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Adoption of renewable energy sources and sustainable performance in palestinian industrial and commercial sectors with governmental role as a moderator: An explanatory approach

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Journal of Open Innovation: Technology, Market, and Complexity 2023年第3期9卷

作者： Salem, Isra’ Saleh, Yahya Alsayed, Mohammed F. Assaf, Ramiz Kanan, Mohammad Musleh Al-Sartawi, Abdalmuttaleb M.A. BinSaddig, Ruaa Engineering Management Master Program Faculty of Graduate Studies An-Najah National University P.O. Box 7 Nablus Palestine Department of Industrial Engineering An-Najah National University P.O. Box 7 Nablus Palestine Department of Energy Engineering and Environment An-Najah National University P.O. Box 7 Nablus Palestine Industrial Engineering Department University of Business and Technology (UBT) Mecca Jeddah Saudi Arabia Accounting Finance and Banking Department Ahlia University Bahrain Dean of Scientific Research University of Business and Technology Saudi Arabia

Renewable energy has attained enormous attention in recent years due to the exhaustion of many energy resources, and the pollution caused by fossil fuels. However, the adoption of renewable energy sources (RESs) is a complicated process influenced by multifarious factors. This study aims to investigate factors influencing the adoption of RESs by the Palestinian industrial and commercial sectors and their effect of this adoption on sustainable performance, besides examining if the government plays a role in moderating the relationship between the adoption of RESs and such sustainable performance. To this end, a quantitative method was used to collect data through questionnaires from 100 top managers in the Palestinian commercial and industrial sectors. The data analysis was conducted using the Smart PLS software to test the formulated hypotheses. The findings support the positive relationship between the adoption of RESs and sustainable performance. There is also a positive relationship between the adoption of RESs and the government's role. However, the relationship between the government's role and sustainable performance is not established, but the government's role is found to be a moderator between adopting RESs and sustainable performance. © 2023 The Authors

关键词： Government's role Industrial and commercial sectors Renewable energy sources (RESs) Sustainable performance

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Scenario Assessment of Neodymium and Cobalt Recycling in ASEAN Countries Based on a Dynamic Material Flow Analysis

SSRN

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SSRN 2023年

作者： Rustandi, Rendi Ahmad Morimoto, Shinichirou Borrirukwisitsak, Siriporn Khwamsawat, Kannika Chaipurimas, Supaluk Leewattananukul, Surachai Khaodhiar, Sutha Systems and Information Engineering Graduate School of Science and Technology University of Tsukuba Ibaraki Tsukuba305-8573 Japan Department of Energy and Environment National Institute of Advanced Industrial Science and Technology Ibaraki Tsukuba305-8569 Japan Department of Environmental Science Faculty of Science Silpakorn University Nakhon Pathom73000 Thailand Center of Excellence on Hazardous Substance Management Chulalongkorn University Bangkok10330 Thailand

Tackling global greenhouse gas (GHG) emissions warrants a radical shift to low-carbon technologies, including batteries and permanent magnets. This shift will increase demand for critical raw materials (CRMs). This study offers dynamic material flow analysis (MFA) to address uncertainties associated with the sustainable supply of neodymium (Nd) and cobalt (Co): CRMs used in NdFeB magnets and lithium-ion batteries in ASEAN. Annual maximum and minimum scenario estimates were conducted for demand and waste of CRMs and CO2 emissions of recycled versus virgin materials. Based on the results, in 2050, 3,209 ton/y of Nd will be discarded, of which 25.3% will be accumulated as hibernating stock. Moreover, 33.79% of Co will be kept as hibernating stock. Recycling NdFeB magnets and batteries could reduce CO2 emissions up to 1,536 kton CO2-Eq/y and 313.5 kton CO2-Eq/y, respectively, by 2050. The proposed dynamic MFA is a useful foundation for the creation of effective global standards. © 2023, The Authors. All rights reserved.

关键词： Carbon dioxide

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Fair Patient Model: Mitigating Bias in the Patient Representation Learned from the Electronic Health Records

arXiv

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arXiv 2023年

作者： Sivarajkumar, Sonish Huang, Yufei Wang, Yanshan Intelligent Systems Program School of Computing and Information University of Pittsburgh PittsburghPA United States Department of Electrical and Computer Engineering University of Pittsburgh PittsburghPA United States Department of Health Information Management University of Pittsburgh PittsburghPA United States Department of Biomedical Informatics University of Pittsburgh PittsburghPA United States Clinical and Translational Science Institute University of Pittsburgh PittsburghPA United States

Objective: To pre-train fair and unbiased patient representations from Electronic Health Records (EHRs) using a novel weighted loss function that reduces bias and improves fairness in deep representation learning models. Methods: We defined a new loss function, called weighted loss function, in the deep representation learning model to balance the importance of different groups of patients and features. We applied the proposed model, called Fair Patient Model (FPM), to a sample of 34,739 patients from the MIMIC-III dataset and learned patient representations for four clinical outcome prediction tasks. Results: FPM outperformed the baseline models in terms of three fairness metrics: demographic parity, equality of opportunity difference, and equalized odds ratio. FPM also achieved comparable predictive performance with the baselines, with an average accuracy of 0.7912. Feature analysis revealed that FPM captured more information from clinical features than the baselines. Conclusion: FPM is a novel method to pre-train fair and unbiased patient representations from EHR data using a weighted loss function. The learned representations can be used for various downstream tasks in healthcare and can be extended to other domains where bias and fairness are important. Copyright © 2023, The Authors. All rights reserved.

关键词： Deep learning

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Electromobility strategy on emerging economies: Beyond selling electric vehicles

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Cleaner Energy systems 2024年 9卷

作者： Velho, Sérgio Roberto Knorr Vanderlinde, Artur Santana Guedes Almeida, Antônio Henrique Aguiar Barbalho, Sanderson César Macêdo Ministry of Development Industry Commerce and Services University of Brasília Esplanada dos Ministérios Block J – 5th-floor/DF Brasília 70053-900 Brazil Production Engineering Department Faculty of Technology University of Brasília Darcy Ribeiro University Campus Federal District Brasília 70910-900 Brazil Production Engineering Department Graduate Program in Mechatronic Systems (PPMEC) Faculty of Technology University of Brasília Darcy Ribeiro University Campus Federal District Brasília 70910-900 Brazil

Electromobility (EM) has emerged as a promising solution to achieve carbon neutrality goals by replacing traditional fossil fuel-powered transportation with electric vehicles (EVs). This sustainable transportation option significantly reduces energy consumption and eliminates greenhouse gas emissions, contributing to mitigating climate change and improving air quality. While some countries have implemented strategies to promote EM adoption, emerging economies like Brazil face complex challenges. This research employs Q-methodology to explore the viewpoints and opinions of Brazilian specialists in the field of EM, identifying challenges and opportunities for successful adoption. The study also examines the broader implications for emerging countries and their automotive industries. The findings emphasize the importance of addressing EV costs, propulsion technologies, and the need for government incentives and policies. Additionally, the research highlights the role of education and urban mobility in promoting EM. While the study offers valuable insights, it acknowledges limitations in the sample and suggests future research directions. © 2024 The Authors

关键词： Automotive value chain Electric vehicles Electromobility Q-methodology Urban mobility

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Grapenet_Lv1 for the Prediction of Optimum Hand-Picking Time of Nagano Purple Grapes

SSRN

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SSRN 2025年

作者： Islam, Md. Parvez Shinagawa, K. Hatou, K. Abdurrakhman, Arief Dian, K. Department of Biomechanical Systems Faculty of Agriculture Ehime University 3-5-7 Tarumi Matsuyama790-8566 Japan United Graduate School of Agriculture Ehime University 3-5-7 Tarumi Matsuyama790-8566 Japan Department of Instrumentation Engineering Institut Teknologi Sepuluh Nopember Surabaya60111 Indonesia Business Mathematics Program Study School of Applied STEM Universitas Prasetiya Mulya BSD Campus BSD City Kav. Edutown I.1 Tangerang15339 Indonesia Indonesia

We investigated the optimum hand-picking time of Nagano Purple, a rare Japanese table grape variety. The color sensitivity between pure red–purple–black and pure purple–black makes it difficult for farmers to harvest these fruits at the right time while maintaining high sweetness level. We manually extracted 13 color parameters, namely, X, Y, Z, x, y, L*, a*, b*, L, a, b, C*, and h, from 355 grape skin samples using a colorimeter, which is a time-consuming and expensive process. In addition, we developed a 15-layer shallow long short-term memory (LSTM) and bidirectional long short-term memory (BLSTM) neural network, namely, GrapeNet_Lv1, with a learnable parameter of 1.39E+06. This network is compact and requires low computational cost for training. Furthermore, it has the ability to prevent the problems of vanishing gradient and overfitting. The combination of all the 13 aforementioned parameters yielded promising results in predicting color and sweetness levels, with test accuracies of 0.83 and 0.76, respectively. In the prediction of color level, our proposed network GrapeNet_Lv1 achieves a high validation accuracy of 0.92, F1 score of 0.88, recall of 0.87, low validation loss of 0.39, and RMSE of 0.31. However, in the prediction of sweetness level, GrapeNet_Lv1 achieves a relatively low validation accuracy of 0.79, F1 score of 0.70, recall of 0.69, high validation loss of 0.72, and RMSE of 0.33. Further research can help improve the accuracy. GrapeNet_Lv1 can be applied to other crops, where, predicting the whose optimal hand-picking time is difficult to predict based on color recognition. Keywords: Neural network;LSTM-BLSTM;Nagano Purple, color, sweetness © 2025, The Authors. All rights reserved.

关键词： Long short-term memory

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Cosmic ray mass composition measurement with the TALE hybrid detector 38

Cosmic ray mass composition measurement with the TALE hybrid...

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38th International Cosmic Ray Conference, ICRC 2023

作者： Fujita, Keitaro Abbasi, R.U. Abe, Y. Abu-Zayyad, T. Allen, M. Arai, Y. Arimura, R. Barcikowski, E. Belz, J.W. Bergman, D.R. Blake, S.A. Buckland, I. Cheon, B.G. Chikawa, M. Fedynitch, A. Fujii, T. Fujisue, K. Fujita, K. Fujiwara, R. Fukushima, M. Furlich, G. Gerber, Z. Globus, N. Hanlon, W. Hayashida, N. He, H. Hibi, R. Hibino, K. Higuchi, R. Honda, K. Ikeda, D. Inoue, N. Ishii, T. Ito, H. Ivanov, D. Iwasaki, A. Jeong, H.M. Jeong, S. Jui, C.C.H. Kadota, K. Kakimoto, F. Kalashev, O. Kasahara, K. Kasami, S. Kawakami, S. Kawata, K. Kharuk, I. Kido, E. Kim, H.B. Kim, J.H. Kim, J.H. Kim, S.W. Kimura, Y. Komae, I. Komori, K. Kusumori, Y. Kuznetsov, M. Kwon, Y.J. Lee, K.H. Lee, M.J. Lubsandorzhiev, B. Lundquist, J.P. Matsuyama, T. Matthews, J.A. Matthews, J.N. Mayta, R. Miyashita, K. Mizuno, K. Mori, M. Murakami, M. Myers, I. Nagataki, S. Nakai, K. Nakamura, T. Nishio, E. Nonaka, T. Ogio, S. Ohoka, H. Okazaki, N. Oku, Y. Okuda, T. Omura, Y. Onishi, M. Ono, M. Oshima, A. Oshima, H. Ozawa, S. Park, I.H. Park, K.Y. Potts, M. Pshirkov, M.S. Remington, J. Rodriguez, D.C. Rott, C. Rubtsov, G.I. Ryu, D. Sagawa, H. Saito, R. Sakaki, N. Sako, T. Sakurai, N. Sato, D. Sato, K. Sato, S. Sekino, K. Shah, P.D. Shibata, N. Shibata, T. Shikita, J. Shimodaira, H. Shin, B.K. Shin, H.S. Shinto, D. Smith, J.D. Sokolsky, P. Stokes, B.T. Stroman, T.A. Takagi, Y. Takahashi, K. Takamura, M. Takeda, M. Takeishi, R. Taketa, A. Takita, M. Tameda, Y. Tanaka, K. Tanaka, M. Thomas, S.B. Thomson, G.B. Tinyakov, P. Tkachev, I. Tokuno, H. Tomida, T. Troitsky, S. Tsuda, R. Tsunesada, Y. Udo, S. Urban, F. Vaiman, I.A. Warren, D. Wong, T. Yamazaki, K. Yashiro, K. Yoshida, F. Zhezher, Y. Zundel, Z. Institute for Cosmic Ray Research The University of Tokyo 5-1-5 Kashiwa-no-Ha Chiba Kashiwa Japan Department of Physics Loyola University Chicago ChicagoIL60660 United States Academic Assembly School of Science and Technology Institute of Engineering Shinshu University Nagano Nagano380-8554 Japan High Energy Astrophysics Institute Department of Physics and Astronomy University of Utah Salt Lake CityUT84112-0830 United States Graduate School of Science Osaka Metropolitan University Sugimoto Sumiyoshi Osaka558-8585 Japan Department of Physics The Research Institute of Natural Science Hanyang University Seongdong-gu Seoul426-791 Korea Republic of Institute for Cosmic Ray Research University of Tokyo Chiba Kashiwa277-8582 Japan Institute of Physics Academia Sinica Taipei City115201 Taiwan Nambu Yoichiro Institute of Theoretical and Experimental Physics Osaka Metropolitan University Sugimoto Sumiyoshi Osaka558-8585 Japan Astrophysical Big Bang Laboratory RIKEN Saitama Wako351-0198 Japan Faculty of Engineering Kanagawa University Kanagawa Yokohama221-8686 Japan Interdisciplinary Graduate School of Medicine and Engineering University of Yamanashi Yamanashi Kofu400-8511 Japan The Graduate School of Science and Engineering Saitama University Saitama Saitama338-8570 Japan Department of Physics SungKyunKwan University Jang-an-gu Suwon16419 Korea Republic of Department of Physics Tokyo City University Setagaya-ku Tokyo158-8557 Japan Institute for Nuclear Research The Russian Academy of Sciences Moscow117312 Russia Faculty of Systems Engineering and Science Shibaura Institute of Technology Minato-ku Tokyo337-8570 Japan Graduate School of Engineering Osaka Electro-Communication University Neyagawa-shi Osaka572-8530 Japan Service de Physique Théorique Université Libre de Bruxelles Brussels Belgium Department of Physics Yonsei University Seodaemun-gu Seoul120-749 Korea Republic of Center for Astrophysics and Cosmology Universi

We report on the cosmic ray mass composition measured by the Telescope Array Low-energy Extension (TALE) hybrid detector. The TALE detector consists of a Fluorescence Detector (FD) station with 10 FD telescopes located at the TA Middle Drum FD Station (itself made up of 14 FD telescopes), and a Surface Detector (SD) array of scintillation counters. The SD array consists of 40 counters with 400 m spacing and 40 counters with 600 m spacing. The FD station, with a total of 24 telescopes, overlooks the SD array and provides sky coverage with an elevation angle range of 3◦ to 59◦. In this contribution, we will present the latest result of the cosmic ray mass composition measurement in the energy range from 1016.5 eV to 1018.5 eV using almost 5 years of TALE hybrid data. © Copyright owned by the author(s) under the terms of the Creative Commons.

关键词： Cosmic rays

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A novel underwater image synthesis method based on a pixel-level self-supervised training strategy

A novel underwater image synthesis method based on a pixel-l...

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2021 IEEE International Conference on Real-Time Computing and Robotics, RCAR 2021

作者： Wu, Zhiheng Wu, Zhengxing Lu, Yue Wang, Jian Yu, Junzhi Institute of Automation Chinese Academy of Sciences State Key Laboratory of Management and Control for Complex Systems Beijing100190 China School of Artificial Intelligence University of Chinese Academy of Sciences Beijing100049 China State Key Laboratory for Turbulence and Complex Systems Department of Advanced Manufacturing and Robotics BIC-ESAT College of Engineering Peking University Beijing100871 China

ISBN: (纸本)9781665436786

With the rapid development of deep neural networks, underwater vision plays an increasingly important role in the underwater robotic operation. However, the scarce underwater datasets greatly limit the performance of deep learning on underwater visual tasks, further hindering the applications of underwater operation. To solve this problem, we propose an underwater image synthesis method, which can directly convert the natural light image into the synthetic underwater image end-to-end. Particularly, a pixel-level self-supervised training strategy is designed to maximize the structural similarity between the synthesized and real images, through training the real underwater images. Finally, extensive experiments are carried out, and the obtained results demonstrate the effectiveness and superiority of our methods by quantitative and qualitative comparisons. The proposed underwater image synthesis method offers a valuable sight for underwater vision and manipulating control. © 2021 IEEE.

关键词： Deep neural networks

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TA SD analysis for inclined air showers 38

TA SD analysis for inclined air showers

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38th International Cosmic Ray Conference, ICRC 2023

作者： Takahashi, K. Sako, T. Fujisue, K. Fujita, K. Kawata, K. Ogio, S. Oshima, H. Sagawa, H. Takeda, M. Abbasi, R.U. Abe, Y. Abu-Zayyad, T. Allen, M. Arai, Y. Arimura, R. Barcikowski, E. Belz, J.W. Bergman, D.R. Blake, S.A. Buckland, I. Cheon, B.G. Chikawa, M. Fedynitch, A. Fujii, T. Fujisue, K. Fujita, K. Fujiwara, R. Fukushima, M. Furlich, G. Gerber, Z. Globus, N. Hanlon, W. Hayashida, N. He, H. Hibi, R. Hibino, K. Higuchi, R. Honda, K. Ikeda, D. Inoue, N. Ishii, T. Ito, H. Ivanov, D. Iwasaki, A. Jeong, H.M. Jeong, S. Jui, C.C.H. Kadota, K. Kakimoto, F. Kalashev, O. Kasahara, K. Kasami, S. Kawakami, S. Kawata, K. Kharuk, I. Kido, E. Kim, H.B. Kim, J.H. Kim, J.H. Kim, S.W. Kimura, Y. Komae, I. Komori, K. Kusumori, Y. Kuznetsov, M. Kwon, Y.J. Lee, K.H. Lee, M.J. Lubsandorzhiev, B. Lundquist, J.P. Matsuyama, T. Matthews, J.A. Matthews, J.N. Mayta, R. Miyashita, K. Mizuno, K. Mori, M. Murakami, M. Myers, I. Nagataki, S. Nakai, K. Nakamura, T. Nishio, E. Nonaka, T. Ogio, S. Ohoka, H. Okazaki, N. Oku, Y. Okuda, T. Omura, Y. Onishi, M. Ono, M. Oshima, A. Oshima, H. Ozawa, S. Park, I.H. Park, K.Y. Potts, M. Pshirkov, M.S. Remington, J. Rodriguez, D.C. Rott, C. Rubtsov, G.I. Ryu, D. Sagawa, H. Saito, R. Sakaki, N. Sako, T. Sakurai, N. Sato, D. Sato, K. Sato, S. Sekino, K. Shah, P.D. Shibata, N. Shibata, T. Shikita, J. Shimodaira, H. Shin, B.K. Shin, H.S. Shinto, D. Smith, J.D. Sokolsky, P. Stokes, B.T. Stroman, T.A. Takagi, Y. Takahashi, K. Takamura, M. Takeda, M. Takeishi, R. Taketa, A. Takita, M. Tameda, Y. Tanaka, K. Tanaka, M. Thomas, S.B. Thomson, G.B. Tinyakov, P. Tkachev, I. Tokuno, H. Tomida, T. Troitsky, S. Tsuda, R. Tsunesada, Y. Udo, S. Urban, F. Vaiman, I.A. Warren, D. Wong, T. Yamazaki, K. Yashiro, K. Yoshida, F. Zhezher, Y. Zundel, Z. ICRR University of Tokyo 5-1-5 Kashiwa-no-Ha Kashiwa City Chiba277-8582 Japan Department of Physics Loyola University Chicago ChicagoIL60660 United States Academic Assembly School of Science and Technology Institute of Engineering Shinshu University Nagano Nagano380-8554 Japan High Energy Astrophysics Institute Department of Physics and Astronomy University of Utah Salt Lake CityUT84112-0830 United States Graduate School of Science Osaka Metropolitan University Sugimoto Sumiyoshi Osaka558-8585 Japan Department of Physics The Research Institute of Natural Science Hanyang University Seongdong-gu Seoul426-791 Korea Republic of Institute for Cosmic Ray Research University of Tokyo Chiba Kashiwa277-8582 Japan Institute of Physics Academia Sinica Taipei City115201 Taiwan Nambu Yoichiro Institute of Theoretical and Experimental Physics Osaka Metropolitan University Sugimoto Sumiyoshi Osaka558-8585 Japan Astrophysical Big Bang Laboratory RIKEN Saitama Wako351-0198 Japan Faculty of Engineering Kanagawa University Kanagawa Yokohama221-8686 Japan Interdisciplinary Graduate School of Medicine and Engineering University of Yamanashi Yamanashi Kofu400-8511 Japan The Graduate School of Science and Engineering Saitama University Saitama Saitama338-8570 Japan Department of Physics SungKyunKwan University Jang-an-gu Suwon16419 Korea Republic of Department of Physics Tokyo City University Setagaya-ku Tokyo158-8557 Japan Institute for Nuclear Research The Russian Academy of Sciences Moscow117312 Russia Faculty of Systems Engineering and Science Shibaura Institute of Technology Minato-ku Tokyo337-8570 Japan Graduate School of Engineering Osaka Electro-Communication University Neyagawa-shi Osaka572-8530 Japan Service de Physique Théorique Université Libre de Bruxelles Brussels Belgium Department of Physics Yonsei University Seodaemun-gu Seoul120-749 Korea Republic of Center for Astrophysics and Cosmology University of Nova Gorica

The origin of UHECRs is an open question which is complicated due to not very well-known deflections of the charged particles in Galactic and intergalactic magnetic fields. Finding the EeV neutrinos from astronomical sources will be a key to solve the problem of the origin. EeV neutrinos are expected to produce extensive air showers which are observable by the current operational air shower arrays. To search for neutrino-induced showers, it is important to increase both the interaction probability and background rejection power in the analysis of the inclined showers. We study a reconstruction method of the Telescope Array surface detector (TA SD) data for the neutrino-induced inclined air showers. The prime target is to improve the angular resolution for the astronomical objects. In this contribution, we present the detail of analysis method, angular resolution and total exposure of TA SD for neutrinos from the astronomical objects as a function of the declination. © Copyright owned by the author(s) under the terms of the Creative Commons.

关键词： Neutrons

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Cosmic Ray Energy Spectrum and Mass Composition measured by the TALE Fluorescence Detector 38

Cosmic Ray Energy Spectrum and Mass Composition measured by ...

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38th International Cosmic Ray Conference, ICRC 2023

作者： AbuZayyad, Tareq Abbasi, R.U. Abe, Y. Abu-Zayyad, T. Allen, M. Arai, Y. Arimura, R. Barcikowski, E. Belz, J.W. Bergman, D.R. Blake, S.A. Buckland, I. Cheon, B.G. Chikawa, M. Fedynitch, A. Fujii, T. Fujisue, K. Fujita, K. Fujiwara, R. Fukushima, M. Furlich, G. Gerber, Z. Globus, N. Hanlon, W. Hayashida, N. He, H. Hibi, R. Hibino, K. Higuchi, R. Honda, K. Ikeda, D. Inoue, N. Ishii, T. Ito, H. Ivanov, D. Iwasaki, A. Jeong, H.M. Jeong, S. Jui, C.C.H. Kadota, K. Kakimoto, F. Kalashev, O. Kasahara, K. Kasami, S. Kawakami, S. Kawata, K. Kharuk, I. Kido, E. Kim, H.B. Kim, J.H. Kim, J.H. Kim, S.W. Kimura, Y. Komae, I. Komori, K. Kusumori, Y. Kuznetsov, M. Kwon, Y.J. Lee, K.H. Lee, M.J. Lubsandorzhiev, B. Lundquist, J.P. Matsuyama, T. Matthews, J.A. Matthews, J.N. Mayta, R. Miyashita, K. Mizuno, K. Mori, M. Murakami, M. Myers, I. Nagataki, S. Nakai, K. Nakamura, T. Nishio, E. Nonaka, T. Ogio, S. Ohoka, H. Okazaki, N. Oku, Y. Okuda, T. Omura, Y. Onishi, M. Ono, M. Oshima, A. Oshima, H. Ozawa, S. Park, I.H. Park, K.Y. Potts, M. Pshirkov, M.S. Remington, J. Rodriguez, D.C. Rott, C. Rubtsov, G.I. Ryu, D. Sagawa, H. Saito, R. Sakaki, N. Sako, T. Sakurai, N. Sato, D. Sato, K. Sato, S. Sekino, K. Shah, P.D. Shibata, N. Shibata, T. Shikita, J. Shimodaira, H. Shin, B.K. Shin, H.S. Shinto, D. Smith, J.D. Sokolsky, P. Stokes, B.T. Stroman, T.A. Takagi, Y. Takahashi, K. Takamura, M. Takeda, M. Takeishi, R. Taketa, A. Takita, M. Tameda, Y. Tanaka, K. Tanaka, M. Thomas, S.B. Thomson, G.B. Tinyakov, P. Tkachev, I. Tokuno, H. Tomida, T. Troitsky, S. Tsuda, R. Tsunesada, Y. Udo, S. Urban, F. Vaiman, I.A. Warren, D. Wong, T. Yamazaki, K. Yashiro, K. Yoshida, F. Zhezher, Y. Zundel, Z. Loyola University Chicago ChicagoIL United States University of Utah Salt Lake CityUT United States Department of Physics Loyola University Chicago ChicagoIL60660 United States Academic Assembly School of Science and Technology Institute of Engineering Shinshu University Nagano Nagano380-8554 Japan High Energy Astrophysics Institute Department of Physics and Astronomy University of Utah Salt Lake CityUT84112-0830 United States Graduate School of Science Osaka Metropolitan University Sugimoto Sumiyoshi Osaka558-8585 Japan Department of Physics The Research Institute of Natural Science Hanyang University Seongdong-gu Seoul426-791 Korea Republic of Institute for Cosmic Ray Research University of Tokyo Chiba Kashiwa277-8582 Japan Institute of Physics Academia Sinica Taipei City115201 Taiwan Nambu Yoichiro Institute of Theoretical and Experimental Physics Osaka Metropolitan University Sugimoto Sumiyoshi Osaka558-8585 Japan Astrophysical Big Bang Laboratory RIKEN Saitama Wako351-0198 Japan Faculty of Engineering Kanagawa University Kanagawa Yokohama221-8686 Japan Interdisciplinary Graduate School of Medicine and Engineering University of Yamanashi Yamanashi Kofu400-8511 Japan The Graduate School of Science and Engineering Saitama University Saitama Saitama338-8570 Japan Department of Physics SungKyunKwan University Jang-an-gu Suwon16419 Korea Republic of Department of Physics Tokyo City University Setagaya-ku Tokyo158-8557 Japan Institute for Nuclear Research The Russian Academy of Sciences Moscow117312 Russia Faculty of Systems Engineering and Science Shibaura Institute of Technology Minato-ku Tokyo337-8570 Japan Graduate School of Engineering Osaka Electro-Communication University Neyagawa-shi Osaka572-8530 Japan Service de Physique Théorique Université Libre de Bruxelles Brussels1050 Belgium Department of Physics Yonsei University Seodaemun-gu Seoul120-749 Korea Republic of Center for Astrophysics and Cosmology

The Telescope Array (TA) cosmic rays detector located in the State of Utah in the United States is the largest ultra high energy cosmic rays detector in the northern hemisphere. The Telescope Array Low Energy Extension (TALE) fluorescence detector (FD) was added to TA in order to lower the detector’s energy threshold, and has succeeded in measuring the cosmic rays energy spectrum down to PeV energies, by making use of the direct Cherenkov light produced by air showers. In this contribution we present the results of a measurement of the cosmic-ray energy spectrum and mass composition using TALE FD data collected over a period of ∼ 8 years. This contribution provides an update to results on the cosmic-ray energy spectrum and mass composition presented at this conference in 2021. The update includes data collected during 16 additional months of observation and an updated detector simulation sets. © Copyright owned by the author(s) under the terms of the Creative Commons.

关键词： Cosmic ray detectors

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High-speed Video Camera Observations Associated with a Terrestrial Gamma-ray Flash at the Telescope Array Detector. 38

High-speed Video Camera Observations Associated with a Terre...

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38th International Cosmic Ray Conference, ICRC 2023

作者： Abbasi, Rasha Abbasi, R.U. Abe, Y. Abu-Zayyad, T. Allen, M. Arai, Y. Arimura, R. Barcikowski, E. Belz, J.W. Bergman, D.R. Blake, S.A. Buckland, I. Cheon, B.G. Chikawa, M. Fedynitch, A. Fujii, T. Fujisue, K. Fujita, K. Fujiwara, R. Fukushima, M. Furlich, G. Gerber, Z. Globus, N. Hanlon, W. Hayashida, N. He, H. Hibi, R. Hibino, K. Higuchi, R. Honda, K. Ikeda, D. Inoue, N. Ishii, T. Ito, H. Ivanov, D. Iwasaki, A. Jeong, H.M. Jeong, S. Jui, C.C.H. Kadota, K. Kakimoto, F. Kalashev, O. Kasahara, K. Kasami, S. Kawakami, S. Kawata, K. Kharuk, I. Kido, E. Kim, H.B. Kim, J.H. Kim, J.H. Kim, S.W. Kimura, Y. Komae, I. Komori, K. Kusumori, Y. Kuznetsov, M. Kwon, Y.J. Lee, K.H. Lee, M.J. Lubsandorzhiev, B. Lundquist, J.P. Matsuyama, T. Matthews, J.A. Matthews, J.N. Mayta, R. Miyashita, K. Mizuno, K. Mori, M. Murakami, M. Myers, I. Nagataki, S. Nakai, K. Nakamura, T. Nishio, E. Nonaka, T. Ogio, S. Ohoka, H. Okazaki, N. Oku, Y. Okuda, T. Omura, Y. Onishi, M. Ono, M. Oshima, A. Oshima, H. Ozawa, S. Park, I.H. Park, K.Y. Potts, M. Pshirkov, M.S. Remington, J. Rodriguez, D.C. Rott, C. Rubtsov, G.I. Ryu, D. Sagawa, H. Saito, R. Sakaki, N. Sako, T. Sakurai, N. Sato, D. Sato, K. Sato, S. Sekino, K. Shah, P.D. Shibata, N. Shibata, T. Shikita, J. Shimodaira, H. Shin, B.K. Shin, H.S. Shinto, D. Smith, J.D. Sokolsky, P. Stokes, B.T. Stroman, T.A. Takagi, Y. Takahashi, K. Takamura, M. Takeda, M. Takeishi, R. Taketa, A. Takita, M. Tameda, Y. Tanaka, K. Tanaka, M. Thomas, S.B. Thomson, G.B. Tinyakov, P. Tkachev, I. Tokuno, H. Tomida, T. Troitsky, S. Tsuda, R. Tsunesada, Y. Udo, S. Urban, F. Vaiman, I.A. Warren, D. Wong, T. Yamazaki, K. Yashiro, K. Yoshida, F. Zhezher, Y. Zundel, Z. Saba, M.M.F. Krehbiel, P.R. Rison, W. Kieu, N. da Silva, D.R. Stanley, M.A. Rodeheffer, Dan Mazich, J. LeVon, R. Smout, K. Petrizze, A. Loyola University Chicago Chicago United States Department of Physics Loyola University Chicago ChicagoIL60660 United States Academic Assembly School of Science and Technology Institute of Engineering Shinshu University Nagano Nagano380-8554 Japan High Energy Astrophysics Institute Department of Physics and Astronomy University of Utah Salt Lake CityUT84112-0830 United States Graduate School of Science Osaka Metropolitan University Sugimoto Sumiyoshi Osaka558-8585 Japan Department of Physics The Research Institute of Natural Science Hanyang University Seongdong-gu Seoul426-791 Korea Republic of Institute for Cosmic Ray Research University of Tokyo Kashiwa Chiba277-8582 Japan Institute of Physics Academia Sinica Taipei City115201 Taiwan Nambu Yoichiro Institute of Theoretical and Experimental Physics Osaka Metropolitan University Sugimoto Sumiyoshi Osaka558-8585 Japan Astrophysical Big Bang Laboratory RIKEN Wako Saitama351-0198 Japan Faculty of Engineering Kanagawa University Yokohama Kanagawa221-8686 Japan Interdisciplinary Graduate School of Medicine and Engineering University of Yamanashi Yamanashi Kofu400-8511 Japan The Graduate School of Science and Engineering Saitama University Saitama Saitama338-8570 Japan Department of Physics SungKyunKwan University Jang-an-gu Suwon16419 Korea Republic of Department of Physics Tokyo City University Setagaya-ku Tokyo158-8557 Japan Institute for Nuclear Research The Russian Academy of Sciences Moscow117312 Russia Faculty of Systems Engineering and Science Shibaura Institute of Technology Minato-ku Tokyo337-8570 Japan Graduate School of Engineering Osaka Electro-Communication University Neyagawa-shi Osaka572-8530 Japan Service de Physique Théorique Université Libre de Bruxelles Brussels1050 Belgium Department of Physics Yonsei University Seodaemun-gu Seoul120-749 Korea Republic of Center for Astrophysics and Cosmology University of Nova Gorica Nova Gorica5297 Slovenia Fa

This work presents observations of the optical emission of a lightning flash in conjunction with a downward-directed Terrestrial Gamma-ray Flash (TGF) at the Telescope Array detector. Previously, we reported joint observations by the Telescope Array Surface Detector (TASD), the Lightning Mapping Array, a sferic sensor, and a broadband interferometer of particle showers in coincidence with lightning. These observations consisted of energetic showers of approximately less than 10-microsecond duration with footprints on the ground of 3-6 kilometers in diameter, originating in the first one to two milliseconds of downward lightning leaders and in coincidence with the initial breakdown pulses stage of negative cloud-to-ground lighting leaders. Scintillator waveform and simulation studies confirmed that these showers must consist primarily of gamma radiations. In this work, we use the TASD detector, together with a high-speed video camera, in conjunction with multiple lightning instruments at the TASD site, to report on the optical emission associated with a downward-directed terrestrial gamma-ray flash. Results from this study allow us to further the understanding of the initiation and propagation mechanism of terrestrial gamma-ray flashes. It will also further our ability to compare the most recent satellite optical emissions counterpart of upward-directed TGFs to that of downward-directed TGFs. © Copyright owned by the author(s) under the terms of the Creative Commons.

关键词： High speed cameras

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