The menace of road traffic accidents (RTAs) has become a major constraint to development in most developing countries because of driving behaviour. This study examines the effects of road users’ education programmes on driving behaviour toward RTA reduction in Nigeria. Data for the study were collected by random sampling of 287 respondents. The respondents comprising road safety officers and drivers were selected at six (6) zonal headquarters of the Federal Road Safety Commission. The questionnaire presented seventeen (17) statements in a 5-point Likert scale for the respondents to rank in order of importance as they have influenced driving behaviour. The data collected were analysed using exploratory factor analysis to identify the most significant effects of road user education on driving behaviour. The study found that road user education programmes have influenced driving behaviour by improving bad driving acts, maintaining good vehicle conditions, and obeying road communication signs. The finding implies that appropriate driving behaviour will reduce road traffic accidents.

This study investigates university students’ understanding of the mole concept and its implications for chemistry education, highlighting the critical role of mathematical education. A questionnaire was administered to 303 students from universities in Panama, Mexico, Cuba, Chile, and Spain. The results reveal that only 29.7% of participants recognize the mole as a fundamental unit, while 20.8% confuse the amount of substance with a non-existent “Chemical System.” Only 18.5% correctly identified the substance quantity symbol as “n” and 32.7% were aware that Wilhelm Ostwald introduced the term mole, indicating deficiencies in historical knowledge. The significance of these findings highlights major misconceptions and gaps in both conceptual understanding and historical knowledge, underscoring the urgent need for revised teaching strategies. Addressing these issues is crucial for bridging the gap between theoretical knowledge and practical application, thereby enhancing instructional methods and optimizing chemistry education to improve students’ comprehension of fundamental concepts.

Presently, any development initiatives without considering sustainability can barely be imagined. There has been a paradigm shift in the focus of the development partners from the mere development to sustainable development. However, the role of development partners in bringing sustainability in livelihood assets of the rural community has long been questioned. Hence, this study aims to explore the sustainability in the form of changes in livelihood assets of a local community in Bangladesh. This study considers the changes in livelihood assets of the community over the three-time frames - before, during, and after a project implemented by a national NGO called ‘UST’ and subsequently identifies the community’s capacity to sustain the project outcomes after the completion of the project. ‘Sustainable Livelihood Framework (SLF)’ developed by Department for International Development (DFID) was utilized in this study to analyse the vulnerability and livelihood issues of the community members. Data has been collected through focus group discussions, household survey and key informants’ interviews from three distinct villages of ‘Khutamara’ union in the ‘Nilphamari’ district of Bangladesh. The finding of the study states that all the livelihood assets such as the social capital, human capital, natural capital, financial capital, physical capital have positively changed due to the interference of the development partners. This study further finds that even after the completion of project tenure, such positive trends continue to exist among the community members indicating sustainable development. Moreover, political capital- a new type of livelihood has also emerged because of the project implementation which was not quite evident before the inception of the project. In addition, this study explored the unique phenomenon of the Shabolombee Gram, where the transformation altering farmers’, livelihoods does not come from the government or the private sector but originates from a Non-Governmental Organization (NGO). Therefore, the government and its development partners may adopt and incorporate the Modified Sustainable Livelihood Framework (MSLF) to ensure the sustainable development.

Credit risk assessment is one of the most important aspects of financial decision-making processes. This study presents a systematic review of the literature on the application of Artificial Intelligence (AI) and Machine Learning (ML) techniques in credit risk assessment, offering insights into methodologies, outcomes, and prevalent analysis techniques. Covering studies from diverse regions and countries, the review focuses on AI/ML-based credit risk assessment from consumer and corporate perspectives. Employing the PRISMA framework, Antecedents, Decisions, and Outcomes (ADO) framework and stringent inclusion criteria, the review analyses geographic focus, methodologies, results, and analytical techniques. It examines a wide array of datasets and approaches, from traditional statistical methods to advanced AI/ML and deep learning techniques, emphasizing their impact on improving lending practices and ensuring fairness for borrowers. The discussion section critically evaluates the contributions and limitations of existing research papers, providing novel insights and comprehensive coverage. This review highlights the international scope of research in this field, with contributions from various countries providing diverse perspectives. This systematic review enhances understanding of the evolving landscape of credit risk assessment and offers valuable insights into the application, challenges, and opportunities of AI and ML in this critical financial domain. By comparing findings with existing survey papers, this review identifies novel insights and contributions, making it a valuable resource for researchers, practitioners, and policymakers in the financial industry.

The aim of the study is to identify the requirements for qualifying administrative leaders and the challenges they face at King Khalid University, in light of the general framework of the Human Capacities Development Program, which includes four dimensions (values and behaviours-basic skills-future skills-knowledge). A descriptive approach was used, and the study population consisted of academic leaders at King Khalid University, totalling (107). A questionnaire was used as a research tool, comprising three axes and (53) statements to collect data after ensuring their validity and reliability. The results showed the agreement of the study population on the axis of requirements for qualifying administrative leaders at King Khalid University to a very high degree, with an average score of (4.44), and their agreement on the challenges facing the qualification of administrative leaders at King Khalid University to a very high degree, with an average score of (4.11), and their agreement on the mechanisms for qualifying administrative leaders at King Khalid University to a very high degree, with an average score of (4.29). The results also showed no statistically significant differences at the significance level (0.05) between the means of responses of the study population on the requirements, challenges, and mechanisms for qualifying administrative leaders according to variables (gender-academic qualification—experience in the current job). In light of the study results, a proposed strategy was developed, and recommendations were made, including adopting the proposed strategy and governing the programs for qualifying administrative leaders at King Khalid University to ensure transparency, fairness, and accountability at all stages from nomination, preparation, and evaluation, in addition to considering the university’s strategic plan when designing programs for qualifying administrative leaders to adopt the values embraced by the administration and build leaders who contribute to achieving its vision and mission in the long term.

A smart city focuses on enhancing and interconnecting facilities and services through digital technology to offer convenient services for both people and businesses. The basic infrastructure of smart cities consists of modern technologies such as the Internet of Things (IoT), cloud computing and artificial intelligence. These urban areas utilize different networks, such as the Internet and IoT, to share real-time information, improving convenience for the inhabitants. However, the reliance of smart cities on modern technologies exposes them to a range of organized, diverse, and sophisticated cyber threats. Therefore, prioritizing cybersecurity awareness and implementing appropriate measures and solutions are essential to protect the privacy and security of citizens. This study aims to identify cyber threats and their impact on smart cities, as well as the methods and measures required for key areas such as smart government, smart healthcare, smart mobility, smart environment, smart economy, smart living, and smart people. Furthermore, this study seeks to evaluate previous research in this field, establish necessary policies to mitigate these threats, and propose an appropriate model for the infrastructure associated with IT networks in smart cities.