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Nosipho Mthethwa
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Broadband mapping is when the deployment, coverage and quality of broadband are collected and presented for a geographical area.
Broadband mapping is used in several countries to monitor and fast track broadband deployment to ensure internet connectivity for citizens. Literature review has revealed that many European countries have already implemented broadband infrastructure mapping and broadband services mapping.
Studies on broadband mapping show that there are four different types of broadband mapping, namely: broadband infrastructure mapping, broadband service mapping, broadband demand mapping and broadband investment and funding mapping.
Thembela Xaba
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Aflatoxin contamination is a threat to human and animal health and also affects the economic status of a country. Despite the threat it poses to humans, animals and the economy, it continues to be a worldwide problem without proper mitigation strategies and solutions. Aflatoxins contaminate a wide range of agricultural produce, even with control measures in place.
Therefore, researchers continue to investigate the ability, applicability and safety of aflatoxin degrading microorganisms that are promising as microbial degradation and can offer degradation under mild conditions, limiting aesthetic and nutritional value of food.
Vivey Phasha
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The CSIR Advanced Agriculture and Food cluster, together with the University of KwaZulu-Natal through bioprospecting research, have identified an active ingredient from the cultures of Aspergillus Flavus that has potent tyrosinase inhibition activity, which was developed to address skin hyperpigmentation. Kojic Acid, an active ingredient, was produced via fungal fermentation, then modified to increase its stability, safety and efficacy.
The CSIR optimised the production of Kojic Acid and thereafter synthesised a stable derivative. The Kojic Acid and its derivative were assessed for safety and efficiency. A serum formulation incorporating the derivative was then produced and evaluated for skin irritancy and stability. The results showed that it is stable and safe for use on humans.
This anti-pigmentation product technology has a competitive advantage over existing products on the market since it is safe for use and has scientific data proving its efficacy. This has a huge potential for application in the cosmetic industry.
Tina Chunga
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African ginger is an indigenous plant species that grows in the wild and is mostly used by traditional healers to treat asthma. Due to there being a large number of people suffering from asthma, the plant has been over harvested and is now extinct.
The CSIR has identified African ginger cultivation sites in Mpumalanga. To support the use of African ginger in the treatment of asthma, our study compares the African ginger that grows on cultivated land to the one that grows in the wild.
Dr Advaita Singh
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The fight against human immunodeficiency virus (HIV) and acquired immunodeficiency syndrome (AIDS), which emerged 40 years ago, has resulted in many parts of the world reflecting on some of the key milestones achieved and the challenges that still remain.
The CAP256 lineage was originally isolated by the Centre for the AIDS Programme of Research in South Africa (CAPRISA) and the National Institute for Communicable Diseases (NICD) from a South African HIV positive patient during a trial conducted by CAPRISA. The outcome showed that the antibodies from the CAP256 lineage displayed broad specificity and were extremely potent against many HIV-1 subtype A and C strains. A scalable plant-based production process has been developed to produced highly potent anti-HIV antibodies, CAP256-VRC26.08 and CAP256-VRC26.09, for therapeutic use.
The production process demonstrated the ability to use glycoengineered Nicotiana benthamiana, a relative of the tobacco plant, to produce unique glycosylation and rare sulfation post-translational modifications, a result that is not usually seen in plants. This research is ultimately aimed towards developing a cost-effective pre-exposure prophylaxis vaccine, which will passively immunise against HIV/AIDS.
Stefan Karamanski
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Legged robots need to be tested before deployment. Physics engines are typically used for this, but current physics engines do not handle the impulsive nature of legged robotics correctly. This research aims to solve this problem by developing a trajectory optimised physics engine.
Ndumiso Ndlovu
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This project is based on process and product development and in vitro immune-modulatory effects of a standardised multi-plant based solid-liquid extract. Three methods were used for batch-to-batch water extraction, namely: high temperature maceration, soxhlet and reflux extraction. The recovered liquid extract was subjected to downstream processing technology by freeze-drying, spray drying and distillation for powder isolation.
Kanyane Bridgett Malatji
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HIV and Mycobacterium TB cause increased mortality among TB and HIV patients. The diagnosis of HIV and TB is currently done separately and as a result, treatment is delayed, particularly for TB since diagnosis has a long turnaround time. Thus, the project aims to develop a point-of-care assay for multiplex diagnosis of TB and HIV-1 co-infection in human blood using markers for active TB and HIV infection.
Lerato Maboko
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Alzheimer's disease, which is characterised by reduced cholinergic functioning, is generally treated by acetylcholinesterase inhibitors such as donepezil. Although treatment exists, it remains symptomatic and subject to unfavorable adverse effects. Drug discovery is rife with ineffective, cytotoxic, and/or pharmacokinetically unfeasible pharmacophores. The purpose of this study is to assess novel pharmacophores’ in vitro acetylcholinesterase inhibitory, blood-brain barrier permeability and cytotoxic potential.
Keletso Mabel Monareng
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With unprecedented amounts of material data generated from experiments and high-throughput density functional theory, machine learning provides the ability to accelerate the discovery and design of new materials. In this work data-driven density functional theory (DFT), data is employed to develop machine learning models that can predict the densities of sodium-ion battery (SIB) cathode materials. Different machine learning models were successfully developed and validated, using SIB materials’ properties calculated from DFT as input dataset and elemental properties of their constituents. The following models Bayesian ridge, gradient boosting regressor, light gradient boosting machine, extra trees regressor, random forest and orthogonal matching pursuit were developed and evaluated. Extra trees regressor was found to be the best model in predicting density with accuracy measures of 0.95 and 0.09, for coefficient of determination and mean square error, respectively. Thus, the features used have predictive capability with a high accuracy.
