Zobrazeno 1 - 10
of 2 667
pro vyhledávání: '"Chao, Sheng"'
As Earth science enters the era of big data, artificial intelligence (AI) not only offers great potential for solving geoscience problems, but also plays a critical role in accelerating the understanding of the complex, interactive, and multiscale pr
Externí odkaz:
http://arxiv.org/abs/2311.04940
Autor:
Zhang, Hao, Xu, Jin-Jian, Cui, Hong-Wei, Li, Lin, Yang, Yaowen, Tang, Chao-Sheng, Boers, Niklas
Publikováno v:
IEEE Geoscience and Remote Sensing Magazine, 2024
Artificial intelligence (AI) has significantly advanced Earth sciences, yet its full potential in to comprehensively modeling Earth's complex dynamics remains unrealized. Geoscience foundation models (GFMs) emerge as a paradigm-shifting solution, int
Externí odkaz:
http://arxiv.org/abs/2309.06799
Publikováno v:
Chinese Medical Journal, Vol 137, Iss 21, Pp 2567-2576 (2024)
Abstract. Background:. Thyroid cancer (TC) is the most common malignancy of the endocrine system. This study aimed to assess the global distribution of TC incidence and mortality in 2022, as well as to predict the burden for the year 2050. Methods:.
Externí odkaz:
https://doaj.org/article/8fef60e423c344c0b9da1e9e3a6e8f72
Publikováno v:
Journal of Rock Mechanics and Geotechnical Engineering, Vol 16, Iss 10, Pp 4272-4284 (2024)
Soil tensile strength is a critical parameter governing the initiation and propagation of tensile cracking. This study proposes an eco-friendly approach to improve the tensile behavior and crack resistance of clayey soils. To validate the feasibility
Externí odkaz:
https://doaj.org/article/4359069ae5d9487a8eb29148340b4454
Autor:
Rong-Yue Sun, Yue Xu, Qing-Qing Huang, Si-Si Hu, Hua-Zhi Xu, Yan-Zhao Luo, Ting Zhu, Jun-Hui Sun, Yu-Jing Gong, Mian-Mian Zhu, Hong-Wei Wang, Jing-Ye Pan, Chao-Sheng Lu, Dan Wang
Publikováno v:
BMC Medical Genomics, Vol 17, Iss 1, Pp 1-11 (2024)
Abstract Background Genetic variants in COL4A2 are less common than those of COL4A1 and their fetal clinical phenotype has not been well described to date. We present a fetus from China with an intronic variant in COL4A2 associated with a prenatal di
Externí odkaz:
https://doaj.org/article/c4abd43693c04e8c93bdd88b4df5e015
Autor:
Yu Zhang, Chao Sheng, Zhangyan Lyu, Hongji Dai, Fangfang Song, Fengju Song, Yubei Huang, Kexin Chen
Publikováno v:
Cancer Biology & Medicine, Vol 21, Iss 8, Pp 712-723 (2024)
Objective: Few studies have evaluated the benefits of colorectal cancer (CRC) screening integrating both non-genetic and genetic risk factors. Here, we aimed to integrate an existing non-genetic risk model (QCancer-10) and a 139-variant polygenic ris
Externí odkaz:
https://doaj.org/article/978bfc13fc3d46bfa52245841d44af5d
Publikováno v:
Frontiers in Public Health, Vol 12 (2024)
Life and death education is a distinct field of study that has potential practicality and life relevance for us to consider. For example, one notable inquiry pertaining to life education teaching entails appreciation and theoretical understanding of
Externí odkaz:
https://doaj.org/article/641c09aaada2437e8f6469ecef9f1a93
Publikováno v:
Geoderma, Vol 449, Iss , Pp 117033- (2024)
Desiccation cracking is a common and natural phenomenon under a drought climate. The geometric and morphologic characteristics of the crack pattern are critical to understanding the response of soil mechanical and hydraulic properties to drought clim
Externí odkaz:
https://doaj.org/article/dd0e6dda97f6450eb27adb9a27f69c10
Publikováno v:
Lipids in Health and Disease, Vol 23, Iss 1, Pp 1-11 (2024)
Abstract Background Kidney cancer has become known as a metabolic disease. However, there is limited evidence linking metabolic syndrome (MetS) with kidney cancer risk. This study aimed to investigate the association between MetS and its components a
Externí odkaz:
https://doaj.org/article/2b478bba8d3f41a8998d914060ef44c8
Publikováno v:
BMC Medical Informatics and Decision Making, Vol 24, Iss 1, Pp 1-14 (2024)
Abstract Objective The healthcare challenge driven by an aging population and rising demand is one of the most pressing issues leading to emergency department (ED) overcrowding. An emerging solution lies in machine learning’s potential to predict E
Externí odkaz:
https://doaj.org/article/9a47225d6e0947dab2950d687df1981f