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Identification of potential cross-protective epitope between a new type of coronavirus(2019-nCoV)and severe acute respiratory syndrome virus 被引量:11
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作者 Tianyi Qiu Tiantian Mao +5 位作者 Yuan Wang mengdi zhou Jingxuan Qiu Jianwei Wang Jianqing Xu Zhiwei Cao 《Journal of Genetics and Genomics》 SCIE CAS CSCD 2020年第2期115-117,共3页
Recently,a new type of unknown virus causing severe acute res-piratory infection was reported in Wuhan city,Hubei province,China(WHO,2020b).Infection of this virus was first reported in December 2019,and origin of the... Recently,a new type of unknown virus causing severe acute res-piratory infection was reported in Wuhan city,Hubei province,China(WHO,2020b).Infection of this virus was first reported in December 2019,and origin of the virus was traced back to a large seafood/wide animal market in Wuhan city.The serious clinical symptoms of the viral infection,including fever,dry cough,dys-pnea,and pneumonia,may result in progressive respiratory failure and even death.Moreover,the quick spread of the virus has caused an epidemic in China,as well as infection cases worldwide.The whole-genome sequence of Wuhan new virus(WH-Human_.1)was first released on January 10,2020(Zhang,2020),followed by additional ones released in Global Initiative on Sharing All Influ-enza Data(GISAID)(Shu and McCauley,2017).Later,this new virus was determined and announced as a new type of coronavirus(CoV;2019-nCoV)by the World Health Organization(WHO,2020a). 展开更多
关键词 protective WUHAN ACUTE
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A bifunctional MnO_x@PTFE catalytic membrane for efficient low temperature NO_x-SCR and dust removal 被引量:5
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作者 Shasha Feng mengdi zhou +2 位作者 Feng Han Zhaoxiang Zhong Weihong Xing 《Chinese Journal of Chemical Engineering》 SCIE EI CAS CSCD 2020年第5期1260-1267,共8页
Low-temperature selective catalytic reduction of NOx combined with dust removal technique due to its energy conservation characteristic has been attracted much attention for fume purification.In this work,the MnOx wra... Low-temperature selective catalytic reduction of NOx combined with dust removal technique due to its energy conservation characteristic has been attracted much attention for fume purification.In this work,the MnOx wrapped PTFE membrane with efficient dust removal and low-temperature NH3-SCR has been prepared with a facile route.MnOxwith different crystal structures was uniformly grown around the PTFE fibrils through water bath.The flower-sphere-like MnOx@PTFE(O-MnOx@PTFE)and lamellar-interlaced ripple-like MnOx@PTFE(W-MnOx@PTFE)have large specific surface area which is favorable for enhancing catalytic performance.Also,the uniformly wrapped W-MnOxaround the PTFE fibrils optimized the pore structure for ultrafine dust capture.The membrane can almost 100%reject particles that are smaller than 1.0μm with a low filtration resistance.Meanwhile,W-MnOx@PTFE with more surface chemisorbed oxygen has the best NO conversion efficiency of 100%at a comparatively low and wide activity temperature window of 160–210°C,which is far to the thermal limitation of the PTFE.Therefore,this efficient and energy conserving membrane has a bright application prospects for tail gas treatment compared to the original treatment process. 展开更多
关键词 MnO_x PTFE Catalytic membrane LOW-TEMPERATURE SCR
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Research on simulation of gun muzzle flow field empowered by artificial intelligence 被引量:3
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作者 mengdi zhou Linfang Qian +3 位作者 Congyong Cao Guangsong Chen Jin Kong Ming-hao Tong 《Defence Technology(防务技术)》 SCIE EI CAS CSCD 2024年第2期196-208,共13页
Artificial intelligence technology is introduced into the simulation of muzzle flow field to improve its simulation efficiency in this paper.A data-physical fusion driven framework is proposed.First,the known flow fie... Artificial intelligence technology is introduced into the simulation of muzzle flow field to improve its simulation efficiency in this paper.A data-physical fusion driven framework is proposed.First,the known flow field data is used to initialize the model parameters,so that the parameters to be trained are close to the optimal value.Then physical prior knowledge is introduced into the training process so that the prediction results not only meet the known flow field information but also meet the physical conservation laws.Through two examples,it is proved that the model under the fusion driven framework can solve the strongly nonlinear flow field problems,and has stronger generalization and expansion.The proposed model is used to solve a muzzle flow field,and the safety clearance behind the barrel side is divided.It is pointed out that the shape of the safety clearance under different launch speeds is roughly the same,and the pressure disturbance in the area within 9.2 m behind the muzzle section exceeds the safety threshold,which is a dangerous area.Comparison with the CFD results shows that the calculation efficiency of the proposed model is greatly improved under the condition of the same calculation accuracy.The proposed model can quickly and accurately simulate the muzzle flow field under various launch conditions. 展开更多
关键词 Muzzle flow field Artificial intelligence Deep learning Data-physical fusion driven Shock wave
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基于深度学习的车载炮驾驶室表面冲击载荷快速预测方法
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作者 周梦笛 钱林方 +3 位作者 曹从咏 陈光宋 徐亚栋 魏胜程 《Acta Mechanica Sinica》 SCIE EI CAS CSCD 2024年第4期99-112,共14页
在车载炮驾驶室拓扑优化设计和刚强度分析计算中,需要明确大量的、不同射击条件下的冲击载荷.如何快速获取驾驶室表面的冲击载荷是车载炮设计中尚未解决的难题之一.本文将深度学习方法引入到驾驶室表面冲击载荷的求解中,基于卷积-多维特... 在车载炮驾驶室拓扑优化设计和刚强度分析计算中,需要明确大量的、不同射击条件下的冲击载荷.如何快速获取驾驶室表面的冲击载荷是车载炮设计中尚未解决的难题之一.本文将深度学习方法引入到驾驶室表面冲击载荷的求解中,基于卷积-多维特征LSTM神经网络,提出了一种驾驶室表面冲击载荷快速预测方法,实现了不同发射条件下驾驶室表面冲击载荷计算,求解速度接近实时级别.算例结果表明,深度学习模型的求解精度与传统CFD仿真精度相当,但求解耗时在毫秒级,大大提高了计算效率,具备离线训练、在线计算的潜力.且当驾驶室形貌特征轻微变化时,本文模型依然适用.本文成果可快速为驾驶室刚强度校核和拓扑优化提供载荷条件,有助于缩短车载炮研发周期,为车载炮系统的数字孪生模型构建奠定了基础. 展开更多
关键词 深度学习 冲击载荷 驾驶室 CFD仿真 拓扑优化 多维特征 刚强度分析 在线计算
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