|
|
|
题名
|
作者
|
年代
|
出处
|
被引量
|
| 1 | The Deep-Time Digital Earth program:data-driven discovery in geosciences显示文摘Current barriers hindering data-driven discoveries in deep-time Earth(DE)include:substantial volumes of DE data are not digitized;many DE databases do not adhere to FAIR(findable,accessible,interoperable and reusable)principles;we lack a systematic knowledge graph for DE;existing DE databases are geographically heterogeneous;a significant fraction of DE data is not in open-access formats;tailored tools are needed.These challenges motivate the Deep-Time Digital Earth(DDE)program initiated by the International Union of Geological Sciences and developed in cooperation with national geological surveys,professional associations,academic institutions and scientists around the world.DDE’s mission is to build on previous research to develop a systematic DE knowledge graph,a FAIR data infrastructure that links existing databases and makes dark data visible,and tailored tools for DE data,which are universally accessible.DDE aims to harmonize DE data,share global geoscience knowledge and facilitate data-driven discovery in the understanding of Earth’s evolution. | Chengshan Wang Robert MHazen Qiuming Cheng Michael HStephenson Chenghu Zhou Peter Fox Shu-zhong Shen Roland Oberhansli Zengqian Hou Xiaogang Ma Zhiqiang Feng Junxuan Fan Chao Ma Xiumian Hu Bin Luo Juanle Wang Craig M.Schiffries | 2021 | National Science Review2021，8，9： | 14 |
| 2 | COVID-19: Challenges to GIS with Big Data显示文摘The outbreak of the 2019 novel coronavirus disease(COVID-19)has caused more than 100,000 people infected and thousands of deaths.Currently,the number of infections and deaths is still increasing rapidly.COVID-19 seriously threatens human health,production,life,social functioning and international relations.In the fight against COVID-19,Geographic Information Systems(GIS)and big data technologies have played an important role in many aspects,including the rapid aggregation of multi-source big data,rapid visualization of epidemic information,spatial tracking of confirmed cases,prediction of regional transmission,spatial segmentation of the epidemic risk and prevention level,balancing and management of the supply and demand of material resources,and socialemotional guidance and panic elimination,which provided solid spatial information support for decision-making,measures formulation,and effectiveness assessment of COVID-19 prevention and control.GIS has developed and matured relatively quickly and has a complete technological route for data preparation,platform construction,model construction,and map production.However,for the struggle against the widespread epidemic,the main challenge is finding strategies to adjust traditional technical methods and improve speed and accuracy of information provision for social management.At the data level,in the era of big data,data no longer come mainly from the government but are gathered from more diverse enterprises.As a result,the use of GIS faces difficulties in data acquisition and the integration of heterogeneous data,which requires governments,businesses,and academic institutions to jointly promote the formulation of relevant policies.At the technical level,spatial analysis methods for big data are in the ascendancy.Currently and for a long time in the future,the development of GIS should be strengthened to form a data-driven system for rapid knowledge acquisition,which signifies ts that GIS should be used to reinforce the social operation parameterization of models and methods,especially when providing support for social management. | Chenghu Zhou Fenzhen Su Tao Pei An Zhang Yunyan Du Bin Luo Zhidong Cao Juanle Wang Wen Yuan Yunqiang Zhu Ci Song Jie Chen Jun Xu Fujia Li Ting Ma Lili Jiang Fengqin Yan Jiawei Yi Yunfeng Hu Yilan Liao Han Xiao | 2020 | Geography and Sustainability2020，1，1： | 13 |
| 3 | A study on the organizational architecture and standard system of the data sharing network of Earth System Science in China显示文摘 | Wang Juanle Sun Jiulin Zhu Yunqiang | 2013 | Data Science Journal2013，，12： | 1 |
| 4 | TheArtandSeieneeofCompeteneyMo dels显示文摘 | Sanehez Juanl | | 0，，02： | 1 |
| 5 | Degradation kinetics of atrazine and it' s degradation products with ozone and OH radicals: a predictive tool for drinking water treatment 显示文摘 | Juanl Acero Konrao Stemmler Urs Von Gunton | 2000 | Environ Sci Technol2000，34，9： | 1 |
| 6 | TPX2 in malignantly transformed human bronchial epithelial cells by anti-benzo[ a ]pyrene-7,8-diol-9,10-epoxide显示文摘 | Lijuan Zhang He Huang Luyao Deng Ming Chu Lan Xu Juanling Fu Yunlan Zhu Xiuchun Zhang Shulin Liu Zongcan Zhou Yuedan Wang | 2008 | Toxicology2008，，1： | 1 |
| 7 | Silica Sol-Gel Immobilized Amperometric Biosensors for Hydrogen Peroxide 显示文摘 | Juanl L Swee N T Hailin G | 1996 | Anal Chim Acta1996，335，： | 1 |
| 8 | GC-MS Analysis and Antibacterial Activity Study of Volatile Oil from 11 Kinds of Aurantii Fructus Immaturus Processed Products显示文摘[Objectives]To study the volatile components and antibacterial effects of 11 kinds of Aurantii Fructus Immaturus processed products.[Methods]11 kinds of Aurantii Fructus Immaturus processed products were obtained according to the traditional processing method,the volatile oil was extracted by steam distillation,and the composition of volatile oil in the 11 kinds of processed products was analyzed by gas chromatography-mass spectrometry(GC-MS).the relative percentage content of each component in these 11 kinds of processed products was determined using the peak area normalization.The drug sensitivity activity of the volatile oil of these 11 kinds of processed products was tested using the K-B paper diffusion method and the minimum inhibition volume fraction of volatile oil of these 11 kinds of processed products was tested using the microdilution method.[Results]The highest yield of volatile oil of 11 kinds of these processed products was baking(5.193%),and the lowest was stir-bake to scorch(1.998%).A total of 36 chemical components were identified from the volatile oils of these 11 kinds of processed products.The components with the most volatile oil were stir-bake to scorch(24 kinds),and the components with the least volatile oil were the method of processing with rice-washed water(15 kinds).They contain 8 kinds of common chemical components,such as limonene,linalool,myrcene,α-pinene.The highest content of limonene came from processing with honey(60.93%),the lowest came from processing with rice-washed water(55.25%);the highest content of linalool came from processing with rice-washed water(7.139%),the lowest came from processing with honey(5.436%);the highest content of myrcene came from processing with honey(1.899%),the lowest came from stir-bake to scorch(1.632%);the highest content ofα-pinene came from raw Aurantii Fructus Immaturus(2.355%),and the lowest came from stir-bake to scorch(1.618%).The volatile oil of these 11 kinds of Aurantii Fructus Immaturus processed products has good antibacterial effect on Escherichia coli and Staphylococcus aureus.[Conclusions]The oil yields of volatile oils of 11 kinds of Aurantii Fructus Immaturus processed products are different,the content of limonene is significantly different,and the changes of other chemical components and their contents are not significantly different.The volatile oil of 11 kinds of Aurantii Fructus Immaturus processed products has certain antibacterial effect. | Liuping WANG Juanling HUANG Baoping TAO Yaohua LI Zhenzhen PAN | 2020 | Medicinal Plant2020，11，4： | 0 |
| 9 | Classification framework and semantic labeling for Big Earth Data显示文摘Big Earth Data refers to the multidimensional integration and association of scientific data,including geography,resources,environment,ecology,and biology.An effective data classification system and label management strategy are important foundations for long-term management of data resources.The objective of this study was to construct a classification system and realize multidimensional semantic data label management for the Big Earth Data Science Engineering Program(CASEarth).This study constructed two sets of classification and coding systems that realize classification by mapping each other;namely,the geosphere-level and Sustainable Development Goals(SDGs)indicator classifications.This technique was based on natural language processing technology and solved problems with subject-word segmentation,weight calculation,and dynamic matching.A prototype system for classification and label management was constructed based on existing CASEarth datasets of more than 1,100.Furthermore,we expect our study to provide the methodology and technical support for useroriented classification and label management services for Big Earth Data. | Juanle Wang Kun Bu Dongmei Yan Jingyue Wang Bowen Duan Min Zhang and Guojin He | 2023 | Big Earth Data2023，7，3： | 0 |
| 10 | Sustainability of Rail Transport in Africa:A Case Study of Kenya’s Standard Gauge Railway显示文摘Rail transport has a crucial role in shaping the transportation system in a country.For instance,rail transport has played a significant role in movement of goods and people in Kenya and in Africa as whole for almost a century.By 1990,however,the industry started to decline due to competition from more reliable and efficient means of transportation(buses and trucks).Passenger services had almost disappeared(accounting for less than 1%of total traffic).Against this background,this research paper analyses consideration factors for sustainability of the SGR(Standard Gauge Railway)infrastructure in Kenya.A case study method was selected and mainly used the desk top research approach to collect secondary data that were drawn from railway institution records,railway journals,railway magazines,internet and other secondary sources from projects,contract documents and government reports.The research results were used to formulate a roadmap for sustainable railway infrastructure projects.The research also discusses the outcomes and makes some recommendations for railway transportation infrastructure projects sustainability. | Mugo Kenneth Kamumbu Juanling Zhao | 2020 | Journal of Environmental Science and Engineering(A)2020，9，1： | 0 |
| 11 | Spatial-temporal variation and attribution of salinization in the Yellow River Basin from 2015 to 2020显示文摘Under the pressure of SDG15.3.1 compliance,it is imperative to solve the land salinization degradation problem in the Yellow River Basin as China’s granary.From the view of geographical scale,six zoning units were divided in the Yellow River Basin with‘climate-meteorology-geomorphology’as the main controlling factor,and a salinization inversion model was constructed for each zoning unit.Appropriate surface parameters were selected to construct a three-dimensional feature space according to the individual geographical zones.Based on the cloud data processing capability of the Google Earth Engine platform,a feature space inversion process was applied for automatic inversion of salinization.Salinization distribution maps of the Yellow River Basin in 2015 and 2020 were obtained at 30 m resolution by classifying the salinization inversion result.The distribution and spatiotemporal variation of salinization as well as the causes of salinization were analyzed.Reasonable prevention and control suggestions were subsequently proposed.This study could also be scaled up to larger and more complex geographical regions. | Hong Mengmeng Wang Juanle Han Baomin | 2023 | International Journal of Digital Earth2023，16，1： | 0 |
| 12 | Dynamic evolution of spring sand and dust storms and cross-border response in Mongolian plateau from 2000 to 2021显示文摘According to the United Nations Sustainable Development Goals(SDG 15.3),frequent sand and dust storms(SDSs)in the spring are a long-term challenge to the prevention and control of land degradation on the Mongolian plateau.In this study,MODIS remote sensing data are used to monitor and analyse SDS events on the Mongolian Plateau.The annual distribution of spring SDSs(March to May)from 2000 to 2021 are obtained based on the dust storm detection index.The overall classification accuracy is 85.24%and the kappa coefficient is 0.7636.Results show a decrease in the overall frequency of SDS events,where storm events in 2000–2010 are significantly higher than those in the second decade.The cross-border regions between China and Mongolia appear to be SDS intensity centers,particularly those in southern Mongolia.Precipitation exhibits a strong negative correlation with the area affected by SDS,and the correlation coefficient is–0.72.The increase in barren and sand contributes primarily to the increase in SDS,whereas wind prevention and sand control projects undertaken by the Mongolian and Chinese governments promote regional restoration.Policies pertaining to cross-board sandstorm responses on the Mongolian Plateau are recommended. | Yu Zhang Juanle Wang Altansukh Ochir Sonomdagva Chonokhuu Chuluun Togtokh | 2023 | International Journal of Digital Earth2023，16，1： | 0 |
您所在的机构暂未开通此部分的功能，请联系管理员