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Recent Submissions
Municipal Wastewater Sludge as a Sustainable Bioresource: Spatial Analysis Across Ontario
(University of Waterloo, 2025-10-08) Granito Gimenes, Camila
Effective wastewater sludge management is critical for sustainable wastewater treatment, nutrient recovery, and environmental protection. However, Ontario lacks in data of sludge generation and nutrient content, particularly across diverse facility sizes and treatment processes. This study aims to fill that gap by estimating wastewater sludge generation, nitrogen and phosphorus content, and disposal practices across 548 municipal wastewater treatment plants (WWTPs) in Ontario. Using a combination of facility-level annual reports, the Wastewater Systems Effluent Regulations (WSER) database, Ontario Clean Water Agency (OCWA) records, and National Pollutant Release Inventory (NPRI) was developed treatment-specific coefficients from a subset of plants with complete data to extrapolate sludge generation, nitrogen and phosphorus mass for facilities lacking direct data.
For the year 2022, the most recent year with complete data, Ontario’s WWTPs generated an estimated 356,265 ± 35,859 dry metric tons of sludge, with a per capita generation of 23.5 kg/person/year falling within the range reported in the literature (17.8–31.0 kg/person/ year). Nutrient content analysis revealed median concentrations of 29 kg/ metric tons of dry sludge for phosphorus and 42 kg / metric tons of dry sludge for nitrogen, resulting in an estimated 9,937 ± 1,837 metric tons of phosphorus and 15,302 ± 9,044 metric tons of nitrogen generation per year in wastewater sludge. Over 50% of the nutrients are concentrated in larger, anaerobic digester-equipped facilities, located primary in Southern Ontario. Incineration accounts for the end-use of 30% of the total sludge generated, resulting in the loss of their nutrients. In contrast, agricultural disposal, practiced by 140 facilities, allows for nutrient recovery from 26% of total sludge generated.
Spatial and process-level analysis revealed that plant size and stabilization method are predictors of disposal type. Large plants (defined with influent (≥ 37,850 m3/day), which are more likely to operate aerobic or anaerobic digesters, tend to adopt more sustainable disposal methods when conditions permit (e.g. during appropriate seasons). In contrast, small facilities (with influent (≤ 3,785 m3 /day) often lack in advance stabilization and are more likely to rely on less sustainable practices such as landfill. Many of these facilities also lack consistent reporting, making it difficult to track sludge generated and disposal pathways.
By quantifying the generation of sludge and nutrient flows across Ontario, this study provides a baseline for evidence-based decision-making. The data can be used by municipalities and regulators to identify areas with high biosolids generation, data gaps, and to target specific regions for further study or investment. These findings highlight the need for provincial-level data transparency and target strategies to promote nutrient circularity in municipal sludge management, particularly by addressing the data and resource gaps at smaller facilities. While this study provides a valuable province level overview, a key limitation is the reliance on extrapolation data or facilities lacking complete records, underscoring the need for improved, standardized reporting and new methodologies with more data in the future.
Using eye tracking to study the takeover process in conditionally automated driving and piloting systems
(University of Waterloo, 2025-10-08) Ding, Wen
In a conditionally automated environment, human operators are often required to resume manual control when the autonomous system reaches its operational limits — a process referred to as takeover. This takeover process can be challenging for human operators, as they must quickly perceive and comprehend critical system information and successfully resume manual control within a limited amount of time. Following a period of autonomous control, human operators’ Situation Awareness (SA) may be compromised, thus potentially impairing their takeover performance. Consequently, investigating potential approaches to enhance the safety and efficiency of the takeover process is essential. Human eyes are vital in an individual’s information gathering, and eye tracking techniques have been extensively applied in the takeover studies in previous research works. The current study aims at enhancing the takeover procedure by utilizing operators’ eye tracking data. The data analysis methods include machine learning techniques and the statistical approach, which will be applied to driving and piloting domains, respectively.
Simulation experiments were conducted in two domains: a level-3 semi-autonomous vehicle in the driving domain and an autopilot-assisted aircraft landing scenario in the piloting domain. In both domains, operators’ eye tracking data and simulator-derived operational data were recorded during the experiments. The eye tracking data went through two categories of feature extractions: eye movement features linked predominantly to fixation and saccades, and Area-of Interest (AOI) features associated with which AOI the gaze was located. Eye tracking features were analyzed using both traditional statistical techniques and machine learning models. Key eye tracking features included fixation-based metrics and AOI features, such as dwelling time, entry count, and gaze entropy. Operators’ SA and takeover performance were measured by a series of domain-specific metrics, including Situation Awareness Global Assessment Technique (SAGAT) score, Hazard Perception Time (HPT), Takeover Time (TOT) and Resulting acceleration.
Three research topics were discussed in the current thesis and each topic included one driving study and one piloting study. In topic 1, significant differences in eye movement patterns were found between operators with higher versus lower SA, as well as between those with better and worse takeover performance. Besides the notable differences in various Area-of-Interests (AOIs) across three pre-defined Time windows (TWs), in the driving domain, drivers with a better SA and better takeover performance showed inconsistent eye movement patterns after the Takeover Request (TOR) and before they perceived hazards. In the piloting domain, pilots with shorter TOT showed more distributed and complex eye movement pattern before the malfunction alert and after resuming control. During the intervening period, their eye movements were more focused and predictable, indicating fast identification of necessary controls with minimal visual search. In topic 2, significant differences in eye movement patterns were observed between younger and older drivers, as well as between learner and expert pilots. As for driving domain, older drivers exhibited more extensive visual scanning, indicating difficulty in effectively prioritizing information sources under time pressure. In piloting domain, expert pilots not only allocate more attention to critical instrument areas but also dynamically adjust their scanning behavior based on the current tasks. In topic 3, machine learning models trained on eye tracking features successfully performed binary classification for both SA-related and takeover performance related metrics. Model performance was evaluated using standard classification metrics, including accuracy, precision, recall, F1-score, and Area Under the ROC Curve (AUC).
Finally, comparisons were made across Topics 1 and 2, as well as between the driving and piloting domains. The results suggest that better operators can flexibly adapt their gaze strategies to meet task demands, shifting between broad visual scanning and focused searching when appropriate. This shift in patterns underscores the importance of accounting for the specific Time window (TW) when interpreting operators’ eye movements. Overall, this thesis advances the understanding of different eye movement patterns during the takeover process by exploring a range of eye tracking features. The findings support the development of operator training programs and the design of customized interfaces to enhance the safety and efficiency of takeover performance.
Artisanship in a post-industrial present: A physio-biological framework for restorative design artifacts
(University of Waterloo, 2025-10-08) Clouthier, Derrick
digital fabrication
clay extrusion printing
3D printing
psychology
restorative design
environmental psychology
biophilic design
biophilia
clay
Over billions of years, organisms have evolved from single cell organisms into the human species of today. That process shaped the physiology and psychology of the human species. While each person is unique, a product of each individuals experiences and specific genetic endowments, there exists universal features that are innate in the biology of humans. One aspect of this is our brain, a unique organ which has evolved through thousands of generations, and through countless interactions with our environments into a mechanism for our species survival. This evolutionary process created a deep innate relationship between humanity and our natural environments.
When modernism emerged at the turn of the 20th century, it fundamentally changed architecture. The economics of mass production mingled with advancements in medical reasoning to produce an architecture of efficiency. Architects such as Adolf Loos, Le Corbusier, and Alvar Alto translated the sterility and medical principles of the sanatorium into housing and beyond, producing an architecture founded on the principles of air and light as essential elements to health, while peeling architecture away from the “humid ground where disease breeds” as defined by Le Corbusier. Large windows, rooftop terraces, and spotless interiors crafted light filled spaces and spotless environments, perfect for the air and sun cure against tuberculosis, but which increasingly separated individuals from the ground humans have evolved to thrive in. Architecture shed the rich visual complexity, naturalistic illusions, and fluid interior exterior relationships of historic architectures, replacing it with a sterile incubator, targeted toward contemporary concepts of health.
Modernist architectural advancements led to a sterility that has permeated modern architectures, producing a cognitive discord that is actively harmful to individuals. Researchers in neuroscience and environmental psychology have sought to understand this discord, producing studies which seek to better identify the underlying cognitive mechanisms that inform these interactions. Designers in turn have developed frameworks for applying this research to design for well-being. This thesis proposes a framework for restorative design principles, and advocates the harnessing of digital fabrication technologies to produce restorative artifacts for well-being. Through the development of a framework specifically tailored to the production of digitally fabricated artifacts, this thesis proposes a methodology for generating restorative environments through informed design. The artifacts presented in this thesis demonstrate the application of restorative principles through digitally fabricated artifacts, advocating the adoption of a new architectural language for restorative, evolutionarily informed design.
Approaching Memorization in Large Language Models
(University of Waterloo, 2025-10-08) Cheng, Xiaoyu
Large Language Models (LLMs) risk memorizing and reproducing sensitive or proprietary information from their training data. In this thesis, we investigate the behavior and mitigation of memorization in LLMs by adopting a pipeline that combines membership inference and data extraction attacks, and we evaluate memorization across multiple models. Through systematic experiments, we analyze how memorization varies with model size, architecture, and content category. We observe memorization rates ranging from 42% to 64% across the investigated models, demonstrating that memorization remains a persistent issue, and that the existing memorization-revealing pipeline remains valid on these models. Certain content categories are more prone to memorization, and realistic usage scenarios can still trigger it. Finally, we explore knowledge distillation as a mitigation approach: distilling Llama3-8B reduces the extraction rate by approximately 20%, suggesting a viable mitigation option. This work contributes a novel dataset and a BLEU-based evaluation pipeline, providing practical insights for research on LLM memorization.
Perceptions of Dementia among Young Arab Adults in Ontario
(University of Waterloo, 2025-10-06) Al-Saghier, Ruah
Introduction
As dementia rates are projected to rise among ethnic communities in Canada, understanding how these communities perceive the condition is increasingly important (Alzheimer Society of Canada, 2024). This study focuses on young Arab adults due to the Arab population's rapid growth and relatively young age profile in Canada (Statistics Canada, 2022; Canadian Arab Institute, 2019). Given cultural expectations around caregiving, many of these individuals may assume caregiving roles for relatives with dementia in the future. Their perceptions are therefore critical, as they can influence caregiving approaches and help-seeking behaviors. While international studies suggest that Arab communities may hold negative views of dementia (Brijnath et al., 2021; Kane et al., 2021; Abojabel & Werner, 2019), there is limited research exploring these perceptions within the Canadian context.
Objective
The objective of this qualitative study is to explore the perceptions of dementia among young adults between the ages of 18 and 30 who are members of Arab communities in Ontario. The research question is ‘how do young Arab adults perceive dementia?’.
Methods
This study recruited 10 young Arab adults and conducted in-depth, semi-structured interviews with each participant. Although the participants were provided with the choice of having an Arabic or English interview, all the participants opted for an English interview. Two interviews were conducted in-person and eight were conducted online. The study used reflexive thematic analysis to analyze the data using a software called MAXQDA.
Findings
Three themes were generated from the reflexive thematic analysis. The themes provided an idea on how the participants and their communities perceive dementia. The three themes were: Describing dementia, Understanding the causes of dementia, and Living with dementia. The themes shared a range of different perceptions, which may be a reflection of the differences between the participants and their communities. The participants highlight many perceptions that were rooted in religious or spiritual beliefs – highlighting the importance of religion to the community. Overall, many perceptions reflect some stigma in how participants and their community view dementia, such as the hesitancy to use the word dementia or the negative language used to talk about dementia.
Implications
This study shows the value of developing dementia resources that are both culturally and spiritually sensitive for Arab communities. Involving community members in co-creating educational tools, working with places of worship, and acknowledging the role of cultural beliefs in shaping care can help make public health efforts more effective. As for future researchers, there is a pivotal need to include Arabs living with dementia in Canadian research.