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Reduced-Order Modeling and Data Assimilation of the El Niño–Southern Oscillation
No full textSimulations of complex fluid dynamics problems or climate models take weeks to complete even when run parallel in state-of-the-art supercomputers. Given computational resource constraints and the need for adaptable simulation settings, cost-efficient and accurate algorithms are essential. In this thesis, we explore stable, efficient, and accurate methodologies when applied to the El Niño–Southern Oscillation (ENSO), which integrates coupled atmosphere, ocean, and sea surface temperature (SST) mechanisms in the equatorial Pacific. ENSO is one of the most influential and complex climate phenomena, affecting weather patterns across the globe.
ENSO consists of irregular oscillations between warm (El Niño) and cold (La Niña) phases in the Pacific Ocean, significantly impacting global weather patterns. Due to ENSO's inherent complexity and uncertainties, it is particularly suited for stochastic modeling. By modeling these uncertainties, stochastic simulations offer a more accurate representation of ENSO's variability, including its irregular periods and amplitudes. We first study the effects of stochastic perturbations on ENSO dynamics and introduce novel modeling and numerical schemes based on the Wiener Chaos Expansion (WCE). The key idea behind WCE is the explicit discretization of white noise through Fourier expansion. We also compare these methods with Monte Carlo (MC) simulations. Our findings demonstrate that the simulation of the linear stochastic ENSO model driven by the Ornstein-Uhlenbeck process using WCE requires far less computational resources and gives more accurate results compared to MC ensembles. This part of the thesis provides an alternative efficient approach for simulations of stochastic climate models and quantification of statistical moments,i.e, mean and variance.
In the next stage of this research, we explore a reduced-order modeling (ROM) framework based on the POD-Galerkin method when applied to a nonlinear ENSO model. POD-Galerkin reduced order modeling aims to reduce the computational complexity and present high-dimensional problems~(usually PDEs) with reduced-order equations (ODEs). POD modes are optimal in capturing the system’s dominant
features, making it particularly effective for reducing the dimensionality of systems governed by PDEs. By capturing the full-order ENSO (PDE) model with only four modes and four reduced-order equations, we achieve a substantial reduction in computational complexity without significant loss of accuracy. Due to the special properties of the model, we introduce a novel approach using different POD bases, but the same time coefficients for all model components. Moreover, we employ machine learning methods to explore different ROM and model discovery techniques in this part.
The final part of this thesis focuses on the data assimilation of the nonlinear stochastic ENSO model, which forms the core results of this research. We first demonstrate the validity of POD-Galerkin reduced order modeling for the stochastic ENSO driven by the Ornstein-Uhlenbeck process. We project SPDEs onto POD modes derived from the deterministic model and introduce the reduced-order stochastic equations (SDEs). After setting up the filtering framework, we combine these equations and artificial observations in the Pacific ocean, based on realistic experiments, to estimate the ENSO-related SST anomalies. We employ particle filters and test the efficiency using different number of particles and ensembles. From novel ENSO modeling to uncertainty quantification, from reduced order modeling to nonlinear filtering, this thesis provides a promising approach for accurate and efficient predictions of ENSO-related climate variables
Projector Calibration via Overlapping Point Cloud Distance Minimization
No full textProjection mapping is a technique that transforms any 3D surface into an interactive display by projecting visuals that conform to the surface’s shape. Camera and projector calibration is a fundamental prerequisite for accurate spatial measurement and perception in projection mapping. The calibration of projectors is necessary to ensure that they correctly map the surface they are projecting onto. An accurately calibrated projector will have the image projected perfectly in line with the intended surface, without any misalignment. Such alignment is important for a number of applications, one of which is projection mapping, in which multiple projectors are used to create immersive visual displays on complex surfaces such as buildings, stages, or statues.
Since projector calibration involves highly nonlinear relationships between the projector's parameters, a nonlinear optimization is required. Typically such optimizations include reprojection error as the objective functions, which is also one of the most commonly used objective function to calibrate projectors. However, in scenarios where there is a lack of ground truth reprojection error fails to accurately align the multiple overlapping projector point clouds, resulting in visible gaps between them instead of forming a continuous surface.
To address this issue, this thesis proposes a multi-step optimization with a novel global objective function. To analyze its robustness, the proposed optimization is tested both on simulated and on multiple real world configurations. Experimental results show that the proposed approach achieves higher calibration accuracy compared to existing methods, while also maintaining low runtime.
The proposed multi-step optimization process parameterizes the calibration problem as a function of the degree of stereo overlap to improve accuracy. The stereo overlap plays a key role in projection mapping, influencing calibration accuracy and system cost. Understanding the relationship between stereo overlap and calibration error allows for reducing overlap while maintaining acceptable accuracy, thus reducing the number of cameras needed and cutting costs.
In summary, this thesis introduces a novel global objective function that minimizes the distance between overlapping projector point clouds, rather than relying solely on reprojection error. It also provides insight into the required overlap between devices, including both cameras and projectors, helping to achieve higher accuracy while efficiently covering an entire projection surface that may not be uniform
Interaction of electromagnetic fields with two-dimensional materials at the interface between dielectric media
No full textThis thesis investigates the interaction of electromagnetic plane waves with two-dimensional (2D) materials approximated by infinitesimal sheets positioned at interfaces between non-magnetic, isotropic, lossless dielectrics. On their own, 2D materials offer a host of useful properties, including high carrier mobility, dopant-free tuning through the application of external electromagnetic fields or stacking, as well as significant anisotropy. When combined with the excitation of plasmon modes to enhance light-matter interactions, the range of potential applications broadens greatly, including, for example, high-speed optical computation and enhanced light trapping in solar cells.
In this thesis, a new derivation of the boundary condition for out-of-plane response is presented for a 2D material immersed in an infinite homogeneous dielectric. To account for the influence of distinct dielectric surrounding media, Fresnel coefficients are derived using a vacuum gap method. This approach yields novel dispersion relations for surface plasmons that incorporate the out-of-plane response of 2D materials. In the presence of distinct surrounding dielectrics, the out-of-plane mode hybridizes with the in-plane longitudinal plasmon mode. The hybridization is destroyed when the surrounding materials are made identical. Additionally, expressions for the conservation of energy and momentum are derived in terms of the Fresnel field amplitudes for the 2D materials described by singular current sheets. The vacuum gap method is also applied to solve the conservation equations in the presence of dielectric media, as this avoids controversial notions of electromagnetic momentum in media. The electromagnetic stress tensor derived through the vacuum gap method satisfies conservation of linear momentum, thus confirming that the forces on a 2D material can be self-consistently separated from those on surrounding dielectrics.
This theoretical framework is applied to both graphene and phosphorene. For graphene, the reflectance, transmittance, and absorption characteristics are compared with and without considering the out-of-plane response. The analysis confirms that the influence of the out-of-plane component is minimal for plasmon modes at low frequencies as is often assumed, but becomes significant at high frequencies. Forces calculated around frequencies and wavenumbers defined by the plasmon dispersion relation showed significant amplification. However, the new non-monotonic dispersion profile of the hybridized plasmon mode introduces additional resonant and antiresonant behaviour in the forces. To emphasize the in-plane anisotropy of phosphorene, only in-plane response was considered, with a focus on forces in the plasmonic regime at low frequencies. Based on numerical examples, predictions are made for possible future experimental studies of both plasmon modes in the presence of the out-of-plane response and forces on 2D materials for possible optomechanical and sensing applications
Device-Algorithm Co-Optimization of TiOₓ-based Resistive Switching Devices
No full textThe rapid advancement of artificial intelligence (AI) and growing demand for high-performance computing have exposed key limitations in von Neumann architectures, particularly energy inefficiency and data movement bottlenecks. Resistive Random Access Memory (RRAM) has emerged as a promising candidate for next-generation memory technologies, offering non-volatility, high integration density, and the potential for energy-efficient Compute-In-Memory (CIM) architectures. This thesis focuses on the development and optimization of TiOₓ-based RRAM devices, with a particular emphasis on their application in CIM systems.
The work begins with a comprehensive exploration of the device characteristics of TiOₓ-based RRAM, including the influence of electrode materials, oxygen stoichiometry, and physical dimensions on device performance. Through interface engineering and material stack optimization, we achieve significant improvements in forming voltage, endurance, and retention, enabling low-power operation and high reliability. The optimized devices exhibit stable bipolar switching behavior with forming voltages below 1.5 V and operation currents under 100 μA, making them suitable for integration with advanced CMOS technologies.
Building on the optimized device performance, we propose a state-aware multi-bit programming algorithm that significantly reduces the number of programming steps and improves the efficiency of multi-bit operations. The algorithm leverages the state-dependent conductance modulation of RRAM devices, enabling precise control over resistance states and mitigating the effects of fast relaxation and retention loss. Additionally, we introduce an electrical annealing method to further enhance the long-term stability of multi-bit programming, demonstrating its effectiveness in extending the refresh period for CIM applications.
To bridge the gap between device-level optimization and system-level implementation, we present a back-end-of-line (BEOL) integration process for TiOₓ-based RRAM devices on CMOS chips. The integration process is validated through the successful fabrication and characterization of 1T1R arrays, demonstrating reliable resistive switching behavior and compatibility with existing CMOS technologies. This integration paves the way for the development of RRAM-based CIM macros, which combine RRAM arrays with peripheral circuits for high-performance AI computing.
Finally, we discuss future directions for device optimization, hardware-aware CIM design, and system-level integration. Key challenges include reducing programming current, improving retention stability, and developing reconfigurable CIM architectures for emerging AI workloads. The insights and methodologies developed in this thesis provide a foundation for the continued advancement of RRAM technologies and their integration into next-generation computing systems.
In summary, this thesis contributes to the field of RRAM-based CIM by addressing critical challenges in device optimization, multi-bit programming, and CMOS integration. The proposed solutions not only enhance the performance and reliability of RRAM devices but also provide a pathway for their practical implementation in energy-efficient AI hardware
Investigation of Neck Posture and Muscle Activity on Cervical Spine Impact Kinematics Using a Finite Element Human Body Model
No full textWhiplash-associated disorders (WAD) define a broad range of symptoms affecting the neck such as pain and stiffness, reported in up to half of motor vehicle collisions. WAD are typically associated with, but not limited to, low-severity rear impacts. The high incidence of WAD and high socioeconomic cost have led to significant, but still inconclusive, efforts to better understand the associated causal injury mechanisms. Neck posture and muscle behaviour are known factors that contribute to neck injuries during low-severity vehicle impacts. Quantifying the effects of such parameters at the tissue level is challenging in experimental studies but may be informed by computational human body models (HBMs). However, three limitations in neck models have been identified: (1) neck muscle controllers were often tuned to a narrow set of specific load cases, (2) neck models were unable to predict the S-shape (upper cervical spine flexion) magnitude observed in experiments during rear impacts, and (3) defining tissue-level injury thresholds remain elusive for the neck. To address these challenges, three studies were defined for this thesis using a contemporary head and neck finite element model from an average-stature male HBM (Global Human Body Models Consortium (GHBMC)) with the aim of enhancing and evaluating the tissue-level response associated with WAD injury risk following rear impact.
In the first study, a new closed-loop controller with a single set of parameters for neck muscle activation based on known reflex mechanisms was implemented in the GHBMC model. The updated model was assessed over a range of impact conditions. The closed-loop controller had an average cross-correlation to the experimental data of 0.699 for 14 load cases, including frontal, rear and lateral impacts, within 2% to 9% of previous calibrated open-loop approaches.
In the second study, a novel methodology was developed to integrate pre-tension in the neck muscles based on experimental cadaveric and volunteer data and assessed in rear impact scenarios. Only the model with pre-tension achieved flexion of the upper cervical spine at the same magnitude as reported in impact tests with volunteers. Pre-tension increased the muscle tissue strain relative to cases with no pre-tension, and, in some cases, led to potentially injurious-level strains, reinforcing that the initial muscle strain is essential for evaluating WAD injury risk.
In the third study, the methods from the first and second studies (closed-loop muscle activation controller and muscle pre-tension) were combined to assess possible WAD injury mechanisms based on tissue-level analysis of stresses and strains in 4g to 10g rear impacts. The existing injury metrics and tissue-level muscle strains identified that hyperextension was the main injurious phase in low-severity rear impacts. In addition, muscle pre-tension and activation changed the distribution of muscle strains, better representing the injury regions reported in the literature.
New model developments and knowledge obtained from the three studies completed in this research can be generalizable to other HBMs and can be applied to evaluate the efficacy of vehicle safety systems, ultimately reducing injury risk and diminishing societal costs related to low-severity neck injury in the future. Further, the enhanced neck model developed in this work has identified possible areas of experimental interest for future neck injury research
Building an Inter-Institutional and Cross-Functional Research Data Management Community: From Strategy to Implementation
No full textWith the release of the Tri-Agency Research Data Management Policy (Government of Canada, 2021) in March 2021, all Canadian post-secondary institutions and research hospitals that administer Tri-Agency funding were required to develop and post institutional research data management (RDM) strategies by March 1, 2023. As institutions finalized their strategies, they began to consider what implementation would look like. To support inter-institutional, cross-functional dialogue around implementation, a two-day, SSHRC-supported workshop was hosted at the University of Waterloo in September 2023. Over 30 institutions of varying sizes and research intensities sent cohorts of three staff members—representing libraries, information technology, and research offices—to participate in five dialogues with researchers and key partners around challenges and collaborative solutions in RDM strategy implementation.
Through the dialogues, the participants made the following key high-level recommendations:
1. Provide clear expectations and communication around compliance, requirements and service provision
2. Secure buy-in from campus leadership
3. Identify financial support for RDM at institutions
4. Build staff capacity and support skills development, both within institutions and nationally
5. Create and sustain intra-institution coordination, collaboration and service integration around RDM
6. Explore inter-institution coordination and collaboration, including support for smaller institutions in meeting their RDM needs and requirements
7. Support the development of Indigenous Data Sovereignty policies and guidelines
8. Increase researcher training, support, and awareness around RDM
9. Develop national RDM support structures for collaboration and strategy, including a common understanding and language of RDM
These recommendations are relevant to a broad audience, including research funders, government agencies mandating and/or supporting RDM, professional organizations, academic consortia, university administration, researchers and practitioners.
The Waterloo workshop did not provide definitive answers as to how these recommendations should be implemented; rather, it was an opportunity to build a community of professionals from across RDM-supporting units who can work towards successful strategy implementation in their institutions. However, community is not enough. Institutions, research funders, and infrastructure providers must all commit to supporting RDM, whether through clear and timely guidance, sustainable resource provision, hiring and development of staff, or regular and robust training offerings. Ongoing, stable funding—both at the national and the institutional level—will also be necessary to ensure that support and services can be sustained for the long term. RDM is—and has always been—a shared responsibility, and all the parties mentioned above must step up to ensure that its implementation is a success in Canada.Social Sciences and Humanities Research Council of Canada (611-2022-3006) || University of Waterloo || University of Calgary || University of Ottawa || Canadian Association of Research Libraries || OCLC || Compute Ontario || Digital Research Alliance of Canad
Development of a biodegradable contact lens system for ocular drug delivery
No full textPurpose:
The aim of this thesis was to develop a biodegradable ocular drug delivery system (comprising contact lenses and conjunctival inserts), with the ability of controlled release of PVA using a physical cross linking method.
Methods:
In the first experimental chapter (Chapter 3), a commercially available 3D printer was modified and the 3D printing process with a gelatin methacrylate (GelMA) biomaterial ink was optimized. GelMA biomaterial ink was selected as a base material owing to its biocompatibility and demonstrated high levels of controllability. In the second experimental chapter (Chapter 4), the shape fidelity of the 3D printed contact lenses loaded with polyvinyl alcohol (PVA) as a therapeutic agent was evaluated. In the third experimental chapter (Chapter 5), a physical crosslinking strategy was evaluated as a potential modification to prolong the release of PVA from the GelMA network. In the final experimental chapter (Chapter 6), the degradation mechanism of GelMA-based conjunctival inserts in the presence of a matrix metallo proteinase enzyme (MMP9) is described, along with its correlation with the release of PVA.
Results
The results demonstrate that by tuning the printing conditions and ink parameters, soft biomaterials from a GelMA ink of higher shape fidelity and accuracy can be efficiently printed even on low-cost 3D printers. Moreover, a fine interplay between the dye concentration (CDye) and exposure time is key to effective polymerization and resolution, ensuring successful printing of the hydrogel biomaterials with higher structural integrity. It is further possible to add PVA to these lenses and the PVA release curves showed that about 1300 µg of PVA was released over the study duration of 24 hrs. PVA can act as a viscosity enhancer and protect corneal cells against dry eye related desiccation stress. These results were confirmed with the help of non-invasive keratograph break-up time measurements on a 3D printed eyeball model, where 1.4% (w/v) PVA solution displayed significantly higher tear break-up time compared to a control (p < 0.05).
The release rate of PVA from these biomaterials can be controlled by applying short freeze thaw cycles, which induces formation of crystalline domains in the interpenetrating network. The appearance of endothermic peaks at 48 °C and 60 °C in differential scanning calorimetry (DSC) thermograms and 20°–2θ peaks in X-ray diffraction (XRD) patterns suggest the formation of these crystalline domains. The release profiles of the PVA containing hydrogels prove that crystalline domain formation could support sustained PVA release and control its initial burst release. The release profiles displayed highest linearity with the Korsmeyer–Peppas model (0.9944 < R² < 0.9952), indicating that these systems follow non-Fickian or anomalous transport.
The results from this thesis highlight the versatility of 3D printing to fabricate GelMA-based conjunctival inserts. There are different factors that influence the MMP-mediated degradation of GelMA hydrogels, and that the degradation rate is a function of MMP9 enzyme concentration. The 3D printed GelMA/PVA inserts formed a semi-interpenetrating network. The results from the biodegradation study show that about 59.6% and 83.3% of the P-Gel-5% hydrogel was degraded at the end of 8 hrs and 12 hrs in the presence of 50 µg/ml MMP9 enzyme solution. Similarly, about 47.0%, 50.2% and 81.7% of the P-Gel-5% hydrogel was degraded at the end of 8 hrs, 12 hrs, and 24 hrs, respectively, in the presence of 25 µg/ml MMP9 enzyme solution. However, no degradation was observed in the control group incubated with PBS at the end of the study duration of 24 hrs. The PVA release graphs demonstrate that 222.7 ± 20.3 µg, 265.5 ± 27.1 µg and 242.7 ± 30.4 µg of PVA was released at 25 µg/ml, 50 µg/ml and 100 µg/ml MMP9 enzyme concentrations after 24 hrs. These results suggest that degradation rate of GelMA is a function of MMP9 enzyme concentration and the PVA release profiles of these inserts in the presence of different concentrations of MMP9 showed highest linearity with the Korsmeyer–Peppas model.
Conclusions
This thesis has investigated 3D printed CLs and conjunctival inserts for controlled ocular drug delivery. Several important findings have been reported, and the shortcomings have been discussed in this thesis. With the advancements in 3D printing, personalized ophthalmic devices fabricated from 3D printing could be a commercially viable option, but the cost and transparency need to be considered
A remotely delivered exercise-based rehabilitation program for patients with persistent chemotherapy-induced peripheral neuropathy (EX-CIPN): Protocol for a phase I feasibility trial
No full text© 2025 Antonen et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.Background
Chemotherapy-induced peripheral neurotoxicity (CIPN) is a prevalent adverse effect of chemotherapy agents that is estimated to be present in 2/3 of patients who receive neurotoxic chemotherapy. In 30-40% of these patients, CIPN signs and symptoms can persist for months or years post-treatment. Recent studies have supported exercise as a feasible and possibly effective intervention for CIPN; however, more rigorous studies are needed to confirm feasibility, estimate efficacy, and clarify risk. In response, we developed an innovative virtual exercise-based rehabilitation program (EX-CIPN) for cancer survivors with persistent CIPN.
Methods
This study is a phase I study conducted at the Princess Margaret Cancer Centre in cancer survivors with persistent CIPN, with a focus on feasibility, acceptability, and safety. A total of 40 patients aged 18 or older, with persistent CIPN at least 6 months after chemotherapy completion will be recruited and receive the EX-CIPN program. The EX-CIPN program is a 10-week virtual home-based intervention that includes an individualized exercise program supported with a mobile application (Physitrack), wearable technology (FitBit), and weekly virtual check-ins with an oncology exercise specialist. This primary outcome of feasibility will be assessed by examining accrual, retention, and adherence rates. Acceptability will be assessed through qualitative interviews. Safety events will be monitored and reported based on CTCAE v5. Secondary outcomes will be collected using questionnaires and physiological assessments at baseline (T1), after the intervention (T2), and 3-months after intervention (T3).
Conclusion
This phase I study will determine intervention feasibility, acceptability, and safety and will inform the planning for a future Phase II RCT with the EX-CIPN intervention.Cancer Research Society, 1276376
Direct Laser Writing of Laser-Induced Graphene for flexible EMI shielding applications
No full textAs electronic devices become an inseparable part of modern life, the challenge of electromagnetic interference (EMI) continues to grow, driving the demand for next generation shielding materials that are not only lightweight and flexible but also highly efficient in safeguarding future technology. Graphene, a carbon-based material, has attracted significant attention for EMI shielding applications due to its exceptional properties. Various methods exist for producing graphene, such as mechanical exfoliation, chemical vapor deposition, and the reduction of graphene oxide. However, among these, direct laser writing (DLW) has recently gained the most recognition. This method stands out due to its scalability, cost-effectiveness, patternability, and eco-friendliness, making it superior to other graphene production techniques. Additionally, the graphene produced using this approach has demonstrated excellent potential for use in EMI shielding.
As a proof-of-concept, we explore the performance of laser-induced graphene (LIG) derived via different DLW techniques, in particular, CO2, fiber, and ultraviolet (UV) laser systems, for EMI shielding. The effects of laser parameters, particularly laser fluence, on graphene microstructure, electrical conductivity, and EMI shielding effectiveness are systematically investigated. Results indicate that CO2 and fiber lasers both produce highly conductive and structurally optimized LIG with a total shielding effectiveness of 28.6 dB and 29.8 dB, respectively, whereas UV laser processing results in lower conductivity and reduced shielding performance. To enhance EMI shielding, a novel LIG- polydimethylsiloxane (PDMS) hybrid shield (LPHS) is developed, integrating multilayer LIG within a PDMS matrix. The LPHS design significantly improves the shielding efficiency up to 40 dB through enhanced absorption and multiple reflection pathways while maintaining flexibility and handleability of the shields. This study provides a comprehensive framework for optimizing LIG synthesis for EMI shielding applications, paving the way for scalable and cost-effective solutions in modern electronic systems
Assessing the Prevalence of Energy Hardship in Canada: An Enhanced Methodology Integrating Energy Modeling
No full textThe building sector has focused on addressing climate mitigation through the electrification and decarbonization of households, mainly by upgrading building envelope and replacing combustion-based systems with electric heat pumps. However, the impact of climate change could result in more households falling into energy hardship, underscoring the need for an equitable transition. A household falls under energy hardship if its energy expenditure ratio exceeds the defined threshold, regardless of its total household income. Energy hardship encompasses both energy poverty and energy burden. Thus, a household experiences energy poverty if i) its energy expenditure ratio exceeds the defined threshold and ii) the total household income is below low-income cut-offs. A household experiences an energy burden if i) its energy expenditure ratio exceeds the defined threshold and ii) the total household income is above low-income cut-offs. Techno-economic factors such as energy costs, type of fuel, building age and envelope condition, and type of heating and cooling system in a household contribute to energy hardship. Socioeconomic factors such as income, education, and race are also catalysts to the problem, making energy poverty a multidimensional issue with great implications for public health, social equity, and environmental sustainability.
This study aims to quantify energy hardship in Canada in 2019 and 2021 and identify the building and household characteristics experiencing energy poverty. Further analysis was completed for Ontario, Canada to establish a correlation and quantify the impact climate change and household electrification (e.g., switching from a natural gas furnace to a heat pump) have on energy hardship. The study identified key indicators of energy poverty and burden, confirming that household income is the most critical factor. Nearly 40% of Canadian households with an income of CAD50,000 after tax came out of energy hardship after insulation and airtightness upgrades. However, the adoption of an electric heat pump worsened energy hardship by doubling the costs of electricity despite the fact that reduced energy use intensity by nearly 50%. This concluded that energy efficiency measures alone are not enough to remove households out of energy poverty (or hardship, in general) in Ontario.
By analyzing the prevalence, causes, and impacts of energy poverty in Canada and Ontario, this study aims to develop a replicable methodology that provides evidence-based insights to inform policy decisions and support the development of effective interventions that are inclusive and equitable for all household