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Improved material descriptors for bulk modulus in intermetallic compounds via machine learning

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Rare Metals 2023年第7期42卷 2396-2405页

作者： De-Xin Zhu Kun-Ming Pan yuan Wu Xiao-Ye zhou xiang-yue Li Yong-Peng Ren Sai-Ru Shi hua yu Shi-zhong wei Hong-hui Wu xu-sheng Yang National Joint Engineering Research Center for Abrasion Control and Molding of Metal Materials Henan Key Laboratory of High-Temperature Structural and Functional MaterialsHenan University of Science and TechnologyLuoyang471003China Longmen Laboratory Luoyang471003China State Key Laboratory for Advanced Metals and Materials University of Science and Technology BeijingBeijing100083China Guangdong Province Key Laboratory of Durability for Marine Civil Engineering School of Civil EngineeringShenzhen UniversityShenzhen518060China Department of Industrial and Systems Engineering The Hong Kong Polytechnic UniversityHong Kong999077China

Bulk modulus is an important mechanical property in the optimal design and selection of intermetallic *** this study,bulk modulus datasets of intermetallic compounds were collected,and the features affecting the bulk modulus of intermetallics were screened via feature *** features B_(cal),dB_(avg),and TIE(corresponding to calculated bulk modulus,mean bulk modulus,and third ionization energy,respectively)were found to be the dominant factors influencing bulk modulus and can be extended to other multi-component ***,we predicted the bulk modulus with an accuracy of 95%using surrogate machine learning models with the selected features,and these features were also demonstrated to be effective for high-entropy ***,symbolic regression provided an expression for the relationship between bulk modulus and the screened *** machine learning models provide a new approach for optimizing and predicting the bulk moduli of intermetallic compounds.

关键词： Bulk modulus Intermetallic compounds Machine learning Symbolic regression

Value of Kidney Disease Improving Global Outcomes Urine Output Criteria in Critically III Patients： A Secondary Analysis of a Multicenter Prospective Cohort Study

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Chinese Medical Journal 2016年第17期129卷 2050-2057页

作者： Jun-Ping Qin xiang-You yu Chuan-yun Qian Shu-sheng Li Tie-He Qin Er-Zhen Chen Jian-Dong Lin yu-Hang Ai Da-wei Wu De-Xin Liu Ren-hua Sun Zhen-Jie Hu xiang-yuan Cao Fa-chun zhou Zhen-Yang He Li-hua zhou You-zhong An Yan Kang Xiao-chun Ma Ming-Yan Zhao Li Jiang yuan xu Bin Du Medical Intensive Care Unit Peking Union Medical College Hospital Beijing 100730 China Department of Critical Care Medicine Beijing Tongren Hospital Capital Medical University Beijing 100730 China Department of Critical Care Medicine First Affiliated Hospital Xinjiang Medical University Urumqi Xinjiang 830054 China Department of Emergency Medicine and Medical Intensive Care Unit The First Affiliated Hospital of Kunming Medical University Kunming Yunnan 650032 China Department o1 Critical Care Medicine Tongji Hospital Tongji Medical College Huazhong University of Science and Technology Wuhan Hubei 430030 China Department of Critical Care Medicine Guangdong General Hospital Guangzhou Guangdong 510080 China Department of Emergency Medicine Ruijin Hospital Shanghai Jiao Tong University Shanghai 200025 China Department of Critical Care Medicine The First Affiliated Hospital of Fujian Medical University Fuzhou Fujian 350005 China Department of Critical Care Medicine Xiangya Hospital Central South University Changsha Hunan 410008 China Department of Critical Care Medicine Qilu Hospital Shandong University Jinan Shandong 250012 China Department of Emergency and Critical Care Medicine The Second Hospital of Jilin University Changchun Jilin 130041 China Department of Critical Care Medicine Zhejiang Provincial People's Hospital Hangzhou Zhejiang 310014 China Department of Critical Care Medicine Hebei Medical University Fourth Hospital Shijiazhuang Hebei 050011 China Department of Critical Care Medicine Affiliated Hospital of Ningxia Medical University Yinchuan Ningxia 750004 China Department of Emergency and Intensive Care Medicine The First Affiliated Hospital Chongqing Medical University Chongqing 400016 China Department of Critical Care Medicine Hainan Provincial People's Hospital Haikou Hainan 570311 China Department of Critical Care Medicine The Affiliated Hospital of Inner Mongolia Medical College Hohhot Inner Mongolia 010050 China Department of C

Background： Urine output （UO） is an essential criterion of the Kidney Disease Improving Global Outcomes （KD1GO） definition and classification system tbr acute kidney injury （AKI）, of which the diagnostic value has not been extensively studied. We aimed to determine whether AKI based on KDIGO UO criteria （KDtGOLro） could improve the diagnostic and prognostic accuracy, compared with KDIGO serum creatinine criteria （KDIGOscr）.Methods： We conducted a secondary analysis of the database of a previous study conducted by China Critical Care Clinical Trial Group （CCCCTG）, which was a 2-month prospective cohort study （July 1,2009 to August 31,2009） involving 3063 patients in 22 tertiary Intensive Care Units in Mainland of China. AKI was diagnosed and classified separately based on KDIGOt,o and KDlGOsc,. Hospital mortality of patients with more severe AKI classification based on KDIGOvo was compared with other patients by univariate and multivariate regression analyses. Results： The prevalence of AKl increased from 52.4% based on KDIGOscr to 55.4% based on KD1GOsc~ combined with KDIGOuo. KDIGOv~~ also restllted in an upgrade of AKI classification in 7.3% of patients, representing those with more severe AK1 classification based on KDIGOvo. Compared with non-AKI patients or those with maximum AKI classification by KDIGOscr, those with maximum AKI classification by KDIGOuo had a significantly higher hospital mortality of 58.4% （odds ratio [OR]： 7.580, 95% confidence interval [CI]： 4.141-13.873, P 〈 0.001）. In a multivariate logistic regression analysis, AKI based on KDIGOuo （OR： 2.891, 95% CI： 1.964-4.254, P 〈 0.001）, but not based on KDIGOscr （OR： 1.322, 95% CI： 0.902-1.939, P = 0.152）, was an independent risk factor for hospital mortality. Conclusion： UO was a criterion with additional value beyond creatinine criterion for AKI diagnosis and classification, which can help identify a group of patients with high risk of death.

关键词： Acute Kidney Injury Critically Ill Mortality Serum Creatinine Urine Output

Prevalence, risk factors, clinical course, and outcome of acute kidney injury in Chinese intensive care units： a prospective cohort study

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Chinese Medical Journal 2013年第23期126卷 4409-4416页

作者： WEN Ying JIANG Li xu yuan QIAN Chuan-yun LI Shu-sheng QIN Tie-he CHEN Er-zhen LIN Jian-dong AI yu- hang WU Da-wei WANG yu-shan SUN Ren-hua HU Zhen-jie CAO xiang-yuan zhou Fa-chun HE Zhen-yang zhou Li-hua AN You-zhong KANG Yan MA Xiao-chun yu xiang-you ZHAO Ming-yan XI Xiu-ming DU Bin Department of Critical Care Medicine Fuxing Hospital Capital Medical University Beijing 100038 China Department of Critical Care Medicine Beijing Tongren HospitalCapital Medical University Beijing 100730 China Department of Emergency Medicine First Affiliated Hospital of Kunming Medical College Kunming Yunnan 650032 China Department of Critical Care Medicine Tongji Hospital Tongji Medical College Huazhong University of Science & TechnologyWuhan Hubei 430030 China Department of Critical Care Medicine Guangdong General HospitalGuangzhou Guangdong 510080 China Department of Emergency Medicine Ruijin Hospital Shanghai Jiao Tong University Shanghai 200025 China Department of Critical Care Medicine First Affiliated Hospital ofFuiian Medical University Fuzhou Fujian 350005 China Department of Critical Care Medicine Xiangya Hospital CentralSouth University Changsha Hunan 410008 China Department of Critical Care Medicine Qilu Hospital Shandong University Jinan Shandong 250012 China Department of Emergency and Critical Care Medicine The Second Hospital of Jilin University Changchun Jilin 130041 China Department of Critical Care Medicine Zhejiang Provincial People's Hospital Hangzhou Zhejiang 310014 China Department of Critical Care Medicine Hebei Medical University Fourth Hospital Shijiazhuang Hebei 050011 China Department of Critical Care Medicine Affiliated Hospital of Ningxia Medical University Yinchuan Ningxia 750004 China Department of Critical Care Medicine First Affiliated Hospital Chongqing Medical University Chongqing 400016 China Department of Critical Care Medicine Hainan Provincial People's Hospital Haikou Hainan 570311 China Department of Critical Care Medicine Affiliated Hospital of Inner Mongolia Medical College Huhhot Inner Mongolia 010050 China Department of Critical Care Medicine Peking University People's Hospital Beijing 100044 China Department of Critical Care Medicine West China Hospital Sichuan University Chengdu Sichuan 61004

Background Acute kidney injury （AKI） has been recognized as a major healthcare problem affecting millions of patients ***,epidemiologic data concerning AKI in China are still *** objectives of this study were to characterize AKI defined by RIFLE criteria,assess the association with hospital mortality,and evaluate the impact of AKI in the context of other risk *** This prospective multicenter observational study enrolled 3,063 consecutive patients from 1 July 2009 to 31 August 2009 in 22 ICUs across China's *** excluded patients who were admitted for less than 24 hours （n=1623）,younger than 18 years （n=127）,receiving chronic hemodialysis （n=29）,receiving renal transplantation （n=1） and unknown reasons （n=28）.There were 1255 patients in the final *** was diagnosed and classified according to RIFLE *** There were 396 patients （31.6％） who had AKI,with RIFLE maximum class R,I,and F in 126 （10.0％）,91 （7.3％）,and 179 （14.3％） patients,*** function deteriorated in 206 patients （16.4％）.In comparison with non AKI patients,patients in the risk class on ICU admission were more likely to progress to the injury class （odds ratio （OR） 3.564,95％ confidence interval （CI） 1.706-7.443,P =0.001],while patients in the risk class （OR 5.215,95％ CI 2.798-9.719,P ＜0.001） and injury class （OR 13.316,95％ CI 7.507-23.622,P ＜0.001） had a significantly higher probability of deteriorating into failure *** adjusted hazard ratios for 90-day mortality were 1.884 for the risk group,3.401 for the injury group,and 5.306 for the failure *** The prevalence of AKI was high among critically ill patients in Chinese *** comparison with non-AKI patients,patients with RIFLE class R or class I on ICU admission were more susceptibility to progression to class I or class *** RIFLE criteria were robust and correlated well with clinical deterioration and mortality.

关键词： acute kidney injury intensive care units mortality prevalence risk factors

Consensus by Chinese Expert Panel on Chlamydia trachomatis-Resistant and Chlamydia trachomatis-Persistent Infection

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Chinese Medical Journal 2017年第23期130卷 2852-2856页

作者： Man-Li Qi yuan-Li Guo Qian-Qiu Wang xiang-sheng Chen Jian-De Han Xiao-Hong Su Wen-hui Lun Hao Cheng Jin-hua xu Hong-Qing Tian Li Che Zhi-yuan Ya Wen-Li Feng Juan Jiang Ping-yu zhou Xian-Biao Zo Hong-hui xu wei-Min Shi Jun Liu Lin Zhu Quan-zhong Liu Department of Dermatovenerology Tianjin Medical University General HospitalTianjin Neurological InstituteMinistry of Education and Tianjin City Key Laboratory of Post-neuroinjury Neuro-repair and Regeneration in Central Nervous SystemTianjin 300052China Department of Dermatovenerology Tianjin Union Medical CenterTianjin 300121China Department of Clinical Management National Center of STD ControlInstitute of DermatologyChinese Academy of Medical SciencesChina CDCNanjingJiangsu 210042China Department of Dermatovenerology The First Affiliated HospitalSun Yat-sen UniversityGuangzhouGuangdong 510080China Institute of Dermatology Chinese Academy of Medical Sciences and Peking Union Medical CollegeNanjingJiangsu 210042China Department of Dermatovenerology Beijing Ditan Hospital Capital Medical UniversityBeijing 100015China Department of Dermatology Sir Run Run Shaw HospitalSchool of MedicineZhejiang UniversityHangzhouZhejiang 310020China Department of Dermatology Huashan HospitalFudan UniversityShanghai 200040China Shandong Provincial Institute of Dermatology and Venereology Provincial Academy of Medical ScienceJinanShandong 250022China Department of Dermatovenerology The First Affiliated Hospital of Nanchang UniversityNanchangJiangxi 330006China Department of Infection Management and Disease Prevention China-Japan Friendship HospitalBeijing 100029China Department of Dermatovenerology The Second Hospital of Shanxi Medical UniversityTaiyuanShanxi 030001China STD Institute Shanghai Skin Disease HospitalShanghai 200050China Department of Dermatology The First Affiliated Hospital of PLA General HospitalBeijing 100048China Department of Dermatology The First Hospital of China Medical UniversityShenyangLiaoning 110001China Department of Dermatovenerology Shanghai General HospitalShanghai 200080China Department of Dermatovenerology The 4th People's Hospital of Qinghai ProvinceXiningQinghai 810014China Department of Dermatovenerology Shenzhen Hospital Southern Medical Universi

Chlamydia trachomatis （Ct） genital infection is the most common sexually transmitted disease （STD） in China and the US. The morbidity of Ct genital infection in China has increased from 32.48/100,000 in 2008 to 37.18/100,000 in 2015.[1] The major areas of Ct infections are concentrated in the Zhujiang Delta, Changjiang Delta, Minjiang Area, and West China. In these areas, the highest incidence of Ct infection reaches 615.99/100,000 citizens. In the US, there are 1,441,789 reported Ct, which include 627.2 females and 278.4 males per 100,000 population. It is now the most prevalent STD, with its rate increasing to 22% in males and 6% in females.[2] Ct genital infection can cause epididymitis, prostatitis, cervicitis, annexitis, infertility, and atopic pregnancy, which have been identified as the major public health problems.

关键词： Chlamydia trachomatis Persistent Infection Therapy Resistant

Chinese Expert Consensus on Clinical Application of Female Contraceptive Methods

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Reproductive and Developmental Medicine 2018年第4期2卷 208-223页

作者： Li-Nan Cheng Wen Di Yan Ding Guang-sheng Fan xiang-Ying Gu Min Hao Jing He Li-Na Hu Ke-Qin hua wei huang Li Jin Bei-hua Kong Jing-He Lang Jin-hua Leng Jian Li Cai-Xia Liu Guan-yuan Liu Lei Song Xiao-Ye Wang Shang-chun Wu Min xue hui-Xia Yang Qing Yang Shu-zhong Yao Zhen-yu Zhang Ying-Fang zhou Lan Zhu Shanghai Institute of Planned Parenthood Research ShanghaiChina Department of Obstetrics and Gynecology Renji HospitalShanghai Jiao Tong University School of MedicineShanghaiChina Department of Gynecology The First Affiliated Hospital of Xinjiang Medical UniversityÜrümqiChina Department of Obstetrics and Gynecology Peking Union Medical College HospitalChinese Academy of Medical SciencesBeijingChina Department of Family Planning Tianjin Medical University General HospitalTianjinChina Department of Obstetrics and Gynecology The Second Hospital of Shanxi Medical UniversityTaiyuanChina Department of Obstetrics Zhejiang University School of MedicineHangzhouChina Department of Obstetrics and Gynecology The Second Affiliated Hospital of Chongqing Medical UniversityChongqingChina Department of Gynecology Obstetrics and Gynecology Hospital of Fudan UniversityShanghaiChina Department of Obstetrics and Gynecology The West China Second University HospitalSichuan UniversityChengduChina Department of Obstetrics and Gynecology Qilu Hospital of Shandong UniversityJinanChina Department of Family Planning Beijing Obstetrics and Gynecology HospitalCapital Medical UniversityBeijingChina Department of Obstetrics and Gynecology Shengjing Hospital of China Medical UniversityShenyangChina Department of Obstetrics and Gynecology Beijing Chao-Yang HospitalCapital Medical UniversityBeijingChina Department of Obstetrics and Gynecology PLA General HospitalBeijingChina Department of Obstetrics and Gynecology Peking University Third HospitalBeijingChina Research Institute of National Health Commission of the People's Republic of China BeijingChina Department of Gynecology The Third Xiangya Hospital of Central South UniversityChangshaChina Department of Obstetrics and Gynecology Peking University First HospitalBeijingChina Department of Obstetrics and Gynecology The First Affiliated Hospital of Sun Yat-sen UniversityGuangzhouChina

Unintended pregnancy is a global issue, with approximately 85,000,000 women around the world having unintended pregnancy annually. The contents of clinical application of women’s contraceptive methods are very wide, involving multiple areas. This consensus deeply discusses the specific contraceptive needs at different statuses, combined with gynecological diseases, postabortion contraception, and postpartum family planning, ensuring the correct use of contraceptive methods under the corresponding status. The top priority of the consensus is the specific contraception consensus section for women combined with gynecological diseases because medical treatment effect as well as side effects should be weighed carefully. The consensus is to make high-efficiency and individual contraceptive strategy for different groups based on multidisciplinary(gynecology, obstetrics, and family planning) and multidimensional aspects, which can provide uniform guidance for medical and health organizations under the condition as relevant global guidance or consensus is still lacking.

关键词： Contraceptive Methods Gynecological Disease Postabortion Contraception Postpartum Family Planning Unintended Pregnancy

Prevalence, awareness, treatment, and control of hypertension in the non-dialysis chronic kidney disease patients

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Chinese Medical Journal 2013年第12期126卷 2276-2280页

作者： ZHENG Ying CAI Guang-yan CHEN xiang-mei FU Ping CHEN Jiang-hua DING Xiao-qiang yu xue-qing LIN Hong-li LIU Jian XIE Ru-juan WANG Li-ning NI Zhao-hui LIU Fu-you YIN Ai-ping XING Chang-ying WANG Li SHI wei LIU Jian-she HE Ya-ni DING Guo-hua LI Wen-ge WU Guang-li MIAO Li-ning CHEN Nan SU Zhen MEI Chang-lin ZHAO Jiu-yang GU Yong BAI yun-kai LUO hui-min LIN Shan CHEN Meng-hua GONG Li YANG Yi-bin YANG Xiao-ping LI Ying WAN Jian-xin WANG Nian-song LI Hai-ying XI chun-sheng HAO Li xu Yan FANG Jing-ai LIU Bi-cheng LI Rong-shan WANG Rong ZHANG Jing-hong WANG Jian-qin LOU Tan-qi SHAO Feng-min MEI Feng LIU Zhi-hong yuAN wei-jie SUN Shi-ren ZHANG Ling zhou chun-hua CHEN Qin-kai JIA Shun-lian GONG Zhi-feng GUAN Guang-ju XIA Tian zhong Liang-bao Department of Nephrology State key Laboratory of Kidney Disease Chinese PLA General Hospital Beijing 100853 China Nephrology Institute of the Chinese People's Liberation Army Chinese People's Liberation Army Key Laboratory of Nephrology Beijing 100853 China Department of Nephrology West China Hospital of Sichuan University Chengdu Sichuan 610041 China Department of Nephrology First Affiliated Hospital School of Medicine Zhejiang University Hangzhou Zhejiang 310003 China Department of Nephrology Zhongshan Hospital Fudan University Shanghai 200032 China Department of Nephrology First Affiiated Hospital of Sun Yat-sen University Guangzhou Guangdong 510080 China Department of Nephrology First Affiliated Hospital of Dalian Medical University Dalian Liaoning 116011 China Department of Nephrology First Affiliated Hospital of Xinjiang Medical University Urumqi Xinjiang 830054 China Department of Nephrology First Affiliated Hospital of Harbin Medical University Harbin Heilongjiang 150001 China Department of Nephrology First Afftiated Hospital of China Medical University Shenyang Liaoning 110001 China Department of Nephrology Renji Hospital School of Medicine Shanghai Jiao Tong University Shanghai 200025 China Department of Nephrology Second Xiangya Hospital Central South University Changsha Hunan 410000 China Department of Nephrology First Affiliated Hospital of Medical College Xi'an Jiaotong University Xi'an Shaanxi 710061 China Department of Nephrology First Affiliated Hospital of Nanjing Medical University (Jiangsu Province Hospital) Nanjing Jiangsu 210029 China Department of Nephrology Sichuan Provincial People's Hospital Chengdu Sichuan 610072 China Department of Nephrology Guangdong Provincial People's Hospital Guangzhou Guangdong 510030 China Department of Nephrology Affliated Xiehe Hospital Tongji Medical College Huazhong Science and Technology University Wuhan Hubei 430022 China Department of Nephrology Daping Hospital Third Military Medi

Background Data on the epidemiology of hypertension in Chinese non-dialysis chronic kidney disease （CKD） patients are *** aim of the present study was to investigate the prevalence,awareness,treatment,and control of hypertension in the non-dialysis CKD patients through a nationwide,multicenter study in *** The survey was performed in 61 tertiary hospitals in 31 provinces,municipalities,and autonomous regions in China （except Hong Kong,Macao,and Taiwan）.Trained physicians collected demographic and clinical data and measured blood pressure （BP） using a standardized *** was defned as systolic BP ≥140 mmHg and/or diastolic BP ≥90 mmHg,and/or use of antihypertensive *** 〈140/90 mmHg and 〈130/80 mmHg were used as the 2 thresholds of hypertension *** multivariate logistic regression with adjustment for sex and age,we analyzed the association between CKD stages and uncontrolled hypertension in non-dialysis CKD *** The analysis included 8927 non-dialysis CKD *** prevalence,awareness,and treatment of hypertension in non-dialysis CKD patients were 67.3%,85.8%,and 81.0%,*** hypertensive CKD patients,33.1% and 14.1% had controlled BP to 〈140/90 mmHg and 〈130/80 mmHg,*** successive CKD stages,the prevalence of hypertension in non-dialysis CKD patients increased,but the control of hypertension decreased （P〈0.001）.When the threshold of BP 〈130/80 mmHg was considered,the risk of uncontrolled hypertension in CKD 2,3a,3b,4,and 5 stages increased 1.3,1.4,1.4,2.5,and 4.0 times compared with CKD 1 stage,respectively （P〈0.05）.Using the threshold of 〈140/90 mmHg,the risk of uncontrolled hypertension increased in advanced stages （P〈0.05）.Conclusions The prevalence of hypertension Chinese non-dialysis CKD patients was high,and the hypertension control was *** successive CKD stages,the risk of uncontrolled hypertension increased.

关键词： non-dialysis chronic kidney disease chronic kidney disease stages hypertension epidemiology

A practical community-based response strategy to interrupt Ebola transmission in sierra Leone, 2014–2015

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Infectious Diseases of Poverty 2016年第1期5卷 670-679页

作者： zhong-Jie Li Wen-Xiao Tu Xiao-chun Wang Guo-Qing Shi Zun-Dong Yin Hai-Jun Su Tao Shen Da-Peng Zhang Jian-Dong Li Shan Lv chun-Li Cao Rui-Qian Xie Hong-zhou Lu Rong-Meng Jiang Zheng Cao Zhi-Jie An Lei-Lei Li Jie xu Yan-Wen Xiong wei Zang wei Zhang Hong-wei Zhang Wen-Sen Chen hua Ling Wen xu Jian Cai huan-Jin Luo xue-sheng Xing Can-Jun Zheng Qiang wei Xin-xu Li Mei Li Hai Jiang Li-Quan Deng Ming-Quan Chen xiang Huo Feng xu xue-hui Lai Xi-Chen Bai Long-Jie Ye Jian-Yi Yao Wen-Wu Yin Jiao-Jin Sun Lin Xiao Fu-Qiang Liu Xiao-Qiang Liu Hong-wei Fan Zeng-Qiang Kou Ji-Kun zhou Hao Zhang Da-Xin Ni Thomas TSamba Qun Li Hong-Jie yu yu Wang Xiao-Feng Liang Division of Infectious Disease Key Laboratory of Surveillance and Early-warning on Infectious DiseaseChinese Center for Disease Control and PreventionBeijingChina Public Health Emergency Center Chinese Center for Disease Control and PreventionBeijingChina National Center for AIDS/STD Control and Prevention Chinese Center for Disease Control and PreventionBeijingChina Chinese Field Epidemiology Training Program Chinese Center for Disease Control and PreventionBeijingChina National Immunization Program Chinese Center for Disease Control and PreventionBeijingChina Bureau of Disease Prevention and Control National Health and Family Planning Commission of the People’s Republic of ChinaBeijingChina National Institute for Viral Disease Control and Prevention Chinese Center for Disease Control and PreventionBeijingChina National Institute of Parasitic Disease Chinese Center for Disease Control and PreventionShanghaiChina Chinese Center for Health Education BeijingChina Department of Infectious Diseases Shanghai Public Health Clinical CenterShanghaiChina Beijing Ditan Hospital Capital Medical UniversityBeijingChina Health News BeijingChina National Institute for Communicable Disease Control and Prevention Chinese Center for Disease Control and PreventionBeijingChina Department of Training Chinese Center for Health EducationBeijingChina Center for Infectious Diseases Beijing Youan HospitalCapital Medical UniversityBeijingChina Infection Management The First Affiliated Hospital of Nanjing Medical UniversityNanjingChina Chongqing Municipal Center for Disease Control and Prevention ChongqingChina yunnan Provincial Center for Disease Control and Prevention KunmingChina Division of Infectious Disease Control and Prevention Zhejiang Provincial Center for Disease Control and PreventionHangzhouChina Guangdong Provincial Center for Disease Control and Prevention GuangzhouChina Division of Acute Infectious Disease Control and Prevention Hubei Provincial Center for Disease Control and PreventionW

Background:The Ebola virus disease spread rapidly in West Africa in 2014,leading to the loss of thousands of *** engagement was one of the key strategies to interrupt Ebola transmission,and practical community level measures needed to be explored in the field and tailored to the specific context of ***:First,community-level education on Ebola virus disease(EVD)prevention was launched for the community’s social mobilizers in six districts in Sierra Leone beginning in November ***,from January to May of 2015,in three pilot communities,local trained community members were organized to engage in implementation of EVD prevention and transmission interruption measures,by involving them in alert case report,contact tracing,and social *** epidemiological indicators of transmission interruption in three study communities were ***:A total of 6016 community social mobilizers from 185 wards were trained by holding 279 workshops in the six districts,and EVD message reached an estimated 631680 *** three pilot communities,72 EVD alert cases were reported,with 70.8%of them detected by trained local community members,and 14 EVD cases were finally *** tracing detected 64.3%of EVD *** median duration of community infectivity for the cases was 1 *** secondary attack rate was 4.2%,and no third generation of infection was *** health worker was infected,and no unsafe burial and noncompliance to EVD control measures were *** community-based measures were modeled to reduce 77 EVD cases,and the EVD-free goal was achieved four months earlier in study communities than whole country of Sierra ***: The community-based strategy of social mobilization and community engagement was effective in casedetection and reducing the extent of Ebola transmission in a country with weak health system. The successfullypractical experience to reduce the risk of Ebola transmission in the

关键词： Ebola virus disease Community engagement Health education Outbreak control

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

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