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.

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.

Personal information is a vital productive commodity in the digital economy, and its processing has seen unparalleled transformations in both breadth and depth. This article proposes to enhance the legal remedies for personal information rights in contemporary China. Research has revealed multiple practical challenges in China’s judicial practices, such as hesitance to prosecute owing to an absence of substantial legal foundation, improper distribution of the burden of proof, and inadequate integration of criminal-civil judicial safeguards for personal information. This paper advocates for China to elucidate the definition of personal information rights via legislation, enable the litigation of personal information infringement cases, and establish explicit criteria for their acceptance into judicial proceedings. Furthermore, China must develop an appropriate structure for distributing the burden of evidence. It must also use discretionary judgment to properly tackle the problems related to evaluating damages in instances of personal information violations.

The digital era has ushered in significant advancements in Generative Artificial Intelligence (GAI), particularly through Generative Models and Large Language Models (LLMs) like ChatGPT, revolutionizing educational paradigms. This research, set against the backdrop of Society 5.0 and aimed at sustainable educational practices, utilizes qualitative analysis to explore the impact of Generative AI in various learning environments. It highlights the potential of LLMs to offer personalized learning experiences, democratize education, and enhance global educational outcomes. The study finds that Generative AI revitalizes learning methodologies and supports educational systems’ sustainability by catering to diverse learning needs and breaking down access barriers. In conclusion, the paper discusses the future educational strategies influenced by Generative AI, emphasizing the need for alignment with Society 5.0’s principles to foster adaptable and sustainable educational inclusion.