A novel biodegradable polymer-coated sirolimus-eluting stent:1-year results of the HELIOS registry

Background:The HELIOS stent is a sirolimus-eluting stent with a biodegradable polymer and titanium oxide film as the tie-layer.The study aimed to evaluate the safety and efficacy of HELIOS stent in a real-world setting.Methods:The HELIOS registry is a prospective,multicenter,cohort study conducted at 38 centers across China between November 2018 and December 2019.A total of 3060 consecutive patients were enrolled after application of minimal inclusion and exclusion criteria.The primary endpoint was target lesion failure(TLF),defined as a composite of cardiac death,non-fatal target vessel myocardial infarction(MI),and clinically indicated target lesion revascularization(TLR)at 1-year follow-up.Kaplan-Meier methods were used to estimate the cumulative incidence of clinical events and construct survival curves.Results:A total of 2998(98.0%)patients completed the 1-year follow-up.The 1-year incidence of TLF was 3.10%(94/2998,95%closed interval:2.54-3.78%).The rates of cardiac death,non-fatal target vessel MI and clinically indicated TLR were 2.33%(70/2998),0.20%(6/2998),and 0.70%(21/2998),respectively.The rate of stent thrombosis was 0.33%(10/2998).Age≥60 years,diabetes mellitus,family history of coronary artery disease,acute myocardial infarction at admission,and device success were independent predictors of TLF at 1 year.Conclusion:The 1-year incidence rates of TLF and stent thrombosis were 3.10%and 0.33%,respectively,in patients treated with HELIOS stents.Our results provide clinical evidence for interventional cardiologists and policymakers to evaluate HELIOS stent.Clinical trial registration:ClinicalTrials.gov,NCT03916432.

Intelligent sorting method for assembly line based on visual positioning and robotic arm model predictive control

The existing steering device in the fruit and vegetable packaging assembly line cannot adjust the attitude of lettuce to a unified attitude,affecting the input and packaging process of the packaging machine.This study proposes an intelligent assembly line sorting method based on the visual positioning and model predictive control of a robotic arm.First,lightweight improvement based on the YOLOv5 is realized,the lettuce stalk in the background of the conveyor belt is promptly identified,the image of the lettuce stalk in the anchor box area is processed,and the edge contour point set is determined to extract the pixel coordinates of the optimal grasp point and mirror inclination angle of the lettuce.For the intelligent assembly line system,a robot arm kinematics model is constructed and the robot kinematics inverse solutions are calculated.Additionally,the lettuce movement speeds are dynamically measured by the vision system.A combination of the model prediction control,dynamic tracking,and rapid sorting of the lettuce by the robot claw is realized.The results show that the average detection time of a single frame image in the visual positioning part is 0.014 s,which is reduced by 50%;the accuracy and recall are 98%and 95%,respectively.The detection time is significantly reduced by ensuring accuracy.Within the current speed range of the packaging assembly line conveyor belt,the manipulator can grasp lettuce at different speeds stably and fast;the average axial error,average radial error,and adjusted average inclination angle error are 0.71 cm,1.02 cm,and 3.79°,respectively,verifying the high efficiency and stability of the model.The proposed method of this study enables application in the intelligent sorting operation of industrial assembly lines.