While there is a recognised role of optimising lifestyle behaviours such as diet and physical activity in the management of infertility, the best practice for lifestyle management of infertility remains unknown, and factors influencing the lifestyle behaviours of people with infertility are not well understood. The aim of this systematic review is to evaluate the barriers and enablers to a healthy lifestyle in people with infertility, from the perspectives of people with infertility and health professionals, in order to inform optimal behavioural change strategies for lifestyle management of infertility. Ovid MEDLINE(R), PsycINFO, EMBASE, EBM Reviews, and CINAHL Plus were searched from inception to 12th September 2022. Eligible studies were qualitative, quantitative or mixed-methods primary studies which explored barriers and/or enablers to lifestyle for infertility management, from the perspectives of people with infertility and/or health professionals. Two independent reviewers performed quality assessment, using the Centre for Evidence-Based Management Critical Appraisal of a Survey Tool (quantitative and mixed-methods studies) and the Critical Appraisal Skills Programme Qualitative Checklist (qualitative and mixed-methods studies). Data were analysed by inductive thematic analysis with themes mapped to the Capability, Opportunity, Motivation and Behaviour (COM-B) model(1) and Theoretical Domains Framework (TDF)(2). Relevant behaviour change techniques (BCTs)(3) to target the identified enablers and barriers were suggested. After screening 10703 citations and 82 full-texts, 22 studies were included (12 quantitative, 7 mixed-methods and 3 qualitative) with 18 studies including women with infertility (n = 2442), 10 including men with infertility (n = 1372) and 6 including health professionals (n = 261). From the perspectives of people with infertility, themes related to capability (e.g. strategies for behaviour change), opportunity (e.g. limited time, resources and money) and motivation (e.g. interplay between lifestyle and emotional state); themes mapped to 8 TDF domains. From the perspectives of health professionals, themes related to capability (e.g. identification of patients appropriate for lifestyle intervention), opportunity (e.g. mode of delivery) and motivation (e.g. professional responsibility); themes mapped to 6 TDF domains. 34 BCTs were identified across the suggested interventions. This systematic review found that several interacting factors influence lifestyle in people with infertility as well as health professional behaviour with regards to provision of lifestyle interventions for infertility. These factors can be targeted for optimisation of interventions. In light of the limited number of qualitative studies, there is a need for more qualitative research to gain deeper insights into the perspectives of people with infertility and health professionals for further exploration of the complex and interacting factors which shape lifestyle during the fertility journey.

Grain-cooking traditions in Neolithic China have been characterised as a ‘wet’ cuisine based on the boiling and steaming of sticky varieties of cereal. One of these, broomcorn millet, was one of the earliest Chinese crops to move westward into Central Asia and beyond, into regions where grains were typically prepared by grinding and baking. Here, the authors present the genotypes and reconstructed phenotypes of 13 desiccated broomcorn millet samples from Xinjiang (1700 BC–AD 700). The absence in this area of sticky-starch millet and vessels for boiling and steaming suggests that, as they moved west, East Asian cereal crops were decoupled from traditional cooking practices and were incorporated into local cuisines.

Innovations in horse equipment during the early Middle Ages provided advantages to societies from the steppes, reshaping the social landscape of Eurasia. Comparatively little is known about the precise origin of these crucial advances, although the available evidence points to early adoption in East Asia. The authors present new archaeological discoveries from western and northern Mongolia, dating to the fourth and fifth centuries AD, including a wooden frame saddle with horse hide components from Urd Ulaan Uneet and an iron stirrup from Khukh Nuur. Together, these finds suggest that Mongolian groups were early adopters of stirrups and saddles, facilitating the expansion of nomadic hegemony across Eurasia and shaping the conduct of medieval mounted warfare.

In a recent survey of nematodes associated with tobacco in Shandong, China, the root-lesion nematode Pratylenchus coffeae was identified using a combination of morphology and molecular techniques. This nematode species is a serious parasite that damages a variety of plant species. The model plant benthi, Nicotiana benthamiana, is frequently used to study plant-disease interactions. However, it is not known whether this plant species is a host of P. coffeae. The objectives of this study were to evaluate the parasitism and pathogenicity of five populations of the root-lesion nematode P. coffeae on N. benthamiana. N. benthamiana seedlings with the same growth status were chosen and inoculated with 1,000 nematodes per pot. At 60 days after inoculation, the reproductive factors (Rf = final population densities (Pf)/initial population densities (Pi)) for P. coffeae in the rhizosphere of N. benthamiana were all more than 1, suggesting that N. benthamiana was a good host plant for P. coffeae. Nicotiana. benthamiana infected by P. coffeae showed weak growth, decreased tillering, high root reduction, and noticeable brown spots on the roots. Thus, we determined that the model plant N. benthamiana can be used to study plant-P. coffeae interactions.

In recent years, there has been significant momentum in applying deep learning (DL) to machine health monitoring (MHM). It has been widely claimed that DL methodologies are superior to more traditional techniques in this area. This paper aims to investigate this claim by analysing a real-world dataset of helicopter sensor faults provided by Airbus. Specifically, we will address the problem of machine sensor health unsupervised classification. In a 2019 worldwide competition hosted by Airbus, Fujitsu Systems Europe (FSE) won first prize by achieving an F1-score of 93% using a DL model based on generative adversarial networks (GAN). In another comprehensive study, various modified and existing image encoding methods were compared for the convolutional auto-encoder (CAE) model. The best classification result was achieved using the scalogram as the image encoding method, with an F1-score of 91%. In this paper, we use these two studies as benchmarks to compare with basic statistical analysis methods and the one-class supporting vector machine (SVM). Our comparative study demonstrates that while DL-based techniques have great potential, they are not always superior to traditional methods. We therefore recommend that all future published studies of applying DL methods to MHM include appropriately selected traditional reference methods, wherever possible.

With the advent of deep, all-sky radio surveys, the need for ancillary data to make the most of the new, high-quality radio data from surveys like the Evolutionary Map of the Universe (EMU), GaLactic and Extragalactic All-sky Murchison Widefield Array survey eXtended, Very Large Array Sky Survey, and LOFAR Two-metre Sky Survey is growing rapidly. Radio surveys produce significant numbers of Active Galactic Nuclei (AGNs) and have a significantly higher average redshift when compared with optical and infrared all-sky surveys. Thus, traditional methods of estimating redshift are challenged, with spectroscopic surveys not reaching the redshift depth of radio surveys, and AGNs making it difficult for template fitting methods to accurately model the source. Machine Learning (ML) methods have been used, but efforts have typically been directed towards optically selected samples, or samples at significantly lower redshift than expected from upcoming radio surveys. This work compiles and homogenises a radio-selected dataset from both the northern hemisphere (making use of Sloan Digital Sky Survey optical photometry) and southern hemisphere (making use of Dark Energy Survey optical photometry). We then test commonly used ML algorithms such as k-Nearest Neighbours (kNN), Random Forest, ANNz, and GPz on this monolithic radio-selected sample. We show that kNN has the lowest percentage of catastrophic outliers, providing the best match for the majority of science cases in the EMU survey. We note that the wider redshift range of the combined dataset used allows for estimation of sources up to $z = 3$ before random scatter begins to dominate. When binning the data into redshift bins and treating the problem as a classification problem, we are able to correctly identify $\approx$76% of the highest redshift sources—sources at redshift $z > 2.51$—as being in either the highest bin ($z > 2.51$) or second highest ($z = 2.25$).

We investigate the diversity in the sizes and average surface densities of the neutral atomic hydrogen (H i) gas discs in $\sim$280 nearby galaxies detected by the Widefield ASKAP L-band Legacy All-sky Blind Survey (WALLABY). We combine the uniformly observed, interferometric H i data from pilot observations of the Hydra cluster and NGC 4636 group fields with photometry measured from ultraviolet, optical, and near-infrared imaging surveys to investigate the interplay between stellar structure, star formation, and H i structural parameters. We quantify the H i structure by the size of the H i relative to the optical disc and the average H i surface density measured using effective and isodensity radii. For galaxies resolved by $>$$1.3$ beams, we find that galaxies with higher stellar masses and stellar surface densities tend to have less extended H i discs and lower H i surface densities: the isodensity H i structural parameters show a weak negative dependence on stellar mass and stellar mass surface density. These trends strengthen when we limit our sample to galaxies resolved by $>$2 beams. We find that galaxies with higher H i surface densities and more extended H i discs tend to be more star forming: the isodensity H i structural parameters have stronger correlations with star formation. Normalising the H i disc size by the optical effective radius (instead of the isophotal radius) produces positive correlations with stellar masses and stellar surface densities and removes the correlations with star formation. This is due to the effective and isodensity H i radii increasing with mass at similar rates while, in the optical, the effective radius increases slower than the isophotal radius. Our results are in qualitative agreement with previous studies and demonstrate that with WALLABY we can begin to bridge the gap between small galaxy samples with high spatial resolution H i data and large, statistical studies using spatially unresolved, single-dish data.

We present a systematic search for radio counterparts of novae using the Australian Square Kilometer Array Pathfinder (ASKAP). Our search used the Rapid ASKAP Continuum Survey, which covered the entire sky south of declination $+41^{\circ}$ ($\sim$$34000$ square degrees) at a central frequency of 887.5 MHz, the Variables and Slow Transients Pilot Survey, which covered $\sim$$5000$ square degrees per epoch (887.5 MHz), and other ASKAP pilot surveys, which covered $\sim$200–2000 square degrees with 2–12 h integration times. We crossmatched radio sources found in these surveys over a two–year period, from 2019 April to 2021 August, with 440 previously identified optical novae, and found radio counterparts for four novae: V5668 Sgr, V1369 Cen, YZ Ret, and RR Tel. Follow-up observations with the Australian Telescope Compact Array confirm the ejecta thinning across all observed bands with spectral analysis indicative of synchrotron emission in V1369 Cen and YZ Ret. Our light-curve fit with the Hubble Flow model yields a value of $1.65\pm 0.17 \times 10^{-4} \rm \:M_\odot$ for the mass ejected in V1369 Cen. We also derive a peak surface brightness temperature of $250\pm80$ K for YZ Ret. Using Hubble Flow model simulated radio lightcurves for novae, we demonstrate that with a 5$\sigma$ sensitivity limit of 1.5 mJy in 15-min survey observations, we can detect radio emission up to a distance of 4 kpc if ejecta mass is in the range $10^{-3}\rm \:M_\odot$, and upto 1 kpc if ejecta mass is in the range $10^{-5}$–$10^{-3}\rm \:M_\odot$. Our study highlights ASKAP’s ability to contribute to future radio observations for novae within a distance of 1 kpc hosted on white dwarfs with masses $0.4$–$1.25\:\rm M_\odot$, and within a distance of 4 kpc hosted on white dwarfs with masses $0.4$–$1.0\:\rm M_\odot$.

We present the Widefield ASKAP L-band Legacy All-sky Blind surveY (WALLABY) Pilot Phase I Hi kinematic models. This first data release consists of Hi observations of three fields in the direction of the Hydra and Norma clusters, and the NGC 4636 galaxy group. In this paper, we describe how we generate and publicly release flat-disk tilted-ring kinematic models for 109/592 unique Hi detections in these fields. The modelling method adopted here—which we call the WALLABY Kinematic Analysis Proto-Pipeline (WKAPP) and for which the corresponding scripts are also publicly available—consists of combining results from the homogeneous application of the FAT and 3DBarolo algorithms to the subset of 209 detections with sufficient resolution and $S/N$ in order to generate optimised model parameters and uncertainties. The 109 models presented here tend to be gas rich detections resolved by at least 3–4 synthesised beams across their major axes, but there is no obvious environmental bias in the modelling. The data release described here is the first step towards the derivation of similar products for thousands of spatially resolved WALLABY detections via a dedicated kinematic pipeline. Such a large publicly available and homogeneously analysed dataset will be a powerful legacy product that that will enable a wide range of scientific studies.

We present WALLABY pilot data release 1, the first public release of H i pilot survey data from the Wide-field ASKAP L-band Legacy All-sky Blind Survey (WALLABY) on the Australian Square Kilometre Array Pathfinder. Phase 1 of the WALLABY pilot survey targeted three $60\,\mathrm{deg}^{2}$ regions on the sky in the direction of the Hydra and Norma galaxy clusters and the NGC 4636 galaxy group, covering the redshift range of $z \lesssim 0.08$ . The source catalogue, images and spectra of nearly 600 extragalactic H i detections and kinematic models for 109 spatially resolved galaxies are available. As the pilot survey targeted regions containing nearby group and cluster environments, the median redshift of the sample of $z \approx 0.014$ is relatively low compared to the full WALLABY survey. The median galaxy H i mass is $2.3 \times 10^{9}\,{\rm M}_{{\odot}}$ . The target noise level of $1.6\,\mathrm{mJy}$ per 30′′ beam and $18.5\,\mathrm{kHz}$ channel translates into a $5 \sigma$ H i mass sensitivity for point sources of about $5.2 \times 10^{8} \, (D_{\rm L} / \mathrm{100\,Mpc})^{2} \, {\rm M}_{{\odot}}$ across 50 spectral channels ( ${\approx} 200\,\mathrm{km \, s}^{-1}$ ) and a $5 \sigma$ H i column density sensitivity of about $8.6 \times 10^{19} \, (1 + z)^{4}\,\mathrm{cm}^{-2}$ across 5 channels ( ${\approx} 20\,\mathrm{km \, s}^{-1}$ ) for emission filling the 30′′ beam. As expected for a pilot survey, several technical issues and artefacts are still affecting the data quality. Most notably, there are systematic flux errors of up to several 10% caused by uncertainties about the exact size and shape of each of the primary beams as well as the presence of sidelobes due to the finite deconvolution threshold. In addition, artefacts such as residual continuum emission and bandpass ripples have affected some of the data. The pilot survey has been highly successful in uncovering such technical problems, most of which are expected to be addressed and rectified before the start of the full WALLABY survey.