This paper aims to explore the issue of human actions in Islamic thought, focusing on the various stances regarding determinism, free will, and the intermediate position between them. This topic is linked to an ontological question: What are the limits of human responsibility for their actions? Our view is that the different positions on human actions reflect the presence of pluralism within Islamic thought, specifically through the discipline of Islamic theology (kalām). The difference in positions about the human actions within the science of theology expresses the vitality of Islamic thought and its appreciation of the right to differ between theological schools such as the Mu’tazila, Shi’a, and Sunnis, especially in an era dominated by the rationalism of Mu’tazila thought influenced by the methodology of Greek philosophical thought. This difference was recognized, especially in the third and fourth centuries AH/ninth and tenth centuries AD. We consider this difference in discussing the subject of the human actions as evidence of the principle of pluralism in Islam, which allows us to speak of the existence of a significant degree of intellectual tolerance, a subject that has not been studied to date. The prevailing view in studies today on this subject is that the theological groups accuse each other of unbelief, which is a mistaken position, because the saying of unbelief did not appear until after the fourth century AH/tenth century AD when transmission, reliability, and conservatism prevailed in Islamic thought. In addressing this issue, we examine three major stances on human actions as represented by three theological schools: The Mu’tazila (who advocated free will in human actions), the Jabriya (who advocated determinism in human actions), and the Ash’ariyya (who upheld the theory of acquisition). Once this is accomplished, we will explore the philosophy of pluralism in Islam through the lens of kalām. The most important conclusion we reached is that the debate on human actions opened, by the mid-4th century AH/10th century CE, an intellectual horizon that laid the foundations for pluralism in Islamic theological discussions. However, this horizon was soon closed due to various factors, which we have discussed throughout the paper.

With the rapid increase in electric bicycle (e-bikes) use, the rate of associated traffic accidents has also escalated. Prior studies have extensively examined e-bike riders’ injury risks, yet there is a limited understanding of how their behavior contributes to these accidents. This study aims to explore the relationship between e-bike riders’ risk-taking behaviors and the incidence of traffic accidents, and to propose targeted safety measures based on these insights. Utilizing a mixed-methods approach, this research integrates quantitative data from traffic accident reports and qualitative observations from naturalistic studies. The study employs a binary logistic regression model to analyze risk factors and uses observational data to substantiate the model findings. The analysis reveals that assertive driving behaviors among e-bike riders, such as running red lights and speeding, significantly contribute to the high rate of accidents. Moreover, the lack of protective gear and inadequate safety training are identified as critical factors increasing the risk of severe injuries. The study concludes that comprehensive policy interventions, including stricter enforcement of traffic laws and mandatory safety training for e-bike riders, are essential to mitigate the risks associated with e-bike use. The findings advocate for an integrated approach to urban traffic management that enhances the safety of all road users, particularly vulnerable e-bike riders.

This study investigates the core competencies essential for product designers to excel in cross-cultural global markets, with particular emphasis on implications for human resource development and organizational leadership. As design practices increasingly transcend cultural and geographical boundaries, designers are required to integrate advanced technical proficiency, creative problem-solving, technological adaptability, and cultural intelligence to create inclusive, socially responsible, and market-relevant products. Employing a mixed-methods approach—including focus groups and surveys with design professionals, industry executives, and academic leaders—the research identifies key competencies such as flexibility, intercultural communication, ethical integrity, and systems thinking. The findings underscore the necessity of balancing technical expertise with emotional intelligence and transformational leadership capabilities to effectively lead diverse, cross-functional teams. These competencies contribute significantly to fostering innovation, enhancing employee well-being and job satisfaction, and strengthening organizational resilience, thereby supporting sustainable human resource strategies. Furthermore, the study highlights the importance of continuous professional development and lifelong learning in cultivating culturally competent and ethically driven design talent. The insights offer strategic guidance for human resource professionals, organizational leaders, and educational institutions aiming to develop adaptive, inclusive, and future-ready design capabilities aligned with evolving global demands.

The study focused on investigating the effects of varying levels of HA (HA₁ = 0, HA₂ = 25, HA₃ = 50, HA₄ = 75, and HA₅ = 100) on Red Dragon, Red Prince, and Red Meat varieties of red radish. This analysis aimed to unravel the relationship between different levels of HA and their impact on the growth and productivity of red radish genotypes. The findings revealed that the Red Prince genotype attained the utmost plant height of 24.00 cm, an average of 7.50 leaves per plant, a leaf area of 23.11 cm², a canopy cover of 26.76%, a leaf chlorophyll content of 54.60%, a leaf fresh weight of 41.16 g, a leaf dry weight of 8.20 g, a root length measuring 9.73 cm, a root diameter of 3.19 mm, a root fresh weight of 27.60 g, a root dry weight of 6.75 g, and a remarkable total yield of 17.93 tons per hectare. The implications of this study are poised to benefit farmers within the Dera Ismail Khan Region, specifically in the plain areas of Pakistan, by promoting the cultivation of the Red Prince variety.

The goal of this work was to create and assess machine-learning models for estimating the risk of budget overruns in developed projects. Finding the best model for risk forecasting required evaluating the performance of several models. Using a dataset of 177 projects took into account variables like environmental risks employee skill level safety incidents and project complexity. In our experiments, we analyzed the application of different machine learning models to analyze the risk for the management decision policies of developed organizations. The performance of the chosen model Neural Network (MLP) was improved after applying the tuning process which increased the Test R² from −0.37686 before tuning to 0.195637 after tuning. The Support Vector Machine (SVM), Ridge Regression, Lasso Regression, and Random Forest (Tuned) models did not improve, as seen when Test R² is compared to the experiments. No changes in Test R²’s were observed on GBM and XGBoost, which retained same Test R² across different tuning attempts. Stacking Regressor was used only during the hyperparameter tuning phase and brought a Test R² of 0. 022219.Decision Tree was again the worst model among all throughout the experiments, with no signs of improvement in its Test R²; it was −1.4669 for Decision Tree in all experiments arranged on the basis of Gender. These results indicate that although, models such as the Neural Network (MLP) sees improvements due to hyperparameter tuning, there are minimal improvements for most models. This works does highlight some of the weaknesses in specific types of models, as well as identifies areas where additional work can be expected to deliver incremental benefits to the structured applied process of risk assessment in organizational policies.