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MACHINE LEARNING APPROACHES FOR BROAD-SCALE CHARACTERIZATION OF SEAFLOOR GEOLOGY ON THE NORTHWEST ATLANTIC SHELF
No full textThis research applied common machine learning algorithms to map seabed sediment properties and classify seafloor morphology across the Northwest Atlantic Shelf using coarse resolution (> 400 m) open-source datasets. Sediment properties were modelled using random forest, trained with observations from NRCan Seabed grainsize analysis and seafloor photograph databases for offshore Canada. A semi-automated approach was developed to classify seafloor morphology from the GEBCO 2020 bathymetric grid, using a k-means clustering algorithm and manual assignment of feature names based on standardized feature definitions.Mapping seafloor surficial geology provides information necessary for effective marine spatial planning, assessing natural and anthropogenic disturbances to the environment, and science-based fisheries and natural resource management. Traditional methods for seafloor geological mapping depend on by-eye interpretation and delineation by experts in the field. However, these methods are generally subjective, non-repeatable, and lacking in statistical validation. Recent advances in computing technology and modelling techniques, such as machine learning, have allowed scientists to use spatial predictive modelling to efficiently produce statistically accurate and spatially continuous map products that characterize various aspects of seafloor geology.
This research applied common machine learning algorithms to map seabed sediment properties and classify seafloor morphology across the Northwest Atlantic Shelf using coarse resolution (> 400 m) open-source datasets. Sediment properties (hard substrate occurrence, modified Folk class, mean grain size, and % mud/sand/gravel) were modelled using random forest, trained with observations from NRCan Seabed grainsize analysis and seafloor photograph databases for offshore Canada. A semi-automated approach was developed to classify seafloor morphology from the GEBCO 2020 bathymetric grid, using a k-means clustering algorithm and manual assignment of feature names based on standardized feature definitions. The standardized workflow from this study enables the integration of datasets from a variety of sources and provides output maps that are comparable over large regions and across a variety of ocean governance boundaries
Financial Viability of Implementing a Greywater Reuse System in the Life Sciences Centre on Dalhousie University’s Studley Campus
No full textEnvironmental Problem Solving II: The Campus as a Living Laboratory Student PapersThe majority of Earth’s water supply is unsuitable for consumption, with only 2.5% classified as freshwater and 1.7% of that is trapped in glaciers, snowcaps and icecaps (Parece et al., 2013). Although Canada is a water-rich country, regional temperatures are warming due to climate change and our northern environment is experiencing milder winters and hotter summers (Government of Canada, 2024b-c). These changes will affect the annual natural runoffs and will have long-term impacts on Canada's access to renewable sources of freshwater (Government of Canada, 2024a). Abdelalim et al. (2015) found that resources used within an institutional setting have the cumulative environmental impact of a small town. Our study explores the physical and financial viability of implementing a greywater reuse system to flush toilets in the Life Sciences Centre (LSC) on Dalhousie University’s Studley Campus. Light greywater from bathroom sinks is a source of greywater that requires minimal treatment to be reused for toilet flushing, a process that unnecessarily uses high-quality drinking water (Olanrewaju & Ilemobade, 2015). To assess the feasibility, both quantitative calculations and qualitative interviews were conducted. During bathroom analysis, usage was monitored, assumptions were made to estimate greywater generation, and freshwater consumption for toilet flushing was measured. In addition, six Dalhousie experts with extensive knowledge of wastewater systems were interviewed. Their responses provided valuable insight and were coded to determine key takeaways. One set of male and female bathrooms in the common area of the LSC was used as the site for this case study, which revealed bathroom sinks generate approximately 39.9 L/hour of greywater, while toilets and urinals consumed around 275.53 L/hour of freshwater. This significant gap indicated the volume of greywater produced would be insufficient to meet flushing demands, rendering the system physically unfeasible. A cost-benefit analysis of economic feasibility supported these results, with annual water savings amounting to roughly $316.23, and over time, this would not be enough to profit or break even within the expected lifespan of a greywater reuse system. Qualitative analysis also reflected these complications, with only three subcodes for potential benefits emerging, while fourteen subcodes related to challenges and concerns. Although greywater reuse offers environmental benefits and supports sustainable resource management, our findings have indicated this proposed reuse method lacks the physical and financial feasibility required to be implemented in the Life Sciences Centre. As such, alternative water-saving strategies may present a more practical and viable option for Dalhousie University.
Keywords: campus sustainability, cost-benefit analysis, feasibility, wastewater, water conservation, water managemen
Bathymetric Anomaly Detection Towards Simultaneous Localization and Mapping on Autonomous Underwater Vehicles
No full textAutonomous underwater vehicles (AUVs) are uncrewed vehicles that can dive to deep depths or under ice to map the seafloor in the Arctic. Due to the lack of global navigation satellite systems (GNSS) underwater, AUV's rely on inertial navigation to estimate their position. Inertial navigation suffers from unbounded error drift. Simultaneous localization and mapping (SLAM) can be used to correct the AUV's positional estimate by repeatedly observing landmarks in its surrounding terrain. Bathymetry has been used to define landmarks for underwater navigation using feature extraction techniques designed for optical imagery. This thesis describes the development of a novel anomaly detector, `Bathymetric Anomalies from Anti-Motifs' (BAAM), that is purpose-built to detect unique bathymetric landmarks. BAAM exploits known bathymetric motifs (commonly repeated patterns) to detect bathymetric anomalies which can be used as landmarks for SLAM. Bathymetric motifs were extracted from a region of Delaware Bay bathymetry using a 2-D adapted matrix profile algorithm, geometric transformation- and scale-invariant image matrix profile (GTSI-IMP), that was developed in this thesis. The ability to associate landmarks, of BAAM and existing optical feature extraction algorithms, was evaluated using semi-synthetic sonar images of a separate region of Delaware Bay bathymetry. For the conditions used in this research, the BAAM detector combined with the binary robust invariant scalable keypoints (BRISK) descriptor produced more correct matches than many of the optical feature extraction methods. However, the scale-invariant feature transform (SIFT) detector combined with the BRISK descriptor was found to produce the most correct matches in both the noise-free and noisy semi-synthetic sonar images. Despite SIFT-BRISK's ability to produce more correct matches than BAAM-BRISK on these semi-synthetic sonar images, the landmarks identified in the Delaware Bay bathymetry using BAAM were found to be more unique (anomalous) than those identified using SIFT
Synthesis of Phosphino(Silyl) Ligated Nickel and Manganese Complexes for the Catalytic Hydrofunctionalization of Alkenes
No full textTransition metal catalysts play a key role in the synthesis of value-added products from abundant raw materials. While homogeneous catalysts that feature scarce metals such as Pd, Pt, Rh, and Ru have proven effective, recent focus on sustainability has led to interest in utilizing Earth-abundant 3d-metals such as Mn, Fe, Co, and Ni. Multidentate phosphino(silyl) ligands under investigation in the Turculet group have proven useful in 3d-metal mediated catalysis. This document details the development of new tridentate PSiN and bidentate PSi supported Ni and Mn complexes for application in hydrofunctionalization catalysis.
Nickel complexes supported by a new PSiN ligand that features a quinolyl donor, as well as complexes supported by the bidentate CyPSi (CyPSi = κ2-(2-Cy2PC6H4)SiiPr2) ligand were shown to be effective pre-catalysts for alkene tandem isomerization-hydroboration. Deuterium labeling experiments support a Ni-mediated alkene chain-walking mechanism involving reversible alkene insertion/β-hydride elimination. Borylation occurs exclusively at a terminal position, affording high selectivity. Nickel complexes supported by a new PSiInd ligand featuring an indolyl backbone were also pursued, and these complexes along with (CyPSi)Ni species were screened in alkene hydrogenation catalysis. A variety of sterically hindered, unfunctionalized alkenes were readily hydrogenated under mild conditions. Deuteration experiments highlight the occurrence of background chain-walking, similar to that observed in the previous hydroboration studies.
The synthesis of chiral phosphino(silyl) Ni complexes for application in asymmetric catalysis was also targeted. In this regard, a new (BIPHEN-SilaPhos)Ni(η3-C8H13) complex is described. This complex and the previously synthesized ((S,S)-TADDOL-SilaPhos)Ni(η3-C8H13) were applied in the asymmetric hydrogenation of (Z)-2-acetamido-3-arylacrylates to access chiral α-amino acid esters. SilaPhos ligation represents a new approach to chiral ligands featuring chirality at a Si donor. The (S,S)-TADDOL-SilaPhos ligated Ni complex afforded the desired products in near quantitative yields with excellent enantioselectivity (up to 98:2 er). Both direct and transfer hydrogenation with iPrOH as the hydrogen source are shown to be viable pathways for this reactivity.
Progress towards the synthesis of Mn complexes supported by multidentate phosphino(silyl) ligation is also described. Mn(I) tricarbonyl complexes supported by CyPSiP (CyPSiP = κ3-(2-Cy2PC6H4)2SiMe) and PSiN ligation were synthesized and structurally characterized. The utility of Mn pre-catalysts in alkyne semi-hydrogenation and alkene hydrogenation was investigated. In situ generated Mn(II) dialkyl complexes featuring CyPSiP and PSiN ligation are shown to be active in the catalytic hydrogenation of a range of terminal alkenes
A Girl of Constant Sorrow: The Sad Girl, Authenticity and Personas in Popular Music
No full textThis thesis analyzes the music and careers of Billie Eilish and Lana Del Rey to demonstrate how a wave of American female pop stars leveraged the Sad Girl archetype to inform their personas and gain mainstream popularity in the first quarter of the 21st Century. These artists rely upon a culturally constructed sadness that is associated with whiteness and femininity and their inherent privilege to curate their authenticity and market their vulnerability across media. However, artists who adopt the Sad Girl archetype can elicit polarizing appraisals from the public sphere; drawing on works in popular music studies, persona studies, and feminist media studies, I propose a layered approach to persona that divides the public identities of musical performers into a series of coexistent personas to determine that aberrations from audience expectations can confuse the collective consensus and negatively impact artists’ public perception
Assessment of Functional Recovery in Experimental Autoimmune Encephalomyelitis by Putative Remyelinating Drugs
No full textCurrent immune-based therapies for multiple sclerosis (MS) reduce disease relapses but have limited value in slowing disease progression. Remyelination in the central nervous system (CNS) is considered essential for functional recovery in MS. This has driven an intense search for drugs that promote myelin repair. This thesis compared the efficacy of four putative remyelinating drugs at promoting motor recovery in a mouse model of MS termed experimental autoimmune encephalomyelitis (EAE). EAE recapitulates many pathophysiological features of MS including autoimmune mediated demyelination and axonal damage. Furthermore, we have shown that EAE produces MS-like gait deficits in mice. Kinematic gait analysis was therefore employed to identify drugs that promote functional recovery in EAE mice. To this end, we compared the effects of oral administration of pioglitazone, VP3.15, olesoxime, or IRX4204 beginning at peak disease on EAE-induced gait deficits. Unlike pioglitazone, VP3.15, and olesoxime, IRX4204 reduced clinical scores, loss of knee average angle, and elevation of knee and ankle RMS differences. These gait improvements in IRX4204-treated EAE mice were associated with transcriptional and histological signs of reduced inflammation, increased remyelination, and enhanced axonal integrity in the spinal cord. Experimentation with a mouse microglial cell line and primary astrocyte cultures showed that IRX4204 suppressed the expression of pro-inflammatory cytokines induced by treatment with lipopolysaccharide. IRX4204 also enhanced mitochondrial function and the phagocytotic activity of microglia. These findings support the potential of IRX4204 to increase functional recovery in MS by stimulating myelin repair. However, IRX4204 suffers from poor CNS uptake and adverse side effects caused by actions on cells outside of the CNS. To overcome these problems, we developed an intranasal nanoparticle formulation of IRX4204 designed to preferentially deliver this drug to the CNS. Our findings suggest that intranasal nanoparticle delivery is a promising strategy to improve the safety and efficacy of IRX4204 but also reveal limitations of this approach
Staffing Models for Blood Donation Centres: A Model-Driven Approach
No full textBuilding on the work conducted by Blake & Shimla (2014), the model presented by this project generates staff schedules based on the minimum staffing requirements for donation clinics operated by Canadian Blood Services (CBS). The proposed design is comprised of two integer programming models and uses a simplified column generation algorithm. Based on the targets set by the user, the first model selects an optimal configuration of clinic length and bed count. These values are then fed into the second model, which assigns shifts based on the calculated requirements. When compared to schedules generated by the client, the model was able to produce solutions of similar or higher quality while also minimizing the operational costs of the clinics. Beyond optimizing clinic scheduling for CBS, this framework can be adapted and applied to other areas within the healthcare industry