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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.Item Selection of wear-resistant materials and implementation framework for remanufacturing ground exploring tools (GETs) for coal mining applications: case-study of continuous miner cutter (CMC’s) components(2025-04) Akintunde, IB; Lindsay, EE; Olakanmi, EO; Matshediso, BI; Motimedi, T; Botes, A; Pityana, Sisa LGround exploring tools (GETs), used in coal mining industries, encounter severe failure due to their continuous pressing and scratching against the coal seam embedded with hard bands and impurities. Failure of GETs lead to direct cost expenditure due to replacement of worn-out components; besides, significant indirect cost resulting from machine downtime when they are removed, and new ones are reinstalled. Mining businesses replace worn GETs with new parts at an exorbitant cost at a great risk to their sustainability. Replacement goes against the ethos of the circular economy (CE) philosophy which aims at ensuring highest value of resource utilisation while eliminating waste by improving the design of materials, products, and systems. A critical analysis of the approaches of CE for restoring damaged GETs reveals remanufacturing is the best option to adopt to keep GETs in good working conditions. Meanwhile, there is scanty literature to guide remanufacturing practitioners on materials selection and framework for implementing remanufacturing of damaged GETs. This review addresses this challenge by identifying appropriate wear-resistant materials and the most economically feasible remanufacturing technology which restores the performance of GET’s components to at least as new upon remanufacturing. Using the components of continuous miner (CM) as a case study, the operating environments in which GETs function are described to gain insight into the modes of failure encountered. Information gathered from the operation environments of the GETs and their failure modes assisted in selecting appropriate wear-resistant materials. Techno-economic analysis of the remanufacturing of various modes of failure of the components of GETs was carried out to ascertain the economic feasibility of remanufacturing various failure modes. Future perspectives of failure analysis, material selection, and framework for implementing remanufacturing of various failure modes (based on severity of damage) in GETs are presented. This review extends the frontier of knowledge in the fields of GETs remanufacturing and potential wear-resistant materials for GETs to academic researchers and industrial practitioners.Item Wear and tribo-corrosion behavior of laser surface alloyed Ti6Al4V with Ti, C and Ti + C(2025-02) Gayen, TK; Akinlabi, E; Pityana, Sisa L; Majumdar, JDThis study concerns evaluation of wear (against WC ball) and tribo-corrosion (against ZrO2 ball in simulated body fluid) properties of alpha + beta titanium alloy (Ti6Al4V) laser surface alloyed with pure titanium (100% Ti), pure carbon (100% C) and a mixture of Ti + C (in the Ti to C ratio of 90:10 and 50:50). The alloyed zone microstructure consists of α and α′ (100% Ti) and TiC and α′ (for 100% C and a mixture of Ti + C). The average microhardness of the surface was found to be improved from 240 VHN for as-received sample to 501 VHN − 630 VHN for laser surface alloyed one and increased with increasing carbon content. The Young’s modulus was found to vary from 132 to 179 GPa as compared to 114 GPa of Ti6Al4V and increased with increase in carbon content. There is a marginal improvement in wear resistance due to laser surface cladding with 100% Ti and a significant improvement due to the addition of carbon. The coefficient of friction (COF) was also marginally reduced due to laser surface processing with 100% Ti and decreased with increasing carbon content. The mechanism wear was established. Tribo-corrosion resistance in fretting wear mode against ZrO2 in Hank’s solution was found to be increased in terms of decrease in tribo-corrosion volume (0.35-0.24 mm3) and COF (0.43-0.29) as compared to as-received Ti6Al4V (0.43 mm3 and 0.52).Item An assessment of dry reforming of methane: A mitigated approach to technology investment(2025-07) Duma, Zama G; Mehlo, Thembelihle; Soni, MinalDry reforming of methane (DRM) is a reaction of methane and carbon dioxide to produce synthesis gas (syngas), a hydrogen and carbon monoxide (H2/CO) mixture, which can have applications in the petrochemicals sector. While DRM is topical at face value, it does produce a syngas with a low H2/CO ratio not typically used by the industry. This article highlights a desktop literature survey of practical application of a progressive approach to technology investment decisions. Key technical and business risks associated with funding the development of a high-performance DRM catalyst was identified. The study indicated the cost implications of integrating DRM technology with a Fischer-Tropsch (FT) plant where a deficit of H2 in the syngas, >1, requires external supply to increase it to an applicable ratio of 2. The article also compares DRM and its hydrogen-lean syngas with existing syngas production technologies such as steam methane reforming (SMR) and partial oxidation (PO). It also includes an overview of the reactions that influence DRM’s catalyst performance and an integrated impact assessment of DRM when applied to a specific use application.Item Privacy by design for GDPR compliance assessment(2026-12) Siphambili, Nokuthaba; Ngobeni, Sipho J; Shadung, Lesiba D; Netshiya, RofhiwaThe General Data Protection Regulation (GDPR), a European data protection law enacted in 2016, focuses on the protection of the data of individuals in the European Union (EU). Incorporating privacy by design (PbD) principles into Compliance assessment systems ensures that privacy is prioritized in the design and architecture of systems. This paper followed a systematic literature review that discussed privacy by design principles. It then formulates seven Privacy by design principles based on literature analysis. We then highlight a GDPR compliance assessment toolkit (GCAT) and compare the seven PbD principles to the GCAT to show that the GCAT was designed to incorporate privacy by default and privacy by design principles. The observations indicate how privacy by design principles are embedded into the development of the system to enhance trust among users.Item Comparing different food banks: A case study application of a proposed standard(2026-01) Du Plessis, MJ; Vermeulen, E; Aschbacher, H; Grobbelaar, S; Meyer, Isabella AFood banks are increasingly recognised as essential actors in reducing food waste and addressing food insecurity by redistributing surplus food outside formal retail systems. Their appraisal is critical for enabling mutual learning, strengthening international collaboration, benchmarking performance, and enhancing donor credibility. This paper introduces a novel methodology for cross-country comparison of food banks, grounded in the Realist Evaluation's Context–Mechanism–Outcome perspective and structured through a value chain lens to organise and identify indicators. The framework comprises 101 dimensions, representing the most comprehensive comparative assessment of food redistribution organisations to date. The methodology is applied in a case study comparing FoodForward South Africa (FFSA) and Team Austria Tafel (TAT). The application demonstrates both the usability of the framework and the relevance of the identified dimensions for comparative analysis. Findings highlight substantial differences between the South African and Austrian food banks across nearly all dimensions, including scale, operational models, organisational structures, infrastructure, finances, and regulatory contexts. These contrasts underscore the diverse environments in which food banks function. In South Africa's dispersed, high-need context, FFSA's hybrid warehousing and outbound delivery model achieves a broad daily reach. Conversely, in Austria's dense context, TAT's collection-based model operates effectively but at a smaller scale. Despite these differences, both food banks play indispensable roles in reducing waste and supporting vulnerable populations. The study underscores the importance of contextualising evaluation frameworks and offers a transferable tool for systematically comparing food banks across diverse socio-economic settings.Item An experimental comparison of lithium-Iron-phosphate battery charging protocols(2026-02) Mabeo, Reuben T; Thakoordeen, Renesh R; Moholisa, Tsolo E; Khumalo, Ntethelelo PThis study investigates the performance and thermal effects of different charging protocols for Lithium Iron Phosphate (LFP) batteries, focusing on their efficiency and impact on battery temperature. Five protocols—Constant Current (CC), Constant Power (CP), Constant Current Constant Voltage (CCCV), Constant Power Constant Current (CPCC), and Constant Power Constant Voltage (CPCV)—were applied to a commercial LFP battery pack. The results reveal that while the CPCV protocol provides the highest energy and coulombic efficiencies, it also induces significant heat, which can be detrimental. In contrast, the CCCV protocol, although less efficient, offers better temperature control, making it more suitable for applications where thermal management is critical. This study highlights the trade-offs between efficiency and thermal management in battery charging protocols, offering insights for optimizing battery performance in various applicationsItem Impact of Improper Battery Management System Design for Lithium-Iron- Phosphate Batteries(2025-10) Thakoorden, Renesh R; Mabeo, Reuben T; Hlalele, Thabo GThis paper presents an experimental investigation into the impact of Battery Management System (BMS) design on the performance and reliability of Lithium-Iron Phosphate (LiFePO4) batteries. The original objective of this study was to determine the State-of-Health (SoH) of three commercially available LiFePO4 batteries under a selected test protocol. The experimental results showed that the integrated BMSs in all three tested brands exhibited erratic and unpredictable behaviour in their charge and discharge current limits. The initial hypothesis was that the behaviour is directly linked to the overall battery temperature due to the heating during charging and discharging however, no discernible relationship could be determined. Tne observation was the premature shutdown of the batteries as depicted by the sharp current drops. The BMSs shutdown and disconnected the battery from the test equipment thereby ceasing the test. The tests were restarted and the data stitched together to be able to conduct an analysis. This highlights a flaw in the design or implementation of these “off-the-shelf” BMSs, as they limit the optimal operation of these batteries. This study demonstrates that improperly designed and implemented Battery Management Systems can affect battery performance. While the original scope of the tests was to determine SoH, the observed BMS behaviour prevented this assessment, shifting the focus to the critical impact of these design deficiencies.Item Southern Ocean summer warming is regulated by storm-driven mixing(2025-12) Du Plessis, MD; Nicholson, Sarah-Anne; Giddy, I; Monteiro, PMS; Prend, CJ; Swart, SThe Southern Ocean absorbs most of the excess heat resulting from climate change. However, climate projections show a persistent warm summer bias in its sea surface temperatures, indicating a limited understanding of the air–sea heat exchange mechanisms governing this region. Here we examine the impact of storms on the interannual variability of Southern Ocean surface temperatures during summer using in situ observations from underwater and surface robotic vehicles, climate reanalyzes and satellite data. We show that synoptic-scale storms regulate summer sea surface temperatures through alteration of the effective heat capacity of the mixed layer and the entrainment of colder water from below. Storms reduce the summer ocean heat gain by limiting solar radiation reaching the surface. This effect is partially offset by a reduction in heat loss due to turbulent air–sea exchange. We also find that interannual variations in sea surface temperature during summer in the Southern Ocean are driven by changes in storm-mean wind speeds, which are linked to the Southern Annular Mode. Our results demonstrate a causal link between storm forcing and sea surface temperature variability, which is critical for reducing warming biases in climate models and improving future climate projections.Item Evaluating the efficacy of hybrid deep learning models in assessing temporal night-time light trends for the cities of Cape Town, Durban and Johannesburg in South Africa(2025-01) Mncube, Z; Xulu, S; Mbatha, Nkanyiso BIntroduction: Increasing research demonstrates the value of nighttime light (NTL) data for studying human activities, including urban change. The public availability of these products on geospatial computing platforms like Google Earth Engine (GEE) has expanded their use for various applications and adding incorporation of Python and R analysis tools. Methods: Deep learning techniques such as Wavelet Denoise (WD), Empirical Mode Decomposition (EMD), and Enhanced Empirical Mode Decomposition (EEMD) are seldom used in NTL research, but here were used them with long short-term memory (LSTM) to form hybrid models to denoise and decompose NTL trajectory to interpretable frequency levels and intrinsic mode functions (IMFs) that improve trend evaluation. We leveraged these tools to assess the performance of deep learning models in modelling and forecasting NTL trends in Cape Town, Durban, and Johannesburg from 2014 to 2023. Root mean square error (RMSE) and mean absolute error (MAE) were used to evaluate model performance. Results: The findings indicate that integrating decomposition approaches with LSTM enhances the precision and interpretability of NTL modelling. In Cape Town, the RMSE for all models varied from 0.083 to 0.114, while the MAE ranged from 0.063 to 0.085. Durban, RMSE ranged from 0.069 to 0.133, and MAE varied from 0.055 to 0.108. Johannesburg, RMSE ranged from 0.124 to 0.449 and MAE varied from 0.102 to 0.383. Discussion: Because of decomposition advantages, EEMD-LSTM hybrid model showing superior efficacy in Cape Town and Johannesburg, whilst EMD-LSTM model excelled in Durban.Item Enhancing water permeability in thin-film nanocomposite membranes utilizing electrospun recycled PET and graphene oxide(2025-02) Zamisa, Mantsopa K; Sinha Ray, Supraka; Madirisha, MM; Ojijo, Vincent O; Seadira, T; Sadiku, RE; Kumar, Neeraj; Orasugh, JonathanAddressing the challenge of low permeability in Thin-Film Nanocomposite (TFNC) membranes is crucial for improving water filtration efficiency. Despite advancements in membrane technology, the interface between the substrate and active layer remains a critical research gap affecting overall permeability. This study aims to fill this gap using electrospun recycled polyethylene terephthalate (rPET) substrates combined with graphene oxide (GO). A vacuum-assisted self-assembly method was employed to coat microporous rPET substrates with GO. Extensive characterization techniques, including Scanning Electron Microscopy (SEM), Transmission Electron Microscopy (TEM), x-ray diffraction (XRD), Fourier Transform Infrared Spectroscopy (FTIR), and Brunauer–Emmett–Teller (BET) analyses, demonstrated the uniform GO layer formation on rPET substrates, indicating enhanced structural and operational efficiency. The integration of GO resulted in a crystalline structure modification, improved surface morphology, and increased water permeability. The optimized rPET-GO membranes showcased a significant decrease in water contact angle to approximately 93 degrees, denoting enhanced hydrophilicity and, consequently, better permeability compared to uncoated rPET membranes. Despite increased hydrophilicity, the membranes exhibited reduced but stable permeability rates, highlighting the effectiveness of the GO and rPET blend in advancing membrane functionality. These findings mark a significant advancement in membrane technology, offering enhanced water permeability efficiency and paving the way for a substantial impact on sustainable water management. Additionally, this study underscores the importance of recycling in developing advanced materials for environmental applications.Item The effects of processing parameters on hardness, microstructure and corrosion resistance of AlTiZrNbVCr high-entropy alloy(2025-11) Ogunyinka, AO; Popoola, API; Pityana, Sisa L; Sadiku, ER; Popoola, OMThe high-entropy alloys AlTiZrNbVCr (HEAs) are suitable for many applications due to their light weight, high strength, thermal and oxidation resistance. Traditional fabricating methods for HEAs often introduce defects, affecting their mechanical properties and performance. Advanced manufacturing techniques, including additive manufacturing, have been explored to improve microstructures and mechanical characteristics. In this research, the resistance of HEAs to wear and nano hardness properties was investigated. The sample of HEAs was fabricated via laser additive manufacturing, while the experimental analysis was performed using an X-ray diffraction system (XRD) and a scanning electron microscope (SEM) equipped with energy-dispersive spectroscopy (EDS). The result shows that sample A has the highest hardness and wear-resistant microstructure when compared with the other samples B and C. The Fast Fourier Transform (FFT) SEM processing image was determined at a length scale of the dendrite structure to be LC 192 µm. HEAs are applicable in solid hydrogen energy storage and submarines, especially in propulsion systems where space is limited and a high energy density is required.Item Study of microstructure, phase and mechanical properties of a novel titanium aluminide-based alloy fabricated by direct energy deposition(2025-01) Raji, SA; Popoola, API; Popoola, OM; Pityana, Sisa L; Tlotleng, MonnammeTitanium aluminide (TiAl) alloy is deemed to possess desirable properties but exhibits significant drawbacks such as poor fracture toughness, wear and ductility that impedes its structural application and limit workability and production. Hence, it is crucial to accomplish a sufficient stability in relation to strength and ductility without losing other attractive material properties of the TiAl alloy. Therefore, this work is aimed at studying a novel TiAl-based alloy synthesized using direct energy deposition (DED) technique. The alloy was developed through in-situ alloying with Al, Si, Ti, Mo and V elemental powders to fabricate quintenary alloy of Ti-Al-Si-Mo-V. From the results obtained, it was observed that the microstructural and phase analysis of the Ti-Al-Si-Mo-V alloys exhibited varying amount of β0 and ζ-Ti5Si3 phases along the grain interfaces reliant on the amount of Mo and V present with the formation of fully lamellar (FL) and duplex phase (DP) microstructures for 1400 °C and 1200 °C heat treatment temperatures, respectively. The Ti-Al-Si-Mo-V alloy ultimate tensile strength (UTS) was about 6.6–49.3 % greater than Ti-48Al-2 Nb-2Cr (GE-4822) alloy; while the yield strength (YS) was up to 34 % greater than GE alloy based on the nanoindentation results. Consequently, the Ti-Al-Si-Mo-V alloy would perform very well as material for aero-engines parts. The simulation result shows that cracking could be avoided by increasing the processing temperature. It was inferred that the processing temperature does not affect the maximum stress experienced by the TiAl alloy but the minimum stress level changes with processing temperatures.Item The impact of climate-smart agriculture practices on household vulnerability to climate change: Evidence from Zimbabwe(2025-10) Okumu, B; Ntuli, Herbert; Muchapondwa, E; Mudiriza, G; Mukong, AClimate change and variability pose a significant hindrance to agricultural productivity. The adverse effects are particularly concerning in many African countries that rely heavily on rainfed subsistence agriculture for their livelihoods. The promotion of climate-smart agriculture technologies as a pathway to enhancing food security, farmers' welfare, and providing climate adaptation and mitigation benefits is one of the several interventions aimed at improving agricultural productivity. However, there has been a dearth of evidence on the determinants of adoption of climate-smart agriculture practices as well as the impact of climate-smart agriculture practices on food security and household welfare. This paper contributes to this knowledge gap by using the probit model to explore the drivers of uptake of climate-smart agriculture practices, and the inverse probability weighting regression model and the instrumental variable approach to assess the impact on food security, household savings and household vulnerability. We find that the adoption of climate-smart agriculture practices among smallholder farmers is influenced by land ownership, climatic variables, land terrain and household sociodemographic characteristics. The study further revealed that adoption of climate-smart agriculture practices leads to a reduction in household savings and household vulnerability but leads to improved food security. Policy implications are also discussed.Item Natural acids as catalysts for the continuous flow production of the green solvent 2,2,5,5-tetramethyltetrahydrofuran(2025-12) Currie, BM; Van Vuuren, E ∙; Jugmohan, Jaimee; Panayides, Jenny-Lee; Riley, Darren LAs the demand for chemists to adhere to green chemistry principles increases, so does the demand for green solvents. Unfortunately, many green solvents, such as 2,2,5,5-tetramethyltetrahydrofuran (TMTHF), are costly and difficult to source. Traditional synthesis of TMTHF from 2,5-dimethyl-2,5-hexanediol has been reported to be catalysed by acids such as phosphoric and sulfuric acid, or, more recently, by H-beta zeolite. Although H-beta zeolite catalysts are high-yielding and selective, the energy required for their regeneration is high, and their production has questionable environmental impacts. A new approach was developed using flow technologies and naturally occurring acids as catalysts for TMTHF synthesis. Flow technologies are scalable, safe, efficient, and reproducible for daily chemical reactions, aligning with principles of green chemistry. This study observed several key improvements, including i) the use of a natural acid as a catalyst, ii) the use of water as a solvent, and iii) a continuous process for multigram-scale synthesis of TMTHF using citric acid monohydrate, with a yield of 72 %, resulting in a throughput of 8.24 g h−1 (9.43 kg L −1 h−1 space-time yield).Item Seasonality alters nitrogen and phosphorus metabolism of Aspalathus linearis (Burm.f.) R.Dahlgren(2025-09) Du Toit, E; Griebenow, S; Veste, M; Hills, P; Valentine, A; Lötter, Daleen; Kleinert, AAspalathus linearis (rooibos) is an important legume crop species in South Africa, however, its agricultural growth is under threat due to constraints induced by climate change. A reduction in water availability during the rainfall season is expected, influencing variation in growth and functioning through alterations in soil conditions. Therefore, this study aimed to determine the seasonal variation in nitrogen (N) and phosphorus (P) nutrient acquisition for A. linearis grown in two different soils on a commercial farm, by assessing nutrient recycling and mobilisation enzymes that are associated with N and P. Below-ground material sampling occurred in both the summer and winter months, corresponding to the dry and wet seasons of the region respectively. Both soil and seasonal variations had a significant impact on N and P acquisition enzymes. An increase in enzyme activity was seen during wetter seasons across all enzymes studied, with the highest enzyme activity commonly found in the shoots of the plants. Soils with increased carbon (C) and P did not lead to an increase in enzyme activity, however, they did influence amino acid concentrations with increases in amino acid concentrations in wetter seasons, while lower levels of these elements resulted in little change across seasons. This study highlights that A. linearis obtains nutrients during the wetter season allowing growth during the dry season. Furthermore, slight changes in soil conditions lead to changes in seasonal variation of nutrient acquisition, which could increase plant resilience to drought.Item The impact of mobile-based digital technology adoption on livelihood diversification: Evidence from Ethiopia(2026-01) Bule, DL; Ntuli, Herbert; Gandidzanwa, CThe integration of mobile phones and associated services into the diversification of livelihoods has the potential for rural transformation in developing nations. However, mobile-based technology adoption for livelihood activities in the Hadiya Zone, Ethiopia, remains inadequate. This study aims to investigate the impact of mobile-based technology adoption on livelihood diversification in the study area. The results of the instrumental variable Tobit show that mobile-based digital technology adoption positively and significantly influences livelihood diversification. This is evident particularly among the educated, men, remittance recipients, active labourers, landowners, urban residents, and traders. This underscores that the adoption of mobile-based technologies for livelihood activities is uneven, particularly among marginalised populations. Therefore, government, telecom companies, and development agencies should prioritise expanding network coverage, implement inclusive digital policies, and foster skills development. Additionally, promoting mobile money services and addressing affordability barriers are crucial to encouraging the adoption of mobile-based digital services for livelihood activities.Item Artificial intelligence in the battle against epidemics: A review of techniques, developments, performance constraints, and solutions with a focus on lassa fever(2025-12) Ohize, HO; Umaru, ET; Onumanyi, Adeiza J; Chingle, MP; Folorunso, SO; Ambafi, JG; Yusuf, I; Eneojo, AE; Ohize, SOIn recent years, artificial intelligence (AI) has gained recognition as a transformative tool, aiding in the prediction of disease patterns, outbreak control, and the efficient distribution of medical resources. This review explores the extensive contributions of AI in epidemic response, with particular emphasis on its application to Lassa fever. The review begins by analyzing the disease’s epidemiology and transmission patterns, laying the groundwork for understanding AI-driven approaches. Key AI technologies such as machine learning, deep learning, and natural language processing are examined for their impact on surveillance, diagnostics, and treatment innovation. Successful implementations include predictive models for outbreak identification and enhanced vaccine research. However, the integration of AI in epidemic contexts continues to face challenges, including insufficient epidemiological data, high computational requirements, and difficulty incorporating AI within existing healthcare infrastructures. These issues are particularly pronounced in the management of Lassa fever, where data limitations and disease variability add layers of complexity. Existing reviews fail to adequately address the latest AI advances in this domain, particularly in relation to implementation challenges, global trends, and emerging concerns. This gap is addressed by offering a comprehensive overview of AI-driven techniques, ongoing developments, and practical solutions tailored to Lassa fever control and prevention. Ultimately, this review champions an inclusive AI framework that improves preparedness and adaptability in the response to epidemics. By extrapolating insights from Lassa fever, it provides a strategic guide for stakeholders, scientists, healthcare professionals, and policymakers, seeking to take advantage of AI to strengthen public health resilience and epidemic management.