The purpose of this paper is to suggest some ways and mechanisms for creating long-term peace based on sustainable development of the world and the purpose of the work is to develop recommendations aimed at counteracting the emergence of dictatorial regimes that were legitimately established. Five common features of such dictators have been identified, namely: coming to power in a legitimate way, using manipulative technologies, openly declaring their aggressive intentions, gradually implementing their aggressive intentions, creating a military potential with the active participation of developed countries, including those with established democracies. The reasons for the creation of dictatorial regimes are substantiated, namely: the imperfection of electoral legislation, excessive conservatism of legislation, insufficient determination and timeliness of countering the strengthening of dictatorships, “national egoism”, the unscrupulousness of dictators in their foreign and domestic policies. It was determined that in order to actively oppose dictatorial regimes, it is necessary to: improve the system of elections to the highest positions and to the legislative bodies of the state, put a strong barrier against manipulative technologies and fakes, through the improvement and effective application of international legislation with the involvement of artificial intelligence, determine the strategy of relations with dictators in all directions in advance: economic, diplomatic, sports, scientific and technical, etc., establish the scope of relations in direct proportion to the index of democracy in a country with an authoritarian regime and, in order to prevent negative consequences on the economy and social condition of the society of one’s country, determine and carefully regulate import and export activities. It is proposed to start an indicator of the effectiveness of the head of state and an internal truth index of the head of state, as well as measures for moral stimulation of heads of state. As a result of the study, two root causes of threats to the existence of humanity were additionally identified, which directly affect the formation of dictatorial regimes. 1) The emergence on the basis of modern information technologies of a powerful system of manipulative technologies, the use of which leads to the power of future dictators. 2) Belated opposition of the democratic world to the formation of dictatorships. This is expressed in condescension to the initial illegal actions of future dictators, uncontrolled cooperation in the economic, political and humanitarian spheres. Two key mechanisms for achieving sustainable development and long-term peace are proposed.

Purpose: This study aims to clarify the meaning of sport analysis, explore the contributions derived from sporting event analysts, and highlights the importance of responsible sport gambling. It also investigates how sustainable practices can be integrated into sports analysis to enhance social well-being. Design/methodology/approach: Secondary text data from government documents, news articles, and website information were extracted by searching keywords such as sports lottery and sports analysis in traditional Chinese, and then analyzed to establish the research framework and scope. Subsequently, 18 interviews were conducted with stakeholders to gain deeper insights. Findings: The content analyses reveals that sport analysis tends to be sport data science. Sporting event analysts may contribute to improving the performance of players or a team, enhancing spectator sports, and increasing sports lottery revenues. In the leisure aspect, the professionalism of sporting event analysts not only increases epistemic and entertainment values in spectator sports but also boosts engagement with sport lotteries. To ensure these enhancements remain beneficial, it is vital to emphasize responsible sport gambling and sustainable practices that protect vulnerable groups and promote long-term health benefits for those involved in sports. The integration of sustainable practices in sport analysis and the expertise of sporting event analysts can significantly advance economic and social development by generating funds through sport lottery industry for athlete programs, sports infrastructure, and educational initiatives, aligning with multiple Sustainable Development Goals. Additionally, the professionalism of these analysts may enhance public understanding and engagement of sports, promoting increased participation in sports, reducing healthcare costs, and contributing to the development of a healthier and more resilient society. Originality: Emphasizing responsible sports gambling is essential to the sustainability of sports lotteries and the role of sporting event analysts.

The purpose of the article is to examine the changes in cross-border cooperation between Vietnam and China as a result of the development and connectivity of cross-border infrastructure between the two countries. This article is based on a mixed-methods study that includes desk research and surveys. The article explains how the two countries’ approaches to border shifted from ‘barrier’ to the border of ‘connectivity’. Accordingly, the article examines the changes in border management cooperation between the two countries, which serves as a vital basis for cross-border development cooperation. Furthermore, the article examines the perceptions of the two countries regarding the development and connectivity of cross-border infrastructure for comprehensive cooperation between the two countries and beyond. At the same time, the article examines how the two countries promote the development and connectivity of cross-border infrastructure, both hard and soft. The article also examined some initial results and some issues facing the two countries. The paper concludes with some findings. In particular, the article concludes that increased border connectivity will encourage cross-border cooperation and integration between the two countries and help to alleviate security concerns. Although the two countries have made efforts to open their borders, in the transition from a border of ‘barriers’ to a border of ‘connectivity’ remain partly to Vietnamese people’s memories of the 1979 Sino-Vietnamese border war, as well as the impact of the two countries’ unresolved South China Sea disputes. However, Vietnam also tries to promote cross-border cooperation within a controllable level.

Water physico-chemical parameters, such as pH and salinity, play an important role in the larval development of Aedes aegypti, the primary vector of dengue fever. although the role of these two factors is known, the interaction between pH and salinity in various aquatic habitats is still not fully understood, especially in the context of endemic areas. this study explored how the interaction between pH and salinity affects the development of Aedes aegypti larvae in dengue hemorrhagic fever (DHF) endemic areas. this study used a pure experimental design with a posttest-only control group approach. Aedes aegypti instar iv larvae were obtained from eggs collected in north kolaka regency, a dhf endemic area. the independent variables tested were pH (6 and 8) and salinity (0.4 gr/L and 0.6 gr/L), with the control group using pH 7 and no salinity. a two-way anova test was used to evaluate the interaction between pH and salinity, followed by tukey’s hsd post-hoc test to compare treatment groups. the results showed that, independently, pH and salinity had no significant effect on larval survival. however, the interaction between the two variables had a significant effect (p < 0.001). the combination of pH 8 and salinity 0.4 gr/L resulted in the highest survival rate, while pH 6 and salinity 0.6 gr/L caused a significant decrease in larval survival. the combination of alkaline pH (pH 8) and low salinity (0.4 gr/L) is the optimal condition for Aedes aegypti larval survival. the results of this study highlight the importance of considering the interaction between pH and salinity in environmental-based vector control strategies in endemic areas. further research is needed to explore other factors, such as aquatic microbiota and environmental variations, that may affect mosquito larval development.

One of the most frequently debated subjects in international forums is economic growth, which is regarded as a global priority. Consequently, researchers have turned their attention from conventional economic growth at a single average coefficient to divisible economic growth at levels of its value. Although the existing literature has discussed several determinants of economic growth, our article contributes to examining the sources of economic growth in African countries during the generations of reforms from 1990 to 2019 and in the context of economic vulnerability. The variables used in the analysis are gross domestic product, trade openness, financial development, and economic vulnerability. The study uses a quantile regression econometric model to examine these variables at different stages of reform. Quantile regression (QR) estimates for quantiles 0.05 to 0.95 showed mixed results: financial development is favorable to African economic growth at all quantile levels. However, economic vulnerability is a major impediment to economic growth at all quantile levels. In addition, it was found that a high degree of trade openness has a detrimental effect on African economic growth from quantile 0.5 of the dependent variable. Finally, another important result proves that financial development is a remedy for decision-makers against economic vulnerability.

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.