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Structural characterization and tectonic evolution of 1.3 Ga REE-bearing Fox Harbour Volcanic Belt, southeast Labrador - Canada
No full textThe Southeastern Labrador region, Canada, preserves a complex geological history shaped by multiple deformation and metamorphic events. This study investigates the structural evolution, metamorphism, and deformation of the 1.3 Ga Fox Harbour Volcanic Belt (FHVB), a bimodal volcano-sedimentary sequence of peralkaline rhyolites enriched in rare earth elements (REE), mafic rocks, and sedimentary rocks deposited on 1.7-1.5 Ga basement rocks in an extensional setting along the Laurentian margin. Hosted in a highly strained amphibolite-facies corridor within the Lake Melville terrane (LMT), the FHVB domain is bordered by the Long Harbour (LHsz) and Fox Harbour (FHsz) shear zones to the south and north, respectively. Field observations, structural and petrographic analyses, along with U-Pb petrochronology on zircon, monazite, and titanite, reveal a multi-stage tectonic evolution. Deformation that accompanied the main phase of Grenvillian metamorphism (D1; ~1.06–1.04 Ga) locally involved amphibolite-facies metamorphism and anatexis, tight buckle folding, and tectonic burial of the LMT during Grenvillian convergence. The Pinware and Mealy Mountains terranes remained structurally higher in the tectonic pile and were shielded from significant metamorphism. Continued deformation (D2; ~1.04–1.02 Ga) was characterized by cooling, folding, and localized strain during a period of orogenic collapse, characterized by extensional adjustments of the orogenic crust. Late-stage transpressive deformation (D3; ~1.0 Ga) involved greenschist-facies oblique-slip and strike-slip shearing, overprinting earlier amphibolite-facies fabrics and facilitating the FHVB exhumation. These findings refine the tectonometamorphic history of the FHVB, providing new insights into the kinematic evolution of the Southeastern Grenville Province.Includes bibliographical references (pages 110-118
"There's no climate change here": fishing, memory, and the uneven experience of environmental change in rural Newfoundland
No full textThis thesis explores how rural coastal communities in Newfoundland perceive and
respond to environmental change in ways that diverge from global climate narratives.
Focusing on Bay de Verde, it argues that climate change is not seen as a singular crisis, but as
part of a longer, layered history of ecological transformation and economic restructuring.
Drawing on ethnographic fieldwork and historical analysis, the study shows how embodied
knowledge, economic shifts, and intergenerational memory shape local understandings and
responses. It contributes to the anthropology of climate change by reframing adaptation as an
uneven, lived process embedded in entanglements of nature, labour, and capital. "Rather than
framing these as instances of climate change denial, I document how global climate categories
are translated through fisheries labour, where scale, history, and risk produce vernacular ways
of knowing climate
Class-based vs. instance-based interface design for unanticipated user-generated content in student life reporting
No full textThis thesis investigates the effectiveness of Instance-Based versus Class-Based
interface designs in capturing and managing user-generated content within a student
life context. With the proliferation of digital platforms, the volume and variety of usergenerated
content have surged, challenging traditional structured user interface
designs. Traditional Class-Based interface designs often fail to accommodate the
dynamic nature of user-generated content, leading to the potential loss of valuable
insights. In contrast, Instance-Based interface designs offer a flexible, potentially
improving data representation and usability. This thesis explores the consequences of
using Class-based versus Instance-Based interface design to collect user-generated
content, focusing on student life reporting. The study is driven by questions on how
these two interface configurations compare in their capacity to manage the diverse
nature of user-generated content. By applying both designs in a real-world setting and
analyzing the resultant data, the study aims to furnish empirical insights into the
suitability of each design for user-generated content data collection and management.
The findings suggest that while Instance-Based interface design offers significant
improvements in flexibility and data representation, it also poses challenges in terms
of complexity and user engagement. This research contributes to the broader
discourse on data models in the context of big data, highlighting the potential of
Instance-Based interface design to enhance the collection of user-generated content.
Keywords: Conceptual modeling, interface design, data models, instance-based, classbased,
student life reporting.Includes bibliographical references (pages 62-65
Objective realities and subjective perceptions: a multi-level analysis of immigration attitudes in Canada
No full textDespite Canada’s long-standing reputation for welcoming immigrants and strong public support for multiculturalism, increasing polarization exists among Canadians regarding acceptable immigration levels, especially with recent record-high admissions. While existing Canadian scholarship has focused on national trends and macroeconomic factors, my thesis examined the interplay of regional objective economic conditions and subjective national and personal economic perceptions in shaping Canadians’ immigration attitudes.
Using data from the 2021 Canadian Election Study, the analysis showed that negative provincial economic performance (notably lower GDP growth rates) and negative perceptions of national and personal economic conditions were associated with less favorable views on immigration in Canada. Perceived job threats from immigrants also emerged as a strong predictor of these negative attitudes.
These findings are consistent with the Sociotropic Economic Threat Perspective and the Labor Market Competition Theory. While the results related to objective economic markers align with existing research, this thesis contributes to the literature by highlighting the significant role of subjective economic perceptions in shaping Canadians’ immigration views.Includes bibliographical references (pages 137-163
Investigation of a potential interaction between PKD3 and MP-GAP utilizing fluorescent microscopy and FRET
No full textFailures in cytokinesis, the final stage of mitosis, can lead to binucleation, which may act
as an initiation point for cancer development. Protein kinase D3 (PKD3) is an enzyme that belongs
to a family of protein kinases that have key roles in promoting many cellular processes, including
proliferation, survival, and adhesion. It has been demonstrated that PKD3 depletion can cause a
significant increase in binucleation in mouse embryonic fibroblasts (MEFs). In addition, the M�Phase GTPase-Activating Protein (MP-GAP) is shown to play an important role during the
abscission of two daughter cells by inactivating the Ras homolog gene family member A (RhoA).
The Leitges group previously showed that MP-GAP is translocated to the cleavage furrow at the
late cytokinesis, where it colocalizes with RhoA and PKD3. Considering the effect of PKD3
deficiency on cells and the role of MP-GAP in cytokinesis, we aimed to verify the hypothesis that
these two proteins might interact to regulate the final abscission. In this regard, this project was
based on fluorescent microscopy imaging to track the dynamics of fluorescent protein-fused PKD3
and MP-GAP to characterize a potential interaction. In conclusion, while some data were collected
on the endogenous PKD localization in cells, more experiments are required to establish a
definitive strategy to identify a potential interaction.Includes bibliographical references (pages 75-82
Sparsity motivated signal processing: from wireless communications to general applications
No full textSignals are sparse, meaning that their useful components reside in a dimension significantly lower than that
of the observations. This inherent sparsity motivates the development of effective and efficient signal processing
techniques across a broad spectrum of applications and areas, given that many signals encountered in practice
exhibit sparsity in one form or another. This thesis focuses on sparse signal processing in wireless communications and other emerging scenarios involving high-dimensional data.
Millimeter wave (mmWave) and massive multiple-input-multiple-output (mMIMO) are two key enablers for
boosting transmission rates in fifth-generation (5G) and beyond. The former offers considerable bandwidth for
wideband communication, while the latter provides multiplexing gain and diversity gain. Accurate channel state
information (CSI) is essential for mMIMO to realize its full potential. The inherent sparsity of mmWave channels
facilitates accurate channel estimation with reduced system overhead. However, the non-negligible propagation
delay within the mMIMO antenna array, known as beam squint, poses a significant challenge to traditional channel estimation algorithms. An efficient channel estimation technique considering the beam squint effect is therefore introduced.
Massive random access (MRA) presents another challenge in wireless networks when supporting a large user
base. Given the limited number of orthogonal preambles, traditional grant-based random access methods encounter high conflict probabilities and thus fail. Grant-free MRA addresses this issue by assigning each user a unique, non-orthogonal preamble for access detection and identification. Due to the sporadic nature of transmissions, user activity remains sparse, thereby enabling the use of existing sparse signal processing techniques for accurate activity detection. However, most existing research on grant-free MRA has focused on co-located mMIMO systems, and we explore the benefits of incorporating a distributed system, namely, cell-free mMIMO.
Simultaneous localization and communication (SLAC), an emerging focus for next-generation cellular networks,
can also benefit from cell-free mMIMO by the spatially diverse line-of-sight paths between base stations and
the user. Nevertheless, linear time-invariant channel models dominate current SLAC discussions, due to the
widespread success of orthogonal frequency-division multiplexing (OFDM) systems. Reliable communication
in highly dynamic environments recently motivates increasing attention to doubly dispersive channels, a linear
time-variant channel considering both delay spread from multipath and Doppler effects from user mobility. We
investigate cell-free mMIMO with doubly dispersive channels from an SLAC perspective. Apart from wireless communication, sparse signals, such as electroencephalograms (EEGs), are prevalent in biomedical engineering and are characterized by their large data sets. Current sparse Bayesian learning (SBL) algorithms provide satisfactory performance for sparse signal recovery, but they have the drawback of high computational
complexity due to matrix inversion. We aim to universally achieve inversion-free across various SBL
algorithms. Furthermore, sparse signals in specific applications, such as spatiotemporal traffic data from intelligent transportation systems, exhibit multidimensional characteristics. We exploit correlations, such as temporal correlations, through Bayesian tensor decomposition techniques
Advanced offshore reservoir characterization and EOR screening: applications of machine learning and molecular dynamics
No full textEfficient production of underground hydrocarbon resources is a top priority to satisfy the global oil demand, not merely as a source of energy but also as the raw material for numerous products of vital importance in our daily lives. Most of the current daily oil production comes from mature or maturing oil fields, and reserve replacement through new discoveries is not keeping pace with the growing energy demands. Therefore, the petroleum industry has been trying to maximize the recovery from existing and mature oil fields, mainly through Enhanced Oil Recovery (EOR), and extend exploration and production activities to deeper offshore areas and harsher environments such as the Arctic. Offshore reservoirs generally exhibit poor recovery factors due to several challenges and limitations encountered in offshore areas. Given the capital-intensive and risk-prone nature of EOR projects and the volatility of oil prices, the number of EOR projects sanctioned and carried out worldwide is still limited, considering the global need to boost production efficiency from available assets. EOR experience is even more restricted in offshore reservoirs due to several constraining factors, including large well spacings, platform weight and space limitations, and availability of EOR injectants, among others. Therefore, it is critical to identify the best possible EOR options for a reservoir at the earliest possible field development stage to avoid future complications and constraints in EOR design and implementation.
A best-practice workflow for an EOR project would typically consist of several steps, including screening, preliminary technical and economic feasibility studies, laboratory testing, reservoir simulation, pilot testing and analysis of the results, and full-field implementation. EOR screening, which is the first step in this workflow, depends significantly on the knowledge of reservoir fluid and rock data. The ideal approach is to determine the reservoir rock and fluid properties using
direct laboratory tests and measurements. All the reservoir fluid and rock laboratory tests and measurements require samples from reservoir rock and fluids, which, for various reasons, may not always be available, especially at the early stages of reservoir development. On the hand, the laboratory experminets and measurements are usually costly and time-consuming further restricting early-stage decision-making and planning. Therefore, other tools and methods are needed to predict reservoir fluid and rock properties of interest. These predictive techniques include theoretical relationships, empirical correlations, and more advanced methods such as machine learning and molecular simulations. One of the objectives of this study is to develop and assess the performance and functionality of advanced machine learning and MD simulation modelling approaches to predict reservoir fluid and rock properties that may be unavailable for use in EOR screening.
The final goal of this research is to develop an EOR screening tool based on advanced machine learning classification algorithms to provide suggestions as to the best possible EOR options for any candidate reservoir. The suggestions of this EOR screening tool will be based on an extensive dataset of worldwide EOR implementations for various types of reservoirs in terms of properties and conditions. EOR screening is considered an imbalanced classification problem due to the typically disproportionate distribution of different classes (e.g. EOR methods) in most EOR datasets. We attempt to properly deal with this data imbalance issue to ensure the class predictions of the developed EOR screening tool are not biased toward the EOR methods of which more data is available in the dataset. Given the short window of opportunity in offshore developments and the importance of early planning and design of EOR for these reservoirs, it is expected that the advanced EOR screening tool developed in this study can add significant value by facilitating the fast but reliable selection of EOR options
Navigating grand challenges: measuring the impact of CSR decoupling and greenwashing in digital media companies
No full textIn this thesis, I investigated the extent to which corporate social responsibility (CSR) disclosures align with actual CSR performance in the digital media industry, with a particular focus on the phenomena of CSR decoupling and greenwashing. I analyzed a sample of fifty leading digital media companies using the Global Reporting Initiative (GRI) framework, scoring each firm across core indicators related to environmental impact, data privacy, algorithmic transparency, and corporate governance. For each company, I evaluated the CSR disclosures and contrasted them with independently verified performance data, and developed a decoupling index to quantify the divergence between symbolic communication and substantive action.
To support the GRI-based ranking, I conducted a public trust survey and employed multiple linear regression to investigate the link between CSR decoupling and public trust. I also used descriptive statistics and Pearson correlation tests to further evaluate how different CSR performance areas affect stakeholder trust. My findings reveal a persistent gap between CSR disclosures and substantive action, indicating that decoupling and greenwashing are structural features within the digital media sector. The survey results further demonstrate that while CSR decoupling can erode stakeholder trust, the extent of this impact is shaped by factors such as stakeholder awareness and media framing.
This study is centered on three theoretical frameworks: institutional theory, resource dependence theory, and signaling theory. While institutional forces frequently promote symbolic CSR disclosure, signaling theory explains how corporations intentionally manage impressions through communication that lacks substantial support. By integrating theoretical insights with empirical evidence, I offer practical recommendations for policymakers, regulators, and industry leaders, emphasizing the need for enhanced oversight, third-party verification, and genuine alignment between corporate values and actions
Methionine and guanidinoacetic acid metabolism in Yucatan miniature piglets
No full textMethionine, an essential amino acid, plays crucial roles beyond its incorporation into proteins. It
can be converted into S-adenosylmethionine (SAM), the universal methyl donor involved in over
50 transmethylation reactions. These reactions are essential for creatine and phosphatidylcholine
(PC) synthesis and DNA methylation. The first experiment in this thesis investigated the
methionine requirement for synthesizing major transmethylated products, whole body proteins and
tissue specific proteins. Data from the first experiment demonstrated that DNA methylation is
prioritized over hepatic creatine synthesis, while PC synthesis continuously increases with
methionine intake. When methionine was limited, liver protein synthesis was prioritized, followed
by kidney and muscle protein synthesis. Since different tissues have varying methionine
requirements, our data provide insights into why growth is restricted at lower amino acid intakes,
to spare limited amino acids for intestinal function and critical metabolic processes in other vital
organs.. These findings indicate that using protein synthesis alone to determine whole-body
methionine requirements is inadequate, as more methionine is needed to fulfill its non-protein
roles. The second major objective of this thesis was to investigate the effect of dietary methionine
on supplemental guanidinoacetate (GAA) absorption and creatine synthesis in neonatal piglets.
Using a 4-h duodenal infusion with radioisotope tracers and dietary treatments varying in
methionine levels, we found that excess dietary methionine increases the portal appearance of
GAA and enhances creatine synthesis in piglets. Furthermore, our data revealed that GAA
accumulates in the liver when dietary methionine is deficient, although no toxic effect was
apparent. Recently, researchers identified that the GAA + creatine mixture enhanced muscle and
brain creatine levels in healthy individuals. However, there is little information on how the GAA
+ creatine mixture affects GAA absorption, transport, and utilization in pigs. Hence, we compared
the effectiveness of three supplementation options: GAA alone, GAA + methionine, and GAA +
creatine, in enhancing creatine stores and GAA absorption in neonatal piglets. Moreover, we
evaluated the effectiveness of creatine and GAA combinations in enhancing GAA absorption
across the gut in neonatal piglets using an ex vivo Ussing chamber model. This study demonstrated
that both GAA + methionine and GAA + creatine groups showed increased brain creatine levels,
compared to control. Moreover, hepatic creatine concentration was highest in the GAA + creatine
group, compared to control and GAA groups, suggesting GAA+ creatine is the best combination
to improve hepatic creatine stores. Findings from the Ussing chamber model showed that a higher
level of creatine enhanced GAA absorption across the jejunum.
Overall, these studies improve our understanding of methionine metabolism in both protein and
non-protein pathways and GAA metabolism and creatine synthesis in neonatal piglets. These
findings could significantly impact the animal industry and health and disease management across
various populations, including different age groups and animal species.Includes bibliographical reference
Decolonizing HR processes in Canadian business schools: challenges for Indigenous faculty members
No full textThis dissertation investigates the challenges for Indigenous faculty members within Canadian universities, focusing on the decolonization of human resources (HR) processes from a post-humanist perspective. The research analyzes HR-related processes, such as hiring, tenure, and promotion, which often implicitly favor western pedagogical approaches, thereby limiting Indigenous representation. Through a post-humanist lens, the study employs a diffractive reading of institutional documents from three British Columbia universities (UBC, UFV, and TRU), highlighting the need for an alternative approach to HR practices that acknowledge Indigenous knowledge and cultural practices. Originally, this research aimed at using AI and technology (Mapify Pro) to create a cartography for each institution. The initial plan was to extract AI-generated cartography for each institution based on statistical and coding analysis of their collective agreement (HR-related documents). However, the absence of wording observed for the three universities in relation to Indigenous-related matters changed the way I interact with AI technology. Indeed, due to the few occurrences of words/contexts related to Indigenous-related matters, I had to use AI technology to visualize the institutional void (called ‘hauntology’) for Indigenous-related matters in collective agreements. The dissertation advocates for a holistic framework to support meaningful decolonization, proposing actionable recommendations for fostering a more inclusive academic environment that integrates Indigenous epistemologies within the structural fabric of Canadian business schools.Includes bibliographical references (pages 87-93