Theses

Permanent URI for this collectionhttps://uwspace.uwaterloo.ca/handle/10012/6

The theses in UWSpace are publicly accessible unless restricted due to publication or patent pending.

This collection includes a subset of theses submitted by graduates of the University of Waterloo as a partial requirement of a degree program at the Master's or PhD level. It includes all electronically submitted theses. (Electronic submission was optional from 1996 through 2006. Electronic submission became the default submission format in October 2006.)

This collection also includes a subset of UW theses that were scanned through the Theses Canada program. (The subset includes UW PhD theses from 1998 - 2002.)

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QAVSA: Question Answering Using Vector Symbolic Algebras
(University of Waterloo, 2024-11-29) Laube, Ryan
With the advancement of large pretrained language models (PLMs), many question answering (QA) benchmarks have been developed in order to evaluate the capabilities of these models. Augmenting PLMs with external knowledge in the form of Knowledge Graphs (KGs) has been a popular method to improve their question-answering capabilities, and a common method to incorporate KGs is to use Graph Neural Networks (GNNs). As an alternative to GNNs for augmenting PLMs, we propose a novel graph reasoning module using Vector Symbolic Algebra (VSA) graph representations and a k-layer MLP. We demonstrate that our VSA-based model performs as well as QA-GNN, a model combining a PLM and a GNN-module, on 3 multiple-choice question answering (MCQA) datasets. Our model has a simpler architecture than QA-GNN, converges 37% faster during training, and has constant memory requirements as the size of the knowledge graphs increase. Furthermore, a novel method to analyze the VSA-based outputs of QAVSA is presented.
Statistical Foundations for Learning on Graphs
(University of Waterloo, 2024-11-27) Baranwal, Aseem
Graph Neural Networks are one of the most popular architectures used to solve classification problems on data where entities have attribute information accompanied by relational information. Among them, Graph Convolutional Networks and Graph Attention Networks are two of the most popular GNN architectures. In this thesis, I present a statistical framework for understanding node classification on feature-rich relational data. First, I use the framework to study the generalization error and the effects of existing neural network architectures, namely, graph convolutions and graph attention on the Contextual Stochastic Block Model in the regime where the average degree of a node is at least order log squared n in the number of nodes n. Second, I propose a notion of asymptotic local optimality for node classification tasks and design a GNN architecture that is provably optimal in this notion, for the sparse regime, i.e., average degree O(1). In the first part, I present a rigorous theoretical understanding of the effects of graph convolutions in neural networks through the node classification problem of a non-linearly separable Gaussian mixture model coupled with a stochastic block model. First, I identify two quantities corresponding to the signal from the two sources of information: the graph, and the node features, followed by a result that shows that a single graph convolution expands the regime of the distance between the means where multi-layer networks can classify the data by a factor of up to one over square root of the expected degree of a node. Second, I show that with a slightly stronger graph density, two graph convolutions improve this factor to up to 1/sqrt{n}, where n is the number of nodes in the graph. This set of results provides both theoretical and empirical insights into the performance of graph convolutions placed in different combinations among the layers of a neural network, concluding that the performance is mutually similar for all combinations of the placement. In the second part, the analysis of graph attention is provided, where the main result states that in a well-defined ``hard'' regime, every attention mechanism fails to distinguish the intra-class edges from the inter-class edges. In addition, if the signal in the node attributes is sufficiently weak, graph attention convolution cannot perfectly classify the nodes even if the intra-class edges are separable from the inter-class edges. In the third part, I study the node classification problem on feature-decorated graphs in the sparse setting, i.e., when the expected degree of a node is O(1) in the number of nodes, in the fixed-dimensional asymptotic regime, i.e., the dimension of the feature data is fixed while the number of nodes is large. Such graphs are typically known to be locally tree-like. Here, I introduce a notion of Bayes optimality for node classification tasks, called asymptotic local Bayes optimality, and compute the optimal classifier according to this criterion for a fairly general statistical data model with arbitrary distributions of the node features and edge connectivity. The optimal classifier is implementable using a message-passing graph neural network architecture. This is followed by a result that precisely computes the generalization error of this optimal classifier, and compares its performance statistically against existing learning methods on a well-studied data model with naturally identifiable signal-to-noise ratios (SNRs). We find that the optimal message-passing architecture interpolates between a standard MLP in the regime of low graph signal and a typical graph convolutional layer in the regime of high graph signal. Furthermore, I provide a corresponding non-asymptotic result that demonstrates the practical potential of the asymptotically optimal classifier.
Reinforcement Learning for Solving Financial Problems
(University of Waterloo, 2024-11-26) Wang, Lufan
This thesis explores the application of reinforcement learning (RL) to address two impor- tant financial problems: risk management and optimal trade execution. In risk management, we aim to balance returns with associated risks. To achieve this, we propose an enhanced RL model that integrates a dynamic Conditional Value at Risk (CVaR) measure. By leveraging distorted probability measures, CVaR allows the RL agent to emphasize worst-case scenarios, ensuring that potential losses are accounted for while optimizing long-term returns. Our method substantially reduces the model’s training time by efficiently reusing computation results, significantly lowering computational overhead. Furthermore, it optimizes the balance between exploration and exploitation. This approach leads to more robust decision-making in uncertain environments and a better overall return. For optimal trade execution, we formulate a flexible RL-based framework capable of dynamically adjusting to changing market conditions. Our model not only replicates the results of Almgren-Chriss model in linear environments but also demonstrates superior performance in more complex, nonlinear scenarios where traditional methods like Almgren- Chriss face challenges.
On the effects of external support on memory and metamemory
(University of Waterloo, 2024-11-26) Kelly, Megan
Our ability to remember has long been aided by various supports in our environment. Although these supports are indeed helpful when available, compared to having expected no support, there is a memory cost of expecting external memory support. This dissertation presents a series of experiments that systematically examined this cost of expecting external memory support across a variety of conditions and contexts. Central to the dissertation is the proposed explanation for the memory cost: that it occurs because expecting external support leads to reduced efforts at committing the to-be-remembered information into internal memory—or study effort. Results do suggest that the costs to memory of expecting external support can be explained, at least in part, by this study effort hypothesis. But results also evidence memory costs of expecting external support that are not easily explained by reduced study effort. In exploring the influences of expecting external support on metamemory, results suggest that people have a general awareness of their performance ability with and without expected support. However, results also suggest areas of difficulty with respect to metacognitive awareness of performance, implying that metacognitive accuracy could be challenging when using external memory supports. In examining the memory cost of expecting external support across a variety of conditions and contexts, this dissertation provides further insights regarding our use of external memory supports and places the study effort hypothesis on solid footing as a partial explanation for the cost.
Numerical and experimental investigation of effects of deformability of circulating tumor cells in physical occlusion
(University of Waterloo, 2024-11-26) Keshavarz Motamed, Pouyan
The hematogenous spread of metastasis, an indispensable pathway in metastasis progression, occurs when primary tumor cells enter the bloodstream and circulate throughout the body. Understanding the genetic, biochemical, and biomechanical factors contributing to this spread could significantly advance the early diagnosis and treatment of metastasis. Among these factors, the hemodynamic forces in the blood play a crucial role in spreading metastasis to distant organs, as the blood flow is the primary means of transporting the circulating tumor cells (CTC) in the bloodstream. The survival, intravascular arrest, and extravasation of CTCs are significantly influenced by shear stresses from their interactions with blood plasma, blood cells, and endothelial cells forming the inner layer of blood vessels. However, our understanding of these interactions is still limited due to the complex nature of the phenomena. Advanced numerical methods, capable of accounting for the high deformability of CTCs and fluid dynamics in microcapillaries, offer a promising approach to deciphering CTCs' responses to the hemodynamic forces in their microenvironment. Physics-based cellular-scale numerical methods capable of simulating a large number of highly deformable objects immersed in a fluidic domain came into being as advanced methods to help researchers unravel the CTC's role in metastasis. The discrete nature of these numerical methods comes with the price of defining several unknown parameters for the cell model, which directly impact the deformation behavior of the cell interacting with the force sources that exist in CTC’s microenvironment. Therefore, in the first step of this study, a systematic approach has been developed to identify the unknown parameters of the numerical cell model accurately. In this step, the power of the developed identification method has been credited by using the experimental data reported in the literature for various experiments such as stretch experiments of Red Blood Cells (RBCs) and lung cancer cell deformability measurement with constricted microchannels. However, the experimental data in the literature are insufficient to be applied in identifying the cancer cell parameters, mainly because not only the measured time is too high, making the identification step almost impossible to perform, but the reported data also lack various inputs for cancer cell deformability measurement, hindering the acquiring of stable cell models. Therefore, in the second step, experiments of cells passing the constricted microfluidic devices were performed, and the deformability of highly invasive breast cancer cell lines were measured. By creating the numerical domains of the constricted channels and identifying the cell parameters, cell models of various sizes ranging from 13-18 µm that their motion and deformation behavior have been validated according to the experimental data were acquired. As presented in detail in this study, the developed models can replicate the gradual squeezing and shape change of cancer cells into the constricted microchannels as well as the drop of the flow rate during the cell entrance into the constrictions. Targeting CTC mechanical entrapment in the microcapillaries, in the third step, a predictive numerical tool that can predict the CTC's occlusion fate in an arbitrary microvascular system has been developed. The obstacle in this step is that tracking the CTC’s fate within a large fluidic domain is still beyond the capabilities of the cellular scale in-silico models. Therefore, devising a method that divides an arbitrary microvascular system into smaller domains amenable for the in-silico method to calculate the CTC’s fate is the key to overcome the mentioned obstacle. Therefore, substantial numerical investigations were performed on smaller models to determine the relationship between cell fate and mechanical factors in the blood, such as plasma flow rate, cell deformability, capillary geometry, and cell size. The outputs of the numerical investigations have been stored and used later to predict the cell fate and the site of cell entrapment in the arbitrary microvascular system. Afterward, an algorithm for tracking the CTC in the microvasculature and pinpointing its occluded location has been developed. This algorithm takes the initial cell position and size, communicates with the stored data at every microcapillary branch that contains the CTC, and predicts the CTC trajectory from the previously provided information of the microvascular system's anatomic structure and fluid flow.
A Unified Multi-Frame Strategy for Autonomous Vehicle Perception and Localization Using Radar, Camera, LiDAR, and HD Map Fusion
(University of Waterloo, 2024-11-26) Alghooneh, Ahmad Reza
This thesis presents a novel unified perception-localization module by developing an advanced late fusion system that integrates radar, LiDAR, camera, and High Definition (HD) map information. Emphasizing reliability, robustness to inclement weather, and real-time implementation, this approach particularly focuses on radar data—the most crucial component in the fusion process. Although radar data is rich in features and robust against weather changes, it is often with false alarms and clutters. These issues pose challenges to the fusion process if not addressed. Therefore, the radar point cloud is first refined to remove these false alarms and clutter. Unlike existing approaches in the literature that require massive neural networks, this thesis presents a stochastic alternative that provides the same level of accuracy while maintaining real-time performance and minimal resource usage. By utilizing statistical information from the HD map, the system develops a likelihood of object occurrences in the Frenet coordinate system. This likelihood is then fused with a specific set of radar features to formulate a probabilistic classifier. The classifier focuses on detecting clutter and false alarms, removing them to prevent the radar point cloud from misleading the downstream fusion process. This approach significantly reduces noise and irrelevant data, precision up to 94 percent on our dataset, ensuring that the radar primarily focuses on potential obstacles and critical elements such as cars and pedestrians. The \textbf{video} of the results is available \href{https://www.youtube.com/watch?v=cNb_OR19BQk}{here}. In the subsequent phase, the refined radar data is fused with LiDAR and camera data using a novel, robust frustum approach in a late-fusion manner. Unlike previous works that rely solely on perspective equations, our method constructs a cost function and employs the Hungarian matching algorithm to associate camera data with the 3D positions of objects. This late-fusion methodology significantly enhances overall detection accuracy and reliability by effectively integrating data from multiple sensors. The resulting objects are then fed into a novel tracking module that leverages the radar's radial velocity measurements as partial observations while associating objects across frames using the Shortest Simple Path algorithm and radar features. For each individual object, the tracking module builds an Extended Kalman Filter, providing a full-state estimation of their motion states, including position, velocity, and acceleration. The \textbf{video} showing the performance of the \href{https://www.youtube.com/watch?v=LEIqpTD-pwQ}{perception}, and the \textbf{one} for the \href{https://www.youtube.com/watch?v=LNXKZDAgO40}{tracking}. In the localization phase, the previously processed perception information is utilized to improve positioning accuracy without relying on the Global Positioning System (GPS). This approach ensures a unified module that substantially reduces resource consumption. Moreover, methods relying on GPS and inertial sensors such as the Inertial Measurement Unit (IMU) are susceptible to weather and road conditions, which can challenge the reliability of autonomous driving. In contrast, a robust perception unit can overcome this challenge by using radar, a sensor resilient to inclement weather. In this approach, the fused radar-LiDAR point cloud is used to form a local map across multiple frames, and with the help of the Iterative Closest Point (ICP) algorithm, the vehicle's odometry is estimated. Then, using camera-based lane detection, the lateral distance to the centerline and curb is appended to the odometry measurement. Finally, the vehicle's motion model is rewritten in the Frenet frame, incorporating the measurement models from the radar-LiDAR point cloud and camera lane detection in an Extended Kalman Filter (EKF) formulation. This approach outperforms state-of-the-art positioning solutions in both accuracy and resource consumption. The \textbf{video} of the performance with the \href{https://drive.google.com/file/d/1WdNrda2y7kJk67JrCC8o5mcbgH78zvoh/view?usp=share_link}{localization} in the loop.
Automating Protocol Analysis with Generative AI: Classifying Questions in Design Review Meetings Using GPT-4
(University of Waterloo, 2024-11-26) Sakib, Ahmed Shahriar
This study investigates the extent to which GPT-4 can classify question utterances in verbal protocols of design according to Eris' (2004) taxonomy utilizing in-context learning (ICL). Specifically, it examines the impact of various factors on classification, including the size of the prompt data, contextual information inclusion, prompt engineering strategies, cross-dataset applicability, and cross-model evaluation. The findings of this research could pave the way for more widespread adoption of AI in design research, transforming how protocols are analyzed and interpreted, ultimately leading to more efficient and accurate insights into cognitive processes during design activities. A series of experiments were conducted to evaluate the performance of GPT-4 in this context. The experiments involved utilizing ICL by providing the AI model on a dataset of human-labeled questions and testing its ability to classify new questions according to predefined categories. The findings indicate that GPT-4 performs reasonably well in categorizing stand-alone question utterances, achieving alignment with human-sourced labels in many cases. Moreover, GPT-4 also shows promising generalization capability across the datasets used in this study. The study also highlights the potential for using less expensive LLMs for similar tasks without a significant drop in performance, making them a more accessible option. The results also imply that classification accuracy depends on the dataset quality, indicating that performance may improve with a higher-quality dataset. However, the results also reveal that providing additional context does not always enhance, and in some cases even diminishes, the model's performance, highlighting the challenges of context-dependent classification tasks. The implications of these findings suggest that while GPT-4 shows promise as a tool for automating protocol analysis, there are significant limitations that must be addressed to fully leverage its capabilities in design research. In conclusion, this research contributes to the growing body of knowledge on the application of AI in design research, proposing several directions for future research aimed at refining the use of artificial intelligence in qualitative analysis.
Into the Woods: Investigating the Effects of Weather Information and Attentiveness on Outdoor Recreational Activities
(University of Waterloo, 2024-11-22) Woods, Kyle
Responses to quick-onset atmospheric weather hazards, including thunderstorms, are influenced by the characteristics of risk messages and the characteristics of the message receivers. Message characteristics relating to the probability of and imminency of thunderstorm impacts, as well as the severity of the information and use of wireless emergency alerts are thought to influence responses through amplifying recipients’ risk perceptions. Receiver characteristics relating to past experiences, knowledge and preparedness, sociodemographic characteristics, among others, also play an influential role in the hazard-response cycle. However, the complex role that recipients’ attentiveness has in this hazard-response cycle has not been adequately addressed. This thesis investigates the role that attentiveness and thunderstorm information messaging play in outdoor recreational activity responses. For this investigation, an experiment consisting of a hypothetical hiking activity under an evolving thunderstorm threat was carried out in an online survey of a sample of 476 adult respondents who regularly camp and hike in southern Ontario during the thunderstorm season. Respondents received relevant weather information through a forecast displayed on a smartphone screen before the hike and subsequent watches (1 hour later) and warnings (2 hour later) during the hike, constituting three scenarios. Correspondingly, half of the respondents received a severe thunderstorm watch consisting of higher-severity information and a wireless emergency alert notification with a subsequent severe thunderstorm warning. Respondents' attentiveness, risk perceptions, and behavioural response intentions were recorded following each scenario and comparisons were made between responses from the common and higher-severity message conditions groups to investigate the effect of higher-severity information and WEAs across a thunderstorm event. Receiver characteristics thought to potentially influence observed relationships between attentiveness, risk perceptions, and behaviours during the specific experimental situation were also explored to provide a more complete understanding of the pathways of influence to behavioural responses during thunderstorm events. Empirical results illustrate that outdoor recreationists are highly attentive and responsive to thunderstorm information; whereas most respondents are unlikely to go ahead with a hike following a weather forecast mentioning the risk of severe thunderstorms. Official severe thunderstorm watch alerts increased respondents' attentiveness to the weather and led to increased proactive protective action likelihoods by most of the remaining participants. Wireless emergency alerts did not change respondents' attentiveness to severe thunderstorm warnings. The pathways of influence to protective actions show that attentiveness amplifies risk perceptions, which acts as a mediator to behavioural response intentions. Individuals' receiver characteristics affected the observed pathways of influence to protective actions. Most notably, respondents’ general weather attentiveness greatly amplified their likelihood to be attentive to the weather during a thunderstorm event and amplified their likelihood to take protective actions. The conclusions of this research underscore the importance of attentiveness in the hazard-response cycle and the need for easier accessibility and exposure to weather forecasts and official alerts in outdoor recreational areas to increase attentiveness and desirable behavioural responses.
Two Essays on Managers' Feedback Behavior in the Workplace
(University of Waterloo, 2024-11-22) Minnikin, Amy Florine
Previous feedback research has largely focused on the perspective of the feedback recipient, often taking the act of giving feedback for granted. However, providing feedback can be a complicated and demanding task for managers, and there is likely considerable variance in the frequency and types of feedback behaviors in which managers engage. To this end, in this dissertation I present two essays to address this issue. In Essay 1, I develop the Manager Feedback Behavior Scale (MFBS), which is comprised of seven factors: fostering credibility, providing high-quality feedback, delivering feedback with tact, providing positive feedback, providing negative feedback, ensuring availability, and promoting feedback-seeking. Across four studies, I provide evidence for the validity of the MFBS. In Essay 2, I integrate self-regulatory theories of work motivation with the literature on mental health stereotypes. Across two studies, I present evidence that managers adjust the effort they allocate toward feedback behaviors based on perceptions of their subordinates’ mental health. Briefly, the results indicate that these adjustments are driven by beliefs regarding the likelihood that providing feedback will “pay off” in terms of improved performance. As a set, these essays make several contributions to the feedback literature. Specifically, this research elucidates feedback processes from the manager’s point of view, provides a framework for future investigation of managerial feedback behavior, and emphasizes that providing feedback should be considered with more nuance than simply whether feedback was or was not provided.
Carbon Emissions and Evaporation Dynamics at Peatlands Under Active Extraction in Alberta and Quebec, Canada
(University of Waterloo, 2024-11-20) Hunter, Miranda
The extraction of peatlands for horticultural peat use is a small but important source of peatland drainage in Canada, converting these long-term net sinks of carbon (C) into net sources. With demand for peat expected to grow over the coming decades, there is a need to understand how C emissions and water exchange vary with environmental and site management conditions. Extraction operations alter the site hydrology, peat physical and thermal properties, and peat substrate quality, which in turn alter the C cycling and water budget; however, few studies have quantified this. As part of site preparation for extraction, the surface vegetation is removed and a series of drainage ditches are installed to lower the water table, allowing machinery to access the sites. Exterior ditches surround the perimeter of the sites, while interior ditches run the length of the sites, dividing them into 30 m wide fields of peat bounded by ditches. Sites will be extracted for 15 to 40 plus years using the vacuum harvesting method. As part of this, companies repeatedly disturb the surface by harrowing (tilling) the top ~ 5 cm layer to cut it off hydrologically from the peat below. A portion of this newly dry layer is then harvested, processed and sold for use as a horticultural growing medium. This study conducted plot and ecosystem scale measurements of carbon dioxide (CO2), methane (CH4) and evaporation (E) at multiple actively extracted peatlands of varying extraction durations at sites in both Alberta (AB) and Quebec (QC). Specifically, the research objectives were to: i) investigate spatial distribution and seasonal and interannual patterns of C emissions (Chapters 2 and 3); ii) understand the impact of site management, including drainage, harrowing and drainage ditch maintenance, on C fluxes (Chapters 2 and 3) and E (Chapter 4) and iii) assess the environmental drivers of C emissions and E (Chapters 2, 3 and 4). Plot scale C emissions at AB, and ecosystem scale C and E measurements at AB and QC, were conducted for multiple years between 2019 and 2022, with a focus on the March to October period. A peat incubation experiment and a lysimeter experiment were conducted during summer 2022 at AB to understand the impact of substrate quality on C emissions, and the impact of harrowing on E rates, respectively. Water table depth (WTD), volumetric water content (VWC), soil temperature, and a range of atmospheric variables were also measured throughout the study period. We found that while C emissions did not vary spatially across fields, drainage ditches were hotspots of C loss, emitting around double, and ten times the CO2 and CH4 emissions, respectively, of the fields across a range of VWC. Carbon dioxide emission varied by up to 50% seasonally and interannually, with differences driven by the interaction between soil temperature and moisture conditions. Our results demonstrated the importance of characterizing hydrological conditions at drained sites, as the temperature dependence of CO2 emissions increased with increasing moisture content, and CO2 emissions were significantly higher under heavily drained (WTD > 60 cm) conditions. A non-linear relationship between WTD and E demonstrated the strong upward capillary water movement in these heavily compacted sites, and how adequate surface moisture conditions for E can be maintained across a range of WTDs. Site specific WTD thresholds aided in classifying the relative importance of surface and atmospheric variables on E rates. The impact of harrowing on E rates varied with time, which highlighted the importance of considering the length of time between harrowing and harvesting for management operations. This work will have implications for national greenhouse gas reporting, providing data to support updating C emission factors for Canada. The research can be used by industry partners to inform management practices that balance harvesting yields with C emissions. Additionally, due to the absence of vegetation, these study sites provide a unique opportunity to understand environmental controls of heterotrophic respiration and peatland E, without having to partition out the impact of vegetation.
Creation of a Custom Language Model for Pediatric Occupational Therapy Documentation
(University of Waterloo, 2024-11-20) DiMaio, Rachel
KidsAbility is a pediatric rehabilitation center that offers services including occupational therapy (OT) to youth. Documentation, including writing progress notes for each treatment appointment, is essential to OT treatment but can also be time-consuming and tedious. If the time spent on writing progress notes was reduced, KidsAbility believes that their capacity for treatment would increase. This thesis explores the creation of a custom large language model that is intended to decrease the amount of time that clinicians spend writing progress notes by transforming point-form scratch notes from pediatric OT treatment appointments into draft full-form documentation in SOAP format for the clinicians to edit. A dataset of thousands of historical progress notes, with personal health information redacted, was used in the model training paradigm for which different training techniques were explored including domain-adaptive pre-training and LoRA fine-tuning. As there were no corresponding scratch notes in the dataset, few-shot prompting with a human-in-the-loop evaluation process was used to generate matching scratch notes. The historical progress notes and generated point-form notes were used to fine-tune Llama 2 and 3 models on the desired task. Different models’ outputs were evaluated and compared before the final model, a fully fine-tuned Llama 3 8B Instruct model, was selected for a pilot study at KidsAbility in which the custom model was compared against the proprietary Microsoft Co-Pilot model. Ten OT’s participated in the study, using Co-Pilot and then the custom model to write their progress notes for three weeks each. It was found that providing training on how to most effectively use the custom model is important in reducing the amount of time spent on the process. After training, the average time taken to write a note was 7.6 minutes compared to an average of 13.8 minutes before training, both of which are based on subjective reporting. The progress notes written during the pilot study were also used in a quality assessment, in which four OTs scored the custom model notes, Co-Pilot notes, and manually written notes on multiple criteria. Results for this evaluation demonstrated that the notes written with the custom model were of high quality, receiving the highest score for three criteria and the second highest score for the remaining two. For all criteria, the custom model notes scored higher than the manually written notes. Objective timing data collection for determining the impact of using the custom model compared to not using any model was limited by the availability of clinicians.mac
Time trends in abundance and composition of microplastic particles deposited in profundal sediment of two headwater reservoirs within the Grand River Watershed (Ontario, Canada)
(University of Waterloo, 2024-11-20) Watson, Meredith
Plastic pollution has become pervasive in the environment, raising concern for degradation of aquatic ecosystems by microplastics (MPs). Studies on the supply and abundance of MPs in Canadian freshwaters are rapidly emerging, however temporal trends spanning several decades remain sparse. In this study, we report multidecadal records of MP abundance and composition in dated sediment cores from two headwater reservoirs (Belwood Lake and Conestogo Lake) located within an agricultural region of the rapidly urbanizing Grand River Watershed (GRW; southern Ontario, Canada), a major tributary of Lake Erie. Extracted MPs from contiguous 1-cm thick intervals of sediment cores were enumerated and categorized by shape (fragment, fiber). A subset of samples at approximately decadal intervals were chemically characterized using Laser Direct Infrared (LDIR) Spectroscopy. Results reveal that MP concentrations in both reservoirs varied within a similar range (~50-550 particles g/dw) with no observed increasing trend since the start of each record (1957 for Belwood Lake, 1985 for Conestogo Lake). MP flux in Conestogo Lake increased from ~50 particles/cm^2/year in the mid-1980s to ~100 particles/cm^2/year in recently deposited sediment, whereas MP flux varied without a trend between ~5-60 particles/cm^2/year in Belwood Lake since 1957, apart from a peak in the uppermost sample (~150 particles/cm^2/year). More rapid sediment deposition at Conestogo Lake accounts for the difference in MP flux between the reservoirs, suggesting reduction of sediment transport could reduce the supply of MPs to aquatic ecosystems in the GRW. Analysis by LDIR revealed that polyamide, rubber, and polyethylene were the most abundant polymer types in both reservoirs. The relative abundance of rubber particles has increased since the 1990s, indicating an increase of paved road surface and vehicle traffic as a potential source. The findings suggest MP accumulation in these upstream rural reservoirs of the GRW may be primarily driven by local, regional, and hydrologic factors instead of the rise in global plastic production.
Investigating and Optimizing Charge Balance and Its Effect on Efficiency and Lifetime of QLEDs
(University of Waterloo, 2024-11-19) Azadinia, Mohsen
Colloidal quantum dot light-emitting devices (QLEDs) have gained significant attention as next-generation display and solid-state lighting technologies, offering exceptional color purity, tunable emission wavelengths, high photoluminescence quantum yield (PLQY), and solution-processable fabrication techniques. The ability of quantum dots (QDs) to exhibit size-dependent optical properties through quantum confinement effects enables highly saturated red, green, and blue (RGB) emissions. Since their first demonstration in 1994, QLEDs have shown tremendous improvements in performance, achieving external quantum efficiencies (EQE) close to theoretical limits (~20%) and operational lifetimes (T95@100 cd/m²) exceeding 300,000 hours. Despite significant advancements, several unresolved challenges continue to limit the full commercial potential of QLEDs, particularly blue QLEDs (B-QLEDs), which exhibit notably lower electroluminescence (EL) stability compared to their red and green counterparts. A key factor impacting both device efficiency and lifetime is charge imbalance, which can lead to significant reduction in both performance metrics. This imbalance not only reduces the immediate efficiency of the device but also accelerates its long-term operational instability. Additionally, while many developments have focused on red or single-color QLEDs, less attention has been given to conducting comparative studies that evaluate the performance differences among red, green, and blue QLEDs. This leaves gaps in understanding how charge dynamics and performance vary across these colors, particularly in B-QLEDs where the charge dynamics may differ due to changes in the QDs' bandgap. As a result, the exact mechanisms by which charge imbalance affects both efficiency and lifetime, especially in B-QLEDs, remain unclear. Therefore, further research is necessary to better understand these mechanisms and address the remaining challenges. The primary goal of this thesis is to investigate and optimize charge balance in inverted QLEDs, with a focus on studying charge dynamics to better understand the electron and hole supply properties in red, green, and blue QDs. Additionally, this work explores the interactions between excitons and excess charges, examining how excess carriers, either electrons or holes, impact the EL performance of QLEDs. Based on the findings, new charge transport layers (CTLs) are explored to improve the device's charge balance. This research also investigates the EL loss mechanisms in upright B-QLEDs, which remain a major challenge for the commercialization of QLED technology. Finally, new material systems are tested to enhance the EL stability of upright B-QLEDs. To investigate whether commonly used HTLs in highly efficient upright structures can improve charge balance in inverted QLEDs, polymeric HTLs are employed in these devices. To address the challenge of HTL solvent erosion, a suitable recipe is developed for depositing polymeric HTLs on the QDs-EML. The fabricated inverted R-QLEDs exhibit relatively low efficiency, attributed to a poor interface between the QDs-EML and HTL, though not due to damage to the QDs-EML. However, the introduction of a wide bandgap interlayer between the QDs-EML and the HTL results in significant improvements in both efficiency and lifetime, primarily due to enhanced hole supply. Then, electron/hole supply properties of R, G, and B-QDs are investigated in single carrier devices. Results show that widening the bandgap of QDs increases hole supply efficiency but decreases electron efficiency. To investigate their respective electron and hole supply efficiencies, a comparative study is conducted on inverted R, G, and B-QLEDs to explore charge injection characteristics. The findings reveal that in R-QLEDs, the e/h ratio in the QDs-EML is greater than 1, whereas in G- and B-QLEDs, the e/h ratio is less than 1, with charge balance conditions being significantly worse in the case of B-QLEDs. Additionally, photophysical measurements show that, compared to electrons, holes lead to a stronger Auger quenching effect, which is proposed as one possible reason for the poor efficiency and lifetime of B-QLEDs. Finally, by studying spontaneous electron transfer effect at the ETL/QDs-EML interface, it is observed that injecting electrons into the QDs-EML first, rather than holes, is more favorable for efficiency enhancement, suggesting that efficient electron supply is a prerequisite for achieving efficient QLEDs. Based on the findings regarding the charge supply properties of each color, new CTLs are implemented to develop an inverted QLED structure with improved charge balance. The results from this structure show that employing a double ZnMgO ETL approach, where each ETL is annealed at different temperatures to enhance electron supply, along with an HTL featuring a relatively shallow lowest unoccupied molecular orbital (LUMO), leads to EQEs exceeding 23% for inverted R- and G-QLEDs. Additionally, doping the ZnMgO ETL with graphene QDs is proposed as another method to further enhance electron supply in inverted G-QLEDs, leading to improved device efficiency and extended lifetime due to enhanced charge balance. Next, the EL loss mechanism in upright B-QLEDs is systematically studied using non-invasive marking layers at both HTL and ETL to detect charge leakage. The results indicate that electron injection is stronger than hole injection in upright B-QLEDs. Additionally, findings from EL and PL measurements confirm that, aside from some partially reversible deterioration in the PLQY of the QDs-EML, the rapid EL loss in upright B-QLEDs is primarily due to increased electron leakage across the HTL. This leakage causes damage to the hole injection layer (HIL) and diverts holes away from the QDs-EML, leading to a deterioration in hole supply to the QDs-EML. Ultimately, the functional layers in upright B-QLEDs are modified to reduce electron supply and enhance hole supply. The results show that replacing the Al cathode with an Ag/Al electrode, featuring a deeper work function to limit electron injection, results in a 30X improvement in the device's EL stability. Additionally, introducing an insulating polymer layer between two ZnMgO layers to limit electron supply significantly extends the device lifetime by 12X. Furthermore, utilizing a new HTL to block electron leakage and improve hole supply leads to an 8X improvement in EL stability.
Designing and simulating a micro-robot for transporting filamentous cargos in Newtonian and viscoelastic fluids
(University of Waterloo, 2024-11-18) Ghadami, Sepehr
In recent years, there has been a notable surge in interest within the medical field towards minimally invasive procedures, with magnetic micro-robots emerging as a promising avenue. These micro-robots exhibit the capability to traverse various mediums, including viscoelastic and non-Newtonian fluids, facilitating targeted drug delivery and medical interventions. Many current designs, drawing inspiration from micro-swimmers found in biological systems such as bacteria and sperm, utilize a contact-based approach for transporting payloads. However, adhesion between the cargo and the carrier can complicate release at the intended site. In this thesis, our primary aim was to investigate the potential of a helical micro-robot for non-contact delivery of drugs or cargo. We conducted an extensive examination of the shape and geometrical parameters of the helical micro-robot, with a specific focus on its ability to transport passive filaments. Based on our analysis, we propose a novel design comprising three sections with alternating handedness, incorporating two pulling and one pushing microhelices, to improve the capture and transportation of passive filaments in Newtonian fluids using a non-contact approach. Subsequently, we simulated the process of capturing and transporting the passive filament and evaluated the functionality of the newly designed micro-robot. Initially concentrating on naturally straight filaments, we also demonstrated the micro-robot’s capability to capture filaments with intrinsic curvature and those with a spherical payload attached at one end. Our findings provide valuable insights into the mechanics of helical micro-robots and their potential applications in medical procedures and drug delivery. Furthermore, the proposed non-contact delivery method for filamentous cargo could pave the way for the development of more efficient and effective micro-robots for medical purposes. In the second phase of our project, recognizing that most biological fluids exhibit viscoelastic properties due to the presence of protein fibers, we proposed a viscoelastic model. Inspired by the viscoelastic structure of bovine vaginal fluid, we developed and initially characterized this model using creep and strain tests. Subsequently, in the proposed viscoelastic model, we investigated the functionality of the designed micro-robot in the viscoelastic fluid and compared its performance with that of the conventional single-handed helical micro-robot. It was observed that although the designed micro-robot is highly effective in transporting filamentous microcargo without contact in Newtonian fluid, its unique structure presents challenges when moving in viscoelastic fluid.
The Viability of using a Gleeble for Physical Simulation of High Frequency Induction Welded TRIP 690 AHSS
(University of Waterloo, 2024-11-18) Al Hussain, Syed Faique
High Frequency Induction Welding (HFIW) is the predominant process for high volume production of small diameter tubes and pipes for hydroformed automotive and oil and gas applications. This process is well-established due to its high throughput and continuous nature which makes it ideal for industrial use. However, the HFIW process is also complicated, involving several physical phenomena occurring simultaneously such as mechanical deformation during the squeeze-out, phase transformations, large temperature gradients, high heating rates, and electromagnetic induction. These phenomena are difficult to decouple from one another, leading to gaps in the present understanding regarding how each individual phenomenon affects the formation of certain weld defects, such as oxide inclusions trapped within the bond line of the weld joint. With advances in automotive design, new high-Al TRIP steels are being used for automotive hydroforming applications, due to their capability to be used in high strength/light-weight designs. However, HFIW of these materials, such as TRIP 690, is susceptible to the formation of entrapped oxides containing aluminum (Al), manganese (Mn), and silicon (Si) within the bond line, reducing the operation window compared to other steels. In welds containing oxide inclusions, strength and ductility of the weld joint will be significantly decreased. During production, it is difficult to determine the formation of these oxides due to the dynamic and continuous nature of the HFIW process. Conducting mill trials for experimentation is not practical due to economic constraints as there are high operational costs to run a tube mill and trials result in high material usage. Thus, there is a need to be able to physically simulate the HFIW process at a laboratory scale to understand the effect of each of the individual process parameters on the formation of bond line oxide inclusions and weld quality. This study physically simulates the HFIW process in thin sheets of TRIP 690 AHSS using a Gleeble 3500 thermomechanical simulator. The results of this work demonstrated that the Gleeble could reproduce the microstructure across the bond line and heat affected zone of the HFIW produced welds. Mechanical characterization of the welds revealed a similar hardness distribution across both the Gleeble and HFIW welds. Notably, samples containing bond line oxide inclusions such as those found in HFIW welds were also recreated, and the effects of these inclusions on the tensile properties and fracture mechanism were determined. Through this study, the ideal conditions for producing oxide-free welds to ensure superior weld mechanical properties were determined.
RNA-seq exploration of host responses and viral genomic diversity in SARS-CoV-2 infection
(University of Waterloo, 2024-11-18) Luc, Jessica
Since the discovery of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), there have been over 700 million cases and over 7 million deaths worldwide. Although some patients develop severe symptoms such as multiple system organ failure, others can be asymptomatic. This reflects the role of the immune system in disease progression. Although there exist standard PCR and antigen-based tests for SARS-CoV-2 detection and diagnostics, an important research goal is the identification of predictive biomarkers that are indicative of COVID-19 severity. In this thesis, I performed bioinformatic analyses of two original RNA-seq datasets generated by collaborators to gain insights into the mechanisms and host responses of SARS-CoV-2 infection. The first dataset consisted of transcriptomic data from SARS-CoV-2 infected human lung cells as well as bat (Eptesicus fuscus) derived cells, providing insights into host responses of multiple mammalian species. The second dataset consisted of transcriptomic data from nasopharyngeal swabs collected from COVID-19 patients. A bioinformatic approach was used in both datasets to identify host genes that were up-regulated and down-regulated by SARS-CoV-2 infection as well as to identify biologically relevant viral mutations. The analysis resulted in the discovery of a novel R685P mutation in the SARS-CoV-2 spike glycoprotein, that had increased frequency in the Eptesicus fuscus derived cell line. Variant analysis from the clinical nasopharyngeal swab RNA-seq dataset also revealed the existence of a SARS-CoV-2 quasispecies containing multiple distinct viral genotypes with a unique population structure in each patient. Despite each dataset being distinct, a similar bioinformatic analysis was applied to both datasets to reveal host response patterns and visualize the evolution and mutational spectrum of SARS-CoV-2. Although COVID-19 is no longer considered a global emergency, furthering our knowledge of the SARS-CoV-2 infection can aid in the development in new therapeutics and diagnostic tools.
A Parameterized Vibronic Spin-Orbit Coupling Model Protocol Suitable for Spectroscopy
(University of Waterloo, 2024-11-14) Chen, Benny
A diabatization protocol constructing vibronic model Hamiltonians with inclusion of spin-orbit coupling was implemented in Python. This protocol has been extended to include spectroscopic applications. GAMESS package GMC-QDPT level of theory calculations carries out a proposed diabatization scheme to automatically compute a grid of diabatic states in expansions of displaced nuclear coordinates. Diabatic potential energy surfaces can subsequently be constructed through fitting parameters. Generated vibronic models can be used for input to quantum dynamical simulation approaches such as MCTDH and VECC alike, where auto and cross-correlation functions can be obtained after propagation. Simulated gas-phase photoelectron spectra were reproduced for H2O, NH3, and PH3, with excellent agreement to experimentally recorded spectra. Absorption spectra of transition metal trifluorides CoF3 and RhF3, along with iron pentacarbonyl Fe(CO)5, were studied with a triple zeta polarized Sapporo basis set. Both CoF3 and RhF3 showed pronounced splitting originating from spin-orbit coupling effect, whereas Fe(CO)5 only displayed minimal change due to spin-orbit coupling limited to its truncated constant-order spectrum. It is predicted that the Jahn-Teller effect plays a more dominant role over spin-orbit coupling in our Fe(CO)5 model simulated spectra. Streamlining of the protocol has increased its accuracy and robustness, in the interest of supporting future vibronic spin-orbit coupling model research.
Commuting, Spatial Allocations, and Inequalities
(University of Waterloo, 2024-11-14) Yu, Aidi
This thesis examines the complex relationships between commuting times, wage disparities, gender differences, and urban spatial distribution, through the lens of three interconnected studies. The first chapter investigates the relationship between commuting times, wages, and the gender wage gap, with a focus on controlling for occupational choice endogeneity. Using data from the American Community Survey (ACS) and the Occupational Information Network (O*Net), the study highlights how gender differences significantly influence the positive correlation between commuting time and wages, especially among full-time working homeowners in U.S. cities. Through quantile regression analysis, it reveals that while men's returns on commuting diminish as income rises, the commuting gender gap remains relatively constant across the wage distribution. The second chapter delves deeper into the gendered impacts of commuting on wage disparities, addressing the endogeneity of commuting times. By constructing instrumental variables based on exogenous city characteristics from the 2016 ACS, the study isolates the causal effects of commuting on wages. The findings suggest that marital status drives the gender difference in commuting premiums, with married women and single men demanding higher wages to compensate for longer commutes. This chapter contributes to a broader understanding of wage-commute trade-offs and the socio-economic consequences of commuting time. The third chapter explores the interplay between job flexibility, residential location sorting, and wage determination through a monocentric city model. The model incorporates both high- and low-skilled workers and employs a bid-rent framework to determine housing prices and the spatial distribution of labour. The study finds that high-skilled workers' job flexibility significantly impacts their commuting decisions and urban spatial sorting patterns. In low-flexibility settings, high-skilled workers tend to live near the central business district, earning higher wages to offset the high cost of central real estate and commuting. Conversely, increased job flexibility enables these workers to relocate to more distant, affordable areas, thereby reducing the equilibrium skill premium. Together, these chapters provide a comprehensive analysis of how commuting, gender, and job flexibility interact to shape wage patterns and urban spatial structures in contemporary cities.
Ocular Effects of Scleral Lens Wear on Dry Eye Patients
(University of Waterloo, 2024-11-14) Otchere, Heinz
Purpose: Dry eye disease (DED) is among the most complex ocular surface diseases to treat. Complaints of ocular discomfort and dryness are common in DED patients and in contact lens wearers. The use of SL to restore the integrity of the ocular surface in a more severe DED has become increasingly accepted among eye care practitioners. However, little is known about this treatment regimen and its impact on ocular surface in mild to moderate DED. Also, the potential impact of coated SL designs incorporating Hydra-PEG (polyethylene glycol) technology on ocular surface health has not yet been fully investigated. This thesis aimed to address this gap in knowledge and determine whether SL (uncoated or Hydra-PEG) could be used as a viable option for patients who are experiencing milder forms of DED. Over the course of the study, participants were asked to complete DE questionnaires; lens settling and vision, corneal thickness, osmolarity and matrix metalloproteinase 9 (MMP-9) in the pre-corneal tear film were investigated. The study also examined the relationship between the respective parameters and compared the two lens pairs. Methods and Materials: The study was a prospective, double-masked, randomized, dispensing, crossover clinical trial involving five visits, where 20 subjects with mild to moderate dry eye disease (DED) were enrolled. Eligibility of the participants was confirmed following the Tear Film and Ocular Society (TFOS) Diagnostic Report in the first visit: presence of symptoms using the Ocular Surface Disease Index (OSDI) and Standardized Patient Evaluation of Eye Dryness (SPEED) questionnaires (OSDI ≥ 13, SPEED ≥ 4), plus osmolarity values (> 308 mOsmol/L in either eye or interocular difference of > 8 mOsmol/L) and or a positive MMP-9 result (using InflammaDry® test kit) or both. The second visit involved randomization and dispensing of customized hydra-PEG coated or uncoated SL, where each pair of lenses were worn on a daily wear basis for four weeks. Prior to dispensing the lenses, high contrast (HCVA) and low contrast acuities (LCVA) were recorded. The central corneal clearance (CCC) was measured with VisanteTM OCT to determine lens settling over time. Two standard clinical questionnaires (contact lens impact on quality of life (CLIQ) and contact lens dry eye questionnaire 8 (CLDEQ-8)) and an internally developed wearing habit and subjective rating questionnaire were provided to subjects and completed. The third visit (after 4 weeks) involved follow-up of the first randomized SL, where the lenses were evaluated, and clinical measurements repeated. A wash-out period of at least 48 hours was allowed before dispensing (visit 4) and follow-up (visit 5) of the other pair of SL, using the same procedures, measurement protocols and visit schedule. The SL used in the study were Zen™ RC (Alden Optical, Bausch & Lomb, Lancaster, NY, USA) available in only two diameters (14.80 and 15.40 mm), with a central thickness of 250 µm. Results: Eighteen females and two males, mean age 29.10 ± 7.48 years, participated in the study. The overall OSDI and SPEED scores were 36.45 ± 17.08 and 12.50 ± 4.03 respectively. There was no significant difference in the CLIQ and CLDEQ-8 scores between uncoated and coated SL. In terms of wearing habit and subjective ratings, no statistically significant differences were observed in any of the parameters (wear time, dryness, burning, vision, and comfort). This suggests that the use of hydra-PEG coated SL did not show greater performance compared to the uncoated SL. The central corneal clearance (CCC) at the dispensing visit was 260 ± 40 (range: 200 - 300 µm) for both lens pairs. This significantly reduced to 190 ± 40 µm (lens settling: 70 ± 42 µm) for the uncoated SL and 200 ± 30 µm (lens settling: 70 ± 43 µm) for the coated SL at the follow-up visits, (all, p < 0.001). Comparing the CCC for the two lens pairs at the follow-up visits, no significant difference was observed, thus, the lens pairs settled at similar rates. In terms of HCVA and LCVA between the two lens pairs at both the dispensing and follow-up visits, there were no significant differences between them. Also, no significant correlations were found comparing the CCC with HCVA and LCVA of each lens pair at both visits. The CCT at the baseline and follow-up visits were: baseline: 560.55 ± 32.28 µm, post wear of uncoated SL: 557.65 ± 32.10 µm, and post wear of coated SL: 560.50 ± 34.02 µm. There were no significant differences for either lens type for central corneal thickness (CCT) at the baseline and follow-up visits (all, p > 0.05). Also, no significant correlations between CCC and CCT were observed at baseline or follow-up visits. These results demonstrated there were minimal corneal hypoxic effects when these SL were worn on a daily wear basis. For osmolarity measures, there was a statistically significant difference between the baseline and follow-up visit for the coated lenses (311.00 ± 14.86 vs 302.85 ± 7.96 mOsmol/L; p = 0.04). While this is statistically significant, the clinical relevance of this small difference remains questionable. Comparing the two lens pairs, no significant difference was found at all visits. The inflammaDry® test results indicated that 80 % of the participants tested positive for elevated MMP-9 at the baseline visit. There was a reduction in MMP-9 positive test results following the SL wear, however, there were no significant differences between the baseline and follow-up visits for each lens pair. Comparing the two lens pairs, no significant difference was observed. For either lens, no correlation was observed between osmolarity and MMP-9 test results. Conclusion: There is a potential for using SL to manage symptoms in subjects suffering from mild to moderate DED, as the overall wearing habit and subjective ratings showed > 70 % of lens tolerance among the study cohort. SL wear over the month of wear in this cohort induced little change to the cornea or conjunctival tissue. Furthermore, SL may appear to marginally reduce tear film osmolarity, however, further studies are needed to confirm this result and its impact on subjective dryness. The clinical phenomenon of lens settling needs further investigation, especially on its impact on conjunctival morphology. In this cohort of subjects of mild to moderate DED, the hydra-PEG coating technology did not show superior performance over the uncoated lens for any of the factors assessed. Keywords: dry eye disease. scleral contact lens, hydra-PEG, osmolarity, inflammadry, cornea
Safe Memory Reclamation Techniques
(University of Waterloo, 2024-11-14) Singh, Ajay
This dissertation presents three paradigms to address the challenge of concurrent memory reclamation, manifesting as use-after-free errors that arise in concurrent data structures using non-blocking techniques. Each paradigm aligns with one of our three objectives for practical and safe memory reclamation algorithms. Objective 1: Design memory reclamation algorithms that are fast, have a bounded memory footprint, and are easy to use — requiring neither intrusive changes to data structures nor specific architecture or compiler support. These algorithms should also deliver consistent performance across various workloads and be applicable to a wide range of data structures. To achieve this, we introduce the neutralization paradigm with the NBR (Neutralization-Based Reclamation) algorithm and its enhanced version, NBR+ (Optimized Neutralization-Based Reclamation). These algorithms use POSIX signals and a lightweight handshaking mechanism to facilitate safe memory reclamation among threads. By relying solely on atomic reads and writes, they achieve bounded garbage and high performance with minimal overhead compared to existing algorithms. They are straightforward to implement, similar in reasoning and programming effort to two-phased locking, and compatible with numerous data structures. Objective 2: Eliminate the asymmetric synchronization overhead in existing reclamation algorithms, which often incur costly memory fences while eagerly publishing reservations, as seen in algorithms like hazard pointers and hazard eras. We propose the reactive synchronization paradigm, implemented through deferred memory reclamation and POSIX signals. This mechanism enables threads to privately track memory references (or reservations) and share this information on demand, using the publish-on-ping algorithm. This approach serves as a drop-in replacement for hazard pointers and hazard eras and includes a variant (EpochPOP) that combines epochs with the robustness of hazard pointers to approach the performance of epoch-based reclamation. Objective 3: Completely eliminate the batching common in current reclamation algorithms to allow immediate memory reclamation, similar to sequential data structures, while maintaining high performance. We introduce Conditional Access, a hardware-software co-design paradigm implemented in a graphite multi-core simulator. This paradigm leverages cache coherence to enable efficient detection of potential use-after-free errors without explicit shared-memory communication or additional coherence traffic. Conditional Access provides programmers with hardware instructions for immediate memory reclamation with minimal overhead in optimistic data structures. To validate our claims, we designed and conducted extensive benchmark tests to evaluate all proposed algorithms on high-end machines under various scenarios. We paired these algorithms with several real-world concurrent data structures, representing various memory access patterns, and compared their time and space efficiency against numerous state-of-the-art memory reclamation algorithms, demonstrating significant improvements.

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