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| 1 | Global transcriptome analysis for identification of interactions between coding and noncoding RNAs during human erythroid differentiation显示文摘在 erythroid 开发期间编码基因, miRNAs,和 lncRNAs 上的研究在最近的年里被执行了。然而,集中于三种 RNA 类型的集成的分析还得被做。在现在的学习,我们比较了编码基因, miRNA,和 lncRNA 表示侧面的动力学。为了在在 transcriptome 控制这些变化的红血球生成和潜在的机制探索动态变化,铺平,我们利用了定序技术从绳索血获得 transcriptome 数据的高产量造血的干细胞和下列四个 erythroid 区别阶段,以及从成熟的红血房间。结果显示 lncRNAs 为 erythroid 区别正在答应房间标记候选人。聚类分析分类差别表示基因进在 stemness 维护期间对应于动态变化的四种子类型,中间区别,并且成熟。综合分析揭示了 RNA 潜在地参予了控制血细胞成熟的那 noncoding,并且特别与到氧种类和 DNA 损坏的 heme 新陈代谢和回答联系了。这些规章的相互作用在一个全面网络,在 RNA 之间的从而推断的关联和他们的联系功能被显示。这些数据为正常红血球生成的学习提供了一个大量的资源,它将允许 erythroid 开发的进一步的调查和理解并且获得 erythroid 混乱。 | Nan Ding Jiafei Xi Yanming Li Xiaoyan Xie Jian Shi Zhaojun Zhang Yanhua Li Fang Fang Sihan Wang Wen Yue Xuetao Pei Xiangdong Fang | 2016 | Frontiers of Medicine2016，10，3： | 6 |
| 2 | One-step In-situ Synthesis of Vacancy-rich CoFe2O4@Defective Graphene Hybrids as Bifunctional Oxygen Electrocatalysts for Rechargeable Zn-Air Batteries显示文摘Developing efficient catalysts toward both oxygen reduction reaction(ORR)and oxygen evolution reaction(OER)is the core task for rechargeable metal-air batteries.Although integration of two active components should be an effective method to produce the bifunctional catalysts in principle,traditional techniques still can not attain fine tunable surface structure during material-hybridization process.Herein,we present a facile short-time in-situ argon(Ar)plasma strategy to fabricate a high-performance bifunctional hybrid catalyst of vacancy-rich CoFe2O4 synergized with defective graphence(r-CoFe2O4@DG).Reflected by the low voltage gap of 0.79V in two half-reaction measurements,the striking capability to catalyze ORR/OER endows it excellent and durable performance in rechargeable Zn-air batteries,with a maximum power density of 155.2mW/cm^2 and robust stablility(up to 60h).Further experimental and theoretical studies validate its remarkable bifunctional energetics root from plasma-induced surface vacancy defects and interfacial charge polarization between DG and CoFe2O4. | WANG X in ZHUANG Linzhou JIA Yi ZHANG Lijie YANG Qin XU Wenjia YANG Dongjiang YAN Xuecheng ZHANG Longzhou ZHU Zhonghua BROWN Christopher L YUAN Pei YAO Xiangdong | 2020 | Chemical Research in Chinese Universities2020，36，3： | 1 |
| 3 | Manganese-Based Lithium-Ion Battery: Mn_(3)O_(4) Anode Versus LiNi_(0.5)Mn_(1.5)O_(4) Cathode显示文摘Lithium-ion batteries(LIBs)are widely used in portable consumer electronics,clean energy storage,and electric vehicle applications.However,challenges exist for LIBs,including high costs,safety issues,limited Li resources,and manufacturingrelated pollution.In this paper,a novel manganese-based lithium-ion battery with a LiNi_(0.5)Mn_(1.5)O_(4) ‖ Mn_(3)O_(4) structure is reported that is mainly composed of environmental friendly manganese compounds,where Mn_(3)O_(4) and LiNi_(0.5)Mn_(1.5)O_(4) (LNMO)are adopted as the anode and cathode materials,respectively.The proposed structure improves battery safety and reduce costs compared with current battery technology,provides comparable energy density with that of traditional graphite-based batteries.First,the characteristics and the electrochemical performances of the Mn_(3)O_(4) anode and the LNMO cathode are investigated separately against Li metal in half cell configurations,with promising performances being demonstrated by both electrodes.Then,a full cell structure with Mn_(3)O_(4) against LNMO is constructed that provides an average discharge voltage of 3.5 V and an initial specific capacity of 86.2 mA;h;g−1.More importantly,the electrochemical performance of the LNMO‖ Mn_(3)O_(4) full cell and its possible decay mechanisms are discussed systemically;and efficient strategies are proposed to further improve both the electrochemical performance of Mn_(3)O_(4) and the stability of LNMO. | Wenfeng Mao Wei Yue Feng Pei Xiaochen Zhao Xiangdong Huang Guo Ai | 2020 | Automotive Innovation2020，3，2： | 1 |
| 4 | End-to-End Self-Driving Using Deep Neural Networks with Multi-auxiliary Tasks显示文摘End-to-end self-driving is a method that directly maps raw visual images to vehicle control signals using deep convolutional neural network(CNN).Although prediction of steering angle has achieved good result in single task,the current approach does not effectively simultaneously predict the steering angle and the speed.In this paper,various end-to-end multi-task deep learning networks using deep convolutional neural network combined with long short-term memory recurrent neural network(CNN-LSTM)are designed and compared,which could obtain not only the visual spatial information but also the dynamic temporal information in the driving scenarios,and improve steering angle and speed predictions.Furthermore,two auxiliary tasks based on semantic segmentation and object detection are proposed to improve the understanding of driving scenarios.Experiments are conducted on the public Udacity dataset and a newly collected Guangzhou Automotive Cooperate dataset.The results show that the proposed network architecture could predict steering angles and vehicle speed accurately.In addi-tion,the impact of multi-auxiliary tasks on the network performance is analyzed by visualization method,which shows the salient map of network.Finally,the proposed network architecture has been well verified on the autonomous driving simu-lation platform Grand Theft Auto V(GTAV)and experimental road with an average takeover rate of two times per 10 km. | Dan Wang Junjie Wen Yuyong Wang Xiangdong Huang Feng Pei | 2019 | Automotive Innovation2019，2，2： | 1 |
| 5 | Phenotypic Characterization of Porcine IFNc-Producing Lymphocytes in Porcine Reproductive and Respiratory Syndrome Virus Vaccinated and Challenged Pigs显示文摘Porcine reproductive and respiratory syndrome(PRRS) continues to be one of the most important swine diseases worldwide. Interferon-γ(IFNγ)-mediated type Ⅰ cell-mediated immune response plays an important role in protection from,and clearance of, PRRS virus(PRRSV). Several lymphocyte subsets including T-helper, CTLs, Th/memory cells, and cd T lymphocytes were previously reported to produce IFNc during PRRSV infection. However, the proportion and phenotypic characterization of these IFNγ-secreting lymphocytes have not been explored. In this study, IFNc producted by different lymphocyte subsets was assessed by multi-color flow cytometry after vaccination with PRRSV modified live vaccine(PRRSV-MLV) and challenge with homogeneous or heterogeneous PRRSV. The results showed that T-helper cells were the major IFNγ-secreting cell population after PRRSV-MLV vaccination and PRRSV challenge. Additionally, the proportion of IFNγ producing Th/memory cells and γδ T cells increased after PRRSV challenge. This difference was accounted for an enhanced ability to produce IFNγ in Th/memory cells and an enlarged quantity of γδ T cells. The results presented here could contribute to our understanding of the roles of IFNγ in protective immunity against PRRSV infection and may be useful for assessment of cell-mediated immunity in vaccine tests. | Xiangdong Li Zengyang Pei Yilin Bai Lihua Wang Jishu Shi Kegong Tian | 2018 | Virologica Sinica2018，33，6： | 0 |
| 6 | Feasibility and physics potential of detecting ^(8)B solar neutrinos at JUNO显示文摘The Jiangmen Underground Neutrino Observatory(JUNO)features a 20 kt multi-purpose underground liquid scintillator sphere as its main detector.Some of JUNO's features make it an excellent location for^8B solar neutrino measurements,such as its low-energy threshold,high energy resolution compared with water Cherenkov detectors,and much larger target mass compared with previous liquid scintillator detectors.In this paper,we present a comprehensive assessment of JUNO's potential for detecting^8B solar neutrinos via the neutrino-electron elastic scattering process.A reduced 2 MeV threshold for the recoil electron energy is found to be achievable,assuming that the intrinsic radioactive background^(238)U and^(232)Th in the liquid scintillator can be controlled to 10^(-17)g/g.With ten years of data acquisition,approximately 60,000 signal and 30,000 background events are expected.This large sample will enable an examination of the distortion of the recoil electron spectrum that is dominated by the neutrino flavor transformation in the dense solar matter,which will shed new light on the inconsistency between the measured electron spectra and the predictions of the standard three-flavor neutrino oscillation framework.IfDelta m^(2)_(21)=4.8times10^(-5);(7.5times10^(-5))eV^(2),JUNO can provide evidence of neutrino oscillation in the Earth at approximately the 3sigma(2sigma)level by measuring the non-zero signal rate variation with respect to the solar zenith angle.Moreover,JUNO can simultaneously measureDelta m^2_(21)using^8B solar neutrinos to a precision of 20% or better,depending on the central value,and to sub-percent precision using reactor antineutrinos.A comparison of these two measurements from the same detector will help understand the current mild inconsistency between the value of Delta m^2_(21)reported by solar neutrino experiments and the KamLAND experiment. | Angel Abusleme Thomas Adam Shakeel Ahmad Sebastiano Aiello Muhammad Akram Nawab Ali Fengpeng An Guangpeng An Qi An Giuseppe Andronico Nikolay Anfimov Vito Antonelli Tatiana Antoshkina Burin Asavapibhop João Pedro Athayde Marcondes de André Didier Auguste Andrej Babic Wander Baldini Andrea Barresi Eric Baussan Marco Bellato Antonio Bergnoli Enrico Bernieri David Biare Thilo Birkenfeld Sylvie Blin David Blum Simon Blyth Anastasia Bolshakova Mathieu Bongrand Clément Bordereau Dominique Breton Augusto Brigatti Riccardo Brugnera Riccardo Bruno Antonio Budano Max Buesken Mario Buscemi Jose Busto Ilya Butorov Anatael Cabrera Hao Cai Xiao Cai Yanke Cai Zhiyan Cai Antonio Cammi Agustin Campeny Chuanya Cao Guofu Cao Jun Cao Rossella Caruso Cédric Cerna Jinfan Chang Yun Chang Pingping Chen Po-An Chen Shaomin Chen Shenjian Chen Xurong Chen Yi-Wen Chen Yixue Chen Yu Chen Zhang Chen Jie Cheng Yaping Cheng Alexander Chepurnov Davide Chiesa Pietro Chimenti Artem Chukanov Anna Chuvashova Gérard Claverie Catia Clementi Barbara Clerbaux Selma Conforti Di Lorenzo Daniele Corti Salvatore Costa Flavio Dal Corso Christophe De La Taille Jiawei Deng Zhi Deng Ziyan Deng Wilfried Depnering Marco Diaz Xuefeng Ding Yayun Ding Bayu Dirgantara Sergey Dmitrievsky Tadeas Dohnal Georgy Donchenko Jianmeng Dong Damien Dornic Evgeny Doroshkevich Marcos Dracos Frédéric Druillole Shuxian Du Stefano Dusini Martin Dvorak Timo Enqvist Heike Enzmann Andrea Fabbri Lukas Fajt Donghua Fan Lei Fan Can Fang Jian Fang Marco Fargetta Anna Fatkina Dmitry Fedoseev Vladko Fekete Li-Cheng Feng Qichun Feng Richard Ford Andrey Formozov Amélie Fournier Haonan Gan Feng Gao Alberto Garfagnini Alexandre Göttel Christoph Genster Marco Giammarchi Agnese Giaz Nunzio Giudice Franco Giuliani Maxim Gonchar Guanghua Gong Hui Gong Oleg Gorchakov Yuri Gornushkin Marco Grassi Christian Grewing Maxim Gromov Vasily Gromov Minghao Gu Xiaofei Gu Yu Gu Mengyun Guan Nunzio Guardone Maria Gul Cong Guo Jingyuan Guo Wanlei Guo Xinheng Guo Yuhang Guo Paul Hackspacher Caren Hagner Ran Han Yang Han Miao He Wei He Tobias Heinz Patrick Hellmuth Yuekun Heng Rafael Herrera Daojin Hong YuenKeung Hor Shaojing Hou Yee Hsiung Bei-Zhen Hu Hang Hu Jianrun Hu Jun Hu Shouyang Hu Tao Hu Zhuojun Hu Chunhao Huang Guihong Huang Hanxiong Huang Qinhua Huang Wenhao Huang Xingtao Huang Yongbo Huang Jiaqi Hui Wenju Huo Cédric Huss Safeer Hussain Antonio Insolia Ara Ioannisian Daniel Ioannisyan Roberto Isocrate Kuo-Lun Jen Xiaolu Ji Xingzhao Ji Huihui Jia Junji Jia Siyu Jian Di Jiang Xiaoshan Jiang Ruyi Jin Xiaoping Jing Cécile Jollet Jari Joutsenvaara Sirichok Jungthawan Leonidas Kalousis Philipp Kampmann Li Kang Michael Karagounis Narine Kazarian Amir Khan Waseem Khan Khanchai Khosonthongkee Patrick Kinz Denis Korablev Konstantin Kouzakov Alexey Krasnoperov Svetlana Krokhaleva Zinovy Krumshteyn Andre Kruth Nikolay Kutovskiy Pasi Kuusiniemi Tobias Lachenmaier Cecilia Landini Sébastien Leblanc Frederic Lefevre Liping Lei Ruiting Lei Rupert Leitner Jason Leung Demin Li Fei Li Fule Li Haitao Li Huiling Li Jiaqi Li Jin Li Kaijie Li Mengzhao Li Nan Li Nan Li Qingjiang Li Ruhui Li Shanfeng Li Shuaijie Li Tao Li Weidong Li Weiguo Li Xiaomei Li Xiaonan Li Xinglong Li Yi Li Yufeng Li Zhibing Li Ziyuan Li Hao Liang Hao Liang Jingjing Liang Jiajun Liao Daniel Liebau Ayut Limphirat Sukit Limpijumnong Guey-Lin Lin Shengxin Lin Tao Lin Jiajie Ling Ivano Lippi Fang Liu Haidong Liu Hongbang Liu Hongjuan Liu Hongtao Liu Hu Liu Hui Liu Jianglai Liu Jinchang Liu Min Liu Qian Liu Qin Liu Runxuan Liu Shuangyu Liu Shubin Liu Shulin Liu Xiaowei Liu Yan Liu Alexey Lokhov Paolo Lombardi Claudio Lombardo Kai Loo Chuan Lu Haoqi Lu Jingbin Lu Junguang Lu Shuxiang Lu Xiaoxu Lu Bayarto Lubsandorzhiev Sultim Lubsandorzhiev Livia Ludhova Fengjiao Luo Guang Luo Pengwei Luo Shu Luo Wuming Luo Vladimir Lyashuk Qiumei Ma Si Ma Xiaoyan Ma Xubo Ma Jihane Maalmi Yury Malyshkin Fabio Mantovani Francesco Manzali Xin Mao Yajun Mao Stefano MMari Filippo Marini Sadia Marium Cristina Martellini Gisele Martin-Chassard Agnese Martini Davit Mayilyan Axel Müller Ints Mednieks Yue Meng Anselmo Meregaglia Emanuela Meroni David Meyhöfer Mauro Mezzetto Jonathan Miller Lino Miramonti Salvatore Monforte Paolo Montini Michele Montuschi Nikolay Morozov Pavithra Muralidharan Massimiliano Nastasi Dmitry VNaumov Elena Naumova Igor Nemchenok Alexey Nikolaev Feipeng Ning Zhe Ning Hiroshi Nunokawa Lothar Oberauer Juan Pedro Ochoa-Ricoux Alexander Olshevskiy Domizia Orestano Fausto Ortica Hsiao-Ru Pan Alessandro Paoloni Nina Parkalian Sergio Parmeggiano Teerapat Payupol Yatian Pei Nicomede Pelliccia Anguo Peng Haiping Peng Frédéric Perrot Pierre-Alexandre Petitjean Fabrizio Petrucci Luis Felipe Piñeres Rico Oliver Pilarczyk Artyom Popov Pascal Poussot Wathan Pratumwan Ezio Previtali Fazhi Qi Ming Qi Sen Qian Xiaohui Qian Hao Qiao Zhonghua Qin Shoukang Qiu Muhammad Rajput Gioacchino Ranucci Neill Raper Alessandra Re Henning Rebber Abdel Rebii Bin Ren Jie Ren Taras Rezinko Barbara Ricci Markus Robens Mathieu Roche Narongkiat Rodphai Aldo Romani Bedřich Roskovec Christian Roth Xiangdong Ruan Xichao Ruan Saroj Rujirawat Arseniy Rybnikov Andrey Sadovsky Paolo Saggese Giuseppe Salamanna Simone Sanfilippo Anut Sangka Nuanwan Sanguansak Utane Sawangwit Julia Sawatzki Fatma Sawy Michaela Schever Jacky Schuler Cédric Schwab Konstantin Schweizer Dmitry Selivanov Alexandr Selyunin Andrea Serafini Giulio Settanta Mariangela Settimo Muhammad Shahzad Vladislav Sharov Gang Shi Jingyan Shi Yongjiu Shi Vitaly Shutov Andrey Sidorenkov FedorŠimkovic Chiara Sirignano Jaruchit Siripak Monica Sisti Maciej Slupecki Mikhail Smirnov Oleg Smirnov Thiago Sogo-Bezerra Julanan Songwadhana Boonrucksar Soonthornthum Albert Sotnikov Ondrej Sramek Warintorn Sreethawong Achim Stahl Luca Stanco Konstantin Stankevich DušanŠtefánik Hans Steiger Jochen Steinmann Tobias Sterr Matthias Raphael Stock Virginia Strati Alexander Studenikin Gongxing Sun Shifeng Sun Xilei Sun Yongjie Sun Yongzhao Sun Narumon Suwonjandee Michal Szelezniak Jian Tang Qiang Tang Quan Tang Xiao Tang Alexander Tietzsch Igor Tkachev Tomas Tmej Konstantin Treskov Andrea Triossi Giancarlo Troni Wladyslaw Trzaska Cristina Tuve Stefan van Waasen Johannes van den Boom Guillaume Vanroyen Nikolaos Vassilopoulos Vadim Vedin Giuseppe Verde Maxim Vialkov Benoit Viaud Cristina Volpe Vit Vorobel Lucia Votano Pablo Walker Caishen Wang Chung-Hsiang Wang En Wang Guoli Wang Jian Wang Jun Wang Kunyu Wang Lu Wang Meifen Wang Meng Wang Ruiguang Wang Siguang Wang Wei Wang Wenshuai Wang Xi Wang Xiangyue Wang Yangfu Wang Yaoguang Wang Yi Wang Yifang Wang Yuanqing Wang Yuman Wang Zhe Wang Zheng Wang Zhimin Wang Zongyi Wang Apimook Watcharangkool Lianghong Wei Wei Wei Yadong Wei Liangjian Wen Christopher Wiebusch Steven Chan-Fai Wong Bjoern Wonsak Diru Wu Fangliang Wu Qun Wu Wenjie Wu Zhi Wu Michael Wurm Jacques Wurtz Christian Wysotzki Yufei Xi Dongmei Xia Yuguang Xie Zhangquan Xie Zhizhong Xing Benda Xu Donglian Xu Fanrong Xu Jilei Xu Jing Xu Meihang Xu Yin Xu Yu Xu Baojun Yan Xiongbo Yan Yupeng Yan Anbo Yang Changgen Yang Huan Yang Jie Yang Lei Yang Xiaoyu Yang Yifan Yang Haifeng Yao Zafar Yasin Jiaxuan Ye Mei Ye Ugur Yegin Frédéric Yermia Peihuai Yi Xiangwei Yin Zhengyun You Boxiang Yu Chiye Yu Chunxu Yu Hongzhao Yu Miao Yu Xianghui Yu Zeyuan Yu Chengzhuo Yuan Ying Yuan Zhenxiong Yuan Ziyi Yuan Baobiao Yue Noman Zafar Andre Zambanini Pan Zeng Shan Zeng Tingxuan Zeng Yuda Zeng Liang Zhan Feiyang Zhang Guoqing Zhang Haiqiong Zhang Honghao Zhang Jiawen Zhang Jie Zhang Jingbo Zhang Peng Zhang Qingmin Zhang Shiqi Zhang Tao Zhang Xiaomei Zhang Xuantong Zhang Yan Zhang Yinhong Zhang Yiyu Zhang Yongpeng Zhang Yuanyuan Zhang Yumei Zhang Zhenyu Zhang Zhijian Zhang Fengyi Zhao Jie Zhao Rong Zhao Shujun Zhao Tianchi Zhao Dongqin Zheng Hua Zheng Minshan Zheng Yangheng Zheng Weirong Zhong Jing Zhou Li Zhou Nan Zhou Shun Zhou Xiang Zhou Jiang Zhu Kejun Zhu Honglin Zhuang Liang Zong Jiaheng Zou | 2021 | Chinese Physics C2021，45，2： | 0 |
| 7 | Control characteristics of D + A combined multi-pump controlled system显示文摘In order to solve the flow mismatch problem between pumping source output and workload demand,a novel configuration of D + A combined multi-pump controlled hydraulic system,similar to a pump-controlled system,is proposed for a large power hydraulic system in this study. This novel configuration consists of several parallel fixed displacement pumps of different sizes and proportional variable displacement pumps,which is controlled by digital signal( on/off) and analog signal respectively( D + A pumps). The system flow is divided into two parts,one is the total flow from fixed displacement pumps,and the other is the rest desired flow supplied by variable displacement pumps to smooth and improve the demand flow. First,basic design principles and evaluation indicators of the proposed system are introduced. Then,a flow state matrix of the binary-coding digital pumps( 1: 2: 4) is obtained to provide the control signals of pumps. Experimental results show that the system output flow tracks well with acceptable flow deviation,though a little lag behind input signal. | 姚静 Wang Pei Cao Xiaoming Zhang Yang Kong Xiangdong | 2018 | High Technology Letters2018，24，3： | 0 |
| 8 | Machine learning accelerated carbon neutrality research using big data-from predictive models to interatomic potentials显示文摘Carbon neutrality has been proposed as a solution for the current severe energy and climate crisis caused by the overuse of fossil fuels, and machine learning(ML) has exhibited excellent performance in accelerating related research owing to its powerful capacity for big data processing. This review presents a detailed overview of ML accelerated carbon neutrality research with a focus on energy management, screening of novel energy materials, and ML interatomic potentials(MLIPs), with illustrations of two selected MLIP algorithms: moment tensor potential(MTP) and neural equivariant interatomic potential(NequIP). We conclude by outlining the important role of ML in accelerating the achievement of carbon neutrality from global-scale energy management, unprecedented screening of advanced energy materials in massive chemical space, to the revolution of atomicscale simulations of MLIPs, which has the bright prospect of applications. | WU LingJun XU ZhenMing WANG ZiXuan CHEN ZiJian HUANG ZhiChao PENG Chao PEI XiangDong LI XiangGuo MAILOA Jonathan P HSIEH Chang-Yu WU Tao YU Xue-Feng ZHAO HaiTao | 2022 | Science China(Technological Sciences)2022，65，10： | 0 |
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