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7,583 results on '"TAKAHASHI, HIROSHI"'

1. GPC/m: Global Precipitation Climatology by Machine Learning; Quasi-global, Daily, and One Degree Spatial Resolution

Author

Takahashi, Hiroshi G.

Subjects
Physics - Atmospheric and Oceanic Physics
Abstract

This paper presents a new precipitation dataset that is daily, has a spatial resolution of one degree on a quasi-global scale, and spans more than 42 years, using machine learning techniques. The ultimate goal of this dataset is to provide a homogeneous daily precipitation dataset for several decades without gaps, which is suitable for climate analysis. As a first step, 42 years of daily precipitation data was generated using machine learning techniques. The machine learning methods are supervised learning, and the reference data are estimated precipitation datasets from 2001 to 2020. The three machine learning methods are random forest, gradient-boosted decision trees, and convolutional neural networks. The input data are satellite observations and atmospheric circulations from reanalysis, which are somewhat modified based on knowledge of the climatological background. Using the trained statistical models, we predict back to 1979, when daily precipitation data was almost unavailable globally. The detailed procedures are described in this paper. The produced data have been partially evaluated. However, additional evaluations from different perspectives are needed. The advantages and disadvantages of this precipitation dataset are also discussed. Currently, this GPC/m precipitation dataset version is GPC/m-v1-2024., Comment: 8 figures, the daily precipitation data is provided via Zenode (https://doi.org/10.5281/zenodo.13743725). 3 videos are provided as Supplementary Materials

Published
2024

2. Deep Positive-Unlabeled Anomaly Detection for Contaminated Unlabeled Data

Author

Takahashi, Hiroshi, Iwata, Tomoharu, Kumagai, Atsutoshi, and Yamanaka, Yuuki

Subjects
Statistics - Machine Learning, Computer Science - Artificial Intelligence, Computer Science - Machine Learning
Abstract

Semi-supervised anomaly detection, which aims to improve the performance of the anomaly detector by using a small amount of anomaly data in addition to unlabeled data, has attracted attention. Existing semi-supervised approaches assume that unlabeled data are mostly normal. They train the anomaly detector to minimize the anomaly scores for the unlabeled data, and to maximize those for the anomaly data. However, in practice, the unlabeled data are often contaminated with anomalies. This weakens the effect of maximizing the anomaly scores for anomalies, and prevents us from improving the detection performance. To solve this problem, we propose the positive-unlabeled autoencoder, which is based on positive-unlabeled learning and the anomaly detector such as the autoencoder. With our approach, we can approximate the anomaly scores for normal data using the unlabeled and anomaly data. Therefore, without the labeled normal data, we can train the anomaly detector to minimize the anomaly scores for normal data, and to maximize those for the anomaly data. In addition, our approach is applicable to various anomaly detectors such as the DeepSVDD. Experiments on various datasets show that our approach achieves better detection performance than existing approaches., Comment: Under revirew. Code is available at https://github.com/takahashihiroshi/puae

Published
2024

10. Safety and feasibility of intravenous administration of a single dose of allogenic-Muse cells to treat human cervical traumatic spinal cord injury: a clinical trial

Author

Koda, Masao, Imagama, Shiro, Nakashima, Hiroaki, Ito, Sadayuki, Segi, Naoki, Ouchida, Jun, Suda, Kota, Harmon Matsumoto, Satoko, Komatsu, Miki, Endo, Toshiki, Suzuki, Shinsuke, Inami, Satoshi, Ueda, Haruki, Miyagi, Masayuki, Inoue, Gen, Takaso, Masashi, Nagata, Keiji, Yamada, Hiroshi, Kamei, Naosuke, Nakamae, Toshio, Suzuki, Hidenori, Nishida, Norihiro, Funaba, Masahiro, Kumagai, Gentaro, Furuya, Takeo, Yamato, Yu, Funayama, Toru, Takahashi, Hiroshi, and Yamazaki, Masashi

Published
2024
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19. Nowcasting Corporate Product Development Activities Through News Article by BERTopic: The Case of the Japanese Chemical Company

Author

Okazaki, Haruna, Takahashi, Hiroshi, Goos, Gerhard, Series Editor, Hartmanis, Juris, Founding Editor, van Leeuwen, Jan, Series Editor, Hutchison, David, Editorial Board Member, Kanade, Takeo, Editorial Board Member, Kittler, Josef, Editorial Board Member, Kleinberg, Jon M., Editorial Board Member, Kobsa, Alfred, Series Editor, Mattern, Friedemann, Editorial Board Member, Mitchell, John C., Editorial Board Member, Naor, Moni, Editorial Board Member, Nierstrasz, Oscar, Series Editor, Pandu Rangan, C., Editorial Board Member, Sudan, Madhu, Series Editor, Terzopoulos, Demetri, Editorial Board Member, Tygar, Doug, Editorial Board Member, Weikum, Gerhard, Series Editor, Vardi, Moshe Y, Series Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Bono, Mayumi, editor, Takama, Yasufumi, editor, Satoh, Ken, editor, Nguyen, Le-Minh, editor, and Kurahashi, Setsuya, editor

Published
2024
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20. Mechanical Property Enhancement of Cemented Soil Using Agricultural By-Product

Author

Duong, Nga Thanh, Luu, Loc Xuan, Satomi, Tomoaki, Takahashi, Hiroshi, di Prisco, Marco, Series Editor, Chen, Sheng-Hong, Series Editor, Vayas, Ioannis, Series Editor, Kumar Shukla, Sanjay, Series Editor, Sharma, Anuj, Series Editor, Kumar, Nagesh, Series Editor, Wang, Chien Ming, Series Editor, Cui, Zhen-Dong, Series Editor, Reddy, J. N., editor, Luong, Van Hai, editor, and Le, Anh Tuan, editor

Published
2024
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21. Study on Strength Properties of Fiber-Cement-Stabilized Soil Using Waste Gypsum Board Paper

Author

Takahashi, Hiroshi, Sato, Yu, Satomi, Tomoaki, Luu, Xuan Loc, di Prisco, Marco, Series Editor, Chen, Sheng-Hong, Series Editor, Vayas, Ioannis, Series Editor, Kumar Shukla, Sanjay, Series Editor, Sharma, Anuj, Series Editor, Kumar, Nagesh, Series Editor, Wang, Chien Ming, Series Editor, Cui, Zhen-Dong, Series Editor, Reddy, J. N., editor, Luong, Van Hai, editor, and Le, Anh Tuan, editor

Published
2024
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22. One-vs-the-Rest Loss to Focus on Important Samples in Adversarial Training

Author

Kanai, Sekitoshi, Yamaguchi, Shin'ya, Yamada, Masanori, Takahashi, Hiroshi, Ohno, Kentaro, and Ida, Yasutoshi

Subjects
Computer Science - Machine Learning, Computer Science - Artificial Intelligence, Statistics - Machine Learning
Abstract

This paper proposes a new loss function for adversarial training. Since adversarial training has difficulties, e.g., necessity of high model capacity, focusing on important data points by weighting cross-entropy loss has attracted much attention. However, they are vulnerable to sophisticated attacks, e.g., Auto-Attack. This paper experimentally reveals that the cause of their vulnerability is their small margins between logits for the true label and the other labels. Since neural networks classify the data points based on the logits, logit margins should be large enough to avoid flipping the largest logit by the attacks. Importance-aware methods do not increase logit margins of important samples but decrease those of less-important samples compared with cross-entropy loss. To increase logit margins of important samples, we propose switching one-vs-the-rest loss (SOVR), which switches from cross-entropy to one-vs-the-rest loss for important samples that have small logit margins. We prove that one-vs-the-rest loss increases logit margins two times larger than the weighted cross-entropy loss for a simple problem. We experimentally confirm that SOVR increases logit margins of important samples unlike existing methods and achieves better robustness against Auto-Attack than importance-aware methods., Comment: ICML2023, 26 pages, 19 figures

Published
2022

23. Regional climate model intercomparison over the Tibetan Plateau in the GEWEX/LS4P Phase I

Author

Tang, Jianping, Xue, Yongkang, Long, Mengyuan, Ma, Mengnan, Liang, Xin-Zhong, Sugimoto, Shiori, Yang, Kun, Ji, Zhenming, Hong, Jinkyu, Kim, Jeongwon, Xu, Haoran, Zhou, Xu, Sato, Tomonori, Takahashi, Hiroshi G, Wang, Shuyu, Wang, Guiling, Chou, Sin Chan, Guo, Weidong, Yu, Miao, and Pan, Xiaoduo

Subjects
Earth Sciences, Oceanography, Atmospheric Sciences, Climate Change Science, Climate Action, Tibetan Plateau, Regional climate model, Precipitation, Temperature, Seasonal prediction, LS4P, Physical Geography and Environmental Geoscience, Meteorology & Atmospheric Sciences, Atmospheric sciences, Climate change science
Published
2023

31. Successful allogeneic hematopoietic stem cell transplantation for myelodysplastic neoplasms complicated with secondary pulmonary alveolar proteinosis and Behçet's disease harboring GATA2 mutation

Author

Sato, Yuki, Fukatsu, Masahiko, Suzuki, Tomohiro, Sasajima, Tomomi, Gunji, Naohiko, Yoshida, Shuhei, Asano, Naomi, Fukuchi, Koichiro, Mori, Hirotaka, Takano, Motoki, Hayashi, Kiyohito, Takahashi, Hiroshi, Shirado-Harada, Kayo, Kimura, Satoshi, Koyama, Daisuke, Migita, Kiyoshi, and Ikezoe, Takayuki

Published
2023
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35. Quantification of escape from X chromosome inactivation with single-cell omics data reveals heterogeneity across cell types and tissues

Author

Charoensawan, Varodom, Hon, Chung-Chau, Majumder, Partha P., Matangkasombut, Ponpan, Park, Woong-Yang, Prabhakar, Shyam, Shin, Jay W., Carninci, Piero, Chambers, John C., Loh, Marie, Pithukpakorn, Manop, Suktitipat, Bhoom, Yamamoto, Kazuhiko, Rajagopalan, Deepa, Rayan, Nirmala Arul, Sankaran, Shvetha, Chantaraamporn, Juthamard, Chatterjee, Ankita, Ghosh, Supratim, Han, Kyung Yeon, Jevapatarakul, Damita, Nguantad, Sarintip, Sarkar, Sumanta, Thungsatianpun, Narita, Abe, Mai, Furukawa, Seiko, Inoue, Gyo, Myouzen, Keiko, Oh, Jin-Mi, Suzuki, Akari, Ando, Yoshinari, Kojima, Miki, Kouno, Tsukasa, Lim, Jinyeong, Maitra, Arindam, Tan, Le Min, Venkatesh, Prasanna Nori, Choi, Murim, Park, Jong-Eun, Buyamin, Eliora Violain, Kock, Kian Hong, Xuan Lin, Quy Xiao, Moody, Jonathan, Sonthalia, Radhika, Ishigaki, Kazuyoshi, Nakano, Masahiro, Okada, Yukinori, Tomofuji, Yoshihiko, Ho Namkoong, Edahiro, Ryuya, Takano, Tomomi, Nishihara, Hiroshi, Shirai, Yuya, Sonehara, Kyuto, Tanaka, Hiromu, Azekawa, Shuhei, Mikami, Yohei, Lee, Ho, Hasegawa, Takanori, Okudela, Koji, Okuzaki, Daisuke, Motooka, Daisuke, Kanai, Masahiro, Naito, Tatsuhiko, Yamamoto, Kenichi, Wang, Qingbo S., Saiki, Ryunosuke, Ishihara, Rino, Matsubara, Yuta, Hamamoto, Junko, Hayashi, Hiroyuki, Yoshimura, Yukihiro, Tachikawa, Natsuo, Yanagita, Emmy, Hyugaji, Takayoshi, Shimizu, Eigo, Katayama, Kotoe, Kato, Yasuhiro, Morita, Takayoshi, Takahashi, Kazuhisa, Harada, Norihiro, Naito, Toshio, Hiki, Makoto, Matsushita, Yasushi, Takagi, Haruhi, Aoki, Ryousuke, Nakamura, Ai, Harada, Sonoko, Sasano, Hitoshi, Kabata, Hiroki, Masaki, Katsunori, Kamata, Hirofumi, Ikemura, Shinnosuke, Chubachi, Shotaro, Okamori, Satoshi, Terai, Hideki, Morita, Atsuho, Asakura, Takanori, Sasaki, Junichi, Morisaki, Hiroshi, Uwamino, Yoshifumi, Nanki, Kosaku, Uchida, Sho, Uno, Shunsuke, Nishimura, Tomoyasu, Ishiguro, Takashi, Isono, Taisuke, Shibata, Shun, Matsui, Yuma, Hosoda, Chiaki, Takano, Kenji, Nishida, Takashi, Kobayashi, Yoichi, Takaku, Yotaro, Takayanagi, Noboru, Ueda, Soichiro, Tada, Ai, Miyawaki, Masayoshi, Yamamoto, Masaomi, Yoshida, Eriko, Hayashi, Reina, Nagasaka, Tomoki, Arai, Sawako, Kaneko, Yutaro, Sasaki, Kana, Tagaya, Etsuko, Kawana, Masatoshi, Arimura, Ken, Takahashi, Kunihiko, Anzai, Tatsuhiko, Ito, Satoshi, Endo, Akifumi, Uchimura, Yuji, Miyazaki, Yasunari, Honda, Takayuki, Tateishi, Tomoya, Tohda, Shuji, Ichimura, Naoya, Sonobe, Kazunari, Sassa, Chihiro Tani, Nakajima, Jun, Nakano, Yasushi, Nakajima, Yukiko, Anan, Ryusuke, Arai, Ryosuke, Kurihara, Yuko, Harada, Yuko, Nishio, Kazumi, Ueda, Tetsuya, Azuma, Masanori, Saito, Ryuichi, Sado, Toshikatsu, Miyazaki, Yoshimune, Sato, Ryuichi, Haruta, Yuki, Nagasaki, Tadao, Yasui, Yoshinori, Hasegawa, Yoshinori, Mutoh, Yoshikazu, Kimura, Tomoki, Sato, Tomonori, Takei, Reoto, Hagimoto, Satoshi, Noguchi, Yoichiro, Yamano, Yasuhiko, Sasano, Hajime, Ota, Sho, Nakamori, Yasushi, Yoshiya, Kazuhisa, Saito, Fukuki, Yoshihara, Tomoyuki, Wada, Daiki, Iwamura, Hiromu, Kanayama, Syuji, Maruyama, Shuhei, Yoshiyama, Takashi, Ohta, Ken, Kokuto, Hiroyuki, Ogata, Hideo, Tanaka, Yoshiaki, Arakawa, Kenichi, Shimoda, Masafumi, Osawa, Takeshi, Tateno, Hiroki, Hase, Isano, Yoshida, Shuichi, Suzuki, Shoji, Kawada, Miki, Horinouchi, Hirohisa, Saito, Fumitake, Mitamura, Keiko, Hagihara, Masao, Ochi, Junichi, Uchida, Tomoyuki, Baba, Rie, Arai, Daisuke, Ogura, Takayuki, Takahashi, Hidenori, Hagiwara, Shigehiro, Nagao, Genta, Konishi, Shunichiro, Nakachi, Ichiro, Murakami, Koji, Yamada, Mitsuhiro, Sugiura, Hisatoshi, Sano, Hirohito, Matsumoto, Shuichiro, Kimura, Nozomu, Ono, Yoshinao, Baba, Hiroaki, Suzuki, Yusuke, Nakayama, Sohei, Masuzawa, Keita, Namba, Shinichi, Suzuki, Ken, Naito, Yoko, Liu, Yu-Chen, Takuwa, Ayako, Sugihara, Fuminori, Wing, James B., Sakakibara, Shuhei, Hizawa, Nobuyuki, Shiroyama, Takayuki, Miyawaki, Satoru, Kawamura, Yusuke, Nakayama, Akiyoshi, Matsuo, Hirotaka, Yuichi, Maeda, Nii, Takuro, Noda, Yoshimi, Niitsu, Takayuki, Adachi, Yuichi, Enomoto, Takatoshi, Amiya, Saori, Hara, Reina, Yamaguchi, Yuta, Murakami, Teruaki, Kuge, Tomoki, Matsumoto, Kinnosuke, Yamamoto, Yuji, Yamamoto, Makoto, Yoneda, Midori, Kishikawa, Toshihiro, Yamada, Shuhei, Kawabata, Shuhei, Kijima, Noriyuki, Takagaki, Masatoshi, Sasa, Noah, Ueno, Yuya, Suzuki, Motoyuki, Takemoto, Norihiko, Eguchi, Hirotaka, Fukusumi, Takahito, Imai, Takao, Fukushima, Munehisa, Kishima, Haruhiko, Inohara, Hidenori, Tomono, Kazunori, Kato, Kazuto, Takahashi, Meiko, Matsuda, Fumihiko, Hirata, Haruhiko, Takeda, Yoshito, Koh, Hidefumi, Manabe, Tadashi, Funatsu, Yohei, Ito, Fumimaro, Fukui, Takahiro, Shinozuka, Keisuke, Kohashi, Sumiko, Miyazaki, Masatoshi, Shoko, Tomohisa, Kojima, Mitsuaki, Adachi, Tomohiro, Ishikawa, Motonao, Takahashi, Kenichiro, Inoue, Takashi, Hirano, Toshiyuki, Kobayashi, Keigo, Takaoka, Hatsuyo, Watanabe, Kazuyoshi, Miyazawa, Naoki, Kimura, Yasuhiro, Sado, Reiko, Sugimoto, Hideyasu, Kamiya, Akane, Kuwahara, Naota, Fujiwara, Akiko, Matsunaga, Tomohiro, Sato, Yoko, Okada, Takenori, Hirai, Yoshihiro, Kawashima, Hidetoshi, Narita, Atsuya, Niwa, Kazuki, Sekikawa, Yoshiyuki, Nishi, Koichi, Nishitsuji, Masaru, Tani, Mayuko, Suzuki, Junya, Nakatsumi, Hiroki, Ogura, Takashi, Kitamura, Hideya, Hagiwara, Eri, Murohashi, Kota, Okabayashi, Hiroko, Mochimaru, Takao, Nukaga, Shigenari, Satomi, Ryosuke, Oyamada, Yoshitaka, Mori, Nobuaki, Baba, Tomoya, Fukui, Yasutaka, Odate, Mitsuru, Mashimo, Shuko, Makino, Yasushi, Yagi, Kazuma, Hashiguchi, Mizuha, Kagyo, Junko, Shiomi, Tetsuya, Fuke, Satoshi, Saito, Hiroshi, Tsuchida, Tomoya, Fujitani, Shigeki, Takita, Mumon, Morikawa, Daiki, Yoshida, Toru, Izumo, Takehiro, Inomata, Minoru, Kuse, Naoyuki, Awano, Nobuyasu, Tone, Mari, Ito, Akihiro, Nakamura, Yoshihiko, Hoshino, Kota, Maruyama, Junichi, Ishikura, Hiroyasu, Takata, Tohru, Odani, Toshio, Amishima, Masaru, Hattori, Takeshi, Shichinohe, Yasuo, Kagaya, Takashi, Kita, Toshiyuki, Ohta, Kazuhide, Sakagami, Satoru, Koshida, Kiyoshi, Hayashi, Kentaro, Shimizu, Tetsuo, Kozu, Yutaka, Hiranuma, Hisato, Gon, Yasuhiro, Izumi, Namiki, Nagata, Kaoru, Ueda, Ken, Taki, Reiko, Hanada, Satoko, Kawamura, Kodai, Ichikado, Kazuya, Nishiyama, Kenta, Muranaka, Hiroyuki, Nakamura, Kazunori, Hashimoto, Naozumi, Wakahara, Keiko, Koji, Sakamoto, Omote, Norihito, Ando, Akira, Kodama, Nobuhiro, Kaneyama, Yasunari, Shunsuke, Maeda, Kuraki, Takashige, Matsumoto, Takemasa, Yokote, Koutaro, Nakada, Taka-Aki, Abe, Ryuzo, Oshima, Taku, Shimada, Tadanaga, Harada, Masahiro, Takahashi, Takeshi, Ono, Hiroshi, Sakurai, Toshihiro, Shibusawa, Takayuki, Kimizuka, Yoshifumi, Kawana, Akihiko, Sano, Tomoya, Watanabe, Chie, Suematsu, Ryohei, Sageshima, Hisako, Yoshifuji, Ayumi, Ito, Kazuto, Takahashi, Saeko, Ishioka, Kota, Nakamura, Morio, Masuda, Makoto, Wakabayashi, Aya, Watanabe, Hiroki, Ueda, Suguru, Nishikawa, Masanori, Chihara, Yusuke, Takeuchi, Mayumi, Onoi, Keisuke, Shinozuka, Jun, Sueyoshi, Atsushi, Nagasaki, Yoji, Okamoto, Masaki, Ishihara, Sayoko, Shimo, Masatoshi, Tokunaga, Yoshihisa, Kusaka, Yu, Ohba, Takehiko, Isogai, Susumu, Ogawa, Aki, Inoue, Takuya, Fukuyama, Satoru, Eriguchi, Yoshihiro, Yonekawa, Akiko, Kan-o, Keiko, Matsumoto, Koichiro, Kanaoka, Kensuke, Ihara, Shoichi, Komuta, Kiyoshi, Inoue, Yoshiaki, Chiba, Shigeru, Yamagata, Kunihiro, Hiramatsu, Yuji, Kai, Hirayasu, Asano, Koichiro, Oguma, Tsuyoshi, Ito, Yoko, Hashimoto, Satoru, Yamasaki, Masaki, Kasamatsu, Yu, Komase, Yuko, Hida, Naoya, Tsuburai, Takahiro, Oyama, Baku, Takada, Minoru, Kanda, Hidenori, Kitagawa, Yuichiro, Fukuta, Tetsuya, Miyake, Takahito, Yoshida, Shozo, Ogura, Shinji, Abe, Shinji, Kono, Yuta, Togashi, Yuki, Takoi, Hiroyuki, Kikuchi, Ryota, Ogawa, Shinichi, Ogata, Tomouki, Ishihara, Shoichiro, Kanehiro, Arihiko, Ozaki, Shinji, Fuchimoto, Yasuko, Wada, Sae, Fujimoto, Nobukazu, Nishiyama, Kei, Terashima, Mariko, Beppu, Satoru, Yoshida, Kosuke, Narumoto, Osamu, Nagai, Hideaki, Ooshima, Nobuharu, Motegi, Mitsuru, Umeda, Akira, Miyagawa, Kazuya, Shimada, Hisato, Endo, Mayu, Ohira, Yoshiyuki, Watanabe, Masafumi, Inoue, Sumito, Igarashi, Akira, Sato, Masamichi, Sagara, Hironori, Tanaka, Akihiko, Ohta, Shin, Kimura, Tomoyuki, Shibata, Yoko, Tanino, Yoshinori, Nikaido, Takefumi, Minemura, Hiroyuki, Sato, Yuki, Yamada, Yuichiro, Hashino, Takuya, Shinoki, Masato, Iwagoe, Hajime, Takahashi, Hiroshi, Fujii, Kazuhiko, Kishi, Hiroto, Kanai, Masayuki, Imamura, Tomonori, Yamashita, Tatsuya, Yatomi, Masakiyo, Maeno, Toshitaka, Hayashi, Shinichi, Takahashi, Mai, Kuramochi, Mizuki, Kamimaki, Isamu, Tominaga, Yoshiteru, Ishii, Tomoo, Utsugi, Mitsuyoshi, Ono, Akihiro, Tanaka, Toru, Kashiwada, Takeru, Fujita, Kazue, Saito, Yoshinobu, Seike, Masahiro, Watanabe, Hiroko, Matsuse, Hiroto, Kodaka, Norio, Nakano, Chihiro, Oshio, Takeshi, Hirouchi, Takatomo, Makino, Shohei, Egi, Moritoki, Omae, Yosuke, Nannya, Yasuhito, Ueno, Takafumi, Katayama, Kazuhiko, Ai, Masumi, Fukui, Yoshinori, Kumanogoh, Atsushi, Sato, Toshiro, Hasegawa, Naoki, Tokunaga, Katsushi, Ishii, Makoto, Koike, Ryuji, Kitagawa, Yuko, Kimura, Akinori, Imoto, Seiya, Miyano, Satoru, Ogawa, Seishi, Kanai, Takanori, Fukunaga, Koichi, Takeshima, Yusuke, Tanaka, Kentaro, Koichi Matsuda, Yamanashi, Yuji, Furukawa, Yoichi, Morisaki, Takayuki, Murakami, Yoshinori, Kamatani, Yoichiro, Muto, Kaori, Nagai, Akiko, Nakamura, Yusuke, Obara, Wataru, Yamaji, Ken, Asai, Satoshi, Takahashi, Yasuo, Higashiue, Shinichi, Kobayashi, Shuzo, Yamaguchi, Hiroki, Nagata, Yasunobu, Wakita, Satoshi, Nito, Chikako, Iwasaki, Yu-ki, Murayama, Shigeo, Yoshimori, Kozo, Miki, Yoshio, Obata, Daisuke, Higashiyama, Masahiko, Masumoto, Akihide, Koga, Yoshinobu, Koretsune, Yukihiro, Yata, Tomohiro, Ogawa, Kotaro, Namkoong, Ho, Okuno, Tatsusada, Liu, Boxiang, Matsuda, Koichi, and Mochizuki, Hideki

Published
2024
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37. A novel simultaneous three-dimensional volumetric morphological imaging and T2-mapping method, multi-interleaved X-prepared turbo-spin echo with intuitive relaxometry provides more accurate quantification of cervical spinal nerves

Author

Tokeshi, Soichiro, Eguchi, Yawara, Sakai, Takayuki, Yoneyama, Masami, Watanabe, Atsuya, Aoki, Yasuchika, Sato, Masashi, Orita, Sumihisa, Suzuki, Miyako, Inage, Kazuhide, Shiga, Yasuhiro, Inoue, Masahiro, Toshi, Noriyasu, Okuyama, Kohei, Ohyama, Shuhei, Suzuki, Noritaka, Maki, Satoshi, Nakamura, Junichi, Hagiwara, Shigeo, Kawarai, Yuya, Akazawa, Tsutomu, Takahashi, Hiroshi, and Ohtori, Seiji

Published
2024
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45. Short-Term Clinical and Radiographic Evaluation of Patients Treated With Expandable and Static Interbody Spacers Following Lumbar Lateral Interbody Fusion

Author

Eguchi, Yawara, Suzuki, Noritaka, Orita, Sumihisa, Inage, Kazuhide, Narita, Miyako, Shiga, Yasuhiro, Inoue, Masahiro, Toshi, Noriyasu, Tokeshi, Soichiro, Okuyama, Kohei, Ohyama, Shuhei, Maki, Satoshi, Aoki, Yasuchika, Nakamura, Junichi, Hagiwara, Shigeo, Kawarai, Yuya, Akazawa, Tsutomu, Koda, Masao, Takahashi, Hiroshi, and Ohtori, Seiji

Published
2024
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50. Influence of convective processes on weather research and forecasting model precipitation biases over East Asia

Author

Sugimoto, Shiori, Xue, Yongkang, Sato, Tomonori, and Takahashi, Hiroshi G

Subjects
Earth Sciences, Atmospheric Sciences, Climate Change Science, Climate Action, East Asia, Precipitation bias, Cumulus parameterization scheme, WRF model, Oceanography, Physical Geography and Environmental Geoscience, Meteorology & Atmospheric Sciences, Atmospheric sciences, Climate change science
Abstract

Abstract: Dynamical downscaling with a 20 km horizontal resolution was undertaken over East Asia for the period May–August in 1991–2015 using the Weather Research and Forecasting (WRF) model with Grell-3D ensemble cumulus parameterization as a product of the Impact of Initialized Land Temperature and Snowpack on Sub-Seasonal to Seasonal Prediction (LS4P) program. Simulated climatological precipitation biases were investigated over land during June when heavy precipitation occurred. Simulations underestimated precipitation along the Meiyu/Baiu rainband, while overestimating it farther north. Dry and wet biases expanded to south and north of the Yangtze River in China, respectively, marking years with poor precipitation simulations. Model biases in synoptic-scale circulation patterns indicate a weakened clockwise circulation over the western North Pacific in the model due to active convection there, and suppressed northward moisture transport to the Meiyu/Baiu rainband. Moisture convergence was slightly enhanced over central China due to an apparent anticyclonic circulation bias over northern China. In years with large biases, positive feedback between reduced moisture inflow and inactive convection occurred over southern China, while moisture transport to central China intensified on regional scales, with amplification of dry and wet biases over China. The Kain–Fritch scheme was used to test the influence of cumulus parameterization, improving the dry bias over southern China due to the modification of synoptic-scale circulation patterns in the lower troposphere. However, precipitation was further overestimated over central China, with the accuracy of precipitation distribution deteriorating.

Published
2022

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