Search

Your search keyword '"Li, Jian-Hui"' showing total 661 results
Start Over Author "Li, Jian-Hui"
661 results on '"Li, Jian-Hui"'

15. Paired quasi-periodic pulsations of hard X-ray emission in a solar flare

Author

Zhao, Hai-Sheng, Li, Dong, Xiong, Shao-Lin, Zhang, Yan-Qiu, Su, Yang, Chen, Wei, Zhao, Yi, Li, Xiao-Bo, Liu, Jia-Cong, Peng, Wen-Xi, Qiao, Rui, Li, Xin-Qiao, Wen, Xiang-Yang, Song, Li-Ming, Zheng, Shi-Jie, Song, Xin-Ying, Zhao, Xiao-Yun, Huang, Yue, Zhang, Shuang-Nan, Xiao, Shuo, Cai, Ce, An, Zheng-Hua, Chen, Can, Chen, Gang, Chen, Wei, Du, Yan-Qi, Gao, Min, Gong, Ke, Guo, Dong-Ya, Guo, Zhi-Wei, He, Jian-Jian, Li, Bin, Li, Chao, Li, Chao-Yang, Li, Gang, Li, Jian-Hui, Li, Lu, Li, Qing-Xin, Li, Yan-Guo, Liang, Jing, Liang, Xiao-Hua, Liao, Jin-Yuan, Liu, Xiao-Jing, Liu, Ya-Qing, Luo, Qi, Ma, Xiang, Meng, Bin, Ou, Ge, Shi, Dong-Li, Shi, Jing-Yan, Sun, Gong-Xing, Sun, Xi-Lei, Tuo, You-Li, Wang, Chen-Wei, Wang, Hui, Wang, Jin, Wang, Jin-Zhou, Wang, Ping, Wang, Wen-Shuai, Wu, Hong, Xie, Sheng-Lun, Xu, Yan-Bing, Xu, Yu-Peng, Xue, Wang-Chen, Yang, Sheng, Yao, Min, Ye, Jian-Ying, Yi, Qi-Bin, Zhang, Chao-Yue, Zhang, Da-Li, Zhang, Fan, Zhang, Fei, Zhang, Hong-Mei, Zhang, Kai, Zhang, Peng, Zhang, Xiao-Lu, Zhang, Zhen, Zhao, Guo-Ying, Zhao, Shi-Yi, Zheng, Chao, Zhou, Xing, and Zhu, Yue

Published
2023
Full Text
View/download PDF

16. Chinese expert consensus on organ protection of transplantation (2022 edition)

Author

Li, Jian-Hui, Xu, Xiao, Wang, Yan-Feng, Xie, Hai-Yang, Chen, Jing-Yu, Dong, Nian-Guo, Badiwala, Mitesh, Xin, Li-Ming, Ribeiro, Roberto Vanin Pinto, Yin, Hao, Zhang, Hao, Zhang, Jian-Zheng, Huo, Feng, Yang, Jia-Yin, Yang, Hong-Ji, Pan, Hui, Li, Shao-Guang, Qiao, Yin-Biao, Luo, Jia, Li, Hao-Yu, Jia, Jun-Jun, Yu, Hao, Liang, Han, Yang, Si-Jia, Wang, Hao, Liu, Zhong-Yang, Zhang, Li-Cheng, Hu, Xiao-Yi, Wu, Hao, Hu, Yi-Qing, Tang, Pei-Fu, Ye, Qi-Fa, and Zheng, Shu-Sen

Published
2022
Full Text
View/download PDF

19. Postauricular Approach

Author

Su, Yu, Li, Jian-hui, Lee, Su Jeong, Wang, Hui-bing, Gao, Bo, Liu, Ya-qing, Han, Bing, Sun, Yi, Sun, Bao-chun, Gao, Song, Guo, Chang, Ma, Kun, Jin, Zhan-guo, Xue, Jun-fang, Cai, Chao-chan, Xin, Feng, Yan, Xu-kun, Gao, Xue, Cousins, Vincent C, Dai, Pu, editor, Cousins, Vincent C, editor, Song, Yue-shuai, editor, and Gao, Xue, editor

Published
2021
Full Text
View/download PDF

21. Protective effect of FK506 combined with hypothermic mechanical perfusion on donor liver of rats

Author

JIANG Li, LI Jian-hui, YU Hao, LI Hao-yu, XIE Hai-yang, ZHOU Lin, ZHENG Shu-sen

Subjects
hypothermic machine perfusion, fk506, liver transplantation, ischemia reperfusion injury, Medicine
Abstract

Objective To investigate the protective effects of FK506 combined with low temperature mechanical perfusion on the reduction of ischemia reperfusion injury of rat liver transplants. Methods SD rats were divided into HTK group and FK506 + HTK group. Orthotopic liver transplantation was performed 3 hours after machine perfusion of 150 mL HTK (HTK group) or FK506+150 mL HTK (FK506 + HTK group). Blood samples were collected at 3 and 24 hours after transplantation in both groups, and serum samples were centrifuged for liver function test. Twenty-four hours after transplantation, liver tissues were collected and fixed with formalin for HE staining. Results Serum ALT levels in FK506+HTK group were significantly lower than that in HTK group (P＜0.05). Inflammatory infiltration in FK506+HTK group was less than that in the HTK group, and the liver structure was intact. Conclusions FK506 added into perfusate for machine perfusion of the donor liver can effectively reduce liver function damage and inflammation damage within 3 hours after transplantation, and has a certain protective effect on the liver.

Published
2021

36. Machine-learning-based model and simulation analysis of PM2.5 concentration prediction in Beijing

Author

QU Yue, QIAN Xu, SONG Hong-qing, HE Jie, LI Jian-hui, and XIU Hao

Subjects
machine learning, pm2.5, meteorological condition, neural networks, long short-term memory, pollution prediction, Mining engineering. Metallurgy, TN1-997, Environmental engineering, TA170-171
Abstract

In recent years, the air quality in China has become a matter of serious concern. Among the available indicators for evaluating air quality, PM2.5 is one of the most important. It comprises a complex mixture of extremely small particles and liquid droplets emitted into the air, whose diameters are no more than 2.5 μm. Environments with a high PM2.5 index are extremely harmful to human health. Once inhaled, these particles can affect the heart and lungs and cause serious health problems. Air pollution is closely related to meteorological conditions such as wind speed, wind direction, atmospheric stability, temperature, and air humidity. With the development of various machine learning methods, deep learning models based on neural networks are increasingly applied in air pollution research. In this study, the temperature, humidity, wind velocity data at different pressure altitudes from 8 locations around Beijing and average of PM2.5 data in Beijing were analyzed and normalized. Multi-dimensional data was ideal for research applications using machine learning methods. and three neural network models were built, including the back propagation (BP), convolutional neural network (CNN), and long short-term memory (LSTM) models, and trained them using the meteorological and PM2.5 data.The results indicate that the accuracies of the back propagation and convolutional neural network models in predicting the PM2.5 pollution level in the next hour is much lower than that of the long short-term memory model. The PM2.5 pollution index predicted for the next hour by the long short-term memory model is very close to the actual value. This result reveals the strong relationship between the PM2.5 pollution index of Beijing and the local meteorological conditions. The long short-term memory model is trained using meteorological data from different pressure altitudes, and found it to be more accurate in predicting pollution levels when using near-surface meteorological data than that obtained from multiple altitudes.

Published
2019
Full Text
View/download PDF

46. QUANTUM-BEHAVED BAT ALGORITHM COMBINING CONVERGENCE FACTOR AND SELF-LEARNING MUTATION STRATEGIES FOR OPTIMIZATION.

Author

CHEN, Yao, CHEN, Si, and LI, Jian-Hui

Subjects
DIFFERENTIAL evolution, AUTODIDACTICISM, PARTICLE swarm optimization, IMAGE segmentation, ALGORITHMS, CHARACTERISTIC functions, SEARCH algorithms
Abstract

Quantum-behaved Bat Algorithm (QBA) has been successfully applied as an optimal technique for dealing with a variety of optimization problems. Nevertheless, QBA suffers from similar problems as other swarm intelligent algorithms, such as poor exploration search and falling into local optima in certain conditions. Aiming at these shortcomings, an improved algorithm that combines convergence factor and gold sinusoidal self-learning mutation strategies (CGQBA) is proposed. A directional convergence factor is designed for the global position update process, it can improve the exploration search ability of the algorithm. Meanwhile, a selflearning predictive mutation mechanism is added to the algorithm. It contributes to the algorithm to jump out of the local extremum. The improved CGQBA algorithm is tested on 20 test functions with different characteristics in the numerical simulation experiments. The results and statistical tests show that CGQBA algorithm has better convergence speed, accuracy and stability. What is more, the multi-threshold image segmentation is modelled as an optimization problem, CGQBA algorithm is applied to the optimization problem to further verify the effectiveness and practicability in the real-world optimization. The results compared with three classical segmentation methods illustrate that CGQBA algorithm can effectively solve the image segmentation problem. It has a better segmentation effect and anti-noise ability. [ABSTRACT FROM AUTHOR]

Published
2023
Full Text
View/download PDF

Catalog

Books, media, physical & digital resources
See catalog results