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              <text>This research project aims to comprehensively implement and evaluate several machine learning models for the critical task of brain tumour classification using Magnetic Resonance Imaging (MRI) data. A classical Support Vector Machine (SVM) will serve as a baseline, against which the performance of advanced deep learning architectures, including Convolutional Neural Networks (CNNs) and a Bayesian Convolutional Neural Network (BCNN), will be assessed. The study will rigorously compare these models across key performance indicators: classification accuracy, the robustness of uncertainty quantification, and computational efficiency. Ultimately, this work seeks to provide valuable insights into the efficacy and utility of diverse machine learning paradigms in medical image analysis, with a particular focus on the crucial role of uncertainty estimation in supporting more reliable and informed decisions for early brain tumour diagnosis.</text>
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              <text>Eclipsing brown dwarfs are important calibrators of sub-stellar evolution models used to infer the characteristics of directly imaged brown dwarfs and giant exoplanets. Only two double brown dwarf eclipsing binary systems are known, among them 2MASS J15104786-2818174 (2M1510 AB), published in 2020 with a poorly constrained orbital period. The TESS full-frame image (FFI) photometry of this double line eclipsing binary has been analysed, and its orbital period refined to 20.897782 ± 0.000036 d, reducing its present-day uncertainty from 18 h to 8 min.</text>
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              <text>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.</text>
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