Food production and consumption need to substantially change to meet global environmental and public health goals. Increasing grain legume consumption in most countries is key to providing nourishing food for all while contributing to cropping system sustainability with relatively low environmental impact. But what actions have the potential to increase such consumption? The wide knowledge of how to cultivate grain legumes among Swedish farmers, low current consumption in most of the population, and prior shifts in dietary patterns make Sweden an interesting context for studying the potential increase of grain legumes in diets. We identify system-level actions in peer-reviewed and grey literature with the potential to increase grain legume consumption and apply the leverage points framework to evaluate the transformative potential of these actions for the food system in Sweden. Our findings show that most actions suggested in the literature so far focus on increased production, while fewer suggestions integrate production and consumption. Few actions address the deeper leverage points with most transformative potential compared with those with less transformative potential. We qualitatively analyze the actions and develop a chain of leverage illustrating how several actions together could be combined to support change at the deepest leverage point, creating social norms for the consumption of healthy foods. The chain includes developing new tools, facilities and products; changing standards; building feedback loops; changing the food environment; building new information flows between actors; and reforming the value chain. To implement the actions identified in this analysis, a range of value chain actors and supportive policies at the national and European Union levels will be needed.

The global increase in observed forest dieback, characterized by the death of tree foliage, heralds widespread decline in forest ecosystems. This degradation causes significant changes to ecosystem services and functions, including habitat provision and carbon sequestration, which can be difficult to detect using traditional monitoring techniques, highlighting the need for large-scale and high-frequency monitoring. Contemporary developments in the instruments and methods to gather and process data at large scales mean this monitoring is now possible. In particular, the advancement of low-cost drone technology and deep learning on consumer-level hardware provide new opportunities. Here, we use an approach based on deep learning and vegetation indices to assess crown dieback from RGB aerial data without the need for expensive instrumentation such as LiDAR. We use an iterative approach to match crown footprints predicted by deep learning with field-based inventory data from a Mediterranean ecosystem exhibiting drought-induced dieback, and compare expert field-based crown dieback estimation with vegetation index-based estimates. We obtain high overall segmentation accuracy (mAP: 0.519) without the need for additional technical development of the underlying Mask R-CNN model, underscoring the potential of these approaches for non-expert use and proving their applicability to real-world conservation. We also find that color-coordinate based estimates of dieback correlate well with expert field-based estimation. Substituting ground truth for Mask R-CNN model predictions showed negligible impact on dieback estimates, indicating robustness. Our findings demonstrate the potential of automated data collection and processing, including the application of deep learning, to improve the coverage, speed, and cost of forest dieback monitoring.

The maintenance of head-only minimum stunning currents for sheep to ≥ 1.0 Amp as per current legislation was examined in two trials in a commercial abattoir. In the first trial, a Jetco MS100 stunner failed to maintain the current to > 1.0 Amp in 118 of the 228 sheep. In a second trial, a Jetco MS105 delivered sufficient current in all sheep (n = 275) to meet the legislative requirement, apart from a single animal. Recorded electrocardiograms showed a regular heartbeat, with no evidence of ventricular fibrillation, in all animals in both trials following stunning and neck-cut. Only one of the two stun units may therefore be considered to meet the statutory requirements but both may meet the requirements for halal slaughter where pre-stun is considered acceptable.

Laboratory animals need to be monitored to check the status of their health and welfare. Routine checks of laboratory fish are limited to visual observations of physical appearance and behaviour, but for species held in opaque-walled tanks, such checks are compromised by restricted views, poor visibility and provoked behaviour. Here, we report our experience of using in-tank underwater cameras to monitor laboratory populations of salmoniforme, perciforme and cypriniforme fish. A range of cameras and lenses were investigated and trialled. A standard VGA resolution analogue camera with a one-third-inch chip and 3.6-mm lens was selected based on size, picture quality, the proportion of tank in view and cost. A shell for the camera and mounting system were designed to minimise size and cleaning and enable flexible positioning within tanks. Cameras were connected via digital encoders to a server, making video available to the general computer network. Data collected from recordings of rainbow trout (Oncorhynchus mykiss) confirmed provoked behaviour, ie a change in distribution and increase in activity in response to direct viewing and feeding. The networked cameras therefore enable remote viewing of undisturbed behaviour in real time, providing clear, lateral views unaffected by water surface effects, and facilitate increased frequency of checking. Case studies illustrate how camera monitoring can aid detection of abnormalities in behaviour (eg lack of feeding, posture, swimming) and appearance (eg clinical signs, such as lesions), enabling earlier interventions. Furthermore, recordings provide a resource for reference and retrospective analysis, and evidence to support severity classification and identify humane end-points.

The redshifted cosmological 21-cm signal emitted by neutral hydrogen during the first billion years of the universe is much fainter relative to other galactic and extragalactic radio emissions, posing a great challenge towards detection of the signal. Therefore, precise instrumental calibration is a vital prerequisite for the success of radio interferometers such as the Murchison Widefield Array (MWA), which aim for a 21-cm detection. Over the previous years, novel calibration techniques targeting the power spectrum paradigm of EoR science have been actively researched and where possible implemented. Some of these improvements, for the MWA, include the accuracy of sky models used in calibration and the treatment of ionospheric effects, both of which introduce unwanted contamination to the EoR window. Despite sophisticated non-traditional calibration algorithms being continuously developed over the years to incorporate these methods, the large datasets needed for EoR measurements require high computational costs, leading to trade-offs that impede making use of these new tools to maximum benefit. Using recently acquired computation resources for the MWA, we test the full capabilities of the state-of-the-art calibration techniques available for the MWA EoR project, with a focus on both direction-dependent and direction-independent calibration. Specifically, we investigate improvements that can be made in the vital calibration stages of sky modelling, ionospheric correction, and compact source foreground subtraction as applied in the hybrid foreground mitigation approach (one that combines both foreground subtraction and avoidance). Additionally, we investigate a method of ionospheric correction using interpolated ionospheric phase screens and assess its performance in the power spectrum space. Overall, we identify a refined RTS calibration configuration that leads to an at least 2 factor reduction of the EoR window power contamination at the $0.1 \; \textrm{hMpc}^{-1}$ scale. The improvement marks a step further towards detecting the 21-cm signal using the MWA and the forthcoming SKA low telescope.

One of the principal systematic constraints on the Epoch of Reionisation (EoR) experiment is the accuracy of the foreground calibration model. Recent results have shown that highly accurate models of extended foreground sources, and including models for sources in both the primary beam and its sidelobes, are necessary for reducing foreground power. To improve the accuracy of the source models for the EoR fields observed by the Murchison Widefield Array (MWA), we conducted the MWA Long Baseline Epoch of Reionisation Survey (LoBES). This survey consists of multi-frequency observations of the main MWA EoR fields and their eight neighbouring fields using the MWA Phase II extended array. We present the results of the first half of this survey centred on the MWA EoR0 observing field (centred at RA (J2000) $0^\mathrm{h}$ , Dec (J2000) $-27^{\circ}$ ). This half of the survey covers an area of 3 069 degrees $^2$ , with an average rms of 2.1 mJy beam–1. The resulting catalogue contains a total of 80 824 sources, with 16 separate spectral measurements between 100 and 230 MHz, and spectral modelling for 78 $\%$ of these sources. Over this region we estimate that the catalogue is 90 $\%$ complete at 32 mJy, and 70 $\%$ complete at 10.5 mJy. The overall normalised source counts are found to be in good agreement with previous low-frequency surveys at similar sensitivities. Testing the performance of the new source models we measure lower residual rms values for peeled sources, particularly for extended sources, in a set of MWA Phase I data. The 2-dimensional power spectrum of these data residuals also show improvement on small angular scales—consistent with the better angular resolution of the LoBES catalogue. It is clear that the LoBES sky models improve upon the current sky model used by the Australian MWA EoR group for the EoR0 field.

The Epoch of Reionisation (EoR) is the period within which the neutral universe transitioned to an ionised one. This period remains unobserved using low-frequency radio interferometers, which target the 21 cm signal of neutral hydrogen emitted in this era. The Murchison Widefield Array (MWA) radio telescope was built with the detection of this signal as one of its major science goals. One of the most significant challenges towards a successful detection is that of calibration, especially in the presence of the Earth’s ionosphere. By introducing refractive source shifts, distorting source shapes, and scintillating flux densities, the ionosphere is a major nuisance in low-frequency radio astronomy. We introduce sivio, a software tool developed for simulating observations of the MWA through different ionospheric conditions, which is estimated using thin screen approximation models and propagated into the visibilities. This enables us to directly assess the impact of the ionosphere on observed EoR data and the resulting power spectra. We show that the simulated data captures the dispersive behaviour of ionospheric effects. We show that the spatial structure of the simulated ionospheric media is accurately reconstructed either from the resultant source positional offsets or from parameters evaluated during the data calibration procedure. In turn, this will inform on the best strategies of identifying and efficiently eliminating ionospheric contamination in EoR data moving into the Square Kilometre Array era.

Homo sapiens is currently living in serious disharmony with the rest of the natural world. For our species to survive, and for our well-being, we must gather knowledge from multiple perspectives and actively engage in studies of planetary health. The enormous diversity of species, one of the most striking aspects of life on our planet, provides a source of solutions that have been developed through evolution by natural selection by animals living in extreme environments. The food system is central to finding solutions; our current global eating patterns have a negative impact on human health, driven climate change and loss of biodiversity. We propose that the use of solutions derived from nature, an approach termed biomimetics, could mitigate the effects of a changing climate on planetary health as well as human health. For example, activation of the transcription factor Nrf2 may play a role in protecting animals living in extreme environments, or animals exposed to heat stress, pollution and pesticides. In order to meet these challenges, we call for the creation of novel interdisciplinary planetary health research teams.

Precise instrumental calibration is of crucial importance to 21-cm cosmology experiments. The Murchison Widefield Array’s (MWA) Phase II compact configuration offers us opportunities for both redundant calibration and sky-based calibration algorithms; using the two in tandem is a potential approach to mitigate calibration errors caused by inaccurate sky models. The MWA Epoch of Reionization (EoR) experiment targets three patches of the sky (dubbed EoR0, EoR1, and EoR2) with deep observations. Previous work in Li et al. (2018) and (2019) studied the effect of tandem calibration on the EoR0 field and found that it yielded no significant improvement in the power spectrum (PS) over sky-based calibration alone. In this work, we apply similar techniques to the EoR1 field and find a distinct result: the improvements in the PS from tandem calibration are significant. To understand this result, we analyse both the calibration solutions themselves and the effects on the PS over three nights of EoR1 observations. We conclude that the presence of the bright radio galaxy Fornax A in EoR1 degrades the performance of sky-based calibration, which in turn enables redundant calibration to have a larger impact. These results suggest that redundant calibration can indeed mitigate some level of model incompleteness error.

Diffuse, non-thermal emission in galaxy clusters is increasingly being detected in low-frequency radio surveys and images. We present a new diffuse, steep-spectrum, non-thermal radio source within the cluster Abell 1127 found in survey data from the Murchison Widefield Array (MWA). We perform follow-up observations with the ‘extended’ configuration MWA Phase II with improved resolution to better resolve the source and measure its low-frequency spectral properties. We use archival Very Large Array S-band data to remove the discrete source contribution from the MWA data, and from a power law model fit we find a spectral index of –1.83±0.29 broadly consistent with relic-type sources. The source is revealed by the Giant Metrewave Radio Telescope at 150 MHz to have an elongated morphology, with a projected linear size of 850 kpc as measured in the MWA data. Using Chandra observations, we derive morphological estimators and confirm quantitatively that the cluster is in a disturbed dynamical state, consistent with the majority of phoenices and relics being hosted by merging clusters. We discuss the implications of relying on morphology and low-resolution imaging alone for the classification of such sources and highlight the usefulness of the MHz to GHz radio spectrum in classifying these types of emission. Finally, we discuss the benefits and limitations of using the MWA Phase II in conjunction with other instruments for detailed studies of diffuse, steep-spectrum, non-thermal radio emission within galaxy clusters.

To make a power spectrum (PS) detection of the 21-cm signal from the Epoch of Reionisation (EoR), one must avoid/subtract bright foreground sources. Sources such as Fornax A present a modelling challenge due to spatial structures spanning from arc seconds up to a degree. We compare modelling with multi-scale (MS) CLEAN components to ‘shapelets’, an alternative set of basis functions. We introduce a new image-based shapelet modelling package, SHAMFI. We also introduce a new CUDA simulation code (WODEN) to generate point source, Gaussian, and shapelet components into visibilities. We test performance by modelling a simulation of Fornax A, peeling the model from simulated visibilities, and producing a residual PS. We find the shapelet method consistently subtracts large-angular-scale emission well, even when the angular resolution of the data is changed. We find that when increasing the angular resolution of the data, the MS CLEAN model worsens at large angular scales. When testing on real Murchison Widefield Array data, the expected improvement is not seen in real data because of the other dominating systematics still present. Through further simulation, we find the expected differences to be lower than obtainable through current processing pipelines. We conclude shapelets are worthwhile for subtracting extended galaxies, and may prove essential for an EoR detection in the future, once other systematics have been addressed.

We apply two methods to estimate the 21-cm bispectrum from data taken within the Epoch of Reionisation (EoR) project of the Murchison Widefield Array (MWA). Using data acquired with the Phase II compact array allows a direct bispectrum estimate to be undertaken on the multiple redundantly spaced triangles of antenna tiles, as well as an estimate based on data gridded to the uv-plane. The direct and gridded bispectrum estimators are applied to 21 h of high-band (167–197 MHz; z = 6.2–7.5) data from the 2016 and 2017 observing seasons. Analytic predictions for the bispectrum bias and variance for point-source foregrounds are derived. We compare the output of these approaches, the foreground contribution to the signal, and future prospects for measuring the bispectra with redundant and non-redundant arrays. We find that some triangle configurations yield bispectrum estimates that are consistent with the expected noise level after 10 h, while equilateral configurations are strongly foreground-dominated. Careful choice of triangle configurations may be made to reduce foreground bias that hinders power spectrum estimators, and the 21-cm bispectrum may be accessible in less time than the 21-cm power spectrum for some wave modes, with detections in hundreds of hours.

Chronic inflammation is associated with disease risk and mortality in the general population. Soluble urokinase plasminogen activator receptor (suPAR) is a stable marker of chronic inflammation, and a higher serum-concentration of suPAR is found in individuals with an unhealthy lifestyle such as smoking. This article investigates the association between suPAR and dietary quality measured with the dietary quality score (DQS). The DQS is an index of the overall quality of an individual’s dietary habits assessed through a self-administered FFQ. Furthermore, this article investigates the association of both suPAR and the DQS with CVD risk and mortality in the general Danish population. We analysed 5347 individuals aged 30–60 years from the Danish Inter99 study cohort. Multiple linear regression analyses showed a linear inverse association between the DQS and suPAR (P=0·0005). Cox regression analyses showed an 18 (95 % CI 9, 26) % increase in the risk of death from any cause with each 1 ng/ml increase in suPAR. We found no significant association between the DQS and the mortality (hazard ratio: 1·16, 95 % CI 0·79, 1·69). All analyses were adjusted for demographics and lifestyle factors. The association between the DQS and suPAR on the one hand and suPAR and mortality on the other supports the argument that low dietary quality may constitute a health risk through its influence on chronic inflammation. Future research should examine whether suPAR is modifiable through changes in dietary habits.

We provide the first in situ measurements of antenna element beam shapes of the Murchison Widefield Array. Most current processing pipelines use an assumed beam shape, which can cause absolute and relative flux density errors and polarisation ‘leakage’. Understanding the primary beam is then of paramount importance, especially for sensitive experiments such as a measurement of the 21-cm line from the epoch of reionisation, where the calibration requirements are so extreme that tile to tile beam variations may affect our ability to make a detection. Measuring the primary beam shape from visibilities is challenging, as multiple instrumental, atmospheric, and astrophysical factors contribute to uncertainties in the data. Building on the methods of Neben et al. [Radio Sci., 50, 614], we tap directly into the receiving elements of the telescope before any digitisation or correlation of the signal. Using ORBCOMM satellite passes we are able to produce all-sky maps for four separate tiles in the XX polarisation. We find good agreement with the beam model of Sokolowski et al. [2017, PASA, 34, e062], and clearly observe the effects of a missing dipole from a tile in one of our beam maps. We end by motivating and outlining additional on-site experiments.

Understanding provider perceptions of antimicrobial use (AU) feedback is important for optimal implementation. A survey addressing AU attribution scenarios, feedback methods, and implementation barriers was distributed to inpatient providers. As AU scenarios became more complex, disagreement regarding AU attribution arose. All providers were highly concerned about barriers to AU reporting.

The current generation of experiments aiming to detect the neutral hydrogen signal from the Epoch of Reionisation (EoR) is likely to be limited by systematic effects associated with removing foreground sources from target fields. In this paper, we develop a model for the compact foreground sources in one of the target fields of the MWA’s EoR key science experiment: the ‘EoR1’ field. The model is based on both the MWA’s GLEAM survey and GMRT 150 MHz data from the TGSS survey, the latter providing higher angular resolution and better astrometric accuracy for compact sources than is available from the MWA alone. The model contains 5 049 sources, some of which have complicated morphology in MWA data, Fornax A being the most complex. The higher resolution data show that 13% of sources that appear point-like to the MWA have complicated morphology such as double and quad structure, with a typical separation of 33 arcsec. We derive an analytic expression for the error introduced into the EoR two-dimensional power spectrum due to peeling close double sources as single point sources and show that for the measured source properties, the error in the power spectrum is confined to high k⊥ modes that do not affect the overall result for the large-scale cosmological signal of interest. The brightest 10 mis-modelled sources in the field contribute 90% of the power bias in the data, suggesting that it is most critical to improve the models of the brightest sources. With this hybrid model, we reprocess data from the EoR1 field and show a maximum of 8% improved calibration accuracy and a factor of two reduction in residual power in k-space from peeling these sources. Implications for future EoR experiments including the SKA are discussed in relation to the improvements obtained.