University of Bath

High-performance superconducting electric motors have taken transportation electrification to a new era and are of great interest for future hydrogen-powered electric propulsion aircraft. Fully superconducting air-cored motors have great potential to achieve high power density and efficiency. This paper introduces a novel equivalent circuit model for a superconducting motor to analytically calculate magnetic field distribution and then estimate its key performance, including motor electromagnetic torque as well as loss in the rotor electromagnetic shield. Layer theory is used in the airgap winding for rapid evaluation in the early design stage to achieve an effective solution. The paper employs an equivalent circuit to decompose and represent the stator, rotor, airgap, and electromagnetic shield. The parameters of equivalent circuit model are calculated based on the physical dimensions. The results from this analytical methodology are compared and validated with simulations of a 2D finite element model in COMSOL.

Superconducting powertrain is critical for next-generation electric aircraft, allowing for lossless power transmission and significantly increasing efficiency, performance, and range. A superconducting fault current limiter (SFCL) is a device on the DC side that uses superconducting materials to control excessive current during faults, thereby protecting the powertrain and enhancing system stability. Among several superconducting fault current limiters (SFCLs), resistive SFCLs (R-SFCLs) have benefits such as compactness, lightweight, high reliability, and a fail-safe nature. When subjected to alternating magnetic fields or currents, superconducting materials exhibit hysteresis, eddy currents, and flux flow effects, which lead to energy dissipation and reduced efficiency. This also applies to R-SFCLs operating under normal conditions in the superconducting state, where AC losses occur and require appropriate thermal management to mitigate heat generation and prevent unexpected quenching. DC current ripple and its harmonic contents in an R-SFCL cause additional losses, increasing joule heating and potentially driving the superconductor out of its superconducting state, reducing its efficiency and fault-limiting capability. This research was conducted from two perspectives: theoretical calculations and experiments. The objective is to study the losses in the R-SFCL within the superconducting system, including ripple and harmonic effects, and to determine the design parameters of the R-SFCL cooling system to minimise thermal impacts.

We consider adaptive increasingly rare Markov chain Monte Carlo (MCMC) algorithms, which are adaptive MCMC methods, where the adaptation concerning the “past” happens less and less frequently over time. Under a contraction assumption with respect to a Wasserstein-like function we deduce upper bounds of the convergence rate of Monte Carlo sums taking a renormalisation factor into account that is “almost” the one that appears in a law of the iterated logarithm. We demonstrate the applicability of our results by considering different settings, among which are those of simultaneous geometric and uniform ergodicity. All proofs are carried out on an augmented state space, including the classical non-augmented setting as a special case. In contrast to other adaptive MCMC limit theory, some technical assumptions, like diminishing adaptation, are not needed.

This paper reexamines the beta-return relation through the lens of time-varying risk aversion. We show that the security market line (SML) depends critically on the level of aggregate risk aversion. During periods of high risk aversion, the SML exhibits a positive slope and an intercept that is statistically indistinguishable from zero, with investor sentiment playing only a minor role. During periods of low risk aversion, the SML slope becomes negative and the intercept is significantly positive. Investor sentiment affects the SML only when risk aversion is low. These patterns are robust across alternative portfolio constructions, longer investment horizons, and multiple measures of risk aversion.

Knee osteoarthritis causes pain, can limits mobility and is linked to excessive knee loading. Gait retraining with biofeedback shows promise in reducing knee loading and improving pain and function, but optimal feedback strategies remain unclear. This study compared the effects of different biofeedback-based gait retraining approaches on knee joint loading, pain and functional outcomes. Fifty individuals with knee osteoarthritis were randomised to gait pattern feedback group, knee moment feedback group, or control group. Participants underwent a six-week programme, with activity knee pain, functional ability and biomechanical assessments conducted at baseline, post-intervention, and one-month follow-up. Data were analysed using linear mixed models under an intention-to-treat approach. All groups improved in functional ability and activity knee pain post-intervention (p<0.001), with sustained benefits in the intervention groups (p<0.001). Only the gait pattern group showed a lasting reduction in the 1st peak knee adduction moment during (-7.6%, p=0.003; maintained at follow-up). No significant change in foot progression angle was observed in any group. Step width increased during stair ascent and sit-to-stand (p≤0.010) and step length decreased during walking (p=0.021) for all groups, but both changes were transient. Gait retraining improves pain and function in individuals with knee OA, but gait pattern feedback uniquely reduces joint loading during walking, supporting the importance of target-specific personalised gait modifications for long-term biomechanical benefit.

Alcohol use is driven not only by environmental cues but also by individual differences in motivational style. Recent work has demonstrated how memory cues can reduce subsequent desire for alcohol, yet it remains unclear how personality traits shape this effect. To address this, we recruited male and female participants ( N = 169) who completed the behavioural inhibition/approach system (BIS/BAS) scales and were then cued to recall either a previous alcohol drinking episode and estimate the number of alcohol calories consumed (Alcohol Cue, AC) or a control (Neutral Cue, NC). They then rated their desire for alcohol (DAQ). Findings revealed lower desire for those in the AC compared to NC group and separately, a positive association between alcohol desire and BAS and particularly BAS-Drive. We further found that a measure of residual BAS (BAS less BIS) was positively related to desire but did not moderate the effect of memory cue. These findings suggest that being reminded of a previous drinking episode can exert a modest but consistent influence on alcohol desire. • Memory of a recent drinking episode reduced alcohol desire in males and females. • Increases in Behavioural Approach System (BAS) increased alcohol desire. • BAS did not moderate the effect of the alcohol memory cue. • Memory cues could offer a simple method of reducing alcohol desire.

ZFTA-RELA is the most recurrent genetic alteration seen in paediatric supratentorial ependymoma (EPN) and is sufficient to initiate tumours in mice1. Despite its oncogenic potential, ZFTA-RELA (ZR) is observed nearly exclusively in childhood EPN, with tumours located distinctly in the supratentorial brain of the central nervous system1. We proposed that specific chromatin modules accessible during brain development would render distinct cell lineage programs at direct risk of transformation by ZR. To test this hypothesis, we performed combined single-nucleus assay for transposase-accessible chromatin and RNA (snMultiome) sequencing of the developing mouse forebrain compared with ZR-driven mouse and human EPN. We demonstrated that specific developmental lineage programs present in transient progenitor cells and regulated by PLAG/L family transcription factors were at risk of neoplastic transformation. Binding of this chromatin network by ZR or other PLAG/L family motifs targeting fusion oncoproteins led to persistent chromatin accessibility at oncogenic loci and oncogene expression. Cross-species analysis of mouse and human ZR EPN revealed significant cell type heterogeneity indicating incomplete neurogenic and gliogenic differentiation, with a small percentage of cycling progenitor-like or radial glial-like cells that established a putative tumour cell hierarchy. In vivo lineage tracing studies identified neoplastic clones that aggressively dominated tumour growth and established the entire EPN cellular hierarchy. These findings identify developmental epigenomic states that are critical for fusion-oncoprotein-driven transformation and show how these states continue to shape tumour progression.