Central University of Technology, Free State or CUT is a University of Technology in Bloemfontein in the Free State province of South Africa. It was established in 1981 as "Technikon Free State". As part of the South African government's restructuring of tertiary education for the new millennium it was promoted to university of technology status..
Despite the growing availability of Earth observation data, African countries like Mozambique lack an integrated, long-term approach for the combined assessment of LULC change and its caused vegetation stress. This approach is necessary for supporting sustainable land management practices. This study addresses this gap by incorporating advanced remote sensing techniques to monitor combined trends for land cover and vegetation dynamics in Mozambique from 2024 to 2024. This research involved the use of Landsat 8 OLI/TIRS data processed in GEE for LULC classification using RF classifier, NDVI and FVC to evaluate vegetation health in the area. The results reveal that the urban areas have been expanding by 60% since 2014. Forest, which covers 80% of the country's land cover, initially fluctuated but then recovered after 2016. Agricultural land peaked in 2020 but collapsed after it up to 69% by 2024, indicating potential degradation. Mangroves declined by 55% after 2017, while bare land expanded after 2022. NDVI and FVC trends aligned with the land cover changes, with higher values in the northern densely vegetated areas, and lower values in the urban and bare lands of the country. FVC acted as an early warning system and detected pre-deforestation stress that caused forest loss in 2015. The integration of FVC and NDVI acts as a strong framework for tropical land systems monitoring. The findings provide practical guidance for coastal conservation, agricultural restoration, and sustainable urban planning in Mozambique and contribute to SDGs for zero hunger, sustainable cities, and life on Land.
Klebsiella species pose a significant public health concern due to their association with various infections and the rising levels of antibiotic resistance. This study examined the antibiotic resistance profiles of nine Klebsiella species obtained from the culture collection at North-West University’s Potchefstroom campus in South Africa using whole genome sequencing. The average nucleotide identity (ANI), plasmid types, and the identification of antibiotic resistance and virulence genes were performed on Klebsiella species. The nine sequenced Klebsiella spp. isolates were identified as K. pneumoniae (n = 2) originated from sheep faeces, K. variicola (n = 2) and K. michiganensis (n = 5) isolated from water (river stream). The genomes of K. variicola and K. michiganensis contained antibiotic resistance genes for fosfomycin (fosA), nalidixic acid (oqxAB), and β-lactamase (blaLEN24/16 or blaOXY-1-3), aminoglycoside (aph(3’)-Ia_5), efflux pump [mdf(A)] and tetracycline [tet(34)]. Furthermore, K. michiganensis strains harboured the aminoglycoside aph(3’)-Ia gene. K. pneumoniae strains KPT2 and KPT4 contained a plasmid AB595 that encodes for tetracycline (tetA), sulphonamide (sul), and aminoglycoside (aph(3’)-Ia). Core virulence genes encoding siderophores (ent, fep, iutA), adhesins (fim, ecp), and quorum sensing (luxS) were present across Klebsiella spp. isolates. Additional flagellar-related genes, including those for motor assembly (fliE, fliF, fliG, fliH, fliI, and fliJ) and motility (motA and motB), were exclusive in the K. pneumoniae strain KPT4, highlighting their crucial role in biofilm formation and survival under antibiotic stress. The identification of ARGs, including blaSHV-194, fosA6, oqxAB, and tet(A), in K. pneumoniae isolates from sheep further highlights the circulation of antimicrobial resistance determinants in low-resource settings, where surveillance is limited and exposure to untreated animal waste is prevalent. This study provides genomic evidence that rural agricultural environments serve as underappreciated multidrug-resistant and potentially virulent Klebsiella species reservoirs and underscore the need for integrated One Health surveillance in low-resource farming communities.
Changes in land use over space and time are key drivers of water pollution. However, current studies on landuse-water-quality relationships in small watersheds are insufficient to support regional development. Comparative research across large-scale watersheds can better inform water environmental protection, yet such studies remain limited. This study analyzes data from 100 sampling sites across four major watersheds in Zhejiang Province. Using multivariate statistical methods and redundancy analysis, it investigates the effects of land use patterns on water quality across seasons and spatial scales. Results reveal pronounced spatial and temporal heterogeneity among watersheds. In the Qiantang River Basin, pH remains relatively stable, while other indicators vary considerably. Reduced downstream flow, particularly during the dry season, promotes the accumulation of pollutants. During the wet season, water quality in the Feiyun and Ou River Basins is more strongly influenced by geogenic processes related to land use. The Feiyun River Basin, dominated by forests and grasslands, is susceptible to rainfall-induced erosion. In the Ou River Basin, land reclamation alters hydrodynamics and salinity, and precipitation intensification further intensifies land-use impacts. At the spatial scale, the 2000m buffer exerts the strongest influence on water quality in the Feiyun, Ou, Yong, and Jiao River Basins, likely due to longer runoff pathways integrating multiple pollution sources. In contrast, in the Qiantang River Basin, the 500-m buffer is more influential during the dry season, while larger buffers dominate in the wet season. Overall, this study provides a scientific basis for watershed-specific land-use planning and water-quality protection, emphasizing policies tailored to distinct spatiotemporal dynamics.
This paper examines the use of project-based learning (PBL) as a pedagogical foundation for communication design education, focusing on its role in enhancing creativity, collaboration, and the practical application of knowledge. The study draws on a review of literature on PBL and qualitative narrative self-reflections completed by 16 second-year communication design students. Insights were generated from individual and group project experiences, highlighting peer interaction and the extent to which PBL simulates real-world professional dynamics. The findings indicate that engaging students with real-world projects prepares them for the complexities of professional practice and supports the development of adaptable and collaborative design competencies. While PBL offers significant pedagogical value, challenges such as time constraints and difficulties in assessment were noted. The paper recommends clear assessment criteria, flexible project timelines, and continuous instructional support to enhance the effectiveness of PBL implementation. The study confirms that PBL is an important approach for bridging the gap between academic learning and industry expectations in communication design. The continued adoption of PBL can significantly strengthen students’ readiness for professional practice. This study enriches scholarship on experiential and design-based learning by positioning PBL as a transformative, industry-aligned framework for communication design education. It extends understanding of how structured, real-world projects foster creativity, adaptability, and lifelong learning in design disciplines.
In arid environments, shallow hypersaline lakes are critical to regional ecological stability. However, accurately monitoring suspended particulate matter (SPM) in these waters remains challenging for conventional optical remote sensing. The primary obstacles include signal saturation during high-turbidity events, interference from bottom reflectance in shallow zones, and insufficient satellite revisit frequency. To address these limitations, we developed a physics-informed machine learning (PIML) framework to isolate the hydrodynamic drivers of SPM in Ebinur Lake. Unlike purely data-driven approaches, we constructed a feature space grounded in wave mechanics, incorporating variables such as bottom shear stress, effective fetch, and temporal memory into a Random Forest regressor. Crucially, we employed physically downscaled ERA5 instantaneous wind gusts to capture the nonlinear threshold behavior of sediment entrainment. The model demonstrated robust performance, achieving a five-fold cross-validated R-2 of 0.91 (RMSE = 81.14 mg/L; RRMSE = 32.3%) while overcoming optical saturation issues. Feature attribution analysis identified instantaneous wind gusts as the dominant factor (>90% importance), significantly outperforming mean wind speed. We further quantified a critical physical threshold of similar to 12.0 m/s, confirming that sediment resuspension is an energy-limited process triggered by extreme wind events. Additionally, the model functioned as a "virtual geostationary sensor," successfully reconstructing hourly SPM dynamics typically missed by polar-orbiting satellites. This study presents a transferable and physically interpretable paradigm for high-frequency water quality monitoring in data-scarce inland lakes.
