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水文区位指数初探

成都理工大学学报（自然科学版） 2007年第3期34卷 231-237页

作者：曾兵谭海樵毋丽娟中国矿业大学资源与地球科学学院江苏徐州221008

在分析了地表河流系统的自然功能及其生命体征的基础上,提出了水文区位指数及其计算方法。整个系统中各个自然节点间势能向动能的转换为基础的流动性就是其生命体征的核心指标。水文区位就是河流系统的自然节点以及人为节点在河流系统... 详细信息

在分析了地表河流系统的自然功能及其生命体征的基础上,提出了水文区位指数及其计算方法。整个系统中各个自然节点间势能向动能的转换为基础的流动性就是其生命体征的核心指标。水文区位就是河流系统的自然节点以及人为节点在河流系统中的位置。水文区位指数是人为节点加入某河段前后河流流动性变化程度的量化指标,可用该河段动能之比来计算。作为评判河流系统生命体征的主要量化指标,该指数可用于有效地修复并维系河流系统的自然功能。为维系河流系统的生命和流域可持续发展,建议借鉴都江堰两千余年川流不息的经验,将0.4定为河流系统各河段的水文区位指数的参考下限。为实现流域内社会经济与自然水文循环的同步可持续发展,作者探讨了基于水位区位指数的可调控水资源开发利用模式和城市发展模型。

关键词：水文区位指数河流系统河流生命体征水文循环修复

A rapid advice guideline for the diagnosis and treatment of 2019 novel coronavirus(2019-nCoV) infected pneumonia(standard version)

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Military Medical Research 2020年第1期7卷 1-22页

作者： Ying-Hui Jin lin Cai Zhen-Shun Cheng Hong Cheng Tong Deng Yi-Pin Fan Cheng Fang Di Huang Lu-Qi Huang qiao Huang Yong Han Bo Hu Fen Hu bing-Hui li Yi-Rong li Ke liang li-Kai lin li-Sha Luo Jing Ma lin-Lu Ma Zhi-Yong Peng Yun-Bao Pan Zhen-Yu Pan Xue-Qun Ren Hui-Min Sun Ying Wang Yun-Yun Wang Hong Weng Chao-Jie Wei Dong-Fang wu Jian Xia Yong Xiong hai-Bo Xu Xiao-Mei Yao Yu-Feng Yuan Tai-Sheng Ye Xiao-Chun Zhang Ying-Wen Zhang Yin-Gao Zhang Hua-Min Zhang Yan Zhao Ming-juan Zhao Hao Zi Xian-Tao zeng Yong-Yan Wang Xing-Huan Wang 无 Center for Evidence-Based and Translational Medicine Zhongnan Hospital of Wuhan UniversityWuhan 430071China Institute of Hospital Management Wuhan UniversityWuhan 430071China Department of Respiratory Medicine Zhongnan Hospital of Wuhan UniversityWuhan 430071China Department of Pharmacy Zhongnan Hospital of Wuhan UniversityWuhan 430071China Institute of Evidence-Based Medicine and Knowledge Translation Henan UniversityKaifeng 475000China China Academy of Chinese Medical Sciences Beijing 100700China China Center for Evidence Based Traditional Chinese Medicine(CCEBTCM) Beijing 100700China Department of Critical Care Medicine Zhongnan Hospital of Wuhan UniversityWuhan 430071China Department of Clinical Laboratory Zhongnan Hospital of Wuhan UniversityWuhan 430071China Department of Infectious Diseases Zhongnan Hospital of Wuhan UniversityWuhan 430071China Division of Medical Affairs Zhongnan Hospital of Wuhan UniversityWuhan 430071China Division of Nursing Affairs Zhongnan Hospital of Wuhan UniversityWuhan 430071China Office of Nosocomial Infection Control Zhongnan Hospital of Wuhan UniversityWuhan 430071China Emergency Center Zhongnan Hospital of Wuhan UniversityWuhan 430071China Department of Radiology Zhongnan Hospital of Wuhan UniversityWuhan 430071China Department of Health Research Methods Evidenceand ImpactMcMaster UniversityHamiltonON L8S 4L8Canada Department of Traditional Chinese Medicine Zhongnan Hospital of Wuhan UniversityWuhan 430071China Global Health Institute Wuhan UniversityWuhan 430072China the Zhongnan Hospital of wuhan University Novel Coronavirus Management and Research Team Evidence-Based Medicine Chapter of China International Exchange and Promotive Association for Medical and Health Care(CPAM)

In December 2019, a new type viral pneumonia cases occurred in wuhan, Hubei Province;and then named "2019 novel coronavirus(2019-nCoV)" by the World Health Organization(WHO) on 12 January 2020. For it is a never been experienced respiratory disease before and with infection ability widely and quickly, it attracted the world’s attention but without treatment and control manual. For the request from frontline clinicians and public health professionals of 2019-nCoV infected pneumonia management, an evidence-based guideline urgently needs to be developed. Therefore, we drafted this guideline according to the rapid advice guidelines methodology and general rules of WHO guideline development;we also added the first-hand management data of Zhongnan Hospital of wuhan University. This guideline includes the guideline methodology, epidemiological characteristics, disease screening and population prevention, diagnosis, treatment and control(including traditional Chinese Medicine), nosocomial infection prevention and control, and disease nursing of the 2019-nCoV. Moreover, we also provide a whole process of a successful treatment case of the severe 2019-nCoV infected pneumonia and experience and lessons of hospital rescue for 2019-nCoV infections. This rapid advice guideline is suitable for the first frontline doctors and nurses, managers of hospitals and healthcare sections, community residents, public health persons, relevant researchers, and all person who are interested in the 2019-nCoV.

关键词： 2019 novel coronavirus 2019-nCoV Respiratory disease Pneumonia Infectious diseases Rapid advice guideline Clinical practice guideline Evidence-based medicine

The first data release(DR1) of the LAMOST regular survey

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Research in Astronomy and Astrophysics 2015年第8期15卷 1095-1124页

作者： A-li Luo Yong-Heng Zhao Gang Zhao li-Cai Deng Xiao-Wei liu Yi-Peng Jing Gang Wang Hao-Tong Zhang Jian-Rong Shi Xiang-Qun Cui Yao-Quan Chu Guo-Ping li Zhong-Rui Bai Yue wu Yan Cai Shu-Yun Cao Zi-Huang Cao Jeffrey L.Carlin hai-Yuan Chen Jian-Jun Chen Kun-Xin Chen li Chen Xue-Lei Chen Xiao-Yan Chen Ying Chen Norbert Christlieb Jia-Ru Chu Chen-Zhou Cui Yi-qiao Dong bing Du Dong-Wei Fan Lei Feng Jian-Ning Fu Peng Gao Xue-Fei Gong Bo-Zhong Gu Yan-Xin Guo Zhan-Wen Han Bo-liang He Jin-liang Hou Yong-Hui Hou Wen Hou Hong-Zhuan Hu Ning-Sheng Hu Zhong-Wen Hu Zhi-Ying Huo Lei Jia Fang-Hua Jiang Xiang Jiang Zhi-Bo Jiang Ge Jin Xiao Kong Xu Kong Ya-juan Lei Ai-Hua li Chang-Hua li Guang-Wei li hai-Ning li Jian li Qi li Shuang li Sha-Sha li Xin-Nan li Yan li Yin-Bi li Ye-Ping li Yuan liang Chien-Cheng lin Chao liu Gen-Rong liu Guan-Qun liu Zhi-Gang liu Wen-Zhi Lu Yu Luo Yin-Dun Mao Heidi Newberg Ji-Jun Ni Zhao-Xiang Qi Yong-Jun Qi Shi-Yin Shen Huo-Ming Shi Jing Song Yi-Han Song Ding-Qiang Su Hong-Jun Su Zheng-Hong tang Qing-Sheng Tao Yuan Tian Dan Wang Da-Qi Wang Feng-Fei Wang Guo-Min Wang hai Wang Hong-Chi Wang Jian Wang Jia-Ning Wang Jian-ling Wang Jian-Ping Wang Jun-Xian Wang Lei Wang Meng-Xin Wang Shou-Guan Wang Shu-Qing Wang Xia Wang Ya-Nan Wang You Wang Yue-Fei Wang You-Fen Wang Peng Wei Ming-Zhi Wei Hong wu Ke-Fei wu Xue-bing wu Yu-Zhong wu Xiao-Zheng Xing ling-Zhe Xu Xin-Qi Xu Yan Xu Tai-Sheng Yan De-Hua Yang hai-Feng Yang Hui-Qin Yang Ming Yang Zheng-Qiu Yao Yong Yu Hui Yuan hai-Bo Yuan hai-Long Yuan Wei-Min Yuan Chao Zhai En-Peng Zhang Hua-Wei Zhang Jian-Nan Zhang li-Pin Zhang Wei Zhang Yong Zhang Yan-Xia Zhang Zheng-Chao Zhang Ming Zhao Fang Zhou Xu Zhou Jie Zhu Yong-Tian Zhu Si-Cheng Zou Fang Zuo National Astronomical Observatories Chinese Academy of Sciences Department of Astronomy Peking University Shanghai Astronomical Observatory Chinese Academy of Sciences Nanjing Institute of Astronomical Optics & Technology National Astronomical ObservatoriesChinese Academy of Sciences University of Science and Technology of China Department of Physics Applied Physics and AstronomyRensselaer Polytechnic InstituteTroyNY 12180USA Department of Physics and Astronomy Earlham CollegeRichmondIN 47374USA Universitt Heidelberg Zentrum für AstronomieLandessternwarteKnigstuhl 1269117 HeidelbergGermany Department of Astronomy Beijing Normal University Yunnan Observatories Chinese Academy of Sciences Purple Mountain Observatory Chinese Academy of Sciences

The Large sky Area Multi-Object Fiber Spectroscopic Telescope（LAMOST） general survey is a spectroscopic survey that will eventually cover approximately half of the celestial sphere and collect 10 million spectra of stars, galaxies and QSOs. Objects in both the pilot survey and the first year regular survey are included in the LAMOST DR1. The pilot survey started in October 2011 and ended in June 2012, and the data have been released to the public as the LAMOST Pilot Data Release in August 2012. The regular survey started in September 2012, and completed its first year of operation in June 2013. The LAMOST DR1 includes a total of 1202 plates containing 2 955 336 spectra, of which 1 790 879 spectra have observed signalto-noise ratio（SNR） ≥ 10. All data with SNR ≥ 2 are formally released as LAMOST DR1 under the LAMOST data policy. This data release contains a total of 2 204 696 spectra, of which 1 944 329 are stellar spectra, 12 082 are galaxy spectra and 5017 are quasars. The DR1 not only includes spectra, but also three stellar catalogs with measured parameters： late A,FGK-type stars with high quality spectra（1 061 918 entries）, A-type stars（100 073 entries）, and M-type stars（121 522 entries）. This paper introduces the survey design, the observational and instrumental limitations, data reduction and analysis, and some caveats. A description of the FITS structure of spectral files and parameter catalogs is also provided.

关键词： techniques: spectroscopic survey—data release—catalog

青藏高原青稞农家品种淀粉颗粒结合蛋白组成及GBSSI基因5′前导序列的多态性

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作物学报 2012年第7期38卷 1148-1154页

作者：王春萍高丽鹃潘志芬尼玛扎西唐亚伟曾兴权李俏邓光兵龙海余懋群中国科学院成都生物研究所四川成都610041 中国科学院研究生院北京100049 西藏农牧科学院/农业部藏区青稞生物学与遗传育种重点实验室西藏拉萨850032

利用1D-SDS-PAGE分离了261份青藏高原农家青稞的淀粉颗粒结合蛋白,旨在为青藏高原青稞淀粉品质改良和淀粉颗粒结合蛋白机制研究提供依据和基础信息。在分子量45～100kD区域共有21种多态性蛋白条带和78种组合带型,其中2、3、5、10、11为... 详细信息

利用1D-SDS-PAGE分离了261份青藏高原农家青稞的淀粉颗粒结合蛋白,旨在为青藏高原青稞淀粉品质改良和淀粉颗粒结合蛋白机制研究提供依据和基础信息。在分子量45～100kD区域共有21种多态性蛋白条带和78种组合带型,其中2、3、5、10、11为新条带。利用PCR技术克隆了236份农家青稞GBSSI基因5′前导序列,出现1000bp和800bp的多态性片段,且以前者为主,其频率为80.1%。在8份农家青稞及4份引进的低直链淀粉材料的GBSSI基因5′前导序列中共检测到32个多态性位点,包括9个InDels和23个SNPs。GBSSI基因5′前导序列中出现了特有的序列差异,如未出现600bp类型(约400bp的特异缺失),而该缺失被认为是低直连淀粉大麦形成的原因;材料yf127、yf70、011Z1396和09Z586出现了特异点突变。因此认为,青藏高原农家青稞品种的淀粉颗粒结合蛋白具有丰富的多态性和独特性。低直链淀粉青稞GBSSI基因序列的新特征表明可能存在新的低直链淀粉形成机制。

关键词：农家品种青稞淀粉颗粒结合蛋白 GBSSI基因

运用单细胞三重PCR对杜氏肌营养不良进行植入前遗传学诊断

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中南大学学报（医学版） 2007年第2期32卷 246-251页

作者：吴玥丽邬玲仟李艳萍刘冬娥曾桥朱海燕潘乾梁德生胡浩龙志高李娟戴和平夏昆夏家辉中南大学湘雅医院医学遗传学国家重点实验室长沙410078

目的:采用三重PCR技术检测缺失型杜氏肌营养不良(Duchenne muscular dystrophy,DMD)基因部分外显子和性别鉴定位点amelogenin基因,探讨该技术对DMD家系中致病基因携带者进行植入前遗传学诊断(preimplantation genetic diagnosis,PGD)的... 详细信息

目的:采用三重PCR技术检测缺失型杜氏肌营养不良(Duchenne muscular dystrophy,DMD)基因部分外显子和性别鉴定位点amelogenin基因,探讨该技术对DMD家系中致病基因携带者进行植入前遗传学诊断(preimplantation genetic diagnosis,PGD)的可行性。方法:显微操作取正常男性、正常女性和DMD基因8号、47号外显子缺失型DMD患者单个淋巴细胞及无DMD家族史夫妻行体外授精-胚胎移植(in vitro fertilization pre-embryo transfer,IVF-ET)术后废弃的单个卵裂球细胞,采用三重PCR技术扩增DMD基因8号、47号外显子和amelogenin基因。结果:64枚正常人单个淋巴细胞的DMD基因8号、47号外显子和amelogenin基因扩增阳性率分别为93.8%,93.8%和95.3%,假阳性率为2.8%;48枚8号外显子缺失型患者单个淋巴细胞的DMD基因47号外显子和amelogenin基因扩增阳性率均为95.8%,假阳性率为3.3%;48枚47号外显子缺失型患者单个淋巴细胞的DMD基因8号外显子和amelogenin基因扩增阳性率均为95.8%,假阳性率为0;40枚单卵裂球细胞DMD基因8号、47号外显子和amelogenin基因扩增阳性率分别为82.5%,80.0%和77.5%,假阳性率为0。结论:本研究所建立的单细胞三重PCR技术具有较高的扩增阳性率和特异性,有望在缺失型DMD家系中进行PGD的临床应用。

关键词：单细胞PCR 杜氏肌营养不良植入前遗传学诊断 DMD基因 amelogenin基因

Data release of the LAMOST pilot survey

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Research in Astronomy and Astrophysics 2012年第9期12卷 1243-1246页

作者： A-li Luo Hao-Tong Zhang Yong-Heng Zhao Gang Zhao Xiang-Qun Cui Guo-Ping li Yao-Quan Chu Jian-Rong Shi Gang Wang Jian-Nan Zhang Zhong-Rui Bai Xiao-Yan Chen Feng-Fei Wang Yan-Xin Guo Jian-Jun Chen bing Du Xiao Kong Ya-juan Lei Yin-Bi li Yi-Han Song Yue wu Yan-Xia Zhang Xin-lin Zhou Fang Zuo Peng Du lin He Wen Hou Yi-qiao Dong Jian li Guang-Wei li Shuang li Jing Song Yuan Tian Meng-Xin Wang Yong-Hui Hou Zhi-Ying Huo Hong-Zhuan Hu Ning-Sheng Hu Zhong-Wen Hu Lei Jia Fang-Hua Jiang Xiang Jiang Zi-Bo Jiang Ge Jin Ai-Hua li Qi li Yin-Dun Mao Zheng-Hong tang Qing-Sheng Tao liang-Ping Tu Da-Qing Wang Dan Wang Jian-Ping Wang Lei Wang Shou-Guan Wang Shu-Qing Wang Ya-Nan Wang You Wang Yue-Fei Wang Ming-Zhi Wei Xiang-Xiang Xue Xiao-Zheng Xing ling-Zhe Xu Xin-Qi Xu Yan Xu De-Hua Yang Shi-hai Yang Zheng-Qiu Yao Yong Yu Hui Yuan Chao Zhai En-Peng Zhang Jing Zhang li-Ping Zhang WeiZhang Yong Zhang Zhen-Chao Zhang Ming Zhao Fang Zhou Yong-Tian Zhu Jie Zhu Si-Cheng Zou National Astronomical Observatories Chinese Academy of Sciences Beijing 100012 China lal @ lamost o rg Nanjing Institute of Astronomical Optics and Technology National Astronomical ObservatoriesChinese Academy of Sciences Nanjing 210042 China University of Science and Technologyof China Hefei 230026 China Shanghai Astronomical Observatory Chinese Academy of Sciences Shanghai 200030 China Institute of Architecture Design and Research Chinese Academy of Sciences Beijing 100190China

This paper describes the data release of the LAMOST pilot survey, which includes data reduction, calibration, spectral analysis, data products and data access. The accuracy of the released data and the information about the FITS headers of spectra are also introduced. The released data set includes 319 000 spectra and a catalog of these objects.

关键词： techniques: spectroscopic survey — data reduction — data release

Consensus statement on layout and delivery of automatic external defibrillator in China

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Journal of hainan Medical University 2020年第15期26卷 18-23页

作者： Yu Cao Song Chen Yan-Fen Chai Xiao-Hui Chen Yu-Guo Chen Shao-Wen Cheng Wen-Wei Cheng Bang-Han Ding Yang Deng Jie Fu Bang-Jiang Fang Mai-Ying Fan li Gui Ping Gong Wei Guo Shu-Bin Guo liang Huang Ji-Yuan Han Zhong Ji Xian-Fei Ji Xin-Cai Ji Hong-Xu Jin Xin-Jun Jiang Wang-Xiang Jiang Jia-liang liu Xiao-Ran liu Zhi liu Chuan-Zhu Lv Feng Lu tan-Shi li Xin li Yong li Shang-Lun li Shuang-Ming li Xiao-Gang li Bao-Jun li Pei-wu li Chun-Sheng li Zhi-Jun li Chang-Luo li Xiang-Min li Yin-Ping li Zong-Jun Lu Zu-Xun Lu Zhong-Qiu Lu Zhi-Qian Luo Xiao-Xing liao Jian-Bo Lei Tao Ma Yu Ma Yue-Feng Ma Qing-Bian Ma lin-Hao Ma Jun-Qi Ma Shi-Nan Nie Jie-Miao Ou-Yang Peng Peng qiao Pei Shu-Ming Pan Guo-Zhong Qing li-Jie Qin wu-Ying qiao Fei Shao Wei Song Xing-Yue Song Zhen-Ju Song Rong-Ju Sun De-Ya Shang Du-juan Sha Gui-Lan Tao Guo-Gang Tian Ying-Ping Tian Jian-Guang Tian Chao-Yang Tong Zi-Ren tang Meng-Xiong tang Guo-Ping wu Zhi Wan Tao Wang Xin Wang Peng Wang Zhong Wang Tong Wang Ri-Xing Wang Yi-Xin Wang Xiao-Dan Wang ling wu Wei Wei Hua Xiang Feng Xu Jun Xu Jie Xu Miao-Rong Xie Shuo-Gui Xu Tie Xu Feng Yu Wen Yi li-Shan Yang Shi-Jiao Yan Jin-Jian Yao Shou-Chun Yan Xue-Zhong Yu Xian-Zhi Ye Xian-liang Yan Fu-bing Zhou Rong-Bin Zhou Ming Zhou Qiang Zhou Jin Zhou Ping Zhou Chang-Ju Zhu Hua-Dong Zhu Ji-Hong Zhu Hong Zhang Mao Zhang Hua Zhang Na Zhang Guo-Qiang Zhang Guo-Xiu Zhang Jin-Song Zhang Wen-wu Zhang Wen-Zhong Zhang Jian-Feng Zhang Yi-Min Zhu Jun zeng Yuan Zheng Zhi-Jie Zheng Shen Zhao Yan Zhao Min Zhao Bin Zhao Xiao-Dong Zhao Xiao-Jing Zhao Hong-Ke zeng Sheng-Qiang Zou The Chinese Society of Emergency Medicine Research Unit of Island Emergency Medicine Chinese Academy of Medical SciencesHainan Medical University Key Laboratory of Emergency and Trauma of Ministry of Education Hainan Medical UniversityHaikouHainanChina Emergency and Trauma College Hainan Medical UniversityHaikouHainanChina Department of Emergency Hainan Clinical Research Center for Acute and Critical DiseasesThe Second Affiliated Hospital of Hainan Medical UniversityHaikouHainanChina Key Laboratory of hainan Trauma and Disaster Rescue Key Laboratory of Trauma of hainan Medical University

*** Sudden cardiac death(SCD)refers to sudden death due to a variety of cardiac *** is manifested as a sudden loss of consciousness,cardiac arrest,and respiratory arrest and generally shows early symptoms that are atypical and not easily detected[1].According to a recent study,nearly 544000 patients suffer from SCD every year in China[2].

关键词： cardiac death respiratory

CEPC Technical Design Report

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Radiation Detection Technology and Methods 2024年第1期8卷 I0003-I0016,1-1091页

作者： Waleed Abdallah Tiago Carlos Adorno de Freitas Konstantin Afanaciev Shakeel Ahmad Ijaz Ahmed Xiaocong Ai Abid Aleem Wolfgang Altmannshofer Fabio Alves Weiming An Rui An Daniele Paolo Anderle Stefan Antusch Yasuo Arai Andrej Arbuzov Abdesslam Arhrib Mustafa Ashry Sha Bai Yu Bai Yang Bai Vipul Bairathi Csaba Balazs Philip Bambade Yong Ban Tripamo Bandyopadhyay Shou-Shan Bao Desmond P.Barber Ayse Bat Varvara Batozskaya Subash Chandra Behera Alexander Belyaev Michele Bertucci Xiao-Jun Bi Yuanjie Bi Tianjian Bian Fabrizio Bianchi Thomas Biekotter Michela Biglietti Shalva Bilanishvili Deng binglin Denis Bodrov Anton Bogomyagkov Serge Bondarenko Stewart Boogert Maarten Boonekamp Marcello Borri Angelo Bosotti Vincent Boudry Mohammed Boukidi Igor Boyko Ivanka Bozovic Giuseppe Bozzi Jean-Claude Brient Anastasiia Budzinskaya Masroor Bukhari Vladimir Bytev Giacomo Cacciapaglia Hua Cai Wenyong Cai wujun Cai Yijian Cai Yizhou Cai Yuchen Cai haiying Cai Huacheng Cai Lorenzo Calibbi Junsong Cang Guofu Cao Jianshe Cao Antoine Chance Xuejun Chang Yue Chang Zhe Chang Xinyuan Chang Wei Chao Auttakit Chatrabhuti Yimin Che Yuzhi Che Bin Chen Danping Chen Fuqing Chen Fusan Chen Gang Chen Guoming Chen Hua-Xing Chen Huirun Chen Jinhui Chen Ji-Yuan Chen Kai Chen Mali Chen Mingjun Chen Mingshui Chen Ning Chen Shanhong Chen Shanzhen Chen Shao-Long Chen Shaomin Chen Shiqiang Chen Tianlu Chen Wei Chen Xiang Chen Xiaoyu Chen Xin Chen Xun Chen Xurong Chen Ye Chen Ying Chen Yukai Chen Zelin Chen Zilin Chen Gang Chen Boping Chen Chunhui Chen Hok Chuen Cheng Huajie Cheng Shan Cheng Tongguang Cheng Yunlong Chi Pietro Chimenti Wen Han Chiu Guk Cho Ming-Chung Chu Xiaotong Chu Ziliang Chu Guglielmo Coloretti Andreas Crivellin Hanhua Cui Xiaohao Cui Zhaoyuan Cui Brunella D'Anzi ling-Yun Dai Xinchen Dai Xuwen Dai Antonio De Maria Nicola De Filippis Christophe De La Taille Francesca De Mori Chiara De Sio Elisa Del Core Shuangxue Deng Wei-Tian Deng Zhi Deng Ziyan Deng Bhupal Dev tang Dewen Biagio Di Micco Ran Ding Siqin Dingl Yadong Ding haiyi Dong Jianin AGH University of Science and Technology Faculty of Physics and Applied Computer ScienceKrakow Anhui University HefeiAnhui Applied Physics Department Federal Urdu University of ArtsScience and TechnologyIslamabad Banaras Hindu University Institute of ScienceVaranasi Bandirma Onyedi Eylul University Bandirma Beihang University Beijing Beijing Computational Science Research Center Beijing Beijing Conveyi LTD Beijing Beijing Glass Research Institute Co. LtdBeijing Beijing Institute of Technology Beijing Beijing Normal University Beijing Brown University ProvidenceRI Budker Institute of Nuclear Physics Novosibirsk Cadi Ayyad University Laboratory of Fundamental and Applied PhysicsPolydisciplinary FacultyMarrakech Cairo University Giza Center for Theory and Computation National Tsing Hua UniversityHsinchu Central China Normal University WuhanHubei Central South University ChangshaHunan Centro de Fisica Teorica de Particulas Universidade Tecnica de LisboaLisboa Chengdu KaitengSifang Digital Radio&TV Equipment Co. LtdChengduSichuan China academy of engineering physics MianyangSichuan China building materials academy Beijing China Center of Advanced Science and Technology Beijing China Institute of Atomic Energy Beijing China Jiliang University HangzhouZhejiang China Nuclear Instrument CO. LTDBeijing China University of Geosciences Beijing China University of Geosciences WuhanHubei China University of Mining and Technology XuzhouJiangsu China West Normal University NanchongSichuan Chongqing University Department of PhysicsChongqing Chulalongkorn University Bangkok City University of Hong Kong Department of PhysicsHong Kong Cockcroft Institute Daresbury Cornell University IthacaNY CPPM(AMU/IPhU&CNRS/INP) Marseille Dalian Minzu University DalianLiaoning Dalian University of Technology Department of PhysicsDalian Deutsches Elektronen-Synchrotron DESY Hamburg Dzhelepov Laboratory of Nuclear Problems of Joint Institute for Nuclear Research(DLNP JINR) Dubna East China University Of Science And Technol

The Circular Electron Positron Collider(CEPC)is a large scientific project initiated and hosted by China,fostered through extensive collaboration with international *** complex comprises four accelerators:a 30 GeV linac,a 1.1 GeV Damping Ring,a Booster capable of achieving energies up to 180 GeV,and a Collider operating at varying energy modes(Z,W,H,and tt).The linac and Damping Ring are situated on the surface,while the subterranean Booster and Collider are housed in a 100 km circumference underground tunnel,strategically accommodating future expansion with provisions for a potential Super Proton Proton Collider(SPPC).The CEPC primarily serves as a Higgs *** its baseline design with synchrotron radiation(SR)power of 30 MW per beam,it can achieve a luminosity of 5×10^(34)cm^(-2)s^(-1)per interaction point(IP),resulting in an integrated luminosity of 13 ab^(-1)for two IPs over a decade,producing 2.6 million Higgs *** the SR power to 50 MW per beam expands the CEPC's capability to generate 4.3 million Higgs bosons,facilitating precise measurements of Higgs coupling at sub-percent levels,exceeding the precision expected from the HL-LHC by an order of *** Technical Design Report(TDR)follows the Preliminary Conceptual Design Report(Pre-CDR,2015)and the Conceptual Design Report(CDR,2018),comprehensively detailing the machine's layout,performance metrics,physical design and analysis,technical systems design,R&D and prototyping efforts,and associated civil engineering ***,it includes a cost estimate and a preliminary construction timeline,establishing a framework for forthcoming engineering design phase and site selection *** is anticipated to begin around 2027-2028,pending government approval,with an estimated duration of 8 *** commencement of experiments and data collection could potentially be initiated in the mid-2030s.

关键词： initiated exceeding precise

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江西省豆类产业发展现状和对策分析

江西农业学报 2023年第4期35卷 33-38页

作者：柳开楼张景云黄庆海王志美吴艳张大文袁丽娟王春娥周会汶陈红兵王水兴曾招圣黄天宝朱德彬江西省红壤及种质资源研究所/农业农村部酸化土改良与利用重点实验室江西南昌331717 江西省农业科学院蔬菜花卉研究所江西南昌330200 江西省农业技术推广中心江西南昌330046 江西省农业科学院农产品质量安全与标准研究所江西南昌330200 九江学院江西九江332005 南昌大学江西南昌330038 永丰县农技推广中心江西永丰331500 萍乡市农业科学研究中心江西萍乡337000

江西省作为我国重要的鱼米之乡,除了生产稻米之外,也适宜种植大豆等豆类作物。为有序指导江西省的豆类产业发展,分别从豆类资源、种植模式、品种和豆制品等方面对全省豆类产业的发展现状进行概述,系统分析了目前存在的主要问题并进行了... 详细信息

江西省作为我国重要的鱼米之乡,除了生产稻米之外,也适宜种植大豆等豆类作物。为有序指导江西省的豆类产业发展,分别从豆类资源、种植模式、品种和豆制品等方面对全省豆类产业的发展现状进行概述,系统分析了目前存在的主要问题并进行了因素分析。在此基础上,提出了加大政府引导和扶持力度、改善旱地基础设施、多途径扩大大豆面积和调整结构拓展大豆种植等对策,以期促进江西省豆类产业的振兴。

关键词：大豆豌豆产业现状问题分析发展对策