The paper considers an important problem of the successful development of social qualities in an individual using machine learning methods. Social qualities play an important role in forming personal and professional lives, and their development is becoming relevant in modern society. The paper presents an overview of modern research in social psychology and machine learning; besides, it describes the data analysis method to identify factors influencing success in the development of social qualities. By analyzing large amounts of data collected from various sources, the authors of the paper use machine learning algorithms, such as Kohonen maps, decision tree and neural networks, to identify relationships between different variables, including education, environment, personal characteristics, and the development of social skills. Experiments were conducted to analyze the considered datasets, which included the introduction of methods to find dependencies between the input and output parameters. Machine learning introduction to find factors influencing the development of individual social qualities has varying dependence accuracy. The study results could be useful for both practical purposes and further scientific research in social psychology and machine learning. The paper represents an important contribution to understanding the factors that contribute to the successful development of individual social skills and could be useful in the development of programs and interventions in this area. The main objective of the research was to study the functionalities of the machine learning algorithms and various models to predict the students’s success in learning.

This paper provides a disaster resilience-based approach. For the definition of the approach, a three-step method (definition of components, analysis of the resilience pillars and definitions of resilience-based actions) has been followed. To validate the approach, an application scenario for mitigating the COVID-19 pandemic is provided in the paper. The proposed approach contributes to stimulating the co-responsibility quadruple helix of actors in the implementation of actions for disaster management. Moreover, the approach is adaptable and flexible, as it can be used to manage different kinds of disasters, adjusting or changing itself to meet specific needs.

Africa has an extensive and varied cultural history that includes works of art, music, literature, customs, and historical locations. These cultural resources are essential for creating identities, promoting social cohesiveness, and advancing economic development. However, for these institutions to have the greatest impact on the world and contribute to sustainable development, they must be managed and engaged effectively. Exploring the management of cultural institutions in Africa and their potential for global impact and sustainable development is the goal of this research study. The study relies on the extensive review of available literature, case studies, and in-depth interviews with key informants, and data obtained, subjected to content and thematic analyses. It aims to uncover flexible management techniques that can improve the global reach and sustainable development of African cultural institutions by examining successful models and cutting-edge approaches. The results of this study will help those responsible for administering Africa’s cultural institutions to formulate practical guidelines and policy recommendations. Africa can further establish its cultural identity, advance cultural diplomacy, and utilize its cultural capital to propel social and economic advancement by utilizing the potential of these institutions for global impact and sustainable development.

This study provides an evaluation of the environmental impact and economic benefits associated with the disposal of mango waste in Thailand, utilizing the methodologies of life cycle assessment (LCA) and cost-benefit analysis (CBA) in accordance with internationally recognized standards such as ISO 14046 and ISO 14067. The study aimed to assess the environmental impact of mango production in Thailand, with a specific focus on its contribution to global warming. This was achieved through the application of a life cycle assessment methodology, which enabled the determination of the cradle-to-grave environmental impact, including the estimation of the mango production’s global warming potential (GWP). Based on the findings of the feasibility analysis, mango production is identified as a novel opportunity for mango farmers and environmentally conscious consumers. This is due to the fact that the production of mangoes of the highest quality is associated with a carbon footprint and other environmental considerations.  Based on the life cycle assessment conducted on conventional mangoes, taking into account greenhouse gas (GHG) emissions, it has been determined that the disposal of 1 kg of mango waste per 1 rai through landfilling results in an annual emission of 8.669 tons of carbon. This conclusion is based on comprehensive data collected throughout the entire life cycle of the mangoes. Based on the available data, it can be observed that the quantity of gas released through the landfilling process of mango waste exhibits an annual increase in the absence of any intervening measures. The cost benefit analysis conducted on the life cycle assessment (LCA) of traditional mango waste has demonstrated that the potential benefits derived from its utilization are numerous. The utilization of the life cycle assessment (LCA) methodology and the adoption of a sustainable business model exemplify the potential for developing novel eco-sustainable products derived from mango waste in forthcoming time.

Infrastructure development policies have been criticised for lacking a deliberate pro-gender and pro-informal sector orientation. Since African economies are dual enclaves, with the traditional and informal sectors female-dominated, failure to have gendered infrastructure development planning and investment exacerbates gender inequality. The paper examines the effect of the infrastructure development index, the size of the informal economy, and the level of economic development on gender inequality. The paper applies the panel autoregressive distributed lag method to data on the gender inequality index, infrastructure development index, GDP per capita, and size of the informal sector for the period 2005–2018. The sample consists of 44 African countries. The research established that the infrastructure development index, its sub-indices, GDP per capita, and the size of the informal sector are crucial dynamics that governments need to consider carefully when formulating development policies to reduce gender inequality. The research found that investment in infrastructure in general, transport infrastructure, and energy infrastructure reduces gender inequality. infrastructure development has gender inequality increasing effects in some countries and gender inequality reducing effects in others. The pattern suggests that at the continental level a Kuznets-type patten in the relationship between gender inequality and infrastructure development, gender inequality and size of informal sector, and gender inequality and GDP per capita exists. Some countries are in the region where changes in these covariates positively correlate with gender inequality, while others are in the region where further increases in the covariates reduce gender inequality.