Zobrazeno 1 - 10
of 130
pro vyhledávání: '"Bowen Tang"'
Publikováno v:
AIMS Mathematics, Vol 9, Iss 6, Pp 13607-13623 (2024)
We consider the inverse scattering problem of reconstructing the boundary of an obstacle by using far-field data. With the plane wave as the incident wave, a priori information of the impenetrable obstacle can be obtained via the linear sampling meth
Externí odkaz:
https://doaj.org/article/3e16d82f2ebb44d89644a34b3caf3bc9
Autor:
Bowen Tang, Zhangming Niu, Xiaofeng Wang, Junjie Huang, Chao Ma, Jing Peng, Yinghui Jiang, Ruiquan Ge, Hongyu Hu, Luhao Lin, Guang Yang
Publikováno v:
Journal of Cheminformatics, Vol 16, Iss 1, Pp 1-13 (2024)
Abstract Chemical structure segmentation constitutes a pivotal task in cheminformatics, involving the extraction and abstraction of structural information of chemical compounds from text-based sources, including patents and scientific articles. This
Externí odkaz:
https://doaj.org/article/b36e16cf0ecb4e1a884b7eaa0a22ed70
Publikováno v:
High Voltage, Vol 8, Iss 4, Pp 690-697 (2023)
Abstract In this paper we investigated SF6 decomposition behaviour of typical insulation defects in gas‐solid insulated converter transformer valve‐side bushing under partial discharge (PD). Additionally, we compared the results with that of gas
Externí odkaz:
https://doaj.org/article/4a55dc6c6ac04f08b79ab3b09e76ac31
Autor:
Jinlong Li, Qin Qin, Xing Tian, Jiarong Guo, Bowen Tang, Zhigang He, Zhonggui Xie, Yude Wang, Dongwu Wang
Publikováno v:
Biology, Vol 13, Iss 6, p 395 (2024)
In this study, juvenile crayfish hatched from the same population were cultured in different growing environments: pond (D1), paddy field (D2), and aquaculture barrel (D3), and fed for 60 days. Crayfishes were selected randomly, females and males, 50
Externí odkaz:
https://doaj.org/article/a223394755574e928847da7ded6cfce8
Publikováno v:
Clinical and Experimental Obstetrics & Gynecology, Vol 51, Iss 4, p 86 (2024)
Background: Polycystic ovary syndrome (PCOS) stands as one of the most prevalent endocrine disorders affecting women of reproductive age. Despite being recognized for decades, numerous unresolved issues persist regarding its impact on reproductive me
Externí odkaz:
https://doaj.org/article/dd6d1896ea0d41d99a6e9ea0a4edcc80
Publikováno v:
Cancer Medicine, Vol 12, Iss 4, Pp 3962-3971 (2023)
Abstract Searching for reliable indicators for evaluating prognosis diagnosed with clear cell renal cell carcinoma (ccRCC) is crucial for improving clinical therapies. However, current researches have looked mainly at the prognostic value of a single
Externí odkaz:
https://doaj.org/article/ac83158e50794f8dbc14be7c7d17e3a0
Publikováno v:
BenchCouncil Transactions on Benchmarks, Standards and Evaluations, Vol 3, Iss 1, Pp 100106- (2023)
Learning-based malware detection systems (LB-MDS) play a crucial role in defending computer systems from malicious attacks. Nevertheless, these systems can be vulnerable to various attacks, which can have significant consequences. Software obfuscatio
Externí odkaz:
https://doaj.org/article/fd5b5fb5e6114e60b816addc3a136c30
Autor:
Fang Wu, Shuting Jin, Yinghui Jiang, Xurui Jin, Bowen Tang, Zhangming Niu, Xiangrong Liu, Qiang Zhang, Xiangxiang Zeng, Stan Z. Li
Publikováno v:
Advanced Science, Vol 9, Iss 33, Pp n/a-n/a (2022)
Abstract The latest biological findings observe that the motionless “lock‐and‐key” theory is not generally applicable and that changes in atomic sites and binding pose can provide important information for understanding drug binding. However,
Externí odkaz:
https://doaj.org/article/e56f083b9c9b4389815dd5424124dbbe
Publikováno v:
Energy Science & Engineering, Vol 9, Iss 3, Pp 447-460 (2021)
Abstract The loss of shale gas from conventional wells during coring directly affects the accuracy of measurement of shale gas content and the efficient development and utilization of shale gas. The existing methods to determine shale gas loss are no
Externí odkaz:
https://doaj.org/article/b57c7daf83834f6093a8e22df86ceb20
Publikováno v:
Journal of Cheminformatics, Vol 12, Iss 1, Pp 1-9 (2020)
Abstract Efficient and accurate prediction of molecular properties, such as lipophilicity and solubility, is highly desirable for rational compound design in chemical and pharmaceutical industries. To this end, we build and apply a graph-neural-netwo
Externí odkaz:
https://doaj.org/article/2e341dc48d624ee0b01f065af9d41781