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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.

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AI-Enabled R&D in ACLS: Better scientific decisions, faster translation

(2026-08) Cho, Moses A; Tsekoa, Tshepo L

Artificial Intelligence (AI) is becoming a transformative enabler of research and development (R&D) within the Advanced Chemicals and Life Sciences (ACLS) domain. This presentation explores how AI can accelerate the journey from scientific discovery to practical impact by enhancing decision-making, improving research efficiency, and supporting faster translation of innovation into real-world applications. Key examples include the use of computer vision in precision agriculture and food safety for automated quality assessment, yield estimation, defect detection, and waste reduction; the application of African health data to inform diagnostics, therapeutic development, and healthcare decision-making; and the use of predictive AI models in chemicals and materials science to forecast outcomes before synthesis and scale-up. The study highlights 35 identified AI applications across ACLS, demonstrating varying levels of maturity and strategic value. To maximize benefits, four strategic opportunity areas are proposed to focus investment, capability development, and organizational learning. The presentation further emphasizes the importance of tailored acceleration pathways and a shared institutional AI backbone supported by trusted external networks. Collectively, these approaches position AI as a critical catalyst for innovation, sustainability, and competitiveness in scientific research and industrial development.

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Urban planning to strengthen resilience to extreme climate events - a systematic review

(2026-09) Birkmann, J; Rembold, M; Hampel, F; Mack, SL; Jamshed, A; Ehring, BD; Schick, D; Ramirez Herrera, AC; Thomae-Pohl, L; Pieterse, Amy

A growing body of literature shows that cities are key actors in mitigation and adaptation to climate change. However, there is less knowledge about the approaches and challenges urban planners face in building resilience. Existing studies often focus on specific planning tools in selected cities, while limited attention is given to the wider assessment of challenges and tools used in different world regions and across income classes. This paper explores how urban planning-related challenges and measures for strengthening resilience vary across city sizes, regions, and income groups based on a systematic review of scientific papers applying the ROSES standards. The first analysis included 3410 articles, and following multiple screening iterations, 398 papers were ultimately considered for in-depth review. Data extraction was supported by LLM-based software, and the results were verified through in-person checking. We find that administrative issues (institutional fragmentation and lack of cooperation) are mentioned most frequently as a challenge across regions. In contrast, land-use conflicts differ significantly between world regions, though less so between cities of different size. Differences also emerge, e.g. in terms of the use of nature-based approaches (NbA) and digital tools. NbA are more frequently discussed in the literature that refers to small and very small cities compared to megacities and large cities. NbA are not solely common in Europe, but also in Africa and Small Island States. IT and digital tools are more frequently mentioned in papers that deal with cities in high-income countries. This digital divide points to the fact that the resources available to invest in such tools and technology also depend on income levels and financial resources. Overall, the findings underscore that multi-level governance and development conditions are important factors that influence the challenges faced by urban planning and its capacity to support resilience building.