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Acetaminophen overdose-induced acute liver injury can be alleviated by static magnetic field

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Zoological Research 2024年第3期45卷 478-490页

作者： Han-Xiao chen Xin-yu wang Biao yu Chuan-Lin Feng guo-Feng cheng Lei Zhang Jun-Jun wang Ying wang Ruo-Wen guo Xin-Miao Ji Wen-Jing xie wei-Li chen Chao Song Xin Zhang CAS Key Laboratory of High Magnetic Field and Ion Beam Physical Biology High Magnetic Field LaboratoryHefei Institutes of Physical ScienceChinese Academy of SciencesHefeiAnhui 230031China science Island Branch of Graduate school University of Science and Technology of ChinaHefeiAnhui 230026China Institutes of Physical science and information technology Anhui UniversityHefeiAnhui 230601China

Acetaminophen(APAP),the most frequently used mild analgesic and antipyretic drug worldwide,is implicated in causing 46%of all acute liver failures in the USA and between 40%and 70%in *** predominant pharmacological intervention approved for mitigating such overdose is the antioxidant N-acetylcysteine(NAC);however,its efficacy is limited in cases of advanced liver injury or when administered at a late *** the current study,we discovered that treatment with a moderate intensity static magnetic field(SMF)notably reduced the mortality rate in mice subjected to high-dose APAP from 40%to 0%,proving effective at both the initial liver injury stage and the subsequent recovery *** the early phase of liver injury,SMF markedly reduced APAPinduced oxidative stress,free radicals,and liver damage,resulting in a reduction in multiple oxidative stress markers and an increase in the antioxidant glutathione(GSH).During the later stage of liver recovery,application of vertically downward SMF increased DNA synthesis and hepatocyte ***,the combination of NAC and SMF significantly mitigated liver damage induced by high-dose APAP and increased liver recovery,even 24 h post overdose,when the effectiveness of NAC alone substantially ***,this study provides a noninvasive non-pharmaceutical tool that offers dual benefits in the injury and repair stages following APAP *** note,this tool can work as an alternative to or in combination with NAC to prevent or minimize liver damage induced by APAP,and potentially other toxic overdoses.

关键词： Acetaminophen Acute liver injury Static magnetic fields Oxidative stress DNA synthesis

Large circuit models: opportunities and challenges

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science China(information sciences) 2024年第10期67卷 25-66页

作者： Lei chen Yiqi chen Zhufei CHU Wenji FANG Tsung-Yi HO Ru HUANG yu HUANG Sadaf KHAN Min LI Xingquan LI yu LI yun liang Jinwei LIU Yi LIU Yibo LIN guojie LUO Hongyang PAN Zhengyuan SHI Guangyu SUN Dimitrios TSARAS Runsheng wang Ziyi wang Xinming wei zhiyao xie Qiang XU chenhao XUE Junchi YAN Jun YANG Bei yu Mingxuan yuAN Evangeline F.Y.YOUNG Xuan ZENG Haoyi ZHANG Zuodong ZHANG yuxiang ZHAO Hui-Ling ZHEN Ziyang ZHENG Binwu ZHU Keren ZHU Sunan ZOU Huawei Noah’s Ark Lab school of Integrated Circuits Peking University Faculty of Electrical engineering and Computer science Ningbo University Department of Electronic and Computer engineering Hong Kong University of Science and Technology Department of Computer science and engineering The Chinese University of Hong Kong school of Integrated Circuits Southeast University Huawei HiSilicon Peng cheng Laboratory school of Computer science Peking University school of Microelectronics State Key Laboratory of Integrated Chips and System Fudan University school of Artificial Intelligence Shanghai Jiao Tong University

Within the electronic design automation(EDA) domain, artificial intelligence(AI)-driven solutions have emerged as formidable tools, yet they typically augment rather than redefine existing methodologies. These solutions often repurpose deep learning models from other domains, such as vision, text, and graph analytics, applying them to circuit design without tailoring to the unique complexities of electronic circuits. Such an “AI4EDA” approach falls short of achieving a holistic design synthesis and understanding,overlooking the intricate interplay of electrical, logical, and physical facets of circuit data. This study argues for a paradigm shift from AI4EDA towards AI-rooted EDA from the ground up, integrating AI at the core of the design process. Pivotal to this vision is the development of a multimodal circuit representation learning technique, poised to provide a comprehensive understanding by harmonizing and extracting insights from varied data sources, such as functional specifications, register-transfer level(RTL) designs, circuit netlists,and physical layouts. We champion the creation of large circuit models(LCMs) that are inherently multimodal, crafted to decode and express the rich semantics and structures of circuit data, thus fostering more resilient, efficient, and inventive design methodologies. Embracing this AI-rooted philosophy, we foresee a trajectory that transcends the current innovation plateau in EDA, igniting a profound “shift-left” in electronic design methodology. The envisioned advancements herald not just an evolution of existing EDA tools but a revolution, giving rise to novel instruments of design-tools that promise to radically enhance design productivity and inaugurate a new epoch where the optimization of circuit performance, power, and area(PPA) is achieved not incrementally, but through leaps that redefine the benchmarks of electronic systems' capabilities.

关键词： AI-rooted EDA large circuit models (LCMs) multimodal circuit representation learning circuit optimization

Artificial intelligence for geoscience:Progress,challenges,and perspectives

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The Innovation 2024年第5期5卷 136-160,135页

作者： Tianjie Zhao Sheng wang Chaojun Ouyang Min chen chenying Liu Jin Zhang Long yu Fei wang Yong xie Jun Li Fang wang Sabine Grunwald Bryan MWong Fan Zhang Zhen Qian Yongjun Xu chengqing yu wei Han Tao Sun Zezhi Shao Tangwen Qian Zhao chen Jiangyuan Zeng Huai Zhang Husi Letu Bing Zhang Li wang Lei Luo Chong Shi Hongjun Su Hongsheng Zhang Shuai Yin Ni Huang wei Zhao Nan Li Chaolei Zheng Yang Zhou Changping Huang Defeng Feng Qingsong Xu Yan Wu Danfeng Hong Zhenyu wang Yinyi Lin Tangtang Zhang Prashant Kumar Antonio Plaza Jocelyn Chanussot Jiabao Zhang Jiancheng Shi Lizhe wang Aerospace information Research Institute Chinese Academy of SciencesBeijing 100094China school of Computer science China University of GeosciencesWuhan 430078China State Key Laboratory of Mountain Hazards and engineering Resilience Institute of Mountain Hazards and EnvironmentChinese Academy of SciencesChengdu 610299China Key Laboratory of Virtual Geographic Environment(Ministry of Education of prc) Nanjing Normal UniversityNanjing 210023China Data science in Earth Observation Technical University of Munich80333 MunichGermany The National Key Laboratory of Water Disaster Prevention Yangtze Institute for Conservation and DevelopmentHohai UniversityNanjing 210098China Institute of Computing technology Chinese Academy of SciencesBeijing 100190China school of Geographical sciences Nanjing University of Information Science and TechnologyNanjing 210044China State Key Laboratory of Soil and Sustainable Agriculture Institute of Soil ScienceChinese Academy of SciencesNanjing 210008China Soil Water and Ecosystem Sciences DepartmentUniversity of FloridaPO Box 110290GainesvilleFLUSA Materials science engineering Program Cooperating Faculty Member in the Department of Chemistry and Department of Physics Astronomy University of CaliforniaCaliforniaRiversideCA 92521USA Institute of Remote Sensing and Geographical information System School of Earth and Space SciencesPeking UniversityBeijing 100871China Key Laboratory of Computational Geodynamics University of Chinese Academy of SciencesBeijing 100049China International Research Center of Big Data for Sustainable Development Goals Beijing 100094China College of Geography and Remote Sensing Hohai UniversityNanjing 211100China Department of Geography The University of Hong KongHong Kong 999077SARChina Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control Nanjing 210044China school of Environmental science and engineering Nanjing University of Information Science&TechnologyNanjing 210044China Collaborative Inno

This paper explores the evolution of geoscientific inquiry,tracing the progression from traditional physics-based models to modern data-driven approaches facilitated by significant advancements in artificial intelligence(AI)and data collection *** models,which are grounded in physical and numerical frameworks,provide robust explanations by explicitly reconstructing underlying physical ***,their limitations in comprehensively capturing Earth’s complexities and uncertainties pose challenges in optimization and real-world *** contrast,contemporary data-driven models,particularly those utilizing machine learning(ML)and deep learning(DL),leverage extensive geoscience data to glean insights without requiring exhaustive theoretical *** techniques have shown promise in addressing Earth science-related ***,challenges such as data scarcity,computational demands,data privacy concerns,and the“black-box”nature of AI models hinder their seamless integration into *** integration of physics-based and data-driven methodologies into hybrid models presents an alternative *** models,which incorporate domain knowledge to guide AI methodologies,demonstrate enhanced efficiency and performance with reduced training data *** review provides a comprehensive overview of geoscientific research paradigms,emphasizing untapped opportunities at the intersection of advanced AI techniques and *** examines major methodologies,showcases advances in large-scale models,and discusses the challenges and prospects that will shape the future landscape of AI in *** paper outlines a dynamic field ripe with possibilities,poised to unlock new understandings of Earth’s complexities and further advance geoscience exploration.

关键词： Earth utilizing landscape

A Localization Method of High Energy Transients for All-sky Gamma-ray Monitor

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Research in Astronomy and Astrophysics 2024年第10期24卷 25-35页

作者： Yi Zhao wangchen Xue Shaolin Xiong Qi Luo yuanhao wang Jiacong Liu Heng yu Xiaoyun Zhao yue Huang Jinyuan Liao Jianchao Sun Xiaobo Li Qibin Yi Ce Cai Shuo Xiao Shenglun xie Chao Zheng Yanqiu Zhang chenwei wang Wenjun Tan zhiwei guo Chaoyang Li Zhenghua An Gang chen Yanqi Du Min Gao Ke Gong Dongya guo Jiang He Jianjian He Bing Li Gang Li Xinqiao Li Jing liang Xiaohua liang Yaqing Liu Xiang Ma Rui Qiao Liming Song Xinying Song Xilei Sun Jin wang Ping wang Xiangyang Wen Hong Wu Yanbing Xu Sheng Yang Dali Zhang Fan Zhang Hongmei Zhang Peng Zhang Shu Zhang Zhen Zhang Shijie Zheng Keke Zhang Xingbo Han Haiyan Wu Hu Tai Hao Geng Gaopeng Lu wei Xu Fanchao Lyu Hongbo Zhang Fangjun Lu Shuangnan Zhang Department of Astronomy Beijing Normal UniversityBeijing 100875China Key Laboratory of Particle Astrophysics Institute of High Energy PhysicsChinese Academy of SciencesBeijing 100049China university of Chinese Academy of sciences Beijing 100049China school of Physics and Optoelectronics Xiangtan UniversityXiangtan 411105China College of Physics Hebei Normal UniversityShijiazhuang 050024China Guizhou Provincial Key Laboratory of Radio Astronomy and Data Processing Guizhou Normal UniversityGuiyang 550001China school of Physics and Electronic science Guizhou Normal UniversityGuiyang 550001China Institute of Astrophysics Central China Normal UniversityWuhan 430079China College of physics sciences technology Hebei UniversityBaoding 071002China Physics and Space science College China West Normal UniversityNanchong 637002China school of Computing and Artificial Intelligence Southwest Jiaotong UniversityChengdu 611756China College of Electronic and information engineering Tongji UniversityShanghai 201804China Innovation Academy for Microsatellites of Chinese Academy of sciences Shanghai 201304China National Space science Center Chinese Academy of SciencesBeijing 100190China school of Earth and Space sciences University of Science and Technology of ChinaHefei 230026China Electronic information school Wuhan UniversityWuhan 430072China Key Laboratory of Transportation Meteorology of China Meteorological Administration Nanjing Joint Institute for Atmospheric SciencesNanjing 210000China Key Laboratory of Middle Atmosphere and Global Environment Observation Institute of Atmospheric PhysicsChinese Academy of SciencesBeijing 100029China

Fast and reliable localization of high-energy transients is crucial for characterizing the burst properties and guiding the follow-up *** based on the relative counts of different detectors has been widely used for all-sky gamma-ray *** are two major methods for this count distribution localization:χ^(2)minimization method and the Bayesian *** we propose a modified Bayesian method that could take advantage of both the accuracy of the Bayesian method and the simplicity of the χ^(2)*** comprehensive simulations,we find that our Bayesian method with Poisson likelihood is generally more applicable for various bursts than the χ^(2)method,especially for weak *** further proposed a location-spectrum iteration approach based on the Bayesian inference,which could alleviate the problems caused by the spectral difference between the burst and location *** method is very suitable for scenarios with limited computation resources or timesensitive applications,such as in-flight localization software,and low-latency localization for rapidly follow-up observations.

关键词： methods:data analysis methods:analytical (stars:)gamma-ray burst:general

The 2022 report of synergetic roadmap on carbon neutrality and clean air for China:Accelerating transition in key sectors

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Environmental science and Ecotechnology 2024年第3期19卷 4-18页

作者： yu Lei zhicong Yin Xi Lu Qiang Zhang Jicheng Gong Bofeng Cai Cilan Cai Qimin Chai Huopo chen Renjie chen Shi chen Wenhui chen Jing cheng Xiyuan Chi Hancheng Dai Xiangzhao Feng Guannan Geng Jianlin Hu Shan Hu Cunrui Huang Tiantian Li wei Li Xiaomei Li Jun Liu Xin Liu Zhu Liu Jinghui Ma yue Qin Dan Tong Xuhui wang Xuying wang Rui Wu Qingyang Xiao Yang xie Xiaolong Xu Tao Xue Haipeng yu Da Zhang Ning Zhang Shaohui Zhang Shaojun Zhang Xian Zhang Xin Zhang Zengkai Zhang Bo Zheng Yixuan Zheng Jian Zhou Tong Zhu Jinnan wang Kebin He Center of Air Quality Simulation and System Analysis Chinese Academy of Environmental PlanningBeijing100041China Center for Carbon Neutrality Chinese Academy of Environmental PlanningBeijing100041China Key Laboratory of Meteorological Disaster Ministry of Education/Joint International Research Laboratory of Climate and Environment Change(ILCEC)/Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters(CIC-FEMD)Nanjing University of Information Science&TechnologyNanjing210044China State Key Joint Laboratory of Environment Simulation and Pollution Control School of EnvironmentTsinghua UniversityBeijing100084China Institute for Carbon Neutrality Tsinghua UniversityBeijing100084China Ministry of Education Key Laboratory for Earth System Modelling Department of Earth System ScienceTsinghua UniversityBeijing100084China State Key Joint Laboratory for Environment Simulation and Pollution Control College of Environmental Sciences and Engineering and Center for Environment and HealthPeking UniversityBeijing100871China National Center for Climate Change Strategy and International CooperationBeijing100035China Nansen-Zhu International Research Centre Institute of Atmospheric PhysicsChinese Academy of SciencesBeijing100029China school of Public Health Key Lab of Public Health Safety of the Ministry of Education and Key Lab of Health Technology Assessment of the Ministry of HealthFudan UniversityShanghai200032China school of Economics and Management Beijing University of Chemical TechnologyBeijing100029China Department of Earth System science University of CaliforniaIrvineCA92697USA National Meteorological Center China Meteorological AdministrationBeijing100081China College of Environmental sciences and engineering Peking UniversityBeijing100871China Policy Research Center for Environment and Economy Ministry of Ecology and Environment of the People's Republic of ChinaBeijing100029China Jiangsu Key Laboratory of Atmospheric Environment Monitoring

China is now confronting the intertwined challenges of air pollution and climate *** the high synergies between air pollution abatement and climate change mitigation,the Chinese government is actively promoting synergetic control of these two *** Synergetic Roadmap project was launched in 2021 to track and analyze the progress of synergetic control in China by developing and monitoring key *** Synergetic Roadmap 2022 report is the first annual update,featuring 20 indicators across five aspects:synergetic governance system and practices,progress in structural transition,air pollution and associated weather-climate interactions,sources,sinks,and mitigation pathway of atmospheric composition,and health impacts and benefits of coordinated *** to the comprehensive review presented in the 2021 report,the Synergetic Roadmap 2022 report places particular emphasis on progress in 2021 with highlights on actions in key sectors and the relevant *** milestones include the proportion of non-fossil power generation capacity surpassing coal-fired capacity for the first time,a decline in the production of crude steel and cement after years of growth,and the surging penetration of electric ***,in 2022,China issued the first national policy that synergizes abatements of pollution and carbon emissions,marking a new era for China's pollution-carbon *** changes highlight China's efforts to reshape its energy,economic,and transportation structures to meet the demand for synergetic control and sustainable ***,the country has witnessed a slowdown in carbon emission growth,improved air quality,and increased health benefits in recent years.

关键词： Synergetic roadmap Carbon neutrality Clean air

Incidence and prognosis of olfactory and gustatory dysfunctions related to SARS-CoV-2 Omicron strain infection in China:A national multicenter survey of 35,566 individuals

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World Journal of Otorhinolaryngology-Head and Neck Surgery 2024年第2期10卷 113-120页

作者： Meng-Fan Liu Rui-Xia Ma Xian-Bao Cao Hua Zhang Shui-Hong Zhou wei-Hong Jiang Yan Jiang Jing-Wu Sun Qin-Tai Yang Xue-Zhong Li Ya-Nan Sun Li Shi Min wang Xi-cheng Song Fu-Quan chen Xiao-Shu Zhang Hong-Quan wei Shao-Qing yu Dong-Dong Zhu Luo Ba zhi-wei Cao Xu-Ping Xiao Xin wei zhi-Hong Lin Feng-Hong chen Chun-Guang Shan Guang-Ke wang Jing Ye Shen-Hong Qu Chang-Qing Zhao Zhen-Lin wang Hua-Bin Li Feng Liu Xiao-Bo Cui Sheng-Nan Ye Zheng Liu yu Xu Xiao Cai wei Huang Ru-Xin Zhang yu-Lin Zhao guo-Dong yu Guang-Gang Shi Mei-Ping Lu Yang Shen yu-Tong Zhao Jia-Hong Pei Shao-Bing xie Long-Gang yu Ye-Hai Liu Shao-wei Gu yu-cheng Yang Lei cheng Jian-Feng liu Graduate school of beijing university of Chinese Medicine BeijingChina Department of Otorhinolaryngology Head and Neck Surgery China-Japan Friendship HospitalBeijingChina Department of Otorhinolaryngology Head and Neck Surgery The First People's Hospital of YinchuanYinchuanChina Department of Otorhinolaryngology The First People's Hospital of Yunnan ProvinceKunmingChina Department of Otorhinolaryngology The First Affiliated Hospital of Xinjiang Medical UniversityUrumqiChina Department of Otorhinolaryngology Head and Neck Surgery The First Affiliated Hospital of Zhejiang University School of MedicineHangzhouChina Department of Otorhinolaryngology Head and Neck Surgery Xiangya Hospital Central South UniversityChangshaChina Department of Otorhinolaryngology Head and Neck Surgery The Affiliated Hospital of Qingdao UniversityQingdaoChina Department of Otorhinolaryngology Head and Neck Surgery The First Affiliated Hospital of USTCHefeiChina Department of Otorhinolaryngology Head and Neck Surgery The Third Affiliated Hospital of Sun Yat-sen UniversityGuangzhouChina Department of Otorhinolaryngology Head and Neck Surgery Qilu Hospital of Shandong UniversityJinanChina Department of Otorhinolaryngology Head and Neck Surgery The Second Affiliated Hospital of Harbin Medical UniversityHarbinChina Department of Otolaryngology The Second Hospital of Shandong UniversityShandong UniversityJinanChina Department of Otorhinolaryngology Head and Neck Surgery Peking University People's HospitalBeijingChina Department of Otorhinolaryngology Head and Neck Surgery Yantai Yuhuangding HospitalQingdao UniversityYantaiChina Department of Otorhinolaryngology Head and Neck Surgery Xijing HospitalThe Fourth Military Medical UniversityXi'anChina Gansu Provincial Center for Disease Control and Prevention LanzhouChina Department of Otorhinolaryngology Head and Neck Surgery The First Affiliated Hospital of China Medical UniversityShenyangChina Department of Otorhinolaryngology Head and Neck Surgery Tongji Hospit

Objective:This cross-sectional study aimed to determine the epidemiology of olfactory and gustatory dysfunctions related to COVID-19 in ***:This study was conducted by 45 tertiary Grade-A hospitals in *** and offline questionnaire data were obtained from patients infected with COVID-19 between December 28,2022,and February 21,*** collected information included basic demographics,medical history,smoking and drinking history,vaccination history,changes in olfactory and gustatory functions before and after infection,and other postinfection symptoms,as well as the duration and improvement status of olfactory and gustatory ***:Complete questionnaires were obtained from 35,566 *** overall incidence of olfactory and taste dysfunction was 67.75%.Being female or being a cigarette smoker increased the likelihood of developing olfactory and taste *** received four doses of the vaccine or having good oral health or being a alcohol drinker decreased the risk of such *** infection,the average olfactory and taste VAS scores were 8.41 and 8.51,respectively;after infection,they decreased to 3.69 and 4.29 and recovered to 5.83 and 6.55 by the time of the *** median duration of dysosmia and dysgeusia was 15 and 12 days,respectively,with 0.5%of patients having symptoms lasting for more than 28 *** overall self-reported improvement rate was 59.16%.Recovery was higher in males,never smokers,those who received two or three vaccine doses,and those that had never experienced dental health issues,or chronic accompanying ***:The incidence of dysosmia and dysgeusia following infection with the SARS-CoV-2 virus is high in *** and prognosis are influenced by several factors,including sex,SARS-CoV-2 vaccination,history of head-facial trauma,nasal and oral health status,smoking and drinking history,and the persistence of accompanying symptoms.

关键词： epidemiologic studies incidence olfactory disorders prognosis SARS-CoV-2 taste disorders

基于白光中子源的^(197)Au中子辐射俘获截面测量及共振参数分析

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物理学报 2024年第7期73卷 104-113页

作者：罗淏天张奇玮栾广源王晓宇邹翀任杰阮锡超贺国珠鲍杰孙琪黄翰雄王朝辉吴鸿毅顾旻皓余滔解立坤陈永浩安琪白怀勇鲍煜曹平陈昊磊陈琪萍陈裕凯陈朕崔增琪樊瑞睿封常青高可庆韩长材韩子杰何泳成洪杨黄蔚玲黄锡汝季筱璐吉旭阳蒋伟江浩雨姜智杰敬罕涛康玲康明涛李波李超李嘉雯李论李强李晓李样刘荣刘树彬刘星言穆奇丽宁常军齐斌斌任智洲宋英鹏宋朝晖孙虹孙康孙晓阳孙志嘉谭志新唐洪庆唐靖宇唐新懿田斌斌王丽娇王鹏程王琦王涛峰文杰温中伟吴青彪吴晓光吴煊羊奕伟易晗于莉于永积张国辉张林浩张显鹏张玉亮张志永赵豫斌周路平周祖英朱丹阳朱科军朱鹏朱兴华中国原子能科学研究院核数据重点实验室北京102413 中国科学院高能物理研究所北京100049 散裂中子源科学中心东莞523803 核探测与核电子学国家重点实验室北京100049 中国科学技术大学近代物理系核探测与核电子学国家重点实验室合肥230026 北京大学物理学院核物理与核技术国家重点实验室北京100871 中国工程物理研究院核物理与化学研究所绵阳621900 西北核技术研究院西安710024 中国科学院大学北京100049 中国科学技术大学工程与应用物理系合肥230026 北京航空航天大学物理学院北京100083 华能山东石岛湾核电有限公司荣成264312

中子辐射俘获反应在反应堆运行、核装置设计及核天体物理研究中起重要的作用.4πBaF_(2)探测装置有着高时间分辨能力、低中子灵敏度、高探测效率等优点,适合开展中子辐射俘获反应截面数据的测量.中国原子能科学研究院核数据重点实验室... 详细信息

中子辐射俘获反应在反应堆运行、核装置设计及核天体物理研究中起重要的作用.4πBaF_(2)探测装置有着高时间分辨能力、低中子灵敏度、高探测效率等优点,适合开展中子辐射俘获反应截面数据的测量.中国原子能科学研究院核数据重点实验室建立了伽马全吸收装置(Gamma total absorption facility,GTAF),该装置用28块六棱BaF_(2)晶体和12块五棱BaF_(2)晶体构成了外径25 cm,内径10 cm的球壳,覆盖了95.2%的立体角.利用GTAF在中国散裂中子源Back-n束线上,测量了197Au(n,γ)的反应截面数据.测量数据通过能量筛选、PSD方法、晶体多重性筛选进行了初步本底扣除,随后结合对^(nat)C及空样品的测量数据对本底进行了分析及扣除,获得了197Au俘获反应的产额,利用SAMMY程序拟合得到了^(197)Au在1—100 e V的共振能量、中子共振宽度和伽马共振宽度参数.实验测量结果与ENDF/B-VIII.0数据库符合良好,其共振参数存在一定差异,分析原因可能与GTAF能量分辨率、Back-n的中子能谱测量精度、以及实验本底扣除方法相关,这也是下一步工作的重点.

关键词：中子辐射俘获截面共振参数白光中子源伽马全吸收装置

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Hot spots engineering by dielectric support for enhanced photocatalytic redox reactions

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Nano Research 2023年第1期16卷 239-247页

作者： Yan yu yujun xie Pengfei Zhang wei Zhang Wenxing wang Shuyu Zhang Qiongrong Ou wei Li Department of Chemistry State Key Laboratory of Molecular Engineering of PolymersShanghai Key Lab of Molecular Catalysis and Innovative MaterialsLaboratory of Advanced MaterialsFudan UniversityShanghai 200433China Institute for Electric Light Sources School of Information Science and TechnologyFudan UniversityShanghai 200433China Zhuhai Fudan Innovation Institute Guangdong-Macao In-Depth Cooperation Zone in HengqinZhuhai 519000China

Regulating the surface plasmon resonance(SPR)of metallic nanostructures is of great interests for optical and catalytic applications,however,it is still a great challenge for tuning SPR features of small metallic nanoparticles(engineering provides a new strategy for tuning SPR of small metallic nanocrystals towards the development of advanced plasmon-based applications.

关键词： surface plasmon resonance hot spots urchin-like silica nanoparticles photocatalysis core-shell structures TiO_(2)

Motion planning and tracking control of a four-wheel independently driven steered mobile robot with multiple maneuvering modes

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Frontiers of Mechanical engineering 2021年第3期16卷 504-527页

作者： Xiaolong ZHANG yu HUANG Shuting wang Gen LI yuanlong xie wei MENG school of Mechanical science and engineering Huazhong University of Science and TechnologyWuhan 430074China school of information engineering Wuhan University of TechnologyWuhan 430070China

Safe and effective autonomous navigation in dynamic environments is challenging for four-wheel independently driven steered mobile robots(FWIDSMRs)due to the flexible allocation of multiple maneuver *** address this problem,this study proposes a novel multiple mode-based navigation system,which can achieve efficient motion planning and accurate tracking *** reduce the calculation burden and obtain a comprehensive optimized global path,a kinodynamic interior-exterior cell exploration planning method,which leverages the hybrid space of available modes with an incorporated exploration guiding algorithm,is *** utilizing the sampled subgoals and the constructed global path,local planning is then performed to avoid unexpected obstacles and potential *** the desired profile curvature and preselected mode,a fuzzy adaptive receding horizon control is proposed such that the online updating of the predictive horizon is realized to enhance the trajectory-following *** tracking controller design is achieved using the quadratic programming(QP)technique,and the primal-dual neural network optimization technique is used to solve the QP *** results on a real-time FWIDSMR validate that the proposed method shows superior features over some existing methods in terms of efficiency and accuracy.

关键词： mobile robot multiple maneuvering mode motion planning tracking control receding horizon control