Zobrazeno 1 - 10
of 216
pro vyhledávání: '"JIALUN LI"'
Publikováno v:
JACS Au, Vol 4, Iss 10, Pp 3931-3941 (2024)
Externí odkaz:
https://doaj.org/article/e615ebca7cbc435bb4ba7b5482a3ed44
Publikováno v:
Frontiers in Pharmacology, Vol 15 (2024)
Cortex Moutan is the root bark of the buttercup plant Paeonia suffruticosa Andr, of Ranunculaceae family. It has been utilized in Chinese medicine for thousands of years to treat a multitude of diseases, and traditional Chinese documents allege that
Externí odkaz:
https://doaj.org/article/b32c6f51b6ed41d38f56845e67a6b005
Autor:
Bichun Xu, Xianzhi Zhao, Zhiru Feng, Jialun Li, Yiyin Liang, Weiwei Zhang, Liang Chen, Xianqi Shen, Min Qu, Xu Gao, Huojun Zhang
Publikováno v:
Cancer Control, Vol 31 (2024)
Introduction The existing large prospective study demonstrates the benefits of primary radiotherapy in patients with low-volume oligometastatic prostate cancer (OMPC), and there is additional evidence of the benefits of local metastasis-directed ther
Externí odkaz:
https://doaj.org/article/0bf6273a51a4490d9f49aeba20985a7a
Publikováno v:
IEEE Journal of the Electron Devices Society, Vol 12, Pp 318-321 (2024)
This letter reports a high-performance fully-vertical GaN-on-SiC p-i-n diode enabled by a conductive n-AlGaN buffer. The buffer conductivity was optimized by tuning the Al composition. The diode presents an ultra-low specific ON-resistance of 0.25 $\
Externí odkaz:
https://doaj.org/article/ba973af1a55f4af3988a3ac38c75d29c
Autor:
Jialun Li, Lu Lu, Lingling Liu, Xuelian Ren, Jiwei Chen, Xingzhi Yin, Yanhui Xiao, Jiwen Li, Gang Wei, He Huang, Wei Wei, Jiemin Wong
Publikováno v:
Cell Discovery, Vol 9, Iss 1, Pp 1-17 (2023)
Abstract Lysine succinylation is one of the major post-translational modifications occurring on histones and is believed to have significant roles in regulating chromatin structure and function. Currently, histone desuccinylation is widely believed t
Externí odkaz:
https://doaj.org/article/422de330a1dd41e88af52aa4ea52535f
Publikováno v:
Journal of Cloud Computing: Advances, Systems and Applications, Vol 12, Iss 1, Pp 1-12 (2023)
Abstract Task scheduling is a complex problem in cloud computing, and attracts many researchers’ interests. Recently, many deep reinforcement learning (DRL)-based methods have been proposed to learn the scheduling policy through interacting with th
Externí odkaz:
https://doaj.org/article/c716ff3a6f6343628fb477bb7b637fb6
Autor:
Fei Yu, Jialun Li, Yi Jiang, Liying Wang, Xijia Yang, Yue Yang, Xuesong Li, Ke Jiang, Wei Lü, Xiaojuan Sun
Publikováno v:
Advanced Science, Vol 10, Iss 30, Pp n/a-n/a (2023)
Abstract While hydrovoltaic electrical energy generation developments in very recent years have provided an alternative strategy to generate electricity from the direct interaction of materials with water, the two main issues still need to be address
Externí odkaz:
https://doaj.org/article/d7398c5ed8dd4f0aaa2dca246692bbb8
Publikováno v:
IEEE Access, Vol 11, Pp 66872-66881 (2023)
In order to improve the classification accuracy of loudspeaker abnormal sounds, this paper proposes a method based on time-varying specific loudness weighted by energy entropy and principal component analysis. This method simulates human auditory per
Externí odkaz:
https://doaj.org/article/98376eaa93a64f228b69bc1ba4315a4b
Autor:
Xiang Liu, Zemin Zhu, Kexin Wang, Yaofeng Zhang, Jialun Li, Xiangpeng Wang, Xiaodong Zhang, Xiaoying Wang
Publikováno v:
Cancer Imaging, Vol 23, Iss 1, Pp 1-9 (2023)
Abstract Background The evaluation of treatment response according to METastasis Reporting and Data System for Prostate Cancer (MET-RADS-P) criteria is an important but time-consuming task for patients with advanced prostate cancer (APC). A deep lear
Externí odkaz:
https://doaj.org/article/3b110dd509d24151a591a9cee7eb4956
Autor:
Xiang Liu, Rui Wang, Zemin Zhu, Kexin Wang, Yue Gao, Jialun Li, Yaofeng Zhang, Xiangpeng Wang, Xiaodong Zhang, Xiaoying Wang
Publikováno v:
BMC Cancer, Vol 22, Iss 1, Pp 1-12 (2022)
Abstract Background Evaluation of treated tumors according to Response Evaluation Criteria in Solid Tumors (RECIST) criteria is an important but time-consuming task in medical imaging. Deep learning methods are expected to automate the evaluation pro
Externí odkaz:
https://doaj.org/article/0eb4f073975a4cb3adcc3ac184b7476a