Zobrazeno 1 - 10
of 147
pro vyhledávání: '"GUAN Yingjun"'
Publikováno v:
Renmin Zhujiang, Vol 42 (2021)
In view of the problem that there is a large difference in the performance degradation test results of sand and mudstone and the lack of an analytical model for the weakening of bearing capacity of rock-socketed piles under the periodic saturated wat
Externí odkaz:
https://doaj.org/article/b8dbdf4367e848769b235fce0ff2b23c
Autor:
Liu, Xiaofeng, Huang, Yuwei, Zhao, Xianchen, Guan, Yingjun, Li, Yanchun, Yuan, Lei, Wang, Chuncheng, Ma, Chao, Ma, Enlong
Publikováno v:
In Bioorganic Chemistry December 2024 153
Autor:
Li, Yanbin, Zhang, Huimin, Guan, Yingjun, Cheng, Guoyi, Li, Zhaohong, Li, Zhuang, Cao, Mengxi, Yin, Yongguang, Hu, Ligang, Shi, Jianbo, Chen, Baowei
Publikováno v:
In Journal of Hazardous Materials 5 September 2024 476
Autor:
Wang, Qingyun, Li, Manling, Wang, Xuan, Parulian, Nikolaus, Han, Guangxing, Ma, Jiawei, Tu, Jingxuan, Lin, Ying, Zhang, Haoran, Liu, Weili, Chauhan, Aabhas, Guan, Yingjun, Li, Bangzheng, Li, Ruisong, Song, Xiangchen, Fung, Yi R., Ji, Heng, Han, Jiawei, Chang, Shih-Fu, Pustejovsky, James, Rah, Jasmine, Liem, David, Elsayed, Ahmed, Palmer, Martha, Voss, Clare, Schneider, Cynthia, Onyshkevych, Boyan
To combat COVID-19, both clinicians and scientists need to digest vast amounts of relevant biomedical knowledge in scientific literature to understand the disease mechanism and related biological functions. We have developed a novel and comprehensive
Externí odkaz:
http://arxiv.org/abs/2007.00576
We created this EVIDENCEMINER system for automatic textual evidence mining in COVID-19 literature. EVIDENCEMINER is a web-based system that lets users query a natural language statement and automatically retrieves textual evidence from a background c
Externí odkaz:
http://arxiv.org/abs/2004.12563
We created this CORD-NER dataset with comprehensive named entity recognition (NER) on the COVID-19 Open Research Dataset Challenge (CORD-19) corpus (2020-03-13). This CORD-NER dataset covers 75 fine-grained entity types: In addition to the common bio
Externí odkaz:
http://arxiv.org/abs/2003.12218
We analyze nearly 20 million geocoded PubMed articles with author affiliations. Using K-means clustering for the lower 48 US states and mainland China, we find that the average published paper is within a relatively short distance of a few centroids.
Externí odkaz:
http://arxiv.org/abs/1907.05525
Autor:
Guan, Yingjun1 (AUTHOR), Huang, Weiqi1 (AUTHOR), Wang, Hao1 (AUTHOR), Lu, Huanquan1 (AUTHOR), Yang, Huisheng2 (AUTHOR) ciomp_yhsh@126.com
Publikováno v:
Scientific Reports. 12/16/2023, Vol. 13 Issue 1, p1-24. 24p.
Akademický článek
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Publikováno v:
In Ecotoxicology and Environmental Safety 15 December 2019 185