Mangosuthu University of Technology (MUT) is a university of technology situated on the outskirts of Durban, South Africa, on a site overlooking the Indian Ocean. MUT is located in the academic hub in the eThekwini metropole. It is a residential university..
Financial management is the most critical aspect regarding the determination of the success or failure of the public sector within the Republic of South Africa. However, currently, there are several challenges that militate against effective as well as efficient financial management within the public sector. Traditional financial management techniques remain a major obstacle to effective and efficient service delivery in South Africa’s public sector. Legacy systems and fragmented fiscal processes contribute to a lack of financial oversight, reduced accountability, and limited public engagement in budgeting decisions. These weaknesses undermine the credibility and responsiveness of public institutions, eroding citizen trust and deepening governance challenges. In response to these systemic issues, this study explores the transformative potential of innovative financial management reforms to serve as levers for good governance. Specifically, it examines how adopting modern tools and participatory approaches can improve transparency in financial operations, enhance accountability mechanisms, and promote trust between government entities and the communities they serve. By focusing on practical and scalable reforms such as digital financial systems, integrated procurement platforms, and citizen-inclusive budgeting frameworks, the study aims to assess how these strategies can improve governance outcomes within the South African public sector. The overarching goal is to identify evidence-based interventions that not only modernise financial practices but also align with broader objectives of ethical governance and inclusive public administration. The study reveals that innovative financial management reforms, particularly digitalisation and participatory budgeting, hold substantial promise for enhancing good governance in the public sector. These reforms foster greater transparency by making fiscal information more accessible, reinforce accountability through improved oversight mechanisms, and stimulate citizen engagement by involving communities directly in budgetary decisions. Ultimately, this research contributes to the growing discourse on institutional reform by highlighting the importance of innovative financial stewardship in rebuilding public trust and improving service delivery.
This paper proposes a new scalar field cosmological model aimed at studying the late-time acceleration of the universe, based on a parametrization of the deceleration parameter. The main objective is to constrain fundamental cosmological parameters by integrating the latest measurements of the Hubble parameter from various observational datasets, including BAO, BAO + R19, CC + SC + BAO, and CC + SC + BAO + R19 from recent galaxy surveys. With a redshift range covering 0.106
This study investigated teachers’ preparedness, attitudes, and the perceived impact of technology use in lesson delivery in selected Zimbabwean secondary schools. Guided by the Technology Acceptance Model (TAM) and the Technological Pedagogical Content Knowledge (TPCK) Framework, it examined how teacher readiness, institutional support, and infrastructure affect ICT integration. Quantitative data from 59 teachers were analysed using SPSS version 30. Results indicated that teachers generally had positive attitudes and moderate ICT competence, recognising technology’s benefits for student engagement and performance. However, inadequate infrastructure and limited support constrained effective use. The study recommends continuous training, improved resources, and supportive policies for sustainable ICT-driven education.
Integration of artificial intelligence (AI) into mathematics education holds significant potential to enhance learning outcomes; however, its effectiveness in resource-constrained higher education contexts remains uneven due to persistent digital divide barriers. This quantitative study investigates how socioeconomic status shapes first-level (technology access) and second level (digital skills and institutional support) digital divide barriers, and how these factors relate to students’ perceptions of AI-driven mathematics learning. Grounded in van Dijk’s digital divide theory, a cross-sectional survey was administered to 121 undergraduate mathematics students at a historically disadvantaged higher education institution. Descriptive statistics, Pearson correlation, and Chi-square analyses were employed to examine associations among socioeconomic status, access, skills, institutional support, and AI perceptions. The findings indicate that material access barriers, such as limited devices and internet connectivity, remain prevalent among disadvantaged students but show weak or inconsistent associations with perceptions of AI. In contrast, institutional support demonstrates a statistically significant positive relationship with students’ perceptions of AI training (r = 0.212, p < 0.05), highlighting its central role in shaping readiness for AI-enhanced learning. Overall, the results suggest that second-level digital divide factors, particularly structured institutional support, are more influential than access alone in determining students’ engagement with AI in mathematics education. The study implies the need for universities to move beyond infrastructure provision toward comprehensive and sustained institutional strategies that foster confidence, guided engagement, and equitable AI adoption.
The design of polymer-carbon nanocomposites with enhanced adsorption efficiency for emerging contaminants is critical for sustainable water remediation. Graphene-polymer composites are increasingly explored for their potential in the adsorption of organic material, but the molecular mechanisms governing the adsorption and interfacial miscibility remain poorly understood. This study used a multiscale computational framework, integrating quantum and all–atom molecular dynamics simulations with a thermodynamic Flory-Huggins free energy of mixing analysis to elucidate adsorption energetics and the bulk thermodynamic miscibility of graphene oxide (GO)/polyvinyl alcohol (PVA) composites with pharmaceuticals. This multiscale approach provided a prediction of adsorbent–adsorbate interactions consistent with experimental trend-based observation, validating GO–PVA as an efficient hybrid matrix for pharmaceutical adsorption, with the adsorption strength strongly dependent on the molecular structure of the pollutants. The hydrogen bonding and π-π stacking interactions are the predominant binding modes, while the dominant interaction type is physisorption, though chemisorption occurred in a few high-binding-energy adsorbent-adsorbate complexes. Temperature-dependent Flory-Huggins free energy analysis indicated that GO–PVA–H2O systems possess highly favorable mixing thermodynamics, whereas neat PVA–H2O interactions remain unfavorable, highlighting the hydrophilic enhancement conferred by GO. The combined results suggest that GO–PVA composites not only improve water compatibility but also enhance the affinity for pharmaceutical adsorption. Among the tested drugs with consensus rankings, irbesartan and ketoprofen showed the highest affinities toward GO, PVA, and GO–PVA composites. This study provides valuable molecular-level insights supporting the use of GO–PVA composites as promising adsorbents for the removal of pharmaceuticals from aqueous environments.
