Zobrazeno 1 - 10
of 6 194
pro vyhledávání: '"Jin SHI"'
Autor:
Houyu Zhao, Kun Liang, Zeyuan Yu, Yukun Wen, Jin Shi, Tingting Zhang, Xuhua Yu, Xianpeng Zu, Yiqun Fang
Publikováno v:
Neuroscience Research, Vol 207, Iss , Pp 26-36 (2024)
Underwater exercise is becoming increasingly prevalent, during which brain function is necessary but is also at risk. However, no study has explored how prolonged exercise affect the brain in underwater environment. Previous studies have indicated th
Externí odkaz:
https://doaj.org/article/aa1ea050e75c4b36ad641bc6e0945831
Autor:
Yongliang Sha, Huijie Zhuang, Jin Shi, Song Ge, Shiqing He, Yiqiu Wang, Li Ma, Hao Guo, Hui Cheng
Publikováno v:
Discover Oncology, Vol 15, Iss 1, Pp 1-15 (2024)
Abstract Background β-1,3-Galactosyltransferase-4 (B3GALT4), a member of the β-1,3-galactosyltransferase gene family, is essential to the development of many malignancies. However, its biological function in breast cancer is still unknown. Method P
Externí odkaz:
https://doaj.org/article/671ae44fdb66486682acf07209fe6780
Publikováno v:
Humanities & Social Sciences Communications, Vol 11, Iss 1, Pp 1-14 (2024)
Abstract Risk assessment and categorization of terrorist attacks can assist enhance awareness of terrorism and give crucial information support for anti-terrorism efforts. This study utilizes quantitative approaches for the risk assessment and catego
Externí odkaz:
https://doaj.org/article/9aacc246815e47d6b662ef6f44848393
Publikováno v:
Dianxin kexue, Vol 40, Pp 1-12 (2024)
In recent years, reconfigurable intelligent surface (RIS) is regarded as one of the promising technologies for 6G because of low power consumption, low cost and the ability to improve communication transmission rate. The progress in measurements for
Externí odkaz:
https://doaj.org/article/79d408e468194e058b2ad399a42c9d47
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-13 (2024)
Abstract Rapid urbanization increases psychological stress among pedestrians, potentially heightening mental health disorders. This study examines the role of street walls' visual and textural characteristics in stress recovery, using Qingdao as a ca
Externí odkaz:
https://doaj.org/article/8dfd2ae9ba7d4550ae78dc64aef9c25c
Publikováno v:
Earthquake Science, Vol 37, Iss 3, Pp 189-199 (2024)
Carbonaceous materials in seismic fault zones may considerably influence seismic fault slip; however, the formation mechanism of carbonaceous materials remains unclear. In this study, we proposed a novel hypothesis for the formation of carbonaceous m
Externí odkaz:
https://doaj.org/article/04169c05cdbb481b9a74f3584e8c31e4
Publikováno v:
Heliyon, Vol 10, Iss 20, Pp e38710- (2024)
Gastric cancer is one of the most common malignant tumours, with limited treatment options and poor prognosis in its advanced stages. In recent years, breakthroughs in tumour immunotherapy have led to immune checkpoint inhibitors becoming a new class
Externí odkaz:
https://doaj.org/article/f5ecf54ea5014f3c941d874b225732d3
Autor:
Jin Shi, Fan Ding, Dezhu Dai, Xudong Song, Xu Wu, Dongsheng Yan, Xiao Han, Guoquan Tao, Weijie Dai
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-16 (2024)
Abstract While Phorbol-12-myristate-13-acetate-induced protein 1 (Noxa/PMAIP1) assumes a pivotal role in numerous tumors, its clinical implications and underlying mechanisms of gastric cancer (GC) are yet enigmatic. In this investigation, our primary
Externí odkaz:
https://doaj.org/article/4ba4a1bb770640ae8e00057c35e2d217
Publikováno v:
Clinical and Applied Thrombosis/Hemostasis, Vol 30 (2024)
Post-thrombotic syndrome (PTS) is one of the most common long-term complications of lower extremity deep vein thrombosis (DVT). In order to study the long-term adverse prognosis of patients with DVT, explore the influencing factors for the prognosis
Externí odkaz:
https://doaj.org/article/13300a046ecf4e4e816e7e8459985ccf
A light CNN based on residual learning and background estimation for hyperspectral anomaly detection
Autor:
Jiajia Zhang, Pei Xiang, Jin Shi, Xiang Teng, Dong Zhao, Huixin Zhou, Huan Li, Jiangluqi Song
Publikováno v:
International Journal of Applied Earth Observations and Geoinformation, Vol 132, Iss , Pp 104069- (2024)
Existing deep learning-based hyperspectral anomaly detection methods typically perform anomaly detection by reconstructing a clean background. However, for the deep networks, there are many parameters that need to be adjusted. To reduce parameters of
Externí odkaz:
https://doaj.org/article/857513d7ec9845ecbc554eee222f7363