Relational database models offer a pathway for the storage, standardization, and analysis of factors influencing national sports development. While existing research delves into the factors linked with sporting success, there remains an unexplored avenue for the design of databases that seamlessly integrate quantitative analyses of these factors. This study aims to design a relational database to store and analyse quantitative sport development data by employing information technology tools. The database design was carried out in three phases: (i) exploratory study for context analysis, identification, and delimitation of the data scope; (ii) data extraction from primary sources and cataloguing; (iii) database design to allow an integrated analysis of different dimensions and production of quantitative indicators. An entity-relationship diagram and an entity-relationship model were built to organize and store information relating to sports, organizations, people, investments, venues, facilities, materials, events, and sports results, enabling the sharing of data across tables and avoiding redundancies. This strategy demonstrated potential for future knowledge advancement by including the establishment of perpetual data updates through coding and web scraping. This, in turn, empowers the continuous evaluation and vigilance of organizational performance metrics and sports development policies, aligning seamlessly with the journal’s focus on cutting-edge methodologies in the realm of digital technology.

Comparative studies of national values are becoming increasingly important in the context of contemporary globalization processes. An essential condition for the shaping of national values in learners is the enrichment of pedagogical technology with components of digital technology. Both qualitative and quantitative approaches were used in the current study. The purpose of this research is to examine the efficacy of mobile learning in shaping the national values of prospective teachers. The experiment included 180 participants. Diagnostics of the levels of national values formation in the initial stage confirmed the assumption about the low formation of national values among teacher candidates and, consequently, the need for targeted work on their formation. This study demonstrates that significant advances in students’ national values have occurred following the introduction and testing of mobile learning with experimental group (EG) participants to shape national values. The data from this study can serve as the basis for creating strategies for shaping the national values of learners in universities and as a methodological basis for adapting mobile learning for the shaping of national values.

China’s graduate quality management system is designed to ensure that students possess the necessary skills, knowledge, and competencies for future success. This system is rooted in China’s ambitious educational reforms aimed at cultivating a highly skilled workforce to drive economic growth and innovation. Effective graduate quality management significantly impacts employment levels, training models, and national policy formulation. This study investigates the quality management approaches of 56 vocational institutions in Yunnan Province using a 5-level questionnaire and a quantitative research methodology. A sample of 556 individuals was selected through stratified random sampling. Exploratory factor analysis identified five primary components of the quality management model: College graduate quality (mean = 4.56, SD = 0.49), teaching quality (mean = 4.39, SD = 0.42), hardware environment (mean = 4.38, SD = 0.44), social support (mean = 4.37, SD = 0.42), and job satisfaction (mean = 4.38, SD = 0.42). College graduate quality and teaching quality were the most influential factors, while hardware environment, social support, and job satisfaction had lesser impacts.

With the wide application of the Internet and smart systems, data centers (DCs) have become a hot spot of global concern. The energy saving for data centers is at the core of the related works. The thermal performance of a data center directly affects its total energy consumption, as cooling consumption accounts for nearly 50% of total energy consumption. Superior power distribution is a reliable method to improve the thermal performance of DCs. Therefore, analyzing the effects of different power distribution on thermal performance is a challenge for DCs. This paper analyzes the thermal performance numerically and experimentally in DCs with different power distribution. First, it uses Fluent simulate the temperature distribution and flow field distribution in the room, taking the cloud computing room as the research object. Then, it summarizes a formula based on the computing power distribution in a certain range by the numerical and experimental analysis. Finally, it calculates an optimal cooling power by analyzing the cooling power distribution. The results shows that it reduces the maximum temperature difference between the highest temperature of the cabinet from 5-7k to within 1.2k. In addition, the cooling energy consumption is reduced by more than 5%.

Based on Landsat–7ETM + images of 2007 and 2012 and Landsat–8 images of 2018, this study took Fuyang City, Anhui Province (Yingzhou District, Yingdong District, Yingquan District) as the research object, and made a quantitative analysis of land use/cover change in Fuyang City from 2007 to 2018 with the Environment for Visualizing Images (ENVI) software. According to the data of land use types in three phases, the article analyzes the development trend of various land use types and the main reasons for the changes of land use, which provides a certain basis for the urban planning and environmental construction of Fuyang City. The results show that with the rapid economic development and continuous improvement of the urbanization level in Fuyang City during 11 years, the area of various land types in the study area has changed greatly. The area of construction land area changed by 448.27 km², with an increase of 543.57%; the area of arable land changed by 597.52 km², with a decrease of 34.74%; the area of bare land changed by 26.00 km², with a decrease of 80.68%. The changes were closely related to the rapid economic and social development in the study area. Under the influence of environmental protection policies and environmental awareness, the area of forest land changed by 85.00 km², with an increase of 97.58%; the water area changed by 84.35 km², with an increase of 201.39%.

This study evaluates the health and sustainability of higher education systems in nine countries: the USA, UK, Australia, Germany, Canada, China, Brazil, India, and South Africa. Using a multi-level analysis model and principal component analysis (PCA), nine key factors—such as international student numbers, academic levels, and graduate employment rates—were identified, capturing over 90% of the cumulative impact on higher education systems. India, scoring 6.2036 initially, shows significant room for improvement. The study proposes policies to increase graduate employment, promote international faculty collaboration, and enhance India’s educational expenditure, which surpasses 9.8% of GDP. Post-policy simulations suggest India’s score could rise to 8.7432. The paper also addresses the impact of COVID-19 on global education, recommending a hybrid model and increased graduate enrollment in China to reduce unemployment by 5.4%. The research aims to guide sustainable development in higher education globally.