Browsing Faculty of Natural Sciences by Title
Now showing items 1844-1863 of 2571
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The potential of leucosidea sericea against propionibacterium acnes
(Elsevier, 2014)The present study reports on the potential of Leucosidea sericea addressing acne vulgaris. Four known compounds namely phytol acetate, triacontanol, phytol and alpha kosin and one new compound namely, (E)-3,7,11,15-tetra ... -
Potential of resampled multispectral of data for detecting desmodium-brachiaria intercropped with maize in a push-pull system
(ISPRS, 2020)Poor crop yields remain one of the main causes of chronic food insecurity in Africa. This is largely caused by insect pests, weeds, unfavourable climatic conditions and degraded soils. Weed and pest control, based on the ... -
Potential of resampled multispectral data for detecting desmodium-brachiaria intercropped with maize in a 'push-pull' system
(ProQuest, 2020)Poor crop yields remain one of the main causes of chronic food insecurity in Africa. This is largely caused by insect pests, weeds, unfavourable climatic conditions and degraded soils. Weed and pest control, based on the ... -
Powder characteristics blending and microstructural analysis of a hot-pack rolled vacuum arc-melted gamma-tial-based sheet
(The Southern African Institute for Industrial Engineering, 2022)In the quest for cost-effective fabrication processes capable of producing sound γ-TiAl products, the microstructure and mechanical properties of a modified second-generation hot-rolled γ-TiAl-based alloy with nominal ... -
PR-1-Like Protein as a Potential Target for the Identification of Fusarium oxysporum: An In Silico Approach
(BioTech, 2021-07)Fusarium oxysporum remains one of the leading causes of economic losses and poor crop yields; its detection is strained due to its presentation in various morphological and physiological forms. This research work sought ... -
Practical galaxy morphology tools from deep supervised representation learning
(Oxford University Press, 2022)Astronomers have typically set out to solve supervised machine learning problems by creating their own representations from scratch. We show that deep learning models trained to answer every Galaxy Zoo DECaLS question ... -
Pre-race screening and stratification predicts adverse events—A 4-year study in 29585 ultra-marathon entrants, SAFER X
(Wiley-Blackwell, 2020)Pre-race screening and risk stratification in recreational endurance runners may predict adverse events (AEs) during a race. Aim: To determine if pre-race screening and risk stratification predict AEs during a race. Methods: ... -
Pre-race self-reported medical conditions and allergies in 133 641 Comrades ultramarathon (90km) runners - SAFER XXIII
(The Physician and Sportsmedicine, 2023)Objectives: To determine the prevalence of self-reported pre-race chronic medical conditions and allergies in ultramarathon race entrants and to explore if these are associated with an Increased risk of race-day medical ... -
Preceptor reflections on the Community Health clinical rotation for fourth year pharmacy students at the University of the Western Cape
(2019)This paper describes the community health clinic rotation of the Patient Care Experience programme (PaCE) offered to fourth year pharmacy students (2018) at the University of the Western Cape. Reflections from the collective ... -
Predicting amplification of mycn using cpg methylation biomarkers in neuroblastoma
(Future Science Group, 2021)Neuroblastoma is the most common extracranial solid tumor in childhood. Amplification of MYCN in neuroblastoma is a predictor of poor prognosis. Materials and methods: DNA methylation data from the TARGET data matrix were ... -
Predicting coronary artery disease risk in firefighters – a cross-sectional study
(2021-07-30)Background: Firefighters are placed under severe cardiovascular load in performing active duty and, when carrying various coronary artery disease (CAD) risk factors, firefighters are predisposed to significant morbidity ... -
Predicting gamma-ray burster redshifts from their prompt emission properties
(Oxford University Press, 2010)This paper presents a study of the relation between gamma-ray burster redshift and several of its prompt emission properties (spectral lag, light curve variability, peak energy, rise time and the peak bolometric flux ... -
Predicting haplogroups using a versatile machine learning program (PredYMaLe) on a new mutationally balanced 32 Y-STR multiplex (CombYplex): Unlocking the full potential of the human STR mutation rate spectrum to estimate forensic parameters
(Elsevier, 2020)We developed a new mutationally well-balanced 32 Y-STR multiplex (CombYplex) together with a machine learning (ML) program PredYMaLe to assess the impact of STR mutability on haplogourp prediction, while respecting forensic ... -
Predicting Shifts in the geographical distribution of two estuarine plant species from the subtropical and temperate regions of South Africa
(Springer, 2019-11-21)Climate suitability maps are useful to determine changes in the distribution of species. The aim of this study was to predict the future distribution of two estuarine species (Bassia diffusa and Hibiscus tiliaceus) from ... -
Predicting the neutral hydrogen content of galaxies from optical data using machine learning
(Oxford University Press, 2018)We develop a machine learning-based framework to predict the Hi content of galaxies using more straightforwardly observable quantities such as optical photometry and environmental parameters. We train the algorithm on z ... -
Prediction of human-Bacillus anthracis protein–protein interactions using multi-layer neural network
(Oxford University Press, 2018)Triplet amino acids have successfully been included in feature selection to predict human-HPV protein-protein interactions (PPI). The utility of supervised learning methods is curtailed due to experimental data not being ... -
Prediction of Wetland Hydrogeomorphic Type Using Morphometrics and Landscape Characteristics
(Frontiers Media S.A., 2021)Accurate spatial maps of wetlands are critical for regional conservation and rehabilitation assessments, yet this often remains an elusive target. Such maps ideally provide information on wetland occurrence and extent, ... -
Predictive classifier models built from natural products with antimalarial bioactivity using machine learning approach
(Public Library of Science, 2018)In view of the vast number of natural products with potential antiplasmodial bioactivity and cost of conducting antiplasmodial bioactivity assays, it may be judicious to learn from previous antiplasmodial bioassays and ... -
Predictors of multiple injuries in individual distance runners: A retrospective study of 75,401 entrants in 4 annual races- safer xxx
(Elsevier, 2022)There are limited data on factors that predict an increased risk of multiple injuries among distance runners. The objective of this study was to determine risk factors that are predictive of individual runners with a high ... -
Predominant atmospheric and oceanic patterns during coastal marine heatwaves
(Frontiers Media, 2017)As the mean temperatures of the worlds oceans increase, it is predicted that marine heatwaves (MHWs) will occur more frequently and with increased severity. However, it has been shown that variables other than increases ...