Since the 20th National Congress, with the emphasis on innovation and entrepreneurship on country, innovation and entrepreneurship education has become an important part of talent training in universities. The constructivist learning concept advocates that students' learning should respect their own meaning construction, and social mutual assistance and situational construction to acquire knowledge. Based on the current issue of students' innovation and entrepreneurship, this article takes the constructivist learning perspective as a guide to explore strategies to enhance their innovation and entrepreneurship abilities, and is committed to promoting the improvement of their abilities.

With the economic development and the carbon emissions cluster rise, this study uses CiteSpace, VOSviewer, and R-based Bibliometrix software to visualize and analyze the relevant literature on carbon emissions retrieved from the Web of Science database from 2014 to 2023. Through the analysis of the trend of publication volume, author co-citation analysis, institutional co-citation analysis, country co-citation analysis, literature co-citation analysis, thematic analysis of research, research evolution, and other related contents, it reveals the main academic forces, hot research areas, thematic focus changes and cutting-edge trends of international carbon emission research. The results of the study found that the themes of international carbon emissions research focus on carbon emissions, the drivers of carbon neutrality, and the impacts of climate change. An in-depth study of these aspects can help formulate more effective climate policies and emission reduction strategies to achieve global carbon neutrality and combat climate change.

This study examined the role of cryptocurrencies in tourism and their acceptance across EU regions, with particular attention to the digital transformation precipitated by the COVID-19 pandemic. The analysis focuses on the relationship between cryptocurrency acceptance points and the intensity of tourism, highlighting that the acceptance of cryptocurrencies is significantly correlated with tourism services. The literature review highlighted that Web 3.0, especially blockchain technology and decentralized applications, opens new possibilities in tourism, including secure and transparent transactions, and more personalized travel experiences. The research investigated cryptocurrency acceptance points and the intensity of tourism within the EU. The study illuminates that the acceptance of cryptocurrencies significantly correlates with tourism services. The data and methodology demonstrated the analysis methods for examining the relationship between cryptocurrency acceptance points and tourism intensity, including the use of clustering neural networks and Eurostat data utilization. The results showed a positive correlation between the number of cryptocurrency acceptance points and tourism intensity in the EU, affirming the research hypothesis. According to the regression analysis results, each additional cryptocurrency acceptance point is associated with an increase in tourism intensity. The significance of the research lies in highlighting the growing role of digital payment solutions, especially cryptocurrencies, in tourism, and their potential impacts on the EU economy. The analysis supports that the intertwining of tourism and digital financial technologies opens new opportunities in the sector for both providers and tourists.

Credit policies for clean and renewable energy businesses play a crucial role in supporting carbon neutrality efforts to combat climate change. Clustering the credit capacity of these companies to prioritize lending is essential given the limited capital available. Support Vector Machine (SVM) and Artificial Neural Network (ANN) are two robust machine learning algorithms for addressing complex clustering problems. Additionally, hyperparameter selection within these models is effectively enhanced through the support of a robust heuristic optimization algorithm, Particle Swarm Optimization (PSO). To leverage the strength of these advanced machine learning techniques, this paper aims to develop SVM and ANN models, optimized with the PSO, for the clustering problem of green credit capacity in the renewable energy industry. The results show low Mean Square Error (MSE) values for both models, indicating high clustering accuracy. The credit capabilities of wind energy, clean fuel, and biomass pellet companies are illustrated in quadrant charts, providing stakeholders with a clear view to adjust their credit strategies. This helps ensure the efficient operation of banking green credit policies.

The paper proposes a methodology for the analysis and evaluation of the traffic scheme of Bulgarian cities. The authors combine spatial, network, and socio-economic analyses of cities with transport operators’ financial-economic evaluation, sociological studies of transport habits, and the possibilities of new information technologies for transport modeling (such as geographic information systems). The model proposes several approaches to optimize the municipality’s transport scheme. It results from a new need to improve urban traffic, the quality of transport services, and the integration of urban transport into the regional economy of Stara Zagora municipality. It presents a description, analysis, and outline of the opportunities for developing urban transport connectivity and mobility in Stara Zagora municipality. The research results show a deficit of transport connectivity between the different parts of the city, reflecting on the regional economy’s development and the efficiency of the environment and the population.

The 19th century proved to be one of the most complicated periods in Spanish history for the Spanish Crown, as it faced both internal conflicts—the French War of Independence—and external conflict—the independence of what were its territories in most of America. France did not remain indifferent to this and always had a clear idea of where to draw the boundaries of what “belonged” to it. Thus, amid the wave of independence movements in the Spanish colonies, the French continued to produce rich cartography to establish these boundaries and settle their power over the new nations that were arising after the period of revolutions. The cartography of Rigobert Bonne, the last cartographer of the French king and the Revolution Era, and one of its disciples, Eustache Hérisson, represent the perfect witness to the changes over the borders of the Spanish colonies during the change of the century. This study aims to analyze such cartography, examine the rich toponyms it offers, and examine the changes in the boundaries created over time between both empires. The main cartography we will rely on will be that of Bonne, one of the most important cartographers of the 18th century, and his disciple Hérisson, a geographer engineer, who lived through the onset of the conflicts and always prioritized the French perspective and the interests of their nation.