Zobrazeno 1 - 10
of 307
pro vyhledávání: '"LI Huating"'
Publikováno v:
Shanghai Jiaotong Daxue xuebao. Yixue ban, Vol 44, Iss 9, Pp 1190-1196 (2024)
In recent years, the global prevalence of obesity has continued to rise, with a preference for high-sugar and high-fat foods being one of the primary contributors to this condition. Food preference refers to the degree of individual liking for specif
Externí odkaz:
https://doaj.org/article/842caa6ed388489aa96e55a118c5b988
Autor:
WU Qian, LI Huating
Publikováno v:
Shanghai Jiaotong Daxue xuebao. Yixue ban, Vol 44, Iss 1, Pp 131-136 (2024)
Metabolic disorders, characterized by a complex pathogenesis, are experiencing a rising prevalence globally and a trend toward younger populations, making them a significant public health concern. Olfaction, a crucial sensory function, plays a pivota
Externí odkaz:
https://doaj.org/article/4ed6c1b5457a436da8e59b8473b9abbd
Autor:
HAN Rui, WU Qian, LIU Dan, CHENG Di, ZHANG Ying, NI Jiacheng, KANG Piao, CHEN Anran, YU Shujie, FANG Qichen, LI Huating
Publikováno v:
Shanghai Jiaotong Daxue xuebao. Yixue ban, Vol 44, Iss 1, Pp 87-97 (2024)
Objective·To evaluate the changes in cognitive function in overweight and obese adolescents, and explore the association between cognitive function and fibroblast growth factor 21 (FGF21).Methods·A total of 175 adolescents from a senior high school
Externí odkaz:
https://doaj.org/article/9c02eefc33924e2ea994fffce63ae60b
Seismic exploration is currently the most important method for understanding subsurface structures. However, due to surface conditions, seismic receivers may not be uniformly distributed along the measurement line, making the entire exploration work
Externí odkaz:
http://arxiv.org/abs/2411.00911
Seismic exploration is currently the most mature approach for studying subsurface structures, yet the presence of noise greatly restricts its imaging accuracy. Previous methods still face significant challenges: traditional computational methods are
Externí odkaz:
http://arxiv.org/abs/2410.18896
Thin layers and reservoirs may be concealed in areas of low seismic reflection amplitude, making them difficult to recognize. Deep learning (DL) techniques provide new opportunities for accurate impedance prediction by establishing a nonlinear mappin
Externí odkaz:
http://arxiv.org/abs/2408.04932
Seismic impedance inversion is a widely used technique for reservoir characterization. Accurate, high-resolution seismic impedance data form the foundation for subsequent reservoir interpretation. Deep learning methods have demonstrated significant p
Externí odkaz:
http://arxiv.org/abs/2408.02524
Deep learning (DL) techniques have been widely used in prestack three-parameter inversion to address its ill-posed problems. Among these DL techniques, Multi-task learning (MTL) methods can simultaneously train multiple tasks, thereby enhancing model
Externí odkaz:
http://arxiv.org/abs/2407.00684
Seismic impedance inversion is one of the most important part of geophysical exploration. However, due to random noise, the traditional semi-supervised learning (SSL) methods lack generalization and stability. To solve this problem, some authors have
Externí odkaz:
http://arxiv.org/abs/2405.05026
Objective: COVID-19 has spread worldwide and made a huge influence across the world. Modeling the infectious spread situation of COVID-19 is essential to understand the current condition and to formulate intervention measurements. Epidemiological equ
Externí odkaz:
http://arxiv.org/abs/2306.12457