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| 1 | A spike protein S2 antibody efficiently neutralizes the Omicron variant显示文摘The severe acute respiratory syndrome coronavirus 2(SARS-CoV-2)variant B.1.1.529,also named Omicron,is becoming the main circulating strain in many countries worldwide and brings new challenges to preventing COVID-19[1,2,3,4,5].The latest data show that the Omicron variant contains more than 50 mutations.Among them,there are 32 mutations in the spike protein[6],which is the key component that determines the infectivity and antigenicity of the virus.Furthermore,15 mutations are located in the receptor-binding domain(RBD),which is key for viral-cell interactions mediated by angiotensin-converting enzyme 2(ACE-2)[7,8]. | Jia Hu Xiang Chen Xingbing Lu Lijuan Wu Liyuan Yin Lingling Zhu Hao Liang Feng Xu Qinghua Zhou | 2022 | Cellular & Molecular Immunology2022，19，5： | 0 |
| 2 | Low-field NMR application in the characterization of CO_(2)geological storage and utilization related to shale gas reservoirs:a brief review显示文摘CO_(2)geological storage and utilization(CGSU)is considered a far-reaching technique to meet the demand of increasing energy supply and decreasing CO_(2)emissions.For CGSUs related to shale gas reservoirs,experimental investigations have attracted variable methodologies,among which low-field NMR(LF-NMR)is a promising method and is playing an increasingly key role in reservoir characterization.Herein,the application of this nondestructive,sensitive,and quick LF-NMR technique in characterizing CGSU behavior in shale gas reservoirs is reviewed.First,the basic principle of LF-NMR for 1H-fluid detection is introduced,which is the theoretical foundation of the reviewed achievements in this paper.Then,the reviewed works are related to the LF-NMR-based measurements of CH_(4)adsorption capacity and the CO_(2)-CH_(4)interaction in shale,as well as the performance on CO_(2)sequestration and simultaneous enhanced gas recovery from shale.Basically,the reviewed achievements have exhibited a large potential for LF-NMR application in CGSUs related to shale gas reservoirs,although some limitations and deficiencies still need to be improved.Accordingly,some suggestions are proposed for a more responsible development of the LF-NMR technique.Hopefully,this review is helpful in promoting the expanding application of the LF-NMR technique in CGSU implementation in shale gas reservoirs. | Zhaohui LU Ke LI Xingbing LIU Peng ZHAO Jun LIU | 2023 | Frontiers of Earth Science2023，17，3： | 0 |
| 3 | An error analysis and optimization method for combined measurement with binocular vision显示文摘The accurate measurement of surfaces of large aviation components is vital for the assessment of manufacturing and assembly quality of such components.To satisfy the measurement requirement of large-size components,most current researches pay more attention to combined measurement methods utilizing different measuring instruments,but the related researches on error analysis and optimization methods are not taken enough attention.This paper proposes a combined laser-assisted measurement method with feature enhancement techniques,and it also develops an error propagation model of the main factors affecting the overall measurement error in detail.Firstly,the surface of a large-size component is measured by the measurement system at multiple stations.Secondly,a control point coordinate system is established as a bridge to unify all local measurement data into the global coordinate system.To improve the overall measurement accuracy,the pixel extraction error as a key factor causing the overall measurement error is analyzed in detail.Next,the error propagation model is established,and some optimization strategies of layout for minimizing measurement error and transformation error are researched.Finally,experiments are carried out to verify the effectiveness of the proposed method.The results show that the measurement error of the proposed method reaches 0.073%and 0.14%with a 1 D standard ruler and a flat plate,respectively. | Yongkang LU Wei LIU Yang ZHANG Junqing LI Weiqi LUO Yanze ZHANG Hongwen XINGb Lei ZHANG | 2021 | Chinese Journal of Aeronautics2021，34，10： | 0 |
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