Waterloo Research

Permanent URI for this collectionhttps://uwspace.uwaterloo.ca/handle/10012/9972

This is the University of Waterloo Research collection.

Waterloo faculty, students, and staff can contact us or visit the UWSpace guide to learn more about depositing their research.

NOTE: This collection does not include graduate Theses & Dissertations or Major Research Projects.

Browse

Now showing 1 - 20 of 2518

2-Aminopurine-modified DNA homopolymers for robust and sensitive detection of mercury and silver
(Elsevier, 2017-01-15) Zhou, Wenhu; Ding, Jinsong; Liu, Juewen
Heavy metal detection is a key topic in analytical chemistry. DNA-based metal recognition has advanced significantly producing many specific metal ligands, such as thymine for Hg2+ and cytosine for Ag+. For practical applications, however, robust sensors that can work in a diverse range of salt concentrations need to be developed, while most current sensing strategies cannot meet this requirement. In this work, 2-aminopurine (2AP) is used as a fluorescence label embedded in the middle of four 10-mer DNA homopolymers. 2AP can be quenched up to 98% in these DNA without an external quencher. The interaction between 2AP and all common metal ions is studied systematically for both free 2AP base and 2AP embedded DNA homopolymers. With such low background, Hg2+ induces up to 14-fold signal enhancement for the poly-T DNA, and Ag+ enhances up to 10-fold for the poly-C DNA. A detection limit of 3 nM is achieved for both metals. With these four probes, silver and mercury can be readily discriminated from the rest. A comparison with other signaling methods was made using fluorescence resonance energy transfer, graphene oxide, and SYBR Green I staining, respectively, confirming the robustness of the 2AP label. Detection of Hg2+ in Lake Huron water was also achieved with a similar sensitivity. This work has provided a comprehensive fundamental understanding of using 2AP as a label for metal detection, and has achieved the highest fluorescence enhancement for non-protein targets. (C) 2016 Elsevier B.V. All rights reserved.
A 2-class maintenance model with dynamic server behavior
(Springer, 2019-04-29) Granville, Kevin; Drekic, Steve
We analyze a 2-class maintenance system within a single-server polling model framework. There are C+f machines in the system, where C is the cap on the number of machines that can be turned on simultaneously (and hence, be at risk of failure), and the excess f machines comprise a maintenance float which can be used to replace machines that are taken down for repair. The server’s behavior is dynamic, capable of switching queues upon a machine failure or service completion depending on both queue lengths. This generalized server behavior permits the analysis of several classic service policies, including preemptive resume priority, non-preemptive priority, and exhaustive. More complicated polices can also be considered, such as threshold-based ones and a version of the Bernoulli service rule. The system is modeled as a level-dependent quasi-birth-and-death process and matrix analytic methods are used to find the steady-state joint queue length distribution, as well as the distribution for the sojourn time of a broken machine. An upper bound on the expected number of working machines as a function of C is derived, and Little’s Law is used to find the relationship between the expected number of working machines and the expected sojourn time of a failed machine when f=0 or f≥1. Several numerical examples are presented, including how one might optimize an objective function depending on the mean number of working machines, with penalty costs attributed to increasing C or f.
A 30-Year Study of Impacts, Recovery, and Development of Critical Effect Sizes for Endocrine Disruption in White Sucker (Catostomus commersonii) Exposed to Bleached-Kraft Pulp Mill Effluent at Jackfish Bay, Ontario, Canada
(Frontiers, 2021-04-22) Ussery, Erin J.; McMaster, Mark E.; Servos, Mark. R.; Miller, David H.; Munkittrick, Kelly R.
Jackfish Bay is an isolated bay on the north shore of Lake Superior, Canada that has received effluent from a large bleached-kraft pulp mill since the 1940s. Studies conducted in the late 1980s found evidence of reductions in sex steroid hormone levels in multiple fish species living in the Bay, and increased growth, condition and relative liver weights, with a reduction in internal fat storage, reduced gonadal sizes, delayed sexual maturation, and altered levels of circulating sex steroid hormones in white sucker (Catostomus commersonii). These early studies provided some of the first pieces of evidence of endocrine disruption in wild animals. Studies on white sucker have continued at Jackfish Bay, monitoring fish health after the installation of secondary waste treatment (1989), changes in the pulp bleaching process (1990s), during facility maintenance shutdowns and during a series of facility closures associated with changing ownership (2000s), and were carried through to 2019 resulting in a 30-year study of fish health impacts, endocrine disruption, chemical exposure, and ecosystem recovery. The objective of the present study was to summarize and understand more than 75 physiological, endocrine, chemical and whole organism endpoints that have been studied providing important context for the complexity of endocrine responses, species differences, and challenges with extrapolation. Differences in body size, liver size, gonad size and condition persist, although changes in liver and gonad indices are much smaller than in the early years. Population modeling of the initial reproductive alterations predicted a 30% reduction in the population size, however with improvements over the last couple of decades those population impacts improved considerably. Reflection on these 30 years of detailed studies, on environmental conditions, physiological, and whole organism endpoints, gives insight into the complexity of endocrine responses to environmental change and mitigation.
3D bioprinting of liver-mimetic construct with alginate/cellulose nanocrystal hybrid bioink
(Elsevier, 2018-03-01) Wu, Yun; Lin, Zhi Yuan (William); Wenger, Andrew; Tam, Kam C.; Tang, Xiaowu (Shirley)
3D bioprinting is a novel platform for engineering complex, three-dimensional (3D) tissues that mimic real ones. The development of hybrid bioinks is a viable strategy that integrates the desirable properties of the constituents. In this work, we present a hybrid bioink composed of alginate and cellulose nanocrystals (CNCs) and explore its suitability for extrusion-based bioprinting. This bioink possesses excellent shear-thinning property, can be easily extruded through the nozzle, and provides good initial shape fidelity. It has been demonstrated that the viscosities during extrusion were at least two orders of magnitude lower than those at small shear rates, enabling the bioinks to be extruded through the nozzle (100µm inner diameter) readily without clogging. This bioink was then used to print a liver-mimetic honeycomb 3D structure containing fibroblast and hepatoma cells. The structures were crosslinked with CaCl2 and incubated and cultured for 3 days. It was found that the bioprinting process resulted in minimal cell damage making the alginate/CNC hybrid bioink an attractive bioprinting material.
A 3D ellipsoidal volumetric foot–ground contact model for forward dynamics
(Springer, 2018-04-01) Brown, Peter; McPhee, John
Foot–ground contact models are an important part of forward dynamic biomechanic models, particularly those used to model gait, and have many challenges associated with them. Contact models can dramatically increase the complexity of the multibody system equations, especially if the contact surface is relatively large or conforming. Since foot–ground contact has a large potential contact area, creating a computationally efficient model is challenging. This is particularly problematic in predictive simulations, which may determine optimal performance by running a model simulation thousands of times. An ideal contact model must find a balance between accuracy for large, conforming surfaces, and computational efficiency.Volumetric contact modelling is explored as a computationally efficient model for foot–ground contact. Previous foot models have used volumetric contact before, but were limited to 2D motion and approximated the surfaces as spheres or 2D shapes. The model presented here improves on current work by using ellipsoid contact geometry and considering 3D motion and geometry. A gait experiment was used to parametrise and validate the model. The model ran over 100 times faster than real-time (in an inverse simulation at 128 fps) and matched experimental normal force and centre of pressure location with less than 7% root-mean-square error.In most gait studies, only the net reaction forces, centre of pressure, and body motions are recorded and used to identify parameters. In this study, contact pressure was also recorded and used as a part of the identification, which was found to increase parameter optimisation time from 10 to 164 s (due to the additional time needed to calculate the pressure distribution) but helped the results converge to a more realistic model. The model matched experimental pressures with 33–45% root-mean-square error, though some of this was due to measurement errors.The same parametrisation was done with friction included in the foot model. It was determined that the velocity-based friction model that was used was inappropriate for use in an inverse-dynamics simulation. Attempting to optimise the model to match experimental friction resulted in a poor match to the experimental friction forces, inaccurate values for the coefficient of friction, and a poorer match to the experimental normal force.
3D N-doped hybrid architectures assembled from 0D T-Nb2O5 embedded in carbon microtubes toward high-rate Li-ion capacitors
(Elsevier, 2019-02) Tolami Hemmati, Sahar; Li, Ge; Wang, Xiaolei; Ding, Yuanli; Pei, Yu; Yu, Aiping; Chen, Zhongwei
Herein, a unique nitrogen-doped T-Nb2O5/tubular carbon hybrid structure in which T-Nb2O5 nanoparticles are homogeneously embedded in an in-situ formed nitrogen-doped microtubular carbon is synthesized, utilizing a facile and innovative synthesis strategy. This structure addresses the poor electron conductivity and rate capability that hinder T-Nb2O5's promise as an anode for Li-ion devices. Such a distinctive structure possesses a robust framework that has ultrasmall active nanocomponents encapsulated in highly conductive carbon scaffold with hollow interior and abundant voids, enabling fast electron/ion transport and electrolyte penetration. Moreover, nitrogen-doping not only ameliorates the electronic conductivity of the heterostructure, but also induces pseudocapacitance mechanism. When evaluated in a half-cell, the as-prepared material delivers a specific capacitance of 370 F g−1 at 0.1 A g−1 within 1–3 V vs. Li/Li+ and excellent cyclability over 1100 cycles. A high energy density of 86.6 W h kg−1 and high power density of 6.09 kW kg−1 are realized. Additionally, a capacitance retention as high as 81% after 3500 cycles is achieved in an Li-ion Capacitor (LIC) with activated carbon as the cathode and nitrogen-doped T-Nb2O5/tubular carbon as the anode.
3D representation and CNC machining of 2D digital images
(Elsevier, 2018-01-01) Sood, Sumit; Duvedi, Ravinder Kumar; Bedi, Sanjeev; Mann, Stephen
In this paper a new paradigm for CNC carving of digital images in the form of lookalike three-dimensional (3D) surfaces on wooden or metallic plaques is discussed. This work is focused on development of a single page windows based console application for conversion of a two-dimensional (2D) digital image into a 3D freeform surface representation in the form of a point cloud data and STL format. Subsequently, the 3D surface data is then used for generating an efficient toolpath data for 3-axis CNC finish machining using a ball end mill tool. The results from the developed algorithm are validated using a machining simulation in the virtual environment of an Open-GL based 3D graphical simulator ToolSim [1].
A multi-resolution approach to point cloud registration without control points
(MDPI, 2023-02-20) Bash, Eleanor A.; Wecker, Lakin; Rahman, Mir Mustafizur; Dow, Christine F.; McDermid, Greg; Samavati, Faramarz F.; Whitehead, Ken; Moorman, Brian J.; Medrzycka, Dorota; Copland, Luke
Terrestrial photographic imagery combined with structure-from-motion (SfM) provides a relatively easy-to-implement method for monitoring environmental systems, even in remote and rough terrain. However, the collection of in-situ positioning data and the identification of control points required for georeferencing in SfM processing is the primary roadblock to using SfM in difficult-to-access locations; it is also the primary bottleneck for using SfM in a time series. We describe a novel, computationally efficient, and semi-automated approach for georeferencing unreferenced point clouds (UPC) derived from terrestrial overlapping photos to a reference dataset (e.g., DEM or aerial point cloud; hereafter RPC) in order to address this problem. The approach utilizes a Discrete Global Grid System (DGGS), which allows us to capitalize on easily collected rough information about camera deployment to coarsely register the UPC using the RPC. The DGGS also provides a hierarchical set of grids which supports a hierarchical modified iterative closest point algorithm with natural correspondence between the UPC and RPC. The approach requires minimal interaction in a user-friendly interface, while allowing for user adjustment of parameters and inspection of results. We illustrate the approach with two case studies: a close-range (<1 km) vertical glacier calving front reconstructed from two cameras at Fountain Glacier, Nunavut and a long-range (>3 km) scene of relatively flat glacier ice reconstructed from four cameras overlooking Nàłùdäy (Lowell Glacier), Yukon, Canada. We assessed the accuracy of the georeferencing by comparing the UPC to the RPC, as well as surveyed control points; the consistency of the registration was assessed using the difference between successive registered surfaces in the time series. The accuracy of the registration is roughly equal to the ground sampling distance and is consistent across time steps. These results demonstrate the promise of the approach for easy-to-implement georeferencing of point clouds from terrestrial imagery with acceptable accuracy, opening the door for new possibilities in remote monitoring for change-detection, such as monitoring calving rates, glacier surges, or other seasonal changes at remote field locations.
ABCD and beyond: From grain merchants to agricultural value chain managers
(Canadian Food Studies, 2015-09-08) Clapp, Jennifer
The world of agricultural commodity trading firms has changed over the years, although corporate concentration has long been a defining feature of this sector. The four dominant agricultural trading firms—the ABCDs (ADM, Bunge, Cargill and Louis-Dreyfus)—have a long history dating back to the 1800s and early 1900s. First established as private, family-owned grain merchant companies with specific geographical specialties, these firms have since evolved to be quite complex companies. They buy and sell grain as well as a host of other agricultural and non-agricultural commodities, while they also undertake a range of activities from finance to production to processing and distribution. New entrants into this space have also taken on complex structures and activities in a bid to stay competitive. In many ways the world’s major grain trading firms now operate more like cross-sectoral “value chain managers” on a truly global scale compared to their grain trade origins. High degrees of concentration combined with control over a vast array of activities give these firms enormous power to shape key aspects of the global food landscape. As a result, the agricultural commodity-trading sector has important implications for farmer livelihoods, hunger and the environment. Following a brief snapshot of the main firms that dominate global grain trading today, I examine the major trends that have reshaped the sector in the past decade. I then outline the main challenges that these changes present for the food system, and suggest possible research directions moving forward.
Abelian, amenable operator algebras are similar to C∗ -algebras
(Duke University Press, 2016-12) Marcoux, Laurent W.; Popov, Alexey I.
Suppose that H is a complex Hilbert space and that ℬ(H) denotes the bounded linear operators on H. We show that every abelian, amenable operator algebra is similar to a C∗-algebra. We do this by showing that if 𝒜⊆ℬ(H) is an abelian algebra with the property that given any bounded representation ϱ:𝒜→ℬ(Hϱ) of 𝒜 on a Hilbert space Hϱ, every invariant subspace of ϱ(𝒜) is topologically complemented by another invariant subspace of ϱ(𝒜), then 𝒜 is similar to an abelian C∗-algebra.
ABOVE WATER: An Educational Game for Anxiety
(Association for Computing Machinery, 2016-10-16) Wehbe, Rina Renee; Watson, Diane K.; Fortes Tondello, Gustavo; Ganaba, Marim; Stocco, Melissa; Lee, Alvin; Nacke, Lennart
We present Above Water - a digital/physical hybrid game to inform people about the available strategies to cope with two types of Anxiety Disorders - Generalized Anxiety Disorder and Panic Disorder. The game teaches players about existing treatments. This hybrid game is designed to inspire players to share their experiences and develop their own personal narrative. The document also outlines an assessment strategy to study the game and determine its effectiveness as a game for health. The game is designed to educate non-institutionalized individuals with clinical anxiety and panic disorder. Potential players may be diagnosed, seeking intervention information, or a supportive friend.
ABOVE WATER: Extending the Play Space for Health
(Association for Computing Machinery, 2016-11-06) Wehbe, Rina Renee; Watson, Diane K.; Fortes Tondello, Gustavo; Nacke, Lennart
ABOVE WATER is a game that disseminates information about Clinical Anxiety Disorders, particularly Generalized Anxiety Disorder and Panic Disorder. This game focuses on teaching players about treatments as well as providing a safe space for discussion of personal experiences. This game focuses on using the physical world (physical space, physical and tangible cards) and the digital world (accessible by any phone or tablet with a modern web browser) as part of its gameplay.
ABOVE WATER: Extending the Play Space for Health
(Association for Computing Machinery, 2016-11-06) Wehbe, Rina Renee; Watson, Diane K.; Fortes Tondello, Gustavo; Nacke, Lennart
ABOVE WATER is a game that disseminates information about Clinical Anxiety Disorders, particularly Generalized Anxiety Disorder and Panic Disorder. This game focuses on teaching players about treatments as well as providing a safe space for discussion of personal experiences. This game focuses on using the physical world (physical space, physical and tangible cards) and the digital world (accessible by any phone or tablet with a modern web browser) as part of its gameplay.
Academic Librarians and Systematic Reviews: an emerging role in the social sciences
(2017-05-31) Stapleton, Jackie; Brown, Sarah
This conference presentation was delivered at CAPAL Conference on May 31, 2017, Toronto, Ontario. Abstract: Systematic review support is expanding beyond health and medical librarianship. The rise of knowledge translation in the social sciences has resulted in a corresponding increase in the number and type of review studies conducted by researchers and supported by granting agencies such as SSHRC. Academic librarians in the social sciences are poised to position themselves as collaborators in the research process, providing guidance and bringing valuable expertise to the research team. Relating from personal experiences, the speakers will address three points related to systematic reviews in the social sciences: 1) Role of the librarian on a systematic review project; 2) Professional expectations including authorship and adherence to systematic search/reporting standards; 3) Specific challenges faced by the social sciences librarian.
Academic Status Institutional Comparisons Report
(Librarians' and Archivists' Association of the University of Waterloo, 2020-03) Hale, Jordan; Hutchinson, Rebecca; Weaver, Kari D.
This report was distributed to Librarians' and Archivists' Association of the University of Waterloo members in advance of consultations pertaining to a potential change in employment status.
Accelerating peroxidase mimicking nanozymes using DNA
(Royal Society of Chemistry, 2015-09-07) Liu, Biwu; Liu, Juewen
DNA-capped iron oxide nanoparticles are nearly 10-fold more active as a peroxidase mimic for TMB oxidation than naked nanoparticles. To understand the mechanism, the effect of DNA length and sequence is systematically studied, and other types of polymers are also compared. This rate enhancement is more obvious with longer DNA and, in particular, poly-cytosine. Among the various polymer coatings tested, DNA offers the highest rate enhancement. A similar acceleration is also observed for nanoceria. On the other hand, when the positively charged TMB substrate is replaced by the negatively charged ABTS, DNA inhibits oxidation. Therefore, the negatively charged phosphate backbone and bases of DNA can increase TMB binding by the iron oxide nanoparticles, thus facilitating the oxidation reaction in the presence of hydrogen peroxide.
Acceleration of Large Margin Metric Learning for Nearest Neighbor Classification Using Triplet Mining and Stratified Sampling
(University of Waterloo, 2021-01-15) Poorhevari, Parisa Abdolrahim; Ghojogh, Benyamin; Gaudet, Vincent C.; Karray, Fakhri; Crowley, Mark
Metric learning is a technique in manifold learning to find a pro- jection subspace for increasing and decreasing the inter- and intra-class variances, respectively. Some metric learning methods are based on triplet learning with anchor-positive-negative triplets. Large margin metric learning for nearest neighbor classification is one of the fundamental methods to do this. Recently, Siamese networks have been introduced with the triplet loss. Many triplet mining methods have been developed for Siamese nets; however, these techniques have not been applied on the triplets of large mar- gin metric learning. In this work, inspired by the mining methods for Siamese nets, we propose several triplet mining techniques for large margin metric learning. Moreover, a hierarchical approach is proposed, for acceleration and scalability of optimization, where triplets are selected by stratified sampling in hierarchical hyper- spheres. We analyze the proposed methods on three publicly avail- able datasets.
Acceptance of Commercially Available Wearable Activity Trackers Among Adults Aged Over 50 and With Chronic Illness: A Mixed-Methods Evaluation
(JMIR Mhealth Uhealth., 2016-01-27) Mercer, Kathryn; Grindrod, Kelly; Schneider, Eric; Li, Melissa; Chilana, Parmit; Giangregorio, Lora M.
Background: Physical inactivity and sedentary behavior increase the risk of chronic illness and death. The newest generation of “wearable” activity trackers offers potential as a multifaceted intervention to help people become more active. Objective: To examine the usability and usefulness of wearable activity trackers for older adults living with chronic illness. Methods: We recruited a purposive sample of 32 participants over the age of 50, who had been previously diagnosed with a chronic illness, including vascular disease, diabetes, arthritis, and osteoporosis. Participants were between 52 and 84 years of age (mean 64); among the study participants, 23 (72%) were women and the mean body mass index was 31 kg/m2 . Participants tested 5 trackers, including a simple pedometer (Sportline or Mio) followed by 4 wearable activity trackers (Fitbit Zip, Misfit Shine, Jawbone Up 24, and Withings Pulse) in random order. Selected devices represented the range of wearable products and features available on the Canadian market in 2014. Participants wore each device for at least 3 days and evaluated it using a questionnaire developed from the Technology Acceptance Model. We used focus groups to explore participant experiences and a thematic analysis approach to data collection and analysis. Results: Our study resulted in 4 themes: (1) adoption within a comfort zone; (2) self-awareness and goal setting; (3) purposes of data tracking; and (4) future of wearable activity trackers as health care devices. Prior to enrolling, few participants were aware of wearable activity trackers. Most also had been asked by a physician to exercise more and cited this as a motivation for testing the devices. None of the participants planned to purchase the simple pedometer after the study, citing poor accuracy and data loss, whereas 73% (N=32) planned to purchase a wearable activity tracker. Preferences varied but 50% felt they would buy a Fitbit and 42% felt they would buy a Misfit, Jawbone, or Withings. The simple pedometer had a mean acceptance score of 56/95 compared with 63 for the Withings, 65 for the Misfit and Jawbone, and 68 for the Fitbit. To improve usability, older users may benefit from devices that have better compatibility with personal computers or less-expensive Android mobile phones and tablets, and have comprehensive paper-based user manuals and apps that interpret user data. Conclusions: For older adults living with chronic illness, wearable activity trackers are perceived as useful and acceptable. New users may need support to both set up the device and learn how to interpret their data.
Access roads impact enzyme activities in boreal forested peatlands
(Elsevier, 2019-02-15) Saraswati, Saraswati; Parsons, Christopher T.; Strack, Maria
We investigated the impacts of resource access roads on soil enzyme activities in contrasting forested boreal peatlands (bog and fen). In August 2016, a total of 72 peat samples were collected from twelve 20 m long transects perpendicular to access roads, with a further six samples collected from undisturbed reference areas. Sampling locations represent a range in three variables associated with roads: 1) side of the road (upstream/downstream), 2) distance to a culvert (longitudinal; <2 and >20 m), and 3) distance from the road (lateral; 2, 6, and 20 m). Phenol oxidase and hydrolase (glucosidase, sulfatase, xylosidase, glucosaminidase, and phosphatase) enzyme activities were determined for each sample, in addition to water table depth, phenolic concentration, pH, and peat temperature. The average hydrolase activities in the fen were ~four times higher than in the bog. At the bog, the water table depth, phenolic concentration, pH and the activities of phenol oxidase, sulfatase, glucosidase, xylosidase and glucosaminidase were all significantly influenced by one or more road associated factors. The highest enzyme activities in the bog occurred on the downstream side of the road at plots located far from the culvert. In contrast, the flow of water in the fen was not perpendicular to the road. Consequently, no significant variations in water table depth, phenolic concentration, pH or enzyme activity were found with respect to road associated factors. Results indicate that road crossings in boreal peatlands can indirectly alter enzyme activities, likely as part of a causal chain following changes to hydrology and redox conditions. Two of six investigated enzymes had significantly higher activities in the road disturbed areas compared to undisturbed areas, suggesting ultimately that roads may enhance organic matter decomposition rates. However, adequate hydrologic connections through culverts and road construction parallel to the water flow can minimize the road-induced impacts.
Accumulative fold-forging (AFF) as a novel severe plastic deformation process to fabricate a high strength ultra-fine grained layered aluminum alloy structure
(Elsevier, 2018-02-01) Khodabakhshi, Farzad; Gerlich, Adrian P.
A novel severe plastic deformation (SPD) process termed accumulative fold forging (AFF) is introduced to fabricate a homogenous ultra-fine grained (UFG) layered metal structure by repetitive folding and forging aluminum alloy foil. The present work studies AFF applied to thin foils of AA8006 Al-Fe-Mn aluminum alloy after 26 folding steps to produce a UFG structure containing 67,108,864 layers across a 2mm thickness. The structure of the layers and grain refinement are studied using X-ray diffraction (XRD), field-emission scanning electron microscopy (FE-SEM) and scanning-transmission electron microscopy (STEM) analysis. The results indicate a well-bonded inter-layer structure with an average grain size of about 200nm parallel and 250nm perpendicular to the forging direction, while dislocation density increased to ~7.2×1015m−2 following AFF. The mechanical strength of the aluminum foil is evaluated in the terms of indentation hardness testing before and after AFF process. The processed UFGed layered material exhibited an average hardness value of ~61.5 Vickers as compared to the initial value of ~30.4 Vickers for the annealed foil alloy, which indicates an improvement of ~100% due to the contributions of grain refinement, work hardening and interfacial strengthening of the bonded layers.

Browse

Browsing Waterloo Research by Title