2DV modelling of sediment transport processes over full-scale ripples in regular asymmetric oscillatory flow

Wave-induced, steep vortex ripples are ubiquitous features in shallow coastal seas and it is therefore important to fully understand and model the sediment transport processes that occur over them. To this end, two two-dimensional vertical (2DV) models have been critically tested against detailed velocity and sediment concentration measurements above mobile ripples in regular asymmetric oscillatory flow. The two models are a k–ω turbulence-closure model and a discrete-vortex, particle-tracking (DVPT) model, while the data are obtained in the Aberdeen oscillatory flow tunnel (AOFT). The models and the data demonstrate that the time-dependent velocity and suspended sediment concentration above the ripple are dominated by the generation of lee-side vortices and their subsequent ejection at flow reversal. The DVPT model predicts the positions and strengths of the vortices reasonably well, but tends to overpredict the velocity close to the ripple surface. The k–ω model, on the other hand, underpredicts the height to which the vortices are lifted, but is better able to predict the velocity close to the bed. In terms of the cycle- and ripple-averaged horizontal velocity, both models are able to reproduce the observed offshore flow close to and below the ripple crest and the DVPT model is able to produce the onshore flow higher up. In the vicinity of the vortices, the DVPT model better represents the concentration (because of its better prediction of vorticity). The k–ω model, on the other hand, better represents the concentration close to the ripple surface and higher up in the flow (because of the better representation of the near-bed flow and background turbulence). The measured and predicted cycle- and ripple-averaged suspended sediment concentrations are in reasonable agreement and demonstrate the expected region of exponential decay. The models are able to reproduce the observed offshore cycle- and ripple-averaged suspended sediment flux from the ripple troughs upwards, and as a result, produce net offshore suspended sediment transport rates that are in reasonable agreement. The net measured offshore suspended transport rate, based on the integration of fluxes, was found to be consistent with the total net offshore transport measured in the tunnel as a whole once the onshore transport resulting from ripple migration was taken into account, as would be expected. This demonstrates the importance of models being able to predict ripple-migration rates. However, at present neither of the models is able to do so

Numerical model of swash motion and air entrapment within coarse-grained beaches

Copyright 2012 Elsevier B.V., All rights reserved.Peer reviewedPublisher PD

Simultaneous X-ray/optical observations of GX 9+9 (4U 1728-16)

We report on the results of the first simultaneous X-ray (RXTE) and optical (SAAO) observations of the luminous low mass X-ray binary (LMXB) GX 9+9 in 1999 August. The high-speed optical photometry revealed an orbital period of 4.1958 hr and confirmed previous observations, but with greater precision. No X-ray modulation was found at the orbital period. On shorter timescales, a possible 1.4-hr variability was found in the optical light curves which might be related to the mHz quasi-periodic oscillations seen in other LMXBs. We do not find any significant X-ray/optical correlation in the light curves. In X-rays, the colour-colour diagram and hardness-intensity diagram indicate that the source shows characteristics of an atoll source in the upper banana state, with a correlation between intensity and spectral hardness. Time-resolved X-ray spectroscopy suggests that two-component spectral models give a reasonable fit to the X-ray emission. Such models consist of a blackbody component which can be interpreted as the emission from an optically thick accretion disc or an optically thick boundary layer, and a hard Comptonized component for an extended corona.Comment: 19 pages, 13 figures; accepted for publication in MNRA

Subsurface processes generated by bore-driven swash on coarse-grained beaches

Peer reviewedPublisher PD

Biochar Carbon stability in some contrasting soils from Australia

Climate change is one of the biggest challenges facing the world. The largest contributor to climate change is the greenhouse gas CO2, which is released through anthropogenic activities such as burning of fossil fuel and agricultural waste. To find solutions to mitigate climate change, research has been proposed to reduce greenhouse gas emissions or off-setting emissions through carbon (C) sequestration in soil − the largest C pool of terrestrial ecosystems. In this context, long-term C storage through biochar application to agricultural soils has been becoming a priority area of research in the last two decades

Fatal encephalitis due to the scuticociliate Uronema nigricans in sea-caged, southern bluefin tuna Thunnus maccoyii

A syndrome characterized by atypical swimming behaviour followed by rapid death was first reported in captive southern bluefin tuna Thunnus maccoyii (Castelnau) in the winter of 1993. The cause of this behaviour was found to be a parasitic encephalitis due to the scuticociliate Uronema nigricans (Mueller). Based on parasitological and histological findings, it is proposed that the parasites initially colonise the olfactory rosettes and then ascend the olfactory nerves to eventually invade the brain. Possible epidemiological factors involved in the pathogenesis of the disease include water temperature (>18 degrees C) and the immune status of the fish

Continuous patient state attention models

Irregular time-series (ITS) are prevalent in the electronic health records (EHR) as the data is recorded in EHR system as per the clinical guidelines/requirements but not for research and also depends on the patient health status. ITS present challenges in training of machine learning algorithms, which are mostly built on assumption of coherent fixed dimensional feature space. In this paper, we propose a computationally efficient variant of the transformer based on the idea of cross-attention, called Perceiver, for time-series in healthcare. We further develop continuous patient state attention models, using the Perceiver and the transformer to deal with ITS in EHR. The continuous patient state models utilise neural ordinary differential equations to learn the patient health dynamics, i.e., patient health trajectory from the observed irregular time-steps, which enables them to sample any number of time-steps at any time. The performance of the proposed models is evaluated on in-hospital-mortality prediction task on Physionet-2012 challenge and MIMIC-III datasets. The Perceiver model significantly outperforms the baselines and reduces the computational complexity, as compared with the transformer model, without significant loss of performance. The carefully designed experiments to study irregularity in healthcare also show that the continuous patient state models outperform the baselines. The code is publicly released and verified at https://codeocean.com/capsule/4587224