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1. JUNO Sensitivity to Invisible Decay Modes of Neutrons

Author

JUNO Collaboration, Abusleme, Angel, Adam, Thomas, Adamowicz, Kai, Ahmad, Shakeel, Ahmed, Rizwan, Aiello, Sebastiano, An, Fengpeng, An, Qi, Andronico, Giuseppe, Anfimov, Nikolay, Antonelli, Vito, Antoshkina, Tatiana, de André, João Pedro Athayde Marcondes, Auguste, Didier, Bai, Weidong, Balashov, Nikita, Baldini, Wander, Barresi, Andrea, Basilico, Davide, Baussan, Eric, Bellato, Marco, Beretta, Marco, Bergnoli, Antonio, Bick, Daniel, Bieger, Lukas, Biktemerova, Svetlana, Birkenfeld, Thilo, Blake, Iwan, Blyth, Simon, Bolshakova, Anastasia, Bongrand, Mathieu, Breton, Dominique, Brigatti, Augusto, Brugnera, Riccardo, Bruno, Riccardo, Budano, Antonio, Busto, Jose, Cabrera, Anatael, Caccianiga, Barbara, Cai, Hao, Cai, Xiao, Cai, Yanke, Cai, Zhiyan, Callier, Stéphane, Calvez, Steven, Cammi, Antonio, Campeny, Agustin, Cao, Chuanya, Cao, Guofu, Cao, Jun, Caruso, Rossella, Cerna, Cédric, Cerrone, Vanessa, Chang, Jinfan, Chang, Yun, Chatrabhuti, Auttakit, Chen, Chao, Chen, Guoming, Chen, Pingping, Chen, Shaomin, Chen, Xin, Chen, Yiming, Chen, Yixue, Chen, Yu, Chen, Zelin, Chen, Zhangming, Chen, Zhiyuan, Chen, Zikang, Cheng, Jie, Cheng, Yaping, Cheng, Yu Chin, Chepurnov, Alexander, Chetverikov, Alexey, Chiesa, Davide, Chimenti, Pietro, Chin, Yen-Ting, Chou, Po-Lin, Chu, Ziliang, Chukanov, Artem, Claverie, Gérard, Clementi, Catia, Clerbaux, Barbara, Molla, Marta Colomer, Di Lorenzo, Selma Conforti, Coppi, Alberto, Corti, Daniele, Csakli, Simon, Cui, Chenyang, Corso, Flavio Dal, Dalager, Olivia, Datta, Jaydeep, De La Taille, Christophe, Deng, Zhi, Deng, Ziyan, Ding, Xiaoyu, Ding, Xuefeng, Ding, Yayun, Dirgantara, Bayu, Dittrich, Carsten, Dmitrievsky, Sergey, Dohnal, Tadeas, Dolzhikov, Dmitry, Donchenko, Georgy, Dong, Jianmeng, Doroshkevich, Evgeny, Dou, Wei, Dracos, Marcos, Druillole, Frédéric, Du, Ran, Du, Shuxian, Duan, Yujie, Dugas, Katherine, Dusini, Stefano, Duyang, Hongyue, Eck, Jessica, Enqvist, Timo, Fabbri, Andrea, Fahrendholz, Ulrike, Fan, Lei, Fang, Jian, Fang, Wenxing, Fedoseev, Dmitry, Feng, Li-Cheng, Feng, Qichun, Ferraro, Federico, Fournier, Amélie, Fritsch, Fritsch, Gan, Haonan, Gao, Feng, Garfagnini, Alberto, Gavrikov, Arsenii, Giammarchi, Marco, Giudice, Nunzio, Gonchar, Maxim, Gong, Guanghua, Gong, Hui, Gornushkin, Yuri, Grassi, Marco, Gromov, Maxim, Gromov, Vasily, Gu, Minghao, Gu, Xiaofei, Gu, Yu, Guan, Mengyun, Guan, Yuduo, Guardone, Nunzio, Guizzetti, Rosa Maria, Guo, Cong, Guo, Wanlei, Hagner, Caren, Han, Hechong, Han, Ran, Han, Yang, He, Jinhong, He, Miao, He, Wei, He, Xinhai, Heinz, Tobias, Hellmuth, Patrick, Heng, Yuekun, Herrera, Rafael, Hor, YuenKeung, Hou, Shaojing, Hsiung, Yee, Hu, Bei-Zhen, Hu, Hang, Hu, Jun, Hu, Peng, Hu, Shouyang, Hu, Tao, Hu, Yuxiang, Hu, Zhuojun, Huang, Guihong, Huang, Hanxiong, Huang, Jinhao, Huang, Junting, Huang, Kaixuan, Huang, Shengheng, Huang, Wenhao, Huang, Xin, Huang, Xingtao, Huang, Yongbo, Hui, Jiaqi, Huo, Lei, Huo, Wenju, Huss, Cédric, Hussain, Safeer, Imbert, Leonard, Ioannisian, Ara, Isocrate, Roberto, Jafar, Arshak, Jelmini, Beatrice, Jeria, Ignacio, Ji, Xiaolu, Jia, Huihui, Jia, Junji, Jian, Siyu, Jiang, Cailian, Jiang, Di, Jiang, Guangzheng, Jiang, Wei, Jiang, Xiaoshan, Jiang, Xiaozhao, Jiang, Yixuan, Jing, Xiaoping, Jollet, Cécile, Kang, Li, Karaparabil, Rebin, Kazarian, Narine, Khan, Ali, Khatun, Amina, Khosonthongkee, Khanchai, Korablev, Denis, Kouzakov, Konstantin, Krasnoperov, Alexey, Kuleshov, Sergey, Kumaran, Sindhujha, Kutovskiy, Nikolay, Labit, Loïc, Lachenmaier, Tobias, Lai, Haojing, Landini, Cecilia, Leblanc, Sébastien, Lefevre, Frederic, Lei, Ruiting, Leitner, Rupert, Leung, Jason, Li, Demin, Li, Fei, Li, Fule, Li, Gaosong, Li, Hongjian, Li, Huang, Li, Jiajun, Li, Min, Li, Nan, Li, Qingjiang, Li, Ruhui, Li, Rui, Li, Shanfeng, Li, Shuo, Li, Tao, Li, Teng, Li, Weidong, Li, Weiguo, Li, Xiaomei, Li, Xiaonan, Li, Xinglong, Li, Yi, Li, Yichen, Li, Yufeng, Li, Zhaohan, Li, Zhibing, Li, Ziyuan, Li, Zonghai, Liang, An-An, Liang, Hao, Liao, Jiajun, Liao, Yilin, Liao, Yuzhong, Limphirat, Ayut, Lin, Guey-Lin, Lin, Shengxin, Lin, Tao, Ling, Jiajie, Ling, Xin, Lippi, Ivano, Liu, Caimei, Liu, Fang, Liu, Fengcheng, Liu, Haidong, Liu, Haotian, Liu, Hongbang, Liu, Hongjuan, Liu, Hongtao, Liu, Hongyang, Liu, Jianglai, Liu, Jiaxi, Liu, Jinchang, Liu, Min, Liu, Qian, Liu, Qin, Liu, Runxuan, Liu, Shenghui, Liu, Shubin, Liu, Shulin, Liu, Xiaowei, Liu, Xiwen, Liu, Xuewei, Liu, Yankai, Liu, Zhen, Loi, Lorenzo, Lokhov, Alexey, Lombardi, Paolo, Lombardo, Claudio, Loo, Kai, Lu, Chuan, Lu, Haoqi, Lu, Jingbin, Lu, Junguang, Lu, Meishu, Lu, Peizhi, Lu, Shuxiang, Lu, Xianguo, Lubsandorzhiev, Bayarto, Lubsandorzhiev, Sultim, Ludhova, Livia, Lukanov, Arslan, Luo, Fengjiao, Luo, Guang, Luo, Jianyi, Luo, Shu, Luo, Wuming, Luo, Xiaojie, Lyashuk, Vladimir, Ma, Bangzheng, Ma, Bing, Ma, Qiumei, Ma, Si, Ma, Xiaoyan, Ma, Xubo, Maalmi, Jihane, Mai, Jingyu, Malabarba, Marco, Malyshkin, Yury, Mandujano, Roberto Carlos, Mantovani, Fabio, Mao, Xin, Mao, Yajun, Mari, Stefano M., Marini, Filippo, Martini, Agnese, Mayer, Matthias, Mayilyan, Davit, Mednieks, Ints, Meng, Yue, Meraviglia, Anita, Meregaglia, Anselmo, Meroni, Emanuela, Miramonti, Lino, Mohan, Nikhil, Montuschi, Michele, Reveco, Cristobal Morales, Nastasi, Massimiliano, Naumov, Dmitry V., Naumova, Elena, Navas-Nicolas, Diana, Nemchenok, Igor, Thi, Minh Thuan Nguyen, Nikolaev, Alexey, Ning, Feipeng, Ning, Zhe, Nunokawa, Hiroshi, Oberauer, Lothar, Ochoa-Ricoux, Juan Pedro, Olshevskiy, Alexander, Orestano, Domizia, Ortica, Fausto, Othegraven, Rainer, Paoloni, Alessandro, Parker, George, Parmeggiano, Sergio, Patsias, Achilleas, Pei, Yatian, Pelicci, Luca, Peng, Anguo, Peng, Haiping, Peng, Yu, Peng, Zhaoyuan, Percalli, Elisa, Perrin, Willy, Perrot, Frédéric, Petitjean, Pierre-Alexandre, Petrucci, Fabrizio, Pilarczyk, Oliver, Rico, Luis Felipe Piñeres, Popov, Artyom, Poussot, Pascal, Previtali, Ezio, Qi, Fazhi, Qi, Ming, Qi, Xiaohui, Qian, Sen, Qian, Xiaohui, Qian, Zhen, Qiao, Hao, Qin, Zhonghua, Qiu, Shoukang, Qu, Manhao, Qu, Zhenning, Ranucci, Gioacchino, Re, Alessandra, Rebii, Abdel, Redchuk, Mariia, Reina, Gioele, Ren, Bin, Ren, Jie, Ren, Yuhan, Ricci, Barbara, Rientong, Komkrit, Rifai, Mariam, Roche, Mathieu, Rodphai, Narongkiat, Romani, Aldo, Roskovec, Bedřich, Ruan, Xichao, Rybnikov, Arseniy, Sadovsky, Andrey, Saggese, Paolo, Sandanayake, Deshan, Sangka, Anut, Sava, Giuseppe, Sawangwit, Utane, Schever, Michaela, Schwab, Cédric, Schweizer, Konstantin, Selyunin, Alexandr, Serafini, Andrea, Settimo, Mariangela, Shao, Junyu, Sharov, Vladislav, Shi, Hexi, Shi, Jingyan, Shi, Yanan, Shutov, Vitaly, Sidorenkov, Andrey, Šimkovic, Fedor, Singhal, Apeksha, Sirignano, Chiara, Siripak, Jaruchit, Sisti, Monica, Smirnov, Mikhail, Smirnov, Oleg, Sokolov, Sergey, Songwadhana, Julanan, Soonthornthum, Boonrucksar, Sotnikov, Albert, Sreethawong, Warintorn, Stahl, Achim, Stanco, Luca, Stankevich, Konstantin, Steiger, Hans, Steinmann, Jochen, Sterr, Tobias, Stock, Matthias Raphael, Strati, Virginia, Strizh, Michail, Studenikin, Alexander, Su, Aoqi, Su, Jun, Sun, Guangbao, Sun, Shifeng, Sun, Xilei, Sun, Yongjie, Sun, Yongzhao, Sun, Zhengyang, Suwonjandee, Narumon, Takenaka, Akira, Tan, Xiaohan, Tang, Jian, Tang, Jingzhe, Tang, Qiang, Tang, Quan, Tang, Xiao, Hariharan, Vidhya Thara, Tkachev, Igor, Tmej, Tomas, Torri, Marco Danilo Claudio, Triossi, Andrea, Trzaska, Wladyslaw, Tung, Yu-Chen, Tuve, Cristina, Ushakov, Nikita, Vedin, Vadim, Venettacci, Carlo, Verde, Giuseppe, Vialkov, Maxim, Viaud, Benoit, Vollbrecht, Cornelius Moritz, von Sturm, Katharina, Vorobel, Vit, Voronin, Dmitriy, Votano, Lucia, Walker, Pablo, Wang, Caishen, Wang, Chung-Hsiang, Wang, En, Wang, Guoli, Wang, Hanwen, Wang, Jian, Wang, Jun, Wang, Li, Wang, Lu, Wang, Meng, Wang, Mingyuan, Wang, Qianchuan, Wang, Ruiguang, Wang, Sibo, Wang, Siguang, Wang, Wei, Wang, Wenshuai, Wang, Xi, Wang, Xiangyue, Wang, Yangfu, Wang, Yaoguang, Wang, Yi, Wang, Yifang, Wang, Yuanqing, Wang, Yuyi, Wang, Zhe, Wang, Zheng, Wang, Zhimin, Watcharangkool, Apimook, Wei, Wei, Wei, Wenlu, Wei, Yadong, Wei, Yuehuan, Wen, Liangjian, Weng, Jun, Wiebusch, Christopher, Wirth, Rosmarie, Wu, Chengxin, Wu, Diru, Wu, Qun, Wu, Yinhui, Wu, Yiyang, Wu, Zhi, Wurm, Michael, Wurtz, Jacques, Wysotzki, Christian, Xi, Yufei, Xia, Dongmei, Xian, Shishen, Xiang, Ziqian, Xiao, Fei, Xiao, Xiang, Xie, Xiaochuan, Xie, Yijun, Xie, Yuguang, Xin, Zhao, Xing, Zhizhong, Xu, Benda, Xu, Cheng, Xu, Donglian, Xu, Fanrong, Xu, Hangkun, Xu, Jiayang, Xu, Jilei, Xu, Jing, Xu, Jinghuan, Xu, Meihang, Xu, Xunjie, Xu, Yin, Xu, Yu, Yan, Baojun, Yan, Qiyu, Yan, Taylor, Yan, Xiongbo, Yan, Yupeng, Yang, Changgen, Yang, Chengfeng, Yang, Fengfan, Yang, Jie, Yang, Lei, Yang, Pengfei, Yang, Xiaoyu, Yang, Yifan, Yang, Yixiang, Yang, Zekun, Yao, Haifeng, Ye, Jiaxuan, Ye, Mei, Ye, Ziping, Yermia, Frédéric, You, Zhengyun, Yu, Boxiang, Yu, Chiye, Yu, Chunxu, Yu, Guojun, Yu, Hongzhao, Yu, Miao, Yu, Xianghui, Yu, Zeyuan, Yu, Zezhong, Yuan, Cenxi, Yuan, Chengzhuo, Yuan, Ying, Yuan, Zhenxiong, Yue, Baobiao, Zafar, Noman, Zamogilnyi, Kirill, Zavadskyi, Vitalii, Zeng, Fanrui, Zeng, Shan, Zeng, Tingxuan, Zeng, Yuda, Zhan, Liang, Zhang, Aiqiang, Zhang, Bin, Zhang, Binting, Zhang, Feiyang, Zhang, Hangchang, Zhang, Haosen, Zhang, Honghao, Zhang, Jialiang, Zhang, Jiawen, Zhang, Jie, Zhang, Jingbo, Zhang, Jinnan, Zhang, Junwei, Zhang, Lei, Zhang, Peng, Zhang, Ping, Zhang, Qingmin, Zhang, Shiqi, Zhang, Shu, Zhang, Shuihan, Zhang, Siyuan, Zhang, Tao, Zhang, Xiaomei, Zhang, Xin, Zhang, Xuantong, Zhang, Yibing, Zhang, Yinhong, Zhang, Yiyu, Zhang, Yongpeng, Zhang, Yu, Zhang, Yuanyuan, Zhang, Yumei, Zhang, Zhenyu, Zhang, Zhijian, Zhao, Jie, Zhao, Rong, Zhao, Runze, Zhao, Shujun, Zhao, Tianhao, Zheng, Hua, Zheng, Yangheng, Zhou, Jing, Zhou, Li, Zhou, Nan, Zhou, Shun, Zhou, Tong, Zhou, Xiang, Zhou, Xing, Zhu, Jingsen, Zhu, Kangfu, Zhu, Kejun, Zhu, Zhihang, Zhuang, Bo, Zhuang, Honglin, Zong, Liang, and Zou, Jiaheng

Subjects
High Energy Physics - Experiment, High Energy Physics - Phenomenology
Abstract

We explore the bound neutrons decay into invisible particles (e.g., $n\rightarrow 3 \nu$ or $nn \rightarrow 2 \nu$) in the JUNO liquid scintillator detector. The invisible decay includes two decay modes: $ n \rightarrow { inv} $ and $ nn \rightarrow { inv} $. The invisible decays of $s$-shell neutrons in $^{12}{\rm C}$ will leave a highly excited residual nucleus. Subsequently, some de-excitation modes of the excited residual nuclei can produce a time- and space-correlated triple coincidence signal in the JUNO detector. Based on a full Monte Carlo simulation informed with the latest available data, we estimate all backgrounds, including inverse beta decay events of the reactor antineutrino $\bar{\nu}_e$, natural radioactivity, cosmogenic isotopes and neutral current interactions of atmospheric neutrinos. Pulse shape discrimination and multivariate analysis techniques are employed to further suppress backgrounds. With two years of exposure, JUNO is expected to give an order of magnitude improvement compared to the current best limits. After 10 years of data taking, the JUNO expected sensitivities at a 90% confidence level are $\tau/B( n \rightarrow { inv} ) > 5.0 \times 10^{31} \, {\rm yr}$ and $\tau/B( nn \rightarrow { inv} ) > 1.4 \times 10^{32} \, {\rm yr}$., Comment: 28 pages, 7 figures, 4 tables

Published
2024

2. Enhancing RAW-to-sRGB with Decoupled Style Structure in Fourier Domain

Author

He, Xuanhua, Hu, Tao, Wang, Guoli, Wang, Zejin, Wang, Run, Zhang, Qian, Yan, Keyu, Chen, Ziyi, Li, Rui, Xie, Chenjun, Zhang, Jie, and Zhou, Man

Subjects
Computer Science - Computer Vision and Pattern Recognition
Abstract

RAW to sRGB mapping, which aims to convert RAW images from smartphones into RGB form equivalent to that of Digital Single-Lens Reflex (DSLR) cameras, has become an important area of research. However, current methods often ignore the difference between cell phone RAW images and DSLR camera RGB images, a difference that goes beyond the color matrix and extends to spatial structure due to resolution variations. Recent methods directly rebuild color mapping and spatial structure via shared deep representation, limiting optimal performance. Inspired by Image Signal Processing (ISP) pipeline, which distinguishes image restoration and enhancement, we present a novel Neural ISP framework, named FourierISP. This approach breaks the image down into style and structure within the frequency domain, allowing for independent optimization. FourierISP is comprised of three subnetworks: Phase Enhance Subnet for structural refinement, Amplitude Refine Subnet for color learning, and Color Adaptation Subnet for blending them in a smooth manner. This approach sharpens both color and structure, and extensive evaluations across varied datasets confirm that our approach realizes state-of-the-art results. Code will be available at ~\url{https://github.com/alexhe101/FourierISP}.

Published
2024

9. The Effect of Inflation Pressure on the Dielectric Recovery Strength of SF6 Circuit Breakers

Author

Xu, Shijin, Luo, Wei, Wang, Guoli, Gao, Chao, Zhou, Fusheng, Zheng, Yao, Huang, Ruodong, Zhou, Ran, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Chakraborty, Samarjit, Series Editor, Chen, Jiming, Series Editor, Chen, Shanben, Series Editor, Chen, Tan Kay, Series Editor, Dillmann, Rüdiger, Series Editor, Duan, Haibin, Series Editor, Ferrari, Gianluigi, Series Editor, Ferre, Manuel, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Li, Yong, Series Editor, Liang, Qilian, Series Editor, Martín, Ferran, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, Series Editor, Oneto, Luca, Series Editor, Panigrahi, Bijaya Ketan, Series Editor, Pascucci, Federica, Series Editor, Qin, Yong, Series Editor, Seng, Gan Woon, Series Editor, Speidel, Joachim, Series Editor, Veiga, Germano, Series Editor, Wu, Haitao, Series Editor, Zamboni, Walter, Series Editor, Zhang, Junjie James, Series Editor, Tan, Kay Chen, Series Editor, Dong, Xuzhu, editor, and Cai, Li, editor

Published
2024
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10. Simulation of Arc Breaking in a 550 kV 80 kA SF6 Circuit Breaker

Author

Wang, Guoli, Zhong, Weihua, Gao, Chao, Zhou, Fusheng, Yang, Yun, Xiong, Jiaming, Chen, Xipeng, Jia, Lei, Chen, Shizhe, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Chakraborty, Samarjit, Series Editor, Chen, Jiming, Series Editor, Chen, Shanben, Series Editor, Chen, Tan Kay, Series Editor, Dillmann, Rüdiger, Series Editor, Duan, Haibin, Series Editor, Ferrari, Gianluigi, Series Editor, Ferre, Manuel, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Li, Yong, Series Editor, Liang, Qilian, Series Editor, Martín, Ferran, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, Series Editor, Oneto, Luca, Series Editor, Panigrahi, Bijaya Ketan, Series Editor, Pascucci, Federica, Series Editor, Qin, Yong, Series Editor, Seng, Gan Woon, Series Editor, Speidel, Joachim, Series Editor, Veiga, Germano, Series Editor, Wu, Haitao, Series Editor, Zamboni, Walter, Series Editor, Zhang, Junjie James, Series Editor, Tan, Kay Chen, Series Editor, Dong, Xuzhu, editor, and Cai, Li, editor

Published
2024
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22. Model-independent Approach of the JUNO 8B Solar Neutrino Program

Author

Zhao, Jie, primary, Yue, Baobiao, additional, Lu, Haoqi, additional, Li, Yufeng, additional, Ling, Jiajie, additional, Yu, Zeyuan, additional, Abusleme, Angel, additional, Adam, Thomas, additional, Ahmad, Shakeel, additional, Ahmed, Rizwan, additional, Aiello, Sebastiano, additional, Akram, Muhammad, additional, Aleem, Abid, additional, Alexandros, Tsagkarakis, additional, An, Fengpeng, additional, An, Qi, additional, Andronico, Giuseppe, additional, Anfimov, Nikolay, additional, Antonelli, Vito, additional, Antoshkina, Tatiana, additional, Asavapibhop, Burin, additional, Athayde Marcondes de André, João Pedro, additional, Auguste, Didier, additional, Bai, Weidong, additional, Balashov, Nikita, additional, Baldini, Wander, additional, Barresi, Andrea, additional, Basilico, Davide, additional, Baussan, Eric, additional, Bellato, Marco, additional, Bergnoli, Antonio, additional, Birkenfeld, Thilo, additional, Blin, Sylvie, additional, Blum, David, additional, Blyth, Simon, additional, Bolshakova, Anastasia, additional, Bongrand, Mathieu, additional, Bordereau, Clément, additional, Breton, Dominique, additional, Brigatti, Augusto, additional, Brugnera, Riccardo, additional, Bruno, Riccardo, additional, Budano, Antonio, additional, Busto, Jose, additional, Butorov, Ilya, additional, Cabrera, Anatael, additional, Caccianiga, Barbara, additional, Cai, Hao, additional, Cai, Xiao, additional, Cai, Yanke, additional, Cai, Zhiyan, additional, Callegari, Riccardo, additional, Cammi, Antonio, additional, Campeny, Agustin, additional, Cao, Chuanya, additional, Cao, Guofu, additional, Cao, Jun, additional, Caruso, Rossella, additional, Cerna, Cédric, additional, Chan, Chi, additional, Chang, Jinfan, additional, Chang, Yun, additional, Chen, Guoming, additional, Chen, Pingping, additional, Chen, Po-An, additional, Chen, Shaomin, additional, Chen, Xurong, additional, Chen, Yixue, additional, Chen, Yu, additional, Chen, Zhiyuan, additional, Chen, Zikang, additional, Cheng, Jie, additional, Cheng, Yaping, additional, Chepurnov, Alexander, additional, Chetverikov, Alexey, additional, Chiesa, Davide, additional, Chimenti, Pietro, additional, Chukanov, Artem, additional, Claverie, Gérard, additional, Clementi, Catia, additional, Clerbaux, Barbara, additional, Molla, Marta Colomer, additional, Conforti Di Lorenzo, Selma, additional, Corti, Daniele, additional, Dal Corso, Flavio, additional, Dalager, Olivia, additional, De La Taille, Christophe, additional, Deng, Zhi, additional, Deng, Ziyan, additional, Depnering, Wilfried, additional, Diaz, Marco, additional, Ding, Xuefeng, additional, Ding, Yayun, additional, Dirgantara, Bayu, additional, Dmitrievsky, Sergey, additional, Dohnal, Tadeas, additional, Dolzhikov, Dmitry, additional, Donchenko, Georgy, additional, Dong, Jianmeng, additional, Doroshkevich, Evgeny, additional, Dracos, Marcos, additional, Druillole, Frédéric, additional, Du, Ran, additional, Du, Shuxian, additional, Dusini, Stefano, additional, Dvorak, Martin, additional, Enqvist, Timo, additional, Enzmann, Heike, additional, Fabbri, Andrea, additional, Fan, Donghua, additional, Fan, Lei, additional, Fang, Jian, additional, Fang, Wenxing, additional, Fargetta, Marco, additional, Fedoseev, Dmitry, additional, Fei, Zhengyong, additional, Feng, Li-Cheng, additional, Feng, Qichun, additional, Ford, Richard, additional, Fournier, Amélie, additional, Gan, Haonan, additional, Gao, Feng, additional, Garfagnini, Alberto, additional, Gavrikov, Arsenii, additional, Giammarchi, Marco, additional, Giudice, Nunzio, additional, Gonchar, Maxim, additional, Gong, Guanghua, additional, Gong, Hui, additional, Gornushkin, Yuri, additional, Göttel, Alexandre, additional, Grassi, Marco, additional, Gromov, Maxim, additional, Gromov, Vasily, additional, Gu, Minghao, additional, Gu, Xiaofei, additional, Gu, Yu, additional, Guan, Mengyun, additional, Guan, Yuduo, additional, Guardone, Nunzio, additional, Guo, Cong, additional, Guo, Jingyuan, additional, Guo, Wanlei, additional, Guo, Xinheng, additional, Guo, Yuhang, additional, Hackspacher, Paul, additional, Hagner, Caren, additional, Han, Ran, additional, Han, Yang, additional, He, Miao, additional, He, Wei, additional, Heinz, Tobias, additional, Hellmuth, Patrick, additional, Heng, Yuekun, additional, Herrera, Rafael, additional, Hor, YuenKeung, additional, Hou, Shaojing, additional, Hsiung, Yee, additional, Hu, Bei-Zhen, additional, Hu, Hang, additional, Hu, Jianrun, additional, Hu, Jun, additional, Hu, Shouyang, additional, Hu, Tao, additional, Hu, Yuxiang, additional, Hu, Zhuojun, additional, Huang, Guihong, additional, Huang, Hanxiong, additional, Huang, Kaixuan, additional, Huang, Wenhao, additional, Huang, Xin, additional, Huang, Xingtao, additional, Huang, Yongbo, additional, Hui, Jiaqi, additional, Huo, Lei, additional, Huo, Wenju, additional, Huss, Cédric, additional, Hussain, Safeer, additional, Ioannisian, Ara, additional, Isocrate, Roberto, additional, Jelmini, Beatrice, additional, Jeria, Ignacio, additional, Ji, Xiaolu, additional, Jia, Huihui, additional, Jia, Junji, additional, Jian, Siyu, additional, Jiang, Di, additional, Jiang, Wei, additional, Jiang, Xiaoshan, additional, Jing, Xiaoping, additional, Jollet, Cécile, additional, Kalousis, Leonidas, additional, Kampmann, Philipp, additional, Kang, Li, additional, Karaparambil, Rebin, additional, Kazarian, Narine, additional, Khatun, Amina, additional, Khosonthongkee, Khanchai, additional, Korablev, Denis, additional, Kouzakov, Konstantin, additional, Krasnoperov, Alexey, additional, Kutovskiy, Nikolay, additional, Kuusiniemi, Pasi, additional, Lachenmaier, Tobias, additional, Landini, Cecilia, additional, Leblanc, Sébastien, additional, Lebrin, Victor, additional, Lefevre, Frederic, additional, Lei, Ruiting, additional, Leitner, Rupert, additional, Leung, Jason, additional, Li, Daozheng, additional, Li, Demin, additional, Li, Fei, additional, Li, Fule, additional, Li, Gaosong, additional, Li, Huiling, additional, Li, Mengzhao, additional, Li, Min, additional, Li, Nan, additional, Li, Qingjiang, additional, Li, Ruhui, additional, Li, Rui, additional, Li, Shanfeng, additional, Li, Tao, additional, Li, Teng, additional, Li, Weidong, additional, Li, Weiguo, additional, Li, Xiaomei, additional, Li, Xiaonan, additional, Li, Xinglong, additional, Li, Yi, additional, Li, Yichen, additional, Li, Zepeng, additional, Li, Zhaohan, additional, Li, Zhibing, additional, Li, Ziyuan, additional, Li, Zonghai, additional, Liang, Hao, additional, Liao, Jiajun, additional, Limphirat, Ayut, additional, Lin, Guey-Lin, additional, Lin, Shengxin, additional, Lin, Tao, additional, Lippi, Ivano, additional, Liu, Fang, additional, Liu, Haidong, additional, Liu, Haotian, additional, Liu, Hongbang, additional, Liu, Hongjuan, additional, Liu, Hongtao, additional, Liu, Hui, additional, Liu, Jianglai, additional, Liu, Jinchang, additional, Liu, Min, additional, Liu, Qian, additional, Liu, Qin, additional, Liu, Runxuan, additional, Liu, Shubin, additional, Liu, Shulin, additional, Liu, Xiaowei, additional, Liu, Xiwen, additional, Liu, Yan, additional, Liu, Yunzhe, additional, Lokhov, Alexey, additional, Lombardi, Paolo, additional, Lombardo, Claudio, additional, Loo, Kai, additional, Lu, Chuan, additional, Lu, Jingbin, additional, Lu, Junguang, additional, Lu, Shuxiang, additional, Lubsandorzhiev, Bayarto, additional, Lubsandorzhiev, Sultim, additional, Ludhova, Livia, additional, Lukanov, Arslan, additional, Luo, Daibin, additional, Luo, Fengjiao, additional, Luo, Guang, additional, Luo, Shu, additional, Luo, Wuming, additional, Luo, Xiaojie, additional, Lyashuk, Vladimir, additional, Ma, Bangzheng, additional, Ma, Bing, additional, Ma, Qiumei, additional, Ma, Si, additional, Ma, Xiaoyan, additional, Ma, Xubo, additional, Maalmi, Jihane, additional, Mai, Jingyu, additional, Malyshkin, Yury, additional, Mandujano, Roberto Carlos, additional, Mantovani, Fabio, additional, Manzali, Francesco, additional, Mao, Xin, additional, Mao, Yajun, additional, Mari, Stefano M., additional, Marini, Filippo, additional, Martellini, Cristina, additional, Martin-Chassard, Gisele, additional, Martini, Agnese, additional, Mayer, Matthias, additional, Mayilyan, Davit, additional, Mednieks, Ints, additional, Meng, Yue, additional, Meregaglia, Anselmo, additional, Meroni, Emanuela, additional, Meyhöfer, David, additional, Mezzetto, Mauro, additional, Miller, Jonathan, additional, Miramonti, Lino, additional, Montini, Paolo, additional, Montuschi, Michele, additional, Müller, Axel, additional, Nastasi, Massimiliano, additional, Naumov, Dmitry V., additional, Naumova, Elena, additional, Navas-Nicolas, Diana, additional, Nemchenok, Igor, additional, Nguyen Thi, Minh Thuan, additional, Nikolaev, Alexey, additional, Ning, Feipeng, additional, Ning, Zhe, additional, Nunokawa, Hiroshi, additional, Oberauer, Lothar, additional, Ochoa-Ricoux, Juan Pedro, additional, Olshevskiy, Alexander, additional, Orestano, Domizia, additional, Ortica, Fausto, additional, Othegraven, Rainer, additional, Paoloni, Alessandro, additional, Parmeggiano, Sergio, additional, Pei, Yatian, additional, Pelliccia, Nicomede, additional, Peng, Anguo, additional, Peng, Haiping, additional, Peng, Yu, additional, Peng, Zhaoyuan, additional, Perrot, Frédéric, additional, Petitjean, Pierre-Alexandre, additional, Petrucci, Fabrizio, additional, Pilarczyk, Oliver, additional, Piñeres Rico, Luis Felipe, additional, Popov, Artyom, additional, Poussot, Pascal, additional, Previtali, Ezio, additional, Qi, Fazhi, additional, Qi, Ming, additional, Qian, Sen, additional, Qian, Xiaohui, additional, Qian, Zhen, additional, Qiao, Hao, additional, Qin, Zhonghua, additional, Qiu, Shoukang, additional, Ranucci, Gioacchino, additional, Raper, Neill, additional, Re, Alessandra, additional, Rebber, Henning, additional, Rebii, Abdel, additional, Redchuk, Mariia, additional, Ren, Bin, additional, Ren, Jie, additional, Ricci, Barbara, additional, Rifai, Mariam, additional, Roche, Mathieu, additional, Rodphai, Narongkiat, additional, Romani, Aldo, additional, Roskovec, Bedřich, additional, Ruan, Xichao, additional, Rybnikov, Arseniy, additional, Sadovsky, Andrey, additional, Saggese, Paolo, additional, Sanfilippo, Simone, additional, Sangka, Anut, additional, Sawangwit, Utane, additional, Sawatzki, Julia, additional, Schever, Michaela, additional, Schwab, Cédric, additional, Schweizer, Konstantin, additional, Selyunin, Alexandr, additional, Serafini, Andrea, additional, Settanta, Giulio, additional, Settimo, Mariangela, additional, Shao, Zhuang, additional, Sharov, Vladislav, additional, Shaydurova, Arina, additional, Shi, Jingyan, additional, Shi, Yanan, additional, Shutov, Vitaly, additional, Sidorenkov, Andrey, additional, Šimkovic, Fedor, additional, Sirignano, Chiara, additional, Siripak, Jaruchit, additional, Sisti, Monica, additional, Slupecki, Maciej, additional, Smirnov, Mikhail, additional, Smirnov, Oleg, additional, Sogo-Bezerra, Thiago, additional, Sokolov, Sergey, additional, Songwadhana, Julanan, additional, Soonthornthum, Boonrucksar, additional, Sotnikov, Albert, additional, Šrámek, Ondřej, additional, Sreethawong, Warintorn, additional, Stahl, Achim, additional, Stanco, Luca, additional, Stankevich, Konstantin, additional, Štefánik, Dušan, additional, Steiger, Hans, additional, Steinmann, Jochen, additional, Sterr, Tobias, additional, Stock, Matthias Raphael, additional, Strati, Virginia, additional, Studenikin, Alexander, additional, Su, Jun, additional, Sun, Shifeng, additional, Sun, Xilei, additional, Sun, Yongjie, additional, Sun, Yongzhao, additional, Sun, Zhengyang, additional, Suwonjandee, Narumon, additional, Szelezniak, Michal, additional, Tang, Jian, additional, Tang, Qiang, additional, Tang, Quan, additional, Tang, Xiao, additional, Tietzsch, Alexander, additional, Tkachev, Igor, additional, Tmej, Tomas, additional, Claudio Torri, Marco Danilo, additional, Treskov, Konstantin, additional, Triossi, Andrea, additional, Troni, Giancarlo, additional, Trzaska, Wladyslaw, additional, Tuve, Cristina, additional, Ushakov, Nikita, additional, Vedin, Vadim, additional, Verde, Giuseppe, additional, Vialkov, Maxim, additional, Viaud, Benoit, additional, Vollbrecht, Cornelius Moritz, additional, Volpe, Cristina, additional, von Sturm, Katharina, additional, Vorobel, Vit, additional, Voronin, Dmitriy, additional, Votano, Lucia, additional, Walker, Pablo, additional, Wang, Caishen, additional, Wang, Chung-Hsiang, additional, Wang, En, additional, Wang, Guoli, additional, Wang, Jian, additional, Wang, Jun, additional, Wang, Lu, additional, Wang, Meifen, additional, Wang, Meng, additional, Wang, Ruiguang, additional, Wang, Siguang, additional, Wang, Wei, additional, Wang, Wenshuai, additional, Wang, Xi, additional, Wang, Xiangyue, additional, Wang, Yangfu, additional, Wang, Yaoguang, additional, Wang, Yi, additional, Wang, Yifang, additional, Wang, Yuanqing, additional, Wang, Yuman, additional, Wang, Zhe, additional, Wang, Zheng, additional, Wang, Zhimin, additional, Wang, Zongyi, additional, Watcharangkool, Apimook, additional, Wei, Wei, additional, Wei, Wenlu, additional, Wei, Yadong, additional, Wen, Kaile, additional, Wen, Liangjian, additional, Wiebusch, Christopher, additional, Wong, Steven Chan-Fai, additional, Wonsak, Bjoern, additional, Wu, Diru, additional, Wu, Qun, additional, Wu, Zhi, additional, Wurm, Michael, additional, Wurtz, Jacques, additional, Wysotzki, Christian, additional, Xi, Yufei, additional, Xia, Dongmei, additional, Xiao, Xiang, additional, Xie, Xiaochuan, additional, Xie, Yuguang, additional, Xie, Zhangquan, additional, Xin, Zhao, additional, Xing, Zhizhong, additional, Xu, Benda, additional, Xu, Cheng, additional, Xu, Donglian, additional, Xu, Fanrong, additional, Xu, Hangkun, additional, Xu, Jilei, additional, Xu, Jing, additional, Xu, Meihang, additional, Xu, Yin, additional, Xu, Yu, additional, Yan, Baojun, additional, Yan, Taylor, additional, Yan, Wenqi, additional, Yan, Xiongbo, additional, Yan, Yupeng, additional, Yang, Changgen, additional, Yang, Chengfeng, additional, Yang, Huan, additional, Yang, Jie, additional, Yang, Lei, additional, Yang, Xiaoyu, additional, Yang, Yifan, additional, Yao, Haifeng, additional, Ye, Jiaxuan, additional, Ye, Mei, additional, Ye, Ziping, additional, Yermia, Frédéric, additional, Yin, Na, additional, You, Zhengyun, additional, Yu, Boxiang, additional, Yu, Chiye, additional, Yu, Chunxu, additional, Yu, Hongzhao, additional, Yu, Miao, additional, Yu, Xianghui, additional, Yu, Zezhong, additional, Yuan, Cenxi, additional, Yuan, Chengzhuo, additional, Yuan, Ying, additional, Yuan, Zhenxiong, additional, Zafar, Noman, additional, Zavadskyi, Vitalii, additional, Zeng, Shan, additional, Zeng, Tingxuan, additional, Zeng, Yuda, additional, Zhan, Liang, additional, Zhang, Aiqiang, additional, Zhang, Bin, additional, Zhang, Binting, additional, Zhang, Feiyang, additional, Zhang, Guoqing, additional, Zhang, Honghao, additional, Zhang, Jialiang, additional, Zhang, Jiawen, additional, Zhang, Jie, additional, Zhang, Jin, additional, Zhang, Jingbo, additional, Zhang, Jinnan, additional, Zhang, Mohan, additional, Zhang, Peng, additional, Zhang, Qingmin, additional, Zhang, Shiqi, additional, Zhang, Shu, additional, Zhang, Tao, additional, Zhang, Xiaomei, additional, Zhang, Xin, additional, Zhang, Xuantong, additional, Zhang, Xueyao, additional, Zhang, Yinhong, additional, Zhang, Yiyu, additional, Zhang, Yongpeng, additional, Zhang, Yu, additional, Zhang, Yuanyuan, additional, Zhang, Yumei, additional, Zhang, Zhenyu, additional, Zhang, Zhijian, additional, Zhao, Fengyi, additional, Zhao, Rong, additional, Zhao, Runze, additional, Zhao, Shujun, additional, Zheng, Dongqin, additional, Zheng, Hua, additional, Zheng, Yangheng, additional, Zhong, Weirong, additional, Zhou, Jing, additional, Zhou, Li, additional, Zhou, Nan, additional, Zhou, Shun, additional, Zhou, Tong, additional, Zhou, Xiang, additional, Zhu, Jiang, additional, Zhu, Jingsen, additional, Zhu, Kangfu, additional, Zhu, Kejun, additional, Zhu, Zhihang, additional, Zhuang, Bo, additional, Zhuang, Honglin, additional, Zong, Liang, additional, and Zou, Jiaheng, additional

Published
2024
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25. Divergent Roles of the Auxin Response Factors in Lemongrass (Cymbopogon flexuosus (Nees ex Steud.) W. Watson) during Plant Growth.

Author

Wang, Guoli, Zeng, Jian, Du, Canghao, Tang, Qi, Hua, Yuqing, Chen, Mingjie, Yang, Guangxiao, Tu, Min, He, Guangyuan, Li, Yin, He, Jinming, and Chang, Junli

Abstract

Auxin Response Factors (ARFs) make up a plant-specific transcription factor family that mainly couples perception of the phytohormone, auxin, and gene expression programs and plays an important and multi-faceted role during plant growth and development. Lemongrass (Cymbopogon flexuosus) is a representative Cymbopogon species widely used in gardening, beverages, fragrances, traditional medicine, and heavy metal phytoremediation. Biomass yield is an important trait for several agro-economic purposes of lemongrass, such as landscaping, essential oil production, and phytoremediation. Therefore, we performed gene mining of CfARFs and identified 26 and 27 CfARF-encoding genes in each of the haplotype genomes of lemongrass, respectively. Phylogenetic and domain architecture analyses showed that CfARFs can be divided into four groups, among which groups 1, 2, and 3 correspond to activator, repressor, and ETTN-like ARFs, respectively. To identify the CfARFs that may play major roles during the growth of lemongrass plants, RNA-seq was performed on three tissues (leaf, stem, and root) and four developmental stages (3-leaf, 4-leaf, 5-leaf. and mature stages). The expression profiling of CfARFs identified several highly expressed activator and repressor CfARFs and three CfARFs (CfARF3, 18, and 35) with gradually increased levels during leaf growth. Haplotype-resolved transcriptome analysis revealed that biallelic expression dominance is frequent among CfARFs and contributes to their gene expression patterns. In addition, co-expression network analysis identified the modules enriched with CfARFs. By establishing orthologous relationships among CfARFs, sorghum ARFs, and maize ARFs, we showed that CfARFs were mainly expanded by whole-genome duplications, and that the duplicated CfARFs might have been divergent due to differential expression and variations in domains and motifs. Our work provides a detailed catalog of CfARFs in lemongrass, representing a first step toward characterizing CfARF functions, and may be useful in molecular breeding to enhance lemongrass plant growth. [ABSTRACT FROM AUTHOR]

Published
2024
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26. A Sponge Village Flood Response Method Based on GIS and RS Analysis Formation—A Case Study of Jiangou Village.

Author

Liang, Xuanshuo, Guo, Ming, and Wang, Guoli

Subjects
FLOOD damage prevention, GEOGRAPHIC information systems, FLOOD risk, RESERVOIRS, FLOODS, WATER storage, RAINFALL, PRECIPITATION gauges, BODIES of water
Abstract

This study was conducted in response to the Beijing–Tianjin–Hebei mega heavy rainfall event at the end of July 2023, and the severely affected and representative Jiangou village in Beijing was selected as the study area. A variety of methods were used to synthesize and analyze the situation and propose an adaptive response to heavy rainfall and flooding in the village. Based on multi-source remote sensing (RS) data, a comprehensive topographic and hydrological characterization was carried out, and the precipitation before and after the disaster was analyzed; the flood inundation area was extracted using the improved normalized water body index (MNDWI) and OTSU thresholding methods, and the changes of water bodies during the flooding period were quantitatively analyzed; and an improved convolutional-neural-network-based building identification and extraction model was constructed to extract the research distribution of buildings in the area. The sponge city construction (SPCC) method was improved to obtain a method that can mitigate flood risk and adapt to villages by constructing small artificial lakes and local topographic buffers to improve the water storage and drainage capacity of villages. The study shows that these methods are innovative in flood hazard analysis and mitigation but still need further improvement in data accuracy, simulation depth, and system evaluation. [ABSTRACT FROM AUTHOR]

Published
2024
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31. 3D Change Detection Method for Exterior Wall of LNG Storage Tank Supported by Multi‐Source Spatial Data.

Author

Gao, Chutian, Guo, Ming, Wang, Guoli, Guo, Kecai, and Zhao, Youshan

Subjects
LIQUEFIED natural gas storage, OPTICAL scanners, STORAGE tanks, EXTERIOR walls, AIRBORNE lasers, POINT cloud, DEFORMATIONS (Mechanics)
Abstract

Change detection methods for measuring deformation of the LNG storage tank's exterior wall cannot meet the requirements for extensive and comprehensive deformation analysis. The method proposed in this paper uses multi‐source spatial data to detect the deformation of the LNG storage tank's exterior wall. Exterior wall data collected simultaneously by terrestrial and airborne laser scanners, as well as close‐range and oblique photogrammetry, are pre‐processed separately and then registered to the global point clouds. The deformation state of exterior wall is represented by a thorough assessment approach that takes into account four change indices. The results suggest that the registration precision of global point clouds is 6 mm. The global ovality of the LNG storage tank is 0.053%, with a tilt change of 2.58° and a deviation of 27 mm in the direction of the azimuth of 321.98°, an average value of 0.07 mm for depression and protrusion deformation, and a surface flatness of 21.3 mm. In this case, the flatness is greater than the variation threshold of the standard specification, indicating that the tank may have structural uneven settlement or other deformation problems. The attraction of the proposed method resides in its capacity to efficiently and accurately obtain spatial positioning and color information of the LNG storage tank's exterior wall, thereby providing a robust foundation for precise judgments regarding the deformation state. [ABSTRACT FROM AUTHOR]

Published
2024
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34. The microbial biosynthesis of noncanonical terpenoids.

Author

Ma, Mengyu, Li, Mingkai, Wu, Zhenke, Liang, Xiqin, Zheng, Qiusheng, Li, Defang, Wang, Guoli, and An, Tianyue

Subjects
METABOLITES, BIOSYNTHESIS, GANODERMA lucidum, TERPENES, TRITERPENES, BIOCHEMICAL substrates
Abstract

Terpenoids are a class of structurally complex, naturally occurring compounds found predominantly in plant, animal, and microorganism secondary metabolites. Classical terpenoids typically have carbon atoms in multiples of five and follow well-defined carbon skeletons, whereas noncanonical terpenoids deviate from these patterns. These noncanonical terpenoids often result from the methyltransferase-catalyzed methylation modification of substrate units, leading to irregular carbon skeletons. In this comprehensive review, various activities and applications of these noncanonical terpenes have been summarized. Importantly, the review delves into the biosynthetic pathways of noncanonical terpenes, including those with C6, C7, C11, C12, and C16 carbon skeletons, in bacteria and fungi host. It also covers noncanonical triterpenes synthesized from non-squalene substrates and nortriterpenes in Ganoderma lucidum, providing detailed examples to elucidate the intricate biosynthetic processes involved. Finally, the review outlines the potential future applications of noncanonical terpenoids. In conclusion, the insights gathered from this review provide a reference for understanding the biosynthesis of these noncanonical terpenes and pave the way for the discovery of additional unique and novel noncanonical terpenes. Key points: •The activities and applications of noncanonical terpenoids are introduced. •The noncanonical terpenoids with irregular carbon skeletons are presented. •The microbial biosynthesis of noncanonical terpenoids is summarized. [ABSTRACT FROM AUTHOR]

Published
2024
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35. Spatial–Temporal Multiscale Constrained Learning for mmWave-Based Human Pose Estimation

Author

Chen, Lin, Guo, Xuemei, Wang, Guoli, and Li, Hongyi

Abstract

It is a challenging task to reconstruct human pose from millimeter wave (mmWave) radar point clouds due to their sparsity and sensitivity to multipath noise. In order to enhance the inference ability of deep learning models in processing sparse radar point clouds, a learning paradigm with spatial and temporal multiscale constraints is proposed, utilizing prior relationships in skeletal structure and joint movements in both time and space to constrain the learning of pose sequences. Specifically, the proposed spatial multiscale constraint block learns the spatial constraint relationships of human joints using three different scales: adjacent joint constraint, part-level kinematic constraint, and global joint constraint, by which the spatial joint constraint features are aggregated by fusion gate mechanism. On the other hand, the temporal multiscale constraint block is devised to learn the temporal constraint relationships of the joint trajectories using the information of the joint itself and local context-information in time domain. Compared with the single-scale constrained learning paradigm, the potential advantage of the proposed method is that it can reduce the impact of random missing and noise in radar data. Finally, the effectiveness and superiority of the proposed method are fully demonstrated through the experimental results on two public datasets of human pose estimation based on mmWave radar.

Published
2024
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36. MPTFormer: Toward Robust Arm Gesture Pose Tracking Using Dual-View Radar System

Author

Chen, Lin, Guo, Xuemei, and Wang, Guoli

Abstract

Locating human joints using low-cost commercial millimeter-wave (mmWave) radars is an emerging technology. Compared to single-view radar, dual-view radar fusion is more efficient for robust arm gesture pose tracking since it can capture a wider area of human reflection and radial velocity in both directions. One challenging task for dual-view radar fusion is to effectively utilize the reflection points’ spatial and velocity information and focus perceptual cues related to joint position and velocity for accurate joint tracking. In this article, we propose a millimeter-wave pose tracking transformer (MPTFormer), a method for arm gesture pose tracking using both front- and side-view mmWave radars. Specifically, MPTFormer consists of a multidomain fusion transformer (MFFormer) and a joint tracking transformer (JTFormer). In the MFFormer, joint position and velocity estimation tasks are set, and the range–azimuth map (RAM) and range–Doppler map (RDM) of the dual-view radar are set as token embeddings, which interacted with joint position and velocity tokens for learning perceptual cues related to joint position and velocity as well as joint constraint relationships. Meanwhile, the nonlocal dependencies between dual-view radar and its multidomain features are mined to obtain good global feature representation. In the JTFormer, a hybrid learning architecture of the temporal transformer and long short-term memory (LSTM) is designed, which tracks the joint position according to the global and local features of the joint in the temporal dimension. Finally, in the pose-tracking task containing 12 different arm gestures, the proposed method can achieve 25.2 mm mean per joint position error (MPJPE) and 19.1 mm Procrustes analysis-MPJPE (P-MPJPE).

Published
2024
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38. Silencing of tropomodulin 1 inhibits acute myeloid leukemia cell proliferation and tumor growth by elevating karyopherin alpha 2-mediated autophagy.

Author

Xia Y, Wang D, Zhao H, Meng T, Jiang Q, Pan Z, Wang G, An T, Li B, Bi S, Wang H, Lu J, Liu H, Lin H, Lin C, Zheng Q, and Li D

Abstract

Evidence shows that tropomodulin 1 (TMOD1) is a powerful diagnostic marker in the progression of several cancer types. However, the regulatory mechanism of TMOD1 in tumor progression is still unclear. Here, we showed that TMOD1 was highly expressed in acute myeloid leukemia (AML) specimens, and TMOD1-silencing inhibited cell proliferation by inducing autophagy in AML THP-1 and MOLM-13 cells. Mechanistically, the C-terminal region of TMOD1 directly bound to KPNA2, and TMOD1-overexpression promoted KPNA2 ubiquitylation and reduced KPNA2 levels. In contrast, TMOD1-silencing increased KPNA2 levels and facilitated the nuclear transfer of KPNA2, then subsequently induced autophagy and inhibited cell proliferation by increasing the nucleocytoplasmic transport of p53 and AMPK activation. KPNA2/p53 inhibitors attenuated autophagy induced by silencing TMOD1 in AML cells. Silencing TMOD1 also inhibited tumor growth by elevating KPNA2-mediated autophagy in nude mice bearing MOLM-13 xenografts. Collectively, our data demonstrated that TMOD1 could be a novel therapeutic target for AML treatment., Competing Interests: Declaration of Competing Interest The authors declare that they have no conflicts of interest to report regarding the present study., (Copyright © 2024. Published by Elsevier Ltd.)

Published
2024
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39. A chemical proteomics approach for global mapping of functional lysines on cell surface of living cell.

Author

Wang T, Ma S, Ji G, Wang G, Liu Y, Zhang L, Zhang Y, and Lu H

Subjects
Humans, HeLa Cells, Ligands, Endoglin, Lysine metabolism, Proteomics
Abstract

Cell surface proteins are responsible for many crucial physiological roles, and they are also the major category of drug targets as the majority of therapeutics target membrane proteins on the surface of cells to alter cellular signaling. Despite its great significance, ligand discovery against membrane proteins has posed a great challenge mainly due to the special property of their natural habitat. Here, we design a new chemical proteomic probe OPA-S-S-alkyne that can efficiently and selectively target the lysines exposed on the cell surface and develop a chemical proteomics strategy for global analysis of surface functionality (GASF) in living cells. In total, we quantified 2639 cell surface lysines in Hela cell and several hundred residues with high reactivity were discovered, which represents the largest dataset of surface functional lysine sites to date. We discovered and validated that hyper-reactive lysine residues K382 on tyrosine kinase-like orphan receptor 2 (ROR2) and K285 on Endoglin (ENG/CD105) are at the protein interaction interface in co-crystal structures of protein complexes, emphasizing the broad potential functional consequences of cell surface lysines and GASF strategy is highly desirable for discovering new active and ligandable sites that can be functionally interrogated for drug discovery., (© 2024. The Author(s).)

Published
2024
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40. I 2 /CF 3 CO 2 Ag-mediated iodolactonization of various allenoic acids to access versatile 6- to 9-membered ring vinylic iodolactones.

Author

Bao X, Wang G, Dong X, Zhu M, Yang L, Zhu J, Shi Q, Zhang H, and Chen D

Abstract

Medium-sized lactones are important structural units, but their synthesis remains a great challenge. Herein, we report I 2 /CF 3 CO 2 Ag-mediated iodolactonization of allenoic acids to synthesize various 6- to 9-membered ring vinylic iodolactones in 16-89% yield. This protocol not only develops a new cyclization strategy of allenoic acids, but also provides highly functionalized medium-sized lactones containing alkene and halogen groups.

Published
2024
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41. MM-SFENet: multi-scale multi-task localization and classification of bladder cancer in MRI with spatial feature encoder network.

Author

Ren Y, Wang G, Wang P, Liu K, Liu Q, Sun H, Li X, and Wei B

Subjects
Humans, Magnetic Resonance Imaging methods, Urinary Bladder pathology, Urinary Bladder Neoplasms diagnostic imaging
Abstract

Objective . Bladder cancer is a common malignant urinary carcinoma, with muscle-invasive and non-muscle-invasive as its two major subtypes. This paper aims to achieve automated bladder cancer invasiveness localization and classification based on MRI. Approach . Different from previous efforts that segment bladder wall and tumor, we propose a novel end-to-end multi-scale multi-task spatial feature encoder network (MM-SFENet) for locating and classifying bladder cancer, according to the classification criteria of the spatial relationship between the tumor and bladder wall. First, we built a backbone with residual blocks to distinguish bladder wall and tumor; then, a spatial feature encoder is designed to encode the multi-level features of the backbone to learn the criteria. Main Results . We substitute Smooth-L1 Loss with IoU Loss for multi-task learning, to improve the accuracy of the classification task. By learning two datasets collected from bladder cancer patients at the hospital, the mAP, IoU, Acc, Sen and Spec are used as the evaluation metrics. The experimental result could reach 93.34%, 83.16%, 85.65%, 81.51%, 89.23% on test set1 and 80.21%, 75.43%, 79.52%, 71.87%, 77.86% on test set2. Significance . The experimental result demonstrates the effectiveness of the proposed MM-SFENet on the localization and classification of bladder cancer. It may provide an effective supplementary diagnosis method for bladder cancer staging., (© 2024 Institute of Physics and Engineering in Medicine.)

Published
2024
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