Electronic Theses and Dissertations (ETD)
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All theses from 2011 to the present are in this collection, as well as some from 2010 and earlier years.
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Item The role of interactions between cucurbit[7]uril and small molecules in the sodium deoxycholate hydrogel(2024) Rahbari Asr, Nikou; Bohne, CorneliaThe structure of bile salts has hydrophilic (hydroxyl groups) and hydrophobic (alkyl groups) regions, resulting in amphiphilic properties. Bile salts can form aggregates and these aggregates can act as supramolecular hosts for small molecules and encapsulate guest molecules within their structure. Unlike other bile salts, sodium deoxycholate (NaDC), can form supramolecular hydrogels through molecular self-assembly processes by adjusting the pH to around neutral and controlling the temperature. The aim of this work, was to investigate how cucurbit[7]uril (CB[7]), affects the properties of NaDC hydrogel. Cucurbit[n]urils (CB[n]s) are a family of macrocyclic molecules characterized by their pumpkin-shaped structure and a symmetrical hydrophobic cavity. By studying the interactions of CB[7] in NaDC hydrogels, the aim was to understand the potential role of CB[7] in modifying the hydrogel's properties and to determine if CB[7] can serve as a carrier for guest molecules from the NaDC hydrogel to the surrounding medium. To gain a better understanding of the effect of CB[7] and its localization within the NaDC gel, two projects were developed. The objective of the first project was to study how the presence of NaDC aggregates affects the binding dynamics of berberine, a natural isoquinoline alkaloid fluorophore, with the host CB[7] in the presence of mobile aggregates of the NaDC. The presence of NaDC aggregates creates a more heterogeneous environment for the host-guest interactions, potentially affecting the dissociation of berberine from CB[7]. The results showed that the addition of NaDC aggregates changed the distribution of berberine, causing berberine to bind to both CB[7] and NaDC aggregates. The results also revealed that the addition of NaDC aggregates to the berberine@CB[7] complex accelerated the apparent dissociation rate constant of berberine from CB[7]. The objective of the second project was to understand how the presence of CB[7] affects the structure of the NaDC hydrogel and the release of a small molecule from the hydrogel into the surrounding medium, and how this effect differs from the effect of cucurbit[6]uril (CB[6]). To study these effects, I studied the hydrogel's structure using berberine, a hydrophobic and positively charged guest, and rhodamine 6G, a hydrophilic and positively charged dye. The release of rhodamine 6G from the NaDC hydrogel into the surrounding medium was also studied in the presence of CB[7] and CB[6]. The results showed that the presence of CB[7] in the NaDC hydrogel caused the transformation of the spherical aggregates into elongated structures, whereas CB[6] led to the formation of fibrous structures, as observed in previous research conducted by our group. Also, the release profile of rhodamine 6G from the NaDC hydrogel was not significantly affected by the addition of either CB[6] or CB[7].Item Proanthocyanidins in poplar roots - effects on mycorrhizal colonization and nitrogen uptake(2024) Yamakawa, Daisuke; Hawkins, Barbara J.; Constabel, Carsten PeterProanthocyanidins (PAs), also known as condensed tannins, are widespread plant secondary metabolites, especially common in trees. PAs are known for their roles in plant defense and soil nutrient cycling, and their many applications in human medicine and diet. Although substantial research has focused on PA function in plant shoots, few studies have investigated their roles in roots. Some research indicates that PAs act as anti-fungal compounds, suggesting PAs in roots could negatively affect beneficial fungi in soils such as mycorrhizal fungi, which provide nutrients, including nitrogen (N), to host plants. Notably, the growth of the ectomycorrhizal (EcM) fungus Laccaria bicolor was inhibited in vitro by a purified extract of poplar PAs. Therefore, I aimed to evaluate the effects of PAs in roots on mycorrhizal colonization as well as on N uptake by colonized roots. Poplar (Populus. tremula x P. tremuloides) was chosen as the study species because poplars produce a wide range of phenolic compounds, including PAs. I utilized transgenic lines developed previously that have high and low PA concentrations in plant tissues, including roots. Plants from each line were equally divided into two treatment groups inoculated with either the EcM fungus L. bicolor or the arbuscular mycorrhizal (AM) fungus Rhizophagus irregularis, and one non-inoculated control group. Plants were grown in a sandwich culture system that allows co-culture of the mycorrhizal fungi and roots, or inoculated with the fungi in soil in a greenhouse experiment. Uptake of ammonium (NH4+) and nitrate (NO3−) by plant roots was measured using a microelectrode ion flux measurement system (MIFETM), and by 15N-labelling. Successful EcM colonization on poplar roots was confirmed in all the plant lines, while no AM structures were observed in the roots. Contrary to my prediction, the poplar line with low-PAs/phenolics in roots was less colonized by EcM fungi in both sandwich and soil culture. Additionally, plants from all lines inoculated with EcM fungi in sandwich culture system tended to have lower root PA concentrations. Although no significant difference in N uptake among plant lines or mycorrhizal treatments was observed, NH4+ uptake was greater than NO3− uptake. Understanding the effects of the interaction of root PAs and mycorrhizal fungi on mycorrhizal colonization and N uptake will contribute to our knowledge of the ecological and physiological impacts of PAs in the rhizosphere.Item Edge server placement considering resilience in mobile edge computing networks(2024) Begum, Syeda Mahfuza; Pan, JianpingIn today’s rapidly evolving communication landscape, the demand for exceptional Quality of Service (QoS) and Quality of Experience (QoE) in communication networks has reached unprecedented levels. This surge in demand can be attributed to the explosive growth and pervasive deployment of Internet infrastructure. Emerging technologies and novel applications underscore the urgency for a network architecture that not only delivers speed and efficiency but also boasts scalability and resilience beyond the capabilities of traditional cloud computing networks. Mobile Edge Computing (MEC) stands as a promising solution to address these challenges. By deploying Edge Servers (ESs) in close proximity to end-user devices, MEC enables the offloading of delay-sensitive and computationally intensive workloads from mobile applications. This deployment, in turn, mitigates latency issues and enhances the QoE for mobile users. However, the reliability of Edge Server Placement (ESP) within MEC networks is of paramount importance. While several studies have explored the ESP problem in MEC networks, they often focus on two main objectives: minimizing Edge Server (ES) access delay and optimizing workload distribution. However, one critical aspect has been relatively under-emphasized: the resiliency of ESP. The failure or malfunction of ESs, stemming from various challenges, can disrupt operations and degrade the overall QoS/QoE of the network. In this study, we tackle the ESP problem in MEC networks from a distinctive perspective. Our focal point is to minimize ES access delay, efficiently balance workloads, and significantly enhance network resilience. To achieve these objectives, our innovative algorithm employs a dual strategy. First, we utilize the robust K-medoids clustering algorithm for ESP, optimizing the architectural layout of MEC networks. Second, we introduce a bespoke heuristic algorithm designed to allocate multiple ESs to each Base Station (BS), thereby fortifying network resilience. This approach not only adheres to various constraints but also ensures uninterrupted services, even in the face of server failures, while consistently meeting key performance indicators. Experimental results, based on real-world data, prove the effectiveness of our algorithm. It not only reduces access delay and workload imbalances but also ensures responsive performance and uninterrupted services, even in scenarios involving ES failures.Item Improving situation awareness to reduce healthcare-acquired urinary tract infection(2024) Alqarrain, Yaser; Roudsari, Abdul V.Reducing healthcare-acquired urinary tract infections (HAUTI) is a common goal among healthcare providers and organizations. Nurses' situation awareness (SA) skills would likely improve patient status recognition and prevent healthcare-acquired urinary tract infections. Healthcare providers, such as nurses, need eHealth systems that support their situation awareness as they provide care. Integrating Endsley's design principles with machine learning offers a promising approach for developing an SA-oriented dashboard that could help reduce HAUTI. This study takes an initial step toward this goal by exploring context-based variables contributing to HAUTI. I included a comprehensive list of nursing assessments and implemented multiple methodologies to handle the datasets and address missing data. The XGBoost model emerged as the most effective model in predicting HAUTI, isolating factors such as improving skin integrity and mobility and monitoring neurological status as key factors in reducing HAUTI rates. However, these results should be carefully interpreted, given this study's significant missing data. The finding of this study reinforces the necessity of high-quality data to support the interpretation of Machine Learning (ML) models in clinical settings.Item Communicating net-zero climate policy and energy modeling results via an interactive visualization dashboard(2024) Attard, Erica; McPherson, MadeleineThe Canadian Government has pledged to achieve net-zero greenhouse gas emissions by 2050. To achieve this target, energy modeling is required to evaluate different decarbonization pathways and possible policy options, however, its impact is currently stunted due to a communication gap between energy modelers and stakeholders. This thesis presents the development and testing of the Integrated Dashboard for Energy transition Analysis (IDEA), an open-sourced tool used to address the communication gap and promote evidence-based decision making. IDEA enables policy makers to evaluate decarbonization pathways and complex policy decisions through the use of visualizations and an interactive dashboard. A Human Centered Design process was implemented to develop a prototype dashboard and evaluate its functionality and applications. Key stakeholders including Environment and Climate Change Canada, Natural Resources Canada, the David Suzuki Foundation, Clean Energy Canada, BC’s Ministry of Energy, Mines and Low Carbon Innovation and BC’s Climate Action Secretariate were involved in the development and evaluations. An output of this thesis is a fully tested visualization dashboard that is adaptable to multiple models and visualization types. The major contributions of this thesis include insights and guidelines surrounding the needs of stakeholders, a detailed discussion on the current and future applications of IDEA, and a call for further communication tools that can advance data-driven decision making. IDEA successfully operates as a results analysis tool, enabling modeling teams and stakeholders to evaluate complex policy decisions. Future applications include expanding IDEA to a key insights tool, supporting decision makers with the most pertinent information, and a modeling tool, allowing stakeholders to implement their own assumptions and model formulations to conduct independent evaluations. Future work includes implementing the discovered improvements to strengthen IDEA as a results analysis tool and further investigating the feasibility and impact of the other tools uncovered.Item A novel approach to life cycle assessment for early-stage design of low-carbon buildings(2024) Torabi, Mahsa S.; Evins, Ralph; Bristow, DavidBuilding design processes are dynamic and complex. The context of a building project is manifold and depends on the context, climatic conditions and personal design preferences. Many stakeholders may be involved in deciding between a number of possible designs defined by a set of influential design parameters. Building LCA is the state-of-the-art way to provide estimates of the building carbon content and environmental performance of various design alternatives. However, setting up a simulation model can be labour intensive and evaluating it can be computationally unfeasible. As a result, building simulations often occur at the end of the design process instead of being an influential factor in making early design decisions. Given this, the growing availability of machine learning algorithms as a potential method of exploring analytical problems has lead to the development of surrogate models in recent years. The idea of surrogate models is to learn from physics-based models, here a building LCA model, by emulating the simulation outputs given the simulation inputs. The key advantage is their computational efficiency in terms of accuracy and time. They can produce performance estimates for any desired building design within seconds, while in physics based modeling hours maybe needed to run the analysis. This shows the great potential of surrogate modelling to innovate the field. Instead of only being able to assess a few specific designs, entire regions of the design space can be explored, or instant feedback on the sustainability metrics of building can be given to architects during design sessions. This PhD thesis aims to advance the young field of building LCA surrogate models. It contributes by: (a) developing a parametric model capable of whole design space exploration, to solve the issue of lack of building LCA data and (b) deriving surrogate models that can process dataset of building carbon results and estimate the associated impact on building performance. The result of this study can assist architects, engineers, researchers and policy makers both by provided results and also the proposed methodology to integrated LCA in strategic and early-stage decision making in the design process.Item Inferring network topology for distributed machine learning model training(2024) An, Renjun; Wu, KuiWith the application of distributed machine learning in various industries, there is an increasing demand for model training using cloud computing resources. However, many cloud computing service providers refuse to provide end-users with information about the underlying network topology for commercial and security reasons. Due to this opaqueness, it is challenging to arrange the computation modules in different Virtual Machines (VMs) to achieve the best resource utilization efficiency. To address this problem, we propose an algorithm called Flow Tracking (FT), which uses external measurements to infer the internal structure of a general graph. Compared to the state-of-the-art topology inference algorithms, FT achieves the most accurate topology measured in four different metrics. Notably, FT achieves 100% reconstruction of the underlying topology under the shortest-path routing strategy of the underlying network. Experimentally, resource allocation using the inferred topology improves the model training efficiency significantly compared to random allocation.Item Self-admitted scientific debt: Navigating cross-domain challenges in scientific software(2024) Awon, Ahmed Musa; Ernst, NeilScientific software development faces unique cross-domain challenges, requiring expertise from both scientific and software engineering disciplines. These challenges often manifest as technical debt, specifically in the form of Self-Admitted Technical Debt (SATD). While technical debt is a well-recognized issue in software engineering, its impact within scientific software remains underexplored. In particular, the integration of domain-specific scientific knowledge with robust software engineering practices presents ongoing difficulties. This work investigates these cross-domain challenges in scientific software in various fields—including high-energy physics, astronomy, molecular biology, climate modeling, and applied mathematics—through SATD analysis. We examined 28,680 code comments from nine open-source scientific projects, identifying 11 types of technical debt. Among them, we introduced a novel category termed Scientific Debt, representing the issues that arise when integrating scientific findings with software development. We identified five key indicators of SD: assumptions, missing edge cases, accuracy challenges, translation challenges, and the incorporation of new scientific discoveries. Our findings reveal that Scientific Debt accumulates at a significantly higher rate than it is resolved, with the Missing Edge Cases indicator being the most frequently addressed. To further support the management of this debt, we explore the potential of Large Language Models (LLMs) in identifying and predicting cross-domain challenges. Our preliminary investigation suggests that LLMs could help detect issues requiring both scientific and software expertise, offering a promising direction for future efforts to manage and mitigate Scientific Debt.Item Searching for long-lived supersymmetric particles using displaced vertices and missing transverse energy with the ATLAS detector(2024) Carlson, Evan Michael; Trigger, Isabel; Kowalewski, Robert V.The Standard Model of particle physics has been extremely successful in its predictive power and has withstood a wide array of precision tests designed to expose any flaws in its description of fundamental particles. However, the Standard Model is unable to explain several phenomena observed in the universe, such as the nature of the dark matter which makes up more than 80% of the gravitationally interacting matter in the universe. Theories that extend the Standard Model with new fundamental particles have been postulated to address the questions left unanswered by the Standard Model. Many supersymmetric theories provide viable dark matter candidates. In order to more precisely test the Standard Model and its possible extensions, the ATLAS experiment at the Large Hadron Collider has been constructed to measure high energy proton-proton collisions. Long-lived particles (LLPs) are commonly predicted by extensions to the Standard Model. The decay of a LLP to charged particles within the ATLAS Inner Detector would produce tracks that are displaced from the interaction point, which could be reconstructed as a displaced vertex. This dissertation presents a search for displaced vertices with high invariant mass and high track multiplicity in events with significant missing transverse energy in the 2016-2018 data set collected by the ATLAS experiment. The observed number of events is consistent with the number expected from background processes. The results are interpreted in the context of a split-supersymmetry model with long-lived gluinos decaying to neutralinos and Standard Model quarks, and exclusion limits are set at 95% confidence level.Item Education as strategy: Vocational reform and social mobility in neoliberal China(2024) Lu, Yifan; Xu, FengThis thesis explores the evolution of vocational education policies in China, analyzing how market forces, neoliberal ideology, and the centralized control of the Chinese Communist Party (CCP) interact. I argue that while China aims to modernize and enhance its vocational education system to meet changing economic demands, these reforms serve dual purposes. On one hand, they aim to create a market-oriented education system that supports China’s broader economic objectives; on the other, they direct migrant and rural populations into vocational tracks, masking deeper socio-economic divides and using education reform as a tool for political stability rather than social equity. I situate China within the global trends of ‘vocationalism’ which promotes vocational education as a solution to economic and employment challenges. I then explore how vocational education reforms in China, articulated through the 1996 Vocational Education Law and its amendments, align with neoliberal trends that promote “suzhi” (quality) and “talent” to meet industrial demands. I also probe into China’s unique governance model, which combines market- driven reforms with authoritarian controls to shape its education reform. This governance strategy allows for a prioritization of national economic objectives over educational equality and perpetuates class distinctions by directing disadvantaged groups into vocational paths. I conclude that these reforms fail to uplift disadvantaged groups as claimed by state propaganda but only reinforce existing social stratifications. Empirical data for the thesis come from government reports, public media, secondary ethnographic literature and legal research.Item Vectron: A dynamic programming auto vectorization framework(2024) Naser Moghaddasi, Sourena; Numanagić, IbrahimDynamic programming (DP) is a fundamental algorithmic strategy that decomposes large problems into manageable subproblems. It is a cornerstone of many important computational methods in diverse fields, especially in the field of computational genomics, where it is used for sequence comparison. However, as the scale of the data keeps increasing, these algorithms are becoming a major computational bottleneck, and there is a need for strategies that can improve their performance. Here, we present Vectron, a novel auto-vectorization suite that targets array-based DP implementations written in Python and converts them to efficient vectorized counterparts that can efficiently process multiple problem instances in parallel. Leveraging Single Instruction Multiple Data (SIMD) capabilities in modern CPUs, along with Graphics Processing Units (GPUs), Vectron delivers significant speedups, ranging from 10% to more than 20x, over the conventional C++ implementations and manually vectorized and domain-specific state-of-the-art implementations, without necessitating large algorithm or code changes. Vectron's generality enables automatic vectorization of any array-based DP algorithm and, as a result, presents an attractive solution to optimization challenges inherent to DP algorithms.Item Adaptive resource allocation in multi-agent social networks(2024) Malek Akhlagh, Mojtaba; Weber, JensDistributing resources among agents in social networks is an important and challenging problem. It involves deciding on assignment of a subset of resources to each agent based on the system objectives. Various instances of this problem can be observed in healthcare resource distribution, disaster management, cloud resource optimization, etc. In collaborative systems, different coordination techniques have been introduced in order to maximize overall social welfare. However, this problem becomes more complex in large-scale networks with limited connectivity among the agents. Moreover, in dynamic environments, where the set of tasks or resources change over time, an effective system needs to adapt to changes in the environment. Existing mechanisms fall short in addressing the social network constraints, and do not present efficient solutions when dealing with dynamic changes of supply and demand quantities. In this thesis, we view this social resource allocation problem (SRAP) as a multi-agent coordination problem. In a centralized approach, we consider a master agent with global knowledge, which makes decisions for all the agents. We present a greedy mechanism using an efficiency heuristic, and a learning-based mechanism by formulating the SRAP as a Markov Decision Process (MDP), and incorporating deep Q-learning. On the other hand, in a decentralized approach, we present a multi-agent protocol, which relies on local interactions among agents and their local knowledge only. The protocol enables the agents to negotiate with each other on allocation of resources to their tasks. It allows an agent in need of resources to concurrently negotiate with multiple providers and combine their resource contributions. We present greedy and learning-based mechanisms by integrating deep Q-learning into the negotiation process. In addition, the agents are able to cascade their corresponding information along the network, and apply timeouts in their messages. Hence, the decentralized protocol enables the multi-agent system to be self-organized, without relying on any central entity. We evaluate our approaches by developing simulation models of agents, tasks, and resources. We perform experiments on three main types of social networks, namely small-world, scale-free, and random networks. We conduct an empirical study of the performance of these approaches under varying conditions, such as resource availability, resource types, task requirements, etc. Our simulation results present a comprehensive analysis of various approaches across different types of social networks, by highlighting the strengths and limitations of centralized versus decentralized, as well as greedy versus learning-based approaches.Item The salt cod saga: Examining drivers of decline in the Pacific cod fishery (1915-1940)(2024) Moore, Karoline I.; McClenachan, LorenMarine historical ecology and environmental history aim to reconstruct past fisheries to reveal ecological changes and human-ocean relationships. Most existing research emphasizes prominent fisheries with lasting economic and cultural impacts, often overlooking lesser-known fisheries, such as the early 20th-century Pacific salt cod fishery. This fishery operated in the shadow of the dominant Atlantic cod, failing to gain similar significance, and has remained largely understudied. This research investigates the sociopolitical factors influencing the decline of the Pacific salt cod fishery in the 1930s, while also examining the changing relative abundance of Pacific cod during its operation. Utilizing the historical journal Pacific Fisherman, which documented contemporary fishery operations, this research identifies key constraints: limited markets, shifting consumer preferences, and high operational costs hindered mechanisation and product competitiveness in a changing societal landscape. Furthermore, localized depletions and a trend of decreasing fish body size occurred during the fishery's lifespan. The results suggest that the fishery's failure was profoundly shaped by its societal, political, and temporal contexts, particularly as it declined while other fisheries industrialised. This thesis addresses the gap in literature concerning the decline of the Pacific cod fishery and contributes to the understanding of lesser-studied, pre-industrial fisheries. It offers valuable insights into the importance of reconstructing historical fisheries data, especially when such data are scarce.Item Parole for life: A qualitative inquiry into the Canadian life sentence(2024) Kish, Nicole; Humphrey, TamaraLife sentences in Canada punish individuals until their deaths, constituting the harshest sentence permissible under the Criminal Code. Canadian life sentences are presently among the harshest versions of life imprisonment globally. There is a dearth of research into life sentences and their impacts in the Canadian context. To address this, this thesis presents the findings of a qualitative study that considers 19 interviews with life sentenced people in Canada who are living in the community on parole for life. It draws from standpoint theory and thematic analysis as its methodological approach, centering the experiences of people with the sentence, then broadens to locate individual experiences within the legislative and policy framework that they are embedded within and socially organized by. This approach highlights the ways that life sentences constitute an opaquely administered sentencing regime that is operating in conflict with the listed goals and limits of Canada’s prison system. The goal of Canada’s prison system is to be reintegrative, yet through the administration of the sentence, life sentenced people are both expected to and prevented from reaching this goal. This liberatory research roots analysis in critical legal and political theory, centering the impacts of law in society. It demonstrates that the conditions of parole-for-life are operating without procedural safeguards, fracturing families and creating invisible isolation in the community in particularly harmful manners for Indigenous Peoples, and for the many very young people who are given live sentences in Canada. Building on Agamben’s concept of states of exception, parole-for-life is explored as a rising status of exclusion, pronouncing not just the adverse impacts this status creates for those who are subjected to it, but also the power potentialities that the increasing normalization and presence of this status provides to the state. Broadly, findings offer that the presence of perpetual punishment is changing the nature of the relationship between citizen and state. Practical policy and legislative solutions are offered, emphasizing the need to legislate a process to terminate life sentence parole after a successful behavioral period is demonstrated in the community, which is aligned with international human rights law and the practices of many countries globally.Item Re-worlding the self in graphic narratives—A case study of sense, affect, and mad-centered knowledges of psychosis(2024) Kernan, Luke; Boudreault-Fournier, AlexandrineThis doctoral project, Re-worlding the Self in Graphic Narratives—A Case Study of Sense, Affect, and Mad-Centered Knowledges of Psychosis, collaboratively explores and addresses experiences of psychosis (sensory breaks from reality) with Mad-identifying participants who describe their earliest memories of these interior events from a sensorial and visual perspective. Co-creating an arts-based ethnography of psychosis through the ongoing production of artworks and media, I survey the ways that participants’ narratives of psychosis materialize through visual and poetic representations of their lived experiences of madness. I examine how individuals distressed by psychosis move beyond their symptomatic illnesses and narrowly prescribed identities and find new ground to (re)make themselves through expressive processes. Within a synergetic inter-arts research setting, I led a series of five online workshops with two unique groups of participants, each of whom had prior past episodes of psychosis and were immersed in outpatient mental health services. Participants drew from and upon their interior, emotionally charged experiences during the workshops to develop multisensory and narrative drawings that became both prompt and foundation for subsequent individual interviews. We then collaborated on participant-led comics that became the foundational impetus for re-imagining the ethnographic text. Through this novel approach to arts-based research, I aimed to understand psychosis from empathic, sensorial, and visual perspectives. This project documents, engages, and theorizes the role of “psychosic” imagination and creativity in the lives of ten participants who have experienced psychosis as a life event and were involved in comics-making activities. Here, I track how participants, as cherished Mad interlocutors and co-collaborators, sought to resolve communication and subject-positioning issues that arose from the equally ineffable and challenging dynamics of psychosis and madness. These conflicts were internally registered and spurred a vital set of self-fashioning, polyphonic dialogics that primed my interlocutors for self-transformation and psychosic re-worldings. These collective efforts not only de-center ethnographic practice through research-creation strategies, but they succinctly clarify aspects of how madness and pressured, non-normative consciousness are experienced, generating a set of symbolic, poetic, and visual languages to capture expressions of psychosis. Moreover, as a collaborative research-creation practice, our extensive, year-long work aided in destigmatizing and reframing mental duress. Participants simultaneously developed ways to navigate emotional tensions, challenge points, and affective accruals wrought by psychosis through graphic narrative modalities, offering this practice as one that sees Mad-inclusive systems of living myth intertwined with post-traumatic growth.Item Colonial reproductions of everyday spaces: An analysis of the Empress Hotel(2024) Milanova, Maria; Marin, MaraMy thesis argues that the Empress Hotel functions as a colonial infrastructure that not only normalizes but actively reproduces colonial power dynamics through its spatial organization. This landmark embodies and reinforces historical colonial power structures while simultaneously generating new forms of colonial relations, thereby perpetuating the disruption of Indigenous relationships with the land. I make three arguments about how colonialism and colonial relations are embodied and reproduced through the material and spatial structure of the Empress. First, I argue that the Empress Hotel's strategic location atop reclaimed land asserts colonial domination by rendering Indigenous lands as "waste" to be “civilized”. Second, I argue that the Empress’ architecture, the Baronial-Chateau style inspired by European traditions, symbolizes the Canadian state's efforts to legitimize its colonial project and assert its sovereignty. Third, I argue that the practices and artifacts of colonial spaces, including the themed rooms of the Empress, the Bengal Lounge and Palm Court, and ritualized practices like afternoon tea, recreate colonial social hierarchies and relations. I further argue that the organization of these colonial social spaces is inextricably linked to the production of power, with the two being mutually dependent. By examining the micro-level manifestations of colonial power in the Empress Hotel, I illuminate the broader mechanisms of macro-level political domination. This approach addresses a gap in political science, which traditionally overlooks how power manifests in everyday colonial structures. The study contributes to our understanding of how colonial power manifests in everyday structures by critically expanding Henri Lefebvre's work through integration with Glen Coulthard's notion of "colonial relations" to provide a more comprehensive framework for analyzing settler colonialism and the reproduction of colonial relations spatially. At the same time, the research also discloses the potential for resistance in relation to alternative ways of inhabiting these spaces. In so doing, I emphasize the need for critical engagement with the spaces we inhabit and experience.Item “A new way of working” – Expanding First Nations involvement in British Columbia’s renewable energy sector(2024) Peng, Lauren; Shaw, KarenaAs the climate crisis worsens, there is growing urgency to transition away from GHG intensive energy systems, which has prompted extensive efforts to advance renewable energy alternatives. Within British Columbia (BC), the Provincial Government has set emissions reduction targets which will stimulate a need for more clean energy sources to support decarbonization efforts in the years to come. Over the last few decades, many First Nations in BC have expanded their involvement in renewable energy development on their territories through small-scale and community-owned renewable energy projects, advancing these projects as an avenue for self-determination, a source of economic opportunity, self-sufficiency, and energy security. Many First Nations in BC have expressed a desire to continue growing their involvement in the renewable energy sector and are well positioned to meet the growing demand for clean electricity sources. However, many have also faced institutional barriers that have stymied their efforts to advance these ambitions. This thesis begins by developing an analysis of how energy policy and governance in BC shapes opportunities for First Nations involvement in renewable energy development. It then draws upon interviews with Indigenous and non-Indigenous experts working in the field of renewable energy development to better understand First Nations’ aspirations for involvement in BC’s renewable energy sector, the barriers that are inhibiting these aspirations, and potential pathways to overcome these barriers. Interviewees expressed clear aspirations for self-determination, self-sufficiency, and meaningful partnerships across the electricity system. Insights from interviews combined with the policy and landscape analysis clarified barriers embedded in utility models, mandates, policies, and processes that constrain these aspirations, and highlighted potential pathways to more effectively advance goals of ‘reconciliation’ through the renewable energy sector. Findings emphasize that First Nations are not solely seeking to expand their involvement in energy at the local level, but are also seeking fundamental change to the electricity system that would enable meaningful, self-determined partnerships with the state where First Nations can play a role in energy governance more broadly, and can work collaboratively with the state to achieve shared goals. Advancing these goals will require establishing trust-based and equitable partnerships between First Nations and state energy actors to enable greater collaboration within energy governance and decision-making, as well as institutional changes to policies, decision-making processes, and mandates in support of this work.Item Pursuit of the unknown: Understanding refugee decision-making(2024) Hashemirahaghi, Seyedmehdi; Watson, Scott D.The 2015 refugee ‘crisis’ resulted in one of the largest refugee movements since the Second World War. The construction of refugee movements as a ‘crisis’ contributed to state centric responses primarily dehumanizing refugees and promoting restrictive protection policies. The 2015 refugee ‘crisis’ was a reminder that there is a gap in understanding how refugees make their decisions along their journeys as refugee movements of the mid-2010s defied the conventional expectations, in both legal and theoretical realms, for refugee behavior. To fill these gaps, this study explores refugee decision-making by investigating refugees’ own stories. The primary question driving this study is how do refugees make their decisions? And why do different refugees make different decisions within seemingly similar situations? Building on legal, historical, and theoretical accounts of refugee behavior, this study proposes a new theoretical framework, called Interactive Decision-making Model. This model is composed of three main components: spectrum of coercion, spectrum of time, and decision-making environment. Through interactions with these components, refugees make their decisions along their journeys. Utilizing a qualitative narrative analysis approach, this study develops and explores the viability of this model. Through interviews with forty-four refugees from Iran and Syria, it demonstrates how coercion, time, and decision-making environment inform refugees’ decisions throughout their journeys. The findings of these interviews highlight the diversity of refugees’ experiences and behaviors. They also call for more inclusive protection policies that are reflective of refugees’ experiences and decision-making processes.Item Latent Iisights into measurement of academic challenges: An examination of perceived academic challenges scale(2024) Rostampour, Ramin; Hadwin, AllysonBackground: Students often face diverse challenges throughout their educational journey that can significantly impact their learning process. While extensive research has explored self-regulatory perceptions and behaviors that promote student success, there remains a notable gap in understanding and measuring the specific challenges students encounter during their studying. Objectives: To conduct a comprehensive psychometric examination of the Perceived Academic Challenges scale, a self-assessment and diagnostic tool which measures six dimensions of perceived academic challenges: motivation, initiating and sustaining engagement, goal and time management, cognition, metacognition, and social and emotional challenges. These dimensions correspond to key self-regulatory areas linked to success in self-regulated learning. Methods: Four university student samples from six Canadian institutions (total N= 3293) were used. The psychometric process employed both item-level and scale-level analyses, including polytomous item response theory (IRT) and advanced structural equation modeling techniques. Multidimensionality was explored using bifactor and second-order measurement models, and Exploratory Structural Equation Modeling (ESEM). A complementary person-centered study examined intraindividual profiles of challenges. The scale's predictive utility was examined through associations with criterion constructs: students' GPA expectations, self-efficacy for GPA, and actual end-of-semester GPA. Results: IRT analyses confirmed the precision of individual items in assessing various levels of the intended constructs and flagged imprecise items for potential revision. A bifactor ESEM approach demonstrated the best fit to the data, revealing a general factor underlying responses, with cross-loadings enhancing construct interpretability. The general factor and metacognitive factor were found to be highly overlapping, leading to modifications on the measurement model to anchor the general factor to metacognitive challenges. Findings confirmed the measure's adequate psychometric properties, the adequacy of its total score, and its relevance to the criterion constructs. Conclusion: The Academic Challenges scale was found to represent constructs as intended and to be reliable for assessing students' academic challenges across the six dimensions. This dissertation underscores the critical need to refine self-reported measures of students' experiences, emphasizing their unique insights into subjective experiences that other types of data cannot capture. Recommendations for further improvements of the scale are provided, emphasizing the need for continuous refinement of measures in educational research.Item Traffic tracking and air quality: A holistic approach to predicting traffic-related air pollution(2024) Deveer, Laura Ahinee; Minet, LauraOn-road transportation has long been a significant contributor to air pollution in cities. Over the past few decades, the transportation sector, which has been targeted by major regulations, has undergone substantial changes. These changes include a shift in vehicle fleet composition and both natural and artificial alterations to traffic patterns. Despite the importance of on-road transportation for urban mobility, it remains a major source of air pollution and a public health challenge. Therefore, it is essential to accurately measure and model the temporal and spatial distribution of traffic-related air pollution. In that way, targeted implementations can be made to combat the adverse health effects associated to the exposure to these pollutants. In this thesis, we investigate the potential of low-cost methods to accurately estimate air pollutant concentrations. To this end, we employed modern traffic tracking technologies with low-cost sensors and machine learning techniques. The research addresses the effectiveness of leveraging these technologies to understand the factors and interactions that influence air quality. Chapter 2 predicts real-time air pollutant concentrations with high accuracy across pollutants using traffic videos and machine learning algorithms. The results reveal the superior performance of non-linear models over linear models. In addition, the Shapley additive explanation plots employed in this study effectively captured the intricate relationships between pollutants and their predictors. Chapter 3 examines the influences of traffic, particularly from cruise ship activities, on local air quality in James Bay, Victoria, BC. Results indicate that both emissions from traffic and cruise ship activities affected air quality. The integration of low-cost sensors with these traffic tracking technologies proves crucial for accurate air quality analysis and allows for context-specific and real-time assessments, providing valuable insights for policy makers and urban planners.