Zobrazeno 1 - 10
of 722
pro vyhledávání: '"Dan XUE"'
Autor:
Ethan A. Older, Jian Zhang, Zachary E. Ferris, Dan Xue, Zheng Zhong, Mary K. Mitchell, Michael Madden, Yuzhen Wang, Hexin Chen, Prakash Nagarkatti, Mitzi Nagarkatti, Daping Fan, Melissa Ellermann, Yong-Xin Li, Jie Li
Publikováno v:
Nature Communications, Vol 15, Iss 1, Pp 1-17 (2024)
Abstract The trillions of microorganisms inhabiting the human gut are intricately linked to human health. While specific microbes have been associated with diseases, microbial abundance alone cannot reveal the molecular mechanisms involved. One such
Externí odkaz:
https://doaj.org/article/610f9c86477c44328236ec90fbbd6581
Autor:
Ting Zhou, Lan lin, Yawen Zhan, Ziyao Zhang, Ying Jiang, Mi Wu, Dan Xue, Limin Chen, Xiufang Weng, Zhenghui Huang
Publikováno v:
Molecular Medicine, Vol 30, Iss 1, Pp 1-13 (2024)
Abstract Background The development of pulmonary fibrosis involves a cascade of events, in which inflammation mediated by immune cells plays a pivotal role. Chemotherapeutic drugs have been shown to have dual effects on fibrosis, with bleomycin exace
Externí odkaz:
https://doaj.org/article/6c62c71c6bcf457c9f21e07e3fa4622c
Publikováno v:
European Journal of Remote Sensing, Vol 57, Iss 1 (2024)
ABSTRACTAiming the problems that the classification performance of hyperspectral images in existing classification algorithms is highly dependent on spatial-spectral information and that detailed features are ignored in single convolutional channel f
Externí odkaz:
https://doaj.org/article/375a6a388c3c42a9bc1c3c4b46c0cb38
Publikováno v:
IEEE Access, Vol 12, Pp 38542-38550 (2024)
Multiscale Dense Network (MSDN) is a deep convolutional neural network method proposed to solve the loss of fine features in hyperspectral remote sensing images. Multiscale Dense Network (MSDN), which makes full use of the different scale information
Externí odkaz:
https://doaj.org/article/13abe45bb2d945749579e369797006b6
Autor:
Dan Xue, Liangliang Jiang, Zixiang Wei, Maojie Chai, Jiang Liu, Peng Deng, Fuhe Lin, Jian Li, Jiansheng Zhang, Zhangxin Chen
Publikováno v:
Energy Reviews, Vol 3, Iss 1, Pp 100056- (2024)
On the backdrop of dwindling conventional reserves, unconventional reservoirs have emerged as a pivotal chapter in resource extraction. Despite their challenges, such as low permeability, complex fluid storage, and flow mechanisms, hydraulic fracturi
Externí odkaz:
https://doaj.org/article/b6440ab408d147eebc6c4d34d6bbc923
Autor:
Dan Xue, Tengteng Zhu, Hongguang Lin, Peilin Guo, Mengling Li, Mei'e Yu, Fan Yang, Sheng Yang, Xiangqi Chen, Peifang Wei
Publikováno v:
Chinese Medical Journal, Vol 136, Iss 24, Pp 3019-3021 (2023)
Externí odkaz:
https://doaj.org/article/d1408d4a4250432baf7509be5788d11d
Publikováno v:
Mathematics, Vol 12, Iss 15, p 2393 (2024)
In this paper, we propose a stochastic primal-dual adaptive method based on an inexact augmented Lagrangian function to solve non-convex programs, referred to as the SPDAM. Different from existing methods, SPDAM incorporates adaptive step size and mo
Externí odkaz:
https://doaj.org/article/42bf694a065c4a4eb4c4e2c62fd2f43d
Publikováno v:
Sensors, Vol 24, Iss 15, p 4771 (2024)
In order to achieve the non-destructive testing and quality evaluation of stainless-steel resistance spot welding (RSW) joints, a portable ultrasonic spiral C-scan testing instrument was developed based on the principle of ultrasonic pulse reflection
Externí odkaz:
https://doaj.org/article/f39c3bb0d42c4381b27bd063ac5b5e1f
Publikováno v:
Atmosphere, Vol 15, Iss 7, p 747 (2024)
Global climate change increasingly impacts agroecosystems, particularly through high-temperature–drought and low-temperature–drought compound events. This study uses ground meteorological and remote sensing data and employs geostatistics, random
Externí odkaz:
https://doaj.org/article/fcc8218aee6a4bf2adf811f8e514ecf2
Publikováno v:
Environmental Microbiome, Vol 18, Iss 1, Pp 1-18 (2023)
Abstract Background Peatlands contain about 500 Pg of carbon worldwide and play a dual role as both a carbon sink and an important methane (CH4) source, thereby potentially influencing climate change. However, systematic studies on peat properties, m
Externí odkaz:
https://doaj.org/article/667f045ebecc4953b9da741c03be3f54