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Drug-resistant tuberculosis in rural Eastern Cape: Integrating whole-genome sequencing, conceptual transmission modelling and community-based participatory research
(2026-09) Sineke, N; Faye, LM; Dlatu, N; Ombinda-Lemboumba, Saturnin; Apalata, T
Background: Drug-resistant tuberculosis (DR-TB) remains a major challenge in high-burden rural settings where biological, health-system, and social determinants interact. This study integrated whole-genome sequencing (WGS), mathematical modelling and Community-Based Participatory Research (CBPR)-informed principles to examine DR-TB within a conceptual biosocial framework. Methods: WGS data from 32 Mycobacterium tuberculosis isolates were analysed for resistance-associated mutations, phylogenetic lineages and genomic relatedness. A deterministic two-strain model explored drug-susceptible (DS) and DR-TB transmission. Hypothetical CBPR-informed scenarios modified transmission (β), treatment initiation (γ) and resistance amplification (α) parameters over 10 years. Results: Twenty-seven isolates (84.4%) showed resistance to at least one anti-TB drug, and 15 (46.9%) met MDR-TB criteria. Lineages 2 and 4 predominated. Under predefined assumptions, community-informed scenarios produced approximately 40–60% reductions in modelled DS-TB transmission and 20–35% reductions in DR-TB transmission relative to baseline. Conclusions: Integrating genomic evidence with transmission modelling and community-informed assumptions provides a useful hypothesis-generating framework for examining DR-TB. However, the modelled scenarios are exploratory and do not demonstrate the effectiveness of the CBPR intervention. Prospective studies using larger genomic datasets, longitudinal epidemiological data, and empirically measured community-level parameters are required.
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Anemometer calibration: Accuracy, traceability and impact on wind resource assessment
(2026-10) Dikgale, Moyahabo S
Accurate wind resource assessment forms the foundation of every wind energy investment decision, with anemometer-based wind-speed measurements serving as the primary input for evaluating site viability and predicting future energy production. The precision and reliability of these measurements directly influence energy yield estimates, project financing, and overall bankability. Even small sensor-level inaccuracies can propagate through resource assessment models, resulting in significant deviations in projected megawatt output and financial returns over a project's operational lifespan. Consequently, reducing measurement uncertainty at the data acquisition stage is critical for enhancing confidence in performance forecasts and supporting informed investment decisions. By implementing robust measurement practices, calibration procedures, and quality assurance measures, stakeholders can minimise uncertainty, improve energy production accuracy, and safeguard long-term asset value. Ultimately, high-quality wind-speed measurement not only strengthens project feasibility assessments but also contributes to the sustainable and profitable operation of wind energy assets.
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A compact, array-ready dual-polarized stacked patch element for C-band UAV SAR
(2026-05) Mafa, Ike M; Winberg, S; Ferreira, Riaan
This paper presents a compact dual-polarized stacked microstrip patch antenna designed for C-band spaceborne and UAV-mounted Synthetic Aperture Radar (SAR) systems operating in the ITU-allocated 5.25–5.57 GHz band (320 MHz). The antenna employs a novel coupling-excited feed architecture in which two orthogonal coaxial probes excite inverted U-shaped slots etched into a driven patch, enabling strong coupling and improved impedance shaping. A parasitic patch—scaled 5% smaller than the driven patch and incorporating matching rounded corners—is placed above the radiator to form a vertically coupled two-resonator system that broadens the impedance bandwidth while preserving planar symmetry suitable for array integration. Electromagnetic simulations performed in Altair FEKO demonstrate a −8 dB impedance bandwidth of 5.32–5.78 GHz (≈480 MHz), fully covering the 320 MHz SAR allocation. The antenna maintains inter-port isolation better than −17 dB across the band, with a peak isolation of −24.3 dB at 5.55 GHz; such isolation levels significantly reduce crosstalk in dual-polarized SAR channels, improving polarimetric accuracy without requiring external decoupling networks. The realized gain remains stable between 3–5.3 dBi, and cross-polarization levels stay below −18 dB in the main beam region. These results confirm that the proposed architecture offers a compact, low-profile, and wideband dualpolarized radiator well suited for next-generation space-borne and UAV SAR front ends.
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A socio-technical systems (STS) analysis of road fatalities in Gauteng province (2015-2019)
(2026) Masuku, Freeman N; Sinclair, M
Road safety in Gauteng represents a persistent and complex socio-technical challenge, shaped by dynamic interactions between human factors, engineering design, institutional governance, and socio-economic contexts. This study employs a socio-technical systems (STS) framework to analyse the multifaceted contributors to road traffic fatalities in the province for 2015 to 2019; data from 2020 was excluded due to covid-19 mobility distortions that would have confounded analysis of underlying systemic risk factors. Utilising a mixed methods, convergent design, the research integrates qualitative institutional data with quantitative fatality and exposure metrics to model the interplay of social and technical subsystems. Key findings reveal that temporal variables (time of day, seasonal weather patterns), infrastructural and operational factors (road class, posted speed limits), and socio-economic pressures (unemployment rates, population density, GDP per capita) are interconnected within the STS and collectively exacerbate fatality risk. The Spatially Aware Poisson Random Forest (SAPRF) model achieved MAE ≈ 0.031, RMSE ≈ 0.109, and R² ≈ 0.958, substantially outperforming standard random forest (R² ≈ 0.872) and Poisson regression (R² ≈ 0.06). The novelty lies in the first application of SAPRF in a South African road safety context, integrating STS theory with spatially aware machine learning. The study concludes that prevailing behaviour-centric interventions are insufficient and argues for a paradigm shift toward integrated, multi-level policy and design interventions targeting the root systemic couplings and feedback mechanisms inherent in the road transport system.
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An Integrated Value-Addition in Supply Chain Network for Metal-based Additive Manufacturing
(2023-10) Nzengue, ACB; Mpofu, K; Mathe, Ntombizodwa R; Oyesola, M
The increasing speed of product development and the ability to deliver complex, near-net-shaped engineering metal parts are key benefits of additive manufacturing (AM). Producing or replacing parts by leveraging AM relies heavily on supply chain (SC) functions. Inadequately managed SC could lead to lower productivity and process waste. Hence, the aim is to integrate value-adding activities into the SC network using the principles of lean manufacturing, such as Value Stream Mapping (VSM) and flowchart. A case study of a braking system manufacturer company in South Africa was used to exploit VSM and the flowchart for reducing process waste. The result of the case study revealed that the frequent use of expedited shipping increased transportation costs and lead times required excess raw material inventory, and lengthy supplier order processing. The approach demonstrated the need to adjust the business model by virtually synchronising the flow of information across the SC players in the configuration of the entire AM production and distribution activities. The study provides a framework that can guide AM organisations in improving efficiency and achieving significant cost and time savings.