60 10 900 https://linen-dog.lnx.warwick.ac.uk/files/original/18e2ff8f94d0e82051c52ebecb64200f.pot d18186845f9e725b558680cbc1fedacd Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Science, Engineering and Medicine Academic Poster An academic poster Abstract The abstract of the paper Venous thromboembolism (VTE) remains the leading cause of maternal death in the UK. With a significant proportion of cases occurring in the first trimester, there is a clear need for improved preconception care to identify and reduce risk. This mixed-methods study explores women’s awareness, access, and experiences of preconception care in relation to VTE risk through an online survey and focus group discussions. Findings will inform strategies to enhance equitable and effective preconception services, ensuring that women receive timely and tailored advice to support safer pregnancies. Meta Tags Meta tags Maternal Health, Reproductive Health, Preconception Care, Fertility Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Creator An entity primarily responsible for making the resource Tessa Tattersall Contributor An entity responsible for making contributions to the resource Dr Joshua Odendaal Subject The topic of the resource Warwick Medical School Title A name given to the resource Preconception Care Date A point or period of time associated with an event in the lifecycle of the resource 2025 https://linen-dog.lnx.warwick.ac.uk/files/original/bb764642acc179b614770fcd3087c3cc.pdf 83548503b72e3235aab6212f6b9a971d Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Science, Engineering and Medicine Academic Paper An academic paper Abstract The abstract of the paper Within a biological system, proteins are essential; they are the building blocks of life. Their functions range from performing as antibodies to catalysing reactions as enzymes; so, proteins have an extremely varied and extensive use through a variety of industries. With mutations, their stability and functionality can be modified, with even single-point mutations having a strong effect. Therefore, being able to predict the effect in stability changes of these mutations is essential, but often computationally costly and weak when encountering unseen data. With the rise in popularity of protein language models (PLMs), including ESM, there have been improvements, but these models still encounter the same difficulties. This study explores the effect of ensemble learning on improving protein stability predictions. This is done by combining two base models: a convolutional neural network (CNN) using wild-type and mutant sequences, and a neural network trained on frozen ESM embeddings. They each form two base-learners, where each is trained on half the base training data. To combine their predictions, intermediate meta-learners for each model type and a final meta-learner are used. Results show that ensemble learning improves predictions over base models, showing improvements in all performance metrics used. Notably, even the weaker CNN-based learners contributed to improved ensemble performance, reinforcing the benefit of this type of architecture. Although it is necessary to further optimise hyperparameters and include stronger base models in the future, these results indicate that ensemble learning can lead to more accurate protein stability prediction with minimal additional computational cost. Meta Tags Meta tags protein stability predictions, mutation effect prediction, ensemble learning Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Subject The topic of the resource Computer Science Date A point or period of time associated with an event in the lifecycle of the resource 2025 Title A name given to the resource Predicting Protein Stability of Single-Point Mutations using Ensemble Learning and ESM Embeddings Creator An entity primarily responsible for making the resource Victoria Krushovska https://linen-dog.lnx.warwick.ac.uk/files/original/32212e6da1d98a7ef3a88ca202a4ba8b.pdf 8c68705fa054bf92460e971858da9a0d Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Science, Engineering and Medicine Academic Poster An academic poster Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Predicting the solubility of amorphous drugs via machine learning. Subject The topic of the resource Chemistry Creator An entity primarily responsible for making the resource Jonas Miksys Date A point or period of time associated with an event in the lifecycle of the resource 2021 Chemistry Drugs Machine learning https://linen-dog.lnx.warwick.ac.uk/files/original/374a7b4b3fa0121cdf71d5e86726679b.pdf 5817e7ae553243053e5d1aaefc058022 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Social Sciences Subject The topic of the resource Social Sciences Academic Paper An academic paper Abstract The abstract of the paper The present study examined whether flexibility, resource loss/gain, and the ability to maintain daily routines predict post-traumatic stress (PTS) among survivors of the 2023 Turkey earthquakes. We also explored whether post-traumatic stress levels differ by gender (female vs male). Forty-nine earthquake survivors were recruited to complete online questionnaires measuring PTS, cognitive flexibility, flexibility mindset, resource changes, and everyday routine maintenance. Multiple regression analyses indicated that none of these variables significantly predicted PTS (p = .704). Independent samples t-test suggested that females reported significantly higher PTS levels than males, t(20) = 2.27, p = .035. While the findings did not support previous research linking these factors to post-traumatic stress (possibly due to the small sample size) they highlight significant gender differences. Future research should involve larger samples, explore additional factors contributing to post-traumatic stress, and investigate the underlying reasons on females reporting greater post-traumatic stress compared to males. Meta Tags Meta tags Earthquake, post-traumatic stress, Turkey, 2023 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Subject The topic of the resource Psychology Date A point or period of time associated with an event in the lifecycle of the resource 2024 Contributor An entity responsible for making contributions to the resource Professor Robin Goodwin Creator An entity primarily responsible for making the resource Yagmur Tekten Title A name given to the resource Predictors of Post-traumatic Stress Among Individuals Who Survived the February 2023 Earthquakes in Turkey https://linen-dog.lnx.warwick.ac.uk/files/original/5bdd78a6133576dcefdb71963a7350f1.pdf 7d85c0d805a6ee3a195d6697a09f6b87 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Science, Engineering and Medicine Academic Paper An academic paper Abstract The abstract of the paper Premenstrual Dysphoric Disorder is characterised by the cyclical nature of psychological and somatic symptoms occurring in the luteal phase of the menstrual cycle that significantly affect the functioning of various aspects of daily life. Controversy, paucity of knowledge and awareness surrounds the research on Premenstrual dysphoric Disorder. It is an under-researched disorder riddled with methodological limitations, lack of diversity in cohort studies, small samples and a lack of systemic reviews, meta-analysis and randomised control trials. No universal diagnostic and screening standardised method is used worldwide, nor is there a different nomenclature used to describe the disorder. First-line treatment of the disease differs among professional healthcare bodies. The foundations of Premenstrual dysphoric disorder were always controversial, as seen with its inclusion in the American Psychiatric DSM-5 and the World Health Organisation’s ICD11 caused controversy where psychologists and feminist thinkers alike argued that this is a way of pathologising a natural process, adding to the stigma around women’s emotions being tied to their hormones. The pathophysiology of the disease is still relatively unknown. However, a widely accepted cause is the interaction of reproductive steroids like oestrogen, progesterone and allopregnanolone on central neurotransmitters like serotonin and GABAa receptors and the Hypothalamic-pituitary-ovarian axis. Other possible causes, associations, and co-morbidities are discussed. There needs to be more precise definitions around premenstrual dysphoric disorder separated from premenstrual syndrome and more education within healthcare systems about the disorder in order to improve patient-provider communication for better experiences and a more accurate clinical picture of the disorder. As well as more personalised care for women with PMDD and approaching research of the pathophysiology from a psychosomatic perspective. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Subject The topic of the resource Life Sciences Date A point or period of time associated with an event in the lifecycle of the resource 2024 Contributor An entity responsible for making contributions to the resource Olanrewaju Sorinola Title A name given to the resource Premenstrual Dysphoric Disorder Creator An entity primarily responsible for making the resource Amina Mohamed https://linen-dog.lnx.warwick.ac.uk/files/original/dc2234b52a6e72842a1dae0e04dab538.pdf fc0705a1d0ace764c0b2ee1e7873de6f Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Science, Engineering and Medicine Academic Poster An academic poster Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Pressure sensitive adhesives from emulsion polymerization: the effect of molecular weight on adhesion Subject The topic of the resource Life Sciences Creator An entity primarily responsible for making the resource Mars Poxon Date A point or period of time associated with an event in the lifecycle of the resource 2022 adhesion emulsion polymerization molecular weight monodispercity https://linen-dog.lnx.warwick.ac.uk/files/original/818cc9155a11f5410dbee30d8326e2f1.pdf fea550609ee1f1aafaaf9bbd72830fa7 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Social Sciences Subject The topic of the resource Social Sciences Academic Poster An academic poster Abstract The abstract of the paper Only around one-third of London’s tube stations currently offer full step-free access from street to train – a limitation that restricts mobility for many and undermines the goal of an inclusive, equitable London. Enhancing accessibility is therefore not merely an infrastructural priority but a social imperative. Yet, with limited resources, strategic prioritisation is essential. This project adopts a data-driven approach to identify and prioritise stations for accessibility upgrades, maximising social benefit and supporting a fairer, more connected London. Meta Tags Meta tags tfl, London, Tube, TfL, Accessibility, Analytics, Geospatial Analytics, Transport, Access, Train, Business Analytics, Data Analysis, London Tubes, Transport for London, Equity, Access, Step-Free Station, Station Upgrades Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Creator An entity primarily responsible for making the resource Jai Kamat Subject The topic of the resource Warwick Business School Title A name given to the resource Prioritising Step-Free Station Upgrades to Improve Accessibility on the London Tube Network Date A point or period of time associated with an event in the lifecycle of the resource 2025 https://linen-dog.lnx.warwick.ac.uk/files/original/e9fb71e2a6ee2e950f08b3bd334ba5b7.pdf 1921b2f5fafa92ec6941eb03e817507b Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Science, Engineering and Medicine Academic Poster An academic poster Abstract The abstract of the paper This project investigates a novel kind of automaton, PQA and demonstrates that the class of languages it represents has interesting properties. Meta Tags Meta tags Automata, Computer Science, Priority Queue Automata, John Ellis, Formal Languages, Ackermann Hard Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Creator An entity primarily responsible for making the resource John Ellis Contributor An entity responsible for making contributions to the resource John Ellis Title A name given to the resource Priority Queue Automata Subject The topic of the resource Computer Science Date A point or period of time associated with an event in the lifecycle of the resource 2025 https://linen-dog.lnx.warwick.ac.uk/files/original/d2fcf744f738c43ddcf87713e771255f.pdf cf0f55c578581a90deb6a2efbbb71787 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Social Sciences Subject The topic of the resource Social Sciences Academic Poster An academic poster Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Privacy Concerns of Proctoring and Data Governance of Assessed Work: Challenges and Potential Solutions Subject The topic of the resource Education Creator An entity primarily responsible for making the resource Jiaqing Zhu Date A point or period of time associated with an event in the lifecycle of the resource 2021 Artificial intelligence Education Higher education https://linen-dog.lnx.warwick.ac.uk/files/original/c669adda2af884b80d5d76bd4fbf0a82.pdf 6dbb93eb0580ab13078eed5492450660 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Mathematics Academic Poster An academic poster Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Creator An entity primarily responsible for making the resource Danyal Khan Contributor An entity responsible for making contributions to the resource Tommaso Rosati Subject The topic of the resource Percolation Theory Title A name given to the resource Probability and Percolation: Infinite Structure in Infinite Lattices Description An account of the resource Mathematics Date A point or period of time associated with an event in the lifecycle of the resource 2025