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Recent Submissions

Access status: Embargo ,
ASSESSING THE ROLE OF BAF SUBUNIT VARIANTS IMPLICATED IN NEURODEVELOPMENTAL DISORDERS USING DROSOPHILA-BASED FUNCTIONAL ASSAYS
(2025-12-18) Edison, Abigail C.; Not Applicable; Master of Science; Department of Biochemistry & Molecular Biology; Not Applicable; n/a; Not Applicable; Dr. Aarnoud van der Spoel; Dr. Johane Robitaille; Dr. Francesca Di Cara; Dr. Jamie M. Kramer
Neurodevelopmental disorders (NDDs) are frequently caused by variants in genes associated with chromatin regulation, interfering with transcriptional programs that support normal neurodevelopment. These genes include subunits of the Brahma-associated factor (BAF) chromatin-remodelling complex. Functional assays in the model organism Drosophila can inform whether an NDD-associated variant alters the function of the encoded protein. Here, I employed a Drosophila assay to assess variants in the BAF subunit SMARCD1. Knockout of Bap60, the fly orthologue of SMARCD1, is lethal. The expression of human SMARCD1 rescues lethality, forming the basis for a ‘humanised rescue’ assay. I screened 22 SMARCD1 variants of uncertain significance and found a deleterious effect in seven, providing functional evidence that reclassifies the variants to likely pathogenic. Additionally, I developed alternative assays for the BAF subunits ACTL6A/B and SMARCA2/4. Overall, this work provides novel insight on the functional impact of NDD-associated BAF subunit variants, assisting in their clinical classification.
Access status: Embargo ,
INVESTIGATING THE INFLUENCE OF MICROWAVE-ASSISTED PYROLYSIS PARAMETERS ON ADSORPTION CHARACTERISTICS OF BIOCHAR
(2025-12-22) Gohel, Kamleshkumar; Not Applicable; Master of Applied Science; Department of Process Engineering and Applied Science; Not Applicable; NA; Not Applicable; Ghada Koleilat; Mohammad Saeedi; Khaled Benis
Growing attention to environmental sustainability and circular economy practices has promoted the valorization of agricultural and industrial by-products for resource-efficient waste management. This research converts Brewer’s Spent Grain (BSG), a lignocellulosic biomass waste constituting nearly 85% of brewing industry waste, into functional biochar (BC) as an adsorbent for dye removal from water. Microwave-Assisted Pyrolysis (MAP) was used to prepare BSG-BC, and microwave power, irradiation time, and H3PO4 concentration were optimized using Box-Behnken Design (BBD) and Response Surface Methodology (RSM). Characterization (FTIR, SEM, BET, CHNS, TGA) confirmed improved porosity, surface area, and functional groups; the optimized biochar showed thermal stability and BET surface area ~502.9 m2/g. Adsorption experiments with Crystal Violet (CV) and Orange-II (Or-II) showed PSO kinetics (R2>0.99) and Freundlich/Redlich-Peterson isotherms (R2=0.96–0.99), with capacities of 53.28 mg/g (CV) and 46.97 mg/g (Or-II). Fixed-bed columns agreed with batch results, supporting BSG-BC for batch and continuous wastewater treatment.
Access status: Open Access ,
VTSECURE: EARLY WARNING RANSOMWARE DETECTION AND REPORTING SYSTEM VIA VIRUSTOTAL FOR NON-EXPERT USERS
(2026-01-06) Ibekwe, TOBECHUKWU; No; Master of Computer Science; Faculty of Computer Science; Not Applicable; n/a; Not Applicable; Dr. Saurabh Dey; Dr. Malcolm Heywood; Dr. Nur Zincir-Heywood; Dr. Marwa Elsayed
Ransomware is a continuously growing cybersecurity risk to governments and organizations in critical sectors such as power grids, health care, and the banking/finance industry where data privacy and system availability are essential for daily operations. Unlike other commonly known cybersecurity threats, ransomware attacks will not only disrupt operations but also threaten data confidentiality and integrity. To combat ransomware and its harmful effects, early detection systems can be developed and used by organizations and everyday users to identify potential threats before they escalate, hence minimizing the likelihood of successful attacks. This thesis proposes an early warning detection tool that leverages and examines files and URLs for potential threats. This research aims to create a tool for non-expert users, alerting them to harmful websites using VirusTotal’s API. By notifying users before they access malicious websites or download infected files, this tool can help prevent attacks from being triggered in the first place.
Access status: Open Access ,
ADVANCES IN WELD DESIGN FOR HOLLOW STRUCTURAL SECTION CONNECTIONS
(2025-12-22) Newcomb, Benjamin; Not Applicable; Doctor of Philosophy; Department of Civil and Resource Engineering; Not Applicable; Scott Walbridge; Not Applicable; Andrew Corkum; Yi Liu; Kyle Tousignant
A research program involving experimental and finite element (FE) analyses was conducted to investigate effective geometric properties for the design of welds in hollow structural section (HSS) connections as “fit-for-purpose”. The reliability of weld effective length, le, formulae for welds in rectangular hollow section (RHS) and circular hollow section (CHS) connections was examined, and new design formulae for fillet and partial joint penetration (PJP)-groove welds were recommended. Experimental data from tests on RHS gapped-K, overlapped-K, T-, Y-, and X-connections under branch axial load(s) were analysed to assess the reliability of fit-for-purpose weld design in accordance with the European design code, prEN 1993-1-8:2021. Existing le formulae were evaluated in conjunction with the Directional and Simplified Methods of prEN 1993-1-8:2021, and minimum fillet weld throat thicknesses, tw, required to develop the capacity of a connected RHS branch were recommended. An experimental program was then conducted on PJP-groove welds in six transverse plate-to-CHS X-connections to verify new le formulae. Reliability analyses were conducted and design recommendations for fit-for-purpose welds in plate-to-CHS X-connections were provided in accordance with North American design codes (AISC 360-22 and CSA W59:24). An assessment of micromechanics-based ductile fracture criteria was conducted to verify an approach to predict the fracture load of welds in HSS connections simulated in FE software. Stress-strain (σ-ε) curves of weld and base metals were modelled using tensile coupon (TC) data, a post-ultimate material approximation was validated, and eight fracture criteria were calibrated using experiment results. Twelve large-scale experiments and 158 FE simulations were conducted to investigate the reliability of le formulae in CSA W59:24 for fit-for-purpose PJP-groove welds in CHS X-connections with large branch-to-chord diameter, d1/d0 (= β), -ratios. The results were supplemented with previous FE data to verify the reliability of proposed le formulae. The influence of chord “end effects” was also studied, and design formulae were recommended for welds in connections with 0.10 ≤ β ≤ 1.00.
Access status: Open Access ,
LEVERAGING AUGMENTED REALITY AND MACHINE LEARNING TO SUGGEST DIAGNOSES FOR COMMON SKIN DISEASES IN BLACK AFRICANS
(2025-12-24) Olaiya, Olamiposi; No; Master of Computer Science; Faculty of Computer Science; Received; n/a; Yes; Oladapo Oyebode; Mayra Barrera Machuca; RIta Orji
Skin diseases are widespread health conditions that affect people of all skin tones but are often underdiagnosed or misdiagnosed in individuals with darker skin due to limited representation in dermatological research and diagnostic datasets. This thesis presents SkinVista, an mHealth application that integrates Augmented Reality (AR) and Machine Learning (ML) to enhance skin health awareness and support the suggestive diagnosis of common skin conditions among Black African populations. A distinctive strength of this research is the direct collaboration with Black dermatologists, whose clinical expertise informed every stage of SkinVista’s design, model development, and evaluation. This collaboration ensured that the system is contextually appropriate and specifically aligned with the diagnostic nuances of darker skin tones. SkinVista leverages AR-based camera guidance to help users capture high-quality skin images, while an ML model trained on dermatological images representing darker skin tones provides instant diagnostic suggestions for conditions such as acne, eczema, ringworm, and keloids. SkinVista was evaluated in two phases: (1) a pilot study involving six participants, and (2) a main study with seventy-one participants. The pilot study identified considerations and refinements to the study procedures and the application itself. Feedback showed high usability, with a mean SUS score of 85.0, and strong technology acceptance, with participants reporting high perceived usefulness (M = 4.33) and informativeness (M = 4.42) and also confirmed that the AR-guided capture workflow was intuitive and that it was feasible to conduct the study with a larger sample. Building on these refinements, the main study implemented the improved procedures with a larger sample, where participants interacted with the app, completed AR-guided image capture, received ML-based diagnostic suggestions, and evaluated the system using validated scales across usefulness, informativeness, usability, engagement, simplicity, and technology acceptance. Quantitative results showed high perceived usefulness and informativeness, with good usability ratings and positive behavioural intentions toward adoption. Qualitative feedback indicated that participants valued the app’s visual appeal, intuitive navigation, and educational content, while suggesting greater personalization and offline functionality. The findings demonstrate the potential of SkinVista to address diagnostic disparities through intelligent automation. This thesis contributes to Human-Computer Interaction (HCI) and digital health research by providing design insights for creating equitable, AI-driven healthcare tools that empower underrepresented populations and promote accessibility in dermatological care.
Access status: Open Access ,
REVIEW OF THE IMPACT OF ARTIFICIAL INTELLIGENCE ON PROJECT MANAGEMENT PRACTICES: INSIGHTS FROM INDUSTRY EXPERTS IN GHANA
(2026-01-05) Otoo, Daniel; Not Applicable; Master of Science; Business; Not Applicable; NA; Not Applicable; Joyline Makani, PhD; Paola Gonzalez, PhD; Kyung Young Lee, PhD
Advancements in artificial intelligence (AI) are reshaping organizational operations and strategic decision-making, with significant implications for project management (PM). As a core organizational function, PM plays a pivotal role in achieving corporate objectives through the successful execution of projects. The integration of AI into PM processes offers opportunities to enhance efficiency, optimize resource allocation, and improve decision-making. Despite growing scholarly interest, existing literature lacks a comprehensive framework that holistically examines AI’s influence across PM knowledge areas, process groups, and performance domains. Furthermore, methodological limitations persist, as prior studies predominantly employ singular approaches such as systematic literature reviews (SLRs) or quantitative surveys, while qualitative insights remain underexplored. Addressing these gaps, this study adopts a mixed-methods approach, combining an SLR with key informant interviews (KIIs) of industry professionals in Ghana—a region underrepresented in current research yet notable for its advancements in ICT adoption. Guided by the Task-Technology Fit (TTF) model and the Technology-Organization-Environment (TOE) framework, the SLR synthesizes findings from six reputable databases on the impact of AI on the project management body of knowledge (PMBOK) Guide, while KIIs provide contextual insights into practical challenges and opportunities. The research seeks to answer two primary questions: (1) How do AI-driven tools and techniques influence PM practices, including principles, process groups, and performance measures? (2) What challenges arise in implementing AI within PM in Ghana, Africa? Findings are expected to contribute theoretical and practical perspectives, offering actionable recommendations for organizations and future research directions (with four propositions). This study underscores AI’s transformative potential in PM and highlights the need for integrative frameworks to guide its effective adoption.