Prefabricated decoration is an efficient construction mode in the current construction field, with the main purpose of quickly improving the efficiency and quality of decoration through the effective application of modular decoration technology. Therefore, there is a high demand for efficient prefabricated technical talents in various construction units or enterprises in the construction industry. How to cultivate efficient prefabricated technical talents is a problem that relevant professional teachers in universities must pay attention to at present. This paper mainly analyzes the research and practice of the training mode of prefabricated technical talents, summarizes the connotation of prefabricated building and the importance of prefabricated building talent training, analyzes the key points and requirements of prefabricated building teaching, summarizes the problems existing in the training process of prefabricated building talents and puts forward corresponding optimization countermeasures, so as to lay a solid foundation for the optimization of the training mode of prefabricated talents in the next stage and the promotion of talent training level.

Recently, there has been a lot of buzz on social media, particularly in the form of vlogs, about newly launched semi-high speed trains in India popularly known as Vande Bharat Express. However, no information is available about the extent to which people trust the vlogs promoting the trains and the trains themselves. Therefore, this research aims to investigate the impact of watching vlogs about semi-high speed trains on the trust and attitude towards them, and how they perceive the risks associated. This study is guided by the trust transfer theory to investigate how trust transference can lead to a traveler’s intent to use semi-high speed trains. This study involved 338 participants. The relationship between variables was examined using SmartPLS 4 software. The findings indicate that trust in semi-high speed trains can be established through vlogs leading to intention to use. On the theoretical side, it provides insight into how trust, attitude, and perceived risk can affect the adoption of new technology, while on the practical side, it helps to understand how vlog coverage can be used as a tool to increase trust and ultimately drive adoption. Vlog coverage, trust in vlog content, trust in semi-high speed trains and behavioural intention altogether are not well understood in current literature despite the important implication for managers, academicians and consumers alike. This study contributes to the field of transportation and railways, social media and communication, and hospitality and tourism research. The study helps policy makers to understand users’ characteristics regarding the latest social media tools and adopt them accordingly to provide a better governance policy.

Weather and climate services are essential tools that help farmers make informed choices, such as choosing appropriate crop varieties. These services depend considerably on the availability of adequate investments in infrastructure related to weather forecasting, which are often provided by the State in most countries. Zimbabwean farmers generally have limited access to modern weather and climate services. While extensive attempts have been made to investigate farmers’ socioeconomic factors that influence access to and use of weather and climate services, comparative political economy analysis of weather and climate service production and use is limited. To address this knowledge gap, this study examines the production, dissemination, and usage of modern seasonal weather services through a political economy analysis perspective. The findings of this study highlight considerable discrepancies in access and use of seasonal weather forecasts between male and female farmers, those who practise African Traditional Religions versus Christians, and the minority group (Ndau tribe) and the majority group (Manyika tribe). This result suggested the presence of social marginalization. For example, minority Ndau members living in remote areas with limited radio signals and a weak mobile network have limited access to modern seasonal weather forecasts, forcing them to rely much more on indigenous weather forecasts. Further, due to unequal power relations, a greater proportion of male farmers participated in agricultural policy formation processes than their female counterparts. To promote inclusive development and implementation, deliberate efforts need to be made by State authorities to incorporate adherents of African traditional religions, members of minority tribes and female farmers in agricultural policymaking processes, including seasonal weather forecast delivery policies. Further, the study suggests the relaxation or elimination of international sanctions on Zimbabwe by the European Union, United Kingdom and the United States of America, given that they are considerably affecting marginalized groups of farmers in their climate change adaptation practices, including the use of modern weather and climate services. The vast majority of these marginalized farmers never benefitted from the land reform programme and were also not responsible for the design and implementation of this programme which triggered these sanctions.

The purpose of the study is to create proposals and recommendations to improve the system evaluating the quality of governance and efficient use of budget funds in order to improve public welfare and sustainable development. The research methodology included application of statistical methods to review scientific articles, legislative acts and other documents, study models for evaluating the quality of governance and efficient use of budget funds. Mathematical modeling and forecasting methods were also used to assess aspects of governance and predict the results when changes are made, including building a trend model and determining the forecast values of accrued taxes and mandatory payments for 2024–2026. The conclusions highlight there is a positive correlation between the accrued taxes and mandatory payments to the budget of the Republic of Kazakhstan, and an economic growth and changes in tax legislation. The key factors influencing the quality of governance and efficient use of budget funds were identified. Recommendations were developed to improve the quality assessment system and governance of budget funds in order to increase efficiency and responsibility in financial management. The results of the study can be used by public administration bodies and financial institutions to optimize the governance of budget funds.

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 challenge of developing cadastral infrastructure in Africa is inextricably linked to the global issues of sustainable development. Indeed, in light of the constraints inherent to conventional cadastral systems, alternative systems developed through land regulation programmes (LRPs) are compelled to align with the tenets of sustainable development. A discursive study, conducted through a semisystematic literature review, enabled the selection of 53 documents on cadastral systems deployed in multiple countries across the African continent. A number of systems were identified and grouped into four categories: urban, rural, participatory and hybrid cadastral systems. These systems are developed on the basis of standards and sociotechnical approaches, including the LADM, STDM, and FFP, as well as innovative technologies such as blockchain. However, their sustainability is limited by the fact that they are not multipurpose cadastral systems. Consequently, there is an urgent need for studies to develop a global framework that will produce truly significant and sustainable results for all sections of society.