In contemporary English teaching in primary and secondary schools, good use of modern educational technology can greatly improve the efficiency of teachers' teaching and students' learning, especially during the epidemic period, the application of educational technology in teaching has become an indispensable topic. As the guider of students, teachers should have more mature modern education concepts, master various advanced teaching technologies, prevent the use of "formalism" in educational technology, and ensure that network resources can have a positive impact on students' learning efficiency and effect. This paper adopts the methods of field investigation, interview and literature analysis to investigate and study the current situation of the application of modern educational technology in English teaching in Jinhe Middle School in Genhe City, analyze the existing problems, and propose targeted solutions, in order to effectively apply modern educational technology in Jinhe Middle School and improve its English teaching efficiency and effect.

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.

The aim of this study was to analyze scientific production on accounting strategies for the management of sporting events over the last 20 years. The methodology used was mixed, combining the quantitative perspective of bibliometric analysis and the qualitative perspective of the case study, to deepen the analysis of the data set. Using bibliometrics, the number of scientific papers on this topic was quantified. For the study, 853 papers from Scopus and Google Scholar were considered that met the inclusion criteria in terms of relevance and keywords in English (accounting strategies, financial strategies and sporting events). Between 2021 and 2024, scientific production increased significantly (n = 376; 44.1%), with the United States being the largest contributor, with 21.7%. In addition, Plos One was the most important source, with 22 publications. The most cited author was Crawford (333 citations). Most of the publications (81%) were scientific articles, with 37% focused on medicine and 12% focused on social sciences. It is concluded that the literature on accounting strategies for sport event management has been the subject of research, with a wide variety of authors, topics, countries, and resources in general. Thus, financial planning, cost control, proper revenue recognition, tax compliance, all these strategies enable the organization of a sporting event to be profitable, efficient and sustainable. As a result, there is a complete picture of the global influence, perception and importance of research on this topic, which lays the groundwork for future research in this field. The value of the research lies in its ability to provide evidence-based solutions to improve the financial efficiency and sustainability of sporting events.

This research endeavors to assess the legal requirements for the operation of mediation and conciliation centers in the UAE based on Federal Law No. 17 of 2016 and its amendment in 2021 No. 5. It is structured into three main sections: the first establishes and defines these centers, the second defines conciliation procedures and the third considers the preceding. The aim is to identify the legal procedures associated with mediation and conciliation centers within the UAE judicial systems and their function in providing solutions for civil and business litigations with the most efficiency and minor financial investments. It also calls for using other forms of conflict adjudication before adopting the legal approach. The conclusions and recommendations indicate the necessity of further improving the Mediation and Conciliation Centers Law due to the necessity of legislative shifts, which would contribute to the UAE’s leading position in legislation related to centers for mediation and conciliation.

This study applies the multiple streams theory. It will further analyze the internal factors of the confluence of multiple sources, in order to explain why the “Joint Recruitment of Four Universities in Macao” policy has become the agenda of the Macao government. The entrance examination requirements from Macau universities are various. They increase local students’ pressure and consume their energy, thus serving as the source of the Problem Stream. The Policy Stream is represented by the Macau government’s intention to reduce students’ educational burden through establishing a unified assessment system. The Political Stream includes the Macau government’s commitment to improving the Macau education system, such as strengthening the multi-assessment system and the “The Fundamental Law of Non-tertiary Education System”. The convergence of these three sources has opened a policy window for the “Joint Recruitment of Four Universities in Macao” system, leading to a new student evaluation system. This policy not only addresses Macau’s social challenges and improves education governance while also highlighting the city’s educational diversity endeavors. Additionally, the strategies for implementing the “Four-University Joint Examination” policy include reducing the number of exams for students, implementing multi-education and multi-enrollment in higher education institutions, analyzing and improving the examination system based on educational big data, and understanding the basic elements and integration paths of big data in higher education. The Macau government can adjust major settings and enrollment quota allocation in the future, draw in more students from the Community of Portuguese-Speaking Countries and the “Belt and Road” regions, and integrate the joint admission method into the Greater Bay Area education cooperation in order to meet the needs of the growing Macao education industry.