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Liu Yunlan,Ren Mengjuan,Kuang Zhuoran,Luo Xufei,Li Huishan,Zhang Yikai,Wen Wanxin,Cai Yefeng,Ni Xiaojia,Chen Yaolong 한국한의학연구원 2023 Integrative Medicine Research Vol.12 No.1
Background: Cerebral resuscitation is one of the main therapeutic aims in the treatment of cardiac arrest (CA) patients who experience a return of spontaneous circulation (ROSC). However, the therapeutic effects of current treatments are not ideal. The purpose of this study was to evaluate the efficacy of neurological function of acupuncture combined with conventional cardiopulmonary cerebral resuscitationthe (CPCR) for patients after ROSC. Methods: Seven electronic databases and other related websites were searched to identify studies on acupuncture combined with conventional CPCR for patients after ROSC. R software was used to conduct a meta-analysis, and the outcomes that could not be pooled were analyzed using a descriptive analysis. Results: Seven RCTs involving 411 participants who had experienced ROSC were eligible for inclusion. The main acupoints were Neiguan (PC6), Shuigou (DU26), Baihui (DU20), Yongquan (KI1), and Sanyinjiao (SP6). Compared to conventional CPCR, acupuncture combined with conventional CPCR led to signifi- cantly higher Glasgow Coma Scale (GCS) scores on day 3 (mean difference (MD) = 0.89, 95% CI: 0.43, 1.35, I 2 = 0%), day 5 (MD = 1.21, 95% CI: 0.27, 2.15; I 2 = 0%), and day 7 (MD = 1.92, 95% CI: 1.35, 2.50; I 2 = 0%). Conclusion: Acupuncture-assisted conventional CPCR may have a potential role in improving neurologi- cal function in CA patients after ROSC, but the certainty of evidence is very low and more high-quality studies are required.
Zhaoyang Qu,Wanxin Wang,Nan Qu,Yuqing Liu,Hongbo Lv,Kewei Hu,Jianyou Yu,Manyang Gao,Jiajun Song 대한전기학회 2019 Journal of Electrical Engineering & Technology Vol.14 No.6
Due to unfortunate mistake the grant numbers have been omitted in the acknowledgments section: This work is supported by the National Natural Science Foundation of China (No. 51437003), Jilin Province Science and Technology Development Plan Project of China (20160623004TC, 20180201092GX), Jilin Science and Technology Innovation Development Plan Project of China (201830817).
Zhaoyang Qu,Wanxin Wang,Nan Qu,Yuqing Liu,Hongbo Lv,Kewei Hu,Jianyou Yu,Manyang Gao,Jiajun Song 대한전기학회 2019 Journal of Electrical Engineering & Technology Vol.14 No.4
In order to improve the accuracy of forecasts of the electricity sales of power sales companies, a depth forecast model of electricity sales based on the characteristics of the power market is proposed. First, based on survival analysis, the calculation method of the user churn rate in the electricity market is given, and the number of users at a certain moment in the future is predicted. Then, users’ electricity consumption that calculated by the deep belief network and the predicted quantity of users are combined to design a forecast model of electricity sales. Finally, the model is solved utilizing the weighting algorithm of adaptive inertia. The analysis of the example shows that the proposed method achieves a signifi cant improvement in the accuracy of power sales forecasting.
Qu, Zhaoyang,Qu, Nan,Liu, Yaowei,Yin, Xiangai,Qu, Chong,Wang, Wanxin,Han, Jing The Korean Institute of Electrical Engineers 2018 Journal of Electrical Engineering & Technology Vol.13 No.5
With the wide application of intelligent household appliances, the optimization of electricity behavior has become an important component of home-based intelligent electricity. In this study, a multi-objective optimization model in an intelligent electricity environment is proposed based on economy and comfort. Firstly, the domestic consumer's load characteristics are analyzed, and the operating constraints of interruptible and transferable electrical appliances are defined. Then, constraints such as household electrical load, electricity habits, the correlation minimization electricity expenditure model of household appliances, and the comfort model of electricity use are integrated into multi-objective optimization. Finally, a continuous search multi-objective particle swarm algorithm is proposed to solve the optimization problem. The analysis of the corresponding example shows that the multi-objective optimization model can effectively reduce electricity costs and improve electricity use comfort.
Bo Zhang,Pudong Liu,Wanxin Liu,Xiaoshan Bai,Awais Khan,Jianping Yuan 제어·로봇·시스템학회 2024 International Journal of Control, Automation, and Vol.22 No.2
This paper proposes a receding horizon based motion planning method, which allows a sensoryconstrained quadrotor to dynamically plan obstacle-avoiding trajectories in unknown complex environments. First, a two-process search method is proposed to generate an initial feasible path satisfying the dynamics of the quadrotor. Second, the path smoothness is improved by solving a nonlinear optimization problem considering path safety and smoothness. Then, a uniform B-spline is used to interpolate the path with a receding horizon to achieve a safe and dynamically feasible trajectory with minimum trajectory time by solving an optimization problem. Finally, a time adjustment method is proposed based on the relationship between the distance of the B-spline trajectory and the obstacles. Extensive simulation results illustrate that the designed method doubles the safety range, defined as the minimum distance between the quadrotor and the obstacles, and consumes less than 70% of computational running time compared with the state-of-the-art. Outdoor flight experiments performed with a vision-based quadrotor show the satisfying performance of the motion planning approach.
Zhaoyang Qu,Nan Qu,Yaowei Liu,Xiangai Yin,Chong Qu,Wanxin Wang,Jing Han 대한전기학회 2018 Journal of Electrical Engineering & Technology Vol.13 No.5
With the wide application of intelligent household appliances, the optimization of electricity behavior has become an important component of home-based intelligent electricity. In this study, a multi-objective optimization model in an intelligent electricity environment is proposed based on economy and comfort. Firstly, the domestic consumer’s load characteristics are analyzed, and the operating constraints of interruptible and transferable electrical appliances are defined. Then, constraints such as household electrical load, electricity habits, the correlation minimization electricity expenditure model of household appliances, and the comfort model of electricity use are integrated into multi-objective optimization. Finally, a continuous search multi-objective particle swarm algorithm is proposed to solve the optimization problem. The analysis of the corresponding example shows that the multi-objective optimization model can effectively reduce electricity costs and improve electricity use comfort.
Zhaoyang Qu,Jiajun Song,Yuqing Liu,Hongbo Lv,Kewei Hu,Jian Sun,Miao Li,Wei Liu,Mingshi Cui,Wanxin Wang 대한전기학회 2019 Journal of Electrical Engineering & Technology Vol.14 No.6
The problem of load fuctuation in the distribution network and increasing power grid cost input caused by the unpredictable behavior of electric vehicle (EV) users in response to electricity price is investigated in this paper. An optimization model method for the charging and discharging price of electric vehicles is proposed, considering the vehicle owner response and power grid cost. The rule of EV user travel is frst analyzed, and the travel and battery state constraints are defned. Under the constraints of user charging and discharging behavior and battery characteristics, a user transfer rate and unit energy cost function is designed to construct a multi-objective model of charging and discharging price that minimizes electricity expenditure and avoids an increase in power grid investment. Finally, an improved multi-target fsh swarm algorithm is presented to solve the model optimization problem. The example analysis shows that the proposed method can reduce the peak-valley load diference of the system and cost input of the power grid, as well as provide users with regulation ability to access the power grid at diferent time periods