Zobrazeno 1 - 10
of 25 721
pro vyhledávání: '"ZHOU, JUN"'
Autor:
Jiang-Miao Hu
Publikováno v:
Natural Products and Bioprospecting, Vol 8, Iss 4, Pp 199-206 (2018)
Abstract Prof. Zhou Jun, Academician of Chinese Academy of Sciences (1999), is a phytochemist and medicinal chemist of China. He is one of the pioneers of Kunming Institute of Botany, CAS and a major founder of the State Key Laboratory of Phytochemis
Externí odkaz:
https://doaj.org/article/2e9c7f50f5f34c1cb35ea63ada36bb5c
The $\text{Cu}_7\text{P}\text{S}_6$ compound has garnered significant attention due to its potential in thermoelectric applications. In this study, we introduce a neuroevolution potential (NEP), trained on a dataset generated from ab initio molecular
Externí odkaz:
http://arxiv.org/abs/2411.10911
Crystals exhibiting glass-like and low lattice thermal conductivity ($\kappa_{\rm L}$) are not only scientifically intriguing but also practically valuable in various applications, including thermal barrier coatings, thermoelectric energy conversion,
Externí odkaz:
http://arxiv.org/abs/2411.05600
Autor:
Shah, Keyur D., Zhou, Jun, Roper, Justin, Dhabaan, Anees, Al-Hallaq, Hania, Pourmorteza, Amir, Yang, Xiaofeng
Photon-counting computed tomography (PCCT) marks a significant advancement over conventional energy-integrating detector (EID) CT systems. This review highlights PCCT's superior spatial and contrast resolution, reduced radiation dose, and multi-energ
Externí odkaz:
http://arxiv.org/abs/2410.20236
Optimization problems are prevalent across various scenarios. Formulating and then solving optimization problems described by natural language often requires highly specialized human expertise, which could block the widespread application of optimiza
Externí odkaz:
http://arxiv.org/abs/2410.13213
Large vision language models (VLMs) combine large language models with vision encoders, demonstrating promise across various tasks. However, they often underperform in task-specific applications due to domain gaps between pre-training and fine-tuning
Externí odkaz:
http://arxiv.org/abs/2410.06456
The Direct Segment Anything Model (DirectSAM) excels in class-agnostic contour extraction. In this paper, we explore its use by applying it to optical remote sensing imagery, where semantic contour extraction-such as identifying buildings, road netwo
Externí odkaz:
http://arxiv.org/abs/2410.06194
Koopman spectral analysis plays a crucial role in understanding and modeling nonlinear dynamical systems as it reveals key system behaviors and long-term dynamics. However, the presence of measurement noise poses a significant challenge to accurately
Externí odkaz:
http://arxiv.org/abs/2410.00703
Over the past few years, vision transformers (ViTs) have consistently demonstrated remarkable performance across various visual recognition tasks. However, attempts to enhance their robustness have yielded limited success, mainly focusing on differen
Externí odkaz:
http://arxiv.org/abs/2409.19850
Autor:
Liang, Lei, Sun, Mengshu, Gui, Zhengke, Zhu, Zhongshu, Jiang, Zhouyu, Zhong, Ling, Qu, Yuan, Zhao, Peilong, Bo, Zhongpu, Yang, Jin, Xiong, Huaidong, Yuan, Lin, Xu, Jun, Wang, Zaoyang, Zhang, Zhiqiang, Zhang, Wen, Chen, Huajun, Chen, Wenguang, Zhou, Jun
The recently developed retrieval-augmented generation (RAG) technology has enabled the efficient construction of domain-specific applications. However, it also has limitations, including the gap between vector similarity and the relevance of knowledg
Externí odkaz:
http://arxiv.org/abs/2409.13731