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Purpose: Badminton requires fast and pivoting movements, putting athletes at risk of sustaining an anterior cruciate ligament (ACL) injury. The primary purpose is to investigate the return to sport (RTS) and the return to performance (RTP) after an ACL injury in elite badminton athletes. The secondary purpose is to describe ACL injury mechanisms in elite badminton players. Methods: Athletes within the top 200 of the Badminton World Federation World Ranking who sustained an ACL injury between January 2001 and December 2021 were retrospectively included. An anonymous online survey was created in eight languages. RTS, RTP and contributing factors were analysed among athletes aiming to RTP. The injury mechanism was analysed in all participants. Results: Sixty‐six athletes from 32 countries were included. Fifty‐seven athletes (86.4%) aimed to RTP. Forty‐eight out of 57 (84.2%) did RTS. Twenty‐nine (50.9%) managed to successfully RTP. Forty‐nine (74.2%) of ACL injuries occurred during a competition, 14 (21.2%) occured during training. Thirty‐one (49.2%) occurred in the rear court backhand side and 47 (74.6%) occurred during landing after a jump. Conclusion: Forty‐eight out of 57 (84.2%) athletes managed to RTS. Half of the athletes managed to successfully RTP. Most of the ACL injuries occurred during competition, in the rear court backhand side and during landing after a jump. Level of Evidence: Level III. [ABSTRACT FROM AUTHOR]

The accurate evaluation of shale oil and gas reservoirs is of great significance to the integrated development of geology and engineering. Based on the core analysis, conventional logging, and array acoustic logging data, the total organic carbon, hydrocarbon generation potential, brittleness, and anisotropy of shale reservoirs were calculated. The p-wave time difference curves calculated by the artificial neural network (ANN) method and the conventional logging curve fitting method were compared. The multiresolution graph-based clustering (MRGC) method was used to classify shale reservoirs into three categories and evaluate the classification results. Brittle minerals such as quartz and feldspar were mainly found to be present in shale reservoirs and clay minerals which mainly consisted of illite. The Chang 73 reservoir is rich in organic matter and has great potential for survival. The p-wave time difference calculated by the fitting formula of the shear wave time difference meter demonstrated high accuracy and did not require a complex ANN model. MRGC method can well classify shale reservoir types. The classification results reduce the interference of human factors and are more scientific and reasonable. This research method is of great significance for the scientific classification and evaluation of shale reservoirs. [ABSTRACT FROM AUTHOR]