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.

This study conducted a systematic literature review on current and emerging trends in the use of artificial intelligence (AI) for community surveillance, using the PRISMA methodology and the paifal.ai tool for the selection and analysis of relevant sources. Five main thematic areas were identified: AI technologies, specific applications, societal impact, regulations and public policy. Our findings revealed exponential growth in the development and implementation of AI technologies, with applications ranging from public safety to environmental monitoring. However, this advancement poses significant challenges related to privacy, ethics and governance, driving a debate on the need for appropriate regulations. The analysis also highlighted the disparity in the adoption of these technologies among different communities, suggesting a need for inclusive policies to ensure equitable benefits. This study contributes to the understanding of the current scenario of AI in community policing, providing a solid foundation for future research and developments in the field.

Leukemia is a major public health problem in China, but epidemiological studies on leukemia in China are still insufficient. This study aims to analyze leukemia's disease burden and risk factors in China from 2010 to 2021 and provide a basis for leukemia prevention and treatment. Using data from the Global Burden of Disease (GBD) database, trends in the burden of leukemia in China from 2010 to 2021 were analyzed. Additionally, epidemiological differences by gender and age groups were explored. In 2021, there were 531,000 leukemia patients in China, with 106,000 new cases and 59,000 deaths. Compared to 2010, the mortality rate and disability-adjusted life years (DALYs) per 100,000 population in 2021 decreased by 5% and 18%, respectively, while the incidence and prevalence rates increased by 12% and 29%, respectively. Gender and age stratification indicated that males had higher rates across all indicators than females, and elderly individuals faced higher leukemia mortality and DALYs. The most significant decrease in DALYs was observed in children and adolescents under 20. The highest burden of leukemia for males was found in the 85–90 age group, while for females, it was in the 70–74 age group. Major risk factors for leukemia included smoking, high BMI, and exposure to carcinogens, benzene, and formaldehyde. The overall burden of leukemia in China showed a decreasing trend, with significant gender and age differences. More measures are needed to reduce leukemia mortality, particularly focusing on the prevention and treatment of leukemia in males and the elderly.

The need for forest products, agricultural expansion, and dependency on biomass for the household energy source has largely influenced Ethiopia’s forest resources. Consequently, the country lost its forest resources to less than 6% until the millennium. In this study, quantitative and qualitative historical data analysis was employed to understand the socioeconomic benefits of large dam construction to Ethiopia and downstream countries. Moreover, remotely sensed data was also used to analyze the trends of vegetation cover change in the Nile catchment since the commencement of the dam; focusing on areas where there are high settlement and urban areas. It was identified that Ethiopia has one of the lowest electricity consumption per capita in Africa; about 91% of the source of household energy supply depends on fuelwood today and more than 55.7% of the population does not have access to electricity. The normalized difference vegetation index result shows an increment of vegetation area in the Nile catchment and a reduction of no vegetation area from 2011–2021 by 37.1%; which is directly related to the protection of the dam catchment for its sustainability in the last decade. The hydroelectric dam construction has prospects of multi-benefit to Ethiopia and downstream countries either through the direct benefit of hydropower energy production, related socioeconomic values, and reducing risks of destructive flood from Ethiopian highlands. Generally, it explains the reason why to not say ‘No’ to the reservoir as it is an ever more vital tool for fulfilling growing energy demand and supporting ecological stability.

The article is dedicated to analyzing trends in the development of startup infrastructure in Ukraine, Latvia and Georgia. The article is based on concrete data, a comprehensive analysis of statistical and qualitative data on the development of startups in Ukraine, Latvia and Georgia. This provides a reliable basis for the arguments and conclusions. General patterns of startup infrastructure development in the three countries were identified. A PEST analysis of startup infrastructure development in Ukraine, Latvia and Georgia was conducted. Thus, the authors conduct a multidisciplinary analysis that includes not only economic, but also social and technological aspects of startup ecosystems and infrastructures. Suggestions for improving the startup infrastructure in these countries were developed.

The widespread adoption of digital technologies in tourism has transformed the data privacy landscape, necessitating stronger safeguards. This study examines the evolving research environment of digital privacy in tourism management, focusing on publication trends, collaborative networks, and social contract theory. A mixed-methods approach was employed, combining bibliometric analysis, social contract theory, and qualitative content analysis. Data from 2004 to 2023 were analyzed using network visualization tools to identify key researchers and trends. The study highlights a significant increase in academic attention after 2015, reflecting the industry's growing recognition of digital privacy as crucial. Social contract theory provided a framework emphasizing transparency, consent, and accountability. The study also examined high-impact articles and the role of publishers like Elsevier and Wiley. The findings offer practical insights for policymakers, industry leaders, and researchers, advocating for ongoing collaboration to address privacy challenges in tourism.