This paper explores the integration of Large Language Models (LLMs) and Software-Defined Resources (SDR) as innovative tools for enhancing cloud computing education in university curricula. The study emphasizes the importance of practical knowledge in cloud technologies such as Infrastructure as a Service (IaaS), Platform as a Service (PaaS), Software as a Service (SaaS), DevOps, and cloud-native environments. It introduces Lean principles to optimize the teaching framework, promoting efficiency and effectiveness in learning. By examining a comprehensive educational reform project, the research demonstrates that incorporating SDR and LLMs can significantly enhance student engagement and learning outcomes, while also providing essential hands-on skills required in today’s dynamic cloud computing landscape. A key innovation of this study is the development and application of the Entropy-Based Diversity Efficiency Analysis (EDEA) framework, a novel method to measure and optimize the diversity and efficiency of educational content. The EDEA analysis yielded surprising results, showing that applying SDR (i.e., using cloud technologies) and LLMs can each improve a course’s Diversity Efficiency Index (DEI) by approximately one-fifth. The integrated approach presented in this paper provides a structured tool for continuous improvement in education and demonstrates the potential for modernizing educational strategies to better align with the evolving needs of the cloud computing industry.

This study develops an optimisation model to facilitate inter-facility medicine sharing in response to anticipated medicine shortages. These facilities include hospitals and medical representatives. We adopt the concept of collective response proposed in our study literature. The optimisation model is developed according to the real-world practices of inter-facility medicine sharing. We utilise case studies of particular healthcare networks to demonstrate the efficacy of the developed model. The efficacy encompasses the model’s application to real-world case studies, as well as its validity and reliability within a specific system. The results show that the developed model is able to determine which facilities should share the requested amount of medicines; and to reduce total lead times by at least one day compared to the ones obtained in the current practice. The model can be used as a decision-support tool for healthcare practitioners when responding to shortages. The study presents the managerial implications of medicine sharing at the network level and supports the development of collaboration amongst facilities in response to medicine shortages.

A serious problem in the workplace is incivility, which impacts especially vulnerable groups like single mothers who hold jobs and experience subtle unfair or damaging treatment. As the number of single working mothers continues to rise in today’s workforce, this study aims to clarify third-party perceptions about incivility against them at work and subsequent influences on individuals as well as the organization. Because the analysis is embedded in theories of social role expectations and organizational justice, it explores third-party observers’ perceptions (such as coworkers or supervisors) of whether incivility directed at single working mothers differs from that experienced by their comparison group—professionally equivalent peers who do not share equal caregiver responsibilities. The researchers employed a mixed-methods approach, incorporating both quantitative surveys and in-depth qualitative interviews to collect rich data from participants who represented several fields. They report their results that third-party observers are less likely to experience vicarious justification of incivility against single working mothers but may be equally unlikely or even more reluctant than in the case of other employees and furthermore find this data account for these differences. The results illustrate the intricate interplay of gender, family structure and work dynamics on workplace outcomes—all leading to lower job satisfaction rates, a high level of stress or even stagnation in career progression for single working mothers. Our findings also extend the workplace incivility literature by demonstrating ways in which single working mothers are particularly vulnerable to this form of mistreatment and a broader need for organizational policies that cultivate an inclusive, supportive environment. Implications for human resource management, organizational culture and policy based on these findings are discussed as it may provide some recommendations for handling incivility in the workplace environment.

Background: In healthcare, research is essential for improving disease diagnosis and treatment, patient outcomes, and resource management, while fostering evidence-based practice. However, conducting research in this sector can be challenging, and healthcare workers may face various obstacles while engaging in research activities. Therefore, understanding healthcare workers’ attitudes toward research participation is essential for overcoming barriers and increasing research engagement. In this study, these aspects are examined through the analysis of survey data from a tertiary healthcare institution in Saudi Arabia. Method: Data obtained via a survey conducted between April and November 2022 among the healthcare workers and employees at a tertiary care hospital in Saudi Arabia were analyzed using descriptive and bivariate statistics. Results: The study sample comprised 713 respondents, 61.71% of whom were female, 58.06% were 26–41 years old, and 72.93% had not undertaken any research as employees or affiliates. A significant association was noted between age group and time constraints (p = 0.004) and lack of opportunity for research (p = 0.00), which were among the identified barriers to research participation. A significant association was also found between gender and barriers to pursuing research (p = 0.012). When the 193 (27.07%) participants who conducted research were asked about the challenges they encountered during this process, gender was significantly associated with difficulties in allocating time for conducting research (p = 0.042) and challenges in accessing journals and references (p = 0.016). Conclusion: The study findings highlight the importance of addressing the barriers and challenges in promoting positive attitudes toward research participation among healthcare workers considering their gender and age. In this manner, healthcare institutions can adopt an environment conducive for professional research engagement.

The purpose of this study is to address the issue of low local participation in ecotourism management in Indonesia, specifically at the Malela Waterfall ecotourism site in Cicadas Village, Rongga District, West Bandung Regency, West Java, Indonesia. The research method is action research, which includes observation data gathering, in-depth interviews, and Focus Group Discussions. The findings of the study show that by carrying out the process of developing social infrastructure, namely development that prioritizes strengthening human resources in carrying out social service functions in ecotourism activities such as skill training of residents in the field of ecotourism, massive ecotourism outreach, and strengthening social communities—Non-Governmental Organizations (NGOs) and youth organizations as ecotourism actors. This type of development serves to raise awareness and participation among local inhabitants in Malela Waterfall ecotourism in West Bandung Regency. This promotes harmony and mutually beneficial partnerships among all Malela Waterfall ecotourism stakeholders. Furthermore, increasing community participation benefits the well-being of residents in the tourist region.

The idea of emotions that is concealed in human language gives rise to metaphor. It is challenging to compute and develop a framework for emotions in people because of its detachment and diversity. Nonetheless, machine translation heavily relies on the modeling and computation of emotions. When emotion metaphors are calculated into machine translation, the language is significantly more colorful and satisfies translating criteria such as truthfulness, creativity and beauty. Emotional metaphor computation often uses artificial intelligence (AI) and the detection of patterns and it needs massive, superior samples in the emotion metaphor collection. To facilitate data-driven emotion metaphor processing through machine translation, the study constructs a bi-lingual database in both Chinese and English that contains extensive emotion metaphors. The fundamental steps involved in generating the emotion metaphor collection are demonstrated, comprising the basis of theory, design concepts, acquiring data, annotating information and index management. This study examines how well the emotion metaphor corpus functions in machine translation by proposing and testing a novel earthworm swarm-tunsed recurrent network (ES-RN) architecture in a Python tool. Additionally, the comparison study is carried out using machine translation datasets that already exist. The findings of this study demonstrated that emotion metaphors might be expressed in machine translation using the emotion metaphor database developed in this research.

The article presents a study of the connectivity and integration of sovereign bond and stock markets in 10 BRICS+ countries in the context of crisis instabilities in 2019−2024. Financial markets are becoming more integrated, and an increasing share of public investments are carried out across borders, which increases not only the opportunities for participants, but also the risks of a new crisis. The work used data on central bank rates of the considered countries, yield indices of 10-year government bonds, gold and Brent oil prices. The methods include the analysis of exchange rate dynamics, connectivity estimates based on the multivariate concordance coefficient and two-factor Friedman rank variance analysis, VAR models, Granger predictability and cointegration. The objective of this study is to analyze the interrelationship and cointegration between the sovereign bond and equity markets of selected BRICS+ countries during crisis periods. Our findings indicate that market interrelationship intensifies during crises, which in turn amplifies volatility. Additionally, we observed that none of the economies within the BRICS+ group can be classified as fully integrated or entirely isolated markets. The disruption of the interrelationship in the sovereign bond markets of the group is primarily reflected in the inconsistency of dynamic changes between Russia, China, and India. During the global shock of 2019–2020, the crisis spread from China, followed by Indonesia, and later to the other countries of the group. The financial and debt markets of the sampled countries were able to quickly cope with the severe shocks of the COVID-2019 period. The 2022–2024 crisis, which lasted significantly longer, began in Russia before spreading to countries across Asia and Africa. By 2024, Russia’s sovereign bond yields showed a marked decline. The increased market volatility following 2022 disrupted the integration and interrelationship of the stock and debt markets within the BRICS+ countries.

This study evaluates the effectiveness of measures aimed at reducing traffic violations, specifically focusing on wrong-way driving, at intersections in Loja, Ecuador. The high incidence of accidents at these intersections, often resulting from wrong-way driving and non-compliance with traffic regulations, underscores the critical need for effective strategies to enhance road safety. To address this issue, we adopted a multidisciplinary approach to assess the impact of two specific interventions: the implementation of official warnings and the presence of traffic officers at a selected intersection. Data collection involved recording instances of traffic violations, administering road safety surveys, and monitoring the implementation of these interventions. The post-implementation analysis sought to determine the effect of these measures on driver behavior and overall traffic safety. Our findings indicate that while the interventions succeeded in increasing awareness about traffic violations, they did not produce a significant reduction in undesirable driving behaviors. This suggests that, although the presence of warnings and traffic officers is beneficial in raising awareness, these measures alone may not be sufficient to effect substantial behavioral changes. The research provides valuable insights for the development of more comprehensive road safety strategies and emphasizes the need for further studies to explore and address the underlying causes of traffic violations.