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.

Using data from 31 provinces, municipalities, and autonomous regions in mainland China from 2006 to 2019, we employ a double difference (DID) model and a spatial double difference (SDID) model to estimate the impact of the High-speed Railway (HSR) on the income gap between urban and rural residents, as well as its spatial spillover effects. Our research reveals several key findings. Firstly, the introduction of high-speed railways helps to narrow the income gap between urban and rural residents within local areas, but its spatial effects can lead to an increase in the income gap in neighboring provinces. Secondly, from a spatial perspective, intermediate variables such as industrial structure, education, science and technology, and foreign trade can also contribute to balancing the income gap between urban and rural residents, although the impact of population mobility is not significant. Thirdly, further analysis of the spatial effects demonstrates that education plays a significant role in balancing the income gap both within the local province and neighboring provinces. Additionally, adjustments in industrial structure, advancements in science and technology, and foreign trade have stronger spillover effects in reducing the income gap among neighboring provinces compared to their impact at a local level.

Islamic banking is one of the fastest-growing sectors of the financial industry. Several works have been written in this field, but none attempt to learn the entire Islamic banking and financial system. Furthermore, the study could not locate any publications investigating the conceptual and intellectual foundations of this emerging field of inquiry. The current study uses bibliometric methodologies to assess the current state of Islamic banking, financial research, and the upcoming trends. For the people who choose interest-free investments, the current research examines a conceptual research context on Islamic banking and finance at various planning and decision-making stages. One thousand research studies appearing in scholarly journals between 2005 and 2023 were reviewed for the purpose. In order to examine the works on Islamic banking and finance, bibliometric techniques were used, including analysis of citation network, content, co-citation, keyword, and publishing trends. By suggesting thirteen clusters, to enhance research on Islamic banking and finance to help interest-free investors learn more, the goal of the research is to promote the body of knowledge. The field of Islamic banking and finance has grown from a young lot to a prominent teaching and research tool. Investigating and identifying current research trends in this area is crucial. As institutions and society are placing more emphasis on Islamic banking to raise individual citizens’ responsibilities in developing interest-free investing strategies, the findings are crucial to the community of interest-free financiers. Further research urges with the studies not restricted to a thousand researches only.

The following paper assesses the relationship between electricity consumption, economic growth, environmental pollution, and Information and Communications Technology (ICT) development in Kazakhstan. Using the structural equation method, the study analyzes panel data gathered across various regions of Kazakhstan between 2014 and 2022. The data were sourced from official records of the Bureau of National Statistics of Kazakhstan and include all regions of Kazakhstan. The chosen timeframe includes the period from 2014, which marked a significant drop in oil prices that impacted the overall economic situation in the country, to 2022. The main hypotheses of the study relate to the impact of electricity consumption on economic growth, ICT, and environmental sustainability, as well as ICT’s role in economic development and environmental impact. The results show electricity consumption’s positive effect on economic growth and ICT development while also revealing an increase in pollutant emissions (emissions of liquid and gaseous pollutants) with economic growth and electricity consumption. The development of ICT in Kazakhstan has been revealed to not have a direct effect on reducing pollutant emissions into the environment, raising important questions about how technology can be leveraged to mitigate environmental impact, whether current technological advancements are sufficient to address environmental challenges, and what specific measures are needed to enhance the environmental benefits of ICT. There is a clear necessity to integrate sustainable practices and technologies to achieve balanced development. These results offer important insights into the relationships among electricity consumption, technology, economic development, and environmental issues. They underscore the complexity and multidimensionality of these interactions and suggest directions for future research, especially in the context of finding sustainable solutions for balanced development.

Brunei Darussalam is a small Sultanate country with diverse forest cover. One of them would be Mangrove Forest. As it has four main administrative districts, Temburong would be the chosen case study area. The methods of collecting data for this article are by collecting secondary data from official websites and the map in this article (Figure 1) are showing the forest cover in Brunei Darussalam as of 2020. The aim of this article is to explain the mangrove forest especially at the Temburong District. As for the objectives, it would to be able to show the different types of forests in Temburong, hoping in ability to explain the different subtypes of mangroves forest and to explain in general the green jewel of Brunei Darussalam. Temburong has become the second highest tree coverage in Brunei Darussalam of 124 kha as of 2010, while the mangrove forest covering about 66% of total mangrove forest of 12,164 km² out of 18,418 hectares. Mangrove forest has seven subtypes: Bakau species, Nyireh bunga, Linggadai, Nipah, Nipah-Dungun, Pedada and Nibong. Selirong Forest Reserve and Labu Forest Reserve are the two-mangrove forest reserves in Brunei Darussalam at Temburong District. Forest cover in Brunei Darussalam are 3800 hectares as of 2020 and has lost its tree coverage of 1.17 kha and one of the reasons would be forest fire and the tree cover loss due to fire is around 197 ha and the district that has lost its tree cover mostly was at Belait District of total 13.4 kha between the year 2001 until 2022.

Climate change plays a vital role in shaping the knowledge construction of farmers for managing their agricultural land. Therefore, this study aims to analyze the coffee farmers’ knowledge construction process regarding climate change. This research utilizes qualitative methods. This research approach uses the grounded theory, which can help researchers uncover the relationship between the coffee farmers’ knowledge construction and climate change. The data were collected through semi-structured interviews and analyzed using constant comparative methods. The transcription of the field notes was analyzed using NVivo version 12, a program for analyzing qualitative data. There were 33 informants in the study. This study found that the conditions and situations of wind speed and uncertain whether strongly influence the farmers’ construction of climate knowledge. Coffee farmers are looking for new ways to respond to climate change, such as increasing the intensity of the care they give to their coffee plants, gradually harvesting according to the ripeness of the coffee fruits, finding alternative ways to dry the coffee beans, and reducing the use of fertilizer. However, coffee farmers are also starting to adapt old knowledge from their parents to the latest perceived climate phenomena, so that they can look for alternative sources of livelihood outside their farms. This knowledge construction process serves as a form of adaptation by the coffee farmers to climate change, and reflects the dynamic between traditional knowledge and current experience. Understanding this knowledge construction helps coffee farmers to cope with climate change and to design appropriate policy strategies to support the sustainability of coffee farming in an era of climate change. Further research is needed at the regional level.