shvartsman, A., Skwarczynski, K., Smy, M., Sobczyk, J. T., Sobel, H., Soler, F. J. P., Sonoda, Y., Spina, R., Suvorov, S., Suzuki, A., Suzuki, S. Y., Suzuki, Y., Sztuc, A. A., Tada, M., Tajima, M., Takeda, A., Takeuchi, Y., Tanaka, H. K., Tanihara, Y., Tani, M., Teshima, N., Thompson, L. F., Toki, W., Touramanis, C., Towstego, T., Tsui, K. M., Tsukamoto, T., Tzanov, M., Uchida, Y., Vagins, M., Valder, S., Vargas, D., Vasseur, G., Vilela, C., Vinning, W. G. S., Vladisavljevic, T., Wachala, T., Walker, J., Walsh, J. G., Wang, Y., Wark, D., Wascko, M. O., Weber, A., Wendell, R., Wilking, M. J., Wilkinson, C., Wilson, J. R., Wood, K., Wret, C., Xia, J., Yamamoto, K., Yanagisawa, C., Yang, G., Yano, T., Yasutome, K., Yershov, N., Yokoyama, M., Yoshida, T., Yoshimoto, Y., Yu, M., Zalewska, A., Zalipska, J., Zaremba, K., Zarnecki, G., Ziembicki, M., Zito, M., and Zsoldos, S.
Subjects: High Energy Physics - Experiment
Abstract: We report measurements by the T2K experiment of the parameters $\theta_{23}$ and $\Delta m^2_{32}$ which govern the disappearance of muon neutrinos and antineutrinos in the three-flavor PMNS neutrino oscillation model at T2K's neutrino energy and propagation distance. Utilizing the ability of the experiment to run with either a mainly neutrino or a mainly antineutrino beam, muon-like events from each beam mode are used to measure these parameters separately for neutrino and antineutrino oscillations. Data taken from $1.49 \times 10^{21}$ protons on target (POT) in neutrino mode and $1.64 \times 10^{21}$ POT in antineutrino mode are used. The best-fit values obtained by T2K were $\sin^2\left(\theta_{23}\right)=0.51^{+0.06}_{-0.07} \left(0.43^{+0.21}_{-0.05}\right)$ and $\Delta m^2_{32}=2.47^{+0.08}_{-0.09} \left(2.50^{+0.18}_{-0.13}\right)$\evmass for neutrinos (antineutrinos). No significant differences between the values of the parameters describing the disappearance of muon neutrinos and antineutrinos were observed. An analysis using an effective two-flavor neutrino oscillation model where the sine of the mixing angle is allowed to take non-physical values larger than 1 is also performed to check the consistency of our data with the three-flavor model. Our data were found to be consistent with a physical value for the mixing angle.
Published: 2020
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47. Towards accurate quantitative photoacoustic imaging: learning vascular blood oxygen saturation in 3D

Author: Bench, Ciaran, Hauptmann, Andreas, and Cox, Ben
Subjects: Physics - Medical Physics, Electrical Engineering and Systems Science - Image and Video Processing
Abstract: Significance: 2D fully convolutional neural networks have been shown capable of producing maps of sO$_2$ from 2D simulated images of simple tissue models. However, their potential to produce accurate estimates in vivo is uncertain as they are limited by the 2D nature of the training data when the problem is inherently 3D, and they have not been tested with realistic images. Aim: To demonstrate the capability of deep neural networks to process whole 3D images and output 3D maps of vascular sO$_2$ from realistic tissue models/images. Approach: Two separate fully convolutional neural networks were trained to produce 3D maps of vascular blood oxygen saturation and vessel positions from multiwavelength simulated images of tissue models. Results: The mean of the absolute difference between the true mean vessel sO$_2$ and the network output for 40 examples was 4.4% and the standard deviation was 4.5%. Conclusions: 3D fully convolutional networks were shown capable of producing accurate sO$_2$ maps using the full extent of spatial information contained within 3D images generated under conditions mimicking real imaging scenarios. This work demonstrates that networks can cope with some of the confounding effects present in real images such as limited-view artefacts, and have the potential to produce accurate estimates in vivo.
Published: 2020

48. Measurements of $\bar{\nu}_{\mu}$ and $\bar{\nu}_{\mu} + \nu_{\mu}$ charged-current cross-sections without detected pions nor protons on water and hydrocarbon at mean antineutrino energy of 0.86 GeV

Author: Abe, K., Akhlaq, N., Akutsu, R., Ali, A., Alt, C., Andreopoulos, C., Anthony, L., Antonova, M., Aoki, S., Ariga, A., Arihara, T., Asada, Y., Ashida, Y., Atkin, E. T., Awataguchi, Y., Ban, S., Barbi, M., Barker, G. J., Barr, G., Barrow, D., Barry, C., Batkiewicz-Kwasniak, M., Beloshapkin, A., Bench, F., Berardi, V., Berkman, S., Berns, L., Bhadra, S., Bienstock, S., Blondel, A., Bolognesi, S., Bonus, T., Bourguille, B., Boyd, S. B., Brailsford, D., Bravar, A., Berguño, D. Bravo, Bronner, C., Bron, S., Bubak, A., Avanzini, M. Buizza, Calcutt, J., Campbell, T., Cao, S., Cartwright, S. L., Catanesi, M. G., Cervera, A., Chappell, A., Checchia, C., Cherdack, D., Chikuma, N., Christodoulou, G., Cicerchia, M., Coleman, J., Collazuol, G., Cook, L., Coplowe, D., Cudd, A., Dabrowska, A., De Rosa, G., Dealtry, T., Denner, P. F., Dennis, S. R., Densham, C., Di Lodovico, F., Dokania, N., Dolan, S., Doyle, T. A., Drapier, O., Dumarchez, J., Dunne, P., Eguchi, A., Eklund, L., Emery-Schrenk, S., Ereditato, A., Fernandez, P., Feusels, T., Finch, A. J., Fiorentini, G. A., Fiorillo, G., Francois, C., Friend, M., Fujii, Y., Fujita, R., Fukuda, D., Fukuda, R., Fukuda, Y., Fusshoeller, K., Gameil, K., Giganti, C., Golan, T., Gonin, M., Gorin, A., Guigue, M., Hadley, D. R., Haigh, J. T., Hamacher-Baumann, P., Hartz, M., Hasegawa, T., Hassani, S., Hastings, N. C., Hayashino, T., Hayato, Y., Hiramoto, A., Hogan, M., Holeczek, J., Van, N. T. Hong, Honjo, T., Iacob, F., Ichikawa, A. K., Ikeda, M., Ishida, T., Ishii, T., Ishitsuka, M., Iwamoto, K., Izmaylov, A., Izumi, N., Jakkapu, M., Jamieson, B., Jenkins, S. J., Jesús-Valls, C., Jiang, M., Johnson, S., Jonsson, P., Jung, C. K., Junjie, X., Kabirnezhad, M., Kaboth, A. C., Kajita, T., Kakuno, H., Kameda, J., Karlen, D., Kasetti, K., Kataoka, Y., Katayama, Y., Katori, T., Kato, Y., Kearns, E., Khabibullin, M., Khotjantsev, A., Kikawa, T., Kikutani, H., Kim, H., Kim, J., King, S., Kisiel, J., Knight, A., Knox, A., Kobata, T., Kobayashi, T., Koch, L., Koga, T., Konaka, A., Kormos, L. L., Koshio, Y., Kostin, A., Kowalik, K., Kubo, H., Kudenko, Y., Kukita, N., Kuribayashi, S., Kurjata, R., Kutter, T., Kuze, M., Labarga, L., Lagoda, J., Lamoureux, M., Last, D., Laveder, M., Lawe, M., Licciardi, M., Lindner, T., Litchfield, R. P., Liu, S. L., Li, X., Longhin, A., Ludovici, L., Lu, X., Lux, T., Machado, L. N., Magaletti, L., Mahn, K., Malek, M., Manly, S., Maret, L., Marino, A. D., Marti-Magro, L., Martin, J. F., Maruyama, T., Matsubara, T., Matsushita, K., Matveev, V., Mauger, C., Mavrokoridis, K., Mazzucato, E., McCarthy, M., McCauley, N., McElwee, J., McFarland, K. S., McGrew, C., Mefodiev, A., Metelko, C., Mezzetto, M., Minamino, A., Mineev, O., Mine, S., Miura, M., Bueno, L. Molina, Moriyama, S., Morrison, J., Mueller, Th. A., Munteanu, L., Murphy, S., Nagai, Y., Nakadaira, T., Nakahata, M., Nakajima, Y., Nakamura, A., Nakamura, K. G., Nakamura, K., Nakayama, S., Nakaya, T., Nakayoshi, K., Nantais, C., Naseby, C. E. R., Ngoc, T. V., Niewczas, K., Nishikawa, K., Nishimura, Y., Noah, E., Nonnenmacher, T. S., Nova, F., Novella, P., Nowak, J., Nugent, J. C., O'Keeffe, H. M., O'Sullivan, L., Odagawa, T., Ogawa, T., Okada, R., Okumura, K., Okusawa, T., Oser, S. M., Owen, R. A., Oyama, Y., Palladino, V., Palomino, J. L., Paolone, V., Pari, M., Parker, W. C., Parsa, S., Pasternak, J., Paudyal, P., Pavin, M., Payne, D., Penn, G. C., Pickering, L., Pidcott, C., Pintaudi, G., Guerra, E. S. Pinzon, Pistillo, C., Popov, B., Porwit, K., Posiadala-Zezula, M., Pritchard, A., Quilain, B., Radermacher, T., Radicioni, E., Radics, B., Ratoff, P. N., Reinherz-Aronis, E., Riccio, C., Rondio, E., Roth, S., Rubbia, A., Ruggeri, A. C., Ruggles, C., Rychter, A., Sakashita, K., Sánchez, F., Santucci, G., Schloesser, C. M., Scholberg, K., Schwehr, J., Scott, M., Seiya, Y., Sekiguchi, T., Sekiya, H., Sgalaberna, D., Shah, R., Shaikhiev, A., Shaker, F., Shaykina, A., Shiozawa, M., Shorrock, W., Shvartsman, A., Smirnov, A., Smy, M., Sobczyk, J. T., Sobel, H., Soler, F. J. P., Sonoda, Y., Steinmann, J., Suvorov, S., Suzuki, A., Suzuki, S. Y., Suzuki, Y., Sztuc, A. A., Tada, M., Tajima, M., Takeda, A., Takeuchi, Y., Tanaka, H. K., Tanaka, H. A., Tanaka, S., Tanihara, Y., Teshima, N., Thompson, L. F., Toki, W., Touramanis, C., Towstego, T., Tsui, K. M., Tsukamoto, T., Tzanov, M., Uchida, Y., Uno, W., Vagins, M., Valder, S., Vallari, Z., Vargas, D., Vasseur, G., Vilela, C., Vinning, W. G. S., Vladisavljevic, T., Volkov, V. V., Wachala, T., Walker, J., Walsh, J. G., Wang, Y., Wark, D., Wascko, M. O., Weber, A., Wendell, R., Wilking, M. J., Wilkinson, C., Wilson, J. R., Wilson, R. J., Wood, K., Wret, C., Yamada, Y., Yamamoto, K., Yanagisawa, C., Yang, G., Yano, T., Yasutome, K., Yen, S., Yershov, N., Yokoyama, M., Yoshida, T., Yu, M., Zalewska, A., Zalipska, J., Zaremba, K., Zarnecki, G., Ziembicki, M., Zimmerman, E. D., Zito, M., Zsoldos, S., and Zykova, A.
Subjects: High Energy Physics - Experiment
Abstract: We report measurements of the flux-integrated $\bar{\nu}_\mu$ and $\bar{\nu}_\mu+\nu_\mu$ charged-current cross-sections on water and hydrocarbon targets using the T2K anti-neutrino beam, with a mean neutrino energy of 0.86 GeV. The signal is defined as the (anti-)neutrino charged-current interaction with one induced $\mu^\pm$ and no detected charged pion nor proton. These measurements are performed using a new WAGASCI module recently added to the T2K setup in combination with the INGRID Proton module. The phase space of muons is restricted to the high-detection efficiency region, $p_{\mu}>400~{\rm MeV}/c$ and $\theta_{\mu}<30^{\circ}$, in the laboratory frame. Absence of pions and protons in the detectable phase space of "$p_{\pi}>200~{\rm MeV}/c$ and $\theta_{\pi}<70^{\circ}$", and "$p_{\rm p}>600~{\rm MeV}/c$ and $\theta_{\rm p}<70^{\circ}$" is required. In this paper, both of the $\bar{\nu}_\mu$ cross-sections and $\bar{\nu}_\mu+\nu_\mu$ cross-sections on water and hydrocarbon targets, and their ratios are provided by using D'Agostini unfolding method. The results of the integrated $\bar{\nu}_\mu$ cross-section measurements over this phase space are $\sigma_{\rm H_{2}O}\,=\,(1.082\pm0.068(\rm stat.)^{+0.145}_{-0.128}(\rm syst.)) \times 10^{-39}~{\rm cm^{2}/nucleon}$, $\sigma_{\rm CH}\,=\,(1.096\pm0.054(\rm stat.)^{+0.132}_{-0.117}(\rm syst.)) \times 10^{-39}~{\rm cm^{2}/nucleon}$, and $\sigma_{\rm H_{2}O}/\sigma_{\rm CH} = 0.987\pm0.078(\rm stat.)^{+0.093}_{-0.090}(\rm syst.)$. The $\bar{\nu}_\mu+\nu_\mu$ cross-section is $\sigma_{\rm H_{2}O} = (1.155\pm0.064(\rm stat.)^{+0.148}_{-0.129}(\rm syst.)) \times 10^{-39}~{\rm cm^{2}/nucleon}$, $\sigma_{\rm CH}\,=\,(1.159\pm0.049(\rm stat.)^{+0.129}_{-0.115}(\rm syst.)) \times 10^{-39}~{\rm cm^{2}/nucleon}$, and $\sigma_{\rm H_{2}O}/\sigma_{\rm CH}\,=\,0.996\pm0.069(\rm stat.)^{+0.083}_{-0.078}(\rm syst.)$.
Published: 2020
Full Text: View/download PDF

49. Simultaneous measurement of the muon neutrino charged-current cross section on oxygen and carbon without pions in the final state at T2K

Author: Abe, K., Akhlaq, N., Akutsu, R., Ali, A., Alt, C., Andreopoulos, C., Anthony, L., Antonova, M., Aoki, S., Ariga, A., Arihara, T., Asada, Y., Ashida, Y., Atkin, E. T., Awataguchi, Y., Ban, S., Barbi, M., Barker, G. J., Barr, G., Barrow, D., Batkiewicz-Kwasniak, M., Beloshapkin, A., Bench, F., Berardi, V., Berns, L., Bhadra, S., Bienstock, S., Bolognesi, S., Bonus, T., Bourguille, B., Boyd, S. B., Bravar, A., Berguño, D. Bravo, Bronner, C., Bron, S., Bubak, A., Avanzini, M. Buizza, Campbell, T., Cao, S., Cartwright, S. L., Catanesi, M. G., Cervera, A., Cherdack, D., Chikuma, N., Christodoulou, G., Cicerchia, M., Coleman, J., Collazuol, G., Cook, L., Coplowe, D., Cudd, A., Dabrowska, A., De Rosa, G., Dealtry, T., Dennis, S. R., Densham, C., Di Lodovico, F., Dokania, N., Dolan, S., Doyle, T. A., Drapier, O., Dumarchez, J., Dunne, P., Eguchi, A., Eklund, L., Emery-Schrenk, S., Ereditato, A., Finch, A. J., Fiorentini, G. A., Fiorillo, G., Francois, C., Friend, M., Fujii, Y., Fujita, R., Fukuda, D., Fukuda, R., Fukuda, Y., Fusshoeller, K., Giganti, C., Gonin, M., Gorin, A., Guigue, M., Hadley, D. R., Haigh, J. T., Hamacher-Baumann, P., Hartz, M., Hasegawa, T., Hassani, S., Hastings, N. C., Hayato, Y., Hiramoto, A., Hogan, M., Holeczek, J., Van, N. T. Hong, Honjo, T., Iacob, F., Ichikawa, A. K., Ikeda, M., Ishida, T., Ishitsuka, M., Iwamoto, K., Izmaylov, A., Izumi, N., Jakkapu, M., Jamieson, B., Jenkins, S. J., Jesús-Valls, C., Jiang, M., Jonsson, P., Jung, C. K., Junjie, X., Jurj, P. B., Kabirnezhad, M., Kaboth, A. C., Kajita, T., Kakuno, H., Kameda, J., Karlen, D., Kasetti, S. P., Kataoka, Y., Katayama, Y., Katori, T., Kato, Y., Kearns, E., Khabibullin, M., Khotjantsev, A., Kikawa, T., Kikutani, H., Kim, H., King, S., Kisiel, J., Knight, A., Kobata, T., Kobayashi, T., Koch, L., Koga, T., Konaka, A., Kormos, L. L., Koshio, Y., Kostin, A., Kowalik, K., Kubo, H., Kudenko, Y., Kukita, N., Kuribayashi, S., Kurjata, R., Kutter, T., Kuze, M., Labarga, L., Lagoda, J., Lamoureux, M., Last, D., Lawe, M., Licciardi, M., Litchfield, R. P., Liu, S. L., Li, X., Longhin, A., Ludovici, L., Lu, X., Lux, T., Machado, L. N., Magaletti, L., Mahn, K., Malek, M., Manly, S., Maret, L., Marino, A. D., Marti-Magro, L., Maruyama, T., Matsubara, T., Matsushita, K., Matveev, V., Mauger, C., Mavrokoridis, K., Mazzucato, E., McCauley, N., McElwee, J., McFarland, K. S., McGrew, C., Mefodiev, A., Metelko, C., Mezzetto, M., Minamino, A., Mineev, O., Mine, S., Miura, M., Bueno, L. Molina, Moriyama, S., Mueller, Th. A., Munteanu, L., Murphy, S., Nagai, Y., Nakadaira, T., Nakahata, M., Nakajima, Y., Nakamura, A., Nakamura, K., Nakayama, S., Nakaya, T., Nakayoshi, K., Naseby, C. E. R., Ngoc, T. V., Niewczas, K., Nishikawa, K., Nishimura, Y., Noah, E., Nonnenmacher, T. S., Nova, F., Novella, P., Nowak, J., Nugent, J. C., O'Keeffe, H. M., O'Sullivan, L., Odagawa, T., Ogawa, T., Okada, R., Okumura, K., Okusawa, T., Oser, S. M., Owen, R. A., Oyama, Y., Palladino, V., Paolone, V., Pari, M., Parker, W. C., Parsa, S., Pasternak, J., Pavin, M., Payne, D., Penn, G. C., Pickering, L., Pidcott, C., Pintaudi, G., Pistillo, C., Popov, B., Porwit, K., Posiadala-Zezula, M., Pritchard, A., Quilain, B., Radermacher, T., Radicioni, E., Radics, B., Ratoff, P. N., Riccio, C., Rondio, E., Roth, S., Rubbia, A., Ruggeri, A. C., Ruggles, C., Rychter, A., Sakashita, K., Sánchez, F., Santucci, G., Schloesser, C. M., Scholberg, K., Scott, M., Seiya, Y., Sekiguchi, T., Sekiya, H., Sgalaberna, D., Shaikhiev, A., Shaykina, A., Shiozawa, M., Shorrock, W., Shvartsman, A., Smy, M., Sobczyk, J. T., Sobel, H., Soler, F. J. P., Sonoda, Y., Suvorov, S., Suzuki, A., Suzuki, S. Y., Suzuki, Y., Sztuc, A. A., Tada, M., Tajima, M., Takeda, A., Takeuchi, Y., Tanaka, H. K., Tanaka, H. A., Tanaka, S., Tanihara, Y., Tani, M., Teshima, N., Thompson, L. F., Toki, W., Touramanis, C., Towstego, T., Tsui, K. M., Tsukamoto, T., Tzanov, M., Uchida, Y., Vagins, M., Valder, S., Vallari, Z., Vargas, D., Vasseur, G., Vinning, W. G. S., Vladisavljevic, T., Volkov, V. V., Wachala, T., Walker, J., Walsh, J. G., Wang, Y., Wark, D., Wascko, M. O., Weber, A., Wendell, R., Wilking, M. J., Wilkinson, C., Wilson, J. R., Wood, K., Wret, C., Yamamoto, K., Yanagisawa, C., Yang, G., Yano, T., Yasutome, K., Yershov, N., Yokoyama, M., Yoshida, T., Yu, M., Zalewska, A., Zalipska, J., Zaremba, K., Zarnecki, G., Ziembicki, M., Zimmerman, E. D., Zito, M., Zsoldos, S., and Zykova, A.
Subjects: High Energy Physics - Experiment
Abstract: This paper reports the first simultaneous measurement of the double differential muon neutrino charged-current cross section on oxygen and carbon without pions in the final state as a function of the outgoing muon kinematics, made at the ND280 off-axis near detector of the T2K experiment. The ratio of the oxygen and carbon cross sections is also provided to help validate various models' ability to extrapolate between carbon and oxygen nuclear targets, as is required in T2K oscillation analyses. The data are taken using a neutrino beam with an energy spectrum peaked at 0.6 GeV. The extracted measurement is compared with the prediction from different Monte Carlo neutrino-nucleus interaction event generators, showing particular model separation for very forward-going muons. Overall, of the models tested, the result is best described using Local Fermi Gas descriptions of the nuclear ground state with RPA suppression.
Published: 2020
Full Text: View/download PDF

50. Measurement of the charged-current electron (anti-)neutrino inclusive cross-sections at the T2K off-axis near detector ND280

Author: Abe, K., Akhlaq, N., Akutsu, R., Ali, A., Alt, C., Andreopoulos, C., Anthony, L., Antonova, M., Aoki, S., Ariga, A., Arihara, T., Asada, Y., Ashida, Y., Atkin, E. T., Awataguchi, Y., Ban, S., Barbi, M., Barker, G. J., Barr, G., Barrow, D., Barry, C., Batkiewicz-Kwasniak, M., Beloshapkin, A., Bench, F., Berardi, V., Berns, L., Bhadra, S., Bienstock, S., Blondel, A., Bolognesi, S., Bonus, T., Bourguille, B., Boyd, S. B., Brailsford, D., Bravar, A., Berguño, D. Bravo, Bronner, C., Bron, S., Bubak, A., Avanzini, M. Buizza, Calcutt, J., Campbell, T., Cao, S., Cartwright, S. L., Catanesi, M. G., Cervera, A., Chappell, A., Checchia, C., Cherdack, D., Chikuma, N., Christodoulou, G., Cicerchia, M., Coleman, J., Collazuol, G., Cook, L., Coplowe, D., Cudd, A., Dabrowska, A., De Rosa, G., Dealtry, T., Denner, P. F., Dennis, S. R., Densham, C., Di Lodovico, F., Dokania, N., Dolan, S., Doyle, T. A., Drapier, O., Dumarchez, J., Dunne, P., Eguchi, A., Eklund, L., Emery-Schrenk, S., Ereditato, A., Fernandez, P., Feusels, T., Finch, A. J., Fiorentini, G. A., Fiorillo, G., Francois, C., Friend, M., Fujii, Y., Fujita, R., Fukuda, D., Fukuda, R., Fukuda, Y., Fusshoeller, K., Giganti, C., Golan, T., Gonin, M., Gorin, A., Guigue, M., Hadley, D. R., Haigh, J. T., Hamacher-Baumann, P., Hartz, M., Hasegawa, T., Hassani, S., Hastings, N. C., Hayashino, T., Hayato, Y., Hiramoto, A., Hogan, M., Holeczek, J., Van, N. T. Hong, Honjo, T., Iacob, F., Ichikawa, A. K., Ikeda, M., Ishida, T., Ishii, T., Ishitsuka, M., Iwamoto, K., Izmaylov, A., Izumi, N., Jakkapu, M., Jamieson, B., Jenkins, S. J., Jesús-Valls, C., Jiang, M., Johnson, S., Jonsson, P., Jung, C. K., Jurj, P. B., Kabirnezhad, M., Kaboth, A. C., Kajita, T., Kakuno, H., Kameda, J., Karlen, D., Kasetti, S. P., Kataoka, Y., Katayama, Y., Katori, T., Kato, Y., Kearns, E., Khabibullin, M., Khotjantsev, A., Kikawa, T., Kikutani, H., Kim, H., King, S., Kisiel, J., Knight, A., Knox, A., Kobata, T., Kobayashi, T., Koch, L., Koga, T., Konaka, A., Kormos, L. L., Koshio, Y., Kostin, A., Kowalik, K., Kubo, H., Kudenko, Y., Kukita, N., Kuribayashi, S., Kurjata, R., Kutter, T., Kuze, M., Labarga, L., Lagoda, J., Lamoureux, M., Last, D., Laveder, M., Lawe, M., Licciardi, M., Lindner, T., Litchfield, R. P., Liu, S. L., Li, X., Longhin, A., Ludovici, L., Lu, X., Lux, T., Machado, L. N., Magaletti, L., Mahn, K., Malek, M., Manly, S., Maret, L., Marino, A. D., Marti-Magro, L., Martin, J. F., Maruyama, T., Matsubara, T., Matsushita, K., Matveev, V., Mauger, C., Mavrokoridis, K., Mazzucato, E., McCarthy, M., McCauley, N., McElwee, J., McFarland, K. S., McGrew, C., Mefodiev, A., Metelko, C., Mezzetto, M., Minamino, A., Mineev, O., Mine, S., Miura, M., Bueno, L. Molina, Moriyama, S., Morrison, J., Mueller, Th. A., Munteanu, L., Murphy, S., Nagai, Y., Nakadaira, T., Nakahata, M., Nakajima, Y., Nakamura, A., Nakamura, K. G., Nakamura, K., Nakano, Y., Nakayama, S., Nakaya, T., Nakayoshi, K., Nantais, C., Naseby, C. E. R., Ngoc, T. V., Niewczas, K., Nishikawa, K., Nishimura, Y., Noah, E., Nonnenmacher, T. S., Nova, F., Novella, P., Nowak, J., Nugent, J. C., O'Keeffe, H. M., O'Sullivan, L., Odagawa, T., Ogawa, T., Okada, R., Okumura, K., Okusawa, T., Oser, S. M., Owen, R. A., Oyama, Y., Palladino, V., Palomino, J. L., Paolone, V., Pari, M., Parker, W. C., Parsa, S., Pasternak, J., Paudyal, P., Pavin, M., Payne, D., Penn, G. C., Pickering, L., Pidcott, C., Pintaudi, G., Guerra, E. S. Pinzon, Pistillo, C., Popov, B., Porwit, K., Posiadala-Zezula, M., Pritchard, A., Quilain, B., Radermacher, T., Radicioni, E., Radics, B., Ratoff, P. N., Reinherz-Aronis, E., Riccio, C., Rondio, E., Roth, S., Rubbia, A., Ruggeri, A. C., Ruggles, C., Rychter, A., Sakashita, K., Sánchez, F., Santucci, G., Schloesser, C. M., Scholberg, K., Schwehr, J., Scott, M., Seiya, Y., Sekiguchi, T., Sekiya, H., Sgalaberna, D., Shah, R., Shaikhiev, A., Shaker, F., Shaykina, A., Shiozawa, M., Shorrock, W., Shvartsman, A., Skwarczynski, K., Smirnov, A., Smy, M., Sobczyk, J. T., Sobel, H., Soler, F. J. P., Sonoda, Y., Steinmann, J., Suvorov, S., Suzuki, A., Suzuki, S. Y., Suzuki, Y., Sztuc, A. A., Tada, M., Tajima, M., Takeda, A., Takeuchi, Y., Tanaka, H. K., Tanaka, H. A., Tanaka, S., Tanihara, Y., Tani, M., Teshima, N., Thompson, L. F., Toki, W., Touramanis, C., Towstego, T., Tsui, K. M., Tsukamoto, T., Tzanov, M., Uchida, Y., Vagins, M., Valder, S., Vallari, Z., Vargas, D., Vasseur, G., Vilela, C., Vinning, W. G. S., Vladisavljevic, T., Volkov, V. V., Wachala, T., Walker, J., Walsh, J. G., Wang, Y., Wark, D., Wascko, M. O., Weber, A., Wendell, R., Wilking, M. J., Wilkinson, C., Wilson, J. R., Wilson, R. J., Wood, K., Wret, C., Xia, J., Yamada, Y., Yamamoto, K., Yanagisawa, C., Yang, G., Yano, T., Yasutome, K., Yen, S., Yershov, N., Yokoyama, M., Yoshida, T., Yu, M., Zalewska, A., Zalipska, J., Zaremba, K., Zarnecki, G., Ziembicki, M., Zimmerman, E. D., Zito, M., Zsoldos, S., and Zykova, A.
Subjects: High Energy Physics - Experiment
Abstract: The electron (anti-)neutrino component of the T2K neutrino beam constitutes the largest background in the measurement of electron (anti-)neutrino appearance at the far detector. The electron neutrino scattering is measured directly with the T2K off-axis near detector, ND280. The selection of the electron (anti-)neutrino events in the plastic scintillator target from both neutrino and anti-neutrino mode beams is discussed in this paper. The flux integrated single differential charged-current inclusive electron (anti-)neutrino cross-sections, $d\sigma/dp$ and $d\sigma/d\cos(\theta)$, and the total cross-sections in a limited phase-space in momentum and scattering angle ($p > 300$ MeV/c and $\theta \leq 45^{\circ}$) are measured using a binned maximum likelihood fit and compared to the neutrino Monte Carlo generator predictions, resulting in good agreement.
Published: 2020
Full Text: View/download PDF

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