The role of finance in the decision-making of higher education applicants and students: findings from the Going into Higher Education Research study (BIS Research Paper No.9)

"This report summarises findings from the Going into HE research project. From the outset, the aim has been to develop a clear understanding of: the role and importance of finance in the decision-making process of English-domiciled people from different groups who are considering entering full-time Higher Education (HE) in the UK; and the impact of the support arrangements on their decisions. When taken alongside quantitative studies on HE participation and student finances, also published by DIUS/BIS, the qualitative research presented here contributes to an overall assessment of current student finance arrangements and should help to inform future developments." - exec. summary

Modelling hydrological performance of a bauxite residue profile for deposition management of a storage facility

Accurate scheduling of bauxite residue (red mud) deposition time is required in order to prevent the risk of storage facility failure. This study was conducted to precisely determine the hydraulic parameters of bauxite residue and investigate the capability of HYDRUS to accurately estimate the residue moisture profile and the timing for its deposition. The hydraulic properties of the bauxite residue profile were determined by solving an inverse problem. A one-dimensional hydrological model (HYDRUS-1D) was validated using a 300 mm long column filled with bauxite residue and exposed to a dynamic lower boundary condition. After numerical validation, the model was used to simulate the moisture profile of bauxite residue under the climatic conditions of an alumina refinery site in Queensland, Australia, as well as other scenarios (i.e., high (300 mm) and small (1.7 mm) rainfall events of the site). This study showed that the HYDRUS model can be used as a predictive tool to precisely estimate the moisture profile of the bauxite residue and that the timing for the re-deposition of the bauxite residue can be estimated by understanding the moisture profile and desired shear strength of the residue. This study revealed that the examined bauxite residue approaches field capacity (water potential-10 kPa) after three days from a low rainfall event (<1.7 mm) and after eight days from an intense rainfall event (300 mm) at the time of disposal. This suggests that the bauxite residue can be deposited every four days after low rainfall events (as low as 1.7 mm) and every nine days after high rainfall events (as high as 300 mm) at the time of deposition, if bauxite residue experiences an initial drying period following deposition. © 2020 by the authors

Incoherent light in tapered graded-index fibre: a study of transmission and modal noise

© 2022 The Authors. Published by Elsevier Inc. This is an open access article under the CC BY license, http://creativecommons.org/licenses/by/4.0/We investigated the impact of taper length on light transmission through tapered graded-index fibres. We tested commercial fibres from Thorlabs and a custom graded-index fibre using both coherent and incoherent light sources. Our experimental results show optimum performance for taper transition lengths of 25 mm, although our simulations suggest further improvement may be possible for even shorter transition lengths. We also measured the modal noise power fluctuations caused by bending the fibre. Here, we observe that the custom fibre tapers have the highest transmission but suffer from the most modal noise. Accordingly, we find that the commercial graded-index fibre tapers promise practical usage as a beam mode-field converter, as they have lower power fluctuations but retain relatively high transmission if compared to commercial small core step-index fibre.Peer reviewe

Mitigating Modal Noise in Multimode Circular Fibres by Optical Agitation using a Galvanometer

© 2024 The Author(s). Published by Oxford University Press on behalf of Royal Astronomical Society. This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY), https://creativecommons.org/licenses/by/4.0/Modal noise appears due to the non-uniform and unstable distribution of light intensity among the finite number of modes in multimode fibres. It is an important limiting factor in measuring radial velocity precisely by fibre-fed high-resolution spectrographs. The problem can become particularly severe as the fibre's core become smaller and the number of modes that can propagate reduces. Thus, mitigating modal noise in relatively small core fibres still remains a challenge. We present here a novel technique to suppress modal noise. Two movable mirrors in the form of a galvanometer reimage the mode-pattern of an input fibre to an output fibre. The mixing of modes coupled to the output fibre can be controlled by the movement of mirrors applying two sinusoidal signals through a voltage generator. We test the technique for four multimode circular fibres: 10 and 50 micron step-index, 50 micron graded-index, and a combination of 50 micron graded-index and 5:1 tapered fibres (GI50t). We present the results of mode suppression both in terms of the direct image of the output fibre and spectrum of white light obtained with the high-resolution spectrograph. We found that the galvanometer mitigated modal noise in all the tested fibres, but was most useful for smaller core fibres. However, there is a trade-off between the modal noise reduction and light-loss. The GI50t provides the best result with about 60% mitigation of modal noise at a cost of about 5% output light-loss. Our solution is easy to use and can be implemented in fibre-fed spectrographs.Peer reviewe

Magneto-electrical subbands of freely suspended quantum point contacts

We present a versatile design of freely suspended quantum point contacts with particular large one-dimensional subband quantization energies of up to 10meV. The nanoscale bridges embedding a two-dimensional electron system are fabricated from AlGaAs/GaAs heterostructures by electron-beam lithography and etching techniques. Narrow constrictions define quantum point contacts that are capacitively controlled via local in-plane side gates. Employing transport spectroscopy, we investigate the transition from electrostatic subbands to Landau-quantization in a perpendicular magnetic field. The large subband quantization energies allow us to utilize a wide magnetic field range and thereby observe a large exchange splitted spin-gap of the two lowest Landau-levels

Acetonitrile cluster solvation in a cryogenic ethane-methane-propane liquid: Implications for Titan lake chemistry

The atmosphere of Titan, Saturn’s largest moon, exhibits interesting UV- and radiation-driven chemistry between nitrogen and methane, resulting in dipolar, nitrile-containing molecules. The assembly and subsequent solvation of such molecules in the alkane lakes and seas found on the moon’s surface are of particular interest for investigating the possibility of prebiotic chemistry in Titan’s hydrophobic seas. Here we characterize the solvation of acetonitrile, a product of Titan’s atmospheric radiation chemistry tentatively detected on Titan’s surface [H. B. Niemann et al., Nature 438, 779–784 (2005)], in an alkane mixture estimated to match a postulated composition of the smaller lakes during cycles of active drying and rewetting. Molecular dynamics simulations are employed to determine the potential of mean force of acetonitrile (CH_3CN) clusters moving from the alkane vapor into the bulk liquid. We find that the clusters prefer the alkane liquid to the vapor and do not dissociate in the bulk liquid. This opens up the possibility that acetonitrile-based microscopic polar chemistry may be possible in the otherwise nonpolar Titan lakes

Graph Neural Networks for Particle Reconstruction in High Energy Physics detectors

Pattern recognition problems in high energy physics are notably different from traditional machine learning applications in computer vision. Reconstruction algorithms identify and measure the kinematic properties of particles produced in high energy collisions and recorded with complex detector systems. Two critical applications are the reconstruction of charged particle trajectories in tracking detectors and the reconstruction of particle showers in calorimeters. These two problems have unique challenges and characteristics, but both have high dimensionality, high degree of sparsity, and complex geometric layouts. Graph Neural Networks (GNNs) are a relatively new class of deep learning architectures which can deal with such data effectively, allowing scientists to incorporate domain knowledge in a graph structure and learn powerful representations leveraging that structure to identify patterns of interest. In this work we demonstrate the applicability of GNNs to these two diverse particle reconstruction problems

Graph Neural Networks for Particle Reconstruction in High Energy Physics detectors

Pattern recognition problems in high energy physics are notably different from traditional machine learning applications in computer vision. Reconstruction algorithms identify and measure the kinematic properties of particles produced in high energy collisions and recorded with complex detector systems. Two critical applications are the reconstruction of charged particle trajectories in tracking detectors and the reconstruction of particle showers in calorimeters. These two problems have unique challenges and characteristics, but both have high dimensionality, high degree of sparsity, and complex geometric layouts. Graph Neural Networks (GNNs) are a relatively new class of deep learning architectures which can deal with such data effectively, allowing scientists to incorporate domain knowledge in a graph structure and learn powerful representations leveraging that structure to identify patterns of interest. In this work we demonstrate the applicability of GNNs to these two diverse particle reconstruction problems.Comment: Presented at NeurIPS 2019 Workshop "Machine Learning and the Physical Sciences