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Recent Submissions
Assessing the prevalence and youth-directed marketing power of outdoor food and beverage advertisements around schools in six cities across Canada.
(University of Waterloo, 2025-01-24) Morielli, Amanda
Recent policy initiatives in Canada propose to restrict the commercial advertising of foods containing sugars, sodium, or saturated fat to youth on digital and broadcast media. While there is abundant research on youth’s exposure to food and beverage advertising on digital and broadcast media, there is limited research exploring youth’s exposure to outdoor food and beverage advertisements (e.g., freestanding billboards, restaurant exteriors, bus shelters). To address this research gap and inform policy decisions, Manuscript 1 of this thesis describes the prevalence, content, and youth-directed marketing power of outdoor food and beverage advertisements near schools. Manuscript 2 of this thesis explores the association between outdoor F&B advertisement prevalence, food outlet density, degree of urbanization, neighbourhood deprivation, and ethnocultural composition near schools to understand how the built environment and neighbourhood characteristics influence outdoor advertising environments. For this research, data on outdoor advertisements and food outlets within 1000 m of elementary and secondary schools in six cities across Canada (Vancouver, BC; Calgary, AB; Winnipeg, MB; Ottawa, ON; Quebec City, QC; and Halifax, NS) was analyzed, along with Statistics Canada data on deprivation and ethnocultural composition (from the Canadian Index of Multiple Deprivation). Descriptive statistics, chi-square tests, and negative binomial regression models were used to analyze the data. Most (64.5%) outdoor F&B advertisements near schools promote “unhealthy” food and beverage products. The most common marketing techniques used to target youth were youth product/convenience (39.4%), sense of urgency/limited time offer/seasonal (18.4%), and price promotion/discount (13.1%). School areas with high food outlet counts contained 7.429 times more advertisements than those with low counts (CI: 4.805 – 11.486, p < 0.05). The mean count of outdoor advertisements on food outlet exteriors (M = 23.22, SD = 35.52) was 10.6 times higher than the mean count of freestanding outdoor advertisements (M = 2.18, SD = 3.94), revealing that most outdoor F&B advertisements around schools are located on food outlets. Measures for deprivation and ethnocultural composition were not found to have notable patterns of significance with outdoor advertisement, except for residential instability. School areas with a high degree of residential instability contained 1.707 times more advertisements than the school areas with a low degree of residential instability (CI:1.029 - 2.832, p < 0.05). These findings suggest outdoor F&B advertisements near schools primarily promote unhealthy food choices and advertisement prevalence is influenced by features of the built environment, such as food outlet density. Future research should explore the impact of planning and public health policy interventions to reduce outdoor food and beverage advertising to youth. Opportunities for these professions (as well as other relevant disciplines) to collaborate to create healthier food environments for youth should also be identified.
“AnnoTools”: Extending AnnoTree and AnnoView for Database-Wide Genome Annotation, Visualization, and Comparison
(University of Waterloo, 2025-01-24) Tan, Huagang
Genomic analysis has revolutionized our understanding of the biology and evolutionary history of bacterial and archaeal microorganisms, leading to numerous applications in biotechnology, medicine, and environmental sciences. One of the fundamental aspects of genomic analysis is protein functional annotation, which involves assigning biological functions to protein-coding sequences identified within genomes. These annotations are widely used to support analyses, such as examining gene or function distributions across the tree of life and comparing gene neighborhoods across taxa. By combining these analyses, researchers can comprehensively explore gene functions and the mechanisms of given genes or gene clusters. In this thesis, I will introduce a pipeline that supports genomic analysis. The project consists of three parts: data annotation, visualization, and the language model.
The first part of the pipeline is the generation of protein function annotations. Raw protein sequence data is downloaded from the Genome Taxonomy Database (GTDB) and submitted to two tools: Kofamscan and DIAMOND. Kofamscan assigns KEGG ORTHOLOGY IDs to each input sequence, while DIAMOND assigns Uniref IDs, which are then mapped to InterPro IDs. Combining these IDs provides comprehensive and reliable annotations. The data is filtered for quality and stored on a remote server as an annotation database for further analysis.
The second part of the pipeline involves updating two user-friendly, web-based visualization tools, AnnoTree and AnnoView, which utilize the annotation database. AnnoTree displays the distribution and taxonomy of different protein annotations across GTDB using a tree of life representation, offering insights into biological and evolutionary patterns through species phylogenies and supporting genome-wide co-occurrence analysis. AnnoView focuses on comparing and exploring gene neighborhoods, identifying functionally related genes clustered together in genomes as "gene clusters," thus emphasizing window-based co-occurrence analysis. The new annotation database not only provides more comprehensive and accurate annotations, enhancing the databases that both visualization tools rely on, but also extends their functionalities for fast data retrieval and new features.
The last part of the pipeline involves the application of the Word2Vec language model, which treats genome contigs as sentences in natural language and trains the model using the annotation database. After training, the updated model can encode each annotation from a specific protein family into high-dimensional vectors with continuous number, allowing researchers to explore annotations that share similar genomic contexts. This allows protein functions prediction based on this comparative gene neighborhood analysis.
Finally, I will use one protein domain in the Type VI Secretion System (T6SS) as a case study. T6SS is a cell envelope-spanning machine that translocates toxic effector proteins into eukaryotic and prokaryotic cells. Besides the conserved essential core components, there are various effector and accessory proteins in the system. Some proteins are annotated as Domains of Unknown Function (DUF) and are poorly explored. In this case, I will focus on PF20598 (DUF6795), which shares a similar genomic context with one of the T6SS proteins. Using the visualization tools AnnoTree and AnnoView, I will demonstrate that this DUF is part of the T6SS cluster, supporting the hypothesis that it may function as an adaptor protein in T6SS.
In summary, the AnnoTools pipeline integrates all components to enhance comparative genomic analysis with a large-scale annotation database. The user-friendly web-based tools enable researchers to visualize data both genome-wide and at a window-based scale. The ultimate goal of this thesis is to provide researchers with a comprehensive and easy-to-use method for predicting functions of genes or gene clusters of interest.
Data-Based Modeling of Electrochemical Energy and Thermal Systems: Fuel Cell and Lithium-Ion Battery
(University of Waterloo, 2025-01-24) Legala, Adithya
As a solution to combat climate change and environmental pollution, electrochemical energy systems such as Proton Exchange Membrane Fuel Cell (PEMFC) and Lithium-Ion Battery (LIB) are being developed as the replacement for fossil fuel-powered combustion engines, especially for ground transportation and aviation applications. These electrochemical energy systems must be able to operate independently and in conjunction with each other by complementing their advantages and limitations, such as efficiency, range, thermal behavior, aging, and operating environment. This interoperability requires accurate real-time computational models to control, diagnose, and adapt according to field requirements. A typical electrochemical energy system model needs to incorporate effects related to reactant concentrations, system overpotentials, thermodynamics, porous media mechanics, membrane dynamics, gas diffusion, electrode degradation, electrolyte status, ion transport, and chemical kinetics across various operating conditions, all of which result in complex interactions affecting the accuracy and reliability of the system.
Today, both PEMFC and LIB use complex computational physics-based fluid dynamics models in the product development phase, which requires enormous computational power and long lead times for iterative prototype improvements. On the other hand, both PEMFC and LIB rely on simple lookup tables and semi-empirical equations as plant models that require intensive calibration activity to determine the mode of control and diagnosis for automotive applications. However, considering the present-day automotive propulsion systems, which operate in widely varied applications and geographic locations and have short product development cycles, these approaches are not able to comprehend the complexities, hindering the ability of these systems to operate at their full potential and leading to catastrophic failures (e.g., Thermal runaway). Data-based modeling techniques are one of the potential solutions, which is quite in contrast with other empirical or physics-based models where the entire input-output relations of the model are established primarily based on the data. Data-based models use aspects of statistics, probability, and network architecture, avoiding the complexities of physics-based models and intensive calibration, providing better accuracy in most cases, primarily where the complex mechanisms can’t be modeled using specific governing equations, and fast, efficient computation with much less computational resource requirement.
This thesis focuses on data acquisition (identifying and collecting the relevant data) and data-based model development by incorporating machine learning algorithms and regressors to predict the system's performance, thermal behavior, aging, and faults in real-time (on-board diagnostics). Data for these models is acquired through two approaches: experimentation by utilizing Fuel Cell and Green Energy Lab facilities such as the Automated Battery Test Station (ABTS), G20 fuel cell automated test station, and by partnering with the relevant industry. In the second approach, data is generated by simulation of physics-based models (CFD, Semi-empirical, equivalent circuit models) that are experimentally validated in the literature and developed within the research groups of UWaterloo. Development of a data-based model includes the identification of feature vectors (inputs), prediction attributes (outputs), state estimates (internal parameters), non-linearity of the systems, correlation factors of various system entities, and application of machine learning techniques such as feed-forward artificial neural network, support vector machine classifier - regressor, along with their respective adaptations and calibration processes. The primary objectives of this study are to develop data-based models for three main application areas: (i) Prediction of PEMFC performance, internal states of the membrane, cell voltage degradation, and system outputs. (ii) Prediction of LIB heat release rate during discharge and thermal dynamics of an open system during an exothermic reaction. (iii) Prediction of fuel cell battery hybrid electric vehicle’s system dynamics and thermal behavior.
During this study, various data-based models were developed to tackle the problems encountered in fuel cell-battery hybrid systems, such as predicting the fuel cell performance, fuel cell voltage degradation, PEMFC membrane dynamics, lithium-ion battery thermal dynamics, thermal behavior during exothermic reactions and dynamics of fuel-cell battery hybrid system. The results presented in this study proved the data-based model’s applicability in surrogate modeling, real-time system monitoring, controls, and diagnostics of electrochemical energy systems both at the component level and system level. Additionally, the results implicate that the data-based model can serve as a complement and alternative to the traditional computational fluid dynamics models as well as complex physics-based and empirical models to predict thermal gradients and system internal states during multifaceted reactions.
Can We Achieve ‘High-Quality’ Weight Loss Through Anabolic and Weight Loss Supplementation in Combination with Exercise in Overweight and Obese Males and Females?
(University of Waterloo, 2025-01-24) Ocampo, Gabriela
Introduction: In 2022, 32.6% and 29.4% of the Canadian adult population from 18 to 49 years of age were considered overweight and obese, respectively, and therefore may become predisposed to developing a myriad of serious health problems and diseases, as well as psychological problems from discrimination and stigmatization. A traditional method to achieve weight loss is to impose an energy restricted diet, however this method has proven to be problematic as it reduces lean body mass (LBM). The loss of LBM can impede ability to perform daily physical activity, increase risk of injury, and increase risk of sarcopenia and thus it is important to implement exercise and/or increase protein intake to promote high-quality weight loss. Many seek alternatives, such as over-the-counter appetite suppressants, herbal products, or weight-loss supplements, to aid in the process. Purpose: To determine if the consumption of a fat oxidizing, TRIM7, and anabolic, MUSCLE5, supplement while performing a mixed-mode training for 12 weeks can promote a high-quality weight loss in the absence of an energy deficit diet. Furthermore, sex and aerobic fitness and strength outcomes will be examined to observe other differences. Methods: Seventy-four overweight/obese, sedentary males (n=35) and females (n=39) were recruited and randomized into group A and group B (active or placebo supplementation) and performed a 12-week mixed-mode exercise intervention. Prior to training, participants underwent anthropometric, body composition (dual energy x-ray absorptiometry), aerobic fitness (VO2max test) and strength (3-5 repetition max test) assessments. Training consisted of 3 weekly sessions involving 30-minutes of aerobic and 30-minutes of resistance training. Supplementation consisted of one group consuming TRIM7 and MUSCLE5 while the other consumed a placebo, every day for 12 weeks. Results: Analysis was completed for group A (n = 11 males and n = 13 females) and group B (n = 10 males and n = 13 females) who had completed the trial by August 2024. There was no change in body mass in either group (p=0.24) after the 12-week intervention. Group A had a significant increase in percent change of LBM after the intervention, with males gaining 1.2% and females gaining 1.7%, while group B had a slight decrease in LBM post intervention by 0.8% for males and 0.4% for females (p=0.05). There was no difference between the sexes in how the intervention influenced any other body composition measurements (all p≥0.34). Both group A and group B improved aerobic fitness (p=0.003) and strength (all p≤0.05), with no difference between groups, sexes, or interactions. Conclusion: The addition of TRIM7 and MUSCLE5 to a 12-week mixed-mode exercise routine did not elicit a high-quality weight loss in overweight/obese males and females. Furthermore, there were no sex differences observed in body composition measures. Group A did have an increase in LBM, thus surmising group A’s consumption of the active supplements based on the increase in protein intake as the trial remains unblinded.
A Broken History: Examining the Events, Experiences, and Narratives of the High Arctic Relocations, 1950-2010
(University of Waterloo, 2025-01-24) Hossack, Sam
In 1953, the Canadian government moved thirty-five Inuit from Inukjuak in Northern Québec to the High Arctic with promises of better hunting opportunities and the ability to return to their communities within two years if conditions were not to their liking. Two years later, twenty-nine additional Inuit were sent to join them. Since these High Arctic Relocations, government officials, lawyers, and academics have questioned the federal government’s motivations for and responses to the relocations, focusing on the question of whether the government was justified in undertaking an ill-fated humanitarian mission or if the government coerced Inuit into staking Canadian claims to the Arctic.
This dissertation explores the legacy and ongoing influence of the relocations in Canadian history by tracing the documentary, experiential, and political narratives surrounding the High Arctic Relocations from the 1950s to the 2010s. This includes critically re-examining the archival evidence from the 1950s; analyzing Inuit testimony of experiences and contemporary storytelling about the relocations; and examining Inuit, government, and academic political narratives from the 1980s through the 2010s. By examining the narratives of the High Arctic Relocations and framing these narratives using the event, experiences, and memory of relocation over the course of seven decades, this study parses the evolving themes and foci as Inuit struggled to secure recognition and compensation for their suffering. This dissertation re-assesses the government’s motivations for relocating Inuit in the early 1950s and includes analysis of the complexities and limits of government decision-making. It also explores the effects of those decisions on Inuit relocatees through an examination of remembered experiences in the 1990s. Finally, this dissertation analyzes the academic and government framing of the narratives of relocation since the 1990s, investigating how these narratives affect contemporary perceptions of government actions.
This dissertation demonstrates that the intentions of government officials in the 1950s (the event) and vigorous debate about the perceived motivations of government have superseded the outcomes (experience) of the relocations. This evolving discourse has produced generally-accepted conclusions in Canadian history about the alleged motivations for the relocations that find little grounding in the archival record but which have become a key part of the meta-narrative about state sovereignty, deceit, and coercion in the twentieth century Canadian Arctic.