Effects of Human Activities and Natural Processes on Wolverine Populations

Understanding the dynamics of large-carnivore populations is critical in light of expanding human activities that may alter their natural habitats. In this thesis, I examine the effects of both human-induced disturbances and natural environmental factors, on the population density and habitat use of wolverines (Gulo gulo) in the Canadian Rocky Mountains and the Columbia Mountains of British Columbia and Alberta, Canada. Carnivores, such as wolverines, are sensitive to human-caused mortality and large-scale habitat changes as they roam widely and have low reproductive rates and densities. Human impacts, including overharvest, ecosystem changes due to resource extraction and additional decreases in habitat quality because of recreation, may pose growing challenges to wolverine conservation. I employed non-invasive genetic sampling, remote camera surveys and spatial capture-recapture techniques to assess population trends and offer critical insights into how wolverines respond to both human-caused pressures and natural environmental factors. Sampling at a population scale, my research provides evidence that recreational activities not only impact habitat use, but can have detrimental impacts on wolverine population density, even within protected areas. While protected areas appear to be vital for maintaining wolverine populations, especially if they are harvested on unprotected lands, edge effects and high disturbance levels from recreation may compromise their effectiveness. My work thus suggests that human disturbances have both direct and indirect effects on wolverine density, with female wolverines being particularly impacted. Areas with higher road density and recreational activity exhibit lower population densities, highlighting the need to manage human access if protection is a societal objective. I also investigated the role of bottom-up factors, such as persistent spring snow cover, which is associated with wolverine ecology and reproduction. The interaction between natural and anthropogenic factors creates complex patterns in habitat use, but by identifying key drivers of population decline, I offer important conservation implications, emphasizing the necessity for integrated management strategies that balance human land use with the needs of wildlife species. These findings underscore the broader applicability of my research to other carnivores facing similar threats, providing a foundation for future conservation efforts

AlGeoRhythm: Exploring the Geometric Patterns in Poetry Rhythms and the Generation of Beat-Aligned Poetic Texts

This dissertation investigates computational poetry through the lens of two main representatives: rhythms and metaphors. It begins by exploring the inherent challenges of creative data generation in an era of rapid machine learning advancement, questioning what constitutes creativity and how it is being modeled in language. The theoretical part of this research extends the utility of computational geometric methods to analyze rhythmic patterns in Arabic and English poetry. The research identifies key geometric features that likely contribute to the aesthetic appeal of certain rhythmic compositions and hint at universal principles shared in poetry and music. Building on these insights, the thesis utilize byte-level transformer models to align poetic text with specific beat patterns through substitution and rephrasing training objectives. In parallel, an exploration into metaphor detection is presented through an ensemble of encoder-based transformer models that combines word sense disambiguation with contrastive learning to contrast between a word's contextual and basic meanings. Human evaluation studies were conducted to reinforce the theoretical and the generation work, confirming that certain non-standard generated rhythms have been identified to have an aesthetic appeal to the participants as much as standard rhythms. Participants also confirmed the accuracy of our models to align text with beat patterns while maintaining a reasonable level of poetic quality. This thesis contributes innovative frameworks and computational methodologies to bridge theoretical insights with practical applications in the algorithmic composition of ``good" poetic rhythms and creative poetic language, offering promising avenues for future research

Investigating the Reconstitution and Function of Peritoneal Cavity Macrophages after LPS-induced Peritonitis

The tissue-resident macrophages of the peritoneum are sentinel immune cells, in constant motion within the serous fluid of the abdomen. Like most tissue macrophages, the GATA6+ large peritoneal macrophages (LPMs) are responsible for the clearance and removal of pathogens that may break through the defensive barriers of the abdomen. However, upon inflammation incurred by the response of the immune system to foreign matter, the LPM population seemingly disappears and down-regulates its signature cell markers. The aim of this thesis project was to elucidate the fate of the large peritoneal macrophages after stimulation with an inflammatory agent as well as the eventual return of the macrophage resident cell population. This work used genetically engineered, LPM and monocyte-derived fate mapping mice to track the location and re-constitution of the large peritoneal cavity macrophage population after lipopolysaccharide (LPS)-induced peritonitis. A double recombinase, GATA6 and Lyz-M genetically driven fate mapping mouse was engineered to report on the large peritoneal population in response to a biologically relevant dose of lipopolysaccharide. Spectral flow cytometry and confocal whole mount imaging was used to investigate the ‘disappearance’ of LPM from the peritoneal cavity upon stimulation of the noxious agent. After 10 days of LPS administration, the LPM fate mapping mouse and the Ms4a3-monocyte derived reporter mouse were used to illustrate the repopulation of endogenous LPMs and newly recruited monocytes that contribute to the macrophage pool upon resolution of inflammation. My findings suggest that LPMs concentrate and localize at ‘milky spots’ of the omentum. Upon resolution of inflammation, the resident macrophage pool was made up both endogenous GATA6 and bone marrow-derived macrophages

A (2 + 1)-Party One-Instruction Set Processor for Private Function Evaluation

Secure multiparty computation (MPC) is a powerful cryptographic technique which allows mutually distrusting parties to compute a function on their shared inputs. MPC can be viewed as encompassing two main categories, secure function evaluation (SFE) where the function being computed is known to all parties, but the input data is private, and private function evaluation (PFE) where one party has a private function while the other party has private data as input to the function. A major reason MPC has not seen more widespread adoption is due to the fact that to create an efficient MPC protocol for a specific function, traditionally expert cryptographers have had to hand build a custom protocol. One attempt to remedy this issue is the creation of MPC compilers which take as input code in a high-level language and output an optimized MPC protocol. Another attempt has been garbled processors which are hand optimized MPC protocols which emulate specific computer architectures. This thesis presents MPC SUBLEQ, a garbled processor designed for the PFE setting. In particular, it emulates the subtract-and-branch-if-less-than-or-equal-to-zero (SUBLEQ) one-instruction set computer (OISC). Because SUBLEQ only has a single instruction, there is no overhead cost to hide what instruction is currently being executed as there is only one instruction to execute. The data which the instruction is executing on must remain private, but the instruction itself is always known. We also test and compare MPC SUBLEQ against GC-Lite, a similar garbled processor designed for PFE using the SUBBLE OISC, a weaker version of SUBLEQ. We show that MPC SUBLEQ dramatically outperforms GC-Lite due to the significantly lower local computation and online communication costs

Quantification of nitrogen-based compounds: Total N abundance in poultry farms and the development of an ammonia sensor calibration method

Ammonia (NH3) is the most abundant alkaline gas in the atmosphere and is a major contributor to aerosol formation. As agricultural practices are a major atmospheric source of NH3, accurate quantification of N-based compounds in agricultural settings are needed. This thesis describes measurements of total nitrogen (Nt) in 14 Alberta poultry barns using a commercial chemiluminescence (CL) NO/NOx/Nt instrument. The CL analyzer's response to NH3 was calibrated using a newly developed calibration method in which gas streams containing NH3 were generated from ammonium bicarbonate. Using a simple gas delivery setup consisting of two dilution stages and a line heater, the NH3 output was calibrated by quantifying the stoichi-ometric co-emission of CO2 with a relatively inexpensive non-dispersive infrared (NDIR) spec-trometer. Further, the CL analyzer was equipped with an automated inlet valve to differentiate between gas- and aerosol-phase Nt. Mixing ratios of Nt, NOx, NO, and CO2 (which was monitored using a passive NDIR monitor) varied greatly between each poultry barn. While NOx levels were higher than ambient, they were negligible compared to Nt. Further, gas- and aerosol-phase Nt concentrations were equal, indicat-ing most nitrogen was present in the gas-phase. Normalized emission rates for NH3 were calcu-lated, which were (0.09±0.11) g bird-1 d-1 on average. The Nt levels complied with the industry's air quality (AQ) NH3 standard of < 25 ppmv

Indigenous Burn Survivors Experiences of Injury, Care, and Social Reintegration

Burn injuries have potential for significant long-term impact and require highly specialized treatment to limit sequalae. Indigenous people are impacted by burn injuries at disproportionate rates across colonized countries of Canada, United States, Australia and New Zealand. This study aimed to understand Indigenous burn survivors’ experiences of injury, care, and social reintegration. Hermeneutic methodology was employed with efforts to use a decolonizing approach to the research to understand survivors’ experiences. Three Indigenous individuals who had suffered significant integumentary injuries were interviewed to deepen understanding of the topic. Interpretations from this study revealed that preforming healthcare research with Indigenous people requires particular considerations to understand that what is heard by researchers may not reflect the whole story; stigma from scarring and lateral violence can significantly influence burn survivors reintegration to their communities to where they no longer “fit” the same way; sequalae from injuries result in community role disruption and reworking of identities that effect the individuals ability to connect with their Indigenous heritage as well as impact the larger community; and Indigenous individuals experience unique challenges in accessing specialized burn care. I conclude by recognizing the ongoing impacts of colonization, how anti-Indigenous racism threads through each survivor’s story. Injuries occur within complexities often left unaddressed in current healthcare practices allowing assumptions to perpetuate through care and disconnect providers from survivors’ experience. This study offers healthcare providers an opportunity to better understand Indigenous burn survivors and reflect on how assumptions impact daily care practices

Comprehensive Simulation Studies on Hydrogen-Oriented Underground Coal Gasification Across Different Scales

The hydrogen-oriented underground coal gasification (HUCG) technology is emerging as a highly promising approach to address energy demand and environmental concerns while producing clean hydrogen from abundant but inaccessible coal resources. Due to the complexity and high costs of field tests and the challenges of simulating underground conditions in the laboratory, numerical simulation is an effective method for studying the HUCG process. Therefore, this dissertation investigates the mechanisms and feasibility of hydrogen production and storage in UCG systems through multi-scale modeling and simulation approaches. The research includes large-scale numerical simulations and molecular dynamics (MD) simulations to address key challenges in UCG-driven hydrogen production and in-situ hydrogen storage. In the first study, a three-dimensional UCG model with water injection was developed to investigate the evolution of a pore structure and permeability in a coal seam during cavity formation. The results demonstrate that water injection affects both the growth trajectory of a cavity and coal pore characteristics, revealing the complex interactions between hydrological and thermochemical processes. The second study focuses on optimizing hydrogen production through water-assisted strategies in large-scale UCG. Different injection locations and perforations were compared, and the mechanism of hydrogen production and a better strategy of the water injection can be figured out. In addition, a novel water injection technique, which can lead to a fivefold increase in daily hydrogen output and improved cavity stability, was proposed to effectively increase hydrogen production. Finally, molecular dynamics simulations were employed to examine the adsorption and diffusion behaviors of hydrogen and other syngas components (CH₄, CO₂) in low-rank coal. The results showed that H₂ has weak adsorption but high mobility in coal, whereas CO₂ exhibits strong interactions. These findings provide microscopic insights into hydrogen behavior, discussing the feasibility of UCG cavities for in-situ hydrogen storage

The Association between Family Visitation and Adverse Events in the Critically Ill: A Retrospective Cohort Study

Despite advances in treating critical illness, nearly 25% of Intensive Care Unit (ICU) patients experience an adverse event (unintended consequence of medical treatment such as infections, bleeding, or falls). These adverse events can lead to severe patient harm such as disability or death, however, up to 50% of all adverse events are preventable. While ICU healthcare professionals work to minimize adverse events, family (e.g., loved ones, friends) tend to know the patient best, and may be an underutilized resource in identifying and preventing adverse events. The objectives of this thesis are to determine the association between in-person ICU family presence and the 1) incidence rate, and 2) type of in-hospital adverse events in ICU patients. This thesis used a retrospective cohort design and linked two administrative health databases of adult patients admitted to 15 medical, surgical, or neurological ICUs in Alberta, Canada between January 1, 2014 and December 31, 2019. The exposure (family presence) was determined from medical records using a validated free-text natural language processing algorithm. The outcome (adverse event number and type) were determined from the medical record using 17 validated case definitions. We used multivariable mixed-effects negative binomial regression to determine the association between ICU family presence and adverse event incidence rate; and used multivariable mixed-effects logistic regression to determine the association between ICU family presence and adverse event type. We used the Bonferroni correction to reduce spurious findings due to multiple comparisons. This study included records from 26,100 ICU patients; of which 4,451 patients experienced at least one in-hospital adverse event (17.1%). In-person ICU family visits were associated with a significantly reduced incident rate ratio (IRR) of adverse events in patients 30-39 years of age, and patients 50 years of age or older. There were no significant associations between family visitation and adverse event types after adjusting for covariates. The results in this thesis suggest that in-person family presence may reduce the number of in-hospital adverse events in ICU patients. Additional prospective studies are required to clarify the role families play in influencing adverse events

Islamophobia in Canadian Nursing: An Interpretive Phenomenological Study

Muslim Nurses in Canada are experiencing Islamophobia in the workplace as well as in educational institutions. These experiences result in increased mental distress for these nurses, social isolation at the workplace, and considerations of leaving the nursing profession. This thesis explores the experiences of Islamophobia for Registered Nurses who wear the hijab at work in Canada. This study is grounded in Critical Race Theory and aims to answer the following research question: What are the experiences of Islamophobia for female Canadian Registered Nurses who wear the hijab? A total of six participants were interviewed, and the results were analyzed using the Interpretative Phenomenological Analysis method. Muslim nurses’ experiences were characterized by their sense of belonging. Key findings consist of the experiences of Islamophobia being related to the negative stereotypical identity of what it means to be a Muslim woman being associated with these nurses, how they discover their own identity as nurses and finally, how they reconcile their personal and social identities as Muslim women with their identity as Registered Nurses. This study adds to the literature on this topic by uncovering the internal process of self-discovery that Muslim nurses go through after experiencing Islamophobia through being assigned an identity. This process helps them to discover their own identities as well as reconcile what it means to them to be Muslim nurses, thus allowing them to be able to practice comfortably at the workplace. Recommendations of this study are that policy changes should be enacted which protect Muslim nurses and work to reduce the normalization of Islamophobia and the prejudiced beliefs about Muslims in the nursing profession to prevent incidents of Islamophobia. Secondly, more education needs be provided to nursing students as well as staff regarding anti-racism and Islamophobia to encourage the creation of supportive nursing places. Finally, more support needs to be provided to Muslim nurses who are experiencing Islamophobia at the workplace

Two-Dimensional Materials as Electrocatalysts for High-Performance Lithium-Sulfur Batteries

Lithium-ion batteries (LiB) represent state-of-the-art technology in energy storage and power, everything from portable electronic devices to grid-scale energy storage. However, LiB cannot meet future energy demands that require high specific energy and longer cycle life for various rapidly progressing battery applications. Among many other proposed new battery models, Lithium-Sulfur (Li-S) batteries are considered a potential candidate for future energy storage devices due to their significantly higher theoretical specific capacity of 1675 mA h g-1 and high theoretical energy density (2600 Wh kg-1 and 2800 Wh L-1). However, the shuttle effects of lithium polysulfides (LiPSs) and the sluggish reaction kinetics are significant barriers to the commercialization of Li-S batteries. This thesis addresses these challenges through computational and experimental investigations focusing on advanced electrocatalysts. Firstly, density functional theory (DFT) studies on vanadium disulfide (VS2) explored its ability to trap lithium polysulfides (LiPS) and enhance the sulfur reduction reaction (SRR). Results demonstrated moderate LiPS binding and superior electrocatalytic activity of the VS2 (001) facet, significantly lowering energy barriers for LiPS conversion. Secondly, a lamellar stacked VS₂/MoS₂ nanoflower heterostructure was synthesized, combining the conductivity of VS2 with the catalytic activity of MoS2 to effectively mitigate the shuttle effect. Electrochemical testing demonstrates excellent performance for VS₂/MoS₂@S cathodes. It delivers an initial discharge-specific capacity of 1353 mAh g-1 at 0.1 C, and even at a high current density of 1 C, the capacity remains as high as 925 mAh g-1. Finally, a comprehensive DFT study evaluated two-dimensional MXenes as potential electrocatalysts, revealing their moderate LiPS binding affinity and identifying Ta2CO2, Zr2NO2, and Mo2NO2 as promising candidates with lower thermodynamic overpotentials for the SRR. This research provides critical insights into the design of advanced electrocatalysts, ultimately contributing to the development of high-performance Li-S batteries with enhanced efficiency and cycle life