Výsledky vyhledávání

Akademický článek

Does digital transformation foster carbon emissions reduction? Evidence from China’s manufacturing supply chain

Autor: Xu, Ying, Jia, Fu, Chen, Lujie, Wang, Yonggui

Publikováno v: The International Journal of Logistics Management, 2024, Vol. 35, Issue 6, pp. 1827-1846.

Externí odkaz: http://www.emeraldinsight.com/doi/10.1108/IJLM-07-2023-0260

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Akademický článek

Morphological data of the superior vena cava predicted by multiple linear regression equations

Autor: Yuan Wang, Jia Fu, Hao Y. Li, Shi J. Du, Yun Y. Zhang, Hao Y. Wang, Jing W. Wang, Jian F. Mao, Hong T. Zhang, Cheng Chang

Publikováno v: BMC Cardiovascular Disorders, Vol 24, Iss 1, Pp 1-12 (2024)

Abstract This study explores the main surface markers in the hemodialysis puncture catheterization pathway and the relative spatial position of venous vessels in the puncture results, providing data support for venous puncture. Seventy cadavers were

Externí odkaz: https://doaj.org/article/7d5d2d0e86674205a1cb632c34cf25c3

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Akademický článek

Systematic analysis and functional verification of citrus glutathione S-transferases reveals that CsGSTF1 and CsGSTU18 contribute negatively to citrus bacterial canker

Autor: Jia Fu, Liyan Su, Jie Fan, Qiyuan Yu, Xin Huang, Chenxi Zhang, Baohang Xian, Wen Yang, Shuai Wang, Shanchun Chen, Yongrui He, Qiang Li

Publikováno v: Horticultural Plant Journal, Vol 10, Iss 6, Pp 1309-1320 (2024)

Citrus bacterial canker (CBC) is resulted from Xanthomonas citri subsp. citri (Xcc) infection and poses a significant threat to citrus production. Glutathione S-transferases (GSTs) are critical in maintaining redox homeostasis in plants, especially i

Externí odkaz: https://doaj.org/article/b0398b5a59414e64af045ec416d41ede

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Akademický článek

A multicenter dataset for lymph node clinical target volume delineation of nasopharyngeal carcinoma

Autor: Xiangde Luo, Wenjun Liao, Yue Zhao, Youjing Qiu, Jinfeng Xu, Yuan He, Hui Huang, Lu Li, Shichuan Zhang, Jia Fu, Guotai Wang, Shaoting Zhang

Publikováno v: Scientific Data, Vol 11, Iss 1, Pp 1-12 (2024)

Abstract The deep learning (DL)-based prediction of accurate lymph node (LN) clinical target volumes (CTVs) for nasopharyngeal carcinoma (NPC) radiotherapy (RT) remains challenging. One of the main reasons is the variability of contours despite stand

Externí odkaz: https://doaj.org/article/8b3aaffce81947c18ff18d6fcff6dcab

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