The author puts forward the idea that decentralized finance doesn’t act without managerial influence. The management moves from the external circuit to the internal one, there occurs self-ruling and “self-regulation” of the financial system. This indicates the appearance of a new type of financial intermediation—a cyber-social one. The potential of using decentralized finance in post-Soviet countries are formulated the following: freeing up the time of transaction participants due to the autonomy of transactions; a superior degree of information security compared to traditional forms of financial intermediation; financial intermediation cost saving, freeing up human resources; reduction in the speed of transactions; increasing accuracy in contractual relations due to the elimination of the human factor influence; stimulating the development of new business areas expands the competitive environment; information safety due to the constant creation of a large number of backup copies. At the same time, the author identified and substantiated the risks associated with decentralized financial flows, which may have an impact on the well-being of the population of post-Soviet countries. The purpose of this study is to determine the prospects for applying decentralized finance as a growth factor in the well-being of the population in post-Soviet countries.

This study employs the Standard Error Estimation technique to investigate the connections between the digitalization of economy, population, trade openness, financial development, and sustainable development across 127 countries from 1990 to 2019. The findings revealed associations between financial development, population growth, trade openness, economic growth, Digitalization development, foreign direct investment (FDI), and sustainable development. Financial development negatively impacts sustainable development, suggesting that countries with advanced financial systems may struggle to maintain sustainability. Trade openness exhibits a negative association with sustainable development, implying that countries with open trade policies may face challenges in maintaining sustainability, possibly due to heightened competition or resource exploitation. These findings highlight the multifaceted relationship between economic factors and sustainable development, underscoring the importance of comprehensive policies and governance mechanisms in fostering sustainability amidst global economic dynamics.

Demographic policy is one of the key tasks of almost any state at the present time. It correlates with the solution of pressing problems in the economic and social spheres, directly depends on the state of healthcare, education, migration policy and other factors and directly affects the socio-economic development of both individual regions and the country as a whole. Many Russian and foreign researchers believe that demographic indicators very accurately reflect the socio-economic and political situation of the state. The relevance of the study is due to the fact that for the progressive socio-economic development of any country, positive demographic dynamics are necessary. The main sign of the negative demographic situation that has developed in modern Russia and a number of countries, primarily European, is the growing scale of depopulation (population extinction). The purpose of this work was to analyze the existing demographic policy of Russia and compare demographic trends in Russia and other countries. The work uses methods of statistical data analysis, comparison of statistical indicators of fertility, mortality, natural population decline, migration, marriage rates in Russia and the Republic of Srpska, methods of retrospective analysis, research of the institutional environment created by the action of state and national programs “Demography”, “Providing accessible and comfortable housing and public services for citizens of the Russian Federation”, “Strategy of socio-economic development for the period until 2024”, Presidential decrees, etc. Research has shown that despite measures taken to overcome the demographic crisis, Russia’s population continues to decline. According to the Federal State Statistics Service of the Russian Federation (Rosstat), as of 1 January 2023, 146.45 million people lived in Russia. By 1 January 2046, according to a Rosstat forecast published in October 2023 the country’s population will decrease to 138.77 million people. To solve demographic problems in the Russian Federation, a national project “Demography” was developed and approved. The government has allocated more than 3 trillion rubles for its implementation. However, it is not possible to completely overcome the negative trend. The authors proposed a number of economic and ideological measures within the framework of agglomeration, migration, and family support policies that can be used within the framework of socio-economic development strategies and national programs aimed at overcoming the demographic crisis.

Although the problems created by exceeding Earth’s carrying capacity are real, a too-small population also creates problems. The convergence of a nation’s population into small areas (i.e., cities) via processes such as urbanization can accelerate the evolution of a more advanced economy by promoting new divisions of labor and the evolution of new industries. The degree to which population density contributes to this evolution remains unclear. To provide insights into whether an optimal “threshold” population exists, we quantified the relationships between population density and economic development using threshold regression model based on the panel data for 295 Chinese cities from 2007 to 2019. We found that when the population density of the whole city (urban and rural areas combined) exceeded 866 km⁻², the impact of industrial upgrading on the economy decreased; however, when the population density exceeded 15,131 km⁻² in the urban part of the cities, the impact of industrial upgrading increased. Moreover, it appears that different regions in China may have different population density thresholds. Our results provide important insights into urban economic evolution, while also supporting the development of more effective population policies.

Clustering technics, like k-means and its extended version, fuzzy c-means clustering (FCM) are useful tools for identifying typical behaviours based on various attitudes and responses to well-formulated questionnaires, such as among forensic populations. As more or less standard questionnaires for analyzing aggressive attitudes do exist in the literature, the application of these clustering methods seems to be rather straightforward. Especially, fuzzy clustering may lead to new recognitions, as human behaviour and communication are full of uncertainties, which often do not have a probabilistic nature. In this paper, the cluster analysis of a closed forensic (inmate) population will be presented. The goal of this study was by applying fuzzy c-means clustering to facilitate the wider possibilities of analysis of aggressive behaviour which is treated as a heterogeneous construct resulting in two main phenotypes, premeditated and impulsive aggression. Understanding motives of aggression helps reconstruct possible events, sequences of events and scenarios related to a certain crime, and ultimately, to prevent further crimes from happening.