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.

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.

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.