Zobrazeno 1 - 10
of 1 887
pro vyhledávání: '"ZHANG Lingyu"'
Publikováno v:
口腔疾病防治, Vol 32, Iss 10, Pp 772-779 (2024)
Objective To investigate the clinical characteristics and prognosis of crown fractures in immature permanent incisors due to trauma, and identify factors affecting their prognosisto provide a reference for clinical treatment. Methods This study was a
Externí odkaz:
https://doaj.org/article/c762988e339e41f89bf1a9f47c827b78
Publikováno v:
Reviews on Advanced Materials Science, Vol 63, Iss 1, Pp pp. 155-157 (2024)
In order to solve the problems of depleting petroleum asphalt resources and deteriorating pollution of marine products, a systematic study was carried out on the application prospect of waste crab shell (WS) powder as asphalt modifier. In this study,
Externí odkaz:
https://doaj.org/article/2efd1bd77da445b3befe419ce770183b
Publikováno v:
Guangxi Zhiwu, Vol 44, Iss 4, Pp 777-792 (2024)
Angelica dahurica is a common species of medicine and food homology, which is not only a common clinical traditional Chinese medicine, but also a spice, with a wide range of uses. In order to obtain the whole genome sequence information of A. dahuric
Externí odkaz:
https://doaj.org/article/bd713cd49bb84abcab0c3d65a1308615
Autor:
ZHANG Lingyu, PAN Lijia, HOU Suxin, JIANG Shan, YANG Mei, CAO Jiazhen, XU Xiaohong, ZHANG Nan
Publikováno v:
Shipin Kexue, Vol 44, Iss 15, Pp 147-155 (2023)
Objective: In order to explore the effects of Lonicera caerulea berry polyphenols (LCBP) on immunity and intestinal flora in immunosuppressive mice. Methods: Thirty-two mice were randomly divided into a blank control group, a model group, a low-dose
Externí odkaz:
https://doaj.org/article/658c22dd25b04cb18daba9f08eb33d4b
Autor:
ZHANG Lingyu, SHANG Huifang
Publikováno v:
罕见病研究, Vol 1, Iss 2, Pp 206-216 (2022)
Multiple system atrophy (MSA) is a rare and rapidly-progressive neurodegenerative disorder, characterized by the combination of dysautonomia, poor levodopa responsive parkinsonism, cerebellar ataxia, and pyramidal tract signs. Insidious onset, clinic
Externí odkaz:
https://doaj.org/article/892b85d90c1f42edb5c4ea21428a34c1
Spatiotemporal Graph Neural Networks (ST-GNNs) and Transformers have shown significant promise in traffic forecasting by effectively modeling temporal and spatial correlations. However, rapid urbanization in recent years has led to dynamic shifts in
Externí odkaz:
http://arxiv.org/abs/2411.11448
The recent rapid advancement of machine learning has been driven by increasingly powerful models with the growing availability of training data and computational resources. However, real-time decision-making tasks with limited time and sparse learnin
Externí odkaz:
http://arxiv.org/abs/2410.15181
Spatiotemporal neural networks have shown great promise in urban scenarios by effectively capturing temporal and spatial correlations. However, urban environments are constantly evolving, and current model evaluations are often limited to traffic sce
Externí odkaz:
http://arxiv.org/abs/2410.04740
Traffic forecasting is a cornerstone of smart city management, enabling efficient resource allocation and transportation planning. Deep learning, with its ability to capture complex nonlinear patterns in spatiotemporal (ST) data, has emerged as a pow
Externí odkaz:
http://arxiv.org/abs/2410.00385
Recent advancements in Spatiotemporal Graph Neural Networks (ST-GNNs) and Transformers have demonstrated promising potential for traffic forecasting by effectively capturing both temporal and spatial correlations. The generalization ability of spatio
Externí odkaz:
http://arxiv.org/abs/2410.00373