This study aimed to examine the impact of digital leadership among school principals and evaluate the mediating effect of Professional Learning Communities (PLCs) on enhancing teachers’ innovation skills for sustainable technology integration, both in traditional classroom settings and e-learning environments. Employing a quantitative approach with a regression design model, Structural Equation Modelling (SEM) and Partial Least Squares (PLS-SEM) were utilized in this research. A total of 257 teachers from 7 excellent senior high schools in Makassar city participated in the study, responding to the questionnaires administered. The study findings indicate that while principal digital leadership does not directly influence teachers’ innovation skills in technology integration, it directly impacts Professional Learning Communities (PLCs). Moreover, PLCs themselves have a significant influence on teachers’ innovation skills in technology integration. The structural model presented in this study illustrates a noteworthy impact of principal digital leadership on teachers’ innovation skills for technology integration through Professional Learning Communities (PLCs), with a coefficient value of 47.4%. Principal digital leadership is crucial in enhancing teachers’ innovation skills for sustainable technology integration, primarily by leveraging Professional Learning Communities (PLCs). As a result, principals must prioritize the creation of supportive learning environments and implement programs to foster teachers’ proficiency for sustainable technology integration. Additionally, teachers are encouraged to concentrate on communication, collaboration, and relationship-building with colleagues to exchange insights, address challenges, and devise solutions for integrating technology, thereby contributing to sustained school improvement efforts. Finally, this research provides insights for school leaders, policymakers, and educators, emphasizing the need to leverage PLCs to enhance teaching practices and student outcomes, particularly in sustainable technology integration.

Introduction: 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 primary objectives of the Semmelweis Plan include the optimisation and transformation of the health care system, starting with the integration of hospitals and the state control of previously municipally owned hospitals. The transformation of the health care system can have an impact on health services and thus on meeting the needs of the population. In addition to reducing health inequalities and costs, the relevant benefits include improving patients’ chances of recovery and increasing patient safety. The speciality under study is decubitus care. Our hypothesis is that integration will improve the chances of recovery for decubitus patients through access to smart dressings to promote patient safety. Objective: to investigate and demonstrate the effectiveness of integration in improving the chances of recovery for decubitus ulcer patients. Material and methods: The research compared two time periods in the municipality of Kalocsa, Bács-Kiskun County, Southern Hungary. We collected the number of decubitus patients arriving and leaving the hospital from the nursing records and compared the pre-integration period when decubitus patients were provided with conventional dressings (01.01.2006–2012.12.31) and the post-integration period, which entailed the introduction of smart dressings in decubitus care (01.01.2013–2012.12.31). The target population of the study was men and women aged 0–99 years who had developed some degree of decubitus. The sample size of the study was 4456. Independent samples t-test, Chow test and linear trend statistics were used to evaluate the results. Based on the empirical evidence, a SWOT analysis was conducted to further examine the effectiveness of integration. Results: The independent samples t-test model used was significant (for Phase I: t (166) = −16.872, p < 0.001; for Phase II: t (166) = −19.928, p < 0.001; for Phase III: t (166) = −19.928, p < 0.001; for Phase III: t (166) = −16.872, p < 0.001). For stage III: t (166) = −10.078, p < 0.001; for stage IV: t (166) = −10.078, p < 0.001; for stage III: t (166) = −10.078, p < 0.001). for stage III: t (166) = −14.066, p < 0.001). For the Chow test, the p-values were highly significant, indicating a structural break. Although the explanatory power of the regression models was variable (R-squared values ranged from 0.007 to 0.617), they generally supported the change in patient dynamics after integration. Both statistical analyses and SWOT analysis supported our hypothesis and showed that integration through access to smart dressings improves patients’ chances of recovery. Conclusions: Although only one segment of the evidence on the effectiveness of hospital integration was examined in this study, integration in the study area had a positive impact on the effective care of patients with decubitus ulcers, reduced inequalities in care and supported patient safety. In the context of the results obtained, these trends may reflect different systemic changes in patient management strategies in addition to efficient allocation of resources and quality of care.

 Entrepreneurial intentions, considered to be the best predictor of entrepreneurial behaviour, have attracted extensive attention among academics, practitioners, and policymakers. This study examines the mediating role of the theory of planned behaviour between university students’ proactive personality, entrepreneurship education, entrepreneurial opportunities, and entrepreneurial intentions. The results of this study showed that both attitudes toward entrepreneurship and perceived behavioural control mediated these relationships, except that perceived behavioural control did not mediate the effect of entrepreneurship education on entrepreneurial intentions, and subject norm did not mediate any relationship. Lastly, this study guides universities, policymakers and practitioners to fully focus on developing attitude entrepreneurship and perceived behaviour control through education and training among graduates and employees. Suppose there is a presence of good entrepreneurial opportunities. In that case, they will form stronger intentions to start new businesses and expand their businesses to drive socio-economic growth, innovation and job creation among graduates.

This paper presents a coupling of the Monte Carlo method with computational fluid dynamics (CFD) to analyze the flow channel design of an irradiated target through numerical simulations. A novel series flow channel configuration is proposed, which effectively facilitates the removal of heat generated by high-power irradiation from the target without necessitating an increase in the cooling water flow rate. The research assesses the performance of both parallel and serial cooling channels within the target, revealing that, when subjected to equivalent cooling water flow rates, the maximum temperature observed in the target employing the serial channel configuration is lower. This reduction in temperature is ascribed to the accelerated flow of cooling water within the serial channel, which subsequently elevates both the Reynolds number and the Nusselt number, leading to enhanced heat transfer efficiency. Furthermore, the maximum temperature is observed to occur further downstream, thereby circumventing areas of peak heat generation. This phenomenon arises because the cooling water traverses the target plates with the highest internal heat generation at a lower temperature when the flow channels are arranged in series, optimizing the cooling effect on these targets. However, it is crucial to note that the pressure loss associated with the serial structure is two orders of magnitude greater than that of the parallel structure, necessitating increased pump power and imposing stricter requirements on the target container and cooling water pipeline. These findings can serve as a reference for the design of the cooling channels in the target station system, particularly in light of the anticipated increase in beam power during the second phase of the China Spallation Neutron Source (CSNS Ⅱ).

This study, based on the Theory of Planned Behavior (TPB), aims to explore the entrepreneurial intentions of university students in Shandong Province, China, and analyze the major factors influencing these intentions. Structural Equation Modeling was applied to data collected from 680 students across five universities in Shandong Province. The findings reveal that attitudes, subjective norms, and perceived behavioral control significantly influence the students’ entrepreneurial intentions. Specifically, a positive attitude towards the outcomes of entrepreneurship emerged as the strongest factor influencing their intentions, indicating that positive perceptions and expectations of entrepreneurship significantly enhance students’ entrepreneurial inclinations. Perceived behavioral control also showed a strong influence, suggesting that enhancing students’ self-efficacy and awareness of accessible resources is crucial for fostering entrepreneurial intentions. However, the influence of subjective norms was weaker, which may relate to specific cultural and social environmental factors. This study not only provides an empirical basis for entrepreneurship education and policy-making in Shandong Province and beyond but also offers new insights into the application of TPB in the field of entrepreneurship research.

This study provides empirical data on the impact of generative AI in education, with special emphasis on sustainable development goals (SDGs). By conducting a thorough analysis of the relationship between generative AI technologies and educational outcomes, this research fills a critical gap in the literature. The insights offered are valuable for policymakers seeking to leverage new educational technologies to support sustainable development. Using Smart-PLS4, five hypotheses derived from the research questions were tested based on data collected from an E-Questionnaire distributed to academic faculty members and education managers. Of the 311 valid responses, the measurement model assessment confirmed the validity and reliability of the data, while the structural model assessment validated the hypotheses. The study’s findings reveal that New Approaches to Learning Outcome Assessment (NALOA) significantly contribute to achieving SDGs, with a path coefficient of 0.477 (p < 0.001). Similarly, the Use of Generative AI Technologies (UGAIT) has a notable positive impact on SDGs, with a value of 0.221 (p < 0.001). A Paradigm Shift in Education and Educational Process Organization (PSEPQ) also demonstrates a significant, though smaller, effect on SDGs with a coefficient of 0.142 (p = 0.008). However, the Opportunities and Risks of Generative AI in Education (ORGIE) study did not find statistically significant evidence of an impact on SDGs (p = 0.390). These findings highlight the potential opportunities and challenges of using generative AI technologies in education and underscore their key role in advancing sustainable development goals. The study also offers a strategic roadmap for educational institutions, particularly in Oman to harness AI technology in support of sustainable development objectives.