Zobrazeno 1 - 10
of 34
pro vyhledávání: '"Tingting Mi"'
Publikováno v:
Shipin gongye ke-ji, Vol 44, Iss 2, Pp 170-177 (2023)
To clarify the species of the pathogens of soft rot of 'East Red' kiwifruit and the effect of melatonin on its control, using naturally disease 'East Red' kiwifruit as test material, the pathogenic bacteria of soft rot were isolated and cultured usin
Externí odkaz:
https://doaj.org/article/374c8c63a5bc4fd1920cb5bca7d87721
Autor:
Quanjiang Lv, Yiwei Cao, Rongfan Li, Ju Liu, Tianpeng Yang, Tingting Mi, Xiaowen Wang, Wei Liu, Junlin Liu
Publikováno v:
physica status solidi (a).
Publikováno v:
Journal of Bionic Engineering.
Publikováno v:
European Journal of Medical Research, Vol 29, Iss 1, Pp 1-11 (2024)
Abstract Objective Serum lipoprotein(a) [Lp(a)] is a risk factor of cardiovascular diseases. However, the relationship between the serum Lp(a) and clinical outcomes has been seldom studied in Chinese hospitalized patients with cardiovascular diseases
Externí odkaz:
https://doaj.org/article/e4bf5d07ab344068abbf09fee62ec936
Autor:
Senlin Fang, Zhengkun Yi, Tingting Mi, Zhenning Zhou, Chaoxiang Ye, Wanfeng Shang, Tiantian Xu, Xinyu Wu
Publikováno v:
IEEE Transactions on Automation Science and Engineering. :1-11
Publikováno v:
Journal of Luminescence. 257:119699
Autor:
Chaoxiang Ye, Xiaoyu Li, Binhua Huang, Yuanzhe Su, Tingting Mi, Zhenning Zhou, Zhengkun Yi, Xinyu Wu
Publikováno v:
2022 12th International Conference on CYBER Technology in Automation, Control, and Intelligent Systems (CYBER).
Autor:
Zhenning Zhou, Senlin Fang, Chaoxiang Ye, Tingting Mi, Binhua Huang, Xiaoyu Li, Zhengkun Yi, Xinyu Wu
Publikováno v:
2022 IEEE International Conference on Real-time Computing and Robotics (RCAR).
Publikováno v:
Micro and Nanostructures. 175:207489
Autor:
Dashun Que, Senlin Fang, Zhengkun Yi, Chaoxiang Ye, Xinyu Wu, Tingting Mi, Chengliang Liu, Zhenning Zhou
Publikováno v:
RCAR
One of the challenges for robots to grasp unknown objects is to predict whether objects will fall at the beginning of grasping. Evaluating robotic grasp state accurately and efficiently is a significant step to address this issue. In this paper, base