Zobrazeno 1 - 10
of 513
pro vyhledávání: '"LU Binbin"'
Publikováno v:
Polish Journal of Microbiology, Vol 73, Iss 4, Pp 455-465 (2024)
Human papillomavirus type 51 (HPV-51) is associated with various cancers, including cervical cancer. Examining the codon usage bias of the organism can offer valuable insights into its evolutionary patterns and its relationship with the host. This st
Externí odkaz:
https://doaj.org/article/7315ccf4ad724100a89dca14558690ce
Autor:
Murakami, Daisuke, Tsutsumida, Narumasa, Yoshida, Takahiro, Nakaya, Tomoki, Lu, Binbin, Harris, Paul
Although geographically weighted Poisson regression (GWPR) is a popular regression for spatially indexed count data, its development is relatively limited compared to that found for linear geographically weighted regression (GWR), where many extensio
Externí odkaz:
http://arxiv.org/abs/2305.08443
Publikováno v:
Journal of Geodesy and Geoinformation Science, Vol 7, Iss 2, Pp 37-51 (2024)
Population aging has become an inevitable trend and exerted profound influences on socio-economic development in China. In this study, we utilized data from national population census and statistical yearbooks in 2010 and 2020 to explore spatio-tempo
Externí odkaz:
https://doaj.org/article/52f611c1d4824c858f30a0839f8b94c9
Publikováno v:
In Applied Energy 1 November 2024 373
Publikováno v:
In Microchemical Journal October 2024 205
Autor:
Zeng, Shitong, Hu, Xingru, Sun, Shihao, Liu, Shan, Liang, Taibo, Lu, Binbin, Guo, Yalong, Zhang, Weichen, lei, Yu, Han, Lin, Xie, Jianping
Publikováno v:
In Microchemical Journal January 2025 208
Publikováno v:
In Journal of Water Process Engineering January 2025 69
Autor:
Zhang, Hang, Dong, Guanpeng, Li, Bing, Xie, Zunyi, Miao, Changhong, Yang, Fan, Gao, Yang, Meng, Xiaoyu, Yang, Dongyang, Liu, Yong, Zhang, Hongjuan, Wu, Leying, Shi, Fanglin, Chen, Yulong, Wu, Wenjie, Laszkiewicz, Edyta, Liang, Yutian, Lu, Binbin, Yao, Jing, Li, Xuecao
Publikováno v:
In International Journal of Applied Earth Observation and Geoinformation September 2024 133
GWR is a popular approach for investigating the spatial variation in relationships between response and predictor variables, and critically for investigating and understanding process spatial heterogeneity. The geographically weighted (GW) framework
Externí odkaz:
http://arxiv.org/abs/2109.14542
Publikováno v:
In Resources, Environment and Sustainability March 2024 15