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Recent Submissions

Access status: Embargo ,
Genomic Characterization of Five Isolates of Blastocystis Subtype 7
(2026-04-27) Seaton, Gregory; No; Doctor of Philosophy; Department of Biochemistry & Molecular Biology; Not Applicable; Dr. Laura Wegener Parfrey; No; Dr. Claudio H. Slamovits; Dr. James M. Kramer; Dr. Morgan Langille; Dr. Andrew Roger
Blastocystis spp. are common, genetically diverse anaerobic colonizers of the gastrointestinal tracts of both humans and animals. Although they are traditionally regarded as parasites, their precise role in host health remains unclear, in part because cryptic genetic diversity is masked by morphological similarity among divergent lineages. Subtype 7 (ST7) contains several isolates (C, H, E, G and B) that have been shown to exhibit distinct phenotypic differences in experimental settings, suggesting genetic diversity within the subtype. This thesis presents a comparative genomic analysis of those five ST7 isolates, with a focus on genetic differences between the isolates. Genomes of four of the five isolates presented here are newly sequenced using a long-read-based assembly approach resulting in new genomic assemblies that are >98% complete and range from 19.8 (ST7C) to 20.2 (ST7G) Mbp in size and were found to be highly syntenic. Short-read data suggests these Blastocystis ST7 isolates are haploid. For two of the newly sequenced genomes, ST7C and ST7G, the assembly was complete enough to capture 8 and 9 complete chromosomes respectively. Through comparisons of shared syntenic scaffolds amongst isolates, 16 nuclear chromosomes could be hypothetically reconstructed in ST7C. Comparative analyses revealed clear evidence of genomic rearrangements in ST7G and ST7H relative to ST7C. Manual curation was used to create a high-quality gene annotation for ST7C that was propagated to the other genomes yielding 8625-8896 predicted genes per genome. The predicted gene set for ST7B contained 2593 more genes than a previously published genome analysis for this isolate. A pangenome analysis of the five isolates was conducted and a small (228) accessory genome was identified compared to a far larger core gene set (6198) shared by all the isolates. An abundance of endogenous viral elements belonging to the Midsized Eukaryotic Linear dsDNA (MELD) virus class were found and comparative analyses suggest that the MELD viruses first invaded the common ancestor of ST7 and ST6, and then greatly proliferated in the ST7 genomes. The analyses presented here offers insight into the genomic structure and differences between these Blastocystis ST7 isolates.
Access status: Open Access ,
Seismic Retrofit of Dry Precast Concrete Beam To Column Joint Using Shape Memory Alloy
(2026-04-27) Chen, DeZhen; Not Applicable; Master of Applied Science; Department of Civil and Resource Engineering; Not Applicable; N/A; Not Applicable; Pedram Sadeghian; Zoheir Farhat; Fadi Oudah
Superelastic shape memory alloy (SMA) is regarded as an ideal material for enhancing the seismic capacity of structures due to its superelasticity and self-centering properties. This research introduces and validates a new concept for the structural upgrade of seismically deficient precast concrete structures using SMA. The proposed approach establishes partial moment transfer at the beam-column joint, enabling the frame to partially resist lateral loads alongside the building's shear core. To achieve this, a novel device—termed the SMA Partial Moment Transfer (SMA-PMT) device—is developed and validated through experimental testing and analytical modeling using hybrid simulation. The research was executed in three stages, including model development, the experimental joint design and the experimental test. The discussion summarizes the behavior of the experimental joint specimens, focusing on joint moment capacity (yield moment), energy dissipation capabilities, and joint damage assessments. Recommendations for future research are also provided.
Access status: Open Access ,
Phase Change Materials and Storage Design for Pumped Thermal Energy Storage
(2026-04-24) VanLuxemborg, John; Not Applicable; Master of Applied Science; Department of Mechanical Engineering; Not Applicable; Dr. Michael Pegg; Not Applicable; Dr. Baafour Nyantekyi-Kwakye; Dr. Dominic Groulx
Pumped Thermal Energy Storage (PTES) is an emerging energy storage technology; a key component of the system is the Thermal Energy Storage (TES) unit. This thesis investigates the optimization of a multi-tube shell-and-tube TES unit through both numerical simulation and experimental material characterization to enhance thermal performance. A numerical model was developed to evaluate the performance of nine bare-tube configurations, varying from dual to oct-tube arrangements. The addition of longitudinal fins was explored to improve the charging time, while the impact of the length of the TES was also studied. In parallel to the initial numerical studies, potential Phase Change Materials (PCMs) were identified, and four selected materials, adipic acid, D-mannitol, hydroquinone, and LiNO3-LiOH (81:19 wt%), were characterized experimentally using Differential Scanning Calorimetry (DSC) and Thermogravimetric Analysis (TGA). The numerical results indicated that the Oct-4F configuration delivered the most efficient charging performance and highest energy storage density. It was found that a system length between 0.50 m and 0.75 m balanced a sustained power output with maximal latent energy utilization. Experimentally, the synthesized LiNO3-LiOH (81:19 wt%) eutectic proved to be the most viable PCM, exhibiting excellent thermal stability with a melting temperature of 176.24 °C and a latent heat of fusion of 385.28 J/g. However, when the Oct-4F geometry was simulated using the LiNO3-LiOH (81:19 wt%) eutectic and Therminol 59 as the Heat Transfer Fluid (HTF), the system was unable to complete charging within the target eight-hour window. This was driven by the combination of the PCMs extremely high latent heat of fusion and the substantially lower specific heat capacity of the HTF, indicating that further geometric or operational optimizations are required to fully harness the material’s storage potential.
Access status: Open Access ,
Hospital Location Optimization Mixed-Integer Linear Programming Model for Timely Access to EVT Treatment
(2026-04-27) Baradaran-Noveiri, Borna; Not Applicable; Master of Applied Science; Department of Industrial Engineering; Not Applicable; na; Not Applicable; Dr. Peter Vanberkel; Dr. Adela Cora; Dr. Noreen Kamal
Timely access to endovascular thrombectomy (EVT) is critical for improving outcomes in acute ischemic stroke, yet access varies across Canada due to geographic and system-level constraints. This thesis develops a mixed-integer linear programming (MILP) model to optimize the designation of Comprehensive Stroke Centers (CSCs) within existing stroke systems. The objective is to minimize population-weighted time to EVT treatment while incorporating patient routing, inter-facility transfers, time-dependent EVT eligibility decay, and feasibility constraints. Population and travel-time data were used to model access at a granular geographic level, and candidate CSC hospitals were identified through a structured feasibility assessment. Results show that optimized CSC configurations can reduce treatment times by up to 25 minutes and increase the projected number of patients receiving EVT by 7.42%. This framework provides a data-driven approach to improving stroke system design and reducing disparities in EVT access across Canada.
Access status: Open Access ,
Evolving Linear Controllers from YoLo State Capture
(2026-04-23) Hu, Zhengping; Not Applicable; Master of Computer Science; Faculty of Computer Science; Not Applicable; Dr. Andrew McIntyre; Not Applicable; Dr. Yannick Marchand; Dr. Malcolm Heywood
End-to-end deep reinforcement learning (DRL) has become a prominent paradigm for visual control, with wide application in robotics and autonomous systems. However, its monolithic architecture often presents challenges regarding interpretability, computational overhead, and deployment on resource-constrained edge devices. This thesis investigates a decoupled perception-decision framework that combines real-time object detection (YOLOv11n), Heuristic State Rectification (HSR), and Genetic Algorithms (GA). Unlike standard DRL methods that rely on large convolutional networks to map raw pixels directly to actions, our methodology compresses high-dimensional visual inputs into physically semantic, low-dimensional states, empowering minimalist controllers (e.g., linear models with fewer than 50 parameters) to handle complex non-linear dynamics. To address the inherent heteroscedasticity of visual noise in camera-based perception, we introduce a Dynamic Seed Resampling mechanism. Acting as an adaptive regularization strategy, it prevents the agent from overfitting to specific environmental initializations, thereby enhancing the robust generalization of the trained agents. Extensive evaluations against a Proximal Policy Optimization (PPO) baseline across five classic control benchmarks (CartPole, Acrobot, MountainCar, Pendulum, and LunarLander) demonstrates the efficacy of our approach. While the PPO baseline exhibited sensitivity to initialization and encountered bottlenecks in sparse-reward environments, our decoupled framework achieved highly consistent success rates on discrete action tasks with significantly reduced computational cost and thermal output. Furthermore, through an analysis of spatial drift, we empirically quantify the ``Visual Noise Barrier.'' The results elucidate that while the Vision-HSR-GA framework excels in dynamic macroscopic control, achieving absolute zero-velocity precision is fundamentally bottlenecked by the Signal-to-Noise Ratio (SNR) of the frontend perception module. Ultimately, this research validates the proposed framework as a robust, interpretable, and hardware-friendly alternative for visual control tasks.
Access status: Embargo ,
Green technologies for the derivation of bioactive compounds from sea cucumber (Cucumaria frondosa) by-products and the subsequent development of gel platforms for biomedical purposes
(2026-04-23) Lin, Jianan; Not Applicable; Doctor of Philosophy; Department of Process Engineering and Applied Science; Not Applicable; Ozan Ciftci; Yes; Su-Ling Brooks; Guangling Jiao; Azadeh Kermanshahi-pour
The Atlantic sea cucumber, Cucumaria frondosa, generates substantial processing by-products that remain underutilized despite being rich in bioactive compounds and functional biopolymers. This dissertation establishes an integrated marine biorefinery framework that couples green sequential extraction with biomaterial engineering to valorize C. frondosa viscera into both high-value extracts and marine-derived delivery platforms, advancing circular marine bioprocessing for biomedical applications. Supercritical carbon dioxide (scCO2) was employed as a green solvent-based pretreatment to recover lipid fractions and enhance downstream accessibility of polar constituents. Subsequent extractions using ethanol (EtOH) and water significantly improved saponin recovery while preserving antioxidant activity. Sequential scCO2 extraction followed by a 24-hour extraction with 70% EtOH achieved saponin yields of 16.26 ± 2.47 mg OAE/g, comparable to the conventional hexane defatting-ultrasonic extraction (17.31 ± 0.60 mg OAE/g), while coupled 24-hour hot-water extraction yielded 12.99 mg OAE/g, demonstrating that scCO2-assisted sequential extraction provides an efficient and environmentally favourable alternative for saponin isolation. The residual biomass was further repurposed into sea cucumber polysaccharide crudes (SCPSC), which served as a marine-derived structural precursor for gel fabrication. To establish a scalable, crosslinker-free gelation platform, injectable and self-healing polyelectrolyte complex (PEC) hydrogels were developed using chitosan, marine chondroitin sulphate or algal fucoidan, hydrolyzed collagen, and cellulose nanocrystals (CNC). These physically crosslinked networks exhibited tunable swelling (~178-766%), low E-factors down to 0.98, and solid-like rheological behaviour (G' ≫ G"), with mesh sizes of ~5-10 nm and strength modulated through formulation control. Building on this framework, chitosan/SCPSC/CNC/sodium dodecyl sulfate (SDS)-based PEC porous networks were prepared via a semi-dissolution acidification sol-gel transition (SD-A-SGT) followed by poor-solvent-induced aggregation. Despite the compositional heterogeneity of the crude extracts, the resulting organogels formed robust physically crosslinked networks, as evidenced by G' ≫ G", with no crossover between 25 and 50 °, rubbery plateau moduli reaching ~30 kPa, and compressive Young’s moduli up to 18.36 kPa. Equilibrium swelling ratios ranged from ~170 to 770%, with CNC-reinforced formulations typically reaching ~290-350%, while low SDS-containing organogels showed exceptional uptake (~770%) driven by electrostatic chain expansion. Controlled solvent exchange and drying converted these organogels into aerogels and structure-preserving hexane-exchanged xerogels with tunable architectures and functions. Using curcumin as a hydrophobic model payload, the dried gels achieved encapsulation efficiencies up to 45.56 ± 5.37% and loading capacities up to 41.92 ± 3.85 mg/g, while densified conventional xerogels reached a maximum apparent loading of 45.91 ± 4.19 mg/g. Structural and thermal analyses confirmed suppression of curcumin crystallinity via nanoconfinement within the porous matrices. In vitro release studies demonstrated architecture-dependent kinetics, with aerogels reaching ~94% cumulative release within 24 h, compared with ~73% for densified xerogels, enabling tunable burst-to-sustained delivery profiles. Encapsulation also markedly improved curcumin stability against light and heat relative to free curcumin.