درخت حوزه‌های تخصصی

This study aimed to investigate the relationships between curiosity, social support, and emotion regulation in individuals with specific learning disorders (SLD). The objective was to determine how social support and emotion regulation predict levels of curiosity in this population, providing insights for effective interventions. The study employed a cross-sectional design with a sample size of 252 participants, selected based on the Morgan and Krejcie table. Data were collected using the Curiosity and Exploration Inventory-II (CEI-II) for curiosity, the Multidimensional Scale of Perceived Social Support (MSPSS) for social support, and the Difficulties in Emotion Regulation Scale (DERS) for emotion regulation. Pearson correlation and linear regression analyses were conducted using SPSS-27 to examine the relationships between the variables. Descriptive statistics indicated moderate levels of curiosity, social support, and emotion regulation among participants. Pearson correlation analysis revealed significant positive correlations between curiosity and both social support (r = 0.52, p < 0.001) and emotion regulation (r = 0.46, p < 0.001). Regression analysis showed that social support and emotion regulation collectively accounted for 37% of the variance in curiosity (R² = 0.37, F(2, 249) = 72.19, p < 0.001). Both social support (B = 0.32, p < 0.001) and emotion regulation (B = 0.25, p < 0.001) emerged as significant predictors of curiosity. The findings highlight the significant roles of social support and emotion regulation in fostering curiosity among individuals with SLD. Supportive social environments and effective emotion regulation strategies are critical for promoting curiosity and engagement. These insights can inform the development of targeted interventions aimed at enhancing the well-being and academic success of individuals with SLD.

Perishable items such as dairy products, food and medicine, various vegetables, flowers and plants, ready-mix concrete, and blood packages typically have a limited shelf life from production to delivery and can deteriorate over time. To prevent such perishability, these types of products must be delivered to consumers promptly to ensure that the benefits of the producer and distributor are met. One effective factor in delivering various products to the consumer on time is selecting the optimal route for delivering goods or products, which is referred to as the problem of vehicle routing. Vehicle routing for distributing various goods and products is one of the practical issues in the field of research in operations that are very efficient in logistics planning. The objective of this problem is to determine the operational plan of the target vehicles with limited capacity for sending goods and products from the central warehouse depot to a group of consumers that are geographically dispersed in such a way that the number of required vehicles and travel costs are minimized. Considering that the issue mentioned is a very complex problem and it is not possible to find a high-quality answer with accurate methods in a short time for its large scale, the GAMS software has been used to solve this model on a smaller scale. Finally, to demonstrate the practical application of the proposed model in the real world, the distribution of products among customers in the Ports and Maritime Organization of Guilan Province (Bandar-e Anzali) has been studied. The computational results show that distributors can reduce their operational costs by using this approach.