Browse
Recent Submissions
Item Response surface modelling and optimization of oleic acid yield from Sclerocarya birrea kernel oil in supercritical carbon dioxide extraction(2026-03) Reddy, Trishen; Seodigeng, TThis study investigated the potential for maximizing oleic acid (C18:1) yield from Sclerocarya birrea (Marula) kernel oil using supercritical carbon dioxide (CO2) extraction. The investigation utilised a unique dataset comprising nine experimental runs derived from existing literature on Marula oil. Response Surface Methodology (RSM) was employed to evaluate the influence of the two primary independent variables viz. extraction pressure (varied between 250 bar and 450 bar) and extraction temperature (varied between 40 °C and 75 °C). During all runs, the CO2 flow rate, extraction time, and particle size were held constant. A significant second-order polynomial model was developed to predict the yield of oleic acid. To achieve a practical and economically viable outcome, the Optimal (Custom) option within Design-Expert Version 13 software was specifically utilised to optimise the combined effects of temperature and pressure. This customized approach identified the most desirable set of operating conditions viz. temperature of 60 °C and pressure of 250 bar for achieving maximal oleic acid recovery, thus providing a foundational model for sustainable industrial applications.Item Ferrocene-based hybrid drugs as potential anticancer and antibacterial therapeutic agents for incorporation into nanocarriers: In silico, in vitro, molecular docking evaluations(2025-05) Peter, S; Morifi, E; Nwamadi, M; Oselusi, SO; Tantoh, Asongwe LA; Fonkui, TY; Ndinteh, DT; Aderibigbe, BABackground/Objectives: Cancer and bacterial cases are increasing. Hence, new drugs to treat these diseases are paramount. Ferrocene-based hybrid compounds were synthesizedas potential cancer and bacteria therapeutics. Methods: The synthesized compounds were characterized via FTIR, NMR, and LC-MS and evaluated against different cancer cells and bacterial strains. Moreover, computational studies of these compounds were conducted using several silico tools. Results: Among the synthesized compounds, hybrid 10 was the most promising compound, displaying promising anticancer activity with IC50 values between 42.42 and 45.37 and 50.64 and 73.37 µg/mL against HeLa and CHO cancer cells, respectively, with a selective index greater than one on HeLa cancer cells. Compounds 22–26 displayed promising antibacterial activity with a MIC value of 7.8125 µg/mL against most bacterial strains in vitro. The in silico results revealed that this compound has strong binding affinities for 4qtb, 3eqm, and 2w3l cervical cancer proteins, exhibiting binding energies of −7.3, −8.7, and 7.4 kcal/mol, respectively. Furthermore, hybrid 10 showed promising pharmacokinetics and drug-like properties, including high GI absorption, moderate water solubility, favoring the oral administration route, nontoxicity, and is a P-gp substrate. Conclusions: The findings obtained in this study illustrate that hybrid compounds are potential therapeutics that need to be explored. The compounds also contained functionalities relevant for incorporating into nanocarriers to improve their biological activities further. Therefore, further studies are recommended for the most effective compounds to reinforce these findings.Item Cell damage, toxicity and bacterial diversity shifts of microcystis and oscillatoria cultures treated with bacterial isolates(2026-02) Ndlela, Luyanda L; Wesley-Smith, J; Oberholster, PJ; Smit, MThe mitigation of toxic cyanobacterial blooms is a much-researched and ongoing challenge. Seasonal influences, microbial diversity, and the wide range of cyanotoxins known to be associated with cyanobacterial blooms add layers of complexity to these environmental threats. Strategies to remediate blooms must avoid inducing widespread cell lysis and the release of cyanotoxins, which would compound rather than address the problem. Bacterial isolates have been found to be effective in bloom mitigation and can impact the diversity associated with the bloom. The present study reports on the exposure of non-axenic cultures of colonial Microcystis sp. and filamentous Oscillatoria sp. isolated from dams in South Africa to low ratios of four antagonistic bacterial isolates for 4 days. TEM was used to assess ultrastructural changes, HPLC to determine the relative concentrations of microcystin-LR and RR, and next-generation sequencing (NGS) to explore possible shifts in diversity from control samples as a result of exposure to the biological control bacterial isolates used. Ultrastructurally, Microcystis showed greater signs of stress than cells of Oscillatoria, with isolate 1 (Aeromonas lacus) having the least effect overall, whilst Isolate B (Lysinibacillus) and 3Y (Pseudomonas sp.) induced cell lysis in Microcystis. All isolates reduced the concentration of the toxic microcystin-LR, while the -RR variant often increased after 4 days. Minimal diversity shifts were noted in Microcystis-treated cultures, whilst those of Oscillatoria showed a greater diversity shift, indicating an increase in families containing isolates linked to bloom decline.Item Computational thermal analysis of FeCrV15+TiB2 coatings on EN48 baseplate by using the COMSOL Multiphysics(2025-07) Aramide, BP; Jamiru, T; Adegbola, TA; Popoola, API; Adeoti, MO; Sadiku, R; Pityana, Sisa LThis study seeks to elucidate the thermal effects of including TiB2 powder on the geometric evolution of FeCrV15 coating using a 3D simulation of the laser cladding process. The process entails applying a coating of FeCrV15 powder onto the EN48 substrate and incorporating TiB2 powder into the coating to evaluate the feasibility of IPG laser-applied coating layers. In order to modify the laser cladding process, the conservation equations of energy, momentum, and mass are linked via the temperature variable and resolved. Intricate hypotheses are employed in mathematical modeling to address the boundary conditions arising from the laser melting of several materials, thereby simplifying issues associated with varying material properties. Moving mesh is employed to ascertain the deformation of a free surface by utilizing the Arbitrary Lagrangian and Eulerian (ALE) methodology. The simulation disregards thermo-capillary forces and their influence on fluid dynamics within the liquefied pool to achieve process optimization. The developed procedure simulation also assesses the thermal dispersion associated with the procedure. The results provide approximate information regarding the influence of TiB2 on the development of clad geometry and the thermal gradient.Item Surface plasmon resonance-based biosensing towards the detection of multidrug-resistant tuberculosis(2026) Chauke, Sipho H; Hlekelele, Lerato; Maphanga, Charles; Tjale, Mabotse; Dube, FS; Ombinda-Lemboumba, Saturnin; Mthunzi-Kufa, PCurrent diagnostic tools for multidrug-resistant tuberculosis (MDR-TB) are molecular assay-based and have challenges associated with labor-intensive workflows, complex laboratory infrastructures, and limited mutation coverage. This highlights the need for alternative techniques that can be used as diagnostic tools for MDR-TB. In this study, we demonstrated the use of an surface plasmon resonance (SPR)-based biosensor chip for the detection of selected genes (InhA, KatG, and RpoB) within the MDR-TB genome using single-stranded deoxyribonucleic acids (ssDNA) targets and thiolated probes. The probes were successfully functionalized to AuNPs and confirmed using UV–vis and DLS. On SPR-based detection, the hybridization of the selected probes to complementary and non-complementary targets induced changes in the resonance angles. The hybridization of the selected probes to the targets was observed at resonance angles of 46.85, 46.77, 45.84, and 46.91° for the IS6110, InhA, KatG, and RpoB genes, respectively. In contrast, the unhybridized probe and the non-complementary targets exhibited resonance angles of 46.33, 46.05, 45.53, and 45.85° for the IS6110, InhA, KatG, and RpoB genes, respectively. The data showed that SPR-based biosensing can be refined and considered as an alternative approach to detect and differentiate between different ssDNA targets using thiolated probes as biorecognition elements for MDR-TB detection.Item Assessing tools for detecting AI-generated content in higher education(2025-01) Baloyi, Errol; Siphambili, Nokuthaba; Mahlasela, Oyena NArtificial Intelligence (AI) has rapidly transformed the world, particularly following the introduction of Chat Generative Pre-Trained Transformer (ChatGPT) on November 30, 2022. This innovation has sparked a surge of interest in AI, leading to significant investments and attention in both the private and public sectors. AI applications are now widespread, ranging from smart farming to automated cyber threat detection. In higher education, AI has emerged as a potential game changer, enhancing learning experiences and expanding educational access to diverse communities. For example, some institutions have utilized AI to reduce dropout rates, while others have employed AI for student assistance. Research has also shown that students primarily use AI tools like ChatGPT for academic tasks, such as writing assignments and conducting research projects. In South Africa, a recent survey of educational leaders highlighted a growing push to integrate new AI tools, like ChatGPT, into the educational system. However, the use of AI has raised ethical concerns, particularly regarding plagiarism. For instance, some students at the University of South Africa (UNISA) faced disciplinary action after it was discovered that they had used AI tools inappropriately. A gap exists in the ethical use of AI in higher education, although some universities, such as the University of Cape Town (UCT), are making progress. UCT has published student guidelines on the ethical use of AI tools, which include ensuring that any final product is the student’s own work and not simply copied from an AI generator. Therefore, the objective of this paper is to evaluate free AI detection tools that can help students check their work and ensure they are not unknowingly submitting AI-generated content. This will also ensure that, if students do use AI, they properly acknowledge it, as another key clause in the UCT guidelines and similar policies requires individuals to acknowledge any use of AI in their work. Each tool was assessed based on its features, performance, usability, and support.Item A model-based systems engineering framework for technology roadmaps (MBSE-TRM): Application to electronic warfare systems(2026-02) Reddy, Reeshen; Sinha, STechnology-intensive industries face accelerating change driven by disruptive innovations, geopolitical shifts, and the dynamics of Industry 4.0. In this environment, managers require strategic tools that can align markets, products, and technologies over time while retaining adaptability. Technology roadmaps (TRMs) are widely used for this purpose; however, current practice remains largely qualitative, workshop-led, and reliant on subject matter expertise. This constrains their utility in dynamic environments. This paper develops a Model-Based Systems Engineering framework for Technology Roadmaps (MBSE-TRM) to address these limitations. The research advances theory by introducing a conceptual metamodel that captures the ontology of TRM, formalizing its structure and lifecycle using SysML, and demonstrating how tacit practitioner logic can be represented explicitly. Validation is undertaken in the domain of Electronic Warfare (EW) against radar, a technology-intensive field characterized by rapid innovation cycles and strategic importance. The findings show that MBSE-TRM enables improved transparency, traceability, and adaptability, supporting managers and engineers in steering innovation strategies under conditions of volatility. By bridging systems engineering principles with technology strategy, MBSE-TRM provides a structured yet flexible framework for aligning strategic intent with evolving technology options in Industry 4.0 and beyond.Item Resource recovery and water reclamation from acid mine drainage: Market analysis, industry trends, and future research directions(2026-01) Mahlohla, MB; Masindi, Vhahangwele; Muedi, KL; Tekere, M; Baloyi, Siwela J; Foteini, SAcid mine drainage (AMD) is a highly recalcitrant wastewater that is typically generated from coal and metal mining activities and contains elevated levels of (heavy) metals and sulphates, along with rare earth elements (REEs) and radionuclides in some instances. This review seeks to elucidate AMD’s physicochemical characteristics and resource recovery avenues that can underpin circularity and introduce the waste-to-resource paradigm. Opportunities for major metals (e.g., iron (Fe) aluminum (Al), and manganese (Mn)) and critical minerals, such as v cobalt (Co), nickel (Ni), and notably rare earth elements (REEs), recovery, along with other minor constituents such as radionuclides were explored. Other valorization avenues such as sulfates transformation to sulfuric acid and recovery and water reclamation were further explored. The techniques for resource recovery from AMD, such as precipitation, adsorption, solvent extraction and ion exchange, were discussed, as well as possible industrial uses of the recovered materials (e.g., coagulants, adsorbents, pigments and catalysts). AMD beneficiation and valorization can minimize the ecological footprint of AMD and reduce virgin resource extraction, such as REEs, while water reclamation can provide water security in water-scarce countries. The recovered resources can provide an important revenue stream, via offsetting treatment costs and even making the process self-sustainable due to the high value of certain products. For example, the REEs global market in 2023 was USD$5.9 billion and is expected to reach USD$14.2 billion by 2033, with a compound annual growth rate (CAGR) of 12%, thus denoting that recovering REEs from AMD could be profitable, while it also reduces mining requirements and associated environmental impacts. Finally, knowledge gaps in terms of recoverability, along with their challenges and prospects and avenues for further research, were also distilled.Item Deconstructing the complexity of measuring food security in South Africa: a systematic review and meta-analysis (2000–2024)(2026-03) Masamha, B; Gwanzura, O; Mutanga, Shingirirai SMeasuring the non-observable nature of food security has remained complex mainly because of the construct’s complexity and its continuously evolving nature. The main challenges in measuring food security involve determining what is to be measured and how it is measured. In South Africa, various approaches and indicators have led to divergent food security measurement outcomes, leading to inaccurate assessment, monitoring, and targeting of context-specific food security interventions. This study analyses food access, availability, and stability measurement metrics and proposes a clear food security measurement approach for South Africa. Comprehensive reviews of food security indices with a national scope and subsequent meta-analysis to determine these indicators’ effect size, publication bias, and heterogeneity have not been adequately explored.Item Atomised NiTiTa from elemental powders for additive manufacturing of biomedical components(2026-04) Motibane, Londiwe P; Mkhonto, D; Tshabalala, Lerato C; Becker, THReadily available feedstock for Additive Manufacturing (AM) is in high demand as the technology advances and finds more applications worldwide. As such, the field of designing advanced alloys tailored for AM requires powder feedstocks engineered for both printability and application-specific performance. Nitinol (NiTi) is a shape-memory alloy that is biocompatible, super-elasticity, and exhibits the shape-memory effect; however, its functional window remains narrow for next-generation implants. Here we refine NiTi through ternary alloying with tantalum to create NiTiTa powder using ultrasonic atomisation under a highly controlled inert atmosphere on an Amazemet rePowder platform. To accommodate the disparate melting points and suppress elemental evaporation, two alloying strategies are considered and discussed: Ni, Ti and Ta mix, and Ti and Ta mix with the addition of Ni in the second phase of casting. Cast-rod microstructures, powder morphology, NiTi (D₅₀ ≈ 51 µm), and chemical composition (Ni 51.78, Ti 46.24 and Ta 1.98 wt.%) were characterised by SEM-EDS and XRD. Differential scanning calorimetry revealed a tailored martensitic transformation range (As ≈ 28 °C) suitable for physiological conditions. XRD confirmed predominant B2 and B19′ phases with minor Ta peaks. The findings confirm the feasibility of producing homogeneous, AM-ready NiTiTa powders, providing the foundation for forthcoming laser powder bed fusion trials aimed at patient-specific biomedical devices.Item The utilization of satellite imagery and machine learning to detect paved pavements from unpaved pavements in Gauteng, South Africa(2026-01) Singano, AfikaSatellite imagery analysis has become increasingly important for various applications, including urban planning, infrastructure development, transport asset management and disaster response. One critical task in satellite image analysis involves the detection and classification of roads. In this study, an approach utilizing the YOLO (You Only Look Once) Convolutional Neural Network (CNN) object detection model is proposed to distinguish between paved and unpaved roads from satellite imagery. Leveraging a custom dataset curated for this purpose, a YOLO object detection model was trained on Google Colab Pro's infrastructure, achieving promising results. Our methodology offers a robust and efficient solution for road type detection, with potential applications in urban development, transport planning, and environmental monitoring.Item Pharmacogenomics in Africa: A potential catalyst for precision medicine in genetically diverse populations(2025-03) Twesigomwe, D; Mazhindu, TA; Nagy, M; Agesa, G; Scholefield, Janine; Masimirembwa, CGenetic variation is a major determinant of drug response across populations. Owing to advances in sequencing technologies over the last two decades, several clinically actionable variants or haplotypes have been characterized in genes that encode proteins mediating drug pharmacokinetics or pharmacodynamics. Therefore, clinical application of pharmacogenomics has gained significant traction as a promising tool for enabling drug therapy optimization to mitigate adverse drug reactions while promoting drug efficacy. However, the implementation of pharmacogenetics testing has been slow in African settings and other resource-limited global regions. Moreover, there is a need to address gaps in various pharmacogenomics knowledgebases, especially regarding the genetic diversity in underrepresented populations. It is also important to ensure that emerging assays and technologies do not heighten existing healthcare disparities affecting African populations. We present the status of pharmacogenomics in Africa, highlighting its potential to impact health outcomes in the safe and efficacious use of medicines.Item Study of phase constituents, microstructural evolution, tensile properties and micro-Vickers hardness of as-cast and water quenched Ti-Mo-Fe alloy(2025-03) Moshokoa, NA; Makhatha, E; Raganya, Mampai L; Makoana, Nkutwane W; Mkhonto, D; Phasha, MThis study investigates phase constituents, microstructural evolution, tensile properties and micro-Vickers hardness of as-cast (AC) and water quenched (WQ) Ti-Mo-Fe alloys with varying molybdenum and iron contents. Three ternary alloys with Ti-8.6Mo-3.3Fe (TMF4), Ti-13Mo-2.2Fe (TMF5), and Ti-16.5Mo-1.1Fe (TMF6) compositions were designed from three theoretical methods, namely, electron per atom (e/a) ratio, the molybdenum equivalence (Moeq) and the Bo-Md. These alloys were cast using the arc melting furnace operating under inert atmosphere, followed by solution treatment and quenching. Different characterization techniques were used to analyse the microstructural evolution and phase constituents of the alloys XRD patterns of TMF4 and TMF5 samples in both AC and WQ conditions showed the presence of β and α″ phases whereas XRD peaks of TMF6 alloy in both conditions belonged to only β phase. Optical micrographs of all studied alloys in AC and WQ conditions showed only β equiaxed grains with different grain sizes. The EBSD phase maps of WQ TMF5 and TMF6 alloys revealed the presence of ω and β phases. It was illustrated that with an increase in β stability, the ultimate tensile strength (UTS) decreased slightly from 547 MPa to 540 MPa while elastic modulus of TMF5 and TMF6 decreased from 88 GPa to 74 GPa respectively.Item Numerical analysis of the failure mechanisms of continuous miner’s cutter sleeves for redesign and remanufacture(2025-03) Onyono, SO; Kyekyere, E; Lindsay, EE; Mswela, N; Olakanmi, EO; Prasad, RVS; Ndeda, R; Motimedi, T; Botes, A; Pityana, Sisa LTraditional failure analysis employs visual and microscopic examinations to identify modes, causative factors, and mechanisms of component’s damage. This approach is deficient in determining actual stresses and deformation which cause component’s failure; analysing how component’s geometry influence its failure; and assessing the feasibility of the recommended remedial measures to mitigate component’s failure. To address these concerns in failed sleeves of continuous miner’s cutter (CMCs); this study employed ANSYS software for finite element analysis (FEA), analytical calculation for model verification, while simulation findings were validated via microscopic observations. Collar fracture resulted from a high stress concentration (above 200 MPa) along the transition fillet areas while plastic deformation was caused by stresses above 100 MPa. Interactions between the sleeve and the rock seam generated cyclic stresses between 17–25 MPa which caused collar wear. Geometrical redesign of the sleeve collar by increasing fillet radius from 1 to 9 mm reduced stress to 133.03 MPa due to lower stress concentration factor. Surface modification with hybrid composite (TiC10%wt-WC10%wt) exhibited the best wear-resistance experimentally with the stress reduced to 6.8 MPa upon impact. Simultaneous combination of geometrical redesign and surface modification of the sleeve via laser cladding reduced deformation by 16.53 % (from 0.01277 mm to 0.010658 mm) and stress from 379.78 MPa to 116.44 MPa. It is concluded that multi-faceted failure analysis is a comprehensive approach that not only uncovers the failure modes, causes and mechanisms of premature failure of rotary sleeves, but also ascertains the causative stresses and remedial measures to mitigate the failure of CMC’s sleeves.Item Scanning strategy for grain size control in the multitrack laser metal deposition for additive manufacturing applications(2025-12) Khomenko, M; Makoana, Nkutwane W; Ronzhin, D; Pityana, Sisa LThe comprehensive investigation of scanning strategies of the multitrack layers produced by laser metal deposition (LMD) with coaxial powder feeding is presented. The first two steps of the part additive production are optimized using a previously developed hydrodynamic model in search for low waviness and microstructure control. We verify the numerical model for the single-track LMD showing rather good correspondence. The main parameters of the scanning strategy i.e. scanning path, overlap ratio and idle time are optimized for additive manufacturing (AM) applications. We show that the optimal overlap ratio is dependent on processing parameters and multitrack investigation is needed for its estimation. A new method for optimizing layer growth parameters is proposed, which is in the adjusting of the geometry of a single track when the process conditions change instead of searching for new hatch spacing. Feasibility for modifying the average crystalline size and the preservation of the layer geometry and scanning strategy is presented both numerically and in experiments. The possibility of controlling the grain size of similar layers is another step for building parts with a defined quality.Item Vision-type deep deterministic policy gradient for robotic manipulation with applications to ABB robots(2025-12) Dikole, Realeboga G; Baloyi, Andrew A; Sekopa, Teboho LThis research explores a vision-based Deep Deterministic Policy Gradient (DDPG) algorithm for robotic manipulations within the ABB IRB120 robot arm scenario. The robot is trained to perform reach tasks based on RGB image observations within a simulated OpenAI Gym environment. Performance is determined by comparing the ABB robot’s performance against that of the Franka Emika Panda robot using the same training regime. The study also contrasts image-based observations with traditional sensor data, with different learning efficiency and convergence. The experiment results show that the vision-based DDPG algorithm has a 70% success rate, confirming it can learn control policies directly from visual observations. In addition, the ABB robot exhibits more stable learning behaviour than the Panda robot. These findings support the use of vision-driven reinforcement learning for precise and dynamic robotic control.Item Evaluating reinforcement learning-Based xApps for user-centric resource allocation in open RAN(2025-03) Nokane, Boikobo; Isong, B; Masonta, Moshe TDynamic radio resource management is essential for optimising performance in an open radio access network (RAN). However, traditional methods often struggle with real time decision-making and resource allocation in dynamic environments. Intelligent solutions, such as xApps running on near-real-time (near-RT) RAN Intelligent Controllers (RICs), offer promising advancements in adaptability and efficiency. This paper evaluates the performance of 5 reinforcement learning (RL) algorithms: Advantage Actor-Critic (A2C), Asynchronous Advantage Actor-Critic (A3C), Proximal Policy Optimisation (PPO), Deep Q-Network (DQN) and Soft Actor Critic (SAC), which were implemented as xApps for dynamic resource allocation in an open RAN setting. We analyse how effectively each algorithm learns to allocate resources by associating user equipment (UE), connected to different service classes: video, voice and data, to base stations as they move through a simulated network environment. Additionally, we evaluate the agents by comparing their throughput, latency and reward performance, and validate the results by examining them over 5 seeds run under the same network configurations. Our findings reveal that DQN achieves the highest rewards and fastest convergence, followed by SAC, PPO offers stable learning at moderate reward levels, while A2C and A3C show slower convergence and lower rewards. These results demonstrate both the advantages and limitations of using RL for dynamic resource management in open RAN systems. Finally, we discuss future directions, such as exploring multi agent systems and deploying xApps in real-world open RAN testbeds, to advance practical applications.Item Artificial Neural Network-Based Optimisation of Geometric Characteristics in Laser Metal Deposition of TiC/Ti6Al4V(2025-02) Tlale, T; Mashinini, P; Masina, Bathusile NLaser metal deposition operates on the principle of layer-by-layer material addition, wherein each layer is formed by overlapping individual single tracks. Consequently, clads formed serve as the fundamental building blocks for this technology. Their quality directly affects the overall build quality, particularly the geometric characteristics, which are also critical to process productivity. In the present work, geometric characteristics of TiC/Ti6Al4V single tracks fabricated via laser metal deposition are optimised. An artificial neural network model was developed to predict the clad width, height, and dilution using processing parameters, laser power, scan speed, and powder feed rate, as model inputs. The Particle Swarm Optimisation algorithm was employed for hyperparameter selection. The hyperparameter-optimised model achieved a mean squared error of 0.00183 and an R2 score of 0.979 during training, and a mean squared error of 0.00709 and an R2 score of 0.887 during testing. Although the small discrepancy between training and testing metrics suggests slight overfitting, likely due to the size of the dataset, the model achieved a mean absolute percentage error of less than 10% during testing. Subsequently, process plots generated by the model predictions were used to identify suitable parameters, and a processing map was developed to highlight the window that achieves suitable dilution (14–24%), defect-free sound bonding, and thick and dense clads.Item A fully satellite-driven workflow for hydrodynamic modeling in data-scarce coastal systems: Integrating ICESat-2, Sentinel-2, SWOT and reanalysis models(2026-03) Payandeh, AR; Simard, M; Jensen, D; Campbell, AD; Van Deventer, Heidi; Christensen, AHydrodynamic models in coastal and estuarine systems are typically constrained by sparse bathymetry, boundary, and validation data, especially in regions where field campaigns are costly or impractical. Here we develop and test a fully satellite- driven framework for hydrodynamic modeling in South Africa’s Langebaan Lagoon without using any local in situ measurements. Bathymetry is derived by training multispectral Sentinel-2 reflectance against ICESat-2 ATL24 photon- derived depths using an XGBoost model optimized with Bayesian search. The final satellite derived bathymetry reproduces independent ATL24 points with RMSE = 0.45 m and R2 = 0.97. This bathymetry was used in a depth-averaged Delft3D Flexible Mesh model driven at the open boundary by TPXO tidal harmonics and by ERA5 winds. We validate modeled water surface elevation against 16 SWOT low- rate (250 m, unsmoothed) passes in 2023. SWOT–model comparisons yield an overall RMSE of 0.11 m and R2 = 0.61, with typical point differences <0.10 m (~5% of the 2 m tidal range), and showed consistent spatial gradients in water level from the offshore boundary, through Saldanha Bay, and into the lagoon. At the offshore boundary, TPXO and SWOT sea surface heights agree closely (R2 = 0.86). A ~26 min phase lag, determined using a lag-correlation analysis, reduces the TPXO–SWOT RMSE from 0.18 m to 0.11 m, indicating that phase differences explain some of the mismatch, with remaining differences likely linked to non- tidal signals. Our results demonstrate that combining passive optical, photon- counting LiDAR, radar interferometry, and global tidal/atmospheric models enables robust, transferrable hydrodynamic modeling in data-scarce coastal systems, offering a cost-effective pathway for monitoring.Item Combination therapies in drug repurposing: Personalized approaches to combatting leukaemia and multiple myeloma(2025-04) Monchusi, Bernice A; Dube, Phumuzile; Takundwa, Mutsa M; Kenmogne, VL; Malise, T; Thimiri Govindaraj, Deepak BDespite advances in cancer research, treating malignancies remains challenging due to issues like drug resistance, disease heterogeneity, and the limited efficacy of current therapies, particularly in relapsed or refractory cases. In recent years, several drugs originally approved for non-cancer indications have shown potential in cancer treatment, demonstrating anti-proliferative, anti-metastatic, and immunomodulatory effects. Drug repurposing has shown immense promise due to well-established safety profiles and mechanisms of action of the compounds. However, the implementation is fraught with clinical, logistical, regulatory, and ethical challenges, especially in diseases such as leukaemia and multiple myeloma. This chapter examines the treatment challenges in leukaemia and multiple myeloma, focusing on the role of drug repurposing in addressing therapeutic resistance and disease variability. It highlights the potential of personalized, tailored combination therapies, using repurposed drug components, to offer more effective, targeted, and cost-efficient treatment strategies, overcoming resistance and improving patient outcomes.