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Science Bulletin 2019年第6期64卷 370-373页

作者： Peng Gong Han liu Meinan Zhang Congcong li Jie Wang Huabing Huang Nicholas Clinton Luyan Ji Wenyu li Yuqi Bai Bin Chen Bing Xu Zhiliang Zhu Cui Yuan Hoi Ping Suen Jing Guo Nan Xu Weijia li Yuanyuan zhao Jun Yang Chaoqing Yu Xi Wang Haohuan Fu Le Yu Iryna Dronova Fengming Hui Xiao Cheng Xueli Shi Fengjin Xiao Qiufeng liu lianchun Song Ministry of Education Key Laboratory for Earth System Modeling Department of Earth System Science Tsinghua University AI for Earth Lab Cross-Strait Institute Tsinghua University Department of environmental Science Policy and Management University of CaliforniaBerkeley State Key Laboratory of Remote Sensing Science Institute of Remote Sensing and Digital Earth Chinese Academy of Sciences Google LLC Institute of Electronics Chinese Academy of Sciences United States Geological Survey National Supercomputing Center in Wuxi Department of Landscape Architecture University of CaliforniaBerkeley State Key Laboratory of Remote Sensing Science College of Global Change and Earth System Science Beijing Normal University National Climate Center China Meteorological Administration

As the world strives to reduce the impact of population growth, urbanization, agricultural expansion, and climate change on food security, energy and water shortage, resource over-exploration, biodiversity loss, environmental pollution, and ultimately human health, timely and higher resolution land cover information is urgently needed to achieve the sustainable development goals of the United Nations.

关键词： the world strives to reduce timely and higher resolution information is urgently needed

Taking the pulse of COVID-19:a spatiotemporal perspective

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International Journal of Digital Earth 2020年第10期13卷 1186-1211页

作者： Chaowei Yang Dexuan Sha Qian liu Yun li Hai Lan Weihe Wendy Guan Tao Hu Zhenlong li Zhiran Zhang John Hoot Thompson Zifu Wang David Wong Shiyang Ruan Manzhu Yu Douglas Richardson Luyao Zhang Ruizhi Hou You Zhoua Cheng Zhong Yifei Tian Fayez Beaini Kyla Carte Colin Flynn Wei liu Dieter Pfoser Shuming Bao Mei li Haoyuan Zhang Chunbo liu Jie Jiang Shihong Du liang zhao Mingyue Lu lin li Huan Zhou Andrew Ding NSF Spatiotemporal Innovation Center George Mason Univ.FairfaxVAUSA Department of Geography and GeoInformation Science George Mason Univ.FairfaxVAUSA Department of Geographical sciences University of MarylandCollege ParkMDUSA Center for Geographic Analysis Harvard UniversityCambridgeMAUSA Geoinformation and Big Data Research Lab Department of GeographyUniversity of South CarolinaColumbiaSCUSA Chinese Academy of Surveying and Mapping BeijingPeople’s Republic of China School of resource and environmental sciences Wuhan UniversityWuhanPeople’s Republic of China Cloud Computeand Storage OperationsInformation Technology ServicesGeorge Mason UniversityFairfaxVAUSA Department of Geography Pennsylvania State UniversityState CollegePAUSA School of Business Management East China Normal UniversityShanghaiPeople’s Republic of China School of Mathematical sciences East China Normal UniversityShanghaiPeople’s Republic of China Department of Psychology George Mason UniversityFairfaxVAUSA mDepartment of Computer Science George Mason UniversityFairfaxVAUSA Department of Information Technology George Mason UniversityFairfaxVAUSA Department of Biology George Mason UniversityFairfaxVAUSA College of Land Science and Technology China Agricultural UniversityBeijingPeople’s Republic of China china Data Institute Ann ArborMIUSA Institute of Remote Sensing and GIS Peking UniversityBeijingPeople’s Republic of China Aerospace Information Research Institute Chinese Academy of SciencesBeijingPeople’s Republic of China School of Geomatics and Urban Spatial Informatics Beijing University of Civil Engineering and ArchitectureBeijingPeople’s Republic of China School of Geographical sciences Nanjing University of Information Science&TechnologyNanjingPeople’s Republic of China School of Geodesy and Geomatics Wuhan UniversityWuhanPeople’s Republic of China wFaculty of Environment University of WaterlooWaterlooCanada

The sudden outbreak of the Coronavirus disease(COVID-19)swept across the world in early 2020,triggering the lockdowns of several billion people across many countries,including china,Spain,India,the U.K.,Italy,France,Germany,Brazil,Russia,and the *** transmission of the virus accelerated rapidly with the most confirmed cases in the U.S.,India,Russia,and *** response to this national and global emergency,the NSF Spatiotemporal Innovation Center brought together a taskforce of international researchers and assembled implementation strategies to rapidly respond to this crisis,for supporting research,saving lives,and protecting the health of global *** perspective paper presents our collective view on the global health emergency and our effort in collecting,analyzing,and sharing relevant data on global policy and government responses,human mobility,environmental impact,socioeconomical impact;in developing research capabilities and mitigation measures with global scientists,promoting collaborative research on outbreak dynamics,and reflecting on the dynamic responses from human societies.

关键词： Big Data Earth system emergency geospatial sciences epidemics applications

The hidden risk of microplastic-associated pathogens in aquatic environments

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Eco-Environment & Health 2023年第3期2卷 142-151页

作者： Huan Zhong Mengjie Wu Christian Sonne Su Shiung Lam Raymond W.M.Kwong Yuelu Jiang Xiaoli zhao Xuemei Sun Xuxiang Zhang Chengjun li Yuanyuan li Guangbo Qu Feng Jiang Huahong Shi Rong Ji Hongqiang Ren School of Environment Nanjing UniversityState Key Laboratory of Pollution Control and Resource ReuseNanjing 210023China Department of Bioscience Arctic Research CentreAarhus UniversityRoskildeDenmark Higher Institution Centre of Excellence(HICoE) Institute of Tropical Aquaculture and Fisheries(AKUATROP)Universiti Malaysia Terengganu21030 Kuala NerusTerengganuMalaysia Department of Biology York University4700 Keele StreetTorontoON M3J 1P3Canada Tsinghua Shenzhen International Graduate School Shenzhen 518055China State Key Laboratory of environmental Criteria and Risk Assessment Chinese Research Academy of Environmental SciencesBeijing 100012China yellow Sea Fisheries Research Institute Chinese Academy of Fishery SciencesQingdao 266071China Institute of environmental Research at Greater Bay Area Key Laboratory for Water Quality and Conservation of the Pearl River DeltaMinistry of EducationGuangzhou UniversityGuangzhou 510006China Key Laboratory of Environment and Health(HUST) Ministry of Education&Ministry of Environmental Protectionand State Key Laboratory of Environmental Health(Incubation)School of Public HealthTongji Medical CollegeHuazhong University of Science and TechnologyWuhan 430030China State Key Laboratory of environmental Chemistry and Ecotoxicology Research Center for Eco-Environmental SciencesChinese Academy of SciencesBeijing 100085China School of environmental Science and Engineering Guangdong Provincial Key Lab of Environmental Pollution Control and Remediation TechnologySun Yat-sen UniversityGuangzhou 510275China State Key Laboratory of Estuarine and Coastal Research East China Normal UniversityShanghai 200241China university Centre for Research and Development Department of ChemistryChandigarh UniversityGharuanMohaliPunjabIndia

Increasing studies of plastisphere have raised public concern about microplastics(MPs)as vectors for pathogens,especially in aquatic ***,the extent to which pathogens affect human health through MPs remains unclear,as controversies persist regarding the distinct pathogen colonization on MPs as well as the transmission routes and infection probability of MP-associated pathogens from water to *** this review,we critically discuss whether and how pathogens approach humans via MPs,shedding light on the potential health risks *** on cutting-edge multidisciplinary research,we show that some MPs may facilitate the growth and long-range transmission of specific pathogens in aquatic environments,ultimately increasing the risk of infection in *** identify MP-and pathogen-rich settings,such as wastewater treatment plants,aquaculture farms,and swimming pools,as possible sites for human exposure to MP-associated *** review emphasizes the need for further research and targeted interventions to better understand and mitigate the potential health risks associated with MP-mediated pathogen transmission.

关键词： Microplastics Pathogens Colonization Transmission Public health

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康养旅游相关概念辨析与国际研究进展

旅游论坛 2020年第1期13卷 69-81页

作者：李鹏赵永明叶卉悦华南师范大学地理科学学院广东广州510631 中国旅游协会温泉旅游分会北京100020 香港中文大学地理与资源管理学系中国香港

康养旅游(wellness tourism)隶属于健康旅游(health tourism)的范畴,是新近国际旅游研究的热点领域。文章通过对康养旅游概念的源起及其流变的梳理,辨明了康养旅游与健康旅游、温泉疗法、疗养旅游、医疗旅游等相关概念的关系。研究表明... 详细信息

康养旅游(wellness tourism)隶属于健康旅游(health tourism)的范畴,是新近国际旅游研究的热点领域。文章通过对康养旅游概念的源起及其流变的梳理,辨明了康养旅游与健康旅游、温泉疗法、疗养旅游、医疗旅游等相关概念的关系。研究表明,康养旅游的产品形式会根据不同国家和地区的资源禀赋、健康政策、消费市场的特点而产生变化,因此,不同地区的康养旅游内涵、构成与产品形式是学术界研究的焦点之一。而在康养旅游的功能分析上,主要聚焦于对人的身体、精神以及生活质量等方面。最后,康养旅游者出游前的动机、旅游中的体验与游后的满意度和行为意向构成了康养旅游者研究的主体内容。康养旅游是中国旅游业转型发展的一条可行道路,应从国家政策保障、目的地建设和公民健康观念入手,培育中国康养旅游市场,提升全民健康水平。同时,文章也为未来中国康养旅游的研究议题提出了相关建议。

关键词：康养旅游健康旅游康养旅游功能康养旅游者

Anticarin-β shows a promising antiosteosarcoma effect by specifically inhibiting CCT4 to impair proteostasis

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Acta Pharmaceutica Sinica B 2022年第5期12卷 2268-2279页

作者： Gan Wang Min Zhang Ping Meng Chengbo Long Xiaodong Luo Xingwei Yang Yunfei Wang Zhiye Zhang James Mwangi Peter Muiruri Kamau Zhi Daic Zunfu Ke Yi Zhang Wenlin Chen Xudong zhao Fei Ge Qiumin Lv Mingqiang Rong Dongsheng li Yang Jin Xia Sheng Ren Lai Key Laboratory of Animal Models and Human Disease Mechanisms Chinese Academy of Sciences/Key Laboratory of Bioactive Peptides of Yunnan ProvinceKIZ-CUHK Joint Laboratory of Bioresources and Molecular Research in Common DiseasesNational Resource Center for Non-Human PrimatesKunming Primate Research Centerand National Research Facility for Phenotypic&Genetic Analysis of Model Animals(Primate Facility)Kunming Institute of ZoologyKunming 650107China university of Chinese Academy of sciences Beijing 100049China State Key Laboratory of Phytochemistry and Plant resources in West china Kunming Institute of BotanyChinese Academy of SciencesKunming 650201China Institutes for Drug Discovery and Development Chinese Academy of SciencesShanghai 201203China Sino-African Joint Research Center Chinese Academy of ScienceWuhan 430074China Department of Pathology First Afﬁliated HospitalSun Yat-sen UniversityGuangzhou 510080China Department of Orthopaedic Surgery First Afﬁliated Hospital of Zhengzhou UniversityZhengzhou 450052China Department of Breast Surgery Third Afﬁliated Hospital of Kunming Medical UniversityYunnan Cancer CenterKunming 650118China Department of Breast Surgery First Afﬁliated Hospital of Kunming Medical UniversityKunming 650032China Department of Biosciences University of OsloOslo 0316Norway Key Laboratory of Environment and Health Ministry of Education&Ministry of Environmental ProtectionAnd State Key Laboratory of Environmental HealthSchool of Public HealthTongji Medical CollegeHuazhong University of Science and TechnologyWuhan 434000China Center for Biosafety Mega-Science Chinese Academy of SciencesWuhan 430071China

Unlike healthy, non-transformed cells, the proteostasis network of cancer cells is taxed to produce proteins involved in tumor development. Cancer cells have a higher dependency on molecular chaperones to maintain proteostasis. The chaperonin T-complex protein ring complex(TRiC) contains eight paralogous subunits(CCT1-8), and assists the folding of as many as 10% of cytosolic *** is essential for the progression of some cancers, but the roles of TRiC subunits in osteosarcoma remain to be explored. Here, we show that CCT4/TRiC is significantly correlated in human osteosarcoma,and plays a critical role in osteosarcoma cell survival. We identify a compound anticarin-β that can specifically bind to and inhibit CCT4. Anticarin-β shows higher selectivity in cancer cells than in normal cells. Mechanistically, anticarin-β potently impedes CCT4-mediated STAT3 maturation. Anticarin-β displays remarkable antitumor efficacy in orthotopic and patient-derived xenograft models of ***, our data uncover a key role of CCT4 in osteosarcoma, and propose a promising treatment strategy for osteosarcoma by disrupting CCT4 and proteostasis.

关键词： Proteostasis CCT TRiC Osteosarcoma STAT3 Anticarin-β PDX model

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路网扩张对董志塬景观生态的影响

Journal of Geographical sciences 2023年第12期33卷 2549-2566页

作者：杨思齐金钊罗达冯立 State Key Laboratory of Loess and Quaternary Geology Institute of Earth EnvironmentCASXi’an710061China State Key Laboratory of Earth Surface Processes and resource Ecology Faculty of Geographical ScienceBeijing Normal UniversityBeijing100875China CAS Center for Excellence in Quaternary Science and Global Change Xi’an710061China university of Chinese Academy of sciences Beijing100049China Institute of Global environmental Change Xi’an Jiaotong UniversityXi’an710049China

Road network expansion can result in the fragmentation of ecological landscapes due to the transformation of landscape processes and ***,knowledge about these processes and patterns is *** this study,the road network and landscape patterns in the Dongzhi tableland of the Chinese Loess Plateau(CLP) between 2005 and 2020 were characterized,and their spatial relationships were *** results showed that(1) the kernel density estimation(KDE) method is useful in characterizing road network *** the bandwidth value is four,the boundary of the road network kernel can be distinguished clearly.(2) The road network in the tableland expanded greatly over the past 15 years,and the total area of road kernels in the Dongzhi tableland increased from 55.73 km~2 in 2005 to 223.55 km~2 in 2020.(3) High-density road networks were generally distributed on cultivated and constructed lands where the slopes were generally 0°–5°,while low-and medium-density road networks were mostly distributed in grassland areas where the slopes were greater than 5°.(4) Road network density is closely related to the coverage of cultivated and constructed *** results of this study are helpful in understanding the potential impact of road network evolution on the landscape at a regional scale.

关键词： kernel density estimation road network expansion landscape metrics loess tableland

COVID-19疫情期间京津冀大气污染物变化及影响因素分析

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环境科学 2021年第3期42卷 1205-1214页

作者：赵雪沈楠驰李令军武高峰陶静赵文吉首都师范大学资源环境与旅游学院北京100048 北京市生态环境监测中心北京100048

为了应对COVID-19疫情,京津冀地区采取了一系列严格的管控措施,这些措施导致了大气污染物人为源排量的减少,为探究大气污染受人类活动的影响程度提供了时机.将疫情防控分为前期、初期、中期和后期这4个阶段,并结合气象、交通量和工业数... 详细信息

为了应对COVID-19疫情,京津冀地区采取了一系列严格的管控措施,这些措施导致了大气污染物人为源排量的减少,为探究大气污染受人类活动的影响程度提供了时机.将疫情防控分为前期、初期、中期和后期这4个阶段,并结合气象、交通量和工业数据,综合运用数理统计和空间分析方法,得出各时间段大气污染物的变化情况及影响因素,为京津冀地区进一步治理大气污染提出了合理化建议.结果表明:(1)京津冀三地在疫情防控期总体的AQI值和6项污染物同比2019年均有下降,其中SO_(2)、PM_(10)和NO_(2)的降幅较大(分别为26.5%、24.3%和16.9%);由初期到后期,各污染物(除O3)总体处于下降趋势;O_(3)在初期增幅大(76.2%),中后期增幅放缓.(2)防控初期北京市的重污染天气是污染物本地积累、二次转化和区域传输共同作用的结果;北京2月份的PM_(2.5)浓度同比相似气象条件下的2014年2月偏低近6成;若仅考虑人为减排的影响,则各污染物浓度同比2019年均有下降.(3)防控中后期,随着交通量和工业复工率进一步扩大,各污染物变化趋于平稳或有微升;重工业城市的热异常辐射强度与主要污染物的灰色关联度大于0.6,即控制工业排量仍是治理大气污染的关键.

关键词： COVID-19疫情京津冀地区空气质量污染特征人为影响

空间恢复力理论支持下的人地系统动态研究进展

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地理学报 2020年第5期75卷 891-903页

作者：刘焱序傅伯杰王帅赵文武李琰北京师范大学地理科学学部地表过程与资源生态国家重点实验室北京100875 中国科学院生态环境研究中心城市与区域生态国家重点实验室北京100085

人地系统的概念表现了人与地在特定的地域中相互联系、相互作用而形成的一种动态结构,面向人地系统动态运行过程的复杂性,亟待构建更有力的指标体系表征地球系统和人类系统相互影响与反馈的过程。空间恢复力可以被理解为以保障人地系统... 详细信息

人地系统的概念表现了人与地在特定的地域中相互联系、相互作用而形成的一种动态结构,面向人地系统动态运行过程的复杂性,亟待构建更有力的指标体系表征地球系统和人类系统相互影响与反馈的过程。空间恢复力可以被理解为以保障人地系统结构稳定为目标的地域空间整体对自然和社会扰动的吸收、复原或转化能力,为人地系统研究中针对性理论模式和可定量化指标体系的塑造提供新途径。本文以从自然维度出发的政策与生态系统空间恢复力、从社会维度出发的环境变化与社区生产生活空间恢复力、从综合描述方式出发的空间恢复力综合指标体系三个角度梳理空间恢复力研究现状,并从结构、功能、阈值三个方面研讨不同地域功能类型下的空间恢复力指标体系,提出认知保障系统可持续性的空间状态、明晰人地系统动态过程的空间阈值、满足生态保护与社会进步国家需求三项内容可以作为人地系统动态研究的重要方向。

关键词：人地系统动态景观生态学可持续性阈值国家需求

Mapping high resolution National Soil Information Grids of china

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Science Bulletin 2022年第3期67卷 328-340页

作者： Feng liu Huayong Wu Yuguo zhao Decheng li Jin-ling Yang Xiaodong Song Zhou Shi A-Xing Zhu Gan-lin Zhang State Key Laboratory of Soil and Sustainable Agriculture Institute of Soil ScienceChinese Academy of SciencesNanjing 210008China university of Chinese Academy of sciences Beijing 100049China Institute of Agricultural Remote Sensing and Information Technology Application College of Environmental and Resource SciencesZhejiang UniversityHangzhou 310058China Key Laboratory of Virtual Geographic Environment of Ministry of Education Nanjing Normal UniversityNanjing 210023China State Key Laboratory of resources and environmental Information System Institute of Geographic Sciences and Natural Resources ResearchChinese Academy of SciencesBeijing 100101China Key Laboratory of Watershed Geographic Science Nanjing Institute of Geography and LimnologyChinese Academy of SciencesNanjing 210008China

Soil spatial information has traditionally been presented as polygon maps at coarse scales. Solving global and local issues, including food security, water regulation, land degradation, and climate change requires higher quality, more consistent and detailed soil information. Accurate prediction of soil variation over large and complex areas with limited samples remains a challenge, which is especially significant for china due to its vast land area which contains the most diverse soil landscapes in the world. Here, we integrated predictive soil mapping paradigm with adaptive depth function fitting, state-of-the-art ensemble machine learning and high-resolution soil-forming environment characterization in a highperformance parallel computing environment to generate 90-m resolution national gridded maps of nine soil properties(pH, organic carbon, nitrogen, phosphorus, potassium, cation exchange capacity, bulk density, coarse fragments, and thickness) at multiple depths across china. This was based on approximately5000 representative soil profiles collected in a recent national soil survey and a suite of detailed covariates to characterize soil-forming environments. The predictive accuracy ranged from very good to moderate(Model Efficiency Coefficients from 0.71 to 0.36) at 0–5 cm. The predictive accuracy for most soil properties declined with depth. Compared with previous soil maps, we achieved significantly more detailed and accurate predictions which could well represent soil variations across the territory and are a significant contribution to the *** project. The relative importance of soil-forming factors in the predictions varied by specific soil property and depth, suggesting the complexity and non-stationarity of comprehensive multi-factor interactions in the process of soil development.

关键词： Predictive soil mapping Soil-landscape model Machine learning Depth function Large and complex areas Soil spatial variation

北京城区油松灰分含量与大气质量指数相关分析

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北京师范大学学报（自然科学版） 2000年第2期36卷 281-284页

作者：赵烨刘芸赵承易李璐北京师范大学资源与环境科学系北京100875 北京师范大学分析测试中心北京100875

在对北京城区进行环境调查的基础上 ,采集不同功能区 19个样点的油松树枝样品 ,测定其中的灰分含量 .结果表明 :北京城区油松树枝灰分含量是从西北向东南呈逐渐增加趋势 ,在公园绿地附近一般有局部降低的现象 ;在交通枢纽及工业区附近... 详细信息

在对北京城区进行环境调查的基础上 ,采集不同功能区 19个样点的油松树枝样品 ,测定其中的灰分含量 .结果表明 :北京城区油松树枝灰分含量是从西北向东南呈逐渐增加趋势 ,在公园绿地附近一般有局部降低的现象 ;在交通枢纽及工业区附近的油松树枝灰分含量最高 ,可达1.14%～ 2 .76 % ,商业区及居民区灰分含量居中 ,其值在 0 .51%～ 0 .95%之间 ;城区西北边缘的公园区灰分含量最低 ,其值小于 0 .52 % .将上述测定结果与 1998 0 2— 1999 0 1北京市 8个样点的大气污染物标准指数平均值进行相关分析 ,得相关方程 :y =10 8.6 7+54.6 2x (r =0 .80 93,n =8) ,分析了该相关式的物理意义。

关键词：北京油松灰分大气污染物标准指数大气质量