Zobrazeno 1 - 10
of 10
pro vyhledávání: '"Bingguang Chen"'
Publikováno v:
Materials, Vol 16, Iss 6, p 2193 (2023)
As a new type of pre-reinforcement material for tunnel faces, glass fiber-reinforced polymer (GFRP) bolts can effectively and safely improve the stability of tunnel faces in soft surrounding rocks and speed up excavation. Therefore, in this paper, sy
Externí odkaz:
https://doaj.org/article/bbb559e90b0242fc966b3f03f72a7f1c
Autor:
Jinrong Xie, Weixiang Qi, Lu Cao, Yuting Tan, Jin Huang, Xiaodong Gu, Bingguang Chen, Peipei Shen, Yutian Zhao, Ying Zhang, Qingwen Zhao, Hecheng Huang, Yubin Wang, Haicheng Fang, Zhenjun Jin, Hui Li, Xuehong Zhao, Xiaofang Qian, Feifei Xu, Dan Ou, Shubei Wang, Cheng Xu, Min Li, Zefei Jiang, Yu Wang, Xiaobo Huang, Jiayi Chen
Publikováno v:
Frontiers in Oncology, Vol 11 (2021)
ObjectiveThe outbreak of COVID-19 pandemic has greatly impacted on radiotherapy (RT) strategy for breast cancer patients, which might lead to increased distressing psychological symptoms. We performed a multi-center cross-section survey to investigat
Externí odkaz:
https://doaj.org/article/3d711dce549943e8863025c572e9dae4
Publikováno v:
Materials, Vol 15, Iss 15, p 5103 (2022)
Steel fibers are widely used because they can effectively improve the tensile, compressive and flexural properties of concrete structures. The selection of steel fiber dosage and aspect ratio at high temperature has an important impact on the flexura
Externí odkaz:
https://doaj.org/article/6e4a63bf2f074c128f54ce9158031598
Publikováno v:
Bulletin of Engineering Geology and the Environment. 82
Autor:
Xuehong Zhao, Weixiang Qi, Fei-Fei Xu, Peipei Shen, Haicheng Fang, Zhenjun Jin, Jin Huang, Ying Zhang, Hui Li, Qingwen Zhao, Yu Wang, Xiaofang Qian, Xiaodong Gu, Jinrong Xie, Yu-Ting Tan, Dan Ou, Cheng Xu, Jiayi Chen, Hecheng Huang, Zefei Jiang, Lu Cao, Min Li, Yubin Wang, Shu-Bei Wang, Xiaobo Huang, Bingguang Chen
Publikováno v:
Cancer Research. 81:SS2-07
Background The outbreak of COVID-19 pandemic in China has greatly impacted the radiotherapy (RT) strategy for breast cancer (BC) patients, which might lead to an increased distressing psychological symptom. Thus, we perform a multi-center cross-secti
Autor:
Rui Zhang, Peiyan Hu, Qi Meng, Yue Wang, Rongchan Zhu, Bingguang Chen, Zhi-Ming Ma, Tie-Yan Liu
We present the deep random vortex network (DRVN), a novel physics-informed framework for simulating and inferring the fluid dynamics governed by the incompressible Navier-Stokes equations. Unlike the existing physics-informed neural network (PINN), w
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8239588ee7cb99ce560e1e51f3122769
https://doi.org/10.1063/5.0110342
https://doi.org/10.1063/5.0110342
Autor:
Bingguang Chen, Kai Liu, Wen-Sheng Wang, Yingjia Li, Youyong Kong, Hui Chen, Ge Wen, Yanjia Deng, Jingyu Zhang, Dong-Liang Cheng
Publikováno v:
Schizophrenia Research. 206:103-110
Previous studies suggest that schizophrenia-related visual perceptual abnormalities are primarily attributed to deficits of the dorsal rather than ventral visual pathway. In this study, we comparatively explored changes in dorsal and ventral networks
Autor:
Bingguang Chen
In this paper, we prove a central limit theorem and establish a moderate deviation principle for the two-dimensional stochastic Navier-Stokes equations with anisotropic viscosity. The proof for moderate deviation principle is based on the weak conver
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::dabbfe4cb01905b314602cf98da6c37e
Publikováno v:
Knowledge Science, Engineering and Management ISBN: 9783319993645
KSEM (1)
KSEM (1)
Bayesian networks (BNs) is a dominate model for representing causal knowledge with uncertainty. Causal discovery with BNs requiring large amount of training data for learning BNs structure. When confronted with small sample scenario the learning task
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e99777a6afbbe85ca5d239f7999962d6
https://doi.org/10.1007/978-3-319-99365-2_31
https://doi.org/10.1007/978-3-319-99365-2_31
Publikováno v:
Proceedings of the 2016 4th International Conference on Machinery, Materials and Information Technology Applications.