In dairy production, high feed efficiency (FE) is important to reduce feed costs and negative impacts of milk production on the climate and environment, yet little is known about the relationship between FE, eating behaviour and activity. This research communication describes how cows differing in FE, expressed as daily energy corrected milk production per unit of feed intake, differed in eating behaviour and activity. We used data from a study of 253 lactations obtained from 97 Holstein and 91 Jersey cows milked in an automatic milking system. Automated feed troughs recorded feed intake behaviour and cows wore a sensor that recorded activity from 5 to 200 d in milk (DIM). We used a mixed linear model to estimate random solutions for individual cows for traits of steps, lying and eating behaviour and calculated their correlation with FE during four periods (5–35, 36–75, 76–120 and 121–200 DIM). Separate analyses were performed for each breed and period. We found that individual level correlations between FE and behaviour traits were stronger in Jersey than in Holstein cows. Eating rate correlated weakly negatively to FE in Holstein cows and more strongly so in Jersey cows, such that efficient Jerseys were slower eaters. The physical activity of Jersey cows was weakly and negatively correlated to FE, but this was not the case in Holstein cows. We conclude that eating rate was consistently negatively associated with FE throughout lactation for Jersey cows, but not for Holstein cows.

The purpose of this study was to examine possible pathways by which genetic risk associated with externalizing is transmitted in families. We used molecular data to disentangle the genetic and environmental pathways contributing to adolescent externalizing behavior in a sample of 1,111 adolescents (50% female; 719 European and 392 African ancestry) and their parents from the Collaborative Study on the Genetics of Alcoholism. We found evidence for genetic nurture such that parental externalizing polygenic scores were associated with adolescent externalizing behavior, over and above the effect of adolescents’ own externalizing polygenic scores. Mediation analysis indicated that parental externalizing psychopathology partly explained the effect of parental genotype on children’s externalizing behavior. We also found evidence for evocative gene-environment correlation, whereby adolescent externalizing polygenic scores were associated with lower parent–child communication, less parent–child closeness, and lower parental knowledge, controlling for parental genotype. These effects were observed among participants of European ancestry but not African ancestry, likely due to the limited predictive power of polygenic scores across ancestral background. These results demonstrate that in addition to genetic transmission, genes influence offspring behavior through the influence of parental genotypes on their children’s environmental experiences, and the role of children’s genotypes in shaping parent–child relationships.

Biomarkers may be useful endophenotypes for genetic studies if they share genetic sources of variation with the outcome, for example, with all-cause mortality. Australian adult study participants who had reported their parental survival information were included in the study: 14,169 participants had polygenic risk scores (PRS) from genotyping and up to 13,365 had biomarker results. We assessed associations between participants’ biomarker results and parental survival, and between biomarker results and eight parental survival PRS at varying p-value cut-offs. Survival in parents was associated with participants’ serum bilirubin, C-reactive protein, HDL cholesterol, triglycerides and uric acid, and with LDL cholesterol for participants’ fathers but not for their mothers. PRS for all-cause mortality were associated with liver function tests (alkaline phosphatase, butyrylcholinesterase, gamma-glutamyl transferase), metabolic tests (LDL and HDL cholesterol, triglycerides, uric acid), and acute-phase reactants (C-reactive protein, globulins). Association between offspring biomarker results and parental survival demonstrates the existence of familial effects common to both, while associations between biomarker results and PRS for mortality favor at least a partial genetic cause of this covariation. Identification of genetic loci affecting mortality-associated biomarkers offers a route to the identification of additional loci affecting mortality.

Evidence of Late Triassic large tetrapods from the UK is rare. Here, we describe a track-bearing surface located on the shoreline near Penarth, south Wales, United Kingdom. The total exposed surface is c. 50 m long and c. 2 m wide, and is split into northern and southern sections by a small fault. We interpret these impressions as tracks, rather than abiogenic sedimentary structures, because of the possession of marked displacement rims and their relationship to each other with regularly spaced impressions forming putative trackways. The impressions are large (up to c. 50 cm in length), but poorly preserved, and retain little information about track-maker anatomy. We discuss alternative, plausible, abiotic mechanisms that might have been responsible for the formation of these features, but reject them in favour of these impressions being tetrapod tracks. We propose that the site is an additional occurrence of the ichnotaxon Eosauropus, representing a sauropodomorph trackmaker, thereby adding a useful new datum to their sparse Late Triassic record in the UK. We also used historical photogrammetry to digitally map the extent of site erosion during 2009–2020. More than 1 m of the surface exposure has been lost over this 11-year period, and the few tracks present in both models show significant smoothing, breakage and loss of detail. These tracks are an important datapoint for Late Triassic palaeontology in the UK, even if they cannot be confidently assigned to a specific trackmaker. The documented loss of the bedding surface highlights the transient and vulnerable nature of our fossil resources, particularly in coastal settings, and the need to gather data as quickly and effectively as possible.

We present the data and initial results from the first pilot survey of the Evolutionary Map of the Universe (EMU), observed at 944 MHz with the Australian Square Kilometre Array Pathfinder (ASKAP) telescope. The survey covers $270 \,\mathrm{deg}^2$ of an area covered by the Dark Energy Survey, reaching a depth of 25–30 $\mu\mathrm{Jy\ beam}^{-1}$ rms at a spatial resolution of $\sim$ 11–18 arcsec, resulting in a catalogue of $\sim$ 220 000 sources, of which $\sim$ 180 000 are single-component sources. Here we present the catalogue of single-component sources, together with (where available) optical and infrared cross-identifications, classifications, and redshifts. This survey explores a new region of parameter space compared to previous surveys. Specifically, the EMU Pilot Survey has a high density of sources, and also a high sensitivity to low surface brightness emission. These properties result in the detection of types of sources that were rarely seen in or absent from previous surveys. We present some of these new results here.

Vulture populations are in severe decline across Africa and prioritization of geographic areas for their conservation is urgently needed. To do so, we compiled three independent datasets on vulture occurrence from road-surveys, GPS-tracking, and citizen science (eBird), and used maximum entropy to build ensemble species distribution models (SDMs). We then identified spatial vulture conservation priorities in Ethiopia, a stronghold for vultures in Africa, while accounting for uncertainty in our predictions. We were able to build robust distribution models for five vulture species across the entirety of Ethiopia, including three Critically Endangered, one Endangered, and one Near Threatened species. We show that priorities occur in the highlands of Ethiopia, which provide particularly important habitat for Bearded Gypaetus barbatus, Hooded Necrosyrtes monachus, Rüppell’s Gyps rüppelli and White-backed Gyps africanus Vultures, as well as the lowlands of north-eastern Ethiopia, which are particularly valuable for the Egyptian Vulture Neophron percnopterus. One-third of the core distribution of the Egyptian Vulture was protected, followed by the White-backed Vulture at one-sixth, and all other species at one-tenth. Overall, only about one-fifth of vulture priority areas were protected. Given that there is limited protection of priority areas and that vultures range widely, we argue that measures of broad spatial and legislative scope will be necessary to address drivers of vulture declines, including poisoning, energy infrastructure, and climate change, while considering the local social context and aiding sustainable development.

Wavelength-dispersive X-ray (WDX) spectroscopy was used to measure silicon atom concentrations in the range 35–100 ppm [corresponding to (3–9) × 1018 cm−3] in doped AlxGa1–xN films using an electron probe microanalyser also equipped with a cathodoluminescence (CL) spectrometer. Doping with Si is the usual way to produce the n-type conducting layers that are critical in GaN- and AlxGa1–xN-based devices such as LEDs and laser diodes. Previously, we have shown excellent agreement for Mg dopant concentrations in p-GaN measured by WDX with values from the more widely used technique of secondary ion mass spectrometry (SIMS). However, a discrepancy between these methods has been reported when quantifying the n-type dopant, silicon. We identify the cause of discrepancy as inherent sample contamination and propose a way to correct this using a calibration relation. This new approach, using a method combining data derived from SIMS measurements on both GaN and AlxGa1–xN samples, provides the means to measure the Si content in these samples with account taken of variations in the ZAF corrections. This method presents a cost-effective and time-saving way to measure the Si doping and can also benefit from simultaneously measuring other signals, such as CL and electron channeling contrast imaging.

The first demonstration of laser action in ruby was made in 1960 by T. H. Maiman of Hughes Research Laboratories, USA. Many laboratories worldwide began the search for lasers using different materials, operating at different wavelengths. In the UK, academia, industry and the central laboratories took up the challenge from the earliest days to develop these systems for a broad range of applications. This historical review looks at the contribution the UK has made to the advancement of the technology, the development of systems and components and their exploitation over the last 60 years.

Mortality risk is known to be associated with many physiological or biochemical risk factors, and polygenic risk scores (PRSs) may offer an additional or alternative approach to risk stratification. We have compared the predictive value of common biochemical tests, PRSs and information on parental survival in a cohort of twins and their families. Common biochemical test results were available for up to 13,365 apparently healthy men and women, aged 17−93 years (mean 49.0, standard deviation [SD] 13.7) at blood collection. PRSs for longevity were available for 14,169 study participants and reported parental survival for 25,784 participants. A search for information on date and cause of death was conducted through the Australian National Death Index, with median follow-up of 11.3 years. Cox regression was used to evaluate associations with mortality from all causes, cancers, cardiovascular diseases and other causes. Linear relationships with all-cause mortality were strongest for C-reactive protein, gamma-glutamyl transferase, glucose and alkaline phosphatase, with hazard ratios (HRs) of 1.16 (95% CI [1.07, 1.24]), 1.15 (95% CI 1.04–1.21), 1.13 (95% CI [1.08, 1.19]) and 1.11 (95% CI [1.05, 1.88]) per SD difference, respectively. Significant nonlinear effects were found for urea, uric acid and butyrylcholinesterase. Lipid risk factors were not statistically significant for mortality in our cohort. Family history and PRS showed weaker but significant associations with survival, with HR in the range 1.05 to 1.09 per SD difference. In conclusion, biochemical tests currently predict long-term mortality more strongly than genetic scores based on genotyping or on reported parental survival.