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Development of a platform for rational diagnostic design using a venom-antibody model
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Oxidative ammonolysis of technical lignins and lignites
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Characterisation of material properties and behaviour of cold bituminous mixtures for road pavements
Published 2008Get full text
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Characterising the potential health risks associated with coal dust
Published 2023“…This model was chosen for its ability to relate response and explanatory variables based on a new set of variables which have undergone dimensionality reduction whilst maximising the covariance. …”
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The impact of socioeconomic factors on municipal fiscal health in South Africa
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Species occupancy, distribution and abundance : indigenous and alien invasive vascular plants on sub-Antarctic Marion Island
Published 2012Get full text
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The application of the homogenisation method to the numerical modelling of cancellous bone
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Strategic selection of communication channels during organisational change
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Antigenic site determination on a SAT2 foot-and-mouth disease virus using a chicken antibody phage display library
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Interactive narrative generation using computational verb theory
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Socioeconomic inequities of malaria prevalence in under-five children in Ghana between 2016 and 2019
Published 2025“…The 2016 and 2019 Ghana malaria indicator survey datasets were analysed using Stata 15. The outcome variable was malaria prevalence in under-five children, explanatory variables included socio-economic status (household wealth), age of child, mother's education, place of stay, region and a few others. …”
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Distribution theory and inference for bivariate extremes
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The reliability of weight optimised steel portal frames
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Investigating distressed venture decision-making during turnarounds
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An exploration of sociodemographic and psychosocial determinants of cognitive performance in a peri-urban clinic population of people with HIV in Cape Town, South Africa
Published 2023“…These non-HIV factors include sociodemographic variables (e.g., age, sex, educational attainment), psychosocial variables (e.g., socioeconomic status, food security, quality of life), psychiatric variables (e.g., depression, problematic alcohol use), and other medical co-morbidities. …”
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