Search Results (21,247)

In this paper, we propose a resolvent-free and projection-free iterative algorithm to solve monotone inclusion problems. The proposed method employs a double inertial extrapolation strategy, in which two distinct inertial steps are used to construct two extrapolated points, together with a new self-adaptive step-size for selecting the inertial parameter in the proposed algorithm. This combination provides an effective strategy to incorporate information from two extrapolated directions without the metric projections and resolvent of an operator. Under suitable assumptions, we establish the strong convergence of the proposed sequence to a solution of the monotone inclusion problem. The obtained convergence result is further applied to minimax and critical point problems. Moreover, numerical experiments in finite and infinite dimensional spaces are presented to compare the proposed method with some existing resolvent-free and inertial schemes. The numerical results demonstrate that the proposed method achieves faster convergence in terms of the number of iterations and provides improved reconstruction performance, with higher SNR and lower MSE for the considered image restoration problems. Further, applications to image reconstruction and compressive sensing provide the practical effectiveness of the proposed approach. Full article

Hepatitis C virus (HCV) infection remains highly prevalent among people who inject drugs (PWID), where treatment effectiveness is strongly influenced by adherence and behavioral relapse. In this study, we develop and analyze a deterministic compartmental model to examine the impact of treatment adherence, relapse, and risk-reduction behaviors on HCV transmission dynamics. The model incorporates key behavioral pathways, including treatment initiation, partial adherence, and relapse to high-risk behavior. Analytical results establish positivity and boundedness of solutions, and the basic reproduction number is derived using the next-generation matrix approach. We show that the disease-free equilibrium is globally asymptotically stable when the reproduction number is below unity, while uniform persistence and a globally stable endemic equilibrium occur when transmission exceeds this threshold. Numerical simulations and sensitivity analyses indicate that the probability of transmission per needle-sharing event and the number of sharing partners are dominant drivers of epidemic persistence. In contrast, treatment uptake and sustained adherence significantly reduce transmission. Relapse to drug misuse undermines treatment benefits by expanding the infectious pool. These findings underscore the importance of integrating antiviral therapy with behavioral support to achieve long-term HCV control among PWID. Full article

Poor water quality monitoring and delayed responses to pollution remain major challenges in low-resource areas. Traditional methods of monitoring water and wastewater resources are ineffective because they take a long time to report contamination. Therefore, this critical review aims to examine how a combination of artificial intelligence (AI) and edge computing can comprehend decentralised, real-time water quality monitoring, even in areas with limited infrastructure and internet, constrained maintenance capacity, and shortages of skilled personnel. To our knowledge, this study is a first-of-its-kind integrated framework that showcases edge AI architectures and refers to specific operational, societal, and infrastructural limitations in the water, sanitation, and hygiene (WASH) sector. The synthesis clearly shows that the implementation of edge AI techniques has the capability to improve global water quality through immediate pollution detection, disaster forecasting, and automatic filter or alarm response without the need for cloud infrastructure. The examples given from developing countries support this statement by demonstrating that the technologies are low-cost and implementable in the long term. The problem of sensor calibration, data quality, and energy efficiency was identified as the most important implementation challenge. There is enough evidence of pilot-scale tests, but long-term validation of the technology in field trials is needed. The authors also present future research directions, such as the integration of AI, edge computing, machine learning, and IoT, and open-source edge frameworks. Edge AI systems provide promising avenues for decentralised water safety surveillance in low-resource communities in real time and can support the sustainable development goals of the United Nations through the realisation of clean water and sanitation for all. Full article

Biomass, particularly agricultural waste, has emerged as a highly attractive alternative fuel source for domestic and industrial applications. This study investigates the suitability and potential of plantain peel biomass (PPB) as a viable feedstock for bioenergy production. The PPB was comprehensively characterized using proximate and ultimate analyses, thermogravimetric analysis (TGA), Fourier-transform infrared (FTIR) spectroscopy, and scanning electron microscopy coupled with energy-dispersive X-ray spectroscopy (SEM-EDS). Experimental results indicate that the weight ratio of plantain peel (skin) to unpeeled plantains ranges from 27% to 47%. Proximate analysis of the PPB yielded volatile matter (VM) of 65.8% and fixed carbon (FC) of 14.5%, suggesting substantial energy potential. The ultimate analysis results, conducted on a dry, ash-free basis, were used to determine the biomass higher heating value (HHV), which ranged from 13.93 to 16.35 MJ/kg. TGA showed that the thermal decomposition of PPB is typical of lignocellulosic biomass, occurring in three distinct stages over a temperature range of 25 to 1000 °C. FTIR spectroscopy identified O-H and C-H as key functional groups present in the PPB, further supporting its viability for biofuel production. Furthermore, SEM micrographs revealed a porous surface texture with heterogeneous particle sizes and shapes. At the same time, EDS confirmed carbon (C), potassium (K), and oxygen (O) as the dominant elements, alongside trace amounts of magnesium (Mg), silicon (Si), phosphorus (P), chlorine (Cl), and iron (Fe). In conclusion, PPB represents a promising and sustainable feedstock for biofuel production in both domestic and industrial sectors. Full article

Flux-modulating machines are emerging as noteworthy machines, particularly in wind turbines. Due to their brushless medium-speed operations, they can be deployed for applications where reliability is a critical factor. Two popular machines in this category are brushless doubly fed machines (BDFMs) and wound-field flux-switching machines (WFFSMs). Although these machines work according to similar flux cross-coupling principles, they have almost contrasting descriptions. While the low power density (power per volume) of BDFMs is well documented in the literature, WFFSMs are commonly touted for their high power densities. In this paper, the performances of BDFMs and WFFSMs are compared to harmonize the perspective on their performances in wind generation applications. It is revealed that the compared BDFM and WFFSM topologies have identical performances with some notable nuances. They generate similar power for a given volume, with the WFFSM having greater efficiency, but they have lower power factors. Compared with conventional topologies like doubly fed induction generators, both flux-modulating topologies have considerably lower power densities. Nevertheless, it has been demonstrated that some design insights for one topology (WFFSM or BDFM) are transferable to the other, such as high-performing pole-pair combinations and magnetic loadings. It should also be noted that design developments such as dual stator configurations are beneficial for both topologies, as they enable significant increases in the power generated for a given volume. Full article

In this work, we prove the strong convergence of an inertial iterative scheme to approximate solutions of the equilibrium fixed point problem associated with nonexpansive mappings in Hilbert spaces. Numerical simulations are carried out to examine the performance of the proposed approach. The results indicate that the proposed inertial approach achieves faster convergence when compared with existing comparable iterative schemes. We also investigate how different choices of initial values influence the convergence behavior of our algorithms and we compare these effects with those observed in classical iterative schemes through graphical illustrations. In applications, we used our approach to solve the signal processing problem. We also apply it to a mathematical model describing the spread of an infectious disease, which illustrates its relevance to real-world dynamical systems. Finally, we show that the proposed method can be applied in solving constrained optimization, variational inequality and split feasibility problems which highlight its flexibility and wide applicability. Full article

Myopia is a growing public health problem expected to affect half the global population by 2050, making appropriate management of the condition necessary. Therefore, the purpose of this study was to investigate the knowledge and practices of South African optometrists regarding childhood myopia management. A quantitative, cross-sectional, descriptive design with a survey method was employed. An online questionnaire was distributed to practicing optometrists and included questions related to demographic information, knowledge of myopia and associated ocular pathologies, diagnostic work-up and management of childhood myopia. Data were summarised using descriptive statistics, and further analysed with univariate binary and ordinal logistic regression analysis where the independent variables were years of experience, certification and interest. A total of 124 completed questionnaires were received. The majority of participants used non-cycloplegic refraction and less than 20% performed dilated fundus examinations. Single vision distance spectacles were most commonly prescribed despite awareness of the efficacy of interventions to slow myopia progression. However, factors such as cost and the need for clinical guidelines limit the practice of evidence-based management. Participants were aware of some of the ocular pathologies associated with high myopia, indicating that this knowledge needs to be reinforced. Results from this study may be used to aid optometry policy development, regulatory council decisions and guide the content of professional development programmes to enhance knowledge. Full article

Assessing the effects of opencast coal mining on surface water is often complex, requiring integrated approaches that combine guideline-based assessments, water quality indices (WQIs), hydrochemical tools, and statistical analyses. This study evaluated multi-year water quality data (2018–2023) from five sites along the Leeuwfonteinspruit, a tributary of the Olifants River Catchment in the Mpumalanga Province, South Africa. Water quality parameters were assessed against the South African Water Quality Guidelines (SAWQGs) for domestic, agricultural, and aquatic ecosystem uses. The results indicate frequent exceedances of SAWQGs for key parameters such as sulfate (SO₄), electrical conductivity (EC), total dissolved solids (TDS), magnesium (Mg), calcium (Ca), iron (Fe), aluminum (Al), and manganese (Mn), particularly at the downstream site. Weighted Arithmetic Water Quality Index (WA-WQI) and Canadian Council of Ministers of the Environment Water Quality Index (CCME-WQI) classified water quality from good at some upstream sites to consistently poor or marginal water quality at downstream sites. Irrigation assessments based on sodium adsorption ratio (SAR), sodium percentage (Na%), and the United States Salinity Laboratory (USSL) diagram indicated that surface water posed a low sodicity risk across the catchment, with salinity identified as the primary constraint to irrigation suitability. Hydrogeochemical evaluation using Gibbs diagrams suggested that the upstream water chemistry is dominated by natural rock–water interactions and dilution processes, while midstream to downstream sites increasingly exhibit characteristics consistent with evaporation–crystallization and anthropogenic influences. Principal Component Analysis (PCA) and correlation analysis further suggested that water quality patterns are largely associated with salinity and mineralization that may be influenced by mining activities, with secondary contributions from agricultural inputs. Overall, the findings suggest that opencast coal mining is an important contributor to surface water quality deterioration in the Leeuwfonteinspruit, although other catchment activities and natural geochemical processes may also contribute. These findings highlight the need for strengthened monitoring, proactive mine water management, and effective regulatory enforcement. Full article

The consequences of changing climate conditions and associated extreme weather are increasingly discussed in the global railway transport sector, as infrastructure damage and service disruptions are more widely reported. The Passenger Rail Agency of South Africa (PRASA) is a critical component of the national passenger rail service that provides safe, reliable and affordable rail services to millions of passengers annually. However, the increasing recorded frequencies of extreme weather events in the country means that PRASA’s operations and infrastructure are not exempt from these emerging hazards. This provided an opportunity for the study to assess the spatio-temporal exposure and climate risk of climate-related extreme weather events to PRASA infrastructure and operations. The study drew on the strengths of a mixed-methods approach, integrating quantitative and qualitative techniques. It combined recorded historical extreme-weather event data from the South African Weather Service (SAWS) with expert-based focus group discussions to address the research questions. Findings show an increase in the recorded frequency of extreme weather events over a period of 103 years (1920–2022) in both areas. These hazards indicate exposure that can lead to damage to physical rail infrastructure and to train service disruptions. In both areas, Kendall’s tau indicated significant positive monotonic trends in the frequency of several weather-related hazards over time. Focus group findings identified coastal flooding, flash floods and sea-level rise as the top priority climate-related risks for PRASA along other key infrastructure vulnerabilities. On this basis, the study recommends both rail infrastructure and operational adaptations. Full article

Rock bolt reinforcement governs underground excavation stability through the combined effects of embedment depth, installation pattern, and interaction with the evolving stress and structural environment. Despite substantial advances across mechanistic, empirical, numerical, discontinuum, dynamic, and field-based research traditions, no unified framework currently integrates these approaches across geological and stress regimes. Current practice, therefore, relies on design methods calibrated within specific contexts, producing optimisation outcomes that are model-dependent, metric-sensitive, and not reliably transferable across site conditions. This review critically synthesises evidence from 30 peer-reviewed studies organised into six analytical categories: mechanistic confinement frameworks, empirical classification systems, numerical parametric investigations, discontinuum- and discrete fracture network (DFN)-based optimisation studies, high-stress and dynamic performance analyses, and field-based performance evaluations. The synthesis establishes three principal findings. First, optimal bolt embedment is stress-regime-dependent; plastic-radius-based design logic is appropriate under moderate static conditions but becomes insufficient under high stress or dynamic loading, where energy absorption capacity and controlled yielding govern performance. Second, in discontinuous rock masses, joint geometry and spacing dominate reinforcement effectiveness, shifting optimisation from uniform length selection toward pattern-specific alignment and multi-length configurations that outperform equal-length grids under DFN-controlled conditions. Third, numerical optimisation outcomes are sensitive to the choice of objective metric and modelling paradigm, such that bolt length and spacing recommendations cannot be transferred across analytical frameworks without explicit mechanism comparison. To integrate these findings, a unified conceptual framework is proposed based on regime classification using three dimensionless indicators: the bolt penetration ratio (Π₁ = L/r_p), which relates embedment to plastic zone radius; the structural interception ratio (Π₂ = S/S_j), which relates bolt spacing to dominant joint spacing; and the stress intensity ratio (Π₃ = σ_in situ/σ_cm), which relates in situ stress to rock mass compressive strength. These indicators identify whether confinement-dominated, structure-dominated, or stress-dominated behaviour governs stability, and direct design logic accordingly. The framework does not prescribe universal geometric thresholds; rather, it provides a structured classification pathway that integrates mechanistic and empirical evidence into a coherent and transferable design logic. Probabilistic validation incorporating geological variability, stochastic fracture network modelling, and iterative field calibration is identified as the necessary development path toward a statistically robust optimisation methodology. Full article

In efforts to survey biting flies, there is a need for a multi-species trap that can capture diverse families of hematophagous flies, thus functioning as a more robust and representative trapping method. The current study evaluated the efficiency of the baited P38T BioFlyTrap with other standard traps, namely the H-trap used in South Africa, the Vavoua (West/Central Africa), and the Nzi (East Africa), in informing decision-making to undertake enhanced surveillance and control interventions against biting flies in South Africa. A comparative study was done using a 4 × 4 Latin Square Design (LSD) approach over a period of 16 days in northeastern KwaZulu-Natal. The H-trap was most efficient for Glossinidae, while the Nzi trap caught the most diverse species dominated by Tabanidae. The P38T BioFlyTrap showed moderate performance across all categories (Glossinidae, Tabanidae, Muscidae (Stomoxyini)) of biting flies. The Vavoua trap was the least effective trap for Glossinidae and Tabanidae, but was relatively effective for Stomoxyini. In this environment, baited P38T BioFlyTrap would be useful for broader spectrum surveillance, while baited H-trap and Nzi remain specifically more performant, respectively for Glossinidae and Tabanidae. Full article

Digital governance has increasingly emerged as a critical institutional mechanism for strengthening public administration, enhancing accountability, improving service delivery, and advancing inclusive development across Africa. Governments across the continent have expanded investments in e-governance systems, digital public infrastructure, artificial intelligence (AI)-enabled administrative systems, interoperable service platforms, and data-driven governance reforms as part of broader modernization and Sustainable Development Goal (SDG) agendas. Despite these developments, digital governance outcomes remain uneven and are frequently constrained by fragmented governance architectures, weak institutional coordination, administrative capacity deficits, regulatory limitations, and persistent socio-economic inequalities. To address these challenges, this study conducts a qualitative Systematic Literature Review (SLR) guided by PRISMA 2020 reporting standards to examine how digital technologies interact with governance systems, institutional structures, administrative capability, and socio-technical inequalities across African public sectors. The review synthesized 42 included studies published between 2015 and 2025 using structured Boolean search strategies, predefined inclusion and exclusion criteria, abductive thematic synthesis, and framework-oriented analytical procedures. The findings identify three interconnected governance constraints shaping digital transformation outcomes across African public sectors: fragmented and centralized governance arrangements; institutional and administrative capability deficits; and persistent digital inequalities and exclusionary governance systems. Although digital governance reforms demonstrate important potential for improving transparency, interoperability, citizen participation, financial inclusion, and administrative efficiency, sustainable transformation outcomes depend heavily on institutional coordination, adaptive governance systems, digital inclusion, regulatory effectiveness, and accountable AI governance arrangements. Building on the synthesized evidence, the study develops a decentralized AI-enabled digital public governance framework linking decentralization, interoperability, institutional coordination, digital inclusion, adaptive governance, and ethical AI governance to sustainable public-sector transformation outcomes. The study contributes theoretically by reconceptualizing digital governance as an institutionally embedded governance transformation process rather than merely a technological modernization agenda. The findings further contribute to sustainability debates by demonstrating how inclusive and decentralized digital governance systems can strengthen institutional resilience, public-sector innovation, and sustainable development outcomes across diverse African governance contexts. Full article

Digital assessment has become central to Open Distance e-Learning (ODeL), yet its implementation often assumes equitable access to digital resources, potentially disadvantaging students studying in diverse geographical and socio-economic contexts. This study examined how students’ living contexts influence their experiences of digital assessment in undergraduate mathematics education at a South African distance education institution. An explanatory sequential mixed-methods design was employed. Survey data were collected from 253 undergraduate students, with 251 participants included in the inferential analyses after excluding two respondents who selected “Other” as their living area category. Quantitative data were analysed using chi-square tests, binary logistic regression, and ordinal logistic regression, while qualitative responses were analysed thematically. The findings revealed that living context was significantly associated with reliable internet access, and internet reliability significantly associated with students’ experiences of typing and submitting digital assessments as well as their perceptions of assessment inclusivity. Qualitative findings further highlighted challenges relating to connectivity, device limitations, mathematical representation, and the need for more flexible assessment practices. The study advances Contextualized Digital Assessment as a conceptual framework for designing equitable digital assessment that recognises students’ diverse technological, geographical, disciplinary, and socio-economic realities. The findings provide practical guidance for higher education institutions seeking to design more inclusive and context-sensitive digital assessment within ODeL environments. Full article

Background/Objectives: Contemporary sport-related concussion management has shifted from prolonged rest toward early, symptom-limited activity and a staged return-to-sport strategy. The Amsterdam framework provides an essential safety hierarchy but does not fully operationalize how clinicians should manipulate exercise dose, task complexity, recovery, and interacting rehabilitation domains within each stage. This Perspective proposes neuroperiodization as a constrained, criterion-based load-prescription framework nested within the Amsterdam strategy. Framework Development: The framework distinguishes prescribed external load from internal response, including symptom change and duration, heart rate, rating of perceived exertion, task quality, confidence, and delayed recovery. Clinical decision-making is organized through a repeated cycle of assessment, prescription, monitoring, adaptation, and reassessment. Proposed Framework: Neuroperiodization supports the concurrent but controlled development of aerobic, cervical, vestibular–ocular, neuromotor, cognitive–motor, and sport-specific capacities. Progression remains subordinate to medical clearance, clinical findings, symptom response, and sport-specific risk. Conclusions: Neuroperiodization should be regarded as a conceptual clinical framework rather than a validated rehabilitation protocol or an alternative return-to-sport clearance pathway. It integrates Amsterdam consensus recommendations, evidence-informed extrapolations, and author-proposed elements and requires population-specific adaptation and prospective evaluation. Full article

The analysis of genetic gain and changes in economic traits among modern and older cultivars is important to estimate breeding progress, evaluate the effectiveness of selection methods, identify optimised and neglected attributes, detect trade-offs, and inform strategies in crop improvement programs. This meta-analysis analysed global genetic gain and changes in seed yield, yield-related traits, and seed compositional attributes in soybean (Glycine max [L.] Merr.). A meta-database comprising 272 genetic gain data points recorded from 29 studies and 2555 mean performances captured from 34 research papers was compiled from research reporting cultivars released globally between the 1920s and 2010s. The mean values extracted from these studies were subjected to the R-Software analysis of variance (ANOVA) to reveal the effects of year of cultivar release and production region on the studied agronomic and compositional attributes. Boxplots were constructed to visualise data distribution and variability, and Pearson correlation and principal component analysis (PCA) were performed to examine inter-relationships among the measured traits with year of cultivar release and production region. Significant differences (p < 0.001) in mean performance were found among decades of cultivar release for seed yield (SY), number of seeds per pod (NSPod), days to flowering (DTF), days to maturity (DTM), and total biomass (TB). Cultivars released in the 2000s attained the highest mean SY of 3737.62 kg ha⁻¹, compared to 2156.08 kg ha⁻¹ observed for varieties released in the 1960s. Annual mean increases for SY ranged from 1.75 to 47 kg ha⁻¹year⁻¹, driven primarily by improvements in number of seeds per plant (NSP), NSPod, plant height (PH), DTF, TB, and hundred seed weight (HSW). Conversely, seed protein content (SPC) declined across most breeding programs, while seed oil content (SOC) showed only modest improvement, and no consistent genetic gains were documented for micronutrient traits, including iron (Fe), zinc (Zn), calcium (Ca), or phytic acid (PA) content. Phytic acid, a potent chelator of essential minerals and a known inhibitor of protein digestibility in monogastric species, represents a critical but largely untracked compositional target in global soybean breeding. The absence of PA as a systematically monitored trait constitutes a significant gap in the literature, with direct implications for the nutritional quality of improved cultivars. Future breeding programs should adopt an integrated approach that simultaneously targets high SY, enhanced micronutrient bioavailability, and reduced antinutritional factor concentrations to advance both agricultural productivity and global food and nutrition security. Full article