Therapeutic effect of a dualchamber pacemaker with the optimized program-control mode on long-qt syndrome

Objectives To explore the optimized program-control mode of a dual-chamber pacemaker combined withβ-blocker to treat congenital long QT syndrome(LQTS). Methods 12 LQTS patients in our hospital that still have symptoms despite use of regular drug therapies or that can not endure the therapies were implanted with DDD cardiac pacemaker.The QT/QTc intervals of those patients were measured at different pacing rates respectively.Their cardiac pacemakers were all programmed to selectively turn on and turn off some related functions at the pacing rate of 80 beats/min.The dosage ofβ-blockers was adjusted according to the patients’ PR intervals and blood pressures.The MACE and the cardiac function of the patients were recorded after operation.Results The measured QT / QTc interval decreased with the pacing rate increasing.The pacing rate of 80 beats/min can make QT/QTc interval basically normal. The MACE of the patients were statistically declined(P = 0.003) and no negative effect on cardiac function was found during the follow-up.Conclusions The optimized program-control mode of a dual-chamber pacemaker combined withβ-blocker to treat congenital LQTS are:to pace at the rate of 80 beats/min and program to turn off lag,sleep,automatic preventing PMT and automatic threshold-capture feature and turn on the PVC,rate adaptation and atrioventricular node priority function.

Increasing Undergraduate Student’s Satisfaction in Higher Educa-tion:Optimal Improvement Path Analysis

Undergraduate student’s satisfaction is fundamental to creating and implementing successful higher education.The present study sought to identify the factors and analyses impact on satisfaction and service quality.The research was carried out in Chinese higher education institution,with a sample of 1660 students.Based on the higher education satisfaction questionnaire,the“optimal path”model of problem improvement was constructed by applying the“structural equation model”,satisfaction and importance matrix diagram,improvement effect size and other tools.Eight major areas of three-dimensional improvement of“satisfaction,importance,and improvement effect”were formed.Identify the issues that students have urgent demands,high importance,and strong improvement effects.Scientifically analyze the main attention focus of each subgroup of students.Concentrate superior resources and strengths,formulate targeted measures and make key breakthroughs based on“light”,“heavy”,“slow”,“urgent”and“classified”.Provide suggestions for improving student’s satisfaction and promoting the development of high-quality connotative and characteristic development in higher education.

Dynamic multi-objective differential evolution algorithm based on the information of evolution progress

The multi-objective differential evolution(MODE)algorithm is an effective method to solve multi-objective optimization problems.However,in the absence of any information of evolution progress,the optimization strategy of the MODE algorithm still appears as an open problem.In this paper,a dynamic multi-objective differential evolution algorithm,based on the information of evolution progress(DMODE-IEP),is developed to improve the optimization performance.The main contributions of DMODE-IEP are as follows.First,the information of evolution progress,using the fitness values,is proposed to describe the evolution progress of MODE.Second,the dynamic adjustment mechanisms of evolution parameter values,mutation strategies and selection parameter value based on the information of evolution progress,are designed to balance the global exploration ability and the local exploitation ability.Third,the convergence of DMODE-IEP is proved using the probability theory.Finally,the testing results on the standard multi-objective optimization problem and the wastewater treatment process verify that the optimization effect of DMODE-IEP algorithm is superior to the other compared state-of-the-art multi-objective optimization algorithms,including the quality of the solutions,and the optimization speed of the algorithm.