| 1 | Hofmeister Effect-Assisted Strong Natural Biopolymer-Based Hydrogels with Multi-Functions显示文摘Natural biopolymer-based hydrogels have been extensively studied in recent years due to their excellent biocompatibility.However,the preparation of multi-functional and tough natural biopolymer-based hydrogels is still a challenging problem.Herein,a natural biopolymer-based hydrogel is prepared using gelatin and carboxymethyl chitosan(CMCS)through a one-step soaking method.The prepared hydrogel without any synthetic polymers and crosslinking agents has a fully physical crosslinking structure.Due to the hydrophobic interaction brought by the Hofmeister effect,the mechanical properties of soaked hydrogels(tensile stress and strain can reach 3.77 MPa and 1082%)are superior to conventional protein hydrogels.In addition,the prepared gelatin/carboxymethyl chitosan(Gel/CMCS)hydrogels exhibit a variety of appealing properties,including good shape memory,fatigue resistance,electrical conductivity,water retention,drug releasing,antibacterial property,and recyclability.This strategy opens up a new horizon to fabricate hydrogels with excellent mechanical properties and multiple functions,which can extend their applications in the biomedicine area and other related fields. | Yaqian Cai Jiachuan Shi Fangzhe Liu Haichao Li Xinya Man Shuang Guan | 2021 | Chinese Journal of Chemistry2021，39，11： | 3 |
| 2 | Research on Driver Monitoring Systems Based on Vital Signs and Behavior Detection显示文摘Aiming at drivers’dangerous driving behavior monitoring and health monitoring,this paper designs an intelligent steering wheel that can monitor dan-gerous driving behavior and a steering wheel sleeve that can monitor physical health.The MTCNN model is primarily used to obtain a driver’s face image in real time.The PFLD algorithm was used to obtain the facial model positioning feature points,and the degree of driver fatigue was determined by combining the relevant parameters.The fatigue algorithm proposed in this paper can improve the effectiveness and accuracy of monitoring.Then,according to the LSTM network model,11 groups of key point information of the human body are obtained,and the human motion track is identified and then combined with the facial information to complete the judgment of driving behavior such as drinking water,smoking and walking.Through the PPG and ECG fusion algorithm based on LSTM,the reliability of the system to collect vital signs such as body temperature,blood pressure,heart rate and blood oxygen of the driver is improved.It was determined that the system could monitor a driver’s driving behavior in real time and consider its health management. | Man Niu Yanqing Wang Xinya Shu Xiaofeng Gao | 2023 | 国际计算机前沿大会会议论文集2023，，2： | 0 |
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