This research introduces a novel framework integrating stochastic finite element analysis (FEA) with advanced circular statistical methods to optimize heat pump efficiency under material uncertainties. The proposed methodologies and optimization focus on balancing the mean efficiency and variability by adjusting the concentration parameter of the Von Mises distribution, which models directional variability in thermal conductivity. The study highlights the superiority of the Von Mises distribution in achieving more consistent and efficient thermal performance compared to the uniform distribution. We also conducted a sensitivity analysis of the parameters for further insights. The results show that optimal tuning of the concentration parameter can significantly reduce efficiency variability while maintaining a mean efficiency above the desired threshold. This demonstrates the importance of considering both stochastic effects and directional consistency in thermal systems, providing robust and reliable design strategies.

The study aims to explore the role of artificial intelligence in enhancing the efficiency of public relations practitioners in Jordanian telecommunication companies. This study belongs to the category of descriptive research and adopted a survey methodology. The study surveyed (86) individuals representing the community of public relations practitioners and customer service personnel in the Jordanian telecommunication companies Zain and Orange.The study findings revealed that less experienced public relations personnel in Zain and Orange, with less than five years of experience, exhibit greater acceptance and enthusiasm for using artificial intelligence applications compared to their more experienced counterparts. The study also indicated that most public relations practitioners in Zain and Orange perceive artificial intelligence applications to have a moderate to significant contribution to achieving public relations functions and enhancing their work, reflecting technological advancement and the need to adapt to rapid changes in the business environment. Moreover, the study also discussed the limits, including that artificial intelligence can analyze large amounts of data related to the market and the audience, which provides further research and study.

This study explores the complex dynamics of handling augmented reality (AR) data in higher education in the United Arab Emirates (UAE). Although there is a growing interest in incorporating augmented reality (AR) to improve learning experiences, there are still issues in efficiently managing the data produced by these apps. This study attempts to understand the elements that affect AR data management by examining the relationship between the investigated variables: faculty readiness, technological limits, financial constraint, and student engagement on data management in higher education institutions in the UAE, building on earlier research that has identified these problems. The research analyzes financial constraints, technological infrastructure, and faculty preparation to understand their impact on AR data management. The study collected detailed empirical data on AR data management in UAE higher education environments using a quantitative research methods approach, surveys. The reasons for choosing this research method include cost-effectiveness, flexibility in questionnaire design, anonymity and confidentiality involved in the chosen methods. The results of this study are expected to enhance academic discourse by highlighting the obstacles and remedies to improving the efficiency of AR technology data management at higher education institutions. The findings are expected to enlighten decision-making in higher education institutions on maximizing AR technology’s benefits for improved learning outcomes.

Introduction, purpose of the study: In Central Europe, in Hungary, the state guarantees access to health care and basic health services partly through the Semmelweis Plan adopted in 2011. The Health Plan aims to optimize and transform the health system. The objectives of hospital integration, as set out in the Plan, started with the state ownership of municipal hospitals in 2012, continued with the launch of integration processes in 2012–2013 and culminated today. The transformation of a health system can have an impact on health services and thus on meeting the needs of the population. We aim to study the effectiveness of integration through access to CT diagnostic testing. Our hypothesis is that integration has resulted in increased access to modern diagnostic services. The specialty under study is computed tomography (CT) diagnostic care. Our research shows that the number of people receiving CT diagnostic care has increased significantly because of integration, which has also brought a number of positive benefits, such as reduced health inequalities, reduced travel time, costs and waiting lists. Test material and method: Our quantitative retrospective research was carried out in the hospital of Kalocsa through document analysis. The research material was comparing two time periods in the Kalocsa site of Bács-Kiskun County, Southern Hungary. The number of patients attending CT examinations by area of duty of care according to postal codes was collected: Pre-integration period 2014.01.01–2017.11.30. (Kalocsa did not have CT equipment, so patients who appeared in Kecskemét Hospital but were under the care of Kalocsa), post-integration period 2017.12.01–2019.12.31. (period after the installation of CT in Kalocsa). The target group of the study consisted of women and men together, aged 0–99 years, who appeared for a CT diagnostic examination. The study sample size was 6721 persons. Linear regression statistics were used to evaluate the results. Based on empirical experience, a SWOT analysis was carried out to further investigate the effectiveness of integration. Results: As a result of the integration, the CT scan machine purchased in the Kalocsa District Hospital has enabled an average of 129.7 patients per month to receive CT scans on site without travelling. The model used is significant, explaining 86% of the change in the number of patients served (F = 43.535; p < 0.001, adjusted R² = 0.860). The variable of integration in the model is significant, with an average increase in the number of patients served of 129.7 per month (t = 22.686; p < 0.001) following the introduction of CT due to integration. None of the month variables representing seasonal effects were found to be significant, with no seasonal effect on care. The SWOT analysis has clearly identified the strengths, weaknesses, opportunities and threats related to the integration, the main outcome of which is the acquisition of a CT diagnostic tool. Conclusions: Although we only looked at one segment of the evidence for the effectiveness of hospital integration, integration in the study area has had a positive impact on CT availability, reducing disparities in care.