Faculty of Science (ETDs)
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Item Towards Lifelong Reinforcement Learning through Temporal Logics and Zero-Shot Composition(2024-10) Tasse, Geraud Nangue; Rosman, Benjamin; James, StevenThis thesis addresses the fundamental challenge of creating agents capable of solving a wide range of tasks in their environments, akin to human capabilities. For such agents to be truly useful and be capable of assisting humans in our day-to-day lives, we identify three key abilities that general purpose agents should have: Flexibility, Instructability, and Reliability (FIRe). Flexibility refers to the ability of agents to adapt to various tasks with minimal learning; instructability involves the capacity for agents to understand and execute task specifications provided by humans in a comprehensible manner; and reliability entails agents’ ability to solve tasks safely and effectively with theoretical guarantees on their behavior. To build such agents, reinforcement learning (RL) is the framework of choice given that it is the only one that models the agent-environment interaction. It is also particularly promising since it has shown remarkable success in recent years in various domains—including gaming, scientific research, and robotic control. However, prevailing RL methods often fall short of the FIRe desiderata. They typically exhibit poor sample efficiency, demanding millions of environment interactions to learn optimal behaviors. Task specification relies heavily on hand-designed reward functions, posing challenges for non-experts in defining tasks. Moreover, these methods tend to specialize in single tasks, lacking guarantees on the broader adaptability and behavior robustness desired for lifelong agents that need solve multiple tasks. Clearly, the regular RL framework is not enough, and does not capture important aspects of what makes humans so general—such as the use of language to specify and understand tasks. To address these shortcomings, we propose a principled framework for the logical composition of arbitrary tasks in an environment, and introduce a novel knowledge representation called World Value Functions (WVFs) that will enable agents to solve arbitrary tasks specified using language. The use of logical composition is inspired by the fact that all formal languages are built upon the rules of propositional logics. Hence, if we want agents that understand tasks specified in any formal language, we must define what it means to apply the usual logic operators (conjunction, disjunction, and negation) over tasks. The introduction of WVFs is inspired by the fact that humans seem to always seek general knowledge about how to achieve a variety of goals in their environment, irrespective of the specific task they are learning. Our main contributions include: (i) Instructable agents: We formalize the logical composition of arbitrary tasks in potentially stochastic environments, and ensure that task compositions lead to rewards minimising undesired behaviors. (ii) Flexible agents: We introduce WVFs as a new objective for RL agents, enabling them to solve a variety of tasks in their environment. Additionally, we demonstrate zero-shot skill composition and lifelong sample efficiency. (iii) Reliable agents: We develop methods for agents to understand and execute both natural and formal language instructions, ensuring correctness and safety in task execution, particularly in real-world scenarios. By addressing these challenges, our framework represents a significant step towards achieving the FIRe desiderata in AI agents, thereby enhancing their utility and safety in a lifelong learning setting like the real world.Item Mapping and monitoring the impacts of climate variability on rainfed agriculture in Semi-arid North Darfur, Sudan(University of the Witwatersrand, Johannesburg, 2024-02) Altoom, Mohammed Bashar Adam; Adam, ElhadiRainfed agriculture is vital to food security and income in most parts of the world. However, one-third of the population of developing countries population lives in the less favoured rainfed agricultural regions. Around 75-82% of the total cropland areas in the world are under rainfed agriculture and produce more than 60% of the globe’s cereal grains. However, rainfed agriculture is most prominent in some regions of Africa, such as Sub-Saharan Africa, where more than 95% of the cropland is rainfed. This crucial agriculture sector usually depends on the physical environment and, most importantly, the variability and distribution of rainfall. Therefore, rainfed farming is vulnerable to climate-related hazards, and the crop yield is unreliable and difficult to predict. For instance, the spatio-temporal variability of precipitation extreme events often subjects crops to short-term water deficits, causing crop losses. Sudan heavily depends on rainfed agriculture—about 90% of arable land dominates rainfed cultivation, contributing one-third of the country’s gross domestic product (GDP). Rainfed agriculture is the primary source of livelihood for 65% of the population. Unfortunately, agriculture in North Darfur of the west Sudan is characterised by environmental hazards, e.g., frequent droughts and unpredictable low, poorly distributed, and highly variable monthly/seasonal rainfall. Therefore, using various Earth observation data, this study aimed to monitor the impacts of rainfall variability on rainfed agriculture in North Darfur State in Sudan. Firstly, the study aimed to determine the feasibility of estimating rainfall variability across North Darfur State at daily, monthly and annual timescales using six satellite precipitation products (SPPs), i.e., the Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA), African Rainfall Climatology (ARC), and Climate Hazards Group Infrared Precipitation with Station Data (CHIRPS) were evaluated using four categorical indices, i.e., probability of detection (POD), probability of false alarm (POFA), bias in detection (BID) and Heidke skill score (HSS), and four continuous indices, i.e., Pearson correlation coefficient (r), root mean square error (RMSE), per cent bias (Pbias), and Nash-Sutcliffe model efficiency coefficient (NSE) against ground rain-gauge observations. The other SPPs were Integrated Multi-satellitE Retrievals for Global Precipitation Measurements (GPM) Final Run (GPMIMERG), Precipitation Estimation from Remote Sensing Information using Artificial Neural Networks-Climate Data Record (PERSIANN-CDR), and the Tropical Applications of Meteorology using SATellite and ground-based observations (TAMSAT). Results of the statistical analysis demonstrated that 1) at the daily timescale, the SPPs underestimate daily rainfall by 6.53–17.61%, and CHIRPS was the best for detecting rainy days, while PERSIANN-CDR performed poorly; 2) monthly and annual scales performed better than daily timescale, and TAMSAT and CHIRPS portrayed better performance than the ther SPPs. Secondly, the study assessed the capability of optical Earth Observation Data (EOD), i.e., Sentinel-2 multispectral dataset, to map crop types in the heterogeneous semi-arid environment of North Darfur using machine learning classifiers in Google Earth Engine (GEE) platform. Five datasets were compared against random forest (RF) and support vector machine (SVM) classification algorithms: (1) 10 Sentinel-2 bands (comprising visible, near-infrared and shortwave infrared bands), (2) Sentinel-2 (10 bands) + 8 vegetation indices, (3) visible bands and near-infrared bands only, (4) visible and shortwave infrared bands only, and (5) 8 vegetation indices. The eight vegetation indices were normalised difference vegetation index (NDVI), enhanced vegetation index (EVI), soil-adjusted vegetation index (SAVI), green normalised difference vegetation index (GNDVI, weighted difference vegetation index (WDVI), red edge NDVI (NDVIre), ratio-vegetation index (RVI) and normalised difference infrared index (NDII). Results showed that the RF algorithm produced the highest classification overall accuracy (OA), i.e., 97% and Kappa coefficient (κ), 0.96, using 10 Sentinel-2 bands dataset. Producer’s (PA) and user’s accuracies (UA) were in the range of 40-97% and 40-100%, respectively. Thirdly, the spatiotemporal trend of drought events and their impact on millet production in North Darfur from 1981 to 2020 was analyzed using standardized precipitation index (SPI) and reconnaissance drought index (RDI) by employing different timescales, i.e., 3- month (June-August), 6-month (June-November), and 9-month (June-February) timescales. Drought-yield relationships were assessed using Pearson correlation coefficients (r). Results indicated that RDI is more sensitive to rainfall variabilities than SPI in detecting drought trends. Results revealed that drought events affected North Darfur over broad spatial extents, particularly in 1989, 1990, 1992, 1999, and 2001—an extreme drought event was in 2003. Correlation analysis between the SPI and RDI and the standardized variable of crop yield (SVCY) for millet grain yield showed a strong agreement between them. Moderate to extreme reductions in millet crop yield occurred in 1992, 1999, 2001, and 2003, corresponding to the moderate to extreme drought indicated by RDI. Severe crop losses were in Kabkabiya and Umm Kadadda. Fourthly, this study aimed to map and monitor spatio-temporal dynamics of rainfed agriculture in North Darfur State from 1984 to 2019 using multitemporal Landsat observation data using random forest (RF) classification algorithm. Overall, Landsat Operational Landsat Imageries (OLI) outperformed Landsat Multispectral Scanner (MSS), Landsat Thematic Mapper (TM), Landsat Enhanced Thematic Mapper Plus (ETM+) in monitoring change in agricultural land and other land use land cover (LULC) classes. Overall accuracies ranged between 94.7% and 96.9%, while kappa statistics were greater than 0.90. Results showed that Goz land used for rainfed agriculture increased by 889,622.46 ha between 1994 and 999, while it decreased by 658,568.61 ha between 2004 and 2009. Rainfed cultivation of wadi lands expanded significantly by 580,515.03 ha over the 2014–2019 period and decreased by 182,701.8 ha over the 1994–1999 period. Overall, this study enhances the understanding of spatio-temporal rainfall patterns and current drought trends, aiding in developing more effective policies and resource management strategies. Additionally, it offers crucial spatial data that is currently scarce due to ongoing conflicts, empowering decision-makers to establish sustainable land use monitoring systems. The methodologies used in this study have proved successful in mapping crop types in a fragmented highly heterogeneous fine agricultural semi-arid landscape; such mapping approaches can be applied in other environments with similar characteristics.Item Evaluation of radiation damage on lutetium-aluminium and gold for practical applications using proton irradiation as a surrogate for neutrons(University of the Witwatersrand, Johannesburg, 2024-10) Temaugee, Samuel Terungwa; Mavunda, Risimati D.; Usman, Iyabo T.An understanding of the interaction of energetic radiations from particles such as protons, neutrons, and photons, with the microstructure of materials is crucial for predicting their bulk morphological response in extreme radiation environments. Exposure to these radiation species could lead to changes in the microstructural properties that, in turn, affect the mechanical and physical properties of the macroscopic matter. This thesis investigated the resilience of materials, specifically Au and Lu-Al, to radiation damage, employing computational simulation methods and experimental techniques. The study aims to provide critical insights into the radiation damage sturdiness of Au and Lu-Al, considering their application in reactor technology and other extreme radiation environments. Monte Carlo-based methods were employed to calculate radiation damage in the samples resulting from neutron and proton irradiation, utilizing MCNP6.2 and SRIM-2013, respectively. The objective was to compare ion beam irradiation with neutrons with a view to utilizing proton irradiation as a surrogate for neutron irradiation. Three different state-of-the-art characterization techniques—X-ray diffraction (XRD), High-Resolution Transmission Electron Microscopy (HRTEM), and Flash Differential Calorimetry(F-DSC)—were employed to evaluate damage in the materials before and after proton irradiation using the CLASS Accelerator at MIT, USA. The results of the study indicated that protons within the energy range 0.1 to 1.0 MeV produced similar types of damage in the materials as would neutrons (spectrum 0< E≤20 MeV at SAFARI reactor), suggesting protons as an alternative to neutron irradiation. Defect characterization in the materials using XRD and HRTEM techniques revealed dislocation loops and lines in both Lu-Al and Au, as well as Stacking Faults Tetrahedra (SFT) in the Au material. These defects with proton irradiation were similar to those observed with neutron irradiation in Au and other aluminum alloys. The estimated defect number density ranged from 0.7 to 4.8 × 1014 m−2, showing an increase with rising displacements per atom (dpa) or proton fluence post-irradiation. Lu-Al exhibited higher defect density values than Au, consistent with Monte Carlo simulations. Furthermore, results from the Flash DSC technique revealed significant changes in the characteristics of the power-temperature profiles (melting curves) of Lu-Al as dpa increased, offering insights into radiation-induced processes such as phase transition and precipitate stability at specific defect annealing temperatures. These findings are crucial for radiation damage studies for the binary alloy and warrant further investigation. The observed microstructural defect densities were relatively high, and prolonged exposure of the materials to higher doses could lead to further changes in microstructural properties, consequently influencing the physical and mechanical properties of the macroscopic material.Item Physical property studies, tunnel numerical simulations and in-mine seismic experiments to image the gold orebody at South Deep Gold Mine(University of the Witwatersrand, Johannesburg, 2024-09) Mulanduli, Omphulusa; Manzi, MusaThe investigation endeavors to assess the physical characteristics of deep borehole cores within the Upper Elsburg Reefs (UER) of the South Deep gold mine of the West Rand goldfield. Specifically, these cores are sourced from three boreholes situated approximately 2.6 km beneath the surface within the confines of the South Deep gold mine. The focal point of this study lies in non-destructive testing methods aimed at elucidating the intrinsic attributes of these rocks, with particular attention directed towards seismic velocities and densities. These measurements hold paramount importance in conducting numerical simulations to designing the in-mine (or tunnel) seismic reflection surveys acquired at South Deep gold mine, as part of the ERA-Min3 FUTURE (Fiber-optic sensing and UAV-platform techniques for innovative mineral exploration) project. Cultivating a profound comprehension of the seismic velocities and densities across diverse rock formations can significantly augment the interpretation of seismic reflections, thereby facilitating more refined assessments of subsurface geology and structural configurations. In pursuit of this goal, our study endeavors to delve into the fundamental acoustic properties of the gold-rich UER, with the overarching aim of deepening our understanding of its seismic reflectivity. To realize this objective, a comprehensive array of physical measurements, encompassing ultrasonic velocities and bulk densities, were conducted on drill-core specimens. To accurately portray the physical attributes of the lithological units under scrutiny, a total of twenty-four samples were subjected to exhaustive analysis for density and seismic velocity utilizing a spectrum of methodologies. Density determinations were procured through a diverse set of techniques, including dimensional assessments, employment of the KT20 MagSus tool, and utilization of the SNOWREX AHW-3 Professional Weighing Scale boasting a heightened sensitivity of 0.01 g. Ultrasonic measurements were undertaken employing the Proceq Pundit PL 2000 ultrasonic pulser velocity tester, equipped with two pairs of transducers boasting a center frequency of 54 kHz. The in-mine seismic survey was acquired to delineate geological structures that crosscut and displace the orebody. The study locale encompasses three distinct rock formations: the UER, gold-bearing conglomerate units (termed reefs), basaltic lava, and dyke specimens. The UER primarily comprises quartzites, exhibiting a P-wave velocity range of 5202-5802 m/s, an S-wave range of 3037-4768 m/s, and bulk densities spanning from 2.66 - 2.71 g/cm³. Conglomerate reefs exhibit a P-wave velocity range of 4467-5970 m/s, an S-wave range of 4040-4854 m/s, and bulk densities ranging from 2.67-2.94 g/cm³. Lava samples extracted from the boreholes showcase a P-wave velocity range of 5916 - 6711 m/s, an S-wave range of 3275-5659 m/s, and bulk densities spanning from 2.75-2.90 g/cm³. Singular dyke samples were encountered, exhibiting a P-wave velocity of 5921.5 m/s, an S-wave velocity of 5385 m/s, and a density of 2.85 g/cm³. The study employed the synth-seis code to simulate 1D seismic responses based on borehole data collected from the mine, aiming to validate findings from velocity and density measurements. Analysis of the seismograms indicated notable contrasts between conglomerates and quartzites, particularly evident in density and S-wave measurements, suggesting potential for improved rock discrimination with alternative seismic sources. Additionally, 2D numerical simulations were conducted to model wave propagation in the Upper Elsburg Reef (UER), revealing discrepancies between simulated and synthetic seismogram results, indicating potential limitations in seismic imaging. Furthermore, ray tracing was used to design a seismic survey inside the mine along the tunnel floor to image VCR (Ventersdorp Contact Reef) orebody and other geological structures. The real seismic survey was finally conducted inside the tunnel (SDT1), demonstrated the value of in-mine reflection seismic surveys for mapping geological structures at significant depths, which would otherwise be costly and logistically challenging. Despite noise interference from mine operations, processing algorithms enabled extraction of reflections and structural mapping from the dataset, underscoring the importance of such surveys in mining exploration and planning.Item Applications of Recurrent Neural Networks in Modeling the COVID-19 Pandemic(University of the Witwatersrand, Johannesburg, 2024-03) Hayashi, Kentaro; Mellado, BruceThis study attempted to introduce moving averages and a feature selection method to the forecasting model, with the aim of improving the fluctuating values and unstable accuracy of the risk index developed by the University of Witwatersrand and iThemba LABS and used by the Gauteng Department of Health. It was confirmed that the introduction of moving averages improved the fluctuation of the values, with the seven-day moving average being the most effective. For feature selection, Correlation-based Feature Selection(CFS), the simplest of the filter methods with low computational complexity, was introduced as it is not possible to spend as much time as possible on daily operations due to providing information timely. The introduction of CFS was found to enable efficient feature selection.Item The perceptions of Moretele residents of small scale agriculture: The case of Ga-Moeka village in the North-West Province(University of the Witwatersrand, Johannesburg, 2024-02) Malivhadza, Takalani; Pillay Gonzalez, SaritaIn South Africa, small-scale agriculture is hindered by various obstacles such as the lack of structural initiatives towards land reform, the dominance of agri-business, and related difficulties of penetrating and flourishing in the market. This research sought to understand perceptions of rural residents of Ga-Moeka (in the North-West province in South Africa) of small-scale agriculture for positive rural development. Small-scale agriculture in rural areas like Ga-Moeka is perceived and practiced as a leisure activity. While the economic potential of small-scale agriculture is recognised, it is not necessarily considered as a primary mechanism to drive positive rural development. Perceptions of small-scale agriculture in the area indicate there is a need to further explore the economic potential of rural areas in a non-binary manner. Additionally, a significant and unexpected finding was the need to also challenge the definition of rural areas and stray away from binary definitions of urban/rural. The findings in this research may support policy makers to assess and put strategies in place that are in alignment with the public’s interest, enhancing their participation in government initiatives and fast-tracking rural development.Item Insight into the genomic architecture of a South African entomopathogenic nematode and its associated bacterial symbiont(University of the Witwatersrand, Johannesburg, 2019) Naidoo, Stephanie; Gray, Vincent M.Nematoda is one of the most prolific and biologically-diverse of all animal phyla, with species adopting lifestyles ranging from free-living to parasitic. Among the diversity of parasitic nematodes lies a specialized group known as entomopathogenic nematodes that features the ability to rapidly kill insect hosts facilitated through a mutualist association with insect pathogenic bacteria. South Africa offers a range of undisturbed habitats that plays host to a great diversity of plant and insect species. Therein lies an opportunity for the recovery of novel entomopathogenic nematode species with a greater tolerance towards local environments and insects, which could potentially be exploited for biological control. In this study, a small-scale survey was conducted in the Gauteng province of South Africa in 2014, which led to the isolation of a new steinernematid, Steinernema sp. HBG28 and its associated bacterial symbiont, Xenorhabdus khoisanae strain MCB. It was found that phase I and phase II variants of X. khoisanae strain MCB featured the ability to swarm on solid agar. This is the first report of swarming behaviour observed in Xenorhabdus bacteria undergoing phenotypic variation. Genomic sequencing was performed on X. khoisanae strain MCB, revealing a genome of 4,6 Mbp in length with 3,869 protein- coding genes, of which, fourteen genes were specifically implicated in flagellar motility. Comparative genomic analyses with other Xenorhabdus spp. indicated the presence of these flagellar motility genes, with the exception of two chemotaxis genes found only in X. khoisanae (cheA and cheY), suggesting that these genes may be necessary in bacterial swarming during phase variation. Additionally, a draft genome assembly of Steinernema sp. HBG28 was produced, which was 97 Mbp in length and consisted of 35,869 predicted protein-coding genes, 1,281 tRNAs and 43 rRNAs. Further genomic characterization of Steinernema sp. HBG28 confirmed its mutual role iii in insect pathogenicity along with its bacterial symbiont. This study was unique as it represented the first genomic characterization of a new Steinernema entomopathogenic nematode species and its associated bacterial symbiont in South Africa. Furthermore, this study paves the way for further research into the biological mechanisms involved in host-parasite and host-symbiont interactions.Item Capability of multi-remote sensing satellite data in detecting and monitoring cyanobacteria and algal blooms in the Vaal dam, South Africa(University of the Witwatersrand, Johannesburg, 2024-03) Obaid, Altayeb Adam Alsafi; Adam, Elhadi M.I.; Ali, Khalid A.Vaal Dam is a large dam in South Africa. It is the primary source of potable water for the metropolitan and industrial areas of Gauteng province and other surrounding areas. The dam's surface area is about 320 km². It’s the second biggest dam in South Africa in terms of surface area, and it drains a catchment area of approximately 38,000 km². The dam's total capacity is about 2.603 × 10⁶ m³ (Haarhoff and Tempelhoff, 2007). The dam catchment area holds various anthropogenic activities, including major agricultural activities, mining, and some industrial activities (Obaid et al., 2023, Du Plessis, 2017), as well as many formal and informal settlements. The dam water is strongly affected by such activities, releasing chemical, physical, and biological contaminants and dissolved urban effluents, most of which enrich the nutrients that reach the dam water in some way. Water resources assessment and monitoring are crucial practices due to their direct contribution to the effective use of such resources. They require precise information about the water quantity and quality. Monitoring of inland water resources has been conducted using in-situ sampling and in-vitro measurement of the water quality constituents. However, these methods have limitations such as high cost, labor-intensive limited spatial and temporal coverage, and time consumption. Over the last few years, remote sensing has been examined for water quality monitoring as a cost- effective system. This research has tested satellite remote sensing to detect some water quality parameters in the Vaal Dam of South Africa. The main objective of this research is to examine the recent generation multispectral satellite sensors, Sentinel-2 MSI, and Landsat-8 OLI data to detect and assess chlorophyll-a and cyanobacteria in the Vaal Dam, South Africa to be used as a cost-effective monitoring tool. To achieve the objective, the research first aimed to understand how the spatial and temporal dynamics of land use, and land cover (LULC) impact algal growth in the dam reservoir. Land use land cover classification was conducted in the catchment area of the Vaal Dam using a pixel-based classification method. Landsat data for the period from 1986 to 2021 were classified using a random forest (RF) classifier in seven-year intervals (1986, 1993, 2000, 2007, 2014, and 2021). Applying the RF classifier revealed that overall classification accuracies (OA) ranged from 87% in the 2014 classified image to 95% in the 2007 image. The change-detection analysis revealed the continuous increase of the settlement class owing to the continuous population growth. A lot of anthropogenic activities associated with population growth have been recognized to release contaminants into the surrounding environment and might end up reaching the water resources causing significant deterioration. As a result, Vaal Dam encounters significant nutrient input from multiple sources within its catchment. This situation raised the frequency of the Harmful Algal Blooms (HABs) within the dam reservoir during recent years. The study also performed a time series analysis for the potential nutrients expected to be the enhancing factors for algal blooms in the Vaal Dam. Using chlorophyll−a (Chl−a) as a proxy of HABs, along with the concentrations of potential nutrients, statistical measures, and water quality data were applied to understand the trend of selected water quality parameters. These parameters were: Chl−a, total phosphorus (TP), nitrate and nitrite nitrogen NO₃NO₂_N), organic nitrogen (KJEL_N), ammonia nitrogen (NH₄_N), dissolved oxygen (DO) and the water temperature. The results reveal that the HAB productivity in the Vaal Dam is influenced by the levels of TP and KJEL_N, which exhibited a significant correlation with Chl−a concentrations. From the Long- term analysis of Chl−a and its driving factors, some very high values of Chl−a concentrations and its driving factors TP and KJEL_N were recorded in erratic individual dates which suggested some nutrients rich in wastes find their way to the dam. Another important notice was that the average Chl-a concentration significantly increased during the period of the study (1986 to 2023) it increased from 4.75 μg/L in the first decade (1990–2000) to 10.51 μg/L in the second decade (2000–2010) and reaching 16.7 μg/L in the last decade (2010–2020). Additionally, Chl−a data extracted from Landsat-8 satellite images was utilized to visualize the spatial distribution of HABs in the reservoir. The satellite data analysis during the last decade revealed that the spatial dynamics of HABs are influenced by the dam’s geometry and the levels of discharge from its two feeding rivers, with higher concentrations observed in meandering areas of the reservoir, and within zones of restricted water circulation. These spatial distribution patterns of HABs are associated with spatial variations of algal species in term of domination through the seasons of the year. The research also examined the utility of remote sensing techniques for mapping algal blooms using the current generation Sentinel-2 and Landsat-8 data. The effectiveness of some band ratio indices in the blue-green and red-near infrared wavelengths was tested. The results suggested that the blue-green band ratio of Landsat-8 [Rrs(560)/Rrs(443)], and red/NIR of Sentinel-2 [Rrs(705)/Rrs(665)] were found to be the best indices for Chl-a retrieval in the Vaal Dam. Results for the Landsat OLI dataset showed R² = 0.89; RMSE = 0.36 μg/L, P < 0.05, and the Sentinel MSI dataset revealed R² = 0.75; RMSE = 0.48 μg/L, P < 0.05 which is a high degree of accuracy. As the potential toxicity comes from the cyanobacterial bloom, the study examines different models to assess and map cyanobacteria concentration in the dam reservoir. Sentinel-2 and in-situ hyperspectral data have been used. None of the Sentinel-2 band ratios showed a significant correlation with the laboratory-measured values of the cyanobacteria. The in-situ measured Hyperspectra showed strong correlations between the band ratios Rrs(705)/Rrs(655) and Rrs(705)/Rrs(620), and the measured cyanobacteria (R² = 0.96 and R² = 0.95 respectively). Chlorophyll−a concentration was retrieved using band ratio indices in the red-NIR region. The strongest correlation was found between the retrieved Chl−a of band ratio Rrs(705)/Rrs(665) and the laboratory-measured Chl−a concentrations for both reflectance datasets. This correlation resulted in an R² value of 0.78 for Sentinel-2 reflectance data and an R² value of 0.93 for in-situ hyperspectral data. A Semi-analytical algorithm for estimating the Chl−a and phycocyanin (PC) pigments has also been examined. The algorithm uses the ratio of the calculated Chl−a absorption at 665 and phycocyanin absorption at 620 nm to their specific absorption coefficients a∗ (655) and a∗ (620) to estimate the concentration of Chl−a and phycocyanin respectively. It resulted in a strong correlation with measured chlorophyll-a, R² = 0.95. The algorithm also strongly correlated with measured cyanobacteria using the absorption to specific absorption ratio at 620 nm (R² = 0.97). However, the estimated values of cyanobacteria using a Semi-analytical algorithm resulted in cyanobacterial concentration values a little bit higher compared to the measured ones, hence, some factors used by the model need to be adjusted to the Vaal Dam site for better estimations. This research revealed that using band ratio indices of Landsat-8 and Sentinel-2 data are valuable tools for mapping chlorophyll-a in the Vaal Dam, a key indicator of phytoplankton biomass. Furthermore, using the semi-analytical algorithm with hyperspectral data is key for estimating the cyanobacteria concentration in the dam water. Models developed in this research will significantly improve near-real-time and long-term chlorophyll-a monitoring of the Vaal Dam. It will effectively help researchers and environmental agencies monitor changes in algal biomass of the dam water to address public health issues related to water quality. It helps to identify areas of high nutrient input and assess the effectiveness of water quality management strategies. It is of prime importance that the developments within the catchment of the Vaal Dam be carefully considered as it is one of the primary sources of dam water. The research recommends implementing the existing regulatory policies for effluent dispersal within the catchment to protect ecosystem functioning and water resources from further deterioration in their quality. It also recommends regular monitoring to detect real-time changes in HABs using satellite remote sensing.Item Studies on the chemistry and biochemistry of gold(III) carboxamide pincer chelates(University of the Witwatersrand, Johannesburg, 2024-06) Razuwika, Rufaro; Nowakowska, Monika; Mathura, adhnaCancer, a group of diseases characterised by the uncontrollable growth of abnormal or mutated cells within an organ, is a global concern. Metallodrugs have emerged as promising solutions to this pandemic, leading to intense research on different metal complexes. In this study, gold(III) carboxamide pincer complexes were evaluated as potential chemotherapeutic agents. The novel NNN-type carboxamide pincer molecules (ligands) effectively stabilising the gold(III) metal centre. The strong σ-donor properties of both the anionic and pyridine N groups further enhanced this stability. Ligands 1a-1f exhibited atropisomerism, a common feature in drug discovery, and containing special heterocycles such as quinolones, indazole, benzophenone, and phenanthroline, which are particularly relevant in drug development. Atropisomerism, however, was lost upon metalation of the ligands. Three complexes, 2d, 2e, and 2f, were successfully synthesised and isolated. Complex 2d was subjected to biochemical property testing and in vitro analysis due to its superior stability and solubility compared to 2e (poor stability) and 2f (poor solubility in the buffer solution used in the study). Speciation studies, combined with computational studies, suggested that 2d exists as a neutral complex under physiological conditions. This inert complex demonstrated stability against the reducing agent glutathione, indicating resilience to reduction under physiological conditions. DNA spectroscopic titration studies revealed that 2d exhibited intensive interaction with ct-DNA, with binding constants Ka1 = 1.48 x109 M-1 and Ka2 = 6.59 x105 M-1. This interaction resulted in a notable increase in the DNA melting point by 4 °C and an enhancement in viscosity in a dose-responsive manner. The DNA titrations, melting point, and viscosity studies suggested a dual binding mode of 2d to ct-DNA, involving base binding with a nearly equal preference for A, T, G, and C bases, and groove binding. Complex 2d exhibited a high affinity towards the transport protein HSA (Ka values were 1.57 x104 M-1), suggesting that it can be transported in the body by means of the HSA-mediated pathway, enhancing its efficacy and stability. In comparison to its affinity towards DNA, there is a significant difference allowing for the successful transfer of 2d from HSA to DNA. The poor solubility of complex 2d in aqueous environments may have hindered its cellular uptake, but binding to HSA could mitigate this, ensuring minimal interference with its cytotoxicity towards different cancer cell lines. MTT studies demonstrated that 2d has comparable cytotoxicity towards the breast cancer cell line MCF-7 with an IC50 of 9 µM. The IC50 for HT-29 was, however, too high to measure accurately (>100 µM). In conclusion, complex 2d exhibits promising anticancer properties based on its DNA binding studies and cytotoxicity evaluations. This suggests that this class of compounds can be applied in cancer treatments, with potential modifications to compounds 2e and 2f to improve their solubility and stability.Item Optimization of Prostate Plan in a Pelvic Prosthesis Phantom(University of the Witwatersrand, Johannesburg, 2024-09) Dumela, Khombo Eunice; Oderinde, Oluwaseyi M.; Usman, IyaboT.Background: An increasing number of elderly prostate cancer patients with high-density material hip prosthesis are referred for external beam Radiotherapy (EBRT). Radiation treatment of pelvis cancer patients with high-density hip prosthesis needs special attention because of the artifacts created in the computed tomography (CT) field of view and the radiotherapy dosimetry challenges. The accuracy of the treatment planning dose calculation algorithms determines the accuracy of the dose delivered to the patient during radiation therapy. However, the most available algorithms do not accurately model the absorption of high-density metals’ scattering properties and underestimate the resulting dose perturbations. Aim: This study aims to optimize the dose distribution of prostate 3D conformal treatment, intensity-modulated radiotherapy (IMRT) and volumetric-modulated arc therapy (VMAT) in an in-house metallic hip prosthesis phantom. Methods and materials: In this study, an ionization chamber and Gafchromic (EBT3) films were used to physically measure the prostate point dose in an in-house pelvic phantom. The pelvic phantom was irradiated on the Linac with four static fields, namely, (1) anterior field, (2) posterior field, (3) right lateral field passing through the bone of the normal hip and (4) left lateral passing through the hip prosthesis. IMRT and VMATs plans were also generated on the phantom. The phantom was also irradiated with IMRT and VMATs plan. The use of single arc versus two arcs with avoidance sector were also evaluated. The phantom consists of different materials; Nylon-12 (a solid water-equivalent material) to simulate the prostate with a central cavity to accommodate an ionization chamber and film, superflab gel bolus to simulate human soft tissue, dental wax to simulate human soft tissue, bone anatomy for the right hip and a titanium implant to replace the bony structure of the left hip. For the static fields, an in-house pelvic phantom was simulated using the EGSnrc Monte Carlo code, and 6 and 15 MV photon energies were employed as in an experimental setting. The prostate point doses computed by the Treatment Planning System (TPS), measured using ionisation chamber, and Gafchromic EBT3 film were compared with the prostate point doses simulated by Monte Carlo code. Results and discussion: The novel phantom was constructed using superflab gel bolus, Nylon-12, dental wax, pig bone insert and a titanium alloy hip replacement. The radiological equivalence of the superflab gel bolus and dental wax was determined employing linear attenuation coefficients and then compared to an RW3 Solid water phantom. EGSnrc Monte Carlo (MC) code was used in this study. Before using Monte Carlo codes, they need to be validated by comparing the Linear accelerator Monte Carlo simulated dose distribution with the experimental data measured in a Linear accelerator using water and ionization chamber for 6 MV and 15 MV photon beams of different field sizes. The EGSnrc dose distributions were compared with the experimental measurements using a gamma analysis, employing a 2 %/2 mm distance-to-agreement criterion. The EGSnrc Monte Carlo calculated dose distribution agreed well with experimental measurements within 2 %. The MC beam model was then used to compute the dose distribution in an in-house pelvic phantom. The comparison of the measurements between the TPS calculated prostate point dose and ionization chamber for the 6 MV and 15 MV photon beams was: anterior (gantry 0°) 1.8 % and -0.5 %; posterior (gantry 180°) 1.7 % and -0.2 %; left lateral (gantry 90°) 6.3% and 4.2 %; right lateral (gantry 270°) -2.2 % and -2.1 % respectively. Results obtained for Gafchromic EBT3 film measured doses were: anterior 2.3 % and 1.3 %; posterior -0.9 % and 0.2 %, left lateral 4.5 % and 3.5 %; right lateral -2.1 % and -2.5%, for the 6 MV and 15 MV photon beams, respectively. Consequently, results obtained for comparison of TPS, ion chamber and Film with MC simulated doses were: anterior 3.9 %, -2.1 and -1.6% %; posterior 1.8 %, -0.1% and -2.7 %; left lateral -0.2 %, 6.5 % and 4.7 %; right lateral 0.4 %, -2.6% and -2.5 %, for the 6 MV photon beam. And for 15 MV photon beam the results were: anterior 1.9 %, -3.8 and -0.6%; posterior 2.0 %, -2.3 % and -2.2 %; left lateral 0.5 %, 3.7 % and 2.9 %; right lateral 0.4 %, -2.4 % and -2.9 %. Monte Carlo simulations and film measurements have a statistically significant difference of p<0.001, with the film measurements having a higher value than MC simulations except on the left lateral field. Monte Carlo simulations and ionization chamber measurements also show a significant difference of p<0.001, with the ionization chamber having a higher value than the MC simulation, except for the left lateral field passing through the hip prosthesis. The comparison of the measurements between the TPS calculated prostate point dose with ionization chamber and Gafchromic EBT3 film for the 6 MV IMRT plan of the beam passing through the prosthesis was 2.2 % and 3.3%, respectively. While the IMRT plan with avoided beam was 1.9 % and 3.1% for ionization chamber and Gafchromic EBT3 film, respectively. The comparison of the measurements between the TPS calculated prostate point dose for the 6 MV VMAT plan without avoiding for the beam passing through the prosthesis was 1.1 % and 2.2 % for ionization chamber and Gafchromic EBT3 film, respectively. While for VMAT plan with avoided sector as 3.0 % and 4.0% for ionization chamber and Gafchromic EBT3 film, respectively. The test suggested a significant difference of p=0.0001 between the distribution of film measurements and TPS calculated dose. Meanwhile, for ionization chamber measurements and TPS calculated dose; the test indicated a significant difference between ion chamber measurements and TPS calculated dose with a significant level of less than 0.001. in addition, MC simulated dose and TPS calculated dose; the test shows a percentage difference of -0.2 % and 0.5 % for 6 MV and 15 MV photon beams in the lateral field that passes through the prosthesis. The test indicated the significant difference of p=0.001 which is slightly lower compared to the other comparisons. Conclusion: The dual dosimetric pelvic prosthesis phantom is easy to assembly and is more convenient for second dose check for patients with hip prostheses. Through the use of the pelvic phantom, it was possible to measure the prostate point dose using ionization chamber and films. The TPS overestimated the prostate point dose because the treatment planning algorithm could not accurately determine the CT number and the electron density of the prosthesis due to the limitation on the CT scanner. The maximum deviation calculated in this study for TPS, ionization chamber Gafchromic EBT3 films when compared to Monte Carlo simulated dose comes from the lateral fields passing through the prosthesis for both 6 MV and 15 MV photon beams.