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"Totally Invisible": The experiences of domestic violence and abuse victims/survivors and children engaging with private law family court processes in Northern Ireland
No full textSharing our Screen - Does the online delivery of Equity, Diversity and Inclusion training provide a blueprint for asynchronous professional development training in healthcare?
No full textAsynchronous professional development training continues to gain traction in the healthcare sector, and yet debate continues about how it can best be delivered, and policies written to support its adoption. To address a gap for universally-accessible Equity, Diversity and Inclusion (ED&I) training in Northern Ireland, Queen's University Belfast (QUB), Ulster University (UU) and the Northern Ireland Medical Training Agency (NIMDTA) co-developed an award-winning ED&I training course for healthcare staff with an educational supervisory role. Iterative evaluation allowed for policy recommendations to be developed to support healthcare educators to develop asynchronous e-learning resources
Deploying AI in uncertain environments: a technical limitation or a human characteristic?
No full textThe relationship between AI and uncertainty in high-stakes public environments has not yet been given the attention that it requires. While technical literature often frames uncertainty as a limitation that should be resolved or minimised, this project draws attention to an alternative interpretation: uncertainty as a fundamental and valuable component of human judgment, particularly within many aspects of public sector decision-making, and therefore minimising uncertainty to design more effective AI can become undesirable. My research investigates how AI systems designed for predictability, consistency, and optimization struggle to operate effectively in environments where discretion, ambiguity, and pluralism are not only unavoidable but often necessary. This project advances the conceptual understanding of uncertainty in AI ethics and governance while also offering early empirical insights through experiments with large language models in legal interpretive tasks. The overarching aim is to develop normative and technical guidance for building AI systems that align more meaningfully with the social and institutional functions of uncertainty. Additionally, I acknowledge the benefits of meaningfully minimising environmental uncertainties for AI systems and my future work aspires to produce a framework to help guide when adaptations to reduce uncertainty for public sector AI are permittable and when they should not be made to ensure the inherent humanness of society remains intact
The legal landscape for deep-sea mining in the Area: A primer for practitioners
No full textA general overview of the legal regime for managing deep-sea mineral resources of the seafloor in areas beyond national jurisdiction (‘the Area’) is presented with a focus on the protection of the marine environment. This primer aims to provide the background to and translate complex legal principles of international law relevant to activities related to deep-sea mining in the Area for those who do not have a background in legal studies. An introduction to international law, where it is relevant to deep-sea mining, is presented, as well as an overview of the United Nations Convention on the Law of the Sea, including its historical development. The role of the International Seabed Authority (ISA) in managing and regulating mineral-related activities in the Area is expounded, and a brief overview of the state-of-play regarding developments of the ISA Mining Code is represented, including calls for a moratorium on deep-sea mining by several ISA member states. Lastly, the role of other international legal frameworks pertaining to the Area and the protection of its environment is addressed. Overlaps in competencies between international and regional organisations are identified where they might lead to conflicts, providing as example a Marine Protected Area, designated by the Convention for the Protection of the Marine Environment of the North-East Atlantic, that partly intersects with the Area
An investigation of visual foundation models robustness
No full textVisual Foundation Models (VFMs) are becoming ubiquitous in computer vision, powering systems for diverse tasks such as object detection, image classification, segmentation, pose estimation, and motion tracking. VFMs are capitalizing on seminal innovations in deep learning models, such as LeNet-5, AlexNet, ResNet, VGGNet, InceptionNet, DenseNet, YOLO, and ViT, to deliver superior performance across a range of critical computer vision applications. These include security-sensitive domains like biometric verification, autonomous vehicle perception, and medical image analysis, where robustness is essential to fostering trust between technology and the end-users. This article investigates network robustness requirements crucial in computer vision systems to adapt effectively to dynamic environments influenced by factors such as lighting, weather conditions, and sensor characteristics. We examine the prevalent empirical defenses and robust training employed to enhance vision network robustness against real-world challenges such as distributional shifts, noisy and spatially distorted inputs, and adversarial attacks. Subsequently, we provide a comprehensive analysis of the challenges associated with these defense mechanisms, including network properties and components to guide ablation studies and benchmarking metrics to evaluate network robustness
Preclinical screening platform identifies azatadine-dimaleate as a potent repurposed therapeutic against SARS-CoV-2 infection
No full textThe emergence of SARS-CoV-2 posed a major global public health threat, necessitating urgent development of therapeutics. Despite vaccine availability, continuous emergence of viral variants with enhanced transmissibility and immune escape capabilities, and consequential impacts on health services, requires effective antiviral therapeutics. Drug repurposing offers an expeditious strategy to identify therapeutics with established safety profiles. We implemented a comprehensive three-tiered validation approach, screening 2,570 compounds against SARS-CoV-2 in vitro, followed by ex vivo validation in well-differentiated primary human bronchial epithelial cell (WD-PBEC) cultures, and rigorous in vivo assessment. This methodical progression identified Azatadine-Dimaleate, a H1-receptor antagonist, as an exceptional candidate with consistent efficacy across all systems. Azatadine-Dimaleate demonstrated potent antiviral activity- EC50: 4.0 µM (95% CI: 3.2–4.8 µM), reducing viral replication by ~5,000-fold at 25 µM in epithelial cultures and lowering peak viral titers in WD-PBECs by 1.4 log10, and 2.33 log10 at 48 and 96 hpi, respectively, compared to controls. There was also a concomitant reduction in expression of interferons and pro-inflammatory genes, including IL-6. Combination with Remdesivir synergistically enhanced antiviral activity, reducing the EC50 of both drugs by > 60%. In the K18-hACE2 transgenic mouse model, Azatadine-Dimaleate significantly reduced weight loss (4% vs. 12%, p ≤ 0.05), decreased viral loads, and halved viral antigen expression in lung tissues. Unlike many candidates that faltered in complex models, Azatadine-Dimaleate maintained efficacy across all platforms. These findings support its clinical evaluation, alone or in combination with Remdesivir, as a versatile therapeutic with strong potential to address current and emerging SARS-CoV-2 variants.<br/
Nrf2–Keap1 pathway and NLRP3 inflammasome in Parkinson’s disease: mechanistic crosstalk and therapeutic implications
No full textNeurodegenerative disorders such as Parkinson’s disease (PD) are characterized by the progressive degeneration of dopaminergic neurons, which is driven primarily by oxidative stress and chronic neuroinflammation. Central to the cellular antioxidant defense system is the nuclear factor erythroid 2–related factor 2 (Nrf2)–Kelch-like ECH-associated protein 1 (Keap1) pathway, which mitigates oxidative damage and preserves mitochondrial integrity. Concurrently, the NOD-like receptor pyrin domain-containing protein 3 (NLRP3) inflammasome acts as a key mediator of innate immune responses and has been increasingly implicated in neuroinflammatory cascades leading to neuronal loss in PD. Emerging evidence indicates a mechanistic interplay between the Nrf2–Keap1 axis and the NLRP3 inflammasome, wherein Nrf2 activation not only counteracts oxidative stress but also suppresses NLRP3-mediated inflammatory signaling. A comprehensive overview of the molecular crosstalk between the Nrf2 and NLRP3 pathways in the pathogenesis of PD, with emphasis on how impaired Nrf2 signaling exacerbates NLRP3 inflammasome activation, is provided. The preclinical and clinical findings on pharmacological agents that activate Nrf2 or inhibit NLRP3 as potential neuroprotective strategies in PD are also discussed. A growing body of evidence underscores the dual therapeutic benefit of targeting oxidative stress and inflammation via Nrf2 inducers and NLRP3 inhibitors. Nonetheless, obstacles such as restricted blood–brain barrier permeability, unintended effects, and variable clinical trial outcomes hinder the application of these findings in clinical settings. The advancement of disease-modifying therapies for PD hinges on continuous research aimed at deepening the mechanistic understanding of the Nrf2–NLRP3 axis and refining pharmacological strategies.<br/
