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Characterisation of functional properties of Envelopes of highly neutralisation resistant HIV-1 isolates
Published 2019“…Based on our findings, it is clear that reduced entry efficiency does not explain why highly resistant viruses are not more common. …”
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Factors that influence mathematics teachers' use of dynamic software for instruction
Published 2015Get full text
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Measurement invariance of the PCQ-24 over ethnic groups in South Africa
Published 2021Get full text
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Climatic impact on agricultural outputs in Nigeria
Published 2019-11ArticleFull Text AvailableAccess Repository -
An analysis of vegetation pattern and its relationship to NDVI data in the Namaqualand area, South Africa
Published 2017“…A multiple regression model explained 52% of the variance when Mean Annual NDVI was related to climatic variables. …”
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Characterising the potential health risks associated with coal dust
Published 2023“…Elements which explained the variability within the sample characteristics and the responses were clustered using the k-means algorithm to determine classes of samples which display similar characteristics or levels of toxicity. …”
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Environmental and biogeographic influences on the distribution and composition of the southern Cape forests (Veld type 4)
Published 2017“…This study aims at explaining the distribution and composition of the southern Cape forests, the largest forest complex in southern Africa. …”
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Predicting teachers' assessment effectiveness in mathematics-related subjects using bandura five-factor self-efficacy and demographic factors
Published 2011-06ArticleFull Text AvailableAccess Repository -
The maintenance of Body Fluid Homestasis during exercise when drinking ad Libitum
Published 2014“…We have suggested that this can be explained by both behavioural and physiological reasons. …”
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The size and composition of the South African middle class : implications for a consolidating democracy
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Aeolian dust emission dynamics across spatial scales: landforms, controls and characteristics
Published 2018“…A Boosted Regression Tree (BRT) machine-learning algorithm identified the most important surface and sediment characteristics determining dust emission from the measured surfaces. The model explained 70.8% of the deviance in the measured dust flux with the top predictor variables and their relative importance (%) as follows: gravel cover, 16%; moisture content, 14%; kurtosis, 13%; very coarse silt, 13%; very fine sand, 11%; fine sand, 8%; compressive strength, 7%, calcium, 7% and magnesium, 6%. …”
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Testing alternative stable state theory at Afromontane and Milkwood forest-fynbos ecotones
Published 2024“…ASS theory is more suited for explaining ecosystems that exist within the same abiotic conditions. …”
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Continuous flow microwave sterilisation focussing on aqueous media
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Design optimisation of cageless flux barrier rotor reluctance synchronous machine
Published 2012Get full text
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Routing in packet switched computer communication networks
Published 2023“…The important design variables that a network planner is faced with in the design of these networks are discussed. …”
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