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              <text>This project is about the use of Graph Neural Networks (GNNs) to understand the link between graph theory and deep learning. One of the main goals is to understand how GNNs can depict useful patterns in graph-structured data. I analysed the Elliptic Bitcoin transaction dataset which is used for fraud detection. By implementing a node classification model, the project shows how combining information from neighbouring nodes improves prediction accuracy compared to traditional machine learning models. The research illustrates the potential of GNNs in financial forensics and provides insight on model assessment with various metrics such as precision, recall, and F1-score. </text>
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                <text>This project surveys a mathematical problem called the Cartan–Hadamard conjecture.</text>
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              <text>Traditionally, academics have suggested that generating excess returns off timing the market, i.e. buying or selling financial products off frequent predictions requires maintaining an unreasonably high level of predictive accuracy. However, recent advancements in machine learning have motivated the adoption of predictive algorithms in financial markets. This highlights the importance of the question: How accurate do predictive algorithms have to be "useful"? To answer this, we study 2 problems related to the value of predictive accuracy in directional models for trading. We obtain results on the relationship between predictive accuracy and returns, and results on quantifying thresholds for when a predictive signal provides significant edge. </text>
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              <text>Ruthenium(II) polypyridyl complexes are promising alternatives to platinum-based anticancer drugs due to their tunable photophysical properties and reversible DNA interactions. This study reports the synthesis, characterisation, and DNA-binding analysis of [Ru(dmbpy)₂(tpphz)]²⁺. The complex was successfully prepared and confirmed using 1H NMR, IR, UV-Vis, and mass spectrometry. UV-Vis spectra revealed characteristic MLCT bands near 450 nm, while DNA titrations showed hypochromism and red shifts, indicating intercalation. Luminescence studies demonstrated a ‘light-switch’ effect upon DNA addition, consistent with increased emission in the bound state. The binding constant (K_b ≈ 3.9 × 10⁵ M⁻¹) and low quantum yield (Φ ≈ 2%) suggest moderate affinity but promising photoactive potential. Overall, [Ru(dmbpy)₂(tpphz)]²⁺ exhibits characteristics desirable for further investigation as a potential photoactivated anticancer agent.</text>
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              <text>Cellulose is the most abundant natural polymer in the world, acting as the primary structural component in plant cell walls and key in processing several biomaterials. Cellulosic materials are sustainable alternatives to synthesised polymers such as plastics, with the potential to replace them in many sectors, such as textiles and packaging. To utilise cellulose effectively, we must understand how its structure changes under a variety of treatments and processes. Inspired by this notion, this project investigates how different drying methods affect the structure of cellulose extracted from tomatoes, using solid-state nuclear magnetic resonance (ssNMR), a spectroscopic technique that reveals the molecular structure without destroying the sample.</text>
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              <text>Disability, health condition, Personal Independence Payment, Disabled Students’ Allowance, Disability Living Allowance, Students’ Union, welfare, benefits, advice, DWP, support, semi-structured interviews, survey</text>
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                <text>This mixed-methods research project investigates the experiences of disabled students at the University of Warwick in applying for and accessing Personal Independence Payment (PIP), a UK welfare benefit that supports individuals with long-term health conditions or disabilities. The study examines the barriers students face to applying, the challenges encountered throughout the process, and the types and effectiveness of support received. It also explores students’ perceptions of the application outcomes, common misconceptions about PIP, and engagement with Disabled Students’ Allowance (DSA). Ultimately, the project seeks to identify key areas where support mechanisms can be strengthened, with a particular emphasis on enhancing the advice and advocacy services provided by the Students’ Union Advice Centre.</text>
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