Zobrazeno 1 - 10
of 217
pro vyhledávání: '"Wu, Junwen"'
Publikováno v:
Xibei zhiwu xuebao, Vol 44, Iss 7, Pp 1129-1140 (2024)
Abstract [Objective] This study aims to investigate the effects of drought stress on the distribution of carbon (C), nitrogen (N), and phosphorus (P) elements and stoichiometry in organs of Pinus yunnanensis seedlings, and to provide a theoretical
Externí odkaz:
https://doaj.org/article/81a8ff1fbbc646e5a6dcac866f24c9f3
Publikováno v:
Xibei zhiwu xuebao, Vol 44, Iss 5, Pp 782-791 (2024)
[ Objective ] It is of great significance to explore the distribution of NSC ( non-structural carbohy- drate ) and their components in different organs with seasonal changes for revealing the mechanism of car- bon dist
Externí odkaz:
https://doaj.org/article/92808340c69e48a8bcd1f42a7cb5bce5
Publikováno v:
In Journal of Molecular Liquids 15 September 2024 410
Autor:
Wu, Junwen.
Publikováno v:
Connect to a 24 p. preview or request complete full text in PDF format. Access restricted to UC campuses
Thesis (Ph. D.)--University of California, San Diego, 2007.
Title from first page of PDF file (viewed March 22, 2007). Available via ProQuest Digital Dissertations. Vita. Includes bibliographical references (p. 159-170).
Title from first page of PDF file (viewed March 22, 2007). Available via ProQuest Digital Dissertations. Vita. Includes bibliographical references (p. 159-170).
Externí odkaz:
http://wwwlib.umi.com/cr/ucsd/fullcit?p3249649
Publikováno v:
In Journal of Molecular Liquids 1 July 2024 405
Publikováno v:
In Industrial Crops & Products April 2024 210
Autor:
Yan, Xiuli, Guo, Xiaolan, Yao, Anqi, Bao, Hongyan, Li, Da-Wei, Huang, Jr-Chuan, Wu, Junwen, Han, Li-Li, Kao, Shuh-Ji
Publikováno v:
In Journal of Hydrology February 2024 630
Autor:
Pati, Sarthak, Thakur, Siddhesh P., Hamamcı, İbrahim Ethem, Baid, Ujjwal, Baheti, Bhakti, Bhalerao, Megh, Güley, Orhun, Mouchtaris, Sofia, Lang, David, Thermos, Spyridon, Gotkowski, Karol, González, Camila, Grenko, Caleb, Getka, Alexander, Edwards, Brandon, Sheller, Micah, Wu, Junwen, Karkada, Deepthi, Panchumarthy, Ravi, Ahluwalia, Vinayak, Zou, Chunrui, Bashyam, Vishnu, Li, Yuemeng, Haghighi, Babak, Chitalia, Rhea, Abousamra, Shahira, Kurc, Tahsin M., Gastounioti, Aimilia, Er, Sezgin, Bergman, Mark, Saltz, Joel H., Fan, Yong, Shah, Prashant, Mukhopadhyay, Anirban, Tsaftaris, Sotirios A., Menze, Bjoern, Davatzikos, Christos, Kontos, Despina, Karargyris, Alexandros, Umeton, Renato, Mattson, Peter, Bakas, Spyridon
Publikováno v:
Commun Eng 2, 23 (2023)
Deep Learning (DL) has the potential to optimize machine learning in both the scientific and clinical communities. However, greater expertise is required to develop DL algorithms, and the variability of implementations hinders their reproducibility,
Externí odkaz:
http://arxiv.org/abs/2103.01006
Autor:
Liu, Yuanxi, Wu, Junwen wujunwen@swfu.edu.cn, Wu, Danzi, Xiao, Jiandong, Sun, Jianli, Zhao, Zhijuan
Publikováno v:
Canadian Journal of Forest Research. 2024, Vol. 54 Issue 2, p147-157. 11p.
Publikováno v:
In Journal of Materials Research and Technology November-December 2023 27:5651-5661