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| 1 | Insight-HXMT observations of the first binary neutron star merger GW170817显示文摘Finding the electromagnetic(EM) counterpart of binary compact star merger, especially the binary neutron star(BNS) merger,is critically important for gravitational wave(GW) astronomy, cosmology and fundamental physics. On Aug. 17, 2017,Advanced LIGO and Fermi/GBM independently triggered the first BNS merger, GW170817, and its high energy EM counterpart,GRB 170817 A, respectively, resulting in a global observation campaign covering gamma-ray, X-ray, UV, optical, IR, radio as well as neutrinos. The High Energy X-ray telescope(HE) onboard Insight-HXMT(Hard X-ray Modulation Telescope) is the unique high-energy gamma-ray telescope that monitored the entire GW localization area and especially the optical counterpart(SSS17 a/AT2017 gfo) with very large collection area(~1000 cm^2) and microsecond time resolution in 0.2-5 MeV. In addition,Insight-HXMT quickly implemented a Target of Opportunity(ToO) observation to scan the GW localization area for potential X-ray emission from the GW source. Although Insight-HXMT did not detect any significant high energy(0.2-5 MeV) radiation from GW170817, its observation helped to confirm the unexpected weak and soft nature of GRB 170817 A. Meanwhile,Insight-HXMT/HE provides one of the most stringent constraints(~10^(-7) to 10^(-6) erg/cm^2/s) for both GRB170817 A and any other possible precursor or extended emissions in 0.2-5 MeV, which help us to better understand the properties of EM radiation from this BNS merger. Therefore the observation of Insight-HXMT constitutes an important chapter in the full context of multi-wavelength and multi-messenger observation of this historical GW event. | TiPei Li ShaoLin Xiong ShuangNan Zhang FangJun Lu LiMing Song XueLei Cao Zhi Chang Gang Chen Li Chen TianXiang Chen Yong Chen YiBao Chen YuPeng Chen Wei Cui WeiWei Cui JingKang Deng YongWei Dong YuanYuan Du MinXue Fu GuanHua Gao He Gao Min Gao MingYu Ge YuDong Gu Ju Guan ChengCheng Guo DaWei Han Wei Hu Yue Huang Jia Huo ShuMei Jia LuHua Jiang WeiChun Jiang Jing Jin YongJie Jin Bing Li ChengKui Li Gang Li MaoShun Li Wei Li Xian Li XiaoBo Li XuFang Li YanGuo Li ZiJian Li ZhengWei Li XiaoHua Liang JinYuan Liao CongZhan Liu GuoQing Liu HongWei Liu ShaoZhen Liu XiaoJing Liu Yuan Liu YiNong Liu Bo Lu XueFeng Lu Tao Luo Xiang Ma Bin Meng Yi Nang JianYin Nie Ge OU JinLu Qu Na Sai Liang Sun Yin Tan Lian Tao WenHui Tao YouLi Tuo GuoFeng Wang HuanYu Wang Juan Wang WenShuai Wang YuSa Wang XiangYang Wen BoBing WU Mei Wu GuangCheng Xiao He Xu YuPeng Xu LinLi Yan JiaWei Yang Sheng Yang YanJi Yang AiMei Zhang ChunLei Zhang ChengMo Zhang Fan Zhang HongMei Zhang Juan Zhang Qiang Zhang Shu Zhang Tong Zhang Wei Zhang WanChang Zhang WenZhao Zhang Yi Zhang Yue Zhang YiFei Zhang YongJie Zhang Zhao Zhang ZiLiang Zhang HaiSheng Zhao JianLing Zhao XiaoFan Zhao ShiJie Zheng Yue Zhu YuXuan Zhu ChangLin Zou | 2018 | Science China(Physics,Mechanics & Astronomy)2018，61，3： | 12 |
| 2 | The enhanced X-ray Timing and Polarimetry mission—eXTP显示文摘In this paper we present the enhanced X-ray Timing and Polarimetry mission—eXTP. eXTP is a space science mission designed to study fundamental physics under extreme conditions of density, gravity and magnetism. The mission aims at determining the equation of state of matter at supra-nuclear density, measuring effects of QED, and understanding the dynamics of matter in strong-field gravity. In addition to investigating fundamental physics, eXTP will be a very powerful observatory for astrophysics that will provide observations of unprecedented quality on a variety of galactic and extragalactic objects. In particular, its wide field monitoring capabilities will be highly instrumental to detect the electro-magnetic counterparts of gravitational wave sources.The paper provides a detailed description of:(1) the technological and technical aspects, and the expected performance of the instruments of the scientific payload;(2) the elements and functions of the mission, from the spacecraft to the ground segment. | ShuangNan Zhang Andrea Santangelo Marco Feroci YuPeng Xu FangJun Lu Yong Chen Hua Feng Shu Zhang Sφren Brandt Margarita Hernanz Luca Baldini Enrico Bozzo Riccardo Campana Alessandra De Rosa YongWei Dong Yuri Evangelista Vladimir Karas Norbert Meidinger Aline Meuris Kirpal Nandra Teng Pan Giovanni Pareschi Piotr Orleanski QiuShi Huang Stephane Schanne Giorgia Sironi Daniele Spiga Jiri Svoboda Gianpiero Tagliaferri Christoph Tenzer Andrea Vacchi Silvia Zane Dave Walton ZhanShan Wang Berend Winter Xin Wu Jean J.M.in't Zand Mahdi Ahangarianabhari Giovanni Ambrosi Filippo Ambrosino Marco Barbera Stefano Basso Jörg Bayer Ronaldo Bellazzini Pierluigi Bellutti Bruna Bertucci Giuseppe Bertuccio Giacomo Borghi XueLei Cao Franck Cadoux Francesco Ceraudo TianXiang Chen Yu Peng Chen Jerome Chevenez Marta Civitani Wei Cui WeiWei Cui Thomas Dauser Ettore Del Monte Sergio Di Cosimo Sebastian Diebold Victor Doroshenko Michal Dovciak YuanYuan Du Lorenzo Ducci QingMei Fan Yannick Favre Fabio Fuschino JoséLuis Ga'lvez Min Gao MingYu Ge Olivier Gevin Marco Grassi QuanYing Gu YuDong Gu DaWei Han Bin Hong Wei Hu Long Ji ShuMei Jia WeiChun Jiang Thomas Kennedy Ingo Kreykenbohm Irfan Kuvvetli Claudio Labanti Luca Latronico Gang Li MaoShun Li Xian Li Wei Li ZhengWei Li Olivier Limousin HongWei Liu XiaoJing Liu Bo Lu Tao Luo Daniele Macera Piero Malcovati Adrian Martindale Malgorzata Michalska Bin Meng Massimo Minuti Alfredo Morbidini Fabio Muleri Stephane Paltani Emanuele Perinati Antonino Picciotto Claudio Piemonte JinLu Qu Alexandre Rachevski Irina Rashevskaya Jerome Rodriguez Thomas Schanz ZhengXiang Shen LiZhi Sheng JiangBo Song LiMing Song Carmelo Sgro Liang Sun Ying Tan Phil Uttley Bo Wang DianLong Wang GuoFeng Wang Juan Wang LangPing Wang YuSa Wang Anna L.Watts XiangYang Wen Jörn Wilms ShaoLin Xiong JiaWei Yang Sheng Yang YanJi Yang Nian Yu WenDa Zhang Gianluigi Zampa Nicola Zampa Andrzej A.Zdziarski AiMei Zhang ChengMo Zhang Fan Zhang Long Zhang Tong Zhang Yi Zhang XiaoLi Zhang ZiLiang Zhang BaoSheng Zhao ShiJie Zheng Yu Peng Zhou Nicola Zorzi J.Frans Zwart | 2019 | Science China(Physics,Mechanics & Astronomy)2019，62，2： | 11 |
| 3 | The Low Energy X-ray telescope (LE) onboard the Insight-HXMT astronomy satellite显示文摘The Low Energy X-ray telescope(LE) is one of the three main instruments of the Insight-Hard X-ray Modulation Telescope(Insight-HXMT). It is equipped with Swept Charge Device(SCD) sensor arrays with a total geometrical area of 384 cm^2 and an energy band from 0.7 to 13 ke V. In order to evaluate the particle induced X-ray background and the cosmic X-ray background simultaneously, LE adopts collimators to define four types of Field Of Views(FOVs), i.e., 1.6°×6°, 4°×6°, 50°-60°×2°-6 oand the blocked ones which block the X-ray by an aluminum cover. LE is constituted of three detector boxes(LEDs) and an electric control box(LEB) and achieves a good energy resolution of 140 e V@5.9 ke V, an excellent time resolution of 0.98 ms, as well as an extremely low pileup(<1%@18000 cts/s). Detailed performance tests and calibration on the ground have been performed,including energy-channel relation, energy response, detection efficiency and time response. | Yong Chen WeiWei Cui Wei Li Juan Wang YuPeng Xu FangJun Lul YuSa Wang TianXiang Chen DaWei Han Wei Hu Yi Zhang Jia Huo YanJi Yang MaoShun Li Bo Lu ZiLiang Zhang TiPei Li ShuangNan Zhang ShaoLin Xiong Shu Zhang RongFeng Xue XiaoFan Zhao Yue Zhu YuXuan Zhu HongWei Liu YiJung Yang Fan Zhang | 2020 | Science China(Physics,Mechanics & Astronomy)2020，63，4： | 8 |
| 4 | A Small-Scale Medication of Leflunomide as a Treatment of COVID-19 in an Open-Label Blank-Controlled Clinical Trial显示文摘We recently reported that inhibitors against human dihydroorotate dehydrogenase(DHODH)have broad-spectrum antiviral activities including their inhibitory efficacies on SARS-CoV-2 replication in infected cells.However,there are limited data from clinical studies to prove the application of DHODH inhibitors in Coronavirus disease 2019(COVID-19)patients.In the present study,we evaluated Leflunomide,an approved DHODH inhibitor widely used as a modest immune regulator to treat autoimmune diseases,in treating COVID-19 disease with a small-scale of patients.Cases of 10 laboratory-confirmed COVID-19 patients of moderate type with obvious opacity in the lung were included.Five of the patients were treated with Leflunomide,and another five were treated as blank controls without a placebo.All the patients accepted standard supportive treatment for COVID-19.The patients given Leflunomide had a shorter viral shedding time(median of5 days)than the controls(median of 11 days,P=0.046).The patients given Leflunomide also showed a significant reduction in C-reactive protein levels,indicating that immunopathological inflammation was well controlled.No obvious adverse effects were observed in Leflunomide-treated patients,and they all discharged from the hospital faster than controls.This preliminary study on a small-scale compassionate use of Leflunomide provides clues for further understanding of Leflunomide as a potential antiviral drug against COVID-19. | Ke Hu Mengmei Wang Yang Zhao Yunting Zhang Tao Wang Zhishui Zheng Xiaochen Li Shaolin Zeng Dong Zhao Honglin Li Ke Xu Ke Lan | 2020 | Virologica Sinica2020，35，6： | 7 |
| 5 | A survey of routing techniques for satellite networks显示文摘Satellite networks have many advantages over traditional terrestrial networks.However,it is very difficult to design a satellite network with excellent performance.The paper briefly summarizes some existing satellite network routing technologies from the perspective of both single-layer and multilayer satellite constellations,and focuses on the main ideas,characteristics,and existing problems of these routing technologies.For single-layer satellite networks,two routing strategies are discussed,virtual node strategy and virtual topology strategy.Moreover,considering the deficiency of existing multilayer satellite network routing,we discuss the topic invulnerability.Finally,the challenges and problems faced by the satellite network are analyzed and the trend of future development is predicted. | QI Xiaogang MA Jiulong WU Dan LIU Lifang HU Shaolin | 2016 | Journal of Communications and Information Networks2016，1，4： | 3 |
| 6 | Overview to the Hard X-ray Modulation Telescope (Insight-HXMT) Satellite显示文摘As China’s first X-ray astronomical satellite, the Hard X-ray Modulation Telescope (HXMT), which was dubbed as Insight-HXMT after the launch on June 15, 2017, is a wide-band(1-250 ke V) slat-collimator-based X-ray astronomy satellite with the capability of all-sky monitoring in 0.2-3 Me V. It was designed to perform pointing, scanning and gamma-ray burst(GRB)observations and, based on the Direct Demodulation Method (DDM), the image of the scanned sky region can be reconstructed.Here we give an overview of the mission and its progresses, including payload, core sciences, ground calibration/facility, ground segment, data archive, software, in-orbit performance, calibration, background model, observations and some preliminary results. | Shuang-Nan Zhang TiPei Li FangJun Lu LiMing Song YuPeng X u CongZhan Liu Yong Chen XueLei Cao QingCui Bu Zhi Chang Gang Chen Li Chen TianXiang Chen YiBao Chen YuPeng Chen Wei Cui WeiWei Cui JingKang Deng YongWei Dong Yuan Yuan Du MinXue Fu GuanHua Gao He Gao Min Gao MingYu Ge YuDong Gu Ju Guan Can Gungor ChengCheng Guo DaWei Han Wei Hu Yue Huang Jia Huo ShuMei Jia LuHua Jiang WeiChun Jiang Jing Jin YongJie Jin Bing Li ChengKui Li Gang Li MaoShun Li Wei Li Xian Li XiaoBo Li XuFang Li YanGuo Li ZiJian Li ZhengWei Li XiaoHua Liang JinYuan Liao GuoQing Liu HongWei Liu ShaoZhen Liu XiaoJing Liu Yuan Liu YiNong Liu Bo Lu XueFeng Lu Tao Luo Xiang Ma Bin Meng Yi Nang JianYin Nie Ge Ou JinLu Qu Na Sai RenCheng Shang GuoHong Shen Liang Sun Ying Tan Lian Tao YouLi Tuo Chen Wang ChunQin Wang GuoFeng Wang HuanYu Wang Juan Wang WenShuai Wang YuSa Wang XiangYang Wen BaiYang Wu BoBing Wu Mei Wu GuangCheng Xiao ShaoLin Xiong LinLi Yan JiaWei Yang Sheng Yang YanJi Yang QiBin Yi Bin Yuan AiMei Zhang ChunLei Zhang ChengMo Zhang Fan Zhang HongMei Zhang Juan Zhang Qiang Zhang ShenYi Zhangs Shu Zhang Tong Zhang WanChang Zhang Wei Zhang WenZhao Zhang Yi Zhang YiFei Zhang YongJie Zhang Yue Zhang Zhao Zhang Zhi Zhang ZiLiang Zhang HaiSheng Zhao XiaoFan Zhao ShiJie Zheng JianFeng Zhou YuXuan Zhu Yue Zhu RenLin Zhuang | 2020 | Science China(Physics,Mechanics & Astronomy)2020，63，4： | 2 |
| 7 | Genomic Insight into the Antimicrobial Resistance of Streptococcus Suis-Six Countries,2011-2019显示文摘Summary What is already known on this topic?Streptococcus suis(S.suis)is a zoonotic pathogen causing disease in humans and animals,and the emergence of its increased resistance to antimicrobial agents has become a significant challenge in many countries. | Lichao Ma Wanjiang Zhang Jingyun Ma Qingpo Cui Chaoyang Zhang Peng Zhang Chengtao Sun Huarun Sun Yao Zhu Shaolin Wang Shuangyang Ding Gongzheng Hu Zhangqi Shen | 2021 | China CDC weekly2021，3，47： | 2 |
| 8 | Iterative estimators of parameters in a linear model with partially variant coefficients显示文摘 | HU SHAOLIN KARL MEINKE CHEN RUSHAN | 2007 | International Journal of Applied Mathematics and Computer Science2007，17，2： | 1 |
| 9 | Simultaneous detection of resolved glutamate, glutamine and γ-aminobutyric acid at 4 T显示文摘 | HU Jiani YANG Shaolin XUAN Yang | 2007 | Journal of Magnetic Resonance2007，185，： | 1 |
| 10 | The fault locationmethod research of three-layer network system 显示文摘 | Hu Shaolin Li Ye Meinke K | 2012 | International Journal of Advanced Research in Artificial Intelligence2012，1，6： | 1 |
| 11 | Flame smoke detection algorithm based on YOLOv5 in petrochemical plant显示文摘Purpose–Fire smoke detection in petrochemical plant can prevent fire and ensure production safety and life safety.The purpose of this paper is to solve the problem of missed detection and false detection in flame smoke detection under complex factory background.Design/methodology/approach–This paper presents a flame smoke detection algorithm based on YOLOv5.The target regression loss function(CIoU)is used to improve the missed detection and false detection in target detection and improve the model detection performance.The improved activation function avoids gradient disappearance to maintain high real-time performance of the algorithm.Data enhancement technology is used to enhance the ability of the network to extract features and improve the accuracy of the model for small target detection.Findings–Based on the actual situation of flame smoke,the loss function and activation function of YOLOv5 model are improved.Based on the improved YOLOv5 model,a flame smoke detection algorithm with generalization performance is established.The improved model is compared with SSD and YOLOv4-tiny.The accuracy of the improved YOLOv5 model can reach 99.5%,which achieves a more accurate detection effect on flame smoke.The improved network model is superior to the existing methods in running time and accuracy.Originality/value–Aiming at the actual particularity of flame smoke detection,an improved flame smoke detection network model based on YOLOv5 is established.The purpose of optimizing the model is achieved by improving the loss function,and the activation function with stronger nonlinear ability is combined to avoid over-fitting of the network.This method is helpful to improve the problems of missed detection and false detection in flame smoke detection and can be further extended to pedestrian target detection and vehicle running recognition. | Yueting Yang Shaolin Hu Ye Ke Runguan Zhou | 2023 | International Journal of Intelligent Computing and Cybernetics2023，16，3： | 0 |
| 12 | LSTM based prediction algorithm and abnormal change detection for temperature in aerospace gyroscope shell显示文摘Purpose–Abnormal changes in temperature directly affect the stability and reliability of a gyroscope.Predicting the temperature and detecting the abnormal change is great value for timely understanding of the working state of the gyroscope.Considering that the actual collected gyroscope shell temperature data have strong non-linearity and are accompanied by random noise pollution,the prediction accuracy and convergence speed of the traditional method need to be improved.The purpose of this paper is to use a predictive model with strong nonlinear mapping ability to predict the temperature of the gyroscope to improve the prediction accuracy and detect the abnormal change.Design/methodology/approach–In this paper,an double hiddenlayer long-shortterm memory(LSTM)is presentedto predicttemperature data for the gyroscope(including singlepoint andperiod prediction),and the evaluation index of the prediction effect is also proposed,and the prediction effects of shell temperature data are compared by BP network,support vector machine(SVM)and LSTM network.Using the estimated value detects the abnormal change of the gyroscope.Findings–By combined simulation calculation with the gyroscope measured data,the effect of different network hyperparameters on shell temperature prediction of the gyroscope is analyzed,and the LSTM networkcan beusedto predictthe temperature(timeseriesdata).Bycomparingthe performance indicatorsof different prediction methods,the accuracy of the shell temperature estimation by LSTM is better,which can meet the requirements of abnormal change detection.Quick and accurate diagnosis of different types of gyroscopefaults(stepsanddrifts)can beachievedbysettingreasonabledatawindowlengthsandthresholds.Practicalimplications–The LSTMmodelisa deepneuralnetworkmodelwithmultiplenon-linearmapping levels,and can abstract the input signal layer by layer and extract features to discover deeper underlying laws.The improved method has been used to solve the problem of strong non-linearity and random noise pollutionin time series,and the estimated value can detect the abnormal change of the gyroscope.Originality/value–In this paper,based on the LSTM network,an double hidden layer LSTM is presented to predict temperature data for the gyroscope(including single point and period prediction),and validate the effectiveness and feasibility of the algorithm by using shell temperature measurement data.The prediction effects of shell temperature data are compared by BP network,SVM and LSTM network.The LSTM network has the best prediction effect,and is used to predict the temperature of the gyroscope to improve the prediction accuracy and detect the abnormal change. | Haoqiang Shi Shaolin Hu Jiaxu Zhang | 2019 | International Journal of Intelligent Computing and Cybernetics2019，12，2： | 0 |
| 13 | Expert consensus on blood pressure management in critically ill patients显示文摘Introduction For critically ill patients with unstable hemodynamics,goal‑directed therapy for arterial blood pressure is needed with continuous daily bedside monitoring.The prevalence of hypertension in Chinese adults is 25.2%,of which 1–2%of patients may experience a hypertensive emergency,with a mortality rate of 6.9%in the acute phase.The mortality and readmission rates within 90 days of onset are as high as 11%.[1]Furthermore,the mortality rate for patients who experience hypertensive emergencies can reach 50%within 12 months of the incident.[2]The incidence of perioperative hypertension in patients undergoing cardiac surgery is approximately 50%,with this figure dropping to 25%for non-cardiac surgery.Surgery may increase the incidence of perioperative cardio-cerebrovascular adverse events by 3–5%.[3] | Yuetian Yu Ye Gong Bo Hu Bin Ouyang Aijun Pan Jinglun Liu Fen Liu Xiu-Ling Shang Xiang-Hong Yang Guowei Tu Changsong Wang Shaolin Ma Wei Fang Ling Liu Jiao Liu Dechang Chen | 2023 | Journal of Intensive Medicine2023，3，3： | 0 |
| 14 | An improved morphological weighted dynamic similarity measurement algorithm for time series data显示文摘Purpose–The similarity measurement of time series is an important research in time series detection,which is a basic work of time series clustering,anomaly discovery,prediction and many other data mining problems.The purpose of this paper is to design a new similarity measurement algorithm to improve the performance of the original similarity measurement algorithm.The subsequence morphological information is taken into account by the proposed algorithm,and time series is represented by a pattern,so the similarity measurement algorithm is more accurate.Design/methodology/approach–Following some previous researches on similarity measurement,an improved method is presented.This new method combines morphological representation and dynamic time warping(DTW)technique to measure the similarities of time series.After the segmentation of time series data into segments,three parameter values of median,point number and slope are introduced into the improved distance measurement formula.The effectiveness of the morphological weighted DTW algorithm(MW-DTW)is demonstrated by the example of momentum wheel data of an aircraft attitude control system.Findings–The improved method is insensitive to the distortion and expansion of time axis and can be used to detect the morphological changes of time series data.Simulation results confirm that this method proposed in this paper has a high accuracy of similarity measurement.Practical implications–This improved method has been used to solve the problem of similarity measurement in time series,which is widely emerged in different fields of science and engineering,such as the field of control,measurement,monitoring,process signal processing and economic analysis.Originality/value–In the similarity measurement of time series,the distance between sequences is often used as the only detection index.The results of similarity measurement should not be affected by the longitudinal or transverse stretching and translation changes of the sequence,so it is necessary to incorporate themorphological changes of the sequence into similarity measurement.The MW-DTW is more suitable for the actual situation.At the same time,the MW-DTW algorithm reduces the computational complexity by transforming the computational object to subsequences. | Ke Yi Zhou Shaolin Hu | 2018 | International Journal of Intelligent Computing and Cybernetics2018，11，4： | 0 |
| 15 | Current-voltage characteristics of voltage-biased Tl_2Ba_2CaCu_2O_8 intrinsic Josephson junctions显示文摘The voltage-biased current-voltage(I-V)characteristics of intrinsic Josephson junctions(IJJs),which are fabricated with misaligned high temperature superconducting Tl2Ba2Ca Cu2O8(Tl-2212)thin film,are investigated experimentally.Three characteristic regions in the I-V curve are observed at 47 K.In the low voltage part,the current firstly increases and then decreases slowly with increasing the biased voltage,which is shown as a bump.In the next region,the current slightly increases with increasing the biased voltage until a sudden decrease of the current appears.Thereafter,branch structure forms with increasing the voltage on the I-V characteristic.The influence of the self-heating on the I-V characteristics is investigated and the temperature dependence of the I-V characteristics is measured to explore these characteristics in detail. | WANG Pei XIE Wei HU Lei LIU Xin JI Lu HE Ming ZHANG Xu ZHAO XinJie YAN ShaoLin | 2014 | Science China(Physics,Mechanics & Astronomy)2014，57，12： | 0 |
| 16 | CLOF Based Outlier Detection Algorithm of Temperature Data for Ethylene Cracking Furnace显示文摘The flue temperature is one of the important indicators to characterize the combustion state of an ethylene cracker furnace,the outliers of temperature data can lead to the false alarm.Conventional outlier detection algorithms such as the Isolation Forest algorithm and 3-sigma principle cannot detect the outliers accurately.In order to improve the detection accuracy and reduce the computational complexity,an outlier detection algorithm for flue temperature data based on the CLOF(Clipping Local Outlier Factor,CLOF)algorithm is proposed.The algorithm preprocesses the normalized data using the cluster pruning algorithm,and realizes the high accuracy and high efficiency outlier detection in the outliers candidate set.Using the flue temperature data of an ethylene cracking furnace in a petrochemical plant,the main parameters of the CLOF algorithm are selected according to the experimental results,and the outlier detection effect of the Isolation Forest algorithm,the 3-sigma principle,the conventional LOF algorithm and the CLOF algorithm are compared and analyzed.The results show that the appropriate clipping coefficient in the CLOF algorithm can significantly improve the detection efficiency and detection accuracy.Compared with the outlier detection results of the Isolation Forest algorithm and 3-sigma principle,the accuracy of the CLOF detection results is increased,and the amount of data calculation is significantly reduced. | Yidan Xin Shaolin Hu Wenzhuo Chen He Song | 2023 | Journal of Harbin Institute of Technology(New Series)2023，30，4： | 0 |
| 17 | Generalized Ridge Estimation of a Semiparametric Regression Model显示文摘We considered the following semiparametric regres-sion model yi = X iT β+ s ( t i ) + ei (i =1,2,,n). First,the general-ized ridge estimators of both parameters and non-parameters are given without a restrained design matrix. Second,the generalized ridge estimator will be compared with the penalized least squares estimator under a mean squares error,and some conditions in which the former excels the latter are given. Finally,the validity and feasibility of the method is illustrated by a simulation example. | Hongchang Hu Shaolin Rao | 2010 | Wuhan University Journal of Natural Sciences2010，15，4： | 0 |
| 18 | Transmission of Carbapenem Resistance Between Human and Animal NDM-Positive Escherichia coli Strains显示文摘Although carbapenem use is prohibited in animals in China,carbapenem-resistant Escherichia coli(CREC),especially New Delhi metallo-β-lactamase(NDM)-producing strains,are widely prevalent in foodproducing animals.At present,the impact of livestock-associated CREC strains on human populations at the national level is unknown.Here,we conduct a retrospective cross-sectional study to investigate the prevalence of CREC from clinical settings across 22 Chinese provinces or municipalities and analyze anthropogenic factors associated with their presence.We also ascertain the blaNDMand blaKPCabundance among pig and chicken farms and present a detailed genomic framework for CREC of animal and human origin.Overall,631/29799(2.1%)clinical Escherichia coli(E.coli)isolates were identified as CREC.Multivariable analysis revealed that being male,an age below 1,an age between 13 and 18,provinces with greater chicken production,and provinces with higher pig production were associated with higher odds of CREC infection.In general,73.8%(n=45/61)of pig farms and 62.2%(n=28/45)of chicken farms had a blaNDMabundance of 1×10^(-5)to 1×10^(-3)and 1×10^(-3)to 1×10^(-2),respectively.Among all the Chinese NDM-positive E.coli(n=463)available at the National Center for Biotechnology Information(NCBI),the genomic analysis revealed that blaNDM-5and Inc X3 were the predominant carbapenemase gene-plasmid combination,while a highly homogeneous relationship between NDM-positive isolates from humans and animals was demonstrated at the plasmid and core genome levels.All the findings suggest frequent CREC transmission between humans and animals,indicating that further discussions on the use of antibiotics in animals and humans are needed,both in China and across the globe. | Yingbo Shen Fupin Hu Yongqiang Wang Dandan Yin Lu Yang Yiqiang Chen Chunyan Xu Jiyun Li Junyao Jiang Xueyang Wang Yulin Fu Dongyan Shao Dejun Liu Tengfei Ma Chang Cai Zhangqi Shen Shaolin Wang Juan Li Rong Zhang Yuebin Ke Congming Wu Jianzhong Shen Timothy R.Walsh Yang Wang | 2022 | Engineering2022，8，8： | 0 |
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