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您的检索式：作者名="Wanglong WU"
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| 1 | VIPLFaceNet: an open source deep face recognition SDK显示文摘 | Xin LIU Meina KAN Wanglong WU Shiguang SHAN Xilin CHEN | 2017 | Frontiers of Computer Science2017，11，2： | 15 |
| 2 | Implicit discontinuous Galerkin method on agglomerated high-order grids for 3D simulations显示文摘High quality of geometry representation is regarded essential for high-order methods to maintain their high-order accuracy. An agglomerated high-order mesh generating method is investigated in combination with discontinuous Galerkin(DG) method for solving the 3D compressible Euler and Navier-Stokes equations. In this method, a fine linear mesh is first generated by standard commercial mesh generation tools. By taking advantage of an agglomeration method, a quadratic high-order mesh is quickly obtained, which is coarse but provides a high-quality geometry representation, thus very suitable for high-order computations. High-order discretizations are performed on the obtained grids with DG method and the discretized system is treated fully implicitly to obtain steady state solutions. Numerical experiments on several flow problems indicate that the agglomerated high-order mesh works well with DG method in dealing with flow problems of curved geometries. It is also found that with a fully implicit discretized system and a p-sequencing method, the DG method can achieve convergence state within several time steps which shows significant efficiency improvements compared to its explicit counterparts. | Qin Wanglong Lyu Hongqiang Wu Yizhao Zhou Shijie Chen Zhengwu | 2016 | Chinese Journal of Aeronautics2016，29，6： | 1 |
| 3 | Gut microbiota,inflammation,and molecular signatures of host response to infection显示文摘Gut microbial dysbiosis has been linked to many noncommunicable diseases.However,little is known about specific gut microbiota composition and its correlated metabolites associated with molecular signatures underlying host response to infection.Here,we describe the construction of a proteomic risk score based on 20 blood proteomic biomarkers,which have recently been identified as molecular signatures predicting the progression of the COVID-19.We demonstrate that in our cohort of 990 healthy individuals without infection,this proteomic risk score is positively associated with proinflammatory cytokines mainly among older,but not younger,individuals.We further discover that a core set of gut microbiota can accurately predict the above proteomic biomarkers among 301 individuals using a machine learning model and that these gut microbiota features are highly correlated with proinflammatory cytokines in another independent set of 366 individuals.Fecal metabolomics analysis suggests potential amino acid-related pathways linking gut microbiota to host metabolism and inflammation.Overall,our multi-omics analyses suggest that gut microbiota composition and function are closely related to inflammation and molecular signatures of host response to infection among healthy individuals.These results may provide novel insights into the cross-talk between gut microbiota and host immune system. | Wanglong Gou Yuanqing Fu Liang Yue Geng-Dong Chen Xue Cai Menglei Shuai Fengzhe Xu Xiao Yi Hao Chen Yi Zhu Mian-Li Xiao Zengliang Jiang Zelei Miao Congmei Xiao Bo Shen Xiaomai Wu Haihong Zhao Wenhua Ling Jun Wang Yu-Ming Chen Tiannan Guo Ju-Sheng Zheng | 2021 | Journal of Genetics and Genomics2021，48，9： | 1 |
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