Open Theses and Dissertations
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Item Open Access Magnetic Field Characterisation for Gravitational Free Fall Measurements of Antihydrogen in the ALPHA-g Experiment.(2024-09-19) Powell, Adam Michael William; Friesen, Timothy; Thompson, Robert Ian; Wieser, Michael; Cully, Christopher; Malbrunot-Ettenuer, StephanThe bound state of an antiproton and positron, antihydrogen, is an ideal test particle for comparisons between matter and antimatter as hydrogen has been studied extensively through history both experimentally and theoretically. The Antihydrogen Laser Physics Apparatus (ALPHA) collaboration has made significant progress on antihydrogen trapping, cooling, and spectroscopy in recent years.In a new apparatus, ALPHA-g, the collaboration aims to probe the effects of gravity on antimatter. This thesis will focus on the first measurement of the free-fall (or gravitational motion) of antimatter and the magnetic field measurements essential to this observation. The ALPHA apparatus, particularly the ALPHA-g experiment, will be discussed in detail. This thesis will outline hardware improvements to the ALPHA-g's Penning trap as well as the microwave injection path. These developments were critical for the operation of ALPHA-g and electron cyclotron resonance (ECR) magnetometry. In addition, a design for a new Penning trap for ALPHA-g is shown that will be key in future measurements. The electron cyclotron resonance (ECR) magnetometry technique used in ALPHA will be introduced. ECR is needed to measure, set, and monitor the magnetic fields in ALPHA-g, ECR is then the essential tool at the center of successful measurements using ALPHA-g. ECR was also used to constrain major systematic uncertainties through a host of applications of the technique in novel ways including fast repeating ECR and multiple simultaneous locations. This work is the first application of this technique in a high magnetic field gradient, which was an important obstacle to overcome in characterising the magnetic fields in ALPHA-g. This breakthrough result of the first ALPHA-g measurement produced a ratio of antihydrogen gravitational acceleration and ``normal gravity" of $a_{\bar{g}}/g =0.75 \pm 0.13(\text{statistical + systematic}) \pm 0.16 (\text{simulation})$. This ratio is consistent (within errors) with no difference between matter and antimatter gravity. This result has allowed ALPHA to rule out extreme difference between matter and antimatter such as no gravitational interaction or repulsive gravity.Item Open Access Basal autotrophic and heterotrophic food web responses to municipal wastewater effluent exposure in the Bow River, Alberta and experimental streams at Advancing Canadian Water Assets(2024-09-19) Sayles, Breanna K.; Wrona, Frederick J.; Jackson, Leland J.; Culp, Joseph M.Municipal wastewater effluent (MWWE) release into urban rivers act as a main point source of nutrients and environmental substances of concern (ESOCs), such as pharmaceuticals and personal care products, which can alter the water quality of receiving waters and the physiology and ecology of aquatic organisms. Over the years, there have been active efforts to reduce the impact of MWWE on the Bow River’s ecosystem health; however, understanding potential nutrient-ESOC interactions and potential impacts on aquatic organisms are still largely unknown. This study examined the changes in basal autotrophic and heterotrophic community characteristics and responses to Municipal Wastewater Effluent (MWWE) exposures both in the Bow River and in artificial streams at Advancing Canadian Water Assets (ACWA). A main goal was to better understand the responses of riverine biofilms to MWWE complex mixtures and identify potential interactions between nutrients and ESOCs. In the Bow River, increasing MWWE loadings enhanced heterotroph decomposition rates and ash free dry mass (AFDM) accumulation, and the main driver of change identified was nutrient enrichment. In contrast, experiments in the artificial streams found increasing MWWE concentration (0-15 % v/v) suppressed autotroph biomass, produced a subsidy-stress pattern in biofilm AFDM, and had no impact on organic matter decomposition rates. Nutrient-ESOC interactions were suggested as a potential cause for the patterns observed in the artificial streams. In both riverine and stream systems, MWWE impacts consistently showed a shift towards more heterotroph dominant biofilm communities with time (as quantified by the autotrophic index (AI)). The observed MWWE effects on biofilm community composition shift show potential to influence efficient energy transfer to higher trophic levels.Item Open Access A Comparitive Evaluation of GAN Architectures for Generating Synthetic Cloud Workloads(2024-09-17) Sharifisadr, Niloofar; Amannejad, Yasaman; Krishnamurthy, Diwakar; Ginde, Grouri; Far, Behrouz; Abdellatif, AhmadGenerative Adversarial Networks (GANs) are highly successful in areas such as image generation. However, their efficacy in generating time series data, specifically for cloud workload applications, is not well-established. Several GAN architectures are proposed for time series generation, but there is a lack of comprehensive study on performance of these models in cloud workload generation domain. Additionally, prior research has not thoroughly explored the performance of models in relation to dataset attributes, including the length of the data, its seasonality and stationarity. This research addresses these gaps. I conduct a comparative study of four GAN architectures, including TimeGAN, RGAN, TTS-GAN, and V-GAN, using three real-world datasets. The goal is to develop a framework for selecting the best GAN model for cloud workload data generation. I introduce a method to preprocess and characterize the datasets based on existing statistical measures. %, considering varying attributes. To compare the data generated by the models, both qualitatively and quantitatively, I employ them on datasets with diverse characteristics to synthesize data. The synthesized data is then used as input for a microservice application. Response times are measured for both real and synthetic data for comparison. The findings reveal the capabilities and limitations of each model, with regards to input data characteristics. TimeGAN and TTS-GAN are top performing models across various settings. TimeGAN excels at capturing short term temporal dynamics, while TTS-GAN outperforms in capturing long term dependencies. The transformer-based architecture employed in TTS-GAN makes it adept for handling seasonal data across both short and long sequence lengths. Conversely, TimeGAN demonstrates superior performance in capturing seasonal data over shorter periods. The empirical evaluation on the microservice application further confirms the efficacy and applicability of the proposed framework in a realistic testbed setting. This study serves as an empirical guide for practitioners and researchers to choose the most appropriate GAN based on the unique characteristics of their data.Item Open Access Potential for Prebiotic Fiber to Attenuate Obesity Risk and Insulin Resistance in Rat Offspring Exposed to a Maternal Obesogenic Diet with Low-Dose Aspartame Consumption(2024-09-17) Venegas Silva, Gabriel Andres; Reimer, Raylene A.; Shearer, Jane; Thompson, Jennifer A.Maternal diet during pregnancy has a lasting impact on offspring health. Our objective was to examine if offspring postnatal oligofructose prebiotic fibre (Pre) intake could mitigate metabolic risks of a maternal obesogenic diet plus aspartame (APM) consumption. Following 11 weeks of obesity induction, female Sprague-Dawley rats (n=29) were randomized during pregnancy and lactation to a high fat/sucrose (HFS) diet with water control (CTR) or HFS with APM (7mg/kg/day) in drinking water. Offspring of each maternal group were weaned onto the following four groups: CTR-CTR, APM-CTR, CTR-Pre, and APM-Pre from 3-12 weeks of age. Energy intake, body weight, fecal microbiota, and metabolic outcomes including body composition, glucose tolerance, and liver triglycerides were assessed in dams and offspring. Metabolic disturbances were not observed in APM dams yet maternal APM exposure with HFS diet increased hepatic triglyceride levels (p=0.046) and influenced gut microbiota beta diversity (p=0.029) in 3-week old weanlings, and increased body weight in young male offspring at 4-5 weeks of age (p<0.05). By week 12, females in the APM-Pre group had lower body weight (p=0.046), greater (%) lean mass (p=0.044), reduced (%) body fat (p=0.047) compared to CTR-CTR; The female APM-Pre group also had greater (%) lean mass (p=0.006) and reduced (%) body fat (p=0.009) than the APM-CTR group. Postnatal Pre intake improved glucose tolerance and AUC in males (p<0.001) with no effect in females and worsened insulin sensitivity in APM-Pre females (p<0.05) relative to CTR-CTR females with no effect in males. In adult offspring, Pre intake reduced alpha diversity (p<0.001), affected beta diversity (p<0.001), and increased the relative abundance of Bifidobacterium, Blautia, and Streptococcus while decreasing 5 other bacteria including Romboutsia. Maternal APM intake with an HFS diet may disrupt weight homeostasis, increase hepatic triglycerides and gut microbiota in young offspring with no effect of APM seen in later life. Postnatal Pre intake by offspring exposed to a maternal obesogenic diet is linked to lower body weight and improved body composition predominantly seen in female rats with improved glucose control seen in adult male rats. Noticeable shifts in gut microbiota secondary to Pre consumption may mediate these changes.Item Open Access Development of High-Strength Composites with Sustainable Fibers for Structural Applications(2024-09-18) Sarker, Rahul; Kibria, Md Golam; Hu, Jinguang; Sumon, Kazi Z; Trifkovic, MilanaDespite Canada's abundant biomass resources, a significant portion remains underutilized due to a lack of large-scale industrial applications. This research explores the utilization of low-value biomass, specifically aspen fiber, in fused filament fabrication (FFF) to develop biocomposites. Various chemical treatments (NaOH, silane, and maleic anhydride (MA)) were applied to improve fiber compatibility with polylactic acid (PLA). Both untreated and treated fibers at 10% loading were blended with PLA and extruded into 3D printable filaments. Results showed that MA-treated fiber-based composites had around 15% higher tensile strength and modulus, along with a 30% enhancement in storage modulus than untreated ones. Additionally, a 25% reduction in water uptake was witnessed in MA-treated aspen-derived composites. Successfully 3D-printed biocomposites with up to 30% fiber loading were achieved without nozzle clogging, though higher fiber loading negatively impacted mechanical properties. This study also investigates the potential of CNT incorporation in asphaltene-derived carbon fibers and the impact of carbon fiber reinforcement to enhance the mechanical properties of biocomposites. This research contributes to the development of sustainable and high-performance composite materials by exploring the potential of underutilized resources and advanced manufacturing techniques.Item Open Access Event-Based Precipitation Patterns of Ring Current Electrons Observed by Riometers(2024-09-18) Keenan, Christian; Spanswick, Emma Louise; Donovan, Eric F; Knudsen, David J; Wieser, Michael EA primary loss mechanism for high-energy particles in the Earth’s ring current is precipitation into the ionosphere. Precipitation has been historically difficult to quantify since it is primarily studied with in situ satellites. With in situ approaches, it is difficult to understand the spatial-temporal nature of the precipitation. In this thesis, ground-based measurements of high-energy electron precipitation are used to characterize and classify ring current electron precipitation events based on their spatial extent and temporal behaviour. As will be shown, there are multiple types of events visible in the ground-based data. When separated in this manner, these event types display different characteristics that demonstrate they are likely connected to different precipitation mechanisms. These results are important because they shed light on dominant wave-particle interactions in the ring current region, and pave the way for more detailed studies of wave-particle coupling and quantifying ring current losses.Item Open Access Examining the activation of xenobiotic receptors using microbial metabolites and chemical ligands(2024-09-18) Shenoda, Eva Ibrahim Gorgy; Hirota, Simon; Nasser, Yasmin; McCafferty, Donna-MarieThe aryl hydrocarbon receptor (AhR) and pregnane X receptor (PXR) are key xenobiotic receptors involved in regulating chemical metabolism and detoxification. Traditionally, these receptors were known for mediating toxic responses by sensing and responding to chemicals. Recent research shows their role in maintaining gut homeostasis and regulating inflammation. However, the mechanisms by which they induce these responses are not clear. This thesis examines whether the activation of AhR and PXR in epithelial cells by microbial metabolites versus chemical ligands drives unique transcriptional responses and could explain differences in beneficial versus deleterious biological outcomes in the host. PXR and AhR were activated with indole-3-propionic acid (IPA) and indole-3-pyruvic acid (IPyA) as microbial metabolites, and pregnenolone 16α-carbonitrile (PCN) and 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD) as chemical ligands, respectively. We compared responses to these ligands, revealing significant gene expression differences. Further analysis showed both IPyA and TCDD activated genes involved in hypoxia-inducible factor (HIF) signaling and metabolism. IPyA upregulated genes for ATP synthesis and purine biosynthesis, while TCDD promoted genes related to cell cycle, cancer, and apoptosis. Given that AhR translocates to the nucleus upon activation, we hypothesized that the differences in transcriptomic responses and gene induction might be attributed to differences in nuclear translocation of AhR, with TCDD potentially inducing greater nuclear translocation compared to IPyA. To test this hypothesis, we established a cellular fractionation protocol for organoids. However, our results revealed no significant difference in AhR nuclear translocation between the two treatments, suggesting that other factors may affect gene expression in the AhR pathway. These findings highlight AhR and PXR's complex roles in gut health and inflammation, suggesting receptor activation can have both adverse and beneficial effects. This research enhances our understanding of AhR and PXR mechanisms and their potential for therapeutic strategies targeting gut disorders and inflammation.Item Open Access Mechanisms of Mycophenolic Acid-Induced Gastrointestinal Toxicity and Potential Therapeutic Interventions in Primary Mouse Colonic Organoids(2024-09-17) Mack-Bowles, Brenan; Greenway, Steven; Hirota, Simon; Lewis, IanMycophenolate Mofetil (MMF) is a commonly prescribed immunosuppressant that demonstrates important clinical relevance. However, MMF therapy is linked to frequent gastrointestinal (GI) side effects that limit its use. Little is known about the mechanisms underlying MMF-induced GI injury. Using a primary mouse colon organoid model, we have found that mycophenolic acid (MPA), the pharmacologically active metabolite of MMF, significantly alters intestinal barrier function and permeability through modulation of tight junctions. RNA sequencing revealed that MPA significantly disrupted pathways related to cell cycle regulation, DNA replication, cytoskeleton dynamics, and suppression of senescence. MPA was observed to significantly reduce cellular proliferation, which was ameliorated through guanosine supplementation. Addition of exogenous guanosine was also observed to significantly restore barrier function back to control levels. The guanosine studies presented in this thesis suggest MPA’s inhibition of nucleotide metabolism is not selective for lymphocytes but is broader than originally described. This work represents one of the first investigations of MPA using a colon organoid model, providing critical insights into the intracellular mechanisms of MPA-induced GI toxicity.Item Open Access Alternating Current Stimulation for Essential Tremor(2024-09-18) Adeoti, Adesewa Janet; Martino, Davide; Strzalkowski, Nick; Debert, Chantel; Pichardo, Sam; Asmussen, Mike; Dickinson, JamesEssential tremor is the most common movement disorder, characterized by involuntary rhythmic shaking of the hands, head, trunk, vocal cords, or legs. While the pathophysiological mechanisms of essential tremor are not fully understood, research suggests the involvement of a complex network called the cerebello-thalamo-cortical network. This network includes the inferior olive nuclei, cerebellum, red nucleus, thalamus, and cerebral cortex. Tremor generation in essential tremor is believed to be linked to neurodegeneration, abnormalities in a central oscillatory network, or dysfunction of the inhibitory neurotransmitter gamma-aminobutyric acid. Current treatments for essential tremor are largely unappealing to patients due to either being invasive (surgical), ineffective, and/or causing severe side effects. Previous studies on the impact of ACS in tremor are limited in number and lack a standardized protocol. The aim of this thesis was to investigate the effects of open-loop transcranial and transcutaneous alternating current stimulation on tremor in essential tremor, when delivered over the primary motor cortex and arm at a patient’s dominant tremor frequency. Our results revealed that both transcranial and transcutaneous open-loop alternating current stimulation, delivered to the primary motor cortex and upper arm at a patient’s dominant tremor frequency did not reduce tremor amplitude nor increase tremor ratio. Our study, being the first of its kind, informs on the need for more proof of principle studies in this field that will narrow down the most effective stimulation parameters, and structural targets.Item Open Access Choosing the Right Model of Care Together: Informing an Equitable, Patient-Oriented Decision Aid for In-Person vs Virtual Care of Pediatric Chronic Pain(2024-09-17) Marbil, Mica Gabrielle Aragon; Birnie, Kathryn Ann Manson; Noel, Melanie Elizabeth; McArthur, Brae Anne; Metcalfe, Amy LynnBackground. Pediatric chronic pain management can occur virtually or in-person, but youth with chronic pain and their families may not be involved in decisions about treatment delivery. Decision aids can supplement shared decision-making, a collaborative decision-making approach between patients and health professionals, and promote patient involvement. To inform the development of a decision aid for in-person versus virtual pediatric chronic pain care, this study sought to understand decision-making practices for in-person versus virtual care (part A) and glean desired decision aid features (part B) from patients’ (youth and caregivers) and health professionals’ experiences. Methods. In part A, an online survey on virtual care and decision-making practices was sent to international pediatric pain clinics. Main findings were descriptively summarized. In part B, patients and health professionals completed an online demographics survey and a semi-structured interview on virtual care decision-making experiences to inform decision aid features. Reflexive thematic analysis described common themes. Results. In part A, 67 clinic responses were included. Virtual care constituted <25% of overall pediatric chronic pain management. Families were reported to play the largest role in decisions. Top factors influencing decision-making included new referrals, patient demographics and location, and patient values and preferences. Most clinics did not evaluate in-person versus virtual care decisions. In part B, 11 patients (5 youth, 6 caregivers) and 15 health professionals participated. Four main themes were generated from health professionals, suggesting that the decision aid should: 1) contextualize the individual patient; 2) promote patient engagement and adherence to care; 3) support clinician characteristics and values; and 4) contextualize the decision-making encounter. Three themes created from patient perspectives guide the decision aid to: 1) communicate patient needs and preferences; 2) facilitate navigation of the healthcare system; and 3) build partnership in a paternalistic system. Discussion. Decision-making for in-person versus virtual pediatric chronic pain management is not always shared. Patients and health professionals have individual preferences for decision-making processes. The future decision aid prototype should consider the unique contexts surrounding health professionals and patients to best support decision-making needs.Item Open Access Probing Galactic Magnetism near the Galactic Center with THOR-GC(2024-09-18) Weatherhead, Kierra; Stil, Jeroen; Taylor, Matthew; Friesen, Timothy; Leahy, DenisThe Galactic magnetic field (GMF) permeates the entire Milky Way and plays an important role in the dynamics of the Galaxy. An understanding of the GMF is required to create a comprehensive model of the Galaxy. As the GMF does not radiate, it must be observed indirectly by studying the polarization properties of light. This thesis presents the polarization calibration of the Galactic center extension of the HI/OH/Radio Recombination Line Survey of the Milky Way (THOR-GC). THOR-GC covers the Galactic center, a complex region where the GMF is poorly understood. Polarization observations in THOR-GC can aid in uncovering the nature of the GMF in this region. As well, analysis of a highly polarized transient source identified in THOR-GC reveals that its variability is much larger than previously found and that the source may be a fast-moving neutron star in an extreme environment.Item Open Access An Exploration of Causality in Social Media Data with Knowledge Graphs(2024-09-17) Ravi, Rahul; Rokne, Jon; Ginde, Gouri; Bonnell, Tyler; Abdel Latif, AhmadThis study explores the integration of Knowledge Graphs (KGs) with Large Language Models (LLMs) to perform causal analysis on text-based social media data. The objective is to uncover the underlying causes and sentiments driving discussions around emergency management scenarios such as the Israel-Palestine conflict, thereby providing critical insights for decision-making. The research focuses on advanced techniques to effectively represent text as KGs and retrieve the most suitable context of information to analyse. Various methods are evaluated across different datasets. The proposed model, PRAGyan, combines LLMs and KGs under the Retrieval Augmented Generation (RAG) framework. It utilizes the Neo4J Graph Database to handle continuous real time data and GPT-3.5 Turbo LLM for causal reasoning. This yields more accurate results compared to the baseline model (GPT-3.5 Turbo LLM without KG). Quantitative analysis using metrics such as BLEU and cosine similarity show an improvement by 10%.Item Open Access Index-Calculus Algorithms for Computing Class Groups of Quartic Number Fields(2024-09-17) Marquis, David; Jacobson Jr, Michael John; Scheidler, Renate; Bauer, Mark L; Nguyen, Dang Khoa; Fiori, AndrewWe address the problem of quickly computing the class group and unit group for quartic number fields of large discriminant. Index-calculus algorithms are the fastest way to solve this problem for arbitrary number fields. Our focus is primarily on improvements to relation generation, one of the main stages in an index-calculus algorithm. In the quadratic case, the self-initialization approach to relation generation developed by Jacobson has been very successful, but applying this idea to quartic fields has not been attempted. We present a novel generalization of this approach that is applicable to quartic number fields. Additionally, we characterize the efficiency of our method in terms of the size of the roots of the field’s defining polynomial. We discuss our implementation of a complete index-calculus algorithm using this approach. Our implementation's relation generation produces relations significantly faster than the current state-of-the-art, Magma. Our implementation of the complete algorithm, including the improved relation generation, is faster than Magma for number fields whose defining polynomial has small roots, and is comparable for typical number fields.Item Open Access Ancient Celtic Religion and Western Projections of Indigeneity: A Genealogical Methodology(2024-09-17) Riel, Monique Donna Lee; Cassis, Marica; Muessig, Carolyn; Ginn, Craig; Jenkins, JacquelineThis thesis is a methodological tracing of the ways in which Indigenous peoples and knowledges have been used in studies on ancient Celtic religion from the sixteenth century to the present. Anthropological, sociological, postcolonial, and ontological approaches in the construction of ancient Celtic religious pasts result in popular ideas about ancient Celtic peoples that are drawn from Indigenous peoples but are rarely reflected upon critically. Thus, this work serves as a critical intervention in the way that studies on ancient Celtic religion engage with Indigenous peoples and knowledges. I conclude that: (1) Indigenous practices and knowledges are often filtered through Western onto-epistemology, resulting in Western projections of indigeneity onto ancient Celtic peoples; (2) distinct peoples are continuously collapsed into homogeneity to facilitate the construction of ancient Celtic religious knowledges and practices, and (3) the field should endeavour to move toward relational praxis if we are to continue to draw from Indigenous peoples and knowledges for ancient Western European religious pasts. This genealogical method traces the appropriation and misrepresentation of Indigenous peoples in the field of ancient Celtic religion in particular, but it could be applied in other historical and religious fields wherein Indigenous peoples and practices are used uncritically.Item Open Access Calibration of Two Factor Vasicek and Hull-White Models with Contemporary Data(2024-09-18) Vithanalage, Wathsala Chamodi; Ambagaspitiya, Rohana; Scollnik, David P. M.; Kang, Sang JinThe calibration attempts to understand the intricacies of interest rate dynamics by evaluating the effectiveness of three models: the Two-Factor Vasicek, the One-Factor Hull-White, and the Two-Factor Hull-White. Information from the U. S. Department of the Treasury was used for the estimation of the Two-Factor Vasicek model while the Hull-White models used Bloomberg data. The Vasicek model, based on two factors, is useful with regard to long-term movements in the rate but exhibits certain problems with regard to the calibration of convergence. The Hull-White model, with one-factor, is relatively good at short-term expectations. In contrast, the two-factor Hull-White model is a more sophisticated model that gives a more detailed picture of the behavior of interest rates at different maturities, but the calibration of which involves volatilities is difficult. Hence, regardless of the fact that simpler models may be adequate for some specific purposes, the results show that more complex models can indeed be more accurate if properly fine-tuned. This implies that the selection of a particular model depends on the type characteristics of the data and the application needs; thus, this work highlights the fact that financial modeling is a dynamic process.Item Open Access Issues in Detection of AI-Generated Source Code(2024-09-17) Bukhari, Sufiyan Ahmed; De Carli, Lorenzo; Tan, Peng Seng Benjamin; Abdel Latif, Ahmad Hazzaa KhaderAI coding assistants hold the promise of revolutionizing software development, but they also introduce new risks. The underlying large language models (LLMs) can generate faulty or insecure code either unintentionally or through malicious attacks. Additionally, there's a potential for AI assistants to inadvertently copy copyrighted code, leading to legal issues. To mitigate risks associated with AI-generated code, it's crucial to track its origin throughout the software supply chain. This requires distinguishing between human and AI-authored code. We first conducted a study investigating the feasibility of using lexical and syntactic features for this purpose. The results of our study were promising, it showed 92% accuracy and encouraged us to enhance our stylometric methods and delve deeper in the problem of detecting AI generated code. Next, we used a larger dataset with a bigger feature set for detecting AI-generated code. Our classifiers achieved up to 93% accuracy on standardized tasks indicating that it is possible to reliably differentiate between human and AI-generated code. Subsequently, we assess the resilience of these methods against adversarial attacks by using the LLM itself as an obfuscation tool. We introduce the concepts of LLM-based obfuscation and alteration attacks, demonstrating their efficacy in evading stylometric detection. The classifiers' performances were notably impacted by both obfuscation and alteration attacks. Recall scores dipped to 58% for obfuscation and 73% for alteration compared to the scores of our trained AI-code detection classifiers. This substantial decline in performances indicates the inability of the model to correctly identify AI-generated code when facing adversarial attacks. These results suggest that the attacks effectively disguised the AI-generated code, enabling it to bypass the classifier undetected. This underscores the challenges posed by these adversarial techniques and highlights the need for more robust detection methods.Item Open Access Testing Bidirectional Effects between Maternal and Child Depression During Middle Childhood(2024-09-18) Hewitt, Jackson; Madigan, Sheri; McArthur, Brae Anne; Yeates, Keith; Birnie, Kathryn; Kopala Sibley, DanielBackground: To date, the understanding of depression within families has primarily focused on a single direction, from parents to children. Extensive research has focused on this perspective, leading to the development of various hypotheses, such as the spillover hypothesis and the intergenerational transmission of depression. These unidirectional hypotheses suggest that parent depression influences the development of child depression. More recently, a new hypothesis has emerged – child evocative effects. This hypothesis proposes that there are more bidirectional and dynamic interactions within the family unit, wherein children can also influence parents’ depression. Objectives: Using a prospective pregnancy cohort, we tested both potentially co-occurring phenomena. First, we tested the potential bidirectional effects of mother and child depressive symptoms across four waves of data during the middle childhood period. Second, we tested whether child sex and family socioeconomic status moderated associations. Methods: This study was based on data from 1801 mothers and children from the All Our Families cohort from Calgary, Alberta. Maternal and child depression and demographic information was assessed through validated self-report measures of depressive symptoms at four timepoints (Time 1: Spring 2020, child age 9.66 years; Time 2: Spring 2021, child age 10.40 years; Time 3: Fall-Winter 2021-2022, child age 11.08 years, and Time 4: Winter 2023, child age 12.82 years). Child sex and family socioeconomic status was reported by mothers at Time 1. Results: Results of a random-intercept cross-lagged panel analysis revealed that child depression at Time 1 predicted higher maternal depression at Time 2 (β = .12; 95% CI .02, .22). Additionally, child depression at Time 2 predicted higher maternal depression at Time 3 (β = .17; 95% CI .07, .26). The obverse association was not supported. Child sex and family socioeconomic status did not moderate associations. Conclusions: Contrary to conventional theorizing, we found evidence for child-evocative effects but not maternal spillover effects of depressive symptoms. Our study sheds light on the nuances of how depression potentially develops within families and challenges conventional theorizing of a unidirectional spillover from caregiver to child depression. It establishes a framework for future research to incorporate bidirectional and potentially transactional relationships when considering depression transmission within families. Furthermore, it emphasizes the need to incorporate the complex dynamics of family interactions into prevention and intervention efforts.Item Open Access Application of Metallomics Techniques to Probe the Biotransformation of Toxic Metals in the Bloodstream-Organ System(2024-09-17) Doroudian, Maryam; Gailer, Jurgen; Musgrove, Amanda; Fraser, Marie; Kimura-Hara, Susana; Wang, FeiyueAnthropogenic activities contribute significantly to the emission of toxic metal(loid) species (TMS) into the environment, thus exposing human populations, including children, to these pollutants via diet, drinking water and consumer products. Therefore, the influx of TMS into the bloodstream and their biochemistry are directly implicated in their chronic toxicity, presenting a new bioinorganic chemistry frontier. This thesis presents results obtained by applying metallomics methods to analyze biological fluids for TMS and metalloentities to unravel new aspects of their bioinorganic chemistry which are implicated in the etiology of environmental diseases. To this end size exclusion chromatography coupled with an inductively coupled plasma atomic emission spectrometer (SEC-ICP-AES) was used for the qualitative identification of major metalloproteins in (red blood cell) RBC cytosol, including hemoglobin, carbonic anhydrase I, and Cu, Zn superoxide dismutase, making this method useful for studying the role of these proteins in essential element dyshomeostasis following chronic exposure to TMS. In addition, intracellular biochemical processes between mercuric mercury (Hg2+) and methylmercury (MeHg+) with small molecular weight thiols were investigated at near physiological conditions. Using reversed-phase high-performance liquid chromatography (RP-HPLC) coupled with ICP-AES and electrospray ionization mass spectrometry (ESI-MS), competitive interactions between Hg2+ and MeHg+, N-acetyl-L-cysteine (NAC), and glutathione (GSH) were examined. In the presence of equimolar concentrations of GAH and NAC, Hg2+ formed Hg(GS)(NAC) and Hg(NAC)2, while MeHg+ formed MeHg(GS) and MeHg(NAC) on the column, which suggests that NAC can modulate the metabolism of these mercurials within mammalian cells, offering insights into their potential mobilization from tissues. Metallomics tools were also employed to examine interactions between carbonic anhydrase I (CA I) released from ruptured RBCs with human blood plasma. Observing all endogenous Cu, Fe, and Zn-metalloproteins before and after adding CA I to plasma demonstrated that CA I does not bind to plasma proteins in vitro, suggesting that it could actively participate in adverse processes at the bloodstream-endothelial interface. Last but not least, I discuss in a perspective article that a deeper understanding of the bioinorganic chemistry of the bloodstream is essential for comprehending both the adverse effects of TMS on human health and the toxic side effects of metal-based anticancer drugs. The article highlights the critical role of metallomics tools in elucidating the underlying mechanisms.Item Open Access Intelligent Production Optimization in Real-Time by Implementing Hybrid Data-Physics Simulation(2024-09-13) Matoorian, Raya; Shor, Roman; Aguilera, Roberto; Chen, Zhangxing; Chen, Nancy; Alhajj, Reda; James, LesleyThis research introduces a novel approach to overcoming key challenges in applying machine learning (ML) for production forecasting and performance evaluation in conventional and unconventional reservoirs. By leveraging a hybrid data-physics architecture (HDP), this approach addresses limitations such as poor generalizability, the need for extensive training datasets, and discrepancies between model outputs and physical principles. The HDP integrates physical equations such as decline curves into a deep neural network, enabling the two to function together during forward and backward propagation. The training data includes various factors influencing production rates, encompassing information that may not readily conform to conventional physical equations. This hybridization enables the inclusion of supplementary data that influence production. These data points help derive the model's physical parameters, leading to more accurate production rate calculations, and improving production forecasts. An extensive assessment was conducted using publicly available data, including Duvernay formation, SPE-RTA well data, and Volve oil field. Three different methodologies were used to compute future production rates: traditional decline curves, ML, and HDP modeling. The results compared with different statistical metrics, demonstrated that HDP model consistently exhibited superior precision in production forecasting. A key advantage of HDP is its ability to generate accurate predictions without extensive training samples (physics acts as a constraint and helps the network to train faster), beneficial for newly established wells with limited production histories. The predictive outcomes align well with fundamental physical models, validating their applicability for short-term and long-term production forecasting. For a real-world case, horizontal wells in Duvernay were used (featuring different well designs, drilling, and completion parameters) to build different predictive models and then generate thousands of scenarios. These scenarios are used to find an optimized solution for drilling and hydraulic fracturing operations. Afterward, the best scenario was selected using multi-criteria decision-making and decision tree methodologies. The applicability of HDP was extended to generate reliable sweet spot maps for new drilling targets. Finally, this research advances production performance evaluation by bridging the gap between data-driven and physics-based approaches and enhances the accuracy and reliability of production forecasts and optimization, offering a robust tool for both operators and researchers.Item Open Access An Experimental Investigation of Ejector Ramjet Performance at Static Conditions(2024-09-16) Long, Lisa; Johansen, Craig; Gates, Ian; Bauwens, LucThe performance of a methane-fueled ejector ramjet (ERJ) equipped with the Atlantis Intake System (AIS) was tested at static conditions. For static tests with no forward velocity, the AIS ERJ successfully entrained and mixed the stagnant surrounding air to create a stoichiometric mixture of 17.2 when the Mach 2 primary jet’s total pressure was 625 ± 25 kPa. Combustion was most stable when the air-fuel mixture was lean. The maximum positive thrust and specific impulse were 22 ± 3 and 189 ± 33 s, respectively, when the primary jet total pressure was 400 kPa. Engine performance was compared to a 1D Ejector Ramjet (1D-ERAM) solver and showed good agreement with a 95% confidence interval during combustion. The solver did not accurately predict the combustion limits of the engine. Additional tests were performed with a nitrogen-diluted fuel jet, which extended the range of conditions for which the ERJ could sustain combustion. The engine demonstrated increased thrust when the primary jet’s total pressure was increased. The inverse Damkohler number was investigated as a tool for predicting engine blowout and provided improved resolution of the engine’s combustion limits, which could be applied to the 1D-ERAM solver