Reference Values of Physical Performance in Handball Players Aged 13-19 Years: Taking into Account Their Biological Maturity.

Biological maturity status significantly influences success in handball, impacting an athlete's performance and overall development. This study aimed to examine the anthropometric and physical performance variables concerning age and maturity status, establishing reference values for physical performance among Tunisian players. A total of 560 handball players (309 males and 251 females aged 13-19 years) were categorized based on maturity status: early (n = 98), average (n = 262), and late (n = 200), determined through Mirwald and colleagues' equations. Anthropometric, physical fitness, and physiological data were collected for reference value creation. Our findings revealed significantly higher anthropometric parameters (p = 0.003) in late-maturing athletes compared to their early-maturing counterparts. Post-pubertal athletes showed significantly superior (p = 0.002) jumping ability, change of direction, and aerobic performance compared to their pre-pubertal peers. Additionally, male athletes outperformed females in both fitness (p = 0.001) and aerobic (p = 0.001) performance. A notable age-by-maturity interaction emerged for most performance outcomes (η2 ranging from 0.011 to 0.084), highlighting increased sex-specific differences as athletes progressed in age. Percentile values are provided for males and females, offering valuable insights for coaches and sports scientists to design personalized training programs. Understanding a player's performance relative to these percentiles allows trainers to tailor workouts, addressing specific strengths and weaknesses for enhanced development and competitiveness.

Role of Optimization in RNA-Protein-Binding Prediction.

RNA-binding proteins (RBPs) play an important role in regulating biological processes, such as gene regulation. Understanding their behaviors, for example, their binding site, can be helpful in understanding RBP-related diseases. Studies have focused on predicting RNA binding by means of machine learning algorithms including deep convolutional neural network models. One of the integral parts of modeling deep learning is achieving optimal hyperparameter tuning and minimizing a loss function using optimization algorithms. In this paper, we investigate the role of optimization in the RBP classification problem using the CLIP-Seq 21 dataset. Three optimization methods are employed on the RNA-protein binding CNN prediction model; namely, grid search, random search, and Bayesian optimizer. The empirical results show an AUC of 94.42%, 93.78%, 93.23% and 92.68% on the ELAVL1C, ELAVL1B, ELAVL1A, and HNRNPC datasets, respectively, and a mean AUC of 85.30 on 24 datasets. This paper's findings provide evidence on the role of optimizers in improving the performance of RNA-protein binding prediction.

Design of Adaptive Fractional-Order Fixed-Time Sliding Mode Control for Robotic Manipulators.

In this investigation, the adaptive fractional-order non-singular fixed-time terminal sliding mode (AFoFxNTSM) control for the uncertain dynamics of robotic manipulators with external disturbances is introduced. The idea of fractional-order non-singular fixed-time terminal sliding mode (FoFxNTSM) control is presented as the initial step. This approach, which combines the benefits of a fractional-order parameter with the advantages of NTSM, gives rapid fixed-time convergence, non-singularity, and chatter-free control inputs. After that, an adaptive control strategy is merged with the FoFxNTSM, and the resulting model is given the label AFoFxNTSM. This is done in order to account for the unknown dynamics of the system, which are caused by uncertainties and bounded external disturbances. The Lyapunov analysis reveals how stable the closed-loop system is over a fixed time. The pertinent simulation results are offered here for the purposes of evaluating and illustrating the performance of the suggested scheme applied on a PUMA 560 robot.

An Intelligent Automated System for Detecting Malicious Vehicles in Intelligent Transportation Systems.

The exponential growth of intelligent vehicles(IVs) development has resulted in a complex network. As the number of IVs in a network increases, so does the number of connections. As a result, a great deal of data is generated. This complexity leads to insecure communication, traffic congestion, security, and privacy issues in vehicular networks (VNs). In addition, detecting malicious IVs, data integration, and data validation are major issues in VNs that affect network performance. A blockchain-based model for secure communication and malicious IV detection is proposed to address the above issues. In addition, this system also addresses data integration and transaction validation using an encryption scheme for secure communication. A multi-chain concept separates the legitimate and malicious data into two chains: the Integrity chain (I-chain) and Fraud chain (F-chain). This multi-chain mechanism solves the storage problem and reduces the computing power. The integration of blockchain in the proposed model provides privacy, network security, transparency, and immutability. To address the storage issue, the InterPlanetary File System (IPFS) is integrated with Certificate Authority (CA). A reputation mechanism is introduced to detect malicious IVs in the network based on ratings. This reputation mechanism is also used to prevent Sybil attack. The evaluation of the proposed work is based on the cost of smart contracts and computation time. Furthermore, two attacker models are presented to prevent the selfish mining attack and the Sybil attack. Finally, a security analysis of the proposed smart contracts with their security vulnerabilities is also presented.

Specific physical performances among male elite youth soccer players: effect of maturity status.

BACKGROUND: There is a lack of studies that investigated the relationship between anthropometric profile, biological maturity and specific soccer performances. Therefore, the aims of the present study were to establish normative data of anthropometric and specific physical performances and to determine the impact age and somatic maturation on young soccer players (U13-U19, n=487). METHODS: Measurements include anthropometric variables to determine the age of peak height velocity (PHV), leg muscle volume (LMV) and soccer specific test (SST); Squat jump (SJ), Counter Movement jump (CMJ), sprint 10 meter (T10m), sprint 20 meter (T20m), sprint 30 meter (T30m) and intermittent-endurance tests. RESULTS: Reference values showed a significant difference between anthropometric variables, LMV and SST according to PHV categories. (M)ANOVA analysis showed a significant age using maturity interaction effect of all anthropometric variables. A significant result was reported in the majority of SST performances for the age, the T10m and for T20m performances. The full model of multiple regressions and the multiple equations was used to determine the best predictors of physical performances according to anthropometric variables. CONCLUSIONS: This study provides normative data for anthropometric characteristics and physical performances according to chronological age (U13-U19) and maturity groups of young soccer players.

Soccer-related performance in eumenorrheic Tunisian high-level soccer players: effects of menstrual cycle phase and moment of day.

BACKGROUND: This study aimed to examine the combined effects of menstrual cycle phase and moment of day on female soccer players' performances in the five-jump test (5JT), the repeated shuttle-sprint ability test (RSSA), and the Yo-Yo intermittent recovery test level 1 (YYIRT1). METHODS: Eleven eumenorrheic Tunisian high-level soccer players volunteered to participate. Each subject individually participated in three testing periods: one in the early follicular phase (menses), one in the late follicular phase, and another in the luteal phase. In each period, two test sessions were conducted: one at 07:30 and another at 17:30. The testing routines included the 5JT, the RSSA, and the YYIRT1. RESULTS: None of the measured variables were altered due to menstrual cycle phase (all P>0.05). Mean time during RSSA was significantly lower in the afternoon session compared to the morning session (8.48±0.27 s and 8.77±0.34 s, respectively, P<0.001), while 5JT performance was significantly higher in the afternoon compared to the morning (9.08±0.58 m and 8.60±0.56 m, respectively, P<0.001). CONCLUSIONS: Soccer-specific endurance as well as jumping and repeated sprinting ability of Tunisian female high-level soccer players are not affected due to menstrual cycle phase neither in the morning nor in the afternoon.

Reference values of vertical jumping performances in healthy Tunisian adolescent.

BACKGROUND: The assessment of normal values of muscle strength can be determined for the health outcome of adolescents, especially those who are living in a developing country. AIMS: The purpose of this study is to identify the relationship between anthropometric variables and vertical jumping performances. The jump height and the average of power were measured to establish reference values of vertical jumping parameters in Tunisian healthy adolescents aged 13-19 in both sexes. SUBJECTS AND METHODS: Five hundred and twenty-five school adolescents (242 males and 283 females) were randomly selected to participate in this study. Maximum height and average of power reached in countermovement jump and squat jump were provided by an Optojump device. Full and stepwise regression models were used to identify which anthropometric parameters significantly contributed to performance variables. RESULTS: All anthropometric parameters increased with age. Reference values and multiple prediction equations of vertical jump parameters were set based on a large sample of healthy Tunisian adolescents. The multiple regressions showed that age, mass, sitting height, waist size, fat-free mass and leg muscle volume for boys and mass for girls were the best predictors of jumping performances. CONCLUSION: This study provides normative data for jumping performances in Tunisian healthy adolescents aged 13-19 in both sexes. The percentiles values are calculated to estimate the levels of adolescents with high or low jumping performances.