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Portable Analyzer for Rapid Analysis of Total Protein, Fat and Lactose Contents in Raw Milk Measured by Non-dispersive Short-wave Near-infrared Spectrometry

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Chemical Research in Chinese Universities 2013年第1期29卷 15-19页

作者： feng xu-dong su rui xu nan wang xing-hua yu ai-min zhang han-qi cao yan-bo College of Chemistry Jilin University Changchun 130012 P. R. China

A novel portable analyzer for raw milk quality control during the material purchase at dairy plants was developed, by which the percentages（mass fraction） of main components including total protein, fat, and lactose of an unhomogenized milk sample could be determinated in 1 min with the help of non-dispersive short-wave near-infrared （NDSWNIR） spectrometry in a wavelength range from 600 nm to 1100 nm and multivariate calibration. The analyzer was designed with a single-beam optical system, which comprised a temperature control module, a multi-channel narrow-band light source（16 wavelengths）, a glass absorption cell with 15 mm sample thickness, a silicon photodiode detector, several compound lenses and a recorder module. A total of 80 raw milk samples were collected at a dairy farm twice a month for 4 months. The samples were scanned with a common UV-Vis-NIR spectrometer and analyzed according to China GB standard methods. The uninformative variables elimination（UVE） method was carried out on the spectrum data and the percentages of main components of all the samples to choose the peak emitting wavelength of each channel of the light source. Another 90 raw milk samples were collected from the same dairy farm thrice a month for 3 months. The samples were analyzed according to China GB standard methods and with the proposed analyzer. The percentages of the main components and the NDSWNIR absorption data of the samples were used for the construction and validation of the multivariate calibration model with partial least squares（PLS） method. The root-mean-square errors of prediction（RMSEP） of total protein, fat and lactose were 0.201, 0.172 and 0.247 and the coefficients of correlation（R） were 0.932, 0.981 and 0.933, respectively.

关键词： Portable analyzer Raw milk Non-dispersive short-wave near-infrared(NDSWNIR) spectrometry Multiva-riate calibration

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Ionic Liquid-based Microwave-assisted Liquid-liquid Microextraction and High Performance Liquid Chromatography Determination of sulfonamides from Animal Oils

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Chemical Research in Chinese Universities 2013年第4期29卷 647-652页

作者： feng xu-dong LIANG Fang-hui su rui WU Li-jie LI xue-yuan wang xing-hua zhang han-qi yu ai-min College of Chemistry Jilin University Changehun 130012 P. R. China Department of Pharmacy Changchun Medical College Changchun 130117 P. R. China

The authors performed ionic liquid-based microwave-assisted liquid-liquid microextraction（IL-based MALLME） coupled with high performance liquid chromatographic separation for the determination of 6 sulfonamides （SAs） from animal oils. The target analytes were extracted from animal oil samples with sodium hydroxide solution containing 1-butyl-3-methylimidazolium tetrafluoroborateand as the extraction solvent under microwave irradiation. The experimental parameters of the IL-based MALLME, including types of ILs, volume of IL, amount of ion-pairing agent（NHaPF6）, pH value of sample solution, and extraction temperature and time were evaluated. The limits of detection and quantification obtained were in a range of 0.4--0.5μg/kg and a range of 1.2--1.8μg/kg, respectively. The accuracy of the method was evaluated by analyzing five spiked animal oil samples at two fortified levels（5 and 50μg/kg）, and the recoveries of SAs varied from 81.4% to 114.5% with relative standard deviations ranging from 0.8% to 9.0%.

关键词： Ionic liquid-based microwave-assisted liquid-liquid microextraction(IL-based MALLME) High perfor-mance liquid chromatography(HPLC) sulfonamide Animal oil

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Analysis of Peanut Oil Adulterated with Other Edible Oils by Spectrophotometry

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Chemical Research in Chinese Universities 2012年第1期28卷 14-18页

作者： su rui1, wang xing-hua1, ZHAO Tian-qi1, yu Wen-zhi1, feng xu-dong1, zhang han-qi1 and yu ai-min1,2 1. College of Chemistry, Jilin University, Changchun 130012, P. R. China 2. Changchun Jilin University Little Swan Instrument Co., Ltd., Changchun 130012, P. R. China College of Chemistry Jilin University Changchun 130012

Since peanut oil（PO） is more expensive than other seed oils, some PO is adulterated with other cheap seed oils, such as soybean oil, palm olein, cottonseed oil, corn oil and rapeseed oil. The conventional method for deter mining whether PO was adulterated is to detect the freezing point of oils. The proposed method for the determination of adulterants in PO was based on monitoring the change of absorbance when the sample was refrigerated. A special spectrophotometer was developed. A total of 10 kinds of POs from different suppliers were chosen and adulterated with other seed oils at the volume fraction levels ranging from 5% to 30%. A total of 150 samples were analyzed by the proposed method and the results were satisfactory.

关键词： Peanut oil Adulteration Spectrophotometry Direct analysis

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Feasibility of controlling hepatitis E in Jiangsu Province, China: a modelling study

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Infectious Diseases of Poverty 2021年第3期10卷 116-117页

作者： Meng yang Xiao-qing Cheng Ze-yu Zhao Pei-hua Li Jia rui Sheng-nan Lin Jing-Wen xu yuan-Zhao Zhu Yao wang xing-Chun Liu Li Luo Bin Deng Chan Liu Jie-feng huang Tian-Long yang Zhuo-yang Li Wei-Kang Liu Wen-dong Liu Ben-hua Zhao yue He qi Yin Si-Ying Mao yan-hua su xue-feng zhang Tian-Mu Chen State Key Laboratory of Molecular Vacci no logy and Molecular Diagnostics School of Public HealthXiamen University4221-117 South Xiang'an RoadXiang'an DistrictXiamen City 361102Fujian ProvincePeople's Republic of China Jiangsu Center for Disease Control and Prevention Nanjing CityJiangsu ProvincePeople's Republic of China

Background:Hepatitis E,an acute zoonotic disease caused by the hepatitis E virus(HEV),has a relatively high burden in developing *** current research model on hepatitis E mainly uses experimental animal models(such as pigs,chickens,and rabbits)to explain the transmission of *** studies have developed a multi-host and multiroute transmission dynamic model(MHMRTDM)to explore the transmission feature of ***,this study aimed to explore its transmission and evaluate the effectiveness of intervention using the dataset of Jiangsu Province.

关键词： Hepatitis E Transmission dynamic model Meteorological factor Intervention Transmissibility

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The In-Flight Realtime Trigger and Localization Software of GECAM

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Research in Astronomy and Astrophysics 2024年第10期24卷 11-24页

作者： Xiao-yun Zhao Shao-Lin Xiong Xiang-yang Wen Xin-qiao Li Ce Cai Shuo Xiao qi Luo Wen-Xi Peng dong-Ya Guo Zheng-hua An Ke Gong Jin-yuan Liao yan-qiu zhang yue huang Lu Li xing Wen Fei zhang Jing Duan Chen-Wei wang dong-Li Shi Peng zhang qi-Bin Yi Chao-yang Li yan-Bing xu Xiao-hua Liang Ya-qing Liu Da-Li zhang Xi-Lei sun Fan zhang Gang Chen huan-yu wang Sheng yang Xiao-Jing Liu min Gao Mao-Shun Li Jin-Zhou wang xing Zhou Yi Zhao wang-Chen xue Chao Zheng Jia-Cong Liu xing-bo han Jin-Ling qi Jia huang Ke-Ke zhang Can Chen Xiong-Tao yang dong-Jie Hou yu-Sa wang rui qiao Xiang Ma Xiao-bo Li Ping wang Xin-Ying Song Li-ming Song Shi-Jie Zheng Bing Li Hong-Mei zhang yue Zhu Wei Chen Jian-Jian He Zhen zhang Jin Hou Hong-Jun wang yan-Chao Hao Xiang-yu wang Zong-yuan yang Zhi-Long Wen Zhi Chang yuan-yuan Du rui Gao Xiao-Fei Lan yan-Guo Li Gang Li xu-Fang Li Fang-Jun Lu Hong Lu Bin Meng feng Shi Hui wang Hui-Zhen wang yu-Peng xu Jia-Wei yang xue-Juan yang Shuang-nan zhang Chao-yue zhang Cheng-Mo zhang Zhi-Cheng Tang Cheng Cheng Key Laboratory of Particle Astrophysics Institute of High Energy PhysicsChinese Academy of SciencesBeijing 100049China University of Chinese Academy of Sciences Chinese Academy of SciencesBeijing 100049China School of Information Science and Technology Southwest Jiaotong UniversityChengdu 611756China Key Laboratory of Stellar and Interstellar Physics and Department of Physics Xiangtan UniversityXiangtan 411105China Physics and Space Science College China West Normal UniversityNanchong 637002China Department of Astronomy Beijing Normal UniversityBeijing 100875China Innovation Academy for Microsatellites of CAS Shanghai 201203China Changchun University of Science and Technology Changchun 130022China Chinese Academy of Sciences South America Center for Astronomy National Astronomical ObservatoriesCASBeijing 100101China

Realtime trigger and localization of bursts are the key functions of GECAM,an all-sky gamma-ray monitor launched on 2020 December *** developed a multifunctional trigger and localization software operating in the CPU of the GECAM Electronic *** onboard software has the following features:high trigger efficiency for real celestial bursts with a suppression of false triggers caused by charged particle bursts and background fluctuation,dedicated localization algorithm optimized for both short and long bursts,and low time latency of the trigger information which is downlinked through the Global Short Message Communication service of the global BeiDou navigation *** paper provides a detailed description of the design and development of the trigger and localization software system for *** covers the general design,workflow,the main functions,and the algorithms used in the *** paper also includes on-ground trigger tests using simulated gamma-ray bursts generated by a dedicated X-ray tube,as well as an overview of the performance for real celestial bursts during its in-orbit operation.

关键词： telescopes instrumentation:detectors methods:observational

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Frontiers in high entropy alloys and high entropy functional materials

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Rare Metals 2024年第10期43卷 4639-4776页

作者： Wen-Tao zhang xue-qian wang feng-qi zhang Xiao-Ya Cui Bing-Bing Fan Jia-ming Guo Zhi-min Guo rui huang Wen huang xu-bo Li Meng-Ru Li yan Ma Zhi-hua Shen Yong-Gang sun De-Zhuang wang Fei-yang wang Li-qiang wang nan wang Tian-Li wang Wei wang Xiao-yang wang Yi-han wang Fu-Jie yu yu-Zhen Yin Ling-Kun zhang Yi zhang Jian-yang zhang qi Zhao yu-Ping Zhao Xin-dong Zhu Yasir Sohail Ya-nan Chen Tao feng qi-Long Gao Hai-yan He Yong-Jiang huang Zeng-Bao Jiao hua Ji Yao Jiang qiang Li Xiao-ming Li Wei-Bing Liao huai-Jun Lin Hui Liu qi Liu qing-feng Liu Wei-Di Liu Xiong-Jun Liu yang Lu Yi-Ping Lu Wen Ma xue-Fei Miao Jie Pan qing wang Hong-Hui Wu yuan Wu Tao yang Wei-ming yang qian yu Jin-yu zhang Zhi-Gang Chen Liang Mao yang Ren Bao-Long Shen xun-Li wang Zhe Jia He Zhu Zhen-Duo Wu Si Lan School of Materials Science and Engineering Nanjing University of Science and TechnologyNanjing 210094China Jiangsu Key Laboratory for Advanced Metallic Materials School of Materials Science and EngineeringSoutheast UniversityNanjing 211189China Department of Physics City University of Hong KongHongKong 999077China School of Materials Science and Engineering Tianjin UniversityTianjin 300072China School of Physics and Microelectronics Zhengzhou UniversityZhengzhou 450001China Department of Mechanical Engineering Research Institute for Advanced ManufacturingThe Hong Kong Polytechnic UniversityHong Kong 100872China Center of Electron Microscopy and State Key Laboratory of Silicon Materials School of Materials Science and EngineeringZhejiang UniversityHangzhou 310027China Key Laboratory of Solidification Control and Digital Preparation Technology(Liaoning Province) School of Materials Science and EngineeringDalian University of TechnologyDalian 116024China Institute of Advanced Wear&Corrosion Resistance and Functional Materials Jinan UniversityGuangzhou 510632China School of Mechanics and Civil Engineering China University of Mining and TechnologyXuzhou 221116China School of Physical Sciences Great Bay UniversityDongguan 523000China School of Materials Science and Engineering Harbin Institute of TechnologyHarbin 150001China State Key Laboratory of Materials-Oriented Chemical Engineering College of Chemical EngineeringNanjing Tech UniversityNanjing 211816China Beijing Advanced Innovation Center for Materials Genome Engineering Research Institute for Carbon NeutralityUniversity of Science and Technology BeijingBeijing 100083China Department of Mechanical Engineering The University of Hong KongHong Kong 999077China School of Computing Macquarie UniversitySydney 2113Australia Key Laboratory of Optoelectronic Devices and Systems of ministry of Education and Guangdong Province College of Physics and Optoelectronic EngineeringShenzhen UniversityShenzhen 518060China State Key Laborato

Owing to their exceptional properties,high-entropy alloys(HEAs)and high-entropy materials have emerged as promising research areas and shown diverse ***,the recent advances in the field are comprehensively reviewed,organized into five *** first section introduces the background of HEAs,covering their definition,significance,application prospects,basic properties,design principles,and *** subsequent section focuses on cutting-edge high-entropy structural materials,highlighting developments such as nanostructured alloys,grain boundary engineering,eutectic systems,cryogenic alloys,thin films,micro-nano-lattice structures,additive manufacturing,high entropy metallic glasses,nano-precipitate strengthened alloys,composition modulation,alloy fibers,and refractory *** the following section,the emphasis shifts to functional materials,exploring HEAs as catalysts,magneto-caloric materials,corrosion-resistant alloys,radiation-resistant alloys,hydrogen storage systems,and materials for ***,the review encompasses functional high-entropy materials outside the realm of alloys,including thermoelectric,quantum dots,nanooxide catalysts,energy storage materials,negative thermal expansion ceramics,and high-entropy wave absorption *** paper concludes with an outlook,discussing future directions and potential growth areas in the *** this comprehensive review,researchers,engineers,and scientists may gain valuable insights into the recent progress and opportunities for further exploration in the exciting domains of high-entropy alloys and functional materials.

关键词： High entropy alloys Cutting-edge structural materials Cutting-edgefunctional materials

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Association of Overlapped and Un-overlapped Comorbidities with COVID-19 Severity and Treatment Outcomes: A Retrospective Cohort Study from Nine Provinces in China

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Biomedical and Environmental Sciences 2020年第12期33卷 893-905页

作者： MA yan ZHU dong Shan CHEN Ren bo SHI nan nan LIU Si Hong FAN Yi Pin WU Gui Hui yanG Pu Ye Bai Jiang feng CHEN Hong CHEN Li Ying feng qiao GUO Tuan Mao HOU Yong HU Gui Fen HU Xiao Mei HU yun Hong huaNG Jin huaNG qiu hua huaNG Shao Zhen JI Liang JIN Hai Hao LEI Xiao LI Chun yan LI min qing LI Qun Tang LI Xian Yong LIU Hong De LIU Jin Ping LIU zhang MA yu Ting MAO Ya MO Liu Fen NA Hui wang Jing Wei SONG Fang Li suN Sheng wang dong Ting wang ming xuan wang Xiao yan wang Yin Zhen wang yu dong WU Wei WU Lan Ping XIAO yan hua XIE Hai Jun xu Hong ming xu Shou Fang xuE rui Xia yanG Chun yanG Kai Jun yuAN Sheng Li zhang Gong qi zhang Jin bo zhang Lin Song ZHAO Shu Sen ZHAO Wan Ying ZHENG Kai ZHOU Ying Chun ZHU Jun Teng ZHU Tian qing zhang hua min wang yan Ping wang Yong yan 无 Institute of Basic Research in Clinical Medicine China Academy of Chinese Medical SciencesBeijing 100700China Centre for Health Management and Policy Research School of Public HealthCheeloo College of MedicineShandong UniversityJinan 250012ShandongChina Institute of Information on Traditional Chinese Medicine China Academy of Chinese Medical SciencesBeijing 100700China Department of Tuberculosis The Public Health Clinical Center of ChengduChengdu 610066SichuanChina Department of Infectious Disease Shaanxi Infectious Disease HospitalXi'an 610113ShaanxiChina Department of Infectious Disease Yulin Chinese Medicine HospitalYulin 719000ShaanxiChina President's Office The First Hospital of QiqiharQiqihar 161005HeilongjiangChina Department of Traditional Chinese Medicine Shangluo Central HospitalShangluo 726000ShaanxiChina Department of Traditional Chinese Medicine The People's Hospital of QitaiheQitaihe 154603HeilongjiangChina Department of Scientific Research Xianyang Central HospitalXianyang 712000ShaanxiChina Department of traditional Chinese medicine The First Affiliated Hospital of Anhui University of Traditional Chinese MedicineHefei 230012AnhuiChina Department of Infectious Disease Heping Hospital Affiliated to Changzhi Medical CollegeChangzhi 046000ShanxiChina Department of Traditional Chinese Medicine Langfang Hospital of Chinese MedicineLangfang 065000HeibeiChina Department of Traditional Chinese Medicine Xingtai Hospital of Chinese MedicineXingtai 054001HeibeiChina Department of Traditional Chinese Medicine The People's Hospital of Guangxi Zhuang Autonomous RegionNanning 168600GuangxiChina Department of Traditional Chinese Medicine The First People'sHospital of FangchenggangFangchenggang 538001GuangxiChina Department of Traditional Chinese Medicine Mianyang Hospital of Traditional Chinese MedicineMianyang 621000SichuanChina Department of Traditional Chinese Medicine Liuzhou People's HospitalLiuzhou 545006GansuChina Department of Traditional Chinese Medici

Objective Several COVID-19 patients have overlapping comorbidities. The independent role of each component contributing to the risk of COVID-19 is unknown, and how some non-cardiometabolic comorbidities affect the risk of COVID-19 remains *** A retrospective follow-up design was adopted. A total of 1,160 laboratory-confirmed patients were enrolled from nine provinces in China. Data on comorbidities were obtained from the patients’ medical records. Multivariable logistic regression models were used to estimate the odds ratio(OR) and 95% confidence interval(95% CI) of the associations between comorbidities(cardiometabolic or non-cardiometabolic diseases), clinical severity, and treatment outcomes of *** Overall, 158(13.6%) patients were diagnosed with severe illness and 32(2.7%) had unfavorable outcomes. Hypertension(2.87, 1.30–6.32), type 2 diabetes(T2 DM)(3.57, 2.32–5.49),cardiovascular disease(CVD)(3.78, 1.81–7.89), fatty liver disease(7.53, 1.96–28.96), hyperlipidemia(2.15, 1.26–3.67), other lung diseases(6.00, 3.01–11.96), and electrolyte imbalance(10.40, 3.00–26.10)were independently linked to increased odds of being severely ill. T2 DM(6.07, 2.89–12.75), CVD(8.47,6.03–11.89), and electrolyte imbalance(19.44, 11.47–32.96) were also strong predictors of unfavorable outcomes. Women with comorbidities were more likely to have severe disease on admission(5.46,3.25–9.19), while men with comorbidities were more likely to have unfavorable treatment outcomes(6.58, 1.46–29.64) within two *** Besides hypertension, diabetes, and CVD, fatty liver disease, hyperlipidemia, other lung diseases, and electrolyte imbalance were independent risk factors for COVID-19 severity and poor treatment outcome. Women with comorbidities were more likely to have severe disease, while men with comorbidities were more likely to have unfavorable treatment outcomes.

关键词： Comorbidities COVID-19 Severity Gender Age Treatment outcome

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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

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Paired quasi-periodic pulsations of hard X-ray emission in a solar flare

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Science China(Physics,Mechanics & Astronomy) 2023年第5期66卷 195-206页

作者： Hai-Sheng Zhao dong Li Shao-Lin Xiong yan-qiu zhang yang su Wei Chen Yi Zhao Xiao-bo Li Jia-Cong Liu Wen-Xi Peng rui qiao Xin-qiao Li Xiang-yang Wen Li-ming Song Shi-Jie Zheng Xin-Ying Song Xiao-yun Zhao yue huang Shuang-nan zhang Shuo Xiao Ce Cai Zheng-hua An Can Chen Gang Chen Wei Chen yan-qi Du min Gao Ke Gong dong-Ya Guo Zhi-Wei Guo Jian-Jian He Bin Li Chao Li Chao-yang Li Gang Li Jian-Hui Li Lu Li qing-Xin Li yan-Guo Li Jing Liang Xiao-hua Liang Jin-yuan Liao Xiao-Jing Liu Ya-qing Liu qi Luo Xiang Ma Bin Meng Ge Ou dong-Li Shi Jing-yan Shi Gong-xing sun Xi-Lei sun You-Li Tuo Chen-Wei wang Hui wang Jin wang Jin-Zhou wang Ping wang Wen-Shuai wang Hong Wu Sheng-Lun Xie yan-Bing xu yu-Peng xu wang-Chen xue Sheng yang min Yao Jian-Ying Ye qi-Bin Yi Chao-yue zhang Da-Li zhang Fan zhang Fei zhang Hong-Mei zhang Kai zhang Peng zhang Xiao-Lu zhang Zhen zhang Guo-Ying Zhao Shi-Yi Zhao Chao Zheng xing Zhou yue Zhu Key Laboratory for Particle Astrophysics Institute of High Energy PhysicsChinese Academy of SciencesBeijing 100049China Purple Mountain Observatory Chinese Academy of SciencesNanjing 210023China University of Chinese Academy of Sciences Beijing 100049China Department of Astronomy Beijing Normal UniversityBeijing 100875China School of Computing and Artificial Intelligence Southwest Jiaotong UniversityChengdu 611756China Physics and Space Science College China West Normal UniversityNanchong 637002China Key Laboratory of Stellar and Interstellar Physics and Department of Physics Xiangtan UniversityXiangtan 411105China Institute of Astrophysics Central China Normal UniversityWuhan 430079China School of Physics Changchun University of Science and TechnologyChangchun 130022China College of Physics and Engineering Qufu Normal UniversityQufu 273165China College of Physics Sciences&Technology Hebei UniversityBaoding 071002China

We investigate high time resolution data obtained by the Gravitational wave high-energy Electromagnetic Counterpart All-sky Monitor(GECAM)during the flare event on 2022 April 21 at 01:52 *** subpeaks with durations of 4-6 s have been detected in the hard X-ray precursor phase,and the key feature is that they appear in pairs and seem like double-peak *** subpeaks are rarely observed in hard X-ray band and confirmed by the microwave obtained by Nobeyama Radio Polarimeters(NoRP)and Radio Solar Telescope Network(RSTN).While an exponential function can describe the continuum component of the time profile from the precursor to part of the impulsive *** periods of quasi-periodic pulsations(QPPs)are detected to be about 7.3 and 12.8 s for the precursor and impulsive phase,respectively,with at least 95%confidence *** paired QPPs are assumed to be double-peak QPPs and then the scenario of current loop coalescence model is found to be in good agreement with our *** precursor phase can be interpreted as the oscillating coalescence of two islands,while the impulsive phase can be interpreted as more islands to coalesce one by one to form larger islands.

关键词： solar flare QPPs loop coalescence circular-ribbon flare

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Inverted U-Shaped Associations between Glycemic Indices and Serum Uric Acid Levels in the General Chinese Population:Findings from the China Cardiometabolic Disease and Cancer Cohort(4C)Study

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Biomedical and Environmental Sciences 2021年第1期34卷 9-18页

作者： ZHU yuan yue ZHENG rui Zhi wang Gui Xia CHEN Li SHI Li Xin su qing xu min xu yu CHEN yu Hong yu xue feng yan Li wang Tian Ge ZHAO Zhi yun qiN Gui Jun WAN qin CHEN Gang GAO Zheng nan SHEN Fei Xia LUO Zuo Jie qiN Ying Fen HUO Ya nan LI qiang YE Zhen zhang Yin Fei LIU Chao wang You min WU Sheng Li yanG Tao DENG hua Cong ZHAO Jia Jun CHEN Lu Lu MU Yi ming TANG xu Lei HU Ru Ying wang Wei qing NING Guang LI Mian LU Jie Li BI yu Fang Department of Endocrine and Metabolic Diseases Shanghai Institute of Endocrine and Metabolic DiseasesRuijin HospitalShanghai Jiao Tong University School of MedicineShanghai 200025China Shanghai National Clinical Research Center for Metabolic Diseases Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR ChinaShanghai National Center for Translational MedicineRuijin Hospital.Shanghai Jiao Tong UniversitySchool of MedicineShanghai 200025China The First Hospital of Jilin University Changchun 130021JinlinChina qilu Hospital of Shandong University Jinan 250012ShandongChina Affiliated Hospital of Guiyang Medical College Guiyang 550004GuizhouChina Xinhua Hospital Affiliated to Shanghai Jiaotong University School of Medicine Shanghai 200092China Tongji Hospital.Tongji Medical College Huazhong University of Science and TechnologyWuhan 430030HubeiChina sun Yat-sen Memorial Hospital Sun Yat-sen UniversityGuangzhou 510120GuangdongChina The First Affiliated Hospital of Zhengzhou University Zhengzhou 450052HenanChina The Affiliated Hospital of Southwest Medical University Luzhou 646099SichuanChina Fujian Provincial Hospital Fujian Medical UniversityFuzhou 350001FujianChina Dalian Municipal Central Hospital Dalian 116003LiaoningChina The First Affiliated Hospital of Wenzhou Medical University Wenzhou 325000ZhejiangChina The First Affiliated Hospital of Guangxi Medical University Nanning 530021GuangxiChina Jiangxi Provincial People's Hospital Affiliated to nanchang University Nanchang 330006JiangxiChina The Second Affiliated Hospital of Harbin Medical University Harbin 150086HeilongjiangChina Zhejiang Provincial Center for Disease Control and Prevention Hangzhou 310051ZhejiangChina Central Hospital of Shanghai Jiading District Shanghai 201800China Jiangsu Province Hospital on Integration of Chinese and Western Medicine Nanjing 210028JiangsuChina The First Affiliated Hospital of Anhui Medical University Hefei 230022AnhuiChina Karamay Municipal

Objective The relationship between serum uric acid(suA)levels and glycemic indices,including plasma glucose(FPG),2-hour postload glucose(2 h-PG),and glycated hemoglobin(HbA1 c),remains *** aimed to explore the associations between glycemic indices and suA levels in the general Chinese *** The current study was a cross-sectional analysis using the first follow-up survey data from The China Cardiometabolic Disease and Cancer Cohort Study.A total of 105,922 community-dwelling adults aged≥40 years underwent the oral glucose tolerance test and uric acid *** nonlinear relationships between glycemic indices and suA levels were explored using generalized additive *** A total of 30,941 men and 62,361 women were eligible for the current *** additive models verified the inverted U-shaped association between glycemic indices and suA levels,but with different inflection points in men and *** thresholds for FPG,2 h-PG,and HbA1 c for men and women were 6.5/8.0 mmol/L,11.0/14.0 mmol/L,and 6.1/6.5,respectively(suA levels increased with increasing glycemic indices before the inflection points and then eventually decreased with further increases in the glycemic indices).Conclusion An inverted U-shaped association was observed between major glycemic indices and uric acid levels in both sexes,while the inflection points were reached earlier in men than in women.

关键词： Cross-sectional study Serum uric acid Glycemic index Glycemic status

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