Objective: Sleep-wake disorders is a common disease in children and adolescents. In recent years, there has been an increasing number of studies on the intervention of exercise therapy in sleep-wake disorders. This study aims to systematically review the development status, research frontiers, research hotspots and development trends of exercise therapy in the through bibliometric methods. Methods: The data comes from the Web of Science Core Collection database. Select all the original data from the establishment of the database to 26 April 2024. Summarize the external characteristics of the literature through Web of Science, Use Excel 2021, Origin 2021, VOS viewers 1.6.20 and Cite Space 6.3.R1 to visually analyze countries/regions, institutions, journals, authors, co-cited references and co-occurrence keywords, use the bibliometric online analysis platform (https://bibliometric.com/) to analyze the changes of keywords and extended keywords over the years. Results: We received a total of 775 publications. The works were sourced from 1429 institutions in 75 countries/regions, published in 113 journals, and written by 4332 authors. The number of publications peaked in 2012, 2018, 2019 and 2021 respectively. In the United States, Harvard University and Children (Basel) have the highest number of publications in this field. The analysis of co-cited references shows that there are three main research frontiers in this field, including 24-hour exercise behavior guidelines for children and adolescents, COVID-19 lockdown and cardiometabolic risk. Screen time, mental health, validity, depression, guidelines, stress, and mediterranean diet are still the current research hotspots in the field, and may become potential research hotspots in the future. Conclusion: The development of research in the field of exercise therapy for children and adolescents with sleep-wake disorders is relatively slow, and there is still a lack of cross-regional scientific research collaborations between countries/regions, institutions and individuals. Our research suggests that it may be a worthwhile research direction to promote the establishment of healthy lifestyle behaviors in the gathering environment of children and adolescents, formulate targeted policies for disease prevention, diagnosis and management, strictly implement preventive measures, improve the level of diagnosis, and dig deep into the precise treatment plan of diseases.

The significance of remittances to the Vietnamese economy necessitates investigating how they affect the value of the Vietnamese currency and other macroeconomic factors. Macroeconomic articles struggle to discover their impact on economic development, but measured remittances by migrant workers have recently soared. There is no academic study that has examined this phenomenon in Vietnam. This study uses wavelet frameworks to analyze the lead-lag nexus between exchange rates, remittances, and economic growth in Vietnam in time-frequency domains from 1995 to 2020. Overall, we find that: (i) remittances enhance economic growth in the short and medium run; (ii) exchange rates boost remittances in the short and medium run; (iii) exchange rates promote GDP in all frequency and time domains. Moreover, the partial wavelet coherence and multiple wavelet coherence frameworks also offered evidence supporting the wavelet coherence approach. More importantly, the outcomes of wavelet-based Granger causality unveil that there is two-way causality between the selected indicators, which means that all the indicators can predict each other at different frequencies. Our empirical results provide meaningful information for market participants and policymakers.

The advent of the era of big data has brought great changes to accounting work, and vocational colleges and universities, as the main place for cultivating application-oriented new business talents, need to change the way of talent training in time in the face of this change. By describing the impact of the era of big data on the demand for new business talents, this paper analyzes the analysis of the training of new business and scientific and technological talents in vocational colleges and universities in the era of big data from the perspectives of talent training target positioning, professional curriculum setting and teacher quality, accurately locates the talent training goals of new business professional groups in vocational colleges, scientifically sets up the curriculum system, and comprehensively improves the teaching staff.

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.

In this Data science research on Education, it analyses the alcohol consumption, parent’s education, study time and other factors may influence on student performance.

This project analyzes the evolution of the manufacturing sector in Portugal from 2009 to 2021, focusing on the variations in the number of active companies across various subcategories, such as food, textiles, and metal product industries. The goal of this analysis is to understand the dynamics of growth and contraction within each sector, providing insights for companies to adjust their market and operational strategies. Key objectives include analyzing the overall evolution in the number of companies, identifying subcategories with notable changes, and providing a comprehensive analysis of observed trends and patterns. The study is based on data from PORDATA 2024, and the research employs temporal trend analysis, linear and quadratic regression, and the Pareto representation to identify patterns of growth and decline. By comparing annual data, the project uncovers periods of growth and decline, allowing for a deeper understanding of the sector’s dynamics. The findings also highlight variations in periods of economic crises and during the Covid-19 pandemic, and recommendations for action are presented to support businesses resilience and continuity. These results are valuable for companies within the manufacturing sectors analyzed and policy makers, guiding strategic decisions to navigate the complexities of the market dynamics and to ensuring long-term organizational sustainable success.