Sustainable development within music education is essential, particularly in ensuring that popular music can continually and effectively serve educational systems. This research aims to 1) examine pop music chord progression, 2) develop a chord progression book specifically for teaching music students, and 3) evaluate the effectiveness of this educational tool in improving music composition skills. A mixed-methods approach, incorporating both qualitative and quantitative research, was used. Research tools included an interview guide, Ioc forms, a textbook, and a performance assessment form. Interviews were conducted with five experts in pop music composition, while a group of 14 undergraduate music students participated in the experimental study. These methods evaluated how teaching popular music chord composition enhances students’ practical composition abilities. The findings indicate that 1) chord composition in popular music primarily involves five aspects: melody, rhythm, chord structure, music form, and melody development techniques, with melody and chord as the foundational elements; 2) the chord progression textbook for popular music differs from traditional composition theory texts, combining theory and practical application with a focus on chord progression techniques; and 3) instruction in popular music chord composition significantly enhances students’ skills in melody creation, production, and listening, ultimately fostering practical music creation abilities. This study supports the sustainable integration of popular music in both music infrastructure construction and music education system development, offering insights into how such integration can drive long-term advancements in music education.

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.

During his 22-year rule, Turkey’s populist leader Erdoğan not only ensured his control of mainstream media ownership, but he also aligned the language and style of these media with his own populist politics. This investigation presents a unique perspective by highlighting the AKP’s establishment of a network of loyal media outlets and business individuals through crony capitalism while also demonstrating that the party garnered loyalty from religious foundations, and the urban poor due to the aid and financial support provided by AKP municipalities. The primary objective of this research is to offer a distinct scholarly contribution by analyzing the influence of crony capitalism and welfare policies within the context of populist politics. This study employed a methodology centered around network graphs designed to reveal connections between the AKP, various media outlets, and associations and foundations, thereby highlighting the AKP’s association with key actors involved in the establishment of a neoliberal-conservative hegemony.

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.