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Item Exploring the use of data in a digital twin for the marine and coastal environment(2025-03) Haupt, Shelley; Sibolla, Bolelang H; Molapo, Nkadimeng R; Mdakane, Lizwe W; Fourie, Nicolene MRThe ocean plays a vital role in our society and represents a constantly changing landscape that is not well understood and therefore needs continuous monitoring and research. Sustainable monitoring is essential to assess both the current and future state of our oceans. However, conventional monitoring faces significant challenges, including issues of accessibility, and spatial and temporal constraints. The development of digital twins of the ocean (DTO) offers an emerging technology that could revolutionise our understanding of marine and coastal environments. Current DTO have shown effectiveness in monitoring marine and coastal environments in the European context. However, there is a need for a DTO for the Southern African and Western Indian Ocean regions that addresses specific concerns that are relevant to these regions. Successful development of a DTO depends on the availability of high-quality data. Therefore, various data inputs are necessary to build an accurate digital twin. This paper explores the data that can be utilised in a DTO, detailing how different ocean variables are collected and integrated into the digital twin. As a first step towards the development of a DTO in these regions, the paper proposes a data management plan and its implementation in the development of DTO. The data management plan is based on the phases of data in a geospatial data life cycle. Challenges regarding the management of data in this DTO and possible solutions are presented in the conclusion.Item Experimental investigation of compression properties of binary quenched Ti–Mo alloys for potential use as load-bearing implants(2025-04) Moshokoa, NA; Raganya, Mampai L; Makoana, Nkutwane W; Mkhonto, D; Phasha, MJ; Makhatha, MECompression properties of three binary Ti–Mo alloys for potential use as load-bearing implants were investigated in this study. Three binary alloys, namely, Ti–15Mo, Ti–17Mo, and Ti–20Mo, were designed using theoretical predictive methods and produced using a plasma melting system. Melted ingots were heat treated in a muffle furnace at 1100 °C for 1 h and quenched in ice brine water. X-ray diffraction patterns demonstrated β + α″ phase peaks, deformation mechanisms showed thin parallel plates in TM15, wide deformation bands, and wavy thin lines in TM17 and wavy thin lines only in TM20 alloy. Compressive yield and ultimate strength as well as hardness decreased with an increase in Mo content. On contrary, compression strain increased with increasing Mo content.Item Optimizing translation for low-resource languages: Efficient fine-tuning with custom prompt engineering in large language models(2025-06) Khoboko, PW; Marivate, V; Sefara, Tshephisho JTraining large language models (LLMs) can be prohibitively expensive. However, the emergence of new Parameter-Efficient Fine-Tuning (PEFT) strategies provides a cost-effective approach to unlocking the potential of LLMs across a variety of natural language processing (NLP) tasks. In this study, we selected the Mistral 7B language model as our primary LLM due to its superior performance, which surpasses that of LLAMA 2 13B across multiple benchmarks. By leveraging PEFT methods, we aimed to significantly reduce the cost of fine-tuning while maintaining high levels of performance. Despite their advancements, LLMs often struggle with translation tasks for low-resource languages, particularly morphologically rich African languages. To address this, we employed customized prompt engineering techniques to enhance LLM translation capabilities for these languages. Our experimentation focused on fine-tuning the Mistral 7B model to identify the best-performing ensemble using a custom prompt strategy. The results obtained from the fine-tuned Mistral 7B model were compared against several models: Serengeti, Gemma, Google Translate, and No Language Left Behind (NLLB). Specifically, Serengeti and Gemma were fine-tuned using the same custom prompt strategy as the Mistral model, while Google Translate and NLLB Gemma, which are pre-trained to handle English-to-Zulu and English-to-Xhosa translations, were evaluated directly on the test data set. This comparative analysis allowed us to assess the efficacy of the fine-tuned Mistral 7B model against both custom-tuned and pre-trained translation models. LLMs have traditionally struggled to produce high-quality translations, especially for low-resource languages. Our experiments revealed that the key to improving translation performance lies in using the correct prompt during fine-tuning. We used the Mistral 7B model to develop a custom prompt that significantly enhanced translation quality for English-to-Zulu and English-to-Xhosa language pairs. After fine-tuning the Mistral 7B model for 30 GPU days, we compared its performance to the No Language Left Behind (NLLB) model and Google Translator API on the same test dataset. While NLLB achieved the highest scores across BLEU, G-Eval (cosine similarity), and Chrf++ (F1-score), our results demonstrated that Mistral 7B, with the custom prompt, still performed competitively. Additionally, we showed that our prompt template can improve the translation accuracy of other models, such as Gemma and Serengeti, when applied to high-quality bilingual datasets. This demonstrates that our custom prompt strategy is adaptable across different model architectures, bilingual settings, and is highly effective in accelerating learning for low-resource language translation.Item Advancements in antimicrobial textiles: Fabrication, mechanisms of action, and applications(2025) Orasugh, JT; Temane, Lesego Y; Pillai, Sreejarani K; Ray, Suprakas SWithin the past decade, much attention has been drawn to antimicrobial textiles due to their vast potential for reducing the spread of infectious diseases and improving hygiene standards in various environments. This review paper discusses recent studies on preparation methods, modes of action, effectiveness against different microorganisms, and applications of antimicrobial textiles in diverse industries. It examines further challenges, including durability, environmental impact, and regulatory considerations, and looks at prospects for developing and integrating these novel materials. This paper intends to provide a broad-based understanding of state-of-the-art technologies and emerging trends in antimicrobial textiles by integrating existing knowledge and highlighting recent advances in this field that contribute much to improved public health and safety.Item Towards mine modernisation: Digitisation of foundational supervisory leadership development training(0005) Khan, Sumaya; Auret, MariusDue to the modernisation of mines, traditional training methods may be supplemented to support the upskilling of supervisors in mines. A project was initiated by the SAMERDI SATCAP programme to demonstrate the “art of possibility” through a modern training methodology. Two exemplar digital supervisory leadership development modules for underground gold and platinum-group metal conventional and modernising mines, were developed for potential uptake by the mining industry. These exemplar modules were exhibited on a digital platform, towards leading and driving mining modernisation. The research adopted a mixed method approach that included a literature review, a review of an existing supervisory leadership development programme, data gathering, a pilot study, and stakeholder validation workshops. The research supported the development of exemplar digitised modules. The two digitised modules were showcased to the industry for potential adoption. Training slides, a facilitator guide, and a training video were developed for ease of use by industry. The training modules are generic and not specific to a particular mine. They may be used by multi-commodity mines, including gold and platinum-group metals, as ‘stand-alone’ modules. They are customisable, through consultation with relevant service providers for specific working environments. The findings indicated that both the traditional classroom training and the new digitised online learning solution offer advantages for supervisory leadership development. Digital learning is not a new concept for supervisors at mines and modern training methods are well-supported by supervisors in the industry. A ‘modernised’ training solution may consider a ‘blended’ learning approach that combines traditional training with digital methods.Item Enhanced ethylene gas sensing with Ag-modified β-Ga2O3 nanorods: Experiment and DFT calculations(2025-11) Gatsi, NC; Mhlongo, Gugu H; Moloto, N; Mwonga, PV; Ozoemena, KI; ErasmusCoetsee, E, RM; Swart, HC; Ntwaeaborwa, OMThis study reports, for the first time, the sensitive detection of ethylene by Ag-modified β-Ga2O3 nanorods synthesized by hydrothermal method. Surface modification of β-Ga2O3 nanorods-based sensors by 0.5, 1.0, and 1.5 mol% of silver (Ag) nanoparticles remarkably enhanced the sensor performance. A dramatic enhancement was observed from the 1.0 mol% Ag modified β-Ga2O3 sensor with a response of 3.18, a fast response time of 37 s, and the lowest detectable concentration of 1.3 ppm recorded at a low operating temperature of 140 ℃. Ethylene is a hormone that accelerates ripening in fruits and vegetables and its real-time detection at low concentrations is important for quality monitoring. The proposed underlying sensing mechanism for the detection of ethylene is explained from experimental data and density functional (DFT) theory calculations, and there is a correlation between experimental results and theoretical calculations. The DFT calculations elucidated the electronic sensitization of β-Ga2O3 by Ag.Item A review on material extrusion additive manufacturing of polycarbonate-based blends and composites: Process-structure–property relationships(2025-04) Mehrabadi, NR; Pircheraghi, G; Gasemkhani, A; Sanati, PH; Shahidizadeh, A; Kaviani, A; Ray, Suprakas SPolycarbonate (PC) is a valuable engineering polymer with numerous technical characteristics like desirable mechanical properties, high heat resistance, chemical resistance, optical clarity, and electrical insulation capabilities. Therefore, it finds extensive use in aerospace, automotive, consumer goods, optics, medical devices, and electronics. Materials extrusion additive manufacturing offers several advantages, such as customized geometry, minimal material waste, cost-effectiveness, and ease of material modification. Accordingly, PC has recently emerged as a robust and durable additive manufacturing material. This review aims to investigate how printing parameters in materials extrusion additive manufacturing affect the properties of PC and PC-based materials, with a specific emphasis on mechanical properties. The main drawbacks associated with purelaments, like high PC fi print temperatures, warping tendencies, and a propensity to retract during printing, are also discussed. Considering the significant demand for developing PC blends and composites tailored for application in material-extrusion additive manufacturing, the influence of different types of fillers, including polymeric, metallic, and ceramic, on improving the mechanical behavior is then reviewed. This paper explores the diverse applications of additively manufactured PC parts, especially within advanced areas like aerospace, electrical engineering, and medicine. Lastly, prospects and challenges are presented in the review.Item Bio-composite films from carrageenan/starch reinforced with nanocellulose for active edible food packaging: Development and optimization(2025) Dmitrenko, M; Pasquini, D; Piassi Bernardo, M; De Lima Alves, JM; Kuzminova, A; Dzhakashov, I; Terentyev, A; Joshy, KS; Maya, Mathew J; Dyachkov, APetrochemical plastics are widely used for food protection and preservation; however, they exhibit poor biodegradability, resisting natural degradation through physical, chemical, or enzymatic processes. As a sustainable alternative to conventional plastic packaging, edible films offer effective barriers against moisture, gases, and microbial contamination while being biodegradable, biocompatible, and environmentally friendly. In this study, novel active food packaging materials (in film form) were developed by incorporating starch, carrageenan, nanocellulose (NC), Aloe vera, and hibiscus flower extract. The effects of varying the matrix composition (26.5–73.5 wt.% starch/carrageenan), NC concentration (2.77–17.07 wt.%), and particle type (fibers or crystals) on the film structure and characteristics were analyzed using various methods. Scanning electron microscopy demonstrated good homogeneity and effective dispersion of NC within the blend matrix. An increased carrageenan content in the film improved wettability, moisture absorption, solubility, and water vapor permeability. The mechanical properties of the films were enhanced by NC incorporation and higher carrageenan content. The developed films also exhibited effective UV radiation barriers and biodegradability. Films with low carrageenan content (less than 33.3%) and high NC content (7%, 10% crystals or 10%, 15% fibers) exhibited optimal properties, including enhanced water resistance, hydrophobicity, and mechanical strength, along with reduced water vapor permeability. However, the high water solubility and moisture absorption (above 55% and 14%, respectively) indicated their unsuitability as packaging materials for food products with wet surfaces and high humidity. Theresults suggest that these films are well suited for use as edible food packaging for fruits and vegetables.Item Engineering γ-TiAl alloys: The effects of Sn, Si and Mn on densification, microstructure, and mechanical properties(2025-06) Ellard, JJM; Mathabathe, Maria N; Siyasiya, CW; Bolokang, Amogelang S; Vilane, VN; Rikhotso-Mbungela, Rirhandzu S; McDuling, Christoffel P; Masete, Mosimanegape SIn the quest to enhance the castability of modified second-generation γ-TiAl intermetallic alloys and improve their mechanical properties, the effects of small additions of Sn, Si, and Mn were investigated and compared in terms of densification, microstructural evolution, and corresponding mechanical properties. The alloys were produced by vacuum arc remelting of blended and cold-pressed precursor powders. The processing parameters were uniformly maintained for all the alloys. According to the results, the relative green density of quaternary-Si (Ti-48Al-2Nb-0.7Cr-0.3Si) compact was the highest with a value of 90.00 ± 0.07 %. The addition of 1 at.%Sn improved the castability of the alloy as indicated by the absence of shrinkage cavities and the highest relative density of 99.87 ± 0.06 %. However, after heat treatment, low values of room temperature yield strength (286 ± 23 MPa) and ultimate tensile strength (486 ± 48 MPa) were obtained as the Sn promoted the growth of γ grains and hindered the nucleation of α 2 and Ti 5 Si 3 phases. Conversely, additions of 0.3 at.%Si and 0.3 at.% Mn did not improve the castability of the alloys. However, Si promoted the nucleation of Ti 5 Si 3 precipitates which improved the yield strength to 494 ± 31 MPa and uniform elongation to 1.4 ± 0.1 % after heat treatment. Additionally, the quaternary-Si alloy exhibited improved fatigue properties at room temperature with a fatigue limit of 388 MPa. Its fatigue fracture modes were Inter-lamellar and cleavage at lower stress amplitudes, σ fracture mode dominated at higher σ a. Mn promoted the nucleation of α 2 a, while inter-lamellar-phase to give a moderate value of 426 ± 19 MPa yield strength after heat treatment.Item Aptamers and antibodies in optical biosensing(2025-02) Mpofu, Kelvin T; Chauke, Sipho H; Thwala, Nomcebo L; Mthunzi-Kufa, PatienceOptical biosensing has emerged as a vital tool for real-time, sensitive detection of biological analytes, with aptamers and antibodies leading as key molecular recognition elements. This review examines and compares their distinct roles, advantages, and limitations in optical biosensing. Antibodies, celebrated for their high specificity and mature production protocols, are often preferred in clinical diagnostics. However, challenges like cross-reactivity, environmental sensitivity, and production costs prompt exploration of alternative biorecognition molecules. Aptamers, nucleic acid–based recognition elements, offer several unique advantages, such as ease of synthesis, chemical stability, and amenability to modifications for improved target binding. While their relatively recent discovery means fewer standardized protocols and clinical applications compared to antibodies, aptamers show promise in complex sample matrices and emerging sensor platforms. This review also explores technological advances in both aptamer and antibody integration, surface modification strategies to enhance binding specificity and orientation, and regeneration methods to ensure biosensor reusability. Through a comprehensive comparison, the article aims to identify scenarios where one molecular recognition element holds distinct advantages over the other, paving the way for strategic applications in diagnostics, food safety, and environmental monitoring. In this review, we have explored the advancements and challenges associated with optical biosensing technologies, with a particular focus on LSPR-based sensors. Recent developments in nanoparticle fabrication, hybrid sensor platforms, and external stimulus-responsive systems have opened new avenues for biosensing applications in clinical diagnostics, environmental monitoring, and food safety. The review also discussed the integration of optical biosensors with Raman spectroscopy for enhanced analytical capabilities and highlighted innovations in metamaterial-based sensors for improved sensitivity and specificity. Despite these advances, several challenges remain, including surface stability, reproducibility, and limitations in detecting low-abundance analytes. Addressing these challenges will require further improvements in device design, bioreceptor immobilization strategies, and signal enhancement techniques. Future research efforts should also focus on the development of portable and cost-effective biosensing platforms that can be applied in resource-limited settings. Ultimately, this review provides valuable insights into future trends in aptamer and antibody-based biosensors, encouraging cross-disciplinary collaboration and innovation.Item Arduino-based devices in healthcare and environmental monitoring(2025-04) Tsebesebe, Nkgaphe T; Mpofu, Kelvin T; Sivarasu, S; Mthunzi-Kufa, PatienceRapid increases in diseases and pandemics over the past years have led to the development of more affordable and accessible biosensing equipment, especially in underdeveloped regions. One of the open-source hardware that has the potential to develop advanced health equipment is the Arduino platform. This review emphasizes the importance of open-source technology, specifically the Atmel family of microcontrollers used in the Arduino development board, and the applications of the Arduino platform in biosensing technologies to advance PoC devices. Furthermore, the review highlights the use of machine learning algorithms to enhance the functionality of user-defined prototypes, aiming to realize PoC devices. It also addresses the successes and limitations of microcontrollers and machine learning in the development of PoC devices using open-source technology. The primary purpose of this paper is to investigate how the Arduino platform can be leveraged to create effective and affordable biosensing solutions, by examining the integration of Arduino with various types of biosensors. The review showcases the potential of Arduino to democratize and innovate biosensor technology. Lastly, this paper extends the investigation of applications of Arduino to general health care and environmental monitoring.Item Removal of Tobacco Specific Carcinogenic Nitrosamines in Mainstream Cigarette Smoke and Aqueous Solution─A Review(2025-05) Setshedi, Katlego Z; Maity, Arjun A; Nyakale, Atlegang K; Ramahlare, Sebasa T; Chauke, Vongani P; Nkomzwayo, Thulisile N; Mandiwana, Vusani; Ray, Suprakas S; Hlekelele, LeratoTobacco-specific N-nitrosamines (TSNAs), which are associated with several cancers, are formed during the processing of tobacco alkaloids. Since tobacco smoking poses serious health risks, scientists, governments, and health regulators globally have denounced it and categorized its constituents according to their carcinogenicity. Tobacco smoke investigations are guided by standardized methods (ISO). With the help of standardized smoke-generating machines, precise quantification of TSNAs and other smoke constituents is now possible thanks to advancements in analytical techniques. This information supports initiatives to reduce the amount of TSNAs that smoking exposes people to. This review covers the occurrence, formation pathways, precursors, and control strategies through removal technologies, providing thorough analysis of the state of science today regarding TSNAs. The adsorption characteristics of different materials as possible filter additives or modifiers are critically discussed, emphasizing important elements like porosity, layering, acidity/alkalinity, and surface area that affect their performance for capturing TSNAs from smoke. While scientific understanding of these areas is still evolving, this review intends to provide for the first time research progress on the adsorption properties of various materials, including zeolites, silica, few-layer black phosphorus, metal–organic frameworks, and molecularly imprinted polymers, among others, for reducing TSNAs present in both cigarette smoke and aqueous solutions.Item Effect of infrared heat-moisture treatment and cooling rate on the material properties of amylose–lipid complex nanomaterials(2025-06) Maphumulo, NG; Masanabo, MA; Ray, Suprakas S; Emmambux, MNThere are limited food-compatible nanomaterials to be used in foods, or most of them are not considered as edible or clean label. Isolated amylose–lipid complex (ALC) nanomaterials were subject to infrared heat moisture treatment (IR-HMT) at 110°C for 1, 2, and 3 h continuously or IR-HMT for 1 h followed by different cooling systems (room temperature, refrigeration temperature, and liquid nitrogen) and repeated two more times. Differential scanning calorimetry (DSC) revealed that IR-HMT and an increase in cooling rates resulted in ALC nanomaterials with higher endothermic peak temperatures (Tp) (109–112°C) and the presence of Type II crystallites. Notably, IR-HMT and cooling with room temperature resulted in Type IIa ALC (Tp = 109°C), while cooling with refrigeration temperatures and liquid nitrogen resulted in Type IIb ALC nanomaterials (110–112°C). X-ray diffraction (XRD) revealed higher crystallinity (up to 21%) for IR-HMT ALC with different cooling systems compared to their untreated counterparts (13%). Furthermore, faster cooling resulted in ALC nanomaterials with higher crystallinity compared to slower cooling rate. IR-HMT resulted in ALC nanomaterials with lower viscosity compared to untreated ALC as observed from flow properties. Furthermore, they displayed lower water absorption and solubility indices, suggesting that IR-HMT and different cooling systems led to molecular changes in ALC nanomaterials that affected their properties.Item A wind turbines dataset for South Africa: OpenStreetMap data, deep learning based geo-coordinate correction and capacity analysis(2025-06) Kleebauer, M; Karamanski, Stefan; Callies, D; Braun, MAccurate and detailed spatial data on wind energy infrastructure is essential for renewable energy planning, grid integration, and system analysis. However, publicly available datasets often suffer from limited spatial accuracy, missing attributes, and inconsistent metadata. To address these challenges, this study presents a harmonized and spatially refined dataset of wind turbines in South Africa, combining OpenStreetMap (OSM) data with high-resolution satellite imagery, deep learning-based coordinate correction, and manual curation. The dataset includes 1487 turbines across 42 wind farms, representing over 3.9 GW of installed capacity as of 2025. Of this, more than 3.6 GW is currently operational. The Geo-Coordinates were validated and corrected using a RetinaNet-based object detection model applied to both Google and Bing satellite imagery. Instead of relying solely on spatial precision, the curation process emphasized attribute completeness and consistency. Through systematic verification and cross-referencing with multiple public sources, the final dataset achieves a high level of attribute completeness and internal consistency across all turbines, including turbine type, rated capacity, and commissioning year. The resulting dataset is the most accurate and comprehensive publicly available dataset on wind turbines in South Africa to date. It provides a robust foundation for spatial analysis, energy modeling, and policy assessment related to wind energy development. The dataset is publicly available.Item Spatial and temporal patterns of mangrove forest canopy gaps at the southern distribution limit(2025) Agyekum, MK; Zimmer, M; MacKay, F; Weerts, Steven P; Helfer, VMangrove forest canopy gaps occur in 35 countries across the global distribution of mangrove forests in some 110 countries. Yet, their spatial and temporal patterns and drivers of their formation and closure remain poorly understood. Here, we investigated whether gaps are distributed randomly, clustered, or dispersed over space and time in two showcase areas in South Africa, uMhlathuze, near Richards Bay, and Beachwood, near Durban, to prime better understanding of the underlying processes. We mapped canopy gaps using free satellite imagery within Google Earth Pro and fixed wing-acquired aerial images and analyzed spatiotemporal patterns using the Ripley’s K function and the Emerging Hot Spot Analysis. Kaplan–Meier analyses estimated the time it takes for gaps to close. Canopy gaps in uMhlathuze occurred spatiotemporally clustered, whereas Beachwood canopy gaps primarily exhibited random spatial patterns. The spatial distribution of canopy gaps was linked to great canopy height at both uMhlathuze and Beachwood, supporting the hypothesis of lightning strikes as causal agents of gap formation. Canopy gaps at uMhlathuze remained open for at least 23 yr, and no gap at Beachwood had closed over the 18-yr study time span, rendering our study region near the southern distribution limit of mangroves a contrast to mangrove forests in many other regions of the world. Without active human intervention, the rising frequency of thunderstorms—and consequently, lightning strikes—is expected to increase canopy gap formation in mangrove forests. This will significantly reduce the ability of mangrove and estuarine systems in South Africa to support climate change mitigation and adaptation, weakening the resilience of coastal socioecological systems.Item Synthesis, characterization and antiviral efficacy of valacyclovir loaded polymeric nanoparticles against wild-type herpes simplex virus type 2(2025-06) Obisesan, OS; Tshweu, Lesego L; Nkabinde-Thete, Lindiwe; Ramalapa, Bathabile , OS Tshweu; Ngoepe, MP; Saartjie, R; Mufhandu, HTHerpes simplex virus type 2 (HSV-2) remains a significant public health concern due to its high rates of mortality and morbidity. While various chemotherapeutic options exist for treating HSV-2, they are often inadequate as none provide a definitive cure, and there is a growing issue of drug-resistant strains. The introduction of nanomedicine for antiviral drug delivery offers a promising avenue to enhance the effectiveness of these treatments. This study explored an innovative approach to treating HSV-2 by encapsulating valacyclovir in biodegradable polycaprolactone (PCL) using a double emulsion technique. The formulated valacyclovir-loaded polymeric nanoparticles were characterized, revealing monodispersed particles with an average hydrodynamic size ranging from 154.9 ± 2.1 to 232.8 ± 6.2 nm, along with an encapsulation efficiency of 50%–66% and a drug loading capacity of 11.6%–13.9%. Additionally, there is no significant cytotoxicity of the test compounds to Vero cells at 0.3 mg ml−1 concentration with a cell viability within the range of 85 ± 13.6%−100 ± 4.8%. The antiviral activity of both the free drug (valacyclovir) and the valacyclovir-loaded polymeric nanoparticles was assessed in HSV-2 infected Vero cells. The results demonstrated that the valacyclovir-loaded nanoparticles exhibited a 1.2–1.3fold (p < 0.005) increase in antiviral efficacy compared to the free drug. This study thus presents a novel nanotechnology-based treatment approach for HSV-2, offering enhanced antiviral effectiveness over traditional treatments.Item Enhanced piezo-induced photocatalytic activity of BaTiO3/Cd0.5Zn0.5S Ssingle bondscheme heterojunction for water pollution remediation: Performance, degradation pathway, and toxicity evaluation(2025-06) Mohlala, TT; Yusuf, TL; Masukume, Mike; Ojijo, Vincent O; Mabuba, N, TT YusufPharmaceutical pollutants in water pose a threat to ecosystems and human health by disrupting aquatic life, contributing to antibiotic resistance, and causing hormonal imbalances and increased disease susceptibility in humans. Thus, we report the fabrication of a novel BaTiO3/Cd0.5Zn0.5S heterojunction for the piezo-photocatalytic degradation of ciprofloxacin (CIP) in wastewater. The BaTiO3/Cd0.5Zn0.5S was synthesized via solvothermal deposition of Cd0.5Zn0.5S (CZS) onto BaTiO3 (BTO) nanorods. This heterojunction exhibited superior photocatalytic activity, degrading ciprofloxacin ∼85 % and ∼3 times more effectively than pristine CZS and BTO, respectively. Its enhanced piezo-photocatalytic performance is attributed to the induced piezoelectric effect, sulfur defects, internal electric field, and S-Scheme charge transfer. Scavenger studies identified h+, O2-, and •OH as the major reactive species responsible for CIP degradation. After 90 min, the extent of mineralization reached 46.7 %, and intermediate products were evaluated using Ultra-performance liquid chromatography-mass spectrometry(UPLC-MS), with their toxicity assessed using the Toxicity Estimation Software Tool (T.E.S.T). The catalyst demonstrated excellent stability over four reuse cycles. The successful development of the BTO/CZS heterojunction holds significant promise for advancing environmentally sustainable water treatment and pollution remediation technologies.Item Projected changes in daily temperature extremes for selected locations over South Africa(2025-03) McBride, CM; Kruger, AC; Johnston, Charmaine M; Dyson, LExtreme events, particularly very high temperatures, are expected to increase because of climate change. It is thus essential that localised studies be done to quantify the magnitude of potential changes so that proper planning, especially effective adaptation measures, can be affected. This study analysed annual extreme daily maximum temperatures for future climate change scenarios at 22 locations in South Africa, through analysis of a subset of the Coordinated Regional Downscaling Experiment (CORDEX) model ensemble datasets. The multi-model simulations were validated against observational data obtained from the South African Weather Service for the period 1976–2005. Two study periods of mid- (2036–2065) and far-future (2066–2095) were analysed for two Representative Concentration Pathways, i.e., RCP4.5 and RCP8.5. Bias correction was done on the model data to correct simulated historical climate data, to be more characteristic of observed measurements. While the method included adjustment for variance, systematic underestimations of extremes were still evident. The Generalized Extreme Value distributions were fitted to the bias-corrected projections, and 10-, 50- to 100-year return periods quantile values were estimated. The return period quantile values are likely to increase under both Representative Concentration Pathways in the mid- and far-future periods, with the largest increase in return period quantile values set to occur towards the end of the century under the highest emission scenario. All stations showed an increase in the frequency of days with maximum temperatures above specific critical thresholds, with some stations under the RCP8.5 scenario projected to experience temperatures of greater than 32°C (35°C) for more than 200 (100) days per year by the end of the century, an increase from a baseline of approximately 70 to 150 (14 to 83). For the same scenario, Return periods for 38°C for most stations are projected to be shorter than a year. From the above and considering the likely underestimation in the severity of the projected changes, i.e. too low return period quantile values, the general implication is a strong likelihood that most places in South Africa is likely to experience a strong increase in the intensity, duration, and frequency of very hot extremes in future, with potentially dire consequences to relevant socio-economic sectors. We suggest that future research, comprised of the full set of CORDEX data be conducted to optimise the results of this study.Item Smart buildings: Federated learning-driven secure, transparent and smart energy management system using XAI(2025-06) Khan, MA; Farooq, MS; Saleem, M; Shahzad, T; Ahmad, M; Abbas, S; Abu-Mahfouz, Adnan MIIn modern smart grids and decentralized systems, smart buildings face several key energy management challenges, including data privacy concerns, the need for accurate real-time decisions, the complexity of managing Distributed Energy Resources (DERs), and the lack of transparency in Artificial Intelligence (AI) systems, which erodes user trust. Traditional energy management systems rely on centralized data gathering and processing, where energy data from various sources is accumulated and processed in one location. While centralization aids in decision-making regarding energy distribution, it also raises concerns about data privacy, cybersecurity, and the opaque nature of AI decisions, all of which undermine user confidence. To address these issues, Federated Learning (FL) and Explainable Artificial Intelligence (XAI) offer promising solutions. FL decentralizes model training, enhancing data privacy and security, while XAI provides clear explanations of AI decisions, fostering user trust. When combined, FL and XAI create a secure, transparent, and interpretable framework for managing energy in smart buildings. This paper proposes an FL-driven XAI model that aims to improve data privacy, accelerate real-time decision-making, enhance efficiency, and increase transparency, thereby building user trust. The proposed model demonstrates superior performance in simulations compared to previously published approaches.Item NATO Framework for modeling and simulation of human lethality, injury, and impairment from blast-related threats and its practical implementation to support blast injury research(2025-06) Santago, AC; Bagchi, A; Bieler, D; Cernak, I; Erdik, A; Erlich, T; Franke, A; Huri, PY; Josey, T; Reinecke, John DBlast-related trauma was the predominate source of casualties within Iraq and Afghanistan and has maintained in the Ukraine conflict. Computational modeling is anticipated to accelerate discovery of novel solutions for mitigating injuries and reduce costs in research and development. The North Atlantic Treaty Organization (NATO) saw the future value in a comprehensive, whole human blast effects modeling capability to counter emerging blast threats resulting in establishment of a research technical group (RTG) to develop a framework for the capability. The RTG performed a literature review demonstrating the lack of such a capability along with the necessary pieces needed for a framework. RTG development framework consists of: Model 1 Threat characterization: generates a computational representation of the blast-threat; Module 2 Biophysics: produces the relevant loading profile and predicts biomechanical, pathophysiological, and neurological responses; Module X Injury Prediction and Medical Diagnosis: provides predictions on injuries (e.g., fracture) and Module Y Medical Outcomes provides understanding of the clinical consequences (e.g., functional incapacitation) of those injuries. The framework can assist in mitigating blast injuries and their consequences on Service Member readiness. Key hurdles to its development include a lack of high rate material characteristics and siloed model development.