Quantification of Head Acceleration Events in Rugby League: An Instrumented Mouthguard and Video Analysis Pilot Study

Instrumented mouthguards (iMG) were used to collect head acceleration events (HAE) in men’s professional rugby league matches. Peak linear acceleration (PLA), peak angular acceleration (PAA) and peak change in angular velocity (ΔPAV) were collected using custom-fit iMG set with a 5 g single iMG-axis recording threshold. iMG were fitted to ten male Super League players for thirty-one player matches. Video analysis was conducted on HAE to identify the contact event; impacted player; tackle stage and head loading type. A total of 1622 video-verified HAE were recorded. Approximately three-quarters of HAE (75.7%) occurred below 10 g. Most (98.2%) HAE occurred during tackles (59.3% to tackler; 40.7% to ball carrier) and the initial collision stage of the tackle (43.9%). The initial collision stage resulted in significantly greater PAA and ΔPAV than secondary contact and play the ball tackle stages (p < 0.001). Indirect HAE accounted for 29.8% of HAE and resulted in significantly greater ΔPAV (p < 0.001) than direct HAE, but significantly lower PLA (p < 0.001). Almost all HAE were sustained in the tackle, with the majority occurring during the initial collision stage, making it an area of focus for the development of player protection strategies for both ball carriers and tacklers. League-wide and community-level implementation of iMG could enable a greater understanding of head acceleration exposure between playing positions, cohorts, and levels of play.

How to Stop a Fight - A Qualitative Video Analysis of How Third-parties De-escalate Real-life Interpersonal Conflicts in Public

Objective: While previous research agrees that third-parties often manage to de-escalate interpersonal conflicts when they intervene, we still know little about how they achieve this influence. The aim of the current study is to address this gap in the literature by investigating how third-parties de-escalate conflicts. Method: We conduct a two-part qualitative analysis of CCTV footage of 48 real-life conflicts from the streets of Amsterdam. The first part consists of an inductive analysis of CCTV-footage investigating the typical sequence of de-escalatory interventions. The second part consists of a deductive coding based on the findings from part 1 of the analysis. Results: We identify an ideal-typical model of de-escalation consisting of three phases: objection, separation, and placation. This model describes how third-parties adapt their intervention to the reaction of the antagonists of the conflict through a contingency principle: when the current phase of intervention fails to de-escalate the conflict, the third-party proceeds to the following phase of the model. We also identify observable intervention behaviors that are characteristic of each of the three phases. Conclusions: The findings demonstrate that there is not one way to de-escalate a conflict, but rather that third-parties are successful because they adapt their intervention to the situation at hand. The findings of this study imply that if we want to get closer to understanding when third-party interventions are effective, we need to acknowledge the complexity of these interventions and move beyond the action/inaction dichotomy.

The metabolic cost of turning right side up in the Mediterranean spur-thighed tortoise (Testudo graeca)

Armoured, rigid bodied animals, such as Testudines, must self-right should they find themselves in an inverted position. The ability to self-right is an essential biomechanical and physiological process that influences survival and ultimately fitness. Traits that enhance righting ability may consequently offer an evolutionary advantage. However, the energetic requirements of self-righting are unknown. Using respirometry and kinematic video analysis, we examined the metabolic cost of self-righting in the terrestrial Mediterranean spur-thighed tortoise and compared this to the metabolic cost of locomotion at a moderate, easily sustainable speed. We found that self-righting is, relatively, metabolically expensive and costs around two times the mass-specific power required to walk. Rapid movements of the limbs and head facilitate successful righting however, combined with the constraints of breathing whilst upside down, contribute a significant metabolic cost. Consequently, in the wild, these animals should favour environments or behaviours where the risk of becoming inverted is reduced.

Distributed AI embedded cluster for real-time video analysis systems with edge computing

Herein, on the basis of a distributed AI cluster, a real-time video analysis system is proposed for edge computing. With ARM cluster server as the hardware platform, a distributed software platform is constructed. The system is characterized by flexible expansion, flexible deployment, data security, and network bandwidth efficiency, which makes it suited to edge computing scenarios. According to the measurement data, the system is effective in increasing the speed of AI calculation by over 20 times in comparison with the embedded single board and achieving the calculation effect that matches GPU. Therefore, it is considered suited to the application in heavy computing power such as real-time AI computing.

Analysis of Volleyball Video Intelligent Description Technology Based on Computer Memory Network and Attention Mechanism

There are some problems in the process of video intelligent description and analysis of volleyball, such as poor effective information extraction rate and poor dynamic tracking effect. Based on this, combined with long-term and short-term memory network and attention mechanism, this paper designs an intelligent description model of volleyball video based on deep learning algorithm and studies how to improve the extraction rate of volleyball video information through intelligent detection hardware and image recognition technology. This paper first introduces the application of image recognition technology and deep learning algorithm in the intelligent description of volleyball video, then designs the volleyball video and image recognition model based on deep learning algorithm according to the requirements of volleyball video intelligent description, and selects three correlation factors related to the impact indicators of volleyball skills. This study selects three characteristic parameters associated with volleyball video analysis indexes, namely, take-off, bounce, and hand movement, combined with image sensing hardware assisted sensor network to realize real-time monitoring of action state in volleyball video analysis system. The experimental results show that, compared with the current mainstream sports video intelligent analysis and image recognition methods with data analysis as the core, the intelligent volleyball sports video intelligent description and image recognition system based on the integration of deep learning algorithm and sensor hardware assistance has the advantages of good detection effect, high data effectiveness, low cost, and high efficiency of volleyball sports video analysis. It can effectively improve the efficiency of volleyball video intelligent description.

The Effect of Using Small Group Discussions Through Zoom Breakout Room to Increase the Frequency of Individual Speaking Participation in the Speaking Courses

The purpose of this study is to determine whether the small group discussion method via breakout room zoom may boost student individual engagement in order for them to be more active and confident in learning speaking. This research study used a qualitative method with applied video analysis and questioners' perceptions of students as instruments. The findings found 17 active participants in the observation speaking class and 35 participants preferred small group discussions using the breakout room zoom application, with the majority preferring small group discussions because it helped them to be more active and confident. This method can also boost their confidence for more active participation for individual speaking in class, and they believe that small group discussions via breakout room zoom are the most effective way to deal with a pandemic.