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Trajectory of COVID-19 response and management strategy in China:scientific rationale driven strategy adjustments

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Frontiers of Medicine 2024年第1期18卷 19-30页

作者： Zeyu Zhang Yue Yan Lina Zhao yizhou Bian Ning Zhao You Wu Dahai Zhao Zongjiu Zhang Institute for Hospital Management Tsinghua UniversityBeijing100084China School of Medicine Tsinghua UniversityBeijing100084China School of International and Public Affairs Shanghai Jiao Tong UniversityShanghai200030China Yale University-Shanghai Jiao tong University Joint Center for Health Policy Shanghai Jiao Tong UniversityShanghai200030China

The pneumonia caused by novel coronavirus SARS-CoV-2 infection in early December 2019,which was later named coronavirus disease 2019(COVID-19)by the World Health Organization(WHO),rapidly spread across the *** has made extraordinary efforts to this unprecedented pandemic,put its response and control at a very high level of infectious disease management(Category B but with measures for Category A),given top priority to the people and their lives,and balanced the pandemic control and socio-economic *** more than three years’fighting against this disease,China downgraded the management of COVID-19 to Category B infectious disease on January 8,2023 and the WHO declared the end of public health emergency on May 5,***,the ending of pandemic does not mean that the disease is no longer a health *** against COVID-19 from China and the whole world should be learned to prepare well for the future public health *** article gives a systematic review of the trajectory of COVID-19 development in China,summarizes the critical policy arrangements and provides evidence for the adjustment during policy making process,so as to share experiences with international community and contribute to the global health for all humanity.

关键词： COVID-19 public health response and control strategy science-based policy making

Establishing HI mass vs. stellar mass and halo mass scaling relations using an abundance matching method

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Science China(Physics,Mechanics & Astronomy) 2024年第11期67卷 149-163页

作者： Yi Lu Xiaohu Yang Chengze Liu Haojie Xu Antonios Katsianis Hong Guo Xiaoju Xu yizhou Gu Key Laboratory for Research in Galaxies and Cosmology Shanghai Astronomical ObservatoryChinese Academy of SciencesShanghai 200030China Tsung-Dao Lee Institute and Shanghai Key Laboratory for Particle Physics and CosmologyShanghai Jiao Tong UniversityShanghai 200240China Department of Astronomy School of Physics and AstronomyShanghai Jiao Tong UniversityShanghai 200240China School of Physics and Astronomy Sun Yat-sen UniversityZhuhai CampusZhuhai 519082China

We combined data from the Sloan Digital Sky Survey(SDSS) and the Arecibo Legacy Fast ALFA Survey(ALFALFA) to establish the HI mass vs. stellar mass and halo mass scaling relations using an abundance matching method that is free of the Malmquist bias. To enable abundance matching, a cross-match between the SDSS DR7 galaxy group sample and the ALFALFA HI sources provides a catalog of 16520 HI-galaxy pairs within 14270 galaxy groups(halos). By applying the observational completeness reductions for both optical and HI observations, we used the remaining 8180 ALFALFA matched sources to construct the model constraints. Taking into account the dependence of HI mass on both the galaxy and group properties, we establish two sets of scaling relations: one with a combination of stellar mass,(g-r) color and halo mass, and the other with stellar mass,specific star-formation rate(sSFR), and halo mass. We demonstrate that our models can reproduce the HI mass component as both stellar mass and halo mass. Additional tests showed that the conditional HI mass distributions as a function of the cosmic web type and the satellite fractions were well recovered.

关键词： galaxy groups neutral hydrogen halos statistical

Preparation for CSST:Star-galaxy Classification using a Rotationally Invariant Supervised Machine Learning Method

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Research in Astronomy and Astrophysics 2024年第9期24卷 136-146页

作者： Shiliang Zhang Guanwen Fang Jie Song Ran Li yizhou Gu Zesen Lin Chichun Zhou Yao Dai Xu Kong Institute of Astronomy and Astrophysics Anqing Normal UniversityAnqing 246133China Deep Space Exploration Laboratory/Department of Astronomy University of Science and Technology of ChinaHefei 230026China School of Astronomy and Space Science University of Science and Technology of ChinaHefei 230026China National Astronomical Observatories Chinese Academy of SciencesBeijing 100101China Tsung-Dao Lee Institute and Key Laboratory for Particle Physics Astrophysics and CosmologyMinistry of EducationShanghai Jiao Tong UniversityShanghai 200240China Department of Physics The Chinese University of Hong KongShatinN.T.Hong KongS.A.R.China School of Engineering Dali UniversityDali 671003China

Most existing star-galaxy classifiers depend on the reduced information from catalogs,necessitating careful data processing and feature *** this study,we employ a supervised machine learning method(GoogLeNet)to automatically classify stars and galaxies in the COSMOS *** traditional machine learning methods,we introduce several preprocessing techniques,including noise reduction and the unwrapping of denoised images in polar coordinates,applied to our carefully selected samples of stars and *** dividing the selected samples into training and validation sets in an 8:2 ratio,we evaluate the performance of the GoogLeNet model in distinguishing between stars and *** results indicate that the GoogLeNet model is highly effective,achieving accuracies of 99.6% and 99.9% for stars and galaxies,***,by comparing the results with and without preprocessing,we find that preprocessing can significantly improve classification accuracy(by approximately 2.0% to 6.0%)when the images are *** preparation for the future launch of the China Space Station Telescope(CSST),we also evaluate the performance of the GoogLeNet model on the CSST simulation *** results demonstrate a high level of accuracy(approximately 99.8%),indicating that this model can be effectively utilized for future observations with the CSST.

关键词： methods:data analysis techniques:image processing stars:imaging

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基于灰度共生矩阵的草地未割区域分界线提取

杭州电子科技大学学报（自然科学版） 2016年第2期36卷 62-66,71页

作者：童逸舟刘瑜浙江理工大学机械与自动控制学院浙江杭州310018

利用草地的灰度图像计算灰度共生矩阵,通过比较"自相关"、"对比度"、"能量"、"均匀性"4个不同的特征值矩阵,提取出纹理分割效果最佳的二值图像,然后将二值图横向分割成若干宽度相同的横条,通过计算单条横条内黑色像素点的占有比确定历... 详细信息

利用草地的灰度图像计算灰度共生矩阵,通过比较"自相关"、"对比度"、"能量"、"均匀性"4个不同的特征值矩阵,提取出纹理分割效果最佳的二值图像,然后将二值图横向分割成若干宽度相同的横条,通过计算单条横条内黑色像素点的占有比确定历遍轮廓大小进而找出分割点坐标,最后将每个横条分割点用直线连起来.实验表明,利用灰度共生矩阵能较好地将未割草地的纹理特性提取出来,并通过后期算法处理能相对准确地进行分界线的提取.

关键词：草地分割灰度共生矩阵特征值矩阵历遍轮廓

通智测试——基于动态具身物理社会交互环境的通用人工智能测试

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Engineering 2024年第3期34卷 12-22页

作者： Yujia Peng Jiaheng Han Zhenliang Zhang Lifeng Fan Tengyu Liu Siyuan Qi Xue Feng Yuxi Ma yizhou Wang Song-Chun Zhu National Key Laboratory of General Artificial Intelligence Beijing Institute for General Artificial IntelligenceBeijing 100086China Institute for Artificial Intelligence Peking UniversityBeijing 100871China Beijing Key Laboratory of Behavior and Mental Health School of Psychological and Cognitive SciencesPeking UniversityBeijing 100871China School of Intelligence Science and Technology Peking UniversityBeijing 100871China School of Computer Science Peking UniversityBeijing 100871China

The release of the generative pre-trained transformer(GPT)series has brought artificial general intelligence(AGI)to the forefront of the artificial intelligence(AI)field once ***,the questions of how to define and evaluate AGI remain *** perspective article proposes that the evaluation of AGI should be rooted in dynamic embodied physical and social interactions(DEPSI).More specifically,we propose five critical characteristics to be considered as AGI benchmarks and suggest the tong test as an AGI evaluation *** tong test describes a value-and ability-oriented testing system that delineates five levels of AGI milestones through a virtual environment with DEPSI,allowing for infinite task *** contrast the tong test with classical AI testing systems in terms of various aspects and propose a systematic evaluation system to promote standardized,quantitative,and objective benchmarks and evaluation of AGI.

关键词： Artificial general intelligence Artificial intelligence benchmark Artificial intelligence evaluation Embodied artificial intelligence Value alignment Turing test Causality

基于模糊层次分析法的核安全设备持证单位量化评价研究

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核安全 2021年第5期20卷 16-20页

作者：童一周徐俊龙崔毅生态环境部华北核与辐射安全监督站北京100082

本文从民用核安全设备持证单位监督管理角度出发,综合考虑核安全法律法规及国家核安全局各项监管要求,结合监督实践活动,采用模糊层次分析法(FAHP)对持证单位核安全监督管理量化评价的指标和方法进行了研究。通过构建包含6个准则,近80... 详细信息

本文从民用核安全设备持证单位监督管理角度出发,综合考虑核安全法律法规及国家核安全局各项监管要求,结合监督实践活动,采用模糊层次分析法(FAHP)对持证单位核安全监督管理量化评价的指标和方法进行了研究。通过构建包含6个准则,近80个次级指标的动态评价体系,建立量化评价数学模型。此外,以具体持证单位为例,对其连续3年的监督记录进行了量化分析,得出量化评价结论,识别其存在的薄弱环节,并提出监管建议。该评价方法对实现精准监督、科学决策、依法行政起到了积极作用。

关键词：核安全设备模糊层次量化评价

黏蛋白-4和基质金属蛋白酶-7在种植体周病中的表达及意义

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华西口腔医学杂志 2022年第1期40卷 45-51页

作者：姜丹丹周政沈玉凤唐小雪缑小蕊黄枚钰童一洲陈苗苗余重庆石河子大学医学院第一附属医院口腔科石河子832000 石河子大学口腔医学系石河子832000

目的探讨基质金属蛋白酶(MMP)-7、MMP-8和黏蛋白(MUC)-4在种植体周围龈沟液(PICF)中的水平,分析二者是否具有区分种植体周围疾病与健康个体的能力,以期为寻找辅助种植体周围疾病诊断、评估和治疗的新型参考指标提供理论基础。方法按照... 详细信息

目的探讨基质金属蛋白酶(MMP)-7、MMP-8和黏蛋白(MUC)-4在种植体周围龈沟液(PICF)中的水平,分析二者是否具有区分种植体周围疾病与健康个体的能力,以期为寻找辅助种植体周围疾病诊断、评估和治疗的新型参考指标提供理论基础。方法按照纳入和排除标准选择上部修复体负载2~5年的63位受试者,其中对照组24例,种植体周围炎(PI)组39例。收集受试者一般情况及种植体周围临床指标,X线片测量牙槽骨吸收量,酶联免疫吸附试验法(ELISA)检测PICF中的MUC-4、MMP-7、MMP-8水平。结果PI组和对照组受试者的年龄、性别等参数信息差异无统计学意义,PI组MMP-7(P21.21时,其曲线下面积为0.868,诊断PI的灵敏度为0.96、特异度为0.68;MMP-7、MUC-4并联诊断模型的诊断效能高于两种因子单独诊断,模型对PI的诊断灵敏度为0.96,特异度为0.56。结论MMP-7、MUC-4的水平在PI组与对照组之间差异有统计学意义,可能成为预测是否罹患PI的诊断指标;联合MMP-7、MUC-4对炎症具有较好的诊断价值。

关键词：种植体周围疾病黏蛋白-4 基质金属蛋白酶-7

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水翼船的横摇控制

船舶工程 2024年第1期46卷 92-97,150页

作者：孙义洲许劲松叶睿上海交通大学船舶与海洋工程系上海200240 海思特海事技术(上海)有限公司上海200241

将一条模型尺度的全浸没式水翼艇作为案例船开展横摇控制研究。采用模型预测控制算法有效处理水翼失速角等约束条件,同时限制水翼的大幅剧烈运动,兼顾横摇姿态控制和执行机构保护的双重目标。在预测模型中增添预测偏差量作为前馈项,用... 详细信息

将一条模型尺度的全浸没式水翼艇作为案例船开展横摇控制研究。采用模型预测控制算法有效处理水翼失速角等约束条件,同时限制水翼的大幅剧烈运动,兼顾横摇姿态控制和执行机构保护的双重目标。在预测模型中增添预测偏差量作为前馈项,用以消除稳态误差,对常规模型预测控制算法做出一个重要改进。将案例船配备推进系统和可控水翼进行横摇控制航行试验,结果清晰展示了改进型模型预测控制器的横摇控制效果,这对水翼船的姿态控制研究具有重要借鉴意义。

关键词：全浸没式水翼船横摇控制模型预测控制算法航行试验

Distributed Photovoltaic Real-Time Output Estimation Based on Graph Convolutional Networks

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Journal of Shanghai Jiaotong university(Science) 2024年第2期29卷 290-296页

作者：陈利跃洪道鉴何星卢东祁张乾谢妮娜徐一洲应煌浩 State Grid Zhejiang Electric Power Co. Ltd.Hangzhou 310007China State Grid Zhejiang Taizhou Power Supply Company Taizhou 318000ZhejiangChina Department of Automation School of Electronic Information and Electrical EngineeringShanghai Jiao Tong UniversityShanghai 200240China

The rapid growth of distributed photovoltaic(PV)has remarkable influence for the safe and economic operation of power *** view of the wide geographical distribution and a large number of distributed PV power stations,the current situation is that it is dificult to access the current dispatch data *** to the temporal and spatial characteristics of distributed PV,a graph convolution algorithm based on adaptive learning of adjacency matrix is proposed to estimate the real-time output of distributed PV in regional power *** actual case study shows that the adaptive graph convolution model gives different adjacency matrixes for different PV stations,which makes the corresponding output estimation algorithm have higher accuracy.

关键词： distributed photovoltaic(PV) graph convolution network power estimation