VictorJuiz/thesis huggingface dataset:
In the Face of “Climate Colonialism”: A Critical Analysis of the Government of Canada’s First Nation Adapt Program as a Settler Colonial Policy Response to the Climate Crisis in First Nations Communities
Keywords: Climate Crisis
Enclosure
Indigenous Environmental Justice
Indigenous Planning
Settler Colonialism

First Nations communities have been planning adaptively with the environment since time immemorial and are now forced to respond to the colonial climate crisis. First Nation Adapt (FN Adapt), operated by the Government of Canada, provides funding to projects planning for these increasing changes in First Nations communities. However, the program’s position within a settler colonial institution requires interrogating FN Adapt, as such institutions have an ongoing legacy of enclosing Indigenous planning practices. This research provides a consolidated critique of the program by applying a test of enclosure, to see how the program interacts with Indigenous planning practices, outlined through literature on Indigenous Planning Theory, Anti-Colonial Planning Theory, and Indigenous Environmental Justice. Though FN Adapt makes strides towards supporting culturally relevant planning and fills a void in accessing necessary funding, its overarching government structures limit the program’s ability to fully support Indigenous planning, instead enclosing elements of Indigenous planning practices.
An Equity Evaluation of Bus Prioritization Measures within the Toronto Transit Commission’s 5-year Service Plan 10-year Outlook
Keywords: Bus Prioritization
Equity-Seeking Transit Riders
Service Planning
Toronto
Transit Equity
Transport Poverty

In December of 2019, the Toronto Transit Commission proposed a new equity service policy to provide improved bus service for low socio-economic neighbourhoods in Toronto. While this policy will provide enhanced service for individuals within these communities, methods and data constraints may exclude equity-seeking riders outside these areas promoting greater barriers to access. With this concern in mind, this thesis aims to thoroughly examine the proposed equity policy using quantitative methods and provide recommendations that remove further barriers to transport poverty and transport-related social exclusion.
That Other Side of Our Province: Finding Crisis, Isolation, Rurality and Place in Northwestern Ontarian Theatre
Keywords: Isolation
Northwestern Ontario
Performance Studies
Place Studies
Rural
Theatre

In our vast province of Ontario, discourse surrounding theatre making is heavily focused on large southern and eastern cities. With an autoethnographic approach, this work begins the conversation of theatre making in Northwestern Ontario and the isolation that is within and geographically surrounding that place. With a focus on place studies and rurality, this work anchors to the isolated city of Thunder Bay Ontario and how its challenged uniquely in comparison to other cities in the province. By conducting a small survey of professional theatre in Thunder Bay over the last 5 years, this work revealed a call for a new discourse around theatre in Northwestern Ontario and rural cities in light of the mistreatment of racialized, Indigenous and marginalized bodies. In addition, this work heeds suggestions for radical change within theatre making in places with unique specificity and calls into question how to address theatre in isolated places.
Stomatal Control in C4 Plants with Different Biochemical Sub-pathways
Keywords: C4 Ecology
C4 Plants
Plant Physiological Ecology
Stomatal Physiology

C4 NAD-ME species occurs in drier regions than C4 NADP-ME species, indicating differences in drought responses; however, a physiological mechanism explaining the geographical discrepancies remain uncertain. This study examined gas exchange patterns that might explain different distributions observed between two subtypes of C4 photosynthesis. We measured the response of leaf gas exchange to vapor pressure deficit (VPD) and CO2 in plants from six distinct C4 clades having closely related NAD-ME and NADP-ME species using a Li-Cor 6400 gas exchange system. We found that NAD-ME exhibited higher reductions in stomatal conductance with increases in VPD than NADP-ME species but no consistent subtype differences in C4 cycle activity, represented by the initial slope of the A response to intercellular CO2 concentration. Based on these results, we hypothesize the greater response of gs to increasing VPD may enable NAD-ME plants to outperform NADP-ME plants in hot, dry environments where VPD is normally high.
Post-operative Functional Disability in Unrecognized Cognitive Impairment (POF) Study: An Observational Cohort Study in Patients Undergoing Non-cardiac Surgery
Keywords: Cognitive impairment
Functional impairment
Older adults
Postoperative complications
Surgery

Identifying individuals with unrecognized cognitive impairment may facilitate informed decision-making about the benefits and risks of undergoing surgery in these patients, and how underlying cognitive impairment relates to functional ability. Using simple screening tools in older surgical patients at baseline, post-operative 30-, 90-, and 180-days, we determine the prevalence of unrecognized cognitive impairment and its association with postoperative functional ability. Across all four timepoints, we found a prevalence of unrecognized cognitive impairment in 24.5% of participants (n = 53). A repeated-measures ANOVA showed that there was no significant difference in patients with or without cognitive impairment between baseline and 30-days for IADL, F (1, 43) = 0.389, p = 0.536 or for WHODAS, F (1,45) = 1.62, p = 0.210. We found that simple screening tools for cognitive impairment such as single cognitive question or AD8 can identify potential cognitive impairment in older surgical patients. Follow-up for formal diagnosis is needed.
Semantic Segmentation Models to Analyze Histological Images of Re-endothelialized Lungs
Keywords: Lung recellularization
Machine learning
Re-endothelialization
Semantic Segmentation

The re-endothelialization of an acellular lung scaffold is evaluated through the analysis of histological images, which is an unscalable process due to its time-consuming, work-intensive, and subjective nature. Deep learning methods present a means to accurately automate medical image analysis and in particular, semantic segmentation can be used to evaluate re-endothelialized lungs. In this thesis, we investigated the ability of semantic segmentation to determine key performance metrics in re-endothelialized mouse lungs. The cell seeding coverage, which quantifies the distribution of seeded cells in the lung scaffold, was accurately predicted by our implementation of semantic segmentation. Ruptured and dilated vessels, which deform the lung and signify problems with the recellularization procedure, were segmented with potential for improvement. Through patch-based learning, data augmentation, and transfer learning techniques, we significantly ameliorated model performance. We find that our work provides a proof-of-concept for the standard use of semantic segmentation to analyze recellularized lung images.
PathDiff: Systematic Differential Testing Using Symbolic Analysis
Keywords: Differential Testing
Program Analysis
Semantic Bugs
Symbolic Analysis

Discrepancies among software programs that implement the same specification frequently lead to bugs and vulnerabilities. Differential fuzzers, such as NEZHA, increase the efficiency of finding discrepancies by guiding the fuzzing process with domain-independent behavioural asymmetries. However, the random nature of fuzzing inevitably causes NEZHA to miss discrepancies, even if the pair of paths where the discrepancies lie has already been discovered. In this thesis, we propose PathDiff, a novel differential testing tool that leverages path asymmetry to systematically find all discrepancies for given path-pairs. PathDiff keeps the execution path in one program and iteratively negates each branch in the other program for discrepancies, exhaustively enumerating all discrepancies for given inputs. We have implemented PathDiff and evaluated it against NEZHA on 16 applications, including 12 applications used in the NEZHA paper as well as 4 newly selected ones. The results show that PathDiff finds 4.1× more discrepancies than NEZHA.
Design of an Accelerated Longitudinal Cohort to Estimate Employment Trajectories using Multistate Models in a Population of Young Adults with Systemic Lupus Erythematosus
Keywords: Accelerated longitudinal design
Employment trajectory
experimental design
multi state model
simulation
Systemic Lupus Erythematosus

Background: Systemic Lupus Erythematosus (SLE) is the most common form of Lupus. Objectives: To design a prospective accelerated longitudinal cohort (ALC) to study the employment trajectory of young-adult SLE patients. Methods: We analyzed a multicentre retrospective cohort of SLE patients using multi-state models to assess risk factors for unfavourable employment trajectories. Additionally, we conducted a simulation study to design an ALC that optimized the precision and bias for the probability of transitioning between employment states. Results: Due to insufficient data, model convergence in the retrospective cohort and simulation study was poor. Conclusions: ALCs are an attractive design for prospective studies; however, it is not an appropriate study design for the present population. For rare diseases such as SLE, the number of transitions is likely to be small. Future work should focus on expanding the objective to include additional populations who would benefit from interventions on undesirable employment trajectories.
Utilizing Square Wave Voltammetry Pulse Potential Frequency Profiling for Nucleic Acid Detection
Keywords: Biosensor
Diagnostic
Electrochemistry
Nucleic acid

Developing sensitive and reliable biosensors for nucleic acids that can operate without the use of reagents is critical to expanding the use of genome-level data in routine health monitoring. Towards this goal, a reagentless electrochemical sensor was developed to detect target nucleic acids in amounts as low as 30 fmol. Unlike similar sensors that utilize peak square wave voltammetry current as the variable for detection, this sensor relies on square wave voltammetry frequency-current profiling. The main advantage of this approach, in comparison to similar sensor architectures, is its resistance to false positives – a critical feature for enhancing commercialization. This concept was also applied to the multiplexed detection of three unique nucleic acid targets on a single electrode, using a single redox reporter, under probe saturating conditions. Finally, it was demonstrated that frequency profiling reveals fundamental kinetic information about nucleic acid structures, establishing a simple, low-cost method to elucidate probe kinetics.
Soft Electronic Materials Inspired by Biologic Derivatives for use in Neural Regenerative Applications
Keywords: alginate
hydrogels
microglia
neuroinflammation
regenerative medicine

Regenerative medicine is an interdisciplinary field of medicine that develops methodologies to replace damaged or diseased cells. The recent understanding that neural precursor cell (NPC) behaviour is controlled by signaling from their micro-environment has been at the forefront of development for neurological therapies. The application of electric fields has been shown to promote NPC migration and electrodes have been the most used channel by which brain signals have been investigated and manipulated for therapeutic purposes. A challenge facing neural interfacing therapeutics is seamlessly incorporating electrodes that are typically made of rigid and stiff materials with the soft and dynamic nature of the brain where they would be situated. By minimizing this mechanical mismatch, the aim is to attenuate the host’s biological inflammatory response. In this work hydrogel-based materials are explored as potential alternatives to the existing less biocompatible counterparts with the goal of promoting brain repair following injury or disease.
Predictive Quality Assessment for Fused Filament Fabrication
Keywords: Additive manufacturing
Computer vision
Machine learning

Additive manufacturing is an emerging class of manufacturing technologies which are particularly suitable for producing complex and custom parts. Fused filament fabrication is a common type of additive manufacturing for producing thermoplastic-based parts. The aim of this study is to support future work towards closed-loop control for fused filament fabrication by integrating and extending in-situ monitoring and process understanding. First, a dataset designed to be useful for closed-loop control is proposed. This dataset features 359 tensile specimens fabricated with in-situ images and tensile property measurements. Based on this dataset, machine learning and computer vision methods were applied to develop a model which can navigate the complex relationships between process parameters, in-situ observations, and strength of the final product. Several variants of the model were proposed and their relative effectiveness was studied.
Factors Affecting Orphans and Vulnerable Children Realizing their Right to Education in Mozambique
Keywords: child rights
education
Mozambique
NGOs
orphans and vulnerable children
Sub-Saharan Africa

Despite notable efforts from countries and non-governmental organizations (NGOs) around the world, the right to education among orphans and vulnerable children (OVCs) in Sub-Saharan Africa is far from realized. Despite an increase in the number of girls in school over the past few decades, we cannot overlook the failures and growing disparities faced by the poorest and most vulnerable children. OVCs continue to suffer and face unfair educational access and opportunities despite initiatives by governments, development agencies, international organizations, NGOs, Education for All, Millennium Development Goals, and their successive Sustainable Development Goals. NGOs play a significant role in the educator sector of most African countries. This thesis focuses on the local response of an NGO in Mozambique and seeks to answer: What factors affect (hinder or enhance) OVCs realizing their right to education with a special focus on the female OVCs among them?
A Speculative Hardware Scheduler Supporting Priority Updates
Keywords: Accelerators
Harware-Software Codesign
Irregular Parallelism
Multicores
Programming Models
Speculation

Many important algorithms schedule their tasks according to a priority order. While parallel priority schedulerscommonly implement task enqueue and dequeueMin operations, some algorithms need a priority update operation that alters the scheduling metadata for a task, which is not supported by existing hardware. We present Hive, a task-based multicore architecture that extracts fine-grained parallelism from algorithms with priority updates. Like prior hardware systems for ordered parallelism, Hive uses data- and control-dependence speculation and a large speculative window to execute tasks in parallel and out of order. Hive supports updates by identifying the scheduler-carried dependence, and speculating on it with task versioning, distinct from data versioning. Hive enables safe speculative updates to the schedule to better utilize speculation tracking resources and uncover more parallelism. Across nine benchmarks, Hive improves performance at 256 cores by up to 2.8x over the next best hardware solution.
Service Engagement in Virtually Delivered Psychosis Treatment: A Systematic Review and Mixed Methods Evaluation
Keywords: Early Psychosis Intervention
Mixed Methods Research
Psychosis
Service Engagement
Virtual Care

Disengagement remains a significant dilemma within mental healthcare, and among conditions characterized by psychosis specifically. Traditionally delivered in-person, specialized psychosis services, including early psychosis intervention (EPI), have promptly transitioned to virtual delivery amid the COVID-19 pandemic, despite limited research on engagement in virtual psychosis care. This thesis consists of a systematic review and mixed methods evaluation; the latter examining rates, predictors, and experiences of (dis)engagement within a virtual EPI program. Electronic health records of a cohort of EPI patients enrolled between April-November 2020 were examined; individual interviews and focus group discussions were conducted with patients, family members, and clinicians. Approximately 15.5% of the sample formally disengaged by follow-up (15-24 months); 12.3% disengaged within the first 9 months. Disengagement was associated with lack of early use of SEE (HR=.28, 95% CI=.12-.67) and NEET (HR=3.04, 95% CI=1.03-8.98). Qualitative analysis revealed 5 salient themes and service recommendations, with most preferring a hybrid model.
Reduced Order Numerical Modelling of Electric Commuter Vehicle Battery Thermal Management Systems
Keywords: Battery Thermal Management
Electric Vehicle Thermal Management
Numerical Modeling
Reduced Order

Numerical modelling techniques have been used to study the performance of thermal management solutions for electric vehicle applications. However, these numerical methods require specific knowledge of input parameters and need to be designed carefully to balance accuracy and computational effort before they can be applied to real-world scenarios. The work presented in this thesis follows the process of developing and applying a reduced-order numerical model of an electric vehicle battery pack under wide variety of battery architectures and real-world scenarios. It includes characterizing the thermal properties of Li-ion battery cells for the use of application-specific thermal models, developing a computationally efficient thermal model of an electric vehicle battery and thermal management system, and proposing improvements to an existing case-study vehicle. Changes to the pack architecture and thermal management system resulted in reductions of maximum temperature of 8% and improvements in temperature uniformity of over 66%.
Investigating the Role of JAK2 in Intestinal Homeostasis and Disease
Keywords: Gastrointestinal System
Intestinal Epithelial Cell
Janus Kinases

Intestinal epithelial cells (IECs) are critical in the maintenance of intestinal homeostasis. Janus kinase (JAK) and signal transducers and activators of transcription (STAT)-mediated signalling coordinates the cell-cell communication underpinning many homeostatic, inflammatory, and host-defensive responses. Little is known about the role of JAK2 in IECs. To investigate the role of IEC JAK2 in homeostasis, we generated mice deficient in Jak2 using a Cre-loxP system. These mice exhibited increased intestinal barrier permeability, altered gene expression of tight junction proteins, and increases in TH2 and TH17 cytokine gene expression. Further, these mice exhibited greater histological evidence of intestinal inflammation and when subjected to experimental colitis, lost more body weight than control mice. Overall, IEC Jak2 deletion resulted in mild inflammation and impairments to the intestinal barrier, indicating IEC Jak2 may promote intestinal homeostasis.
Drug Response Prediction and Biomarker Discovery using Multimodal Deep Learning
Keywords: Biomarker
Deep Learning
Drug Discovery
Drug Repurposing
Drug Response Prediction
Multimodal

Patients with the same cancer type respond differently to the same drugs. This difference is partly due to genetic and other molecular variabilities among patients. Efforts in the pharmacogenomics field are underway to better understand the relationship between the patient’s genomic background and their response to therapy. Advances in molecular profiling approaches have paved the way for the systematic screening of drug effects in cancer cell lines. Numerous computational approaches have been proposed to address the sizeable combinatorial space of testing cell lines and drug pairs. Although deep learning algorithms outperform traditional methods, there are still many challenges in drug response prediction (DRP) that ultimately result in these models’ low generalizability, which hampers their clinical application. I have recognized and addressed some of the shortcomings of DRP methods by combining multiple cell line characterization data, addressing drug response data skewness, and improving chemical compound representation. The result is an open-source, Python-based, command-line program available at: https://github.com/LincolnSteinLab/DRP.
A Flat Plate Heat Exchanger for Waste Heat Recovery
Keywords: Falling Film
Fouling
Heat Exchanger
Heat Transfer
Thermal Spray
Waste Heat Recovery

A novel flat-plate drain water heat exchanger was developed and tested to reduce the overall energy consumption of household and commercial water heaters by increasing the cold water supply temperature through heat exchange with waste greywater. Characterization of the DWHR prototype unit demonstrated an average effectiveness of 0.401 across the entire operating flowrate range and an increase in effectiveness of approximately 0.031 on the highest-performing comparable DWHR unit. A novel thermally-sprayed resistive sensor was fabricated and tested to detect the relative amount of fouling on heat exchanger surfaces by locally heating the fluid volume around the sensor and measuring the associated cooling rate in a natural convection environment. The sensor demonstrated the ability to detect a decrease in overall heat transfer coefficient with an increase in thermal conductive resistance, using a curve-fitting lumped body transient conduction model, over a thermal conductive resistance range of approximately 0.05 to 0.6 ?.?/?.
Summer Climate Reconstruction using Tree-ring Blue Intensity in the Mackenzie Delta, Northwest Territories
Keywords: Blue intensity
Dendrochronology
Paleoclimatology
Tree ring
White spruce

This thesis uses tree rings from white spruce taken from the Mackenzie Delta to i) explore the potential to extend the region’s current tree-ring record by using subfossil trees buried under lake sediments, and ii) be the first study in the region to use the tree-ring parameter blue intensity.The sample set spanned 1105-2018, adding crucial sample replication prior to 1500 AD. The subfossil wood from lakes did not extend the chronology. However, it yielded samples that were over 800 years old, indicating that lakes in the region could potentially harbor ancient samples to target for future research. The blue intensity record was strongly correlated with May-September minimum temperatures (r=0.63), while also proving to be highly effective at capturing extreme interannual temperature variations caused by volcanic eruptions. Findings from the blue intensity reconstruction confirm that the parameter can be used as a robust summer temperature proxy in the region.
Dynamic Modelling of Process Chemistry in Kraft Pulp Mills
Keywords: CADSIM Plus
Causticity
Dynamic Modelling
Grade Transition
Kraft Pulp Mills
Reduction Efficiency

Efficiency decline in the recovery cycle of Kraft pulp and paper mills can create dynamic conditions that lead to evaporator scaling and poor combustion properties at the recovery boiler. In extreme cases, these dynamic conditions can evolve into production disruptions and mill shutdowns. Currently, operational strategies are often evaluated with steady-state models without the capability to simulate dynamics, leading to misinformed operational decisions. Dynamic modelling offers the opportunity to provide accurate real-time information to operators to pre-emptively manage dynamic conditions before shutdowns are required. To this end, this research project developed a dynamic model of a Canadian softwood/hardwood pulp mill using CADSIM Plus with model calibration from a mill-wide sampling campaign. Time and impact estimates of common dynamic conditions were determined to inform and improve existing operational strategies. Further, linking the model to mill measurements would equip operators with real-time chemistry measurement leading to optimized process control.