Background: Cerebral palsy (CP) is a neuromotor disorder whereby gait abnormalities are predominant. Motion analysis is instrumental in management. While 3D kinematic labs exist, they are costly to operate, and the expertise required to interpret limits their availability to only a handful of facilities. In response, we have developed an Automated Intelligence (AI) driven pipeline to automate gait evaluation using 2-dimensional video. We assess the performance of this tool in comparison to traditional evaluation using visual assessment by trained human expert. Methods: A dataset of 109 patients with CP (6–37 years) (GMFCS I – II) was processed using our tool. The Edinburgh Visual Gait Score (EVGS) was derived using videos capturing sagittal and coronal views. Algorithm performance was determined by comparing automated EVGS scores against clinical expert scoring. Results: The AI pipeline successfully analysed 105/109 patient videos. For most EVGS parameters (14/17), the algorithm demonstrated moderate to high accuracy (70-94%), while 3 parameters (hindfoot valgus/varus, maximum lateral trunk shift, pelvic rotation at midstance) demonstrated lower accuracy (58-62%). Conclusions: This study validates the feasibility of an AI-augmented pipeline for automating EVGS-based gait assessments. With ongoing development, this technology has potential to improve accessibility to gait analysis and allows deployment outside of traditional settlings.

The Australian SKA Pathfinder (ASKAP) offers powerful new capabilities for studying the polarised and magnetised Universe at radio wavelengths. In this paper, we introduce the Polarisation Sky Survey of the Universe’s Magnetism (POSSUM), a groundbreaking survey with three primary objectives: (1) to create a comprehensive Faraday rotation measure (RM) grid of up to one million compact extragalactic sources across the southern $\sim50$% of the sky (20,630 deg$^2$); (2) to map the intrinsic polarisation and RM properties of a wide range of discrete extragalactic and Galactic objects over the same area; and (3) to contribute interferometric data with excellent surface brightness sensitivity, which can be combined with single-dish data to study the diffuse Galactic interstellar medium. Observations for the full POSSUM survey commenced in May 2023 and are expected to conclude by mid-2028. POSSUM will achieve an RM grid density of around 30–50 RMs per square degree with a median measurement uncertainty of $\sim$1 rad m$^{-2}$. The survey operates primarily over a frequency range of 800–1088 MHz, with an angular resolution of 20” and a typical RMS sensitivity in Stokes Q or U of 18 $\mu$Jy beam$^{-1}$. Additionally, the survey will be supplemented by similar observations covering 1296–1440 MHz over 38% of the sky. POSSUM will enable the discovery and detailed investigation of magnetised phenomena in a wide range of cosmic environments, including the intergalactic medium and cosmic web, galaxy clusters and groups, active galactic nuclei and radio galaxies, the Magellanic System and other nearby galaxies, galaxy halos and the circumgalactic medium, and the magnetic structure of the Milky Way across a very wide range of scales, as well as the interplay between these components. This paper reviews the current science case developed by the POSSUM Collaboration and provides an overview of POSSUM’s observations, data processing, outputs, and its complementarity with other radio and multi-wavelength surveys, including future work with the SKA.

As avionics systems become increasingly complex, traditional fault prediction methods are no longer sufficient to meet modern demands. This paper introduces four advanced fault prediction methods for avionics components, utilising a multi-step prediction strategy combined with a stacking regressor. By selecting various standard regression models as base regressors, these base regressors are first trained on the original data, and their predictions are subsequently used as input features for training a meta-regressor. Additionally, the Tree-structured Parzen Estimator (TPE) algorithm is employed for hyperparameter optimisation. The experimental results demonstrate that the proposed stacking regression methods exhibit superior accuracy in fault prediction compared to traditional single-model approaches.

This contribution focuses on the abatement with hydrogen of CO2 and non-CO2 emissions. It is agenda-setting in two respects. Firstly, it challenges the globally accepted hydrocarbon sustainable aviation fuel (SAF) pathway to sustainability and recommends that our industry accelerates along the hydrogen pathway to ‘green’ aviation. Secondly, it reports a philosophical and analytical investigation of appropriate accuracy on abatement strategies for nitrogen oxides and contrails of large hydrogen airliners. For the second contribution, a comparison is made of nitrogen oxide emissions and contrail avoidance options of two hydrogen airliners and a conventional airliner of similar passenger capacity. The hydrogen aircraft are representative of the first and second innovation waves where the main difference is the weight of the hydrogen tanks. Flights of 1000, 2000, 4000 and 8000 nautical miles are explored. Cranfield’s state of the art simulators for propulsion system integration and gas turbine performance (Orion and Turbomatch) were used for this. There are two primary contributions to knowledge. The first is a new set of questions to be asked of SAF and hydrogen decarbonising features. The second is the quantification of the benefits from hydrogen on non-CO2 emissions. For the second generation of long-range hydrogen-fuelled aircraft having gas turbine propulsion, lighter tanks (needing less thrust and lower gas temperatures) are anticipated to reduce NOx emissions by over 20%; in the case of contrails, the preliminary findings indicate that regardless of the fuel, contrails could largely be avoided with fuel-burn penalties of a few per cent. Mitigating action is only needed for a small fraction of flights. For conventional aircraft this penalty results in more CO2, while for hydrogen aircraft the additional emission is water vapour. The conclusion is that our research community should continue to consider hydrogen as the key ‘greening’ option for aviation, notwithstanding the very significant costs of transition.

Bentonite- and sepiolite-supported copper catalysts have been prepared either by adsorption of Cu(II) from aqueous solutions of copper nitrate at pH ~4.5 or by adsorption of a [Cu(NH3)4]2+ complex from an ammonia solution of CuSO4 at pH ~9.5. The structure and composition of the calcined preparations have been studied by X-ray diffraction, chemical analysis, and energy dispersive X-rays. Textural characteristics have derived from the analysis of the adsorption-desorption isotherms of N2. All catalysts have been tested for the dehydrogenation of methanol to methyl formate. For this reaction, bentonite-based catalysts were found to have very little activity, which indicates that copper located in the inter-lamellar spaces is inaccessible to methanol molecules. On the contrary, copper-sepiolite catalysts showed a very high specific activity even for those catalysts with a very low copper content. The chemical state of copper in the catalysts on-stream has been revealed by X-ray photoelectron spectroscopy and X-ray-induced Auger techniques. In most of the catalysts Cu+ is the dominant copper species.

Ultra-processed plant-based foods, such as plant-based burgers, have gained in popularity. Particularly in the out-of-home (OOH) environment, evidence regarding their nutritional profile and environmental sustainability is still evolving. Plant-based burgers available at selected OOH sites were randomly sampled in Amsterdam, Copenhagen, Lisbon and London. Plant-based burgers (patty, bread and condiment) (n 41) were lab analysed for their energy, macronutrients, amino acids and minerals content per 100 g and serving and were compared with reference values. For the plant-based burgers, the median values per 100 g were 234 kcal, 20·8 g carbohydrates, 3·5 g dietary fibre and 12·0 g fat, including 0·08 g TFS and 2·2 g SFA. Protein content was 8·9 g/100 g, with low protein quality according to amino acid composition. Median Na content was 389 mg/100 g, equivalent to 1 g salt. Compared with references, the median serving provided 31% of energy intake based on a 2000 kcal per day and contributed to carbohydrates (17–28%), dietary fibre (42%), protein (40%), total fat (48%), SFA (26%) and Na (54%). One serving provided 15–23% of the reference values for Ca, K and Mg, while higher contributions were found for Zn, Mn, P and Fe (30–67%). The ultra-processed plant-based burgers provide protein, dietary fibre and essential minerals and contain relatively high levels of energy, Na and total fats. The amino acid composition indicated low protein quality. The multifaceted nutritional profile of plant-based burgers highlights the need for manufacturers to implement improvements to better support healthy dietary habits, including reducing energy, Na and total fats.

From 2017 to 2020, three significant calving events took place on Pine Island Glacier, West Antarctica. Ice-shelf velocities changed over this period and the calving events have been suggested as possible drivers. However, satellite observations also show significant changes in the areal extent of fracture zones, especially in the marginal areas responsible for providing lateral support to the ice shelf. Here, we conduct a model study to identify and quantify drivers of recent ice-flow changes of the Pine Island Ice Shelf. In agreement with recent studies, we find that the calving events caused significant velocity changes over the ice shelf. However, calving alone cannot explain observed velocity changes. Changes in the structural rigidity, i.e. ice damage, further significantly impacted ice flow. We suggest that ice damage evolution of the ice-shelf margins may have influenced recent calving events, and these two processes are linked.

We report on the modification of the spectrum of a passive scalar inside a turbulent flow by the injection of large bubbles. Although the spectral modification through bubbles is well known and well analysed for the velocity fluctuations, little is known on how bubbles change the fluctuations of an approximately passive scalar, in our case temperature. Here we uncover the thermal spectral scaling behaviour of a turbulent multiphase thermal mixing layer. The development of a $-3$ spectral scaling is triggered. By injecting large bubbles (${Re}_{{bub}} = {O}(10^2)$) with gas volume fractions $\alpha$ up to 5 %. For these bubbly flows, the $-5/3$ scaling is still observed at intermediate frequencies for low $\alpha$ but becomes less pronounced when $\alpha$ further increases and it is followed by a steeper $-3$ slope for larger frequencies. This $-3$ scaling range extends with increasing gas volume fraction. The $-3$ scaling exponent coincides with the typical energy spectral scaling for the velocity fluctuations in high-Reynolds-number bubbly flows. We identify the frequency scale of the transition from the $-5/3$ scaling to the $-3$ scaling and show how it depends on the gas volume fraction.

Solvent exchange is a process involving mixing between a good solvent with dissolved solute and a poor solvent. The process creates local oversaturation which causes the nucleation of minute solute droplets. Such ternary systems on a macro-scale have remained unexplored in the turbulent regime. We experimentally study the solvent exchange process by injecting mixtures of ethanol and trans-anethole into water, forming a turbulent buoyant jet in the upward direction. Locally, turbulent mixing causes oversaturation of the trans-anethole following turbulent entrainment. We optically measure the concentration of the nucleated droplets using a light attenuation technique and find that the radial concentration profile has a sub-Gaussian kurtosis. In contrast to the entrainment-based models, the spatial evolution of the oversaturation reveals continuous droplet nucleation downstream and radially across the jet, which we attribute to the limited mixing capacity of the jet. Although we are far from a full quantitative understanding, this work extends the knowledge on solvent exchange into the turbulent regime, and brings in a novel type of flow, broadening the scope of multicomponent, multiphase turbulent jets with phase transition.

Spoofing is a kind of deliberate interference that aims to manipulate global navigation satellite system (GNSS) receivers into counterfeit position solutions. Conventional anti-spoofing methods are implemented prior to the calculation of the position solution, depending on the specific spoofing attack mechanisms. The paper presents a spoofing detection and mitigation method implemented in the position domain. The proposed method projects the correlograms of the visible satellites to a position-clock bias domain to construct the position domain projected correlogram. P(Y) code signatures retrieved from a reference station receiver are used to identify the counterfeit position solution and remove it from the victim receiver. Compared with the conventional single-channel spoofing detection technique, the proposed anti-spoofing method is more robust against thermal noise by combining the energy from multiple satellites. Detailed mathematical derivation of the statistical characteristics of this method is presented. Its effectiveness is validated using a realistic dataset generated by a Spirent GNSS simulator and NordNav wideband front-end. Results show that the proposed algorithm is capable of not only detecting a spoofing attack but also removing the spoofing effect from the victim receiver.

We experimentally investigate the effect of geometrical anisotropy for buoyant spheroidal particles rising in a still fluid. All other parameters, such as the Galileo number (the ratio of gravitational to viscous forces) $Ga \approx 6000$, the ratio of the particle to fluid density $\varGamma \approx 0.53$ and the dimensionless moment of inertia $\boldsymbol{\mathsf{I}}^*= \boldsymbol{\mathsf{I}}_p/\boldsymbol{\mathsf{I}}_f$ (with $\boldsymbol{\mathsf{I}}_p$ being the moment of inertia of the particle and $\boldsymbol{\mathsf{I}}_f$ that of the fluid in an equivalent volume), are kept constant. The geometrical aspect ratio of the spheroids, $\chi$ , is varied systematically from $\chi = 0.2$ (oblate) to 5 (prolate). Based on tracking all degrees of particle motion, we identify six regimes characterised by distinct rise dynamics. Firstly, for $0.83 \le \chi \le 1.20$, increased rotational dynamics are observed and the particle flips over semi-regularly in a ‘tumbling’-like motion. Secondly, for oblate particles with $0.29 \le \chi \le 0.75$, planar regular ‘zig–zag’ motion is observed, where the drag coefficient is independent of $\chi$. Thirdly, for the most extreme oblate geometries ($\chi \le 0.25$), a ‘flutter’-like behaviour is found, characterised by precession of the oscillation plane and an increase in the drag coefficient. For prolate geometries, we observed two coexisting oscillation modes that contribute to complex trajectories: the first is related to oscillations of the pointing vector and the second corresponds to a motion perpendicular to the particle's symmetry axis. We identify a ‘longitudinal’ regime ($1.33 \le \chi \le 2.5$), where both modes are active and a different one, the ‘broadside’-regime ($3 \le \chi \le 4$), where only the second mode is present. Remarkably, for the most prolate particles ($\chi = 5$), we observe an entirely different ‘helical’ rise with completely unique features.

Longan is an economically important sub-tropical fruit tree native to southern China and southeast Asia. Its production has been affected significantly by climate change, but the underlying reasons remain unclear. Herein, the potential growing areas of longan were simulated by the Maxent model under current and future conditions. The results showed excellent prediction performance, with an area under curve of >0.9 for model training and validation. The key environmental variables identified were mean temperature of the coldest quarter, minimum temperature of the coldest month, annual mean temperature and mean temperature of the driest quarter. The optimum suitable areas of longan were found to be concentrated mainly in south-western, southern and eastern China, with a slight increase in optimum suitable areas under two different emission scenarios of three global climatic models. However, its future potential growing areas were predicted to differ among provinces or cities. Suitable growing areas in Sichuan, Jiangxi, Guangxi and Chongqing will first increase and then remain approximately unchanged between the 2050s and 2070s; those in Yunnan, Guangdong and Hainan will remain approximately unchanged from the present to the 2070s; those in Fujian and Guizhou will fluctuate slightly from the present to the 2050s and then increase to the 2070s; those in Taiwan will first decrease and then increase. In summary, the major future production areas of longan will be Guangdong, Hainan and Guangxi provinces, followed by Chongqing, Yunnan, Fujian and Taiwan. Thus, this study serves as a useful guide for the management of longan.

Gravitational waves from coalescing neutron stars encode information about nuclear matter at extreme densities, inaccessible by laboratory experiments. The late inspiral is influenced by the presence of tides, which depend on the neutron star equation of state. Neutron star mergers are expected to often produce rapidly rotating remnant neutron stars that emit gravitational waves. These will provide clues to the extremely hot post-merger environment. This signature of nuclear matter in gravitational waves contains most information in the 2–4 kHz frequency band, which is outside of the most sensitive band of current detectors. We present the design concept and science case for a Neutron Star Extreme Matter Observatory (NEMO): a gravitational-wave interferometer optimised to study nuclear physics with merging neutron stars. The concept uses high-circulating laser power, quantum squeezing, and a detector topology specifically designed to achieve the high-frequency sensitivity necessary to probe nuclear matter using gravitational waves. Above 1 kHz, the proposed strain sensitivity is comparable to full third-generation detectors at a fraction of the cost. Such sensitivity changes expected event rates for detection of post-merger remnants from approximately one per few decades with two A+ detectors to a few per year and potentially allow for the first gravitational-wave observations of supernovae, isolated neutron stars, and other exotica.