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后COVID-19时代采矿业面临大规模挑战 快报文章
地球科学快报,2021年第9期
作者:  刘文浩
Microsoft Word(17Kb)  |  收藏  |  浏览/下载:417/0  |  提交时间:2021/05/08
mining  copper ore  COVID-19  
GlobalData:2020年全球铂金需求将下降7% 快报文章
地球科学快报,2020年第22期
作者:  刘学
Microsoft Word(14Kb)  |  收藏  |  浏览/下载:396/0  |  提交时间:2020/11/25
platinum  demand  COVID-19  China  
OIES发布报告预测疫情后中国石油需求形势 快报文章
地球科学快报,2020年第17期
作者:  刘文浩
Microsoft Word(18Kb)  |  收藏  |  浏览/下载:329/0  |  提交时间:2020/09/09
Covid-19  Oil  China  OIES  
麦肯锡分析新冠肺炎后的油气行业的未来之路 快报文章
地球科学快报,2020年第13期
作者:  王立伟
Microsoft Word(17Kb)  |  收藏  |  浏览/下载:376/0  |  提交时间:2020/07/09
Oil  gas  COVID-19  
CHLOROQUINE HYPE DERAILS CORONAVIRUS DRUG TRIALS 期刊论文
NATURE, 2020, 580 (7805) : 573-573
作者:  Hu, Minjie;  Zheng, Xiaobin;  Fan, Chen-Ming;  Zheng, Yixian
收藏  |  浏览/下载:16/0  |  提交时间:2020/07/03

With politicians touting the potential benefits of malaria drugs to fight COVID-19, some people are turning away from clinical trials of other therapies.


With politicians touting the potential benefits of malaria drugs to fight COVID-19, some people are turning away from clinical trials of other therapies.


  
OIES研判新冠疫情对全球天然气市场的影响 快报文章
地球科学快报,2020年第11期
作者:  刘文浩
Microsoft Word(33Kb)  |  收藏  |  浏览/下载:340/0  |  提交时间:2020/06/09
Gas  COVID-19  
OPEN SCIENCE TAKES ON COVID-19 期刊论文
NATURE, 2020, 581 (7806) : 109-110
作者:  Mudelsee, Manfred;  Borngen, Michael;  Tetzlaff, Gerd;  Grunewald, Uwe
收藏  |  浏览/下载:11/0  |  提交时间:2020/07/03

Data sharing, open-source designs for medical equipment, and hobbyists are all being harnessed to combat COVID-19.


Data sharing, open-source designs for medical equipment, and hobbyists are all being harnessed to combat COVID-19.


  
IEA关注新冠病毒危机对全球能源需求的影响 快报文章
地球科学快报,2020年第10期
作者:  王立伟
Microsoft Word(19Kb)  |  收藏  |  浏览/下载:339/0  |  提交时间:2020/05/25
COVID-19  energy  demand  
Population flow drives spatio-temporal distribution of COVID-19 in China 期刊论文
NATURE, 2020
作者:  Fernandez, Diego Carlos;  Komal, Ruchi;  Langel, Jennifer;  Ma, Jun;  Duy, Phan Q.;  Penzo, Mario A.;  Zhao, Haiqing;  Hattar, Samer
收藏  |  浏览/下载:69/0  |  提交时间:2020/07/03

Sudden, large-scale and diffuse human migration can amplify localized outbreaks of disease into widespread epidemics(1-4). Rapid and accurate tracking of aggregate population flows may therefore be epidemiologically informative. Here we use 11,478,484 counts of mobile phone data from individuals leaving or transiting through the prefecture of Wuhan between 1 January and 24 January 2020 as they moved to 296 prefectures throughout mainland China. First, we document the efficacy of quarantine in ceasing movement. Second, we show that the distribution of population outflow from Wuhan accurately predicts the relative frequency and geographical distribution of infections with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) until 19 February 2020, across mainland China. Third, we develop a spatio-temporal '  risk source'  model that leverages population flow data (which operationalize the risk that emanates from epidemic epicentres) not only to forecast the distribution of confirmed cases, but also to identify regions that have a high risk of transmission at an early stage. Fourth, we use this risk source model to statistically derive the geographical spread of COVID-19 and the growth pattern based on the population outflow from Wuhan  the model yields a benchmark trend and an index for assessing the risk of community transmission of COVID-19 over time for different locations. This approach can be used by policy-makers in any nation with available data to make rapid and accurate risk assessments and to plan the allocation of limited resources ahead of ongoing outbreaks.


Modelling of population flows in China enables the forecasting of the distribution of confirmed cases of COVID-19 and the identification of areas at high risk of SARS-CoV-2 transmission at an early stage.


  
Massively multiplexed nucleic acid detection with Cas13 期刊论文
NATURE, 2020, 582 (7811) : 277-+
作者:  Mahato, Biraj;  Kaya, Koray Dogan;  Fan, Yan;  Sumien, Nathalie;  Shetty, Ritu A.;  Zhang, Wei;  Davis, Delaney;  Mock, Thomas;  Batabyal, Subrata;  Ni, Aiguo;  Mohanty, Samarendra;  Han, Zongchao;  Farjo, Rafal;  Forster, Michael J.;  Swaroop, Anand;  Chavala, Sai H.
收藏  |  浏览/下载:62/0  |  提交时间:2020/07/03

CRISPR-based nucleic acid detection is used in a platform that can simultaneously detect 169 human-associated viruses in multiple samples, providing scalable, multiplexed pathogen detection aimed at routine surveillance for public health.


The great majority of globally circulating pathogens go undetected, undermining patient care and hindering outbreak preparedness and response. To enable routine surveillance and comprehensive diagnostic applications, there is a need for detection technologies that can scale to test many samples(1-3)while simultaneously testing for many pathogens(4-6). Here, we develop Combinatorial Arrayed Reactions for Multiplexed Evaluation of Nucleic acids (CARMEN), a platform for scalable, multiplexed pathogen detection. In the CARMEN platform, nanolitre droplets containing CRISPR-based nucleic acid detection reagents(7)self-organize in a microwell array(8)to pair with droplets of amplified samples, testing each sample against each CRISPR RNA (crRNA) in replicate. The combination of CARMEN and Cas13 detection (CARMEN-Cas13) enables robust testing of more than 4,500 crRNA-target pairs on a single array. Using CARMEN-Cas13, we developed a multiplexed assay that simultaneously differentiates all 169 human-associated viruses with at least 10 published genome sequences and rapidly incorporated an additional crRNA to detect the causative agent of the 2020 COVID-19 pandemic. CARMEN-Cas13 further enables comprehensive subtyping of influenza A strains and multiplexed identification of dozens of HIV drug-resistance mutations. The intrinsic multiplexing and throughput capabilities of CARMEN make it practical to scale, as miniaturization decreases reagent cost per test by more than 300-fold. Scalable, highly multiplexed CRISPR-based nucleic acid detection shifts diagnostic and surveillance efforts from targeted testing of high-priority samples to comprehensive testing of large sample sets, greatly benefiting patients and public health(9-11).