Muscle Contractile Properties Measured by the Tensiomyography (TMG) Method in Top-Level Football Players of Different Playing Positions: The Case of Serbian Super League

The aim of this study is to investigate the differences in muscle contractile properties measured by the TMG method between top-level football players of different playing positions. The sample consisted of 57 football players from the Serbian Super League, divided into three groups: defenders-DF, midfielders-MF, and forwards-FW. Muscles included in the study were the Rectus Femoris (RF), Vastus Medialis (VM), Vastus Lateralis (VL), Biceps Femoris (BF), and Semitendinosus (ST) of the right (R) and left (L) leg. The TMG parameters used in this study were contraction time (Tc), delay time (Td), relaxation time (Tr), maximal displacement (Dm), and sustain time (Ts). The ANOVA results showed that differences in TMG parameters between top-level football players of different playing positions are small and exist only in the Tr of RF (F = 4.658, p = 0.014), BF (F = 4.433, p = 0.016), and ST muscle (F = 3.808, p = 0.028), and the Tc (F = 3.214, p = 0.048) and Td (F = 3.705, p = 0.031) of the VM muscle. All differences were detected between DF and FW players, and all differences were in the left (non-dominant) leg. The results obtained in this study indicate that the training and selection process in football, from the aspect of functional and mechanical muscle properties, should be similar for all players, regardless of playing position. It has been shown that TMG has relatively low sensitive strength for detecting differences between football players of different playing positions.

Cyber Security: Effects of Penalizing Defenders in Cyber-Security Games via Experimentation and Computational Modeling

Cyber-attacks are deliberate attempts by adversaries to illegally access online information of other individuals or organizations. There are likely to be severe monetary consequences for organizations and its workers who face cyber-attacks. However, currently, little is known on how monetary consequences of cyber-attacks may influence the decision-making of defenders and adversaries. In this research, using a cyber-security game, we evaluate the influence of monetary penalties on decisions made by people performing in the roles of human defenders and adversaries via experimentation and computational modeling. In a laboratory experiment, participants were randomly assigned to the role of "hackers" (adversaries) or "analysts" (defenders) in a laboratory experiment across three between-subject conditions: Equal payoffs (EQP), penalizing defenders for false alarms (PDF) and penalizing defenders for misses (PDM). The PDF and PDM conditions were 10-times costlier for defender participants compared to the EQP condition, which served as a baseline. Results revealed an increase (decrease) and decrease (increase) in attack (defend) actions in the PDF and PDM conditions, respectively. Also, both attack-and-defend decisions deviated from Nash equilibriums. To understand the reasons for our results, we calibrated a model based on Instance-Based Learning Theory (IBLT) theory to the attack-and-defend decisions collected in the experiment. The model's parameters revealed an excessive reliance on recency, frequency, and variability mechanisms by both defenders and adversaries. We discuss the implications of our results to different cyber-attack situations where defenders are penalized for their misses and false-alarms.

A meta-analysis of the relationship between moral disengagement and bullying roles in youth

Over the last several years, researchers have become increasingly interested in the influence of moral factors on bullying behaviors. This is the first meta-analytic review to exclusively examine the relationship between moral disengagement (MD) and the key bullying roles of bully, victim, defender, and bystander. Forty-seven independent samples examining a total of 43,809 children/adolescents (aged 7-19) were included in this meta-analysis. Results indicated a positive relationship between MD and bullying (r = 0.31; 95% CI [0.27, 0.34]), MD and victimization (r = 0.08; 95% CI [0.05, 0.12]), and a negative relationship between MD and defending (r = -0.11; 95% CI [-0.17, -0.04]). No significant relationship was found for MD and bystanding behavior. Moderators of bullying type (traditional vs. cyberbullying), reporting type (self vs. peer report), age, and gender were included in the analyses. The results are discussed in the context of relevant literature with particular emphasis on the importance of distinguishing between guilty and unconcerned bystanders, and the significant overlap between bullying and victimization in the cyber context.