The detection of urban expansion through digital processing of satellite images provides valuable information for understanding the dynamics of land use change and its spatial relationship with environmental factors. In order to apply or generate effective land-use planning policies, it is essential to have a historical record of the regional distribution of human settlements, an element that is practically non-existent in our country. For this reason, this text aims to determine the urban growth rate during the period 2000–2014 in the state of Hidalgo, Mexico, and to identify potential expansion zones from Landsat images. Six Landsat scenes were used for the spatial analysis of the state urban coverage and their relationship with the road influence area was evaluated. Two maps were obtained as cartographic products: one of urban coverage distribution and another of the municipalities with the greatest expansion, whose areas are located in the Valle del Mezquital region. However, Mineral de la Reforma, Tetepango, Tizayuca and Pachuca de Soto stand out for their growth rates during the study period: 183.44%, 102%, 94% and 68.5%, respectively. In total, the state urban area in-creased 72.3 km² from 2000 to 2014 with an average growth rate of 1.8% per year. Such growth was associated with the areas of influence of important road infrastructure, such as the Libramiento Arco Norte in Hidalgo. Therefore, the Mezquital Valley and the Mexico Basin are considered as potential regions for urban expansion in the state.

This study applies machine learning methods such as Decision Tree (CART) and Random Forest to classify drought intensity based on meteorological data. The goal of the study was to evaluate the effectiveness of these methods for drought classification and their use in water resource management and agriculture. The methodology involved using two machine learning models that analyzed temperature and humidity indicators, as well as wind speed indicators. The models were trained and tested on real meteorological data to assess their accuracy and identify key factors affecting predictions. Results showed that the Random Forest model achieved the highest accuracy of 94.4% when analyzing temperature and humidity indicators, while the Decision Tree (CART) achieved an accuracy of 93.2%. When analyzing wind speed indicators, the models’ accuracies were 91.3% and 93.0%, respectively. Feature importance revealed that atmospheric pressure, temperature at 2 m, and wind speed are key factors influencing drought intensity. One of the study’s limitations was the insufficient amount of data for high drought levels (classes 4 and 5), indicating the need for further data collection. The innovation of this study lies in the integration of various meteorological parameters to build drought classification models, achieving high prediction accuracy. Unlike previous studies, our approach demonstrates that using a wide range of meteorological data can significantly improve drought classification accuracy. Significant findings include the necessity to expand the dataset and integrate additional climatic parameters to improve models and enhance their reliability.

With the continuous growth of China's social economy, people's demand for spiritual life is increasing. Most of China's land is used to develop real estate and tourist attractions, which involves the protection of some traditional village buildings. Affected by the development of the times and historical factors, it is difficult to carry out the protection and reuse of traditional village buildings. Under the background of rural revitalization, traditional villages have been unable to meet the needs of current social development, and how to transform them into a common concern of rural workers and rural members. Based on this, this paper focuses on the protection and reuse of traditional village buildings, and emphatically analyzes the combination method of active utilization and protection of tradition and the reuse principle of traditional village buildings from the perspective of live transmission.

The Science and Technology Innovation Center holds a pivotal position in the national science and technology innovation system, and a scientific evaluation of the “Sci-tech Innovation Center” will guide its construction direction. This study found the advantages and disadvantages of the four cities through comparison; Hence improvement suggestions were proposed for the weaknesses of the four cities. There are two main paths for the government to drive technology innovation: STI (Science and Technology Innovation) mode and DUI (Doing, Using, Interacting) mode. With the aid of the evaluation index system of the Sci-tech Innovation Center, this article uses fuzzy sets, rough sets and fuzzy dynamic clustering methods to comprehensively evaluate the effects of driving technology innovation in the four cities of Beijing, Shanghai, Shenzhen and Guangzhou. The results found that Shenzhen has a significant effect in DUI, and Beijing has a significant effect in STI. The choice of path is related to the abundance of innovation resources.

Employee Engagement (EE) has become a crucial element for the success of any organization. While psychology has conducted extensive research on EE, accounting has yet to give it the attention it deserves. This systematic literature review (SLR) was conducted to explore the linkage between corporate governance (CG) practices and factors that drive employee engagement (EED) in greater detail. The review identified several key factors influencing EED: board composition, audit committees, top leadership expertise, network power, other stakeholders’ supervision, and above-board application. In particular, the study revealed that effective CG practices have positive EE consequences, such as increased staff morale, job satisfaction, and productivity, and decreased employee turnover rates. The study underlined the importance of an employee-centric culture that encourages empowerment and fosters a sense of belonging in achieving maximum business success. It suggests that companies must create a work environment that promotes EE, provides opportunities for growth and development, recognizes employee contributions, and fosters open communication and collaboration. By leveraging these insights, companies can enhance their business operations and achieve maximum success by fostering a culture of EE and empowerment. The study concludes that businesses prioritizing EE as a core value can create a sustainable competitive advantage, increase their reputation, and attract and retain top talent.