Science

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Now showing 1 - 3 of 3
  • (2022) Oudone, Phetdala
    Thesis
    Dissolved organic carbon is stored and processed in groundwater in three ways. It is stored on minerals by adsorption, it is biologically processed through biodegradation, and it also undergoes a process to return to groundwater called desorption. This biophysiochemical research shows that the groundwater system is therefore a vital part of the global carbon cycle and carbon sink. This research fills a gap in the existing understanding of how to calculate the global carbon budget, as does not yet include the dissolved organic carbon that is stored in groundwater. This thesis exclusively explores processes determining dissolved organic carbon character and concentration in groundwater in different geological environments. This is new, useful knowledge to describe the biophysiochemical process. This research did not examine human interference in adding carbon to groundwater. This research found how dissolved organic carbon is stored and processed in groundwater due to biodegradation and desorption, and how it is adsorbed onto sediment surface. This research explored the characteristics and concentration of Dissolved organic carbon in groundwater by using Liquid Chromatography-Organic Carbon Detection, and other techniques, to examine dissolved organic carbon in terms of its fractions: humic substances, hydrophobic organic carbon, biopolymers, building blocks (BB), low molecular weight neutrals and low molecular weight acids. There were several key findings. First, the results showed that both semi-arid inland low sedimentary organic carbon environments – i.e., Maules Creek and Wellington – were a carbon source; while the high rainfall temperate coastal peatland environment of Anna Bay was a carbon sink. Secondly, another key finding was that dissolved organic carbon was not processed as a whole chemical compound, but it was processed by its fractions where each fraction was processed distinctly. For example, humic substances were only adsorbed/desorbed in groundwater; while low molecular weight neutrals were only consumed by microbes in the biodegradation process in groundwater.

  • (2023) Ma, Mingyou
    Thesis
    With the rapid growth of e-commerce, the surging freight traffic is imposing unprecedented pressure on urban transport systems. To mitigate negative impacts of urban freight traffic, the integrated public transport system, i.e., urban co-modality, has been proposed to utilize the existing urban passenger transport system to also carry freight during off-peak hours. Despite the benefits, the co-modal system might reduce public transport reliability and demand due to freight loading/unloading and transshipment operations. This thesis focuses on understanding and modelling the emerging integrated co-modal system for passengers and freight, and investigating and managing its system-wide impacts. This thesis first uses the smart transit card data to understand the travel behaviour of public transport users, and quantify the impact of public transport reliability on users’ day-to-day travel choices. We find that public transport users tend to reserve safety margin for the unforeseen service unreliability. Besides, we also find that there was under-utilized capacity in transit services operating during off-peak hours, which indicates the potential for transporting freight in the public transport system. With the understanding of service-reliability-based travel choices, this thesis then models the mixed freight-passenger cross-type flow and strategic interactions among operators and users in a standalone co-modal system. We first construct a fundamental game-theoretical model based on the essential characteristics of the co-modal system, such as negative impacts of freight on passenger demand. In the fundamental model, we examine the strategic interaction between a transit operator and a freight operator. We show that introducing the co-modality has the potential to generate Pareto-improving outcomes for the operators. This model is extended by considering the endogenous interactions among freight customers, passengers, freight and transit operators. We find that the co-modal system may enhance levels of services for both passengers and freight customers. Building upon these, this thesis further explores the impact of the co-modal system on the freight transport market with outsourcing arrangements. The non-cooperative and cooperative games among a freight carrier, a freight integrator, and a transit operator are modelled, and the co-modal system performance is quantified.

  • (2023) Zhang, Diana
    Thesis
    Early disease diagnosis can significantly improve patient survival rates as appropriate treatment strategies can be timely administered. A promising approach for disease diagnosis is to analyse chemical biomarkers present in bodily fluids as these molecules can provide insights into human metabolic and physiological processes. Changes in the identity and concentrations of such chemicals can help distinguish healthy from disease states. However, some current methods used to collect, analyse, and identify these chemicals have been challenged by limitations in sampling protocols, the resolving power of instruments, and the ability to interpret advanced data analysis methods. This thesis comprises of five concurrent efforts to enhance diagnostic accuracy by investigating various machine learning and analytical approaches. Firstly, an interpretable machine learning framework for binary disease classification is presented. Using this framework on blood plasma and skin sebum data, the diagnostic performance for Parkinson’s disease and key disease biomarkers are reported. Secondly, a protocol and recommendations for robust skin sebum analysis is described. Following a semi-longitudinal study, the various factors that can impact the collection and detection of volatile organic compounds present in skin sebum is discussed. Thirdly, the clinical utility of high-field asymmetric waveform ion mobility spectrometry (FAIMS) for disease diagnosis is reported. Based on a systematic review and meta-analysis, the diagnostic accuracy and clinical implications of using FAIMS is discussed. Fourthly, the performance of high-resolution FAIMS resulting in enhanced ion separations is reported. Using high-resolution FAIMS, the fundamentals that govern the separation of protonation protein isomers is described. Finally, the use of high-resolution FAIMS to analyse volatile organic compounds present in exhaled breath is demonstrated. Using atmospheric pressure chemical ionisation coupled with high-resolution FAIMS, untargeted breath analysis on individual breath profiles is reported. Overall, by improving analytical and machine learning methods, these findings should increase diagnostic accuracy and enable greater confidence in biomarker analysis.