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1. Development of Focused X-ray Luminescence Compute Tomography Imaging

Author

Fang, Yile, Zhang, Yibing, and Li, Changqing

Subjects
Electrical Engineering and Systems Science - Image and Video Processing
Abstract

X-ray luminescence is produced when contrast agents absorb energy from X-ray photons and release a portion of that energy by emitting photons in the visible and near-infrared range. X-ray luminescence computed tomography (XLCT) was introduced in the past decade as a hybrid molecular imaging modality combining the merits of both X-ray imaging (high spatial resolution) and optical imaging (high sensitivity to tracer nanophosphors).

Published
2024

2. 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

4. The NeurIPS 2022 Neural MMO Challenge: A Massively Multiagent Competition with Specialization and Trade

Author

Liu, Enhong, Suarez, Joseph, You, Chenhui, Wu, Bo, Chen, Bingcheng, Hu, Jun, Chen, Jiaxin, Zhu, Xiaolong, Zhu, Clare, Togelius, Julian, Mohanty, Sharada, Hong, Weijun, Du, Rui, Zhang, Yibing, Wang, Qinwen, Li, Xinhang, Yuan, Zheng, Li, Xiang, Huang, Yuejia, Zhang, Kun, Yang, Hanhui, Tang, Shiqi, and Isola, Phillip

Subjects
Computer Science - Artificial Intelligence, Computer Science - Machine Learning, Computer Science - Multiagent Systems
Abstract

In this paper, we present the results of the NeurIPS-2022 Neural MMO Challenge, which attracted 500 participants and received over 1,600 submissions. Like the previous IJCAI-2022 Neural MMO Challenge, it involved agents from 16 populations surviving in procedurally generated worlds by collecting resources and defeating opponents. This year's competition runs on the latest v1.6 Neural MMO, which introduces new equipment, combat, trading, and a better scoring system. These elements combine to pose additional robustness and generalization challenges not present in previous competitions. This paper summarizes the design and results of the challenge, explores the potential of this environment as a benchmark for learning methods, and presents some practical reinforcement learning training approaches for complex tasks with sparse rewards. Additionally, we have open-sourced our baselines, including environment wrappers, benchmarks, and visualization tools for future research.

Published
2023

7. Benchmarking Robustness and Generalization in Multi-Agent Systems: A Case Study on Neural MMO

Author

Chen, Yangkun, Suarez, Joseph, Zhang, Junjie, Yu, Chenghui, Wu, Bo, Chen, Hanmo, Zhu, Hengman, Du, Rui, Qian, Shanliang, Liu, Shuai, Hong, Weijun, He, Jinke, Zhang, Yibing, Zhao, Liang, Zhu, Clare, Togelius, Julian, Mohanty, Sharada, Chen, Jiaxin, Li, Xiu, Zhu, Xiaolong, and Isola, Phillip

Subjects
Computer Science - Artificial Intelligence
Abstract

We present the results of the second Neural MMO challenge, hosted at IJCAI 2022, which received 1600+ submissions. This competition targets robustness and generalization in multi-agent systems: participants train teams of agents to complete a multi-task objective against opponents not seen during training. The competition combines relatively complex environment design with large numbers of agents in the environment. The top submissions demonstrate strong success on this task using mostly standard reinforcement learning (RL) methods combined with domain-specific engineering. We summarize the competition design and results and suggest that, as an academic community, competitions may be a powerful approach to solving hard problems and establishing a solid benchmark for algorithms. We will open-source our benchmark including the environment wrapper, baselines, a visualization tool, and selected policies for further research.

Published
2023

8. C-JUN overexpressing CAR-T cells in acute myeloid leukemia: preclinical characterization and phase I trial

Author

Zuo, Shiyu, Li, Chuo, Sun, Xiaolei, Deng, Biping, Zhang, Yibing, Han, Yajing, Ling, Zhuojun, Xu, Jinlong, Duan, Jiajia, Wang, Zelin, Yu, Xinjian, Zheng, Qinlong, Xu, Xiuwen, Zong, Jiao, Tian, Zhenglong, Shan, Lingling, Tang, Kaiting, Huang, Huifang, Song, Yanzhi, Niu, Qing, Zhou, Dongming, Feng, Sizhou, Han, Zhongchao, Wang, Guoling, Wu, Tong, Pan, Jing, and Feng, Xiaoming

Published
2024
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9. Essential role of liquid phase on melt-processed GdBCO single-grain superconductors

Author

Liu, Xiongfang, Wang, Xuechun, He, Jinyu, Fu, Yixue, Yin, Xinmao, Cai, Chuanbing, Zhang, Yibing, and Zhou, Difan

Subjects
Condensed Matter - Superconductivity, Condensed Matter - Materials Science, Physics - Applied Physics
Abstract

RE-Ba-Cu-O (RE denotes rare earth elements) single-grain superconductors have garnered considerable attention owning to their ability to trap strong magnetic field and self-stability for maglev. Here, we employed a modified melt-growth method by adding liquid source (LS) to provide a liquid rich environment during crystal growth. It further enables a significantly low maximum processing temperature (Tmax) even approaching peritectic decomposition temperature. This method was referred as the liquid source rich low Tmax (LS+LTmax) growth method which combines the advantage of Top Seeded Infiltration Growth (TSIG) into Top Seeded Melt-texture Growth (TSMG). The LS+LTmax method synergistically regulates the perfect appearance and high superconducting performance in REBCO single grains. The complementary role of liquid source and low Tmax on the crystallization has been carefully investigated. Microstructure analysis demonstrates that the LS+LTmax processed GdBCO single grains show clear advantages of uniform distribution of RE3+ ions as well as RE211 particles. The inhibition of Gd211 coarsening leads to improved pining properties. GdBCO single-grain superconductors with diameter of 18 mm and 25 mm show maximum trapped magnetic field of 0.746 T and 1.140 T at 77 K. These trapped fields are significantly higher than those of conventional TSMG samples. Particularly, at grain boundaries with reduced RE211 density superior flux pinning performance has been observed. It indicates the existence of multiple pinning mechanisms at these areas. The presented strategy provides essential LS+LTmax technology for processing high performance single-grain superconductors with improved reliability which is considered important for engineering applications.

Published
2023

10. Measurement of neutrino oscillations using neutrino and antineutrino beams in the NOvA experiment

Author

Zhang, Yibing

Subjects
QC0793 Elementary particle physics
Abstract

NOvA is a long-baseline accelerator neutrino oscillation experiment using the NuMI neutrino beam from Fermilab. Its main physics goals are to probe the 3-flavour oscillation parameters: neutrino mass hierarchy, CP-violating phase δ_cp and octant of θ₂₃ mixing angle by observing electron neutrino appearance and muon neutrino disappearance. Two functionally identical detectors are placed off-axis from the centre of the NuMI beam. The near detector at Fermilab is 100 m underground, and the far detector is located on the surface at Ash River, 810 km away from the beam source. The initial neutrino beam spectra are measured using the near detector data and the oscillation parameters are extracted by fitting the observed data to the predicted neutrino spectrum in the far detector. This thesis is centered around how to improve the sensitivity of |Δm²₃₂| and θ₂₃ measurements in the muon neutrino disappearance analysis. NOvA will take data for about 12 years. The operation of the NOvA experiment for each year costs tens of millions of dollars, thus it is valuable to maximise the sensitivity of the analysis. Three samples of muon neutrino events are studied in this thesis to improve the analysis sensitivities. First, higher energy muon neutrinos are investigated by extending the energy range in NOvA's current standard analysis. Second, for the sample of events used in NOvA's existing analysis, a new energy estimator which has been developed to improve the neutrino energy resolution is considered. Furthermore, in addition to binning the events as function of energy and hadronic energy fraction, three particle identifiers are introduced to separate neutrino events by signal purity to reduce the effects from backgrounds. Third, an additional lower purity sample of muon neutrino charged current (CC) events that look similar to neutral current events and have not been included in NOvA's existing analyses have been studied. This thesis reanalyses NOvA's data used in the 2020 analysis, corresponding to an exposure of 13.60×10²⁰ protons on target (POT) in the neutrino beam mode recorded from February 6, 2014 to March 20, 2020, and 12.50×10²⁰ protons on target in the antineutrino beam mode recorded between June 29, 2016 to February 26, 2019. This thesis has implemented a fit to Asimov fake data, generated where sin²θ₂₃ = 0.59 and Δm²₃₂ = 2.5 × 10⁻³ eV². These sensitivity studies show that the uncertainty range of |Δm²₃₂| at 1 σ in the new analysis is reduced by 5.5% and the significance of maximal disappearance rejection improves by 7.7%, compared to the standard analysis. This is equivalent to adding 11-16% more data. This thesis also implements the fit from combining electron neutrino appearance and muon neutrino disappearance. The combined analysis shows that the best fit values are very close to the standard analysis. However, the uncertainty range of Δm²₃₂ at 1 σ is reduced by 3.7% using the new analysis. The maximal disappearance significance is not improved in the new analysis, but the new analysis slightly improves the rejection of the disfavoured octant.

Published
2023

23. Combinatorial immunotherapies overcome MYC-driven immune evasion in triple negative breast cancer

Author

Lee, Joyce V, Housley, Filomena, Yau, Christina, Nakagawa, Rachel, Winkler, Juliane, Anttila, Johanna M, Munne, Pauliina M, Savelius, Mariel, Houlahan, Kathleen E, Van de Mark, Daniel, Hemmati, Golzar, Hernandez, Grace A, Zhang, Yibing, Samson, Susan, Baas, Carole, Kok, Marleen, Esserman, Laura J, van ‘t Veer, Laura J, Rugo, Hope S, Curtis, Christina, Klefström, Juha, Matloubian, Mehrdad, and Goga, Andrei

Subjects
Biomedical and Clinical Sciences, Oncology and Carcinogenesis, Immunology, Vaccine Related, Cancer, Breast Cancer, Immunization, Animals, B7-H1 Antigen, Humans, Immune Checkpoint Inhibitors, Immune Evasion, Immunotherapy, Mice, Proto-Oncogene Proteins c-myc, Signal Transduction, Triple Negative Breast Neoplasms
Abstract

Few patients with triple negative breast cancer (TNBC) benefit from immune checkpoint inhibitors with complete and durable remissions being quite rare. Oncogenes can regulate tumor immune infiltration, however whether oncogenes dictate diminished response to immunotherapy and whether these effects are reversible remains poorly understood. Here, we report that TNBCs with elevated MYC expression are resistant to immune checkpoint inhibitor therapy. Using mouse models and patient data, we show that MYC signaling is associated with low tumor cell PD-L1, low overall immune cell infiltration, and low tumor cell MHC-I expression. Restoring interferon signaling in the tumor increases MHC-I expression. By combining a TLR9 agonist and an agonistic antibody against OX40 with anti-PD-L1, mice experience tumor regression and are protected from new TNBC tumor outgrowth. Our findings demonstrate that MYC-dependent immune evasion is reversible and druggable, and when strategically targeted, may improve outcomes for patients treated with immune checkpoint inhibitors.

Published
2022

24. Autologous CD7 CAR-T cells generated without T cell pre-selection in pediatric patients with relapsed/refractory T-ALL: A phase I trial

Author

Zhao, Liping, Li, Chuo, Zuo, Shiyu, Han, Yajing, Deng, Biping, Ling, Zhuojun, Zhang, Yanlei, Peng, Shuixiu, Xu, Jinlong, Duan, Jiajia, Wang, Zelin, Yu, Xinjian, Zheng, Qinlong, Xu, Xiuwen, Yuan, Ying, Tian, Zhenglong, Tang, Kaiting, Zhang, Yibing, Niu, Qing, Zhang, Jiecheng, Chang, Alex H., Luo, Yuechen, Feng, Xiaoming, and Pan, Jing

Published
2024
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25. Sequential CD19 and CD22 chimeric antigen receptor T-cell therapy for childhood refractory or relapsed B-cell acute lymphocytic leukaemia: a single-arm, phase 2 study

Author

Pan, Jing, Tang, Kaiting, Luo, Yuechen, Seery, Samuel, Tan, Yue, Deng, Biping, Liu, Feng, Xu, Xiuwen, Ling, Zhuojun, Song, Weiliang, Xu, Jinlong, Duan, Jiajia, Wang, Zelin, Li, Chunyu, Wang, Kai, Zhang, Yibing, Yu, Xinjian, Zheng, Qinlong, Zhao, Liping, Zhang, Jiecheng, Chang, Alex H, and Feng, Xiaoming

Published
2023
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30. Invisible neutrino decays at the MOMENT experiment

Author

Tang, Jian, Wang, TseChun, and Zhang, Yibing

Subjects
High Energy Physics - Phenomenology
Abstract

We investigate invisible decays of the third neutrino mass eigenstate in future accelerator neutrino experiments using muon-decay beams such as MuOn-decay MEdium baseline NeuTrino beam experiment (MOMENT). MOMENT has an outstanding performance to measure the deficit or excess in the spectra caused by neutrino decays, especially in $\nu_\mu$ and $\bar{\nu}_\mu$ disappearance channels. Such an experiment will improve the constraints of the neutrino lifetime $\tau_3$. Compared with exclusion limits in the current accelerator neutrino experiments T2K and NOvA under the stable $\nu$ assumption, we expect that MOMENT gives the bound of $\tau_3/m_3\ge1.46\times10^{-11}$~s/eV at $3\sigma$ confidence level, which is better than their recent limits: $\tau_3/m_3\ge 7\times10^{-13}$~s/eV in NOvA and $\tau_3/m_3\ge 1.41\times10^{-12}$~s/eV in T2K. The non-decay scenario is expected to be excluded by MOMENT at the $>3\sigma$ confidence level, if the best fit results in T2K and NOvA are confirmed. We further find that reducing systematic uncertainties is slightly more important than the running time. Finally, we find very little correlations between $\tau_3/m_3$ and other oscillation parameters, which point to an advantage of MOMENT to measure $\tau_3/m_3$., Comment: update plots and texts

Published
2018
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38. Dietary DHA amplifies LXA4 circuits in tissues and lymph node PMN and is protective in immune-driven dry eye disease

Author

Gao, Yuan, Su, John, Zhang, Yibing, Chan, Allison, Sin, Jun Hyung, Wu, Di, Min, Kyungi, and Gronert, Karsten

Subjects
Eye Disease and Disorders of Vision, Nutrition, Aetiology, 2.1 Biological and endogenous factors, Inflammatory and immune system, Animals, Cells, Cultured, Diet, Docosahexaenoic Acids, Dry Eye Syndromes, Eye, Female, Humans, Lipoxins, Lymph Nodes, Male, Mice, Mice, Inbred C57BL, Neutrophils, T-Lymphocytes, Regulatory, Biological Sciences, Medical and Health Sciences, Immunology
Abstract

Recently identified regulatory PMN control immune-driven dry eye disease (DED) in females by producing the arachidonic acid (ω-6)-derived specialized pro-resolving mediator (SPM), LXA4, in lymph nodes. Dietary ω-3 docosahexaenoic acid (DHA) is protective in DED but mechanisms of action remain elusive. DHA is converted to ω-3 SPMs by PMN via the same lipoxygenases (LOX) that generate LXA4. We investigated if dietary DHA amplifies SPM formation and affects T effector cell function and/or regulatory PMN in DED. DED was induced in mice on a DHA-enriched or ω-3-deficient diet. DHA deficiency amplified DED with marked sex-specific differences. Dietary DHA protection against dry eye disease correlated with increased PMN levels in lymph nodes, ocular tissues, and unexpectedly, selective amplification of LXA4 tissue levels. Dietary DHA increased 12/15-LOX and decreased 5-LOX expression in lymph nodes and isolated lymph node PMN, which correlated with amplified LXA4 formation. Acute DHA treatment rescued DHA-deficient females from exaggerated DED by amplifying lymph node LXA4 formation, increasing Treg and decreasing TH1 and TH17 effector cells. Our results identify DHA regulation of LXA4 producing PMN in ocular tissues and lymph nodes in health and immune disease as novel mechanism and determinant for T-cell responses to routine ocular injury or stress signals.

Published
2018

40. Author Correction: Combinatorial immunotherapies overcome MYC-driven immune evasion in triple negative breast cancer

Author

Lee, Joyce V., Housley, Filomena, Yau, Christina, Nakagawa, Rachel, Winkler, Juliane, Anttila, Johanna M., Munne, Pauliina M., Savelius, Mariel, Houlahan, Kathleen E., Van de Mark, Daniel, Hemmati, Golzar, Hernandez, Grace A., Zhang, Yibing, Samson, Susan, Baas, Carole, Kok, Marleen, Esserman, Laura J., van ‘t Veer, Laura J., Rugo, Hope S., Curtis, Christina, Klefström, Juha, Matloubian, Mehrdad, and Goga, Andrei

Published
2022
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42. Probing Direct and Indirect Unitarity Violation in Future Accelerator Neutrino Facilities

Author

Tang, Jian, Zhang, Yibing, and Li, Yu-Feng

Subjects
High Energy Physics - Phenomenology
Abstract

The possible existence of light and heavy sterile neutrinos may give rise to direct and indirect unitarity violation of the $3\times3$ lepton mixing matrix respectively. In the current work we study the potential of future accelerator neutrino facilities in probing the unitarity violation effects. Taking DUNE, T2HK and a low-energy Neutrino Factory (LENF) as working examples of future accelerator neutrino facilities, we study the distinct effects of direct and indirect unitarity violation on the discovery reach of the leptonic CP violation and precision measurements of $\theta_{23}$ in the three neutrino framework. In addition, constraints on the additional mixing parameters of direct and indirect unitarity violation are also discussed. Finally, we stress that the combination of experiments with different oscillation channels, different neutrino beams and different detector techniques will be an effective solution to the parameter degeneracy problem and give the robust measurement of leptonic CP violation even if the direct and indirect unitarity violation are taken into account., Comment: 19 pages, 6 figures

Published
2017
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43. Study of Non-Standard Charged-Current Interactions at the MOMENT experiment

Author

Tang, Jian and Zhang, Yibing

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

MuOn-decay MEdium baseline NeuTrino beam experiment (MOMENT) is a next-generation accelerator neutrino experiment looking for more physics study. We try to simulate neutrino oscillations confronting with Charged-Current\&Non-Standard neutrino Interactions(CC-NSIs) at MOMENT. These NSIs could alter neutrino production and detection processes and get involved in neutrino oscillation channels. We separate a perturbative discussion of oscillation channels at near and far detectors, and analyze parameter correlations with the impact of CC-NSIs. Taking $\delta_{cp}$ and $\theta_{23}$ as an example, we find that CC-NSIs can induce bias in precision measurements of standard oscillation parameters. In addition, a combination of near and far detectors using Gd-doped water cherenkov technology at MOMENT is able to provide good constraints of CC-NSIs happening at the neutrino production and detection processes., Comment: 14 pages, 5 figures. Matches the published version

Published
2017
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44. Light Recurrent Unit: Towards an Interpretable Recurrent Neural Network for Modeling Long-Range Dependency.

Author

Ye, Hong, Zhang, Yibing, Liu, Huizhou, Li, Xuannong, Chang, Jiaming, and Zheng, Hui

Subjects
NATURAL language processing, COMPUTER vision, PROGRAMMING languages
Abstract

Recurrent neural networks (RNNs) play a pivotal role in natural language processing and computer vision. Long short-term memory (LSTM), as one of the most representative RNNs, is built upon relatively complex architecture with an excessive number of parameters, which results in large storage, high training cost, and lousy interpretability. In this paper, we propose a lightweight network called Light Recurrent Unit (LRU). On the one hand, we designed an accessible gate structure, which has high interpretability and addresses the issue of gradient disappearance. On the other hand, we introduce the Stack Recurrent Cell (SRC) structure to modify the activation function, which not only expedites convergence rates but also enhances the interpretability of the network. Experimental results show that our proposed LRU has the advantages of fewer parameters, strong interpretability, and effective modeling ability for variable length sequences on several datasets. Consequently, LRU could be a promising alternative to traditional RNN models in real-time applications with space or time constraints, potentially reducing storage and training costs while maintaining high performance. [ABSTRACT FROM AUTHOR]

Published
2024
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