Comparative Study of the Long-Term Impact of the COVID-19 Pandemic on Mental Health and Nutritional Practices Among International Elite and Sub-Elite Athletes: A Sample of 1420 Participants from 14 Countries.

BACKGROUND: Although several studies have shown that the Coronavirus Disease 2019 (COVID-19) lockdown has had negative impacts on mental health and eating behaviors among the general population and athletes, few studies have examined the long-term effects on elite and sub-elite athletes. The present study aimed to investigate the long-term impact of COVID-19 lockdown on mental health and eating behaviors in elite versus sub-elite athletes two years into the pandemic. A cross-sectional comparative study was conducted between March and April 2022, involving athletes from 14 countries, using a convenient non-probabilistic and snowball sampling method. A total of 1420 athletes (24.5 ± 7.9 years old, 569 elites, 35% women, and 851 sub-elites, 45% women) completed an online survey-based questionnaire. The questionnaire included a sociodemographic survey, information about the COVID-19 pandemic, the Depression, Anxiety and Stress Scale-21 Items (DASS-21) for mental health assessment, and the Rapid Eating Assessment for Participants (REAP-S) for assessing eating behavior. RESULTS: The results showed that compared to sub-elite athletes, elite athletes had lower scores on the DASS-21 (p = .001) and its subscales of depression (p = .003), anxiety (p = .007), and stress (p < .001), as well as a lower REAP-S score indicating lower diet quality (p = .013). CONCLUSION: In conclusion, two years into the pandemic, elite athletes were likelier to have better mental health profiles than sub-elite athletes but surprisingly had lower diet quality.

The design of NMSS fractional-order predictive functional controller for unstable systems with time delay.

Open-loop unstable systems are more difficult to control than stable processes. In presence of time delay and uncertainty, the complexity of problem increases. In this paper, non-minimal state space predictive functional control (NMSS-PFC) infrastructure has been generalized for control of unstable systems with time delay. At first, NMSS system representation has been extended for a so-called coprime-factorized equivalent model of the unstable processes. Then, the proposed NMSS-fractional-order PFC (NMSS-FOPFC) has been formulated via a fractional order cost function in terms of the output tracking error vector. In the developed formulation and via the NMSS structure, the constraints on inputs of the system could be easily formulated and employment of fractional order cost function led to improved performance even in case of disturbances, perturbations or uncertainties. Closed loop robust stability analysis was also performed based on small gain theorem and verified via simulations. Simulation examples show that the proposed NMSS-FOPFC results in improved nominal and perturbed responses compared to conventional methods. Comparison has been carried out by considering integral of absolute error (IAE) and integral of squared error (ISE) as well as step response transient and steady state properties and the control effort.

AQM controller design for networks supporting TCP vegas: a control theoretical approach.

In this paper, a mathematical model and control theoretical framework for designing AQM controllers in networks supporting TCP Vegas is introduced. We have emphasized on a modified TCP Vegas algorithm that can respond to congestion signals through explicit congestion notification (ECN). The overall nonlinear delayed differential equations of the dynamics model of closed loop system have been derived based on TCP Vegas model. The model is then linearized to derive a transfer function representation between the packet marking probability and the bottleneck router queue length as the input and output of the modified TCP Vegas/AQM system. The model properties have been then examined especially for the case of single bottleneck homogeneous network which is closely investigated. Finally an AQM controller based on Coefficient Diagram Method (CDM) has been designed for the system and its performance has been compared with some other AQM controllers. CDM is a new indirect pole placement method that considers the speed, stability and robustness of the closed loop system in terms of time domain specifications. In order for synthesizing the simulation scenarios, our campus router traffic has been studied experimentally for a sample period of one hour and the corresponding parameters has been extracted. The simulation results are representative of good performance of developed TCP Vegas/AQM structure for different simulated scenarios.

Simplified modeling and generalized predictive position control of an ultrasonic motor.

Ultrasonic motors (USM's) possess heavy nonlinear and load dependent characteristics such as dead-zone and saturation reverse effects, which vary with driving conditions. In this paper, behavior of an ultrasonic motor is modeled using Hammerstein model structure and experimental measurements. Also, model predictive controllers are designed to obtain precise USM position control. Simulation results indicate improved performance of the motor for both set point tracking and disturbance rejection.