Effect of battle rope training on functional movements in young adults

Introduction and Aim: The battle rope exercise had obtained highest peak and mean VO2, highest energy expenditure and highest exercise heart rate than other exercises. There is no related evidence for Battle rope exercises by screening functional movement. The aim of the study was to determine the effect of battle rope training on functional movement screening. &#x0D; Methodology: According to inclusion and exclusion criteria 30 subjects were selected. They were explained about the safety and simplicity of the procedure and by the lottery system they were divided into two groups with 15 subjects in each group. Each subject has undergone pre-test and post-test measurement of functional movement screening (FMS). Group A participants did regular set of floor exercises like pelvic bridging, bird dog exercise, cat and camel exercise for 4 weeks. Group B participants did pelvic bridging, bird dog exercise, cat and camel exercise and battle rope training for 4 weeks. The data collected and tabulated, were statistically analysed. Functional movements: 7patterns of functional movements include deep squat, hurdle step, inline lunge, rotary stability, active straight leg raise, shoulder mobility, and trunk stability push-up.&#x0D; Results: The result of this study were statistically significant in FMS pretest and posttest with the p values (p&lt;0.0001). Between the posttest mean and standard deviation of FMS of both group A and group B are 14.53(2.78), and15.43 (2.60) respectively. And there was a significant difference among the values (p &gt;0.0001).&#x0D; Conclusion: This study concludes that battle rope training is better than traditional floor exercises in improving functional movements among young adults because of its simulation of functional movement patterns.</jats:p

An Intelligent Framework for Timely, Accurate, and Comprehensive Cloud Incident Detection

Cloud incidents (service interruptions or performance degradation) dramatically degrade the reliability of large-scale cloud systems, causing customer dissatisfaction and revenue loss. With years of efforts, cloud providers are able to solve most incidents automatically and rapidly. The secret of this ability is intelligent incident detection. Only when incidents are detected timely, accurately, and comprehensively, can they be diagnosed and mitigated at a satisfiable speed. To overcome the limitations of traditional rule-based detection, we carried out years of incident detection research. We developed a comprehensive AIOps (Artificial Intelligence for IT Operations) framework for incident detection containing a set of data-driven methods. This paper shares our recent experience of developing and deploying such an intelligent incident detection system at Microsoft. We first discuss the real-world challenges of incident detection that constitute the pain points of engineers. Then, we summarize our intelligent solutions proposed in recent years to tackle these challenges. Finally, we show the deployment of the incident detection AIOps framework and demonstrate its practical benefits conveyed to Microsoft cloud services with real cases.</jats:p