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 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.

Background: Kangyang tourism, a wellness tourism niche in China, integrates health preservation with tourism through natural and cultural resources. Despite a growing interest in Kangyang tourism, the factors driving tourist loyalty in this sector are underexplored. Methods: Using a sample of 413 tourists, this study employed Covariance-Based Structural Equation Modeling (CB-SEM) to examine the influence of destination image, service quality, tourist satisfaction, and affective commitment on tourist loyalty. Results: The findings reveal that destination image and service quality positively affect tourist satisfaction, affective commitment, and loyalty. Tourist satisfaction and affective commitment are identified as critical drivers of tourist loyalty. Notably, affective commitment plays a stronger role in fostering loyalty compared to satisfaction. Conclusion: These results highlight the importance of a positive destination image and high service quality in enhancing tourist loyalty through increased emotional and psychological attachment. The findings inform strategies for stakeholders to improve Kangyang tourism’s growth by focusing on emotionally engaging experiences and service excellence.

The purpose of this study is to investigate different factors associated with remote online home-based learning (thereafter named OHL), including technical system quality, perceived quality of contents, perceived ease of use, and perceived usefulness in relation to the satisfaction of undergraduate students following the post-COVID-19 pandemic in Malaysia. Additionally, the mediating roles of attitude are also investigated. Two hundred questionnaires were distributed using judgmental sampling method and 156 completed responses were collected. The data were subsequently analyzed using PLS-SEM. The findings imply that the OHL system is an effective method although it is challenging to operate. In terms of perceived technical system quality, OHL is currently more gratifying for students; however, some have reported that the quality of the content delivered via the remote system is still unsatisfactory. Moreover, the study found that attitude is a significant determinant of undergraduates’ satisfaction with OHL. This study contributes to the advancement of current knowledge by inspecting the factors of the Undergraduate Level OHL System using the mediating roles of attitude. In terms of underpinning theories, Technology Acceptance Model and Information System Model were employed as the guiding principles of the current study.