Faculty of Graduate Studies Online Theses

Permanent URI for this collectionhttps://hdl.handle.net/10222/11163

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Data Exhaust in Voice Assistants: Analysis and Mitigation Approaches
(2025-08-11) Mousavi Diva, Mahsa; Not Applicable; Master of Computer Science; Faculty of Computer Science; Not Applicable; none; Not Applicable; Dr. Nur Zincir-Heywood; Dr. Darshana Upadhyay; Dr. Srini Sampalli
Voice assistants(VAs) such as Siri, Google Assistant, Cortana, and Alexa are increasingly integrated into smartphones, smart home devices, and Internet of Things (IoT) platforms. While offering convenience, these technologies generate significant data exhaust, consisting of background data captured during both active use and passive listening. This passive data generation often occurs without users’ awareness, raising critical privacy, data governance, and security concerns. Despite their ubiquity, a systematic understanding of how, when, and to what extent voice assistants transmit data in real-world settings remains limited. The objective of this thesis is to examine voice assistant privacy policies and network traffic, develop a mobile application to notify users of security risks, and propose mitigation methods. Firstly, we conducted a systematic survey of the privacy policies of four major VAs, focusing on data collection, retention, third-party sharing, transparency, and exploring mitigation methods to limit unnecessary data collection. Based on these findings, Google Assistant was selected for detailed analysis due to its deep integration with Google services and extensive data collection. We subsequently developed an Android application to analyze PCAP files and classify network traffic generated by voice assistants, particularly in background or passive modes. The application identifies active background services, extracts Domain Name System (DNS) queries, and detects unexpected third-party communications. A built-in risk assessment system categorizes background activity into high, medium, or low risk, providing users with clear, contextual explanations. We further performed technical traffic analysis using tools such as Wireshark, evaluating encryption patterns and traffic bursts to better understand behavioral signatures. Our findings confirm that voice assistants can transmit user-related data even without explicit interaction, often to external analytics and ad services. This thesis presents a hybrid framework to uncover hidden data behaviors in voice assistants and proposes mitigation strategies to reduce passive data leakage, enabling more privacy-aware and transparent smart environments.
Embargo
INVESTIGATING THE EFFECTS OF ORTHOPHOSPHATE, SODIUM SILICATE, FREE CHLORINE, AND NITRATE ON THE CORROSION OF TIN-LEAD SOLDER IN PREMISES PLUMBING
(2025-08-11) Lewis, Naomi; Not Applicable; Master of Applied Science; Department of Civil and Resource Engineering; Not Applicable; n/a; Not Applicable; Dr. Margaret Walsh; Dr. Mita Dasog; Dr. Graham Gagnon
Lead is released into drinking water sources from lead-containing materials in plumbing. Even with the implementation of lead service line replacements, residents may still be at risk of lead exposure from old premises plumbing, including lead solder. Lead solder creates a galvanic corrosion scenario and is more affected by changes in source water quality, including nitrate contamination and chemical agents. This long-term study evaluates the effects of various water quality conditions on tin-lead solder corrosion by (1) investigating the effects of orthophosphate, sodium silicate, and free chlorine, and (2) assessing the impacts of nitrate levels and interactions with orthophosphate and free chlorine on lead solder. These experiments utilized simulated copper pipe joints, galvanically connected to 50:50 tin-lead solder, using a dump-and-fill design. The first experiment was conducted over 85 weeks with 207 water changes, and the second experiment for 46 weeks with 123 water changes. The results of this research demonstrated that free chlorine lowered total lead (according to rigorous statistical analysis), which coincided with robust scale formation by scanning electron microscopy. Silicate dramatically increased dissolved and total lead corrosion, and the interaction with orthophosphate and silicate increased total lead. Orthophosphate had no effect on total lead corrosion, yet decreased dissolved lead, indicating that lead phosphates formed but did not always remain as scale. This was confirmed by low phosphate detected by energy dispersive X-ray spectroscopy (EDS) mapping, pitting regions and regions depleted of lead. Silicate and orthophosphate were ineffective on their own, yet with chlorine addition, the combinations had lower median total lead levels. Lastly, this study found that nitrate at 12.5 and 25 mg L-1 (nitrate as nitrogen) induced high conductivity, galvanic current, and corrosion of tin and lead. A statistically significant increase was found in lead release with the addition of orthophosphate at high nitrate levels, indicating it did not aid in protection, but rather worsened lead release.
Open Access
Interplay Between Metabolic Alterations, Bipolar Disorders, and White Matter Microstructure
(2025-08-08) Dietze, Lorielle; Not Applicable; Doctor of Philosophy; Department of Medical Neuroscience; Received; Dr. Sophia Frangou; Yes; Dr. Rudolf Uher; Dr. Matthias Schmidt; Dr. Tomas Hajek
The goal of this dissertation was to describe where and to what extent obesity affects brain white matter in the general population and bipolar disorders. We used magnetic resonance imaging derived diffusion tensor imaging to investigate white matter microstructural alterations in the brain. We conducted voxel-based and region of interest meta-analyses, collaborated with the ENIGMA Bipolar Disorder Working Group to perform mega-analyses in large international samples of over 2000 participants, and explored deeper phenotyping through the Halifax Study. Our results show localized obesity associated white matter abnormalities in the general population. We found obesity, obesity related biomarkers, and psychiatric obesogenic medications added to the white matter alterations in bipolar disorder. Overall, this work has deepened our understanding of how obesity impacts the brain. We hope these insights draw attention to the hidden costs of obesity and provide new treatment options for prevention of negative brain, cognitive, and clinical outcomes.
Open Access
AN INVESTIGATION INTO THE IDENTITES OF WOMEN LIVING WITH AND BEYOND CANCER, AND HOW THEIR IDENTITIES SHAPE EXERCISE EXPERIENCES
(2025-07-30) Hils, Jessica; Not Applicable; Master of Science; School of Health & Human Performance; Received; Dr. Sherry Huybers; Not Applicable; Dr. Lori Dithurbide; Dr. Chris Blanchard; Dr. Melanie Keats
The identities of women living with and beyond cancer (LWBC) and how these identities influence their exercise experiences have not been studied. This qualitative study used semi-structured interviews to investigate the identities of women LWBC and if and how these identities influence their exercise experiences while living within a Western sociocultural landscape. 16 participants were interviewed. Five main themes emerged from analysis of participant interviews, reflecting the research questions that anchored this investigation: 1) What identities emerge as salient among women LWBC? 2) How do women’s co-existing identities influence and interplay with one another? 3) Do the identities of women LWBC influence exercise experiences, and if so, how? 4) Does the interplay of co-existing identities of women LWBC influence exercise experiences, and if so, how? 5) Do women LWBC identify societal gendered expectations in their daily lives, and if so, how do these gendered expectations influence their personal identities and exercise experiences? The results from this study suggest that not only do singular identities of women LWBC often influence their exercise experiences, but so do co-existing identities.
Open Access
Design and Implementation of a 10-bit 50-MS/s Radiation Tolerant Split Coarse/Fine SAR ADC in 65-nm CMOS
(2025-08-11) Yan, Ming; Not Applicable; Doctor of Philosophy; Department of Electrical & Computer Engineering; Not Applicable; Dr. Lihong Zhang; Yes; Dr. Jason Gu; Dr. Michael Freund; Dr. Kamal El-Sankary
Integrated circuits in aerospace applications face significant reliability challenges due to exposure to harsh radiation environments, which can induce Single Event Effects (SEEs) and Total Ionizing Dose (TID) degradation. This thesis presents the design, implementation, and validation of a 10-bit, 50 MS/s Radiation-Hardened by Design (RHBD) Successive Approximation Register (SAR) Analog-to-Digital Converter (ADC) tailored for irradiation conditions. Fabricated in a standard TSMC 65-nm CMOS process, the ADC leverages multiple redundancy strategies at both system and circuit levels to mitigate radiation-induced errors and metastability. At the system level, a novel split Coarse/Fine asynchronous SAR ADC architecture is proposed, which functions as a sub-ranging system under normal conditions and provides robust system-level redundancy. This architecture is designed to detect and discard erroneous conversion bits resulting from SEEs, thereby maintaining data integrity. Circuit-level SEE error detection is achieved through a co-designed scheme incorporating Last Bit Cycle (LBC) detection, which monitors voltage jumps in the DAC, and Metastability Detection (MD) using a ramp generator and threshold trigger. These mechanisms enable the identification and correction of radiation-induced errors and metastability issues via a Coarse/Fine redundant algorithm. Sub-radix-2 DACs are employed in both coarse and fine stages to introduce inherent redundancy for error correction. The prototype RHBD SAR ADC core occupies an area of 0.0875 mm² and consumes 2.79 mW from a 1.2-V supply at 50 MS/s, achieving up to 8.78 Effective Number of Bits (ENOB). Post-irradiation tests confirm functionality up to 100 krad(Si) TID and demonstrate over 90% suppression of large SEEs (>5 LSB) under laser testing, validating the effectiveness of the combined RHBD strategies. This research extends beyond the primary ADC to investigate critical analog components. A Single Event Transient (SET), a temporary voltage pulse caused by a particle strike, poses a significant threat to circuit reliability. To combat this, this work presents a holistic radiation-hardening methodology across multiple design levels. At the system level, a novel split coarse/fine architecture provides efficient redundancy with low overhead. At the circuit level, this work incorporates a radiation-hardened Quatro-Latch comparator and Dual-Interlocked Cell (DICE) logic to mitigate SETs at their source. A comprehensive study on SETs in switched-capacitor amplifiers further led to the proposal of a novel Parallel-Auxiliary Ring Amplifier (PA-RAMP) hardening solution. In summary, this thesis offers a multi-faceted approach to the design and implementation of robust, power-efficient, radiation-hardened mixed-signal circuits, providing validated solutions for critical data acquisition systems in radiation-prone aerospace environments.
Open Access
DEVELOPING AND EVALUATING A BRIEF SEXUAL VIOLENCE INTERVENTION TO SHIFT ATTITUDES, BELIEFS, AND BEHAVIOURS IN EMERGING ADULT MEN
(2025-08-11) Goruk, Kayla Joy; Not Applicable; Master of Science; Department of Psychology and Neuroscience; Received; n/a; Not Applicable; Natalie Rosen; Sandra Meier; Julie Blais
Sexualized violence has severe, far-reaching impacts on mental and physical health worldwide. Prevention efforts that focus on early education for at-risk groups, such as young men, are therefore being increasingly prioritized. The current thesis developed and evaluated a brief Sexual Violence Intervention aimed at improving attitudes, beliefs, and behaviours related to sexual violence and consent in emerging men (ages 18 to 35) in Canada and the UK. A pilot study was first conducted to inform intervention content and self-report measures for the main study. Participants (N = 498) in the main study were randomly assigned to complete either a brief Sexual Violence Intervention or a comparable Plagiarism Control Intervention in Survey 1 before completing a follow-up survey six to eight weeks later. Results indicated that, compared to the Plagiarism Control group, participants in the Sexual Violence Intervention group reported more prosocial attitudes towards subtle coercion, had improved scores on several knowledge quiz outcomes (e.g., understanding of consent and power dynamics), and were better able to recognize non-consensual scenarios at follow-up compared to the Control group. However, the Sexual Violence Intervention did not impact perceptions of ongoing consent, communicative sexuality, some knowledge quiz outcomes (e.g., consent and intoxication), and most perpetration behaviours. A significantly steeper decline in self-report sexual assault was observed in the intervention group at Survey 2, however, group differences in perpetration were not significant. Implications for evidence-based prevention programming and future research are discussed.
Embargo
Development and assessment of encapsulated fermented wild blueberries as a novel functional food ingredient
(2025-08-06) Kilittuwa Gamage, Dinushi Kaushalya; Yes; Master of Science; Department of Plant, Food and Environmental Sciences; Received; n/a; Yes; Dr. Xiaohong Sun; Dr. Petra Kienesberger; Dr. H.P. Vasantha Rupasinghe
This study investigated microencapsulated fermented wild blueberries as a natural alternative to pharmaceutical treatments for metabolic syndrome, which often demonstrate limited efficacy and adverse effects. Fermentation of wild blueberries using Saccharomyces cerevisiae and Komagataeibacter spp. generated health-promoting postbiotics, including short-chain fatty acids. Microencapsulation of the fermented product using a maltodextrin/inulin (1:1 w/w) carrier yielded microcapsules with low moisture content, low hygroscopicity, smaller particle size, satisfactory encapsulation efficiency, and robust stability under varying storage conditions. In a mouse model of diet-induced metabolic syndrome, supplementation with these microparticles significantly reduced weight gain, food intake, plasma and liver lipids, and body fat, alongside improved levels of biomarkers associated with hepatic lipid metabolism. However, glycemic control and insulin sensitivity remained unaffected. These findings suggest that the formulation is a promising natural strategy for managing lipid-related metabolic dysfunction and could serve as an adjunct or alternative to conventional therapies.
Open Access
Dairy DigiD – AI-Driven Facial and Video-Based Recognition for Monitoring Physiological and Reproductive States in Dairy Cattle
(2025-08-07) Mahato, Shubhangi; No; Master of Computer Science; Faculty of Computer Science; Received; na; Yes; Dr. Miriam Gordon; Dr. Oladapo Oyebode; Dr. Suresh Neethirajan
Precision livestock farming increasingly depends on non-invasive, high-fidelity systems capable of monitoring cattle with minimal disruption to behavior or welfare. Conventional identification methods, including ear tags and wearable sensors, often compromise animal comfort and generate inconsistent data under real-world farm conditions. This study introduces Dairy DigiD, a deep learning-based biometric classification framework that categorizes dairy cattle into four physiologically and age-defined groups—young, top-yielding, late gestation, and non-lactating cows. It described a new classification method based on full-body classification using DenseNet121, the use of facial landmark detection from Detectron2, and the real-time detection capabilities of YOLOv11. Dairy DigiD is a multi-model pipeline that is flexible and can operate from either static images or video data. It started with assembling a dataset of more than 8,700 annotated images from commercial dairy farms in Nova Scotia and New Brunswick. DenseNet121 was trained for a baseline for full-image classification, but background variation and occlusion led to considerations of using keypoint-based facial recognition with Detectron2 to improve identification by having model stability on a 30-keypoint landmarks (e.g., eyes, nostrils, and muzzle), resulting in less sensitivity to posture, lighting, and weight variation. For video-based detection, the novelty of using YOLOv11 (latest architecture) for multi-class physiological cattle classification. Roboflow-annotated data and deployed through Gradio on Hugging Face. Built as an interactive interface for real-time streaming, detection overlays, and roles for farm users, YOLO was developed as a useful system. The analysis showed that DenseNet121 had great baseline accuracy (97%); however, in contrast, Detectron2 demonstrated superior adaptability in uncontrolled farm environments, attaining classification accuracies between 93% and 98% on test datasets, and YOLOv11 provided the best performance as a real-time capable method (20 FPS and a maximum latency of 230 ms). The thesis also assesses model explainability on the basis of Grad-CAM, cross-validation accuracy and the impact of dataset imbalance. Ethical considerations, limitations, and future integration possibilities with multimodal systems—such as gait analysis and 3D biometrics—are also acknowledged. Overall, Dairy DigiD represents a critical innovation in precision livestock monitoring and data-based welfare, traceability, and farm automation with minimal animal distress.
Open Access
Investigating the Relationship Between Scientific Capital and Journal Fit
(2025-08-08) Marjoram, Rebecca; Not Applicable; Master of Information; Faculty of Management; Not Applicable; n/a; Not Applicable; Stacy Allison-Cassin; Sandra Toze; Philippe Mongeon
Authorship of journal articles provides an opportunity for scientists to share discoveries and build scientific capital. Previous research has shown disparities in publication based on personal attributes and citation inequality, but the additional hurdle of researchers with less scientific capital adapting their work to match journal scope is less explored. This thesis investigates the relationship between the past performance of researchers (publication output, and number of citations) and scientific domain with the fit of their articles in the publishing journal. 224 journals were selected and publications between 2019-2023 were analyzed to determine journal scope and publication fit using cosine similarity scores. A linear regression analysis showed a statistically significant inverse relationship between the number of publications of authors, publishing in arts & humanities, and publication fit (r2 = 0.519, p < 0.005). Further research is needed to determine what additional factors may influence publication fit and journal scope.
Open Access
LATENT STRUCTURE IDENTIFICATION AND PERSONALIZED VARIABLE SELECTION
(2025-08-10) Zhang, Xinyue; No; Doctor of Philosophy; Department of Mathematics & Statistics - Statistics Division; Not Applicable; Dr. Linglong Kong; No; Dr. Bruce Smith; Dr. Andrew Irwin; Dr. Hong Gu; Dr. Toby Kenney
The identification of latent structures and the selection of personalized variables are critical to enhance the interpretability of models, predictive performance, and decision-making efficiency in complex data environments. There are three parts in this thesis. In the first part, we focus on the development of a method for identifying the latent spatial patterns for a response variable in spatial data. We propose a new method that calculates the similarity scores between different locations with a supervised random forest model to effectively capture spatial dependencies of a response variable. The similarity score is derived from the proportion of trees in which two locations fall in the same terminal node for the same values of other predictors. This resulting similarity matrix is then used to derive eigen-scores and spatial clusters, which significantly improve the performance of models such as XGBoost, GWR, and random forest in both simulations and real datasets. In the second part, we develop an effective neural network pruning method based on backwards LASSO selection that can simultaneously select features and structure. We show that the LASSO shrinkage problem in neural networks can be re-written as a standard weighted regression or classification problem with LASSO penalty. Our proposed method starts from a dense neural network which contains all structures without feedback, and prunes links to select the optimal sparse neural network structure. The results of this structure selection highlight the inadequacy of commonly-used feedforward structures. By examining the selected structure, we are able to gain insight into the linear or nonlinear properties of the estimated function, and thus better interpret the underlying function. Finally, personalized variable selection is a novel topic to address an important problem. In many real-world applications, some variables may be costly or difficult to obtain. For example, in healthcare, ordering excessive medical tests can lead to unnecessary expenses, long waiting times, and patient discomfort. In the personalized variable selection paradigm, we consider the problem of using a fitted model to make predictions for a new observation where we have not yet measured all these costly variables. We assess the predictive value of the potentially useful predictor variables for this new observation, in order to decide which predictors are worth measuring for this observation. We introduce a novel metric called the Expected Loss Improvement Estimate (ELIE), which quantifies the expected gain in predictive accuracy from measuring a missing variable. The core idea of our method is that large ELIE suggests greater variability in predictions, indicating that collecting the true values of the missing variables is highly valuable for those data points. This approach can help us determine when imputation is sufficient and when additional data collection is necessary to maximize model performance.
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Characterizing NOS1AP in the Rodent Cerebellum
(2025-08-06) Thomson, Emily; Fawcett, James; Not Applicable; Master of Science; Department of Pharmacology; Received; Dr. Stefan Krueger; Not Applicable; Dr. Corey Baimel; Dr. James Fawcett
Nitric Oxide Synthase 1 adaptor protein (NOS1AP) has been implicated in several diseases in the CNS. NOS1AP functions as an adaptor protein that can bind to several proteins, including neuronal nitric oxide synthase (nNOS). Mice lacking NOS1AP show significant defects in balance and gait, consistent with a role for NOS1AP in the cerebellum. Although NOS1AP mutant mice show no gross cerebellar defects, using isoform specific antibodies combined with different NOS1AP mutant mice reveals that NOS1APa is expressed in parvalbumin positive interneurons in the outer molecular layer, and is necessary to maintain nNOS localization in these neurons. Unlike NOS1APa, NOS1APc is expressed in Bergmann glia, and is necessary for climbing fiber distribution. Further, quantitative mass spectrometry analysis reveals that loss of NOS1AP influences the expression of proteins involved in GABAergic signaling, highlighting the importance of NOS1AP proteins in maintaining excitatory/inhibitory homeostasis within the cerebellum which is necessary for normal gait.
Open Access
THE ROLE OF HYDROGEN AS A DECARBONIZATION STRATEGY FOR SEA PORTS TO FACILITATE MARITIME TRANSPORT NET ZERO TARGETS OF 2050
(2025-08-08) Halpe, Pramithodha; Not Applicable; Master of Environmental Studies; School for Resource & Environmental Studies; Not Applicable; n/a; Yes; Dr. Michelle Adams; Dr. Michele Acciaro; Dr. Tony R. Walker
This thesis examines the role of hydrogen as a decarbonization strategy for ports in facilitating maritime transport 2050 net-zero targets. Chapter Two explores the challenges ports face in this transition, including economic, technological, and regulatory barriers, and identifies the opportunities ports can use to facilitate it. The next chapter narrows the focus to specifically assess the hydrogen readiness of the top 100 global ports, top 10 shipping lines, and 20 most connected ports, revealing regional disparities. Ports in Europe and North America lead with pilot projects and supportive policies, while other regions lag. Finally, chapter four evaluates the International Maritime Organization’s draft regulations on fuel standards and GHG pricing. The findings show these policies could accelerate hydrogen adoption by making it more financially viable and supporting developing economies to invest more on Hydrogen fuels. The thesis highlights ports’ critical role of energy transition to enable hydrogen-based maritime decarbonization.
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CAN PROBIOTIC SUPPLEMENTATION AND ACUTE MODERATE INTENSITY AEROBIC EXERCISE IMPROVE EXECUTIVE FUNCTION POSTSTRESS?
(2025-08-08) Munroe, Cory; Not Applicable; Doctor of Philosophy; Department of Psychology and Neuroscience; Received; Dr. Eli Puterman; Not Applicable; Dr. Sophie Jacques; Dr. Gail Eskes; Dr. Tara Perrot; Dr. Heather Neyedli
Executive function (EF) is an umbrella term for neuropsychological processes involved in the ability to maintain and manage goals. Given the wide range of day-to-day behaviours these processes help support, there is great interest in understanding whether and how EFs can be improved. As performance on EF tasks typically reaches its peak during young adulthood, an effective approach to improving EF among this population may be to help individuals maintain task performance at the upper end of their own abilities in contexts where EF is often compromised. One such context is acute psychosocial stress, which can transiently impair performance across various behavioural EF measures. Supplementation with probiotics and acute aerobic exercise have both displayed the potential to improve EF in multiple populations and can modulate the function of the hypothalamic-pituitary-adrenal axis—a neuroendocrine system crucial for the organism’s stress response. Therefore, the purpose of this thesis was to investigate the effect of one probiotic supplement (Lactobacillus helveticus R0052 and Bifidobacterium longum R0175; 3x109 CFU) and acute moderate-intensity aerobic exercise (20 minutes of stationary cycling at 70% peak power output) on a measure of EF (Switching Stroop task) when administered following an acute stress paradigm. In Chapter 2, although supplementation with Lactobacillus helveticus R0052 and Bifidobacterium longum R0175 did not improve Switching Stroop performance following the Maastricht Acute Stress Test in a young adult population, the probiotic group decreased response times on a Feature Search task relative to placebo. This effect remained significant after false discovery rate correction. In Chapter 3, young adults exposed to the Montreal Image Stress Task and acute aerobic exercise displayed greater improvements in Switching Stroop accuracy across the testing session compared to those exposed to the Montreal Image Stress Task or acute aerobic exercise alone. Taken together, probiotic supplementation and acute moderate-intensity aerobic exercise display the potential to improve cognitive task performance among young adults, although not in the hypothesized manner. Future research will be crucial to replicate observed effects and identify the mechanisms underlying them.
Open Access
DECODING POULTRY WELFARE: AN INTEGRATED MACHINE LEARNING AND NLP FRAMEWORK FOR VOCALIZATION ANALYSIS
(2025-08-06) Manikandan, Venkatraman; Not Applicable; Master of Computer Science; Faculty of Computer Science; Received; n/a; Yes; Dr. Bruce Rathgeber; Dr. Hassan Sajjad; Dr. Suresh Neethirajan
Poultry vocalizations serve as valuable, non-invasive indicators of health, stress, and overall welfare in farm environments. This thesis presents an integrated machine learning framework combining classical acoustic analysis and natural language processing (NLP) to decode these vocal cues. The first approach uses features like MFCCs, spectral contrast, and zero-crossing rates with models such as Random Forest, LSTM, and TabNet for classifying health, behavior, and stress. The second pipeline transcribes raw audio using Wav2Vec2.0 and applies BERT-based sentiment and linguistic analysis to detect welfare-related vocal shifts. Ensemble models showed strong generalization across welfare contexts, while NLP models uncovered subtle stress-induced vocal patterns. Scalable preprocessing with ThreadPoolExecutor enabled efficient handling of large datasets. These methods support the development of an on-farm, real-time monitoring system for early stress detection, reduced manual labor, and improved animal welfare—contributing to more ethical, sustainable, and productive poultry farming practices.
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IMPACT OF NAD+ SYNTHESIS ENZYMES ON MULTIPLE MYELOMA PATIENT OUTCOMES AND ONGOING INVESTIGATION OF MECHANISMS OF FAMILIAL CLUSTERING OF MULTIPLE MYELOMA IN NOVA SCOTIA
(2025-08-08) Crone, Lara; Not Applicable; Master of Science; Department of Pathology; Received; Dr. Wenda Greer; Not Applicable; Dr. Jeanette Boudreau; Dr. Mahboubeh Rahmani; Dr. Amy Trottier
Multiple myeloma (MM) is an incurable plasma cell neoplasm, which makes it ideal for novel therapeutic targets such as Nicotinamide Dinucleotide (NAD+). NAD+ is synthesized through one of three pathways: catalyzed by NAMPT, NAPRT, or IDO. We compared the expression of these rate-limiting enzymes in NAD+ synthesis against patient outcomes to investigate their feasibility as prognostic biomarkers in MM using OPAL multiplex immunohistochemistry. There was significant increase in NAMPT expression intensity in MM cases compared to control cases. NAPRT and NAMPT co-expressed in MM predicted worse patient survival compared to NAMPT expression alone. Increased NAPRT expression intensity correlated with shorter overall survival. Targeting these two pathways in concert could offer novel therapeutic opportunities for improving MM patient outcomes. We also include our preliminary work on the genetic and environmental causes of familial clustering of MM observed in Nova Scotia.
Open Access
Are there exercise volume and intensity differences between soccer athletes on the same team?
(2025-07-30) Armstrong, Brett; No; Master of Science; School of Health & Human Performance; Received; Dr. Christopher Maclean; Not Applicable; Dr. Lori Dithurbide; Dr. heather Neyedli; Dr. Scott Landry; Dr. Ryan Frayne
Collegiate student athletes must balance their academic responsibilities with rigorous game, practice, and strength training schedules making it difficult for coaches to monitor athlete’s weekly exercise volume and intensity. Therefore, the purpose of this research was to implement a global navigation satellite system (GNSS) to monitor athletes and examine the potential differences in exercise volume and intensity that may exist within a Canadian university soccer program. In year I significant differences between athlete categories were identified for measures of total cumulative distance (m), high-speed running distance (HSR-D: m), rate of high-speed running (R-HSR: m/min). In year II a successful training intervention, based on year I outcomes, increased TD (m), HSR-D (m), R-HSR (m/min) measures for supporter athletes which decreased the training differences between starters and low-minute athletes. This research project successfully implemented a GNSS and developed an intervention that reduced exercise volume and intensity differences between the athlete categories through structured tracking and training opportunities.
Open Access
Supporting and strengthening mental wellness in NunatuKavut
(2025-08-07) Stilwell, Christie; No; Doctor of Philosophy; Faculty of Health; Received; Dr. Cheryl Barnabe; Yes; Dr. Brad A. Meisner; Dr. Aimee Battcock; Dr. Elaine Moody; Dr. Debbie Martin; Dr. Lori Weeks
NunatuKavut Inuit have reported a lack of culturally relevant resources, services, and supports for mental health across their territory. "Understanding People, Place, and Culture: A NunatuKavut Inuit Mental Wellness Initiative” (NWI Project) is a community-based participatory research project led by NunatuKavut Community Council and academic researchers to address the community mental wellness needs of NunatuKavut Inuit in south and central Labrador. This dissertation consists of two separate but related studies that are situated within the NWI Project. The first study described how NunatuKavut Inuit envision community-led mental wellness programming and how community knowledge was used to inform the development of the NunatuKavut Mental Wellness Program Planning Tool. The second study explored narratives of mental wellness and social change among older NunatuKavut Inuit which revealed the impacts of local and global events and the importance of revitalising traditional ways of living and strengthening community connections.
Embargo
A Network-based Simulation Model for Helicopter Rescue Time Estimation in the Canadian Arctic
(2025-08-07) Mohammadi, Mahroo; Not Applicable; Master of Applied Science; Department of Industrial Engineering; Received; Dr. Robert Brown; Not Applicable; Dr. Scott Felmming; Dr. Floris Goerlandt; Dr. Ronald Pelot
Helicopter-based Search and Rescue (SAR) operations in Northern Canada are essential for assisting individuals in distress across both land and marine environments under extreme Arctic conditions. This thesis introduces a practical and adaptable approach to estimate total response time, encompassing the transit time (time to reach the incident location), the on-board time (time required to hoist individuals into the helicopter), and the rescue time (time to transport them to a safe destination). This estimation is supported by a set of integrated models that reflect key operational and environmental conditions. Among these, the HeliSAR Pathfinder (Helicopter Search and Rescue Path Finder) model plays a central role in identifying viable mission routes. The HeliSAR Pathfinder Model generates feasible helicopter rescue routes from operational bases to potential incident locations, accounting for range limitations, fuel capacity, and available refueling stations across the Arctic. These paths form the structural foundation for modeling time-dependent mission activities. Next, the Royal Canadian Armed Forces Helicopter Environmental Operability (RHEO) Model is applied to assess how environmental conditions affect helicopter performance, categorizing weather scenarios as ‘Favorable’, ‘Unfavorable’, or ‘No-Go’. These classifications influence which routes remain viable and how long missions may be delayed or extended due to adverse weather conditions. Building on the route and operability inputs resulting from the HeliSAR Pathfinder and RHEO models, the Helicopter SAR Simulation Model (HESARSI) uses a Discrete Event Simulation (DES) framework to simulate the full mission sequence (including e.g., helicopter takeoff, refueling, search, and rescue). To reflect operational uncertainty, Monte Carlo Simulation (MCS) introduces randomness into key variables such as weather conditions, takeoff readiness, and hoist time for Persons in Distress (PID), producing a distribution of potential transit and rescue durations under varying scenarios. This research also explores the potential benefits of establishing a new SAR helicopter base in Iqaluit, evaluating its impact on transit times across various communities in Northern Canada. The analysis includes an operational accessibility study to determine which incident locations can realistically be reached by helicopter, considering constraints such as flight range, refueling logistics, and environmental conditions. The study further examines how factors like incident distance, seasonal weather variability, refueling requirements, and the number of Persons in Distress (PID) affect the response times. Results reveal significant spatial and seasonal disparities across all response time components. For instance, rescue times in northernmost zones often exceed 27 hours during winter months, whereas southern regions may achieve rescue times of under 15 hours in summer. Overall, this work provides actionable insights for SAR planners and emergency management authorities, enabling more informed strategic decisions to improve safety, responsiveness, and resilience in Canada’s remote Arctic communities and coastal areas.
Embargo
Characterization of ALS Patient iPSC-Derived Motor Neurons
(2025-08-01) Reynolds, Paige; Not Applicable; Master of Science; Department of Medical Neuroscience; Received; Dr. Stefan Kruegar; Not Applicable; Dr. Adam Jonhston; Dr. Ying Zhang
Amyotrophic Lateral Sclerosis (ALS) is a rapidly progressing fatal neurodegenerative disease. It is characterized by motor neuron (MN) degeneration, which leads to the loss of voluntary movement control and premature mortality. Currently, there is no known cure for ALS. Human induced pluripotent stem cells (iPSC) derived from ALS patients have become a powerful tool to study disease mechanisms and identify therapeutic targets. Dr. Rafuse’s lab at Dalhousie University has established several iPSC lines sourced from both healthy individuals and ALS patients harboring the genetic mutations C9ORF72 or TARDBP. In addition, the introduction of Channelrhodopsin-2 (CHR2), a light-sensitive protein, into these cell lines enables the manipulation of cell activity via light stimulation. Using whole-cell patch-clamp, this study aims to systematically characterize MNs derived from these human iPSC lines. My findings revealed that iPSCMNs derived from ALS patients exhibited an aberrant developmental trajectory, characterized by increased maturation rates under harsher culture conditions, abnormal activity patterns, and an early decline in action potential output and synaptic activity compared to healthy controls. Furthermore, chronic optic activation had minor impacts on the healthy control group, but more significantly influenced the development and intrinsic properties of ALS iPSC motor neurons. This presents a potential avenue for modulating cellular behavior at varying developmental stages, thereby potentially extending ALS cell survival.
Open Access
The Role of Pain Sensitization and Muscle Function in Knee Osteoarthritis Mechanics
(2025-08-05) Hannigan, Meaghan; No; Master of Science; School of Physiotherapy (Rehabilitation Research); Received; Dr. Janie Astephen-Wilson; No; Dr. Derek Rutherford; Dr. William Stanish; Dr. Jason McDougall; Dr. Rebecca Moyer
Knee osteoarthritis (KOA) pain is frequently in discordance with structural severity, suggesting sensitization mechanisms. However, the relation of pain sensitization with functional demand and properties remains unexplored, neglecting age-related differences. This thesis investigated associations of pain sensitization with functional demand (muscle capacity utilization; MCU), and muscle stiffness (shear wave velocity; SWV) in individuals with KOA, exploring age-related differences. Thirty-one adults with unilateral KOA completed self-reported questionnaires, quantitative sensory testing, strength testing, gait analysis, and quadriceps ultrasound elastography. MCU was calculated during walking and stairs. Pain sensitization was bilateral despite unilateral KOA. MCU was higher in the contralateral limb across tasks. Sensitization and MCU were negatively associated. Quadriceps SWV was moderately associated with sensitization in the affected limb. Sensitization-MCU associations were stronger in younger participants during stairs, and in older adults during walking. Pain sensitization may contribute to age-related functional compensations in KOA, highlighting the need for interventions tailored to symptoms.