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Recent Submissions

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Microbiology of bentonite clay relevant to a deep geological repository for used nuclear fuel
(University of Waterloo, 2024-11-12) Beaver, Rachel
Nuclear energy is an important source of energy globally, but results in the production of used nuclear fuel. When removed from a nuclear reactor after its useful lifetime, used nuclear fuel is still highly radioactive and must be stored safely for approximately one million years until it returns to the radioactivity level of naturally occurring uranium ore. Canada, along with other countries that have an inventory of used nuclear fuel, is in the process of designing a deep geological repository (DGR) for long-term storage of used nuclear fuel. In this system, used nuclear fuel, itself a stable solid, will be stored in copper-coated steel used fuel containers, and placed in bentonite clay buffer boxes made of highly compacted Wyoming MX-80 bentonite. Buffer boxes would then be stacked in placement rooms approximately 500 m below ground in a suitable host rock with spaces between buffer boxes and host rock filled in with a granulated form of bentonite referred to as gapfill material. To ensure the longevity of a DGR, it is important to consider the role that microorganisms could play, particularly through contributing to corrosion of used fuel containers through a process termed microbiologically influenced corrosion. Expected to dominate occurrences of microbiologically influenced corrosion under anoxic conditions, sulfate-reducing bacteria (SRB) are a primary target of research, but rarely live in isolation, thus necessitating the study of microbial communities that could live in the bentonite clay surrounding used fuel containers on a broader scale. Due to the potentially detrimental role that some microorganisms could play in a DGR, a goal in designing a DGR is to compact bentonite, a type of swelling clay, to a sufficiently high dry density that microbial growth is suppressed upon saturation. The first goal of this thesis was to investigate the bentonite dry density necessary to suppress microbial growth in Wyoming MX-80 bentonite under oxic conditions and gapfill material under both oxic and anoxic conditions. A set of pressure vessel experiments demonstrated suppression of microbial growth under oxic conditions in bentonite compacted to a minimum dry density of 1.4 g/cm3. Under anoxic conditions, growth of heterotrophs was suppressed in pressure vessels with a minimum dry density of 1.45 g/cm3, but culturable SRB persisted in abundances higher than the as-received bentonite starting material in the outer layers of all pressure vessels throughout the full one-year experiment. Additional experiments were conducted to explain the increase in abundance of SRB, which had not previously been observed in other studies. These experiments suggested that the increase in abundance of SRB was likely not inherent to the gapfill material, nor was there evidence for it being a result of differences in SRB medium or in amounts of trace oxygen between studies. In both oxic and anoxic pressure vessels, an initial increase in abundance of culturable heterotrophs was observed prior to complete saturation, presumably as water became available but swelling pressure remained sufficiently low to allow for their growth. Although previously proposed to potentially be associated with a recovery from the viable but not culturable state rather than growth, a follow-up experiment suggested that the initial increase in abundance of culturable heterotrophs was likely a reflection of growth (i.e., cell division). Dry density is an important consideration in DGR design, but it is not the only physical property that could influence microbial growth within a DGR. Temperature is expected to fluctuate from natural subsurface temperatures of <20°C to temperatures as high as 94°C, and little research has been conducted to explore the potential for microbial growth in bentonite at these elevated temperatures. This thesis includes experiments testing the abundance and community composition of microorganisms adapted to a variety of temperatures in as-received and hydrated bentonite. The results showed a low abundance of culturable microorganisms that survived incubation at 60°C, but 16S rRNA gene profiles dominated by presumably unculturable representatives of the thermophilic family Thermoactinomycetaceae. Hydrated bentonite was additionally incubated at temperatures of 75, 90, and 105°C, but DNA sequencing results did not show a shift in community composition from as-received bentonite, suggesting that the natural as-received bentonite microbial community may not include members adapted to these very high temperatures. Lab-scale experiments allow for testing of very specific DGR-relevant conditions (e.g., dry density and temperature) and the effect these have on microbial community abundance and composition. However, a DGR is being designed to exist for upwards of one hundred thousand years, which is not a realistic timescale for any experiment. To circumvent this limitation, one approach is to couple lab-scale experiments to the study of natural analogues, which have naturally existed for DGR-relevant timeframes. This thesis presents a study of the Tsukinuno bentonite deposit in Japan, which can serve as a natural analogue to DGR bentonite. In this study, sequencing of DNA extracted from bentonite revealed microbial communities dominated by sequences associated with Thiobacillus, Hydrogenophaga, Comamonadaceae, and Pseudomonas. Although differences in community composition were observed between samples, microbial communities were relatively similar for all four studied cores and at all depths into the clay bed. A series of geochemical parameters were measured to help identify factors that may influence microbial community composition. The abundance of culturable anaerobic heterotrophs was positively correlated with the concentration of nitrate, which could be used by anaerobes for denitrification, and the abundance of culturable aerobic and anaerobic heterotrophs was negatively correlated with the abundance of the clay mineral montmorillonite, increased concentrations of which would increase the swelling capacity of the bentonite. The results presented throughout this thesis will together be useful for incorporation into future models of microbial activity within a DGR and can ultimately be used to inform DGR design.
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Combined Action Observation, Motor Imagery and Steady State Motion Visual Evoked Potential Based Brain Computer Interface System
(University of Waterloo, 2024-11-12) Ravi, Aravind
Stroke is one of the leading causes of long-term acquired disability in adults worldwide. Gait recovery is a major objective in post-stroke rehabilitation programs. Conventional gait therapy encourages patient involvement, but the results can be slow and/or limited, leading to sub-optimal recovery. Active patient involvement, collaboration, and motivation are key factors that promote efficient motor learning. Therefore, there is a need to develop novel rehabilitation strategies to enhance user engagement by utilizing their movement intent. Brain-computer interfaces (BCIs) based on electroencephalography (EEG) offer an attractive approach for rehabilitation as they enable an alternative method for active participation in therapy. Current visual BCIs provide high decoding accuracy but typically do not activate sensorimotor areas critical for motor recovery. Conversely, BCIs based on motor imagery (MI) activate motor areas but suffer from high inter-subject variability and long user training, resulting in poorer movement intent detection accuracy and potentially leading to high cognitive demand. This thesis proposed a novel BCI paradigm called CAMS—Combined Action Observation (AO), Motor Imagery (MI), and Steady-State Motion Visual Evoked Potentials (SSMVEP). The CAMS paradigm aimed to induce acute changes in movement-related areas of the cortex through the observation and imagery of gait movements, activating both motor and visual cortices to elicit SSMVEP-like responses. Furthermore, the responses elicited by the CAMS paradigm were investigated in two distinct applications to detect user movement intent with the aim of actively engaging the participant. The research conducted across three studies investigates the efficacy of CAMS in enhancing cortical excitability, decoding gait phases, and improving asynchronous visual BCI performance. Twenty-five healthy volunteers participated in this study wherein they observed and imagined lower limb movements of gait as part of the CAMS intervention, which was compared with an SSMVEP control condition. Study I aimed to investigate the acute changes in cortical excitability induced by the CAMS intervention. The results demonstrated significant increases in movement-related cortical potential (MRCP) components, indicating enhanced cortical excitability. For instance, the magnitude of BP1 at channel C1 increased from -1.41 ± 0.54 µV pre-intervention to -3.23 ± 0.5 µV post-intervention (p = 0.009), highlighting the potential of CAMS to engage motor- related brain areas and promote neuroplasticity. Study II focused on decoding the phases of gait (swing and stance) from EEG responses elicited by the CAMS paradigm. Using Linear Discriminant Analysis (LDA) and Support Vector Machine (SVM), the study achieved a classification accuracy of 75% and 78%, respectively, in decoding the swing and stance phases of gait. Study III introduced a novel detection algorithm based on Complex Convolutional Neural Networks (C-CNN) for asynchronous offline CAMS BCI. The C-CNN method achieved high F1-scores for asynchronous operation. Median F1-scores for C-CNN were 0.88 (W=1s), 0.92 (W=2s), and 0.96 (W=3s), with corresponding False activation rates (FARs) of 0.34, 0.30, and 0.27. Additionally, larger stimulus frequency differences resulted in stronger visual BCI classification performance, with combinations (7.5 Hz, 12 Hz) and (8.57 Hz, 12 Hz) yielding the highest accuracies of 87% and 78%, respectively. These findings underscore the potential of the CAMS BCI paradigm in enhancing cortical excitability, eliciting responses for decoding gait phases, and improving asynchronous visual BCI performance while simultaneously engaging the movement related areas of the cortex. By providing a comprehensive investigation of the CAMS paradigm, this work contributes to existing knowledge and helps guide future clinical applications in neurorehabilitation.
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The evolutionary and ecological factors that shape ectoparasite populations and communities at multiple scales
(University of Waterloo, 2024-11-12) Sauk, Alexandra
Although parasites are one of the most prolific and diverse consumer groups on the planet, they are often excluded from biodiversity surveys as they are difficult to detect and identify. This deficit limits our understanding of host-parasite relationships and parasite diversity. The vast diversity of host-parasite relationships means that many ecological and evolutionary forces may be at play, shaping the evolution of host and parasite in different ways and varying between species pairs. Bats and their ectoparasites provide a unique system to study the factors influencing parasite populations and communities. The different ecological niches and social behaviours of bats provide variation in the ectoparasites they encounter, and the selective forces experienced by the ectoparasites. I hypothesised that certain attributes of ectoparasite infections (e.g., ectoparasite diversity and infection level) are influenced by the life history traits of both host and ectoparasite and be the environmental restrictions of individual ectoparasite species. Using a collection of ectoparasites passively collected from bats throughout Atlantic Canada between 1999 and 2017, I quantified the ectoparasite communities of two bat species, Myotis lucifugus and M. septentrionalis, and used model-based inferences to assess the differences in infection of their two most common ectoparasites, the mite Spinturnix americanus and the flea Myodopsylla insignis. I found that both bat species had similar ectoparasite communities while S. americanus and M. insignis showed opposing trends in presence and abundance between the two bat species, in keeping with their different life history strategies. I also used a subset of this collection to compare how life history traits and host-parasite dynamics influence the genetic structure and biogeography of co-infecting ectoparasites. I found limited genetic structure with M. insignis exhibiting some isolation by distance between Labrador and Nova Scotia and S. americanus exhibiting regional differentiation between the island of Newfoundland and the mainland. I also provide a synthesis of the currently described bat ectoparasites in North America and an analysis of how host characteristics and environmental factors influence ectoparasite richness and geographic distribution. I found that estimated ectoparasite richness varies widely between host species but is influenced by sampling effort. Bat ectoparasite diversity appears consistent with the predictions of the latitudinal diversity hypothesis with a 3.4% decrease in species richness for every degree increase in latitude. Overall, my findings add to the evidence that ectoparasite populations and communities are shaped by life history traits of the host and ectoparasite. I suggest multidisciplinary collaborations between bat biologists, parasitologists, and taxonomists are necessary to collect ectoparasites and catalogue bat-ectoparasite associations to better understand the ecological and evolutionary forces that shape these communities and to better be able to conserve them in the face of ongoing threats from climate change and landscape changes.
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Attributing Corporate Carbon Mitigation Outcomes to Substantive Decarbonization Actions through Change Analysis
(University of Waterloo, 2024-11-12) Lin, Meijie
Abstract As corporations increasingly disclose their environmental performance and claim to decarbonize their operations, it becomes challenging to distinguish substantive decarbonization actions from symbolic gestures that obscure business-as-usual operations. Despite numerous studies highlighting the prevalence of symbolic corporate carbon management, a clear method for measuring and comparing substantive corporate decarbonization action is still not well established. This study develops an outcome attribution framework using decomposition and decoupling analysis to measure substantive decarbonization actions that effectively reduce emissions. Using secondary panel data from a sample of firms listed on the Hong Kong Stock Exchange from 2018 to 2023, this study aims to: 1) analyze how changes in emissions can be broken down into changes in carbon intensity, energy intensity, and revenue; 2) evaluate the extent of effective corporate carbon mitigation outcomes that can be attributed to substantive corporate decarbonization actions; and 3) examine the correlation between substantive actions and emission reductions. The findings reveal a generally low level of substantive actions, aligning with previous research that suggests corporate climate actions are often more symbolic than substantive. More notably, the weak correlation between substantive actions and emission reductions underscores the limitation of using mitigation outcomes as a proxy for the effectiveness or substantiveness of corporate climate actions. This result emphasizes the influence of unintended external driving factors that may obscure symbolic actions and enable business-as-usual operations to persist under seemingly positive mitigation outcomes. The outcome attribution framework developed in this study offers a novel approach for researchers and decision-makers to measure and compare substantive decarbonization actions at scale, which enhances the decision-usefulness of the commonly disclosed metrics, provides clarity on the effectiveness of corporate decarbonization initiatives, and ultimately guides resources towards meaningful climate actions and advances best practices.
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Fatigue of Aluminum Gas Metal Arc Welds in Electric Vehicle Battery Pack
(University of Waterloo, 2024-11-12) Burchat, Thomas
Aluminum extrusions, when strengthened with precipitation hardening, are an ideal material for lightweight structures. The gas metal arc welding (GMAW) process offers a cost effective and high-volume method of joining mating plates for large structural components. As the automotive industry is looking for lightweight structures to offset the increased weight of electric vehicle battery packs, it is crucial to understand the process limitations and resulting fatigue properties of aluminum GMA welds to ensure the structure outlasts the battery chemistry and warranty. High volume manufactured aluminum welds are controlled with weld acceptance criteria, which are in turn predicted with statistical representation of randomly tested samples. This research investigated the aluminum GMAW process window that consistently produces welds within the industry partner acceptance criteria and resulting microstructure. This research performed component level testing of 2.3 mm AA-6061-T6 mating plates in the tee joint and lap configurations under quasi static and cyclic loading conditions. The quasi-static testing revealed the influence of porosity on the maximum load before rupture of lap shear joints, and the failure location of the joint and lap joint geometries. The cyclic test results showed crack initiation behavior through the thickness of the heat affected zone (HAZ) when observed by digital image correlation (DIC) during testing. Fracture surface analysis revealed crack initiation zones along existing defects and preexisting cracks attached to the root area of the weld for both tee joint and lap joint samples. Structural stress methods are employed to correlate far field nodal force and moment derived stresses to the observed failure locations in thin sheet aluminum welds, excluding local effects. Load life data is translated to structural stress life data for 2.3 mm thick tested samples, as well as for additional 4mm and 8 mm thick samples provided by the industry partner. Stress life data is segregated based on a bending stress to total stress bending ratio into two distinct structural stress curves. Power law regression is used to calculate a line of best fit through each curve. Random samples configurations are excluded from a separate regression, which is used to predict the life of the excluded samples within 3 folds (3x) from tested sample life. Mean stress corrections are used to further collapse test data into single membrane and bending curves but applied thickness corrections increased observed scatter amongst test data.