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              <text>The Ehlers-Danlos syndromes (EDS) are a group of genetic disorders characterised by joint hypermobility, stretchy skin, or fragile skin, which are not well understood and can have a disabling effect on a person’s life. These syndromes are caused by changes in the structure and function of proteins, such as collagen, which comprise the extracellular matrix (ECM). The ECM holds cells together, but not much is known about how changes in its composition and molecular dynamics contribute to the development of EDS. This study will use solid-state nuclear magnetic resonance (NMR) spectroscopy to determine the atomic structure and dynamics of ECM obtained from cell culture of fibroblasts from people with and without EDS. By carrying out quantitative comparison of NMR relaxation spectra of the two types of samples, we aim to find similarities and differences that lead to the identification of molecular signatures of specific subtypes of EDS. We envisage that this research will lead to a deeper understanding of EDS and provide insights into how it develops and operates on a molecular level. In the long term, we anticipate that our work may lead to developing better diagnosis strategies and more targeted treatments.</text>
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              <text>Ehlers-Danlos Syndrome, Solid-State NMR, Collagen, Extracellular Matrix</text>
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                <text>Using Solid-State NMR to Identify Molecular Dynamic Signatures of Extracellular Matrix Dysfunction in Ehlers-Danlos Cells </text>
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                <text>Rabiah Ahmed</text>
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                <text>Dr. Wing Ying Chow, Christopher Dean, Abi Hesson and Dr Adil Safeer</text>
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                <text>Using Solid-State NMR on Biological Samples</text>
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          <name>Abstract</name>
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              <text>This project investigates whether time-series signals can be compressed without losing the information needed for reliable classification. Four compression methods—PAA, PLA, APCA and Fourier representations—are evaluated on the FordA and ECG5000 datasets using a shared neural-network classifier. The experiments examine classification performance, training and inference efficiency, and robustness to noise and missing values when only 50% or 25% of the original input width is retained. Signal reconstructions and PCA visualisations are also used to examine which structures remain after compression. The results show that Fourier representations provide the strongest overall trade-off, sometimes improving classification performance while reducing input width and model size, although computational speed-ups depend on the dataset and compression method.</text>
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              <text>machine learning, dimensionality reduction, signal processing, Fourier transform, neural networks, robustness</text>
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                <text>Time-Series Compression for Classification: Performance, Efficiency and Robustness on FordA and ECG5000</text>
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                <text>Kaitao (Kenneth) Jiang</text>
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                <text>Weiren Yu</text>
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                <text>Computer Science – Machine Learning and Time-Series Analysis</text>
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              <text>In this project, I investigate how the timing and strength of mosquito vector-control interventions can be optimised to reduce dengue transmission in Veracruz, Mexico. I develop a seasonally forced SEIR model, fitted to historical dengue case data from 2006, to assess the effectiveness of larval control and adulticide independently and in combination. I explore how changes in implementation start day, intervention duration and control strength affect the reduction in dengue cases to identify the optimal strategy. I then explore how long their effectiveness can be maintained when the intervention is delayed.</text>
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              <text>Dengue, Vector control, Intervention timing, Model fitting,</text>
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                <text>Optimising mosquito control timing to reduce dengue cases in Veracruz, Mexico</text>
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                <text>Rhiana Arora</text>
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                <text>Alexander Kaye</text>
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                <text>Vector control of Dengue</text>
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              <text>This project investigates digit phenomena motivated by a question of Paul Erdős. We study the occurrence of the digit 7 in powers of 2, asking whether every sufficiently large power of 2 contains the digit 7. More generally, we consider the sequence (a·2ⁿ) for varying positive integers a and formulate the following conjecture: the set of a for which a·2ⁿ contains the digit 7 for all sufficiently large n has full natural density. In pursuit of this conjecture, we develop useful combinatorial and arithmetic estimates, together with a dynamical approach to the leading digits of these numbers.</text>
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              <text>number theory, digit occurrence, powers of two, geometric progressions, Benford's law, natural density, logarithmic density, dynamical systems, shrinking targets, irrational rotations, combinatorics, Erdős</text>
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                <text>Digit Occurrence in Geometric Progressions</text>
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                <text>Mathematics – Number Theory and Dynamical Systems</text>
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            <name>Date</name>
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                <text>21/09/2026</text>
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                <text>Joel Moreira</text>
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          <name>Abstract</name>
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              <text>This paper discusses the polity of the Norman adventurer Roussel de Bailleul which existed between 1073 and 1075. It answers how the polity survived for nearly two years with the use of a 'Norman Frontier Society Model' which was similar to other Norman polities such as the Kingdom of Sicily and the Principality of Antioch. Alongside this model, primary sources are utilised to create a contextualised picture of this polity in terms of its politics, economy and society.</text>
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                <text>The Normans in Anatolia: An Analysis of the Functioning of the Polity of Roussel de Bailleul during the 1070s</text>
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                <text>Byzantine Anatolia during the 1070s, primarily the polity of Roussel de Bailleul</text>
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                <text>1073-1075</text>
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                <text>Aysu Dincer Hadjianastasis</text>
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      <name>Academic Poster</name>
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              <text>This poster examines changes in caregivers use of iconic gestures during shared book reading with infants aged 13-14 months and 18 months. It investigates whether caregivers increase their use of iconic gestures as infants develop, and whether this change is due to unique or repeated gestures. The findings show caregivers produce significantly more iconic gestures at 18 months, with increase driven by unique gestures. Caregivers further shift towards object based &amp; shorter gestures, suggesting they communicative behaviour adapts alongside infants developing language. </text>
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              <text>Psychology, Iconic Gestures, Infant development, Caregiver Infant Interaction, Early Communication</text>
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                <text>From 13-14 to 18 Months: A Comparison of Caregivers’ use of Iconic Gestures During Shared Book Readings with Infants &#13;
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                <text>Leah Palmer</text>
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                <text>Suzanne Aussems, Teruni Ahamat</text>
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                <text>Caregivers' Iconic Gestures </text>
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          <name>Abstract</name>
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              <text>Fraudulent banking transactions create substantial financial and operational risks for financial institutions and their customers. The increasing availability of transaction-level data provides an opportunity to identify potentially fraudulent activity using statistical learning methods. This study aims to develop and compare statistical models for predicting whether a banking transaction is fraudulent. A labelled dataset containing approximately 200,000 transaction records is used, with fraud status represented by the binary response variable Fraud. After the removal of direct personal identifiers and other unsuitable fields, variables describing transaction characteristics, customer information, account balances, merchant categories, locations and transaction devices are considered as potential predictors.  The labelled data are divided into a 70% training set and a 30% test set using stratified sampling. Two multiple logistic regression models are developed using different sets or representations of the predictor variables. For each model, backward stepwise selection based on the Akaike Information Criterion is used to reduce the full set of candidate predictors. Five-fold cross-validation is conducted within the training data to examine the predictive performance of the modelling procedures. The two final models are then fitted using the complete training set and applied to the independent test set.  The test predictions are compared with the actual fraud outcomes using confusion matrices, and the predictive accuracy of each model is calculated. Model 1 achieved a test accuracy of 96.91%, while Model 2 achieved a slightly higher accuracy of 96.93%. Therefore, Model 2 was selected as the final model based on its higher test accuracy. The findings demonstrate how logistic regression and backward variable selection can be used to support the identification of potentially fraudulent banking transactions. However, the results should be interpreted considering limitations relating to data quality and the possible use of simulated transaction data.</text>
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              <text>fraud detection, banking transactions, logistic regression, statistical modelling, R</text>
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                <text>Fraud detection in bank transactions using statistical modelling</text>
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                <text>Fraud detection in bank transactions </text>
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                <text>2026-09-26</text>
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                <text>Lisa Li</text>
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        <src>https://linen-dog.lnx.warwick.ac.uk/files/original/78556ff2169f5de5007487a6ad32c038.pdf</src>
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              <text>The Russia--Ukraine war disrupted global food commodity markets, raising concerns over food prices and food security across Africa. This study examines whether countries with greater pre-war dependence on cereal imports from Russia and Ukraine experienced larger increases in domestic food inflation following the outbreak of the conflict, and whether transmission varied with economic development.  Using a monthly panel of 25 African economies from January 2017 to September 2025, the study employs a Difference-in-Differences framework exploiting cross-country variation in pre-war import dependence. Country and month fixed effects account for unobserved heterogeneity and common global shocks, while exchange-rate movements are included as a control. Robustness is assessed using alternative treatment definitions, fixed-effects specifications, placebo tests and leave-one-country-out estimation.  The baseline results provide limited evidence that pre-war dependence on Russian and Ukrainian cereal imports systematically increased domestic food inflation following the outbreak of the war. However, substantial heterogeneity emerges across countries. Higher economic development is associated with significantly smaller increases in food inflation. Further analysis indicates that supplier concentration and domestic cereal production capacity help explain this resilience. Overall, the findings suggest that structural characteristics, rather than import dependence alone, shape countries' resilience to global food commodity shocks.</text>
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              <text>Economics, Food inflation, Food prices, Commodity price shocks, Russia-Ukraine war, Africa, Economic development, Food security, Cereal imports, Import dependence, Economic resilience, Difference-in-Differences, International economics</text>
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                <text>The Transmission of Global Food Commodity Shocks to Food Inflation in Africa: Evidence from the Russia–Ukraine War</text>
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                <text>Daniel Whitehouse, Prof Natalie Chen</text>
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              <text>This project studies the weak and strong cop numbers of Cayley graphs of finitely generated groups, with particular emphasis on methods for proving that the strong cop number is infinite. After reviewing several known results and techniques, we investigate a number of non-hyperbolic examples. For right-angled Artin groups, we use quasi-retractions onto Z² to determine their strong cop numbers in the non-free case. A novelty of this work is the proof that the discrete three-dimensional Heisenberg group H₃(Z) has infinite strong cop number. To show this, we introduce a weighted coordinate function comparable to the word metric and use the natural Heisenberg dilations to construct a sequence of quasi-homotheties. Motivated by this argument, we study a semidirect product Z³ ⋊ₐ Z and establish an analogous word-metric comparison, while the corresponding quasi-homothety problem is left open.</text>
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              <text>geometric group theory, cops and robbers, strong cop number, weak cop number, Cayley graphs, Heisenberg group, quasi-homothety, right-angled Artin groups</text>
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                <text>Infinite Strong Cop Number of the Three-Dimensional Heisenberg Group</text>
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                <text>Dr Jerónimo García Mejía (URSS Supervisor)</text>
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              <text>Factorising integers using elliptic curves</text>
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                <text>Factorising integers using elliptic curves</text>
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                <text>Hamza Zahid</text>
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