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An insight on the timely diagnosis of diabetic retinopathy using traditional and ai-driven approaches
No full textDiabetic Retinopathy is a progressive microvascular complication of diabetes that requires early detection to improve patient outcomes. Traditional screening techniques, including fundus photography and optical coherence tomography, provide valuable diagnostic insights but have some limitations, like cost and technical complexity. Artificial intelligence is transforming the detection of diabetic retinopathy, moving away from traditional machine learning models that rely on manually created features to deep learning methods that allow for automatic feature extraction from retinal images. This systematic review investigates the evolution and diagnostic performance of AI-based techniques for DR detection. Studies were included if they applied machine learning or deep learning methods to retinal fundus or OCT images for DR classification. A total of 116 studies were included following comprehensive searches in databases such as PubMed, ScienceDirect, and IEEE Xplore, covering publications up to February 2024. Risk of bias was assessed in a representative sample of six studies, indicating a significant overall risk due to inadequate reporting on blinding and selective outcome reporting. Federated learning emerged as a promising alternative, enabling decentralized collaboration without compromising data privacy. Additionally, the growing focus on Explainable AI helps address the "black-box" nature of deep learning models by providing visual and textual explanations for predictions, thereby enhancing clinician trust and facilitating informed decision-making. By incorporating artificial intelligence with standard diagnostic frameworks, this research highlights the possibility for more accurate, scalable, and reachable diabetic retinopathy detection, paving the way for considerable advancements in ophthalmic problem management and enhancing patient care.peer-reviewe
Non-specific electrostatic interactions and the conversion of horseshoe crab haemocyanin into a phenoloxidase
No full textHaemocyanin is a haemolymph (blood)-based protein and the functional equivalent to haemoglobin – supplying tissues with oxygen in decapod crustaceans, chelicerates, and shelled molluscs. In addition to oxygen transport, haemocyanin plays several roles in innate immunity, wound healing, and ecdysis. Under certain conditions in vitro and in vivo, horseshoe crab (Limulus polyphemus) haemocyanin is converted into a phenoloxidase-like enzyme, yet the protein-ligand interactions associated with this conversion remain unclear. Negatively charged ligands, such as phosphatidylserine and sodium dodecyl sulphate, represent effective endogenous and exogenous activators, respectively. Herein, we explored the nature of the interaction between haemocyanin and phosphatidylserine. We used several spectroscopic techniques and phenoloxidase assays to follow the electrostatic interactions. Manipulating the ionic strength of the assay resulted in less enzyme activity, and reversed haemocyanin conformational changes associated with phosphatidylserine binding (confirmed by fluorescence emission spectra). The addition of wild type and rearranged peptides – mimicking the P181 to K196 region close to the active site of haemocyanin subunit II – to phenoloxidase assays resulted in less product (dopachrome) formation. We propose that non-specific electrostatic interactions between haemocyanin and endogenous activators such as phosphatidylserine facilitate the switch to a phenoloxidase-like enzyme.Some of the initial experimental work was financed by the University of Stirling and supplemented by Swansea University.peer-reviewe
Preface to Booleying in Ireland. A study of an ancient farming tradition in Achill, County Mayo
No full text[No abstract available]peer-reviewe
Conditioning the future: Paris 1937 as a civic and urban event
No full textAmongst the many national and international industrial fairs that have pushed the boundaries of traditional, mostly single-themed fairs of old towards survey-type and novelty-orientated events, the Exposition Internationale des Arts et Techniques dans la Vie Moderne held between late May and late November in Paris, France, arguably holds a special place in the annals of such events. It is in this environment that the Exposition Internationale attempted to present a view of (and to) the world that was at once not totalitarian and artistically new; the former was endeavoured in the form of a visualization of the city through the creation of a new viewing terrace, while the latter emerged in the form of a 600 m2 mural named ‘The Electric Fairy’ whose creation was entrusted to the French artist Raoul Dufy. This paper positions the 1937 Fair between these two re-inscriptions of urban life as a series of modern interventions; it will do so by tracing the many contours of an eminently political and urban translation of modernity into a non-totalitarian way of life with the help of differently structured archival material and original texts from the 1930s.peer-reviewe
Shining a light on solar chemicals and fuels: Findings from a SWOT-led (Strengths, Weaknesses, Opportunities, and Threats) literature review and workshop
No full textSolar chemicals and fuels (SCF) show enormous potential and can offer solutions to renewable energy intermittency and storage while reducing industrial CO2 emissions. Yet many challenges remain. SCF advocates face formidable obstacles, which include coordination across the different technological pathways and information dissemination, prohibitive costs, raw materials scarcity, or lengthy development timelines. Our study, then, offers a deeper and more critical understanding of these challenges through a systematic review that discusses the key Strengths, Weaknesses, Opportunities, and Threats threatening or supporting the development of a SCF market. NVivo software was employed to produce this comprehensive SWOT analysis, which was further complemented with a workshop that validated the data and offers a valuable resource for future strategic planning. Results indicate that while technological immaturity remains a major obstacle, a primary strength lies in SCF technologies' suitability for decentralized deployment and specialized applications. Insights from the literature and our workshop participants highlight SCF's potential for energy integration, alongside the critical need for targeted regulation, education, and training within a cohesive policy framework. Our conclusions also emphasize the value of SWOT analysis and workshops in generating insights to help stakeholders address research gaps, foster collaboration, and secure funding to drive future developments.This research, including the workshop featured in this paper, received support from H2020 Marie Skłodowska-Curie Actionspeer-reviewe
A review in Fe(0)/Fe(Ⅱ) mediated autotrophic denitrification for low C/N wastewater treatment
No full textFe-mediated autotrophic denitrification has emerged as a promising technology for low carbon-to-nitrogen (C/N) wastewater treatment due to its cost-effectiveness, operational safety, and independence from organic carbon. While several reviews have addressed this process, there is still a lack of comprehensive analyses that connect iron materials, denitrification performance, and microbial communities. The practical applicability of solid-phase iron has received little attention, and the key controversial issue - Fe(Ⅱ) oxidation pathway - has not been specifically examined. This review systematically examines both liquid- and solid-phase iron sources, with particular emphasis on the practical applicability of solid-phase iron, and further provides an integrated discussion of denitrification performance and associated functional microbes. In addition, this review summarizes a range of iron-oxidizing denitrifiers and highlights several key genera in detail. It also provides an in-depth analysis of Fe(Ⅱ) oxidation pathways, with particular attention to the ongoing debate regarding the involvement of enzymatic mechanisms. Moreover, the latest advancements in both natural and engineered applications are reviewed. Operational parameters such as temperature (T), pH, dissolved oxygen (DO), Fe/N ratio, and other influencing factors are discussed. Finally, several critical challenges that fundamentally affect Fe-mediated autotrophic denitrification are highlighted. This review aims to support the practical implementation of Fe-mediated autotrophic denitrification in low C/N wastewater treatment and contribute to the sustainable development of environmentally friendly biotechnologies for advanced nitrogen control.This work was financially supported by Research Ireland (22/EPSRC/3856), UK Engineering and Physical Sciences Research Council (EP/X010260/1) and China Scholarship Council (No: 202108610042).peer-reviewe
High-performance multiport antenna with frequency selective surface for 5g ka-band applications
No full textThis paper presents a novel multiport antenna tailored for 5G millimeter-wave (mm-Wave) applications. The proposed design features orthogonally arranged radiating elements to ensure compactness with an overall footprint of just 20 × 26 mm2. A key innovation is the integration of a frequency selective surface (FSS) layer placed above the antenna system to enhance gain and isolation without increasing complexity. This FSS enhances gain by 1.5 dB across the band, achieving a peak gain of 7.5 dBi at 41 GHz. The antenna operates across the entire Ka-band (22–46 GHz), delivering efficiency exceeding 80% and maintaining isolation above 20 dB. Key multiport antenna performance parameters including diversity gain (DG = 10) and envelope correlation coefficient (ECC <0.005) align with performance benchmarks, and experimental measurements validate simulation results. The unique combination of orthogonal element placement and FSS enhancement positions this antenna as a robust solution for next-generation 5G applications.Co‐funded by the European Union. Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union or the European Research Executive Agency. Neither the European Union nor the granting authority can be held responsible for them. Besides that, this publication has emanated from research jointly funded by Taighde Éireann‐Research Ireland under Grant 13/RC/2094_2, the European Union's Marie Sklodowska‐Curie Actions under Grant 101126578 and was supported in part by University of Galway. Additionally the authors appreciate the Princess Nourah bint Abdulrahman University Researchers Supporting Project number (PNURSP2025R828), Princess Nourah bint Abdulrahman University, Riyadh, Saudi Arabia
Embodying empathy: Methods of transforming unresolved complex trauma and addressing autistic embodiment within art practice
No full textThis research explores the creation of costume, performance, and the embodiment of metaphorical armour as a means to process and transform unresolved complex trauma associated with lived experience, for neurodivergent people. Utilising my personal experience as a late-diagnosed autistic individual, the study investigates how trauma alters one’s existence, mental health, and physical well-being. Through the creation of physical forms that represent metaphorical armour, this work explores the hypothesis that trauma survivors can retrain their nervous systems to mitigate the perception of danger in non-threatening situations. The impact of complex trauma on mental health is elucidated, revealing its capacity to induce feelings of worthlessness, shame, and emotional dysregulation, alongside physical manifestations that may predispose individuals to various health issues. This inquiry employs performance as a vital tool for self-actualisation, utilising practices such as mindfulness, grounding, and movement exercises to facilitate transformation. In this context I use the word transformation to indicate experiential benefits such as individual empowerment and reduced anxiety. Additionally, the case study of the Wearable Sculpture Workshop exemplifies the dissemination of these practices, emphasising trauma-informed care in creative processes to minimise re-traumatisation. Ultimately, this research contributes to the understanding of trauma through embodied practices, highlighting the potential for creative expression to foster resilience and recovery for neurodivergent people.
First, using myself as a case study, I describe how unresolved complex trauma has altered my life and how unpacking my complex trauma has led to understanding my neurodivergence. Secondly, through performance, I embody this metaphorical armour and create actions to process and transform my trauma through methods including self-actualisation, breathing, grounding, mindfulness, and movement exercises (Qigong). As a case study, I present the experience of my Wearable Sculpture Workshops, in which I shared the practice of processing and transformation with participants through grounding exercises and the constructing of protective costumes by hand. The workshops were facilitated using the principles of trauma-informed care to avoid re-traumatisation. The workshop process resulted in positive feedback from participants with an emphasis on the calming effects of mindfulness meditations and creative actions. Lastly, I present the interviews of three neurodivergent artists, conducted to access insight into shared and different experiences as Autistic and Autistic with Attention Deficit Hyperactivity Disorder (AuDHD) creative people navigating ableist society
Young system development in a cometary globule: A study of infrared and radio observations of the circumstellar disk around AT Pyx
No full textAims: To understand the formation of planetary systems, it is necessary to observe and study systems at different evolutionary stages and in different environments. This project focuses on the AT Pyx system, a protoplanetary disk-hosting young star located in a cometary globule in the Gum Nebula. This is a unique system in that its formation environment differs greatly from the types of environments disks have generally been observed in to date. Using a host of different sources of data this project aims to infer what processes are at play in the disk and what the prognosis may be for planet formation.
Methods: Using data from the VLT’s (Very Large Telescope) instruments XSHOOTER, ESPRESSO and - most prominently - SPHERE along with data from ALMA (Atacama Large Millimetre-submillimetre Array), a variety of measurements (geometric, photometric and otherwise) are made to characterise the observed disk features such as spiral arms and eccentricity. Mapping of the velocity components is also undertaken using the ALMA gas line data to characterise disk orientation and determine likelihood that the system is experiencing a late-stage infall event.
Results: The disk is measured to have a position angle of ∼ 22◦ and an inclination of ∼ 42.5◦. The disk is found to be eccentric with tentative e ≈ 0.626 when deprojected according to literature values for disk height profile. Under the assumption that the formation of a planet is wholly responsible for the primary and secondary spiral arms, the mass of such a planet is found to range between 0.02 and 3 Jupiter masses. Measurement of the velocities associated with nearby globule cloud material returns appropri- ate velocities for a late-stage infall event. Far-ultraviolet field strength at AT Pyx’s location is found to be low in comparison to other surveyed disks. It is also found that AT Pyx is possibly a binary system.
Conclusions: AT Pyx was the first disk within a cometary globule to be spatially resolved, and is now the first such disk to be investigated to this extent. The work of this project could potentially be a first step into the study of disks in the moderate-FUV environment of the Gum Nebula and its globules. Further work involving the high-resolution imaging of AT Pyx and other such disks is recommended and it is suggested that AT Pyx is an excellent candidate target for the forthcoming ELT. A sample of other disks for study in the same region both inside and outside cometary globules and molecular clouds is presented
Conserved and reacting moieties of metabolic networks
No full textA biochemical reaction network is generally represented as a stoichiometric hypergraph, where each vertex corresponds to a metabolite and each hyperedge represents a reaction. While this representation provides an accurate algebraic and graphical description of metabolic networks, it lacks essential graph-theoretic structures, such as cycles and spanning trees, which are central to topological and structural analysis. Each metabolite can also be represented as a molecular graph, where each vertex corresponds to an atom and each edge represents a chemical bond. This molecular representation at the level of atoms and bonds enables the identifica tion of conserved and reacting structures. A conserved moiety is defined as a group of atoms whose association remains invariant across all reactions in the network. A reacting moiety is a group of bonds that are broken, formed, or change order in at least one reaction. This thesis bridges these two levels of representation by introducing a new method to identify conserved and reacting moieties, enabling a mathematically and biologically meaningful representation of biochemical systems.
First, we introduce and develop a well-established mathematical method to identify con served and reacting moieties. This framework enables the representation of a biochemical network at three interrelated levels: the established metabolite–reaction level, an atom–bond resolution level, and a newly defined conserved–reacting moiety level. The method enhances structural resolution and biological interpretability by bridging these scales.
Second, we relate the stoichiometric hypergraph to a set of graph incidence matrices, where each graph corresponds to a moiety transition graph associated with one species of conserved moiety. This representation provides a graph-theoretical interpretation of the four fundamental subspaces of the stoichiometric matrix and establishes a direct link between the algebraic structure of metabolic models and the topological features of moiety-based graphs, offering new analytical tools for interpreting network structure and modularity.
Finally, we develop a preprocessing method for splitting lumped reactions in metabolic networks using sparse flux analysis. This approach improves chemical granularity by replacing lumped reactions with stoichiometrically equivalent elementary steps, enabling more accurate structural interpretation. This preprocessing step prepares the network for the application of our mathematical framework for conserved and reacting moieties to a real-world genome-scale model. As an illustrative case, we focus on a segment of mitochondrial β-oxidation, showing how this procedure reduces combinatorial complexity and enhances interpretability in a biologically relevant setting.
Overall, this work introduces a multiscale modelling framework that connects chemical structures to the algebraic foundations of constraint-based models. By integrating moiety level representations, the thesis enhances the interpretability, modularity, and scalability of biochemical network analysis. While not demonstrating all possible applications, this approach provides a foundation with potential relevance for systems biology, metabolic engineering, and data-driven model refinement