درخت حوزه‌های تخصصی

Background: The study of the psychological effects of this viral disease on the mental health of individuals at different levels of society, especially elite athletes, is of great importance.Aim: Present study aimed to investigate the psychological status of elite athletes during the COVID-19 pandemic.Materials and Methods: The statistical population of this study included 87 Iranian elite and national athletes in various sports. The statistical population of this study included 87 elite and national athletes in various sports. Data were collected using the stress, anxiety, depression inventory (DASS-14), perceived stress inventory (PSS-14), the revised event impact inventory (IES-R), and the Graz Emotional Disorders Questionnaire.Results: There is no significant difference between the components of depression, anxiety, event impact, and emotional disorders (P≥0.05). There is a significant difference between the mean scores obtained by elite athletes and the mean scores of the stress component (P=0.01). The mean scores obtained by elite athletes were lower than the mean scores in the perceived stress component (P=0.001).Conclusion: The elite Iranian athletes in the Corona pandemic are in a relatively good psychological state.

Objective : Off-grid renewable energy systems are essential for ensuring a sustainable and reliable electricity supply in regions where access to the conventional grid is limited or economically unjustifiable. Designing such systems requires systematic and efficient methodologies that can guide planners in selecting appropriate technologies under diverse environmental and consumption conditions. This study aims to develop an intelligent sizing framework for hybrid renewable energy systems by integrating expert knowledge with geographical, climatic, and load-related variables. The proposed model seeks to identify the optimal combination of photovoltaic panels, wind turbines, battery storage systems, and diesel generators for off-grid applications in Iran.  Methodology: The research methodology employs a two-stage approach. In the first stage, key variables influencing system sizing were identified through a comprehensive review of prior studies and structured interviews with academic and industrial experts. These interviews provided valuable operational insights, enabling the determination of qualitative ranges for model inputs and outputs. In the second stage, the collected expert knowledge was translated into fuzzy rules and implemented within a fuzzy inference system developed in MATLAB, forming an intelligent decision-support engine capable of evaluating multiple operational scenarios. Results : The findings indicate that the proposed model accurately determines optimal configurations for various geographical locations and consumption profiles. Model outputs showed less than 10% deviation from 80% of expert assessments. Moreover, the model generates sizing recommendations within minutes, significantly improving the speed of decision-making. Conclusion : In summary, the developed framework provides a practical and efficient tool for planners and stakeholders involved in designing off-grid hybrid renewable energy systems.