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              <text>Planetary gearboxes play a critical role in wind turbine drivetrains, enabling the efficient conversion of low-speed, high-torque rotor motion into high-speed rotation for electrical generation. However, frictional and material losses within these gear systems can significantly reduce overall turbine performance, particularly under low-speed operating conditions. This study experimentally investigated the mechanical efficiency of a scaled-down, 3D-printed planetary gearbox designed to replicate typical wind turbine gear ratios. A custom test rig was developed, incorporating a 12 V DC motor driving the input shaft at 5 - 25 rpm, with torque and speed measured using a current sensor, load cell and two infrared proximity sensors. Results validated the theoretical 1:8 step-up gear ratio and showed that efficiency increased from 69% at 5 rpm to a peak of approximately 85% around 15 - 16 rpm before declining at higher speeds. These findings demonstrate that small-scale polymer planetary stages can replicate real gearbox behaviour and offer valuable insight into efficiency optimisation and material selection for larger-scale wind energy applications.</text>
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                <text>Tinashe Makuyana</text>
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                <text>My poster and notes on creating operators that satisfy the summation by parts property. These can be used to numerically approximate derivatives and solutionsto differential equations to a very high order of accuracy, with a guarantee that the numerical result is bounded.&#13;
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I tried to create a large variety of operators with this property: some were successful; others weren't. These are inspired by finite differences in that the numerical result's values at the half-integers match what a finite difference would give.</text>
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                <text>Lynn Zhang</text>
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              <text>Hominoidea is a superfamily of Primates comprising all ancient and extant apes, including the lineage that led to Homo sapiens. The fossil record belonging to this superfamily is imperfect due to environmental, spatial, and collection biases. This preliminary study uses previously devised metrics to quantify the completeness of the fossil record of non-hominin (not direct ancestors of Homo) hominoids, to highlight critical knowledge gaps that may be hindering our understanding of hominoid evolution.</text>
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              <text>Nanodiamonds, Hypoxia, Fibre photometry, in vivo </text>
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                <text>Prof Sébastien Perrier </text>
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              <text>Large Language Models (LLMs) achieve outstanding performance but are expensive to fine-tune due to their size. Parameter-efficient fine-tuning (PEFT) methods like Low-Rank Adaptation (LoRA) address this by updating only small low-rank matrices while keeping pretrained weights frozen. This project explores LoRA and its variants—QLoRA, AdaLoRA, and LoRA-One—through theoretical analysis and experiments on the GLUE benchmark using T5-base. Results show that LoRA achieves near full fine-tuning performance with under 1% of trainable parameters. The study highlights LoRA’s efficiency–expressiveness trade-off and contributes to developing more scalable, adaptive fine-tuning strategies for large models.</text>
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