Zobrazeno 1 - 10
of 726
pro vyhledávání: '"CHUNXIAO ZHANG"'
Publikováno v:
Animal Nutrition, Vol 19, Iss , Pp 166-179 (2024)
A 10-week feeding trial, followed by 24-h nitrite stress, was performed to evaluate the effects of dietary selenium-L-methionine (Se-Met) on growth, Se accumulation, antioxidant capacity, transcripts of selenoproteins and histological changes of musc
Externí odkaz:
https://doaj.org/article/ddf199b9b90a4f8180f2d96ee72f090d
Autor:
Yunlong Zhang, Yikun Zhao, Shipeng Ma, Rui Wang, Chunxiao Zhang, Hongli Tian, Yongxue Huo, Yaming Fan, Hongmei Yi, Yawei Liu, Jianrong Ge, Xiaohui Li, Jiuran Zhao, Fengge Wang
Publikováno v:
Computational and Structural Biotechnology Journal, Vol 23, Iss , Pp 2883-2891 (2024)
Crop pedigrees incorporate information on the kinship and genetic evolutionary history of breeding materials. Complete and accurate pedigree information is vital for effective genetic improvement of crops and maximal exploitation of heterosis in crop
Externí odkaz:
https://doaj.org/article/bcd9a0838b784ea880d3af1e111b2978
Autor:
Zerui Hua, Chunxiao Zhang, Jingru He, Yuyan Chen, Shaolong Zhang, Jingxia Sun, Ning Wang, Jun Zhang, Xin Yang, Jiayue Chen, Xiaolan Wei
Publikováno v:
ACS Omega, Vol 9, Iss 47, Pp 47194-47202 (2024)
Externí odkaz:
https://doaj.org/article/352fd3791ef54188b1b2fc4343da1edd
Publikováno v:
Energy and Built Environment, Vol 6, Iss 1, Pp 18-26 (2025)
Hourly global solar radiation data is an important factor for solar energy utilization. Due to the lack of solar radiation observation stations in many areas, some hourly solar radiation models are proposed to predict hourly solar radiation. However,
Externí odkaz:
https://doaj.org/article/53ef522020554b3a8ac4d2554dbb06f0
Autor:
Xinyuan Li, Shengxiong Lin, Xueshan Li, Kangle Lu, Ruijuan Ma, Kai Song, Yong Lin, Ling Wang, Chunxiao Zhang
Publikováno v:
Aquaculture Reports, Vol 39, Iss , Pp 102491- (2024)
Tianchongyou (TC), is a feed ingredient that contains defatted yellow mealworm and the medium during their growth with a crude protein content of more than 65 %. Our previous research found that TC utilization of spotted seabass (Lateolabrax maculatu
Externí odkaz:
https://doaj.org/article/81d9a05b5a474889a612ea25a82a63b9
Publikováno v:
Frontiers in Marine Science, Vol 11 (2024)
IntroductionThe present study aimed to evaluate the effects of substituting fish meal with pork meal in feed on the growth performance, feed utilization, intestinal morphology, and immune function of Penaeus monodon.MethodsA total of 600 uniformly si
Externí odkaz:
https://doaj.org/article/3dea9a23aaf0424eb23199aa40a501ca
Publikováno v:
International Journal of Applied Earth Observations and Geoinformation, Vol 134, Iss , Pp 104239- (2024)
Climate change caused by rapid urbanization in the Guanzhong region of China is becoming an increasingly significant problem. Previous empirical studies have confirmed that landscape patterns inextricably linked with the thermal environment, but stat
Externí odkaz:
https://doaj.org/article/646ccd29ef464733ac5deb81cdf1a219
Publikováno v:
Heliyon, Vol 10, Iss 17, Pp e37370- (2024)
Microplastics have emerged as pervasive contaminants, and determining their occurrence in aquafeed is key for evaluating their risks to farmed animals and, by extension, humans. However, knowledge about microplastic in aquafeed is still limited. Here
Externí odkaz:
https://doaj.org/article/7c7f138d7f4d4a448fc86646833f2404
Autor:
Heng Li, Yuqian Hu, Chunxiao Zhang, Dingtao Shen, Bingli Xu, Min Chen, Wenhao Chu, Rongrong Li
Publikováno v:
International Journal of Applied Earth Observations and Geoinformation, Vol 133, Iss , Pp 104101- (2024)
Recent research has shown that deep learning (DL) faces physical realism challenges in predicting runoff responses under climate change, mainly due to DL’s data dependence and lack of process understanding. In this study, a physics-encoded neural n
Externí odkaz:
https://doaj.org/article/47d710f8145246738b95cb95b06324bf
Publikováno v:
International Journal of Applied Earth Observations and Geoinformation, Vol 131, Iss , Pp 103972- (2024)
Given the increased incidence of pluvial floods due to climate change and urbanization, the demand for highly efficient and accurate modeling within urban drainage systems has intensified, making machine learning and deep learning techniques increasi
Externí odkaz:
https://doaj.org/article/f586b4831e5e4cdd8f98f7932b8da0a8