This study determines the efficiency and productivity of Mexico’s urban and rural municipalities in generating economic welfare between 1990 and 2020. It establishes the incidence of context and space on efficiency, using Data Envelopment Analysis, the Malmquist-Luenberger Metafrontier Productivity Index, and Nonparametric Regression. The results indicate that 4 of the 2456 municipalities analyzed were efficient, that productivity increased, and that context and space influenced efficiency. This highlights the need for policies that optimize resource utilization, enhance investment in education, stimulate local business development, encourage inter-municipal cooperation, reduce rural-urban disparities, and promote sustainability.

Introduction: With the adoption of the rural rehabilitation strategy in recent years, China’s rural tourist industry has entered a golden age of growth. Due to the lack of management and decision-support systems, many rural tourist attractions in China experience a “tourist overload” problem during minor holidays or Golden Week, an extended vacation of seven or more consecutive days in mainland China formed by transferring holidays during a specific holiday period. This poses a severe challenge to tourist attractions and relevant management departments. Objective: This study aims to summarize the elements influencing passenger flow by examining the features of rural tourist attractions outside China’s largest cities. Additionally, the study will investigate the variations in the flow of tourists. Method: Grey Model (1,1) is a first-order, single-variable differential equation model used for forecasting trends in data with exponential growth or decline, particularly when dealing with small and incomplete datasets. Four prediction algorithms—the conventional GM(1,1) model, residual time series GM(1,1) model, single-element input BP neural network model, and multi-element input BP network model—were used to anticipate and assess the passenger flow of scenic sites. Result: The multi-input BP neural network model and residual time series GM(1,1) model have significantly higher prediction accuracy than the conventional GM(1,1) model and unit-input BP neural network model. A multi-input BP neural network model and the residual time series GM(1,1) model were used in tandem to develop a short-term passenger flow warning model for rural tourism in China’s outskirts. Conclusion: This model can guide tourists to staggered trips and alleviate the problem of uneven allocation of tourism resources.

This journal article aims to analyze the relationship between school culture and effective headteacher educational leadership, and how this relationship affects school performance and student learning outcomes. We will explore this important issue in depth and provide institutions and principals with practical advice on how to understand and use school culture to enhance the educational leadership of principals.

With the accelerated pace of society and increasingly fierce competition across various fields, people’s daily stress continues to increase, and anxiety disorders have gradually become a prominent issue in the field of public mental health. Using the psychology work When Panic Attacks: The New, Drug-Free Anxiety Therapy That Can Change Your Life as an example, this paper explores the application of Relevance Theory in the translation of psychotherapy popular science texts. It summarizes the textual features and translation principles of psychotherapy popular science texts, and analyzes the methods and strategies to achieve optimal relevance between the source text and target text on the lexical and syntactic levels, aiming to provide references for future popular science translation practices.

This study aims to guide future research by examining trends and structures in scholarly publications about digital transformation in healthcare. We analyzed English-language, open-access journal articles related to this topic from the Scopus database, irrespective of publication year. Using tools like Microsoft Excel, VOSviewer, and Scopus Analyzer, we found a growing research interest in this area. The most influential article, despite being recent, has been cited 836 times, indicating its impact. Notably, both Western and Eastern countries contribute significantly to this field, with research spanning multiple disciplines, including computer science, medicine, engineering, business, social sciences, and health professions. Our findings can help policymakers allocate resources to impactful research areas, prioritize multidisciplinary collaboration, and promote international partnerships. They also offer insights for technology investment, implementation, and policy decisions. However, this study has limitations. It relied solely on Scopus data and didn’t consider factors like author affiliations. Future research should explore specific collaboration types and the ethical, social, policy, and governance implications of digital transformation in healthcare.

In recent years, enological tourism, also known as wine tourism, has emerged as a globally popular tourism product. The role of wine tourism in Slovakia is similarly significant, given the country’s favourable conditions for the development of wine tourism products. The objective of this study is to analyze the current demand for wine-themed experiences among tourists in the Nitra region. This paper presents a characterization of wine tourism based on an analysis of secondary sources. Following the processing of the initial findings from a demand-oriented questionnaire survey, the authors endeavor to delineate the profile of the wine tourism visitor by examining the demand for wine tourism from the vantage point of domestic consumers. It is the authors’ contention that an understanding of the profile of the wine tourism visitor is beneficial in optimising the provision of wine tourism products and stimulating the development of tourism infrastructure.