This study investigated sex differences in Fe status, and associations between Fe status and endurance and musculoskeletal outcomes, in military training. In total, 2277 British Army trainees (581 women) participated. Fe markers and endurance performance (2·4 km run) were measured at the start (week 1) and end (week 13) of training. Whole-body areal body mineral density (aBMD) and markers of bone metabolism were measured at week 1. Injuries during training were recorded. Training decreased Hb in men and women (mean change (–0·1 (95 % CI –0·2, –0·0) and –0·7 (95 % CI –0·9, –0·6) g/dl, both P < 0·001) but more so in women (P < 0·001). Ferritin decreased in men and women (–27 (95 % CI –28, –23) and –5 (95 % CI –8, –1) µg/l, both P ≤ 0·001) but more so in men (P < 0·001). Soluble transferrin receptor increased in men and women (2·9 (95 % CI 2·3, 3·6) and 3·8 (95 % CI 2·7, 4·9) nmol/l, both P < 0·001), with no difference between sexes (P = 0·872). Erythrocyte distribution width increased in men (0·3 (95 % CI 0·2, 0·4)%, P < 0·001) but not in women (0·1 (95 % CI –0·1, 0·2)%, P = 0·956). Mean corpuscular volume decreased in men (–1·5 (95 % CI –1·8, –1·1) fL, P < 0·001) but not in women (0·4 (95 % CI –0·4, 1·3) fL, P = 0·087). Lower ferritin was associated with slower 2·4 km run time (P = 0·018), sustaining a lower limb overuse injury (P = 0·048), lower aBMD (P = 0·021) and higher beta C-telopeptide cross-links of type 1 collagen and procollagen type 1 N-terminal propeptide (both P < 0·001) controlling for sex. Improving Fe stores before training may protect Hb in women and improve endurance and protect against injury.

Laser-plasma instabilities (LPI) play a detrimental role in energy coupling to the target in inertial confinement fusion (ICF). The recent development of applied strong magnetic fields for use in ICF and laboratory astrophysics experiments has opened opportunities to investigate the role of external magnetic fields on LPIs. Recent numerical studies have shown that stimulated Raman scattering (SRS) can be mitigated by external magnetic fields in the kinetic regime of the instability and warrant systematic experimental studies to validate modelling. To this end, we design experiments at the OMEGA-EP laser facility to investigate the effect of an external perpendicular $B$-field of 5–30 T on the backscattered light spectrum from a gas-jet target. We present measurements from a proof-of-principle experiment, where the backward-SRS (BSRS) is in the kinetic regime, for which the magnetization is expected to produce the greatest effects on instability growth. New simulations motivated by this experiment are used to inform the proposal of an upgraded experimental design. Our simulation predictions show that the new design is suited to experimentally demonstrating BSRS mitigation by an external magnetic field, despite the magnetization effects on the hydrodynamics, as well as the inherent temporal and spatial variations in plasma conditions.

The past 50 yr of advances in weed recognition technologies have poised site-specific weed control (SSWC) on the cusp of requisite performance for large-scale production systems. The technology offers improved management of diverse weed morphology over highly variable background environments. SSWC enables the use of nonselective weed control options, such as lasers and electrical weeding, as feasible in-crop selective alternatives to herbicides by targeting individual weeds. This review looks at the progress made over this half-century of research and its implications for future weed recognition and control efforts; summarizing advances in computer vision techniques and the most recent deep convolutional neural network (CNN) approaches to weed recognition. The first use of CNNs for plant identification in 2015 began an era of rapid improvement in algorithm performance on larger and more diverse datasets. These performance gains and subsequent research have shown that the variability of large-scale cropping systems is best managed by deep learning for in-crop weed recognition. The benefits of deep learning and improved accessibility to open-source software and hardware tools has been evident in the adoption of these tools by weed researchers and the increased popularity of CNN-based weed recognition research. The field of machine learning holds substantial promise for weed control, especially the implementation of truly integrated weed management strategies. Whereas previous approaches sought to reduce environmental variability or manage it with advanced algorithms, research in deep learning architectures suggests that large-scale, multi-modal approaches are the future for weed recognition.

To overcome grass supply shortages on the main grazing block, some pasture-based dairy farmers are using zero-grazing (also known as ‘cut and carry’), whereby cows are periodically housed and fed fresh grass harvested from external land blocks. To determine the effect of zero-grazing on cow performance, two early-lactation experiments were conducted with autumn and spring-calving dairy cows. Cows were assigned to one of two treatments in a randomized complete block design. The two treatments were zero-grazing (ZG) and grazing (G). The ZG group were housed and fed zero-grazed grass, while the G group grazed outdoors at pasture. Both treatments were fed perennial ryegrass (Lolium perenne L.) from the same paddock. In experiment 1, 24 Holstein Friesian cows (n = 12) were studied over a 35-day experimental period in autumn and offered fresh grass, grass silage, ground maize and concentrates. In experiment 2, 30 Holstein Friesian cows (n = 15) were studied over a 42-day experimental period and offered fresh grass and concentrates. Average dry matter intake and milk yield was similar for ZG and G in both experiments. Likewise, ZG did not have an effect on milk composition, body condition or locomotion. Zero-grazing had no effect on total nitrogen excretion or nitrogen utilization efficiency in either experiment, or on rumen pH and ammonia concentration in experiment 1. While zero-grazing may enable farmers to supply fresh grass to early-lactation cows in spring and autumn, results from this study suggest that there are no additional benefits to cow performance in comparison to well-managed grazed grass.

Italian ryegrass is a major weed in winter cereals in the south-central United States. Harvest weed seed control (HWSC) tactics that aim to remove weed seed from crop fields are a potential avenue to reduce Italian ryegrass seedbank inputs. To this effect, a 4-yr, large-plot field study was conducted in College Station, Texas, and Newport, Arkansas, from 2016 to 2019. The treatments were arranged in a split-plot design. The main-plot treatments were (1) no narrow-windrow burning (a HWSC strategy) + disk tillage immediately after harvest, (2) HWSC + disk tillage immediately after harvest, and (3) HWSC + disk tillage 1 mo after harvest. The subplot treatments were (1) pendimethalin (1,065 g ai ha−1; Prowl H2O®) as a delayed preemergence application (herbicide program #1), and (2) a premix of flufenacet (305 g ai ha−1) + metribuzin (76 g ai ha−1; Axiom®) mixed with pyroxasulfone (89 g ai ha−1; Zidua® WG) as an early postemergence application followed by pinoxaden (59 g ai ha−1; Axial® XL) in spring (herbicide program #2). After 4 yr, HWSC alone was significantly better than no HWSC. Herbicide program #2 was superior to herbicide program #1. Herbicide program #2 combined with HWSC was the most effective treatment. The combination of herbicide program #1 and standard harvest practice (no HWSC; check) led to an increase in fall Italian ryegrass densities from 4 plants m−2 in 2017 to 58 plants m−2 in 2019 at College Station. At wheat harvest, Italian ryegrass densities were 58 and 59 shoots m−2 in check plots at College Station and Newport, respectively, whereas the densities were near zero in plots with herbicide program #2 and HWSC at both locations. These results will be useful for developing an improved Italian ryegrass management strategy in this region.

The Late Triassic fauna of the Lossiemouth Sandstone Formation (LSF) from the Elgin area, Scotland, has been pivotal in expanding our understanding of Triassic terrestrial tetrapods. Frustratingly, due to their odd preservation, interpretations of the Elgin Triassic specimens have relied on destructive moulding techniques, which only provide incomplete, and potentially distorted, information. Here, we show that micro-computed tomography (μCT) could revitalise the study of this important assemblage. We describe a long-neglected specimen that was originally identified as a pseudosuchian archosaur, Ornithosuchus woodwardi. μCT scans revealed dozens of bones belonging to at least two taxa: a small-bodied pseudosuchian and a specimen of the procolophonid Leptopleuron lacertinum. The pseudosuchian skeleton possesses a combination of characters that are unique to the clade Erpetosuchidae. As a basis for investigating the phylogenetic relationships of this new specimen, we reviewed the anatomy, taxonomy and systematics of other erpetosuchid specimens from the LSF (all previously referred to Erpetosuchus). Unfortunately, due to the differing representation of the skeleton in the available Erpetosuchus specimens, we cannot determine whether the erpetosuchid specimen we describe here belongs to Erpetosuchus granti (to which we show it is closely related) or if it represents a distinct new taxon. Nevertheless, our results shed light on rarely preserved details of erpetosuchid anatomy. Finally, the unanticipated new information extracted from both previously studied and neglected specimens suggests that fossil remains may be much more widely distributed in the Elgin quarries than previously recognised, and that the richness of the LSF might have been underestimated.

Recent technological advances have led to a novel class of microfluidic devices which can be rapidly fabricated by printing a fluid onto a solid substrate with flows generated passively via surface tension. The nonlinear dependence between flow and the heights of the conduits, however, prevent straightforward calculation of the resulting dynamics. In this paper we use matched asymptotic expansions to predict how flow through these devices can be tuned by changing their geometry. We begin with the simple ‘dumbbell’ configuration in which two fluid drops with different sizes are connected by a long, thin and narrow conduit. We calculate the time scale required for one drop to drain into the other and how this depends both on the geometry of the pinned contact line and volume of fluid deposited into the drops. Our model therefore provides the mechanistic basis to design conduits with a particular fluid flux and/or shear stress, which are often key experimental constraints. Our asymptotic predictions are shown to be in excellent agreement with numerical simulations even for moderate aspect ratios (the ratio of conduit width to length). Next, we show how our results for the simple dumbbell configuration can be extended to predict the flow through networks of conduits with multiple drops and nodes, and hence may assist in their design and implementation. This new mathematical framework has the potential to increase the use of surface tension driven microfluidics across a wide range of disciplines as it allows alternate designs to be rapidly assessed.

Little is known about who would benefit from Internet-based personalised nutrition (PN) interventions. This study aimed to evaluate the characteristics of participants who achieved greatest improvements (i.e. benefit) in diet, adiposity and biomarkers following an Internet-based PN intervention. Adults (n 1607) from seven European countries were recruited into a 6-month, randomised controlled trial (Food4Me) and randomised to receive conventional dietary advice (control) or PN advice. Information on dietary intake, adiposity, physical activity (PA), blood biomarkers and participant characteristics was collected at baseline and month 6. Benefit from the intervention was defined as ≥5 % change in the primary outcome (Healthy Eating Index) and secondary outcomes (waist circumference and BMI, PA, sedentary time and plasma concentrations of cholesterol, carotenoids and omega-3 index) at month 6. For our primary outcome, benefit from the intervention was greater in older participants, women and participants with lower HEI scores at baseline. Benefit was greater for individuals reporting greater self-efficacy for ‘sticking to healthful foods’ and who ‘felt weird if [they] didn’t eat healthily’. Participants benefited more if they reported wanting to improve their health and well-being. The characteristics of individuals benefiting did not differ by other demographic, health-related, anthropometric or genotypic characteristics. Findings were similar for secondary outcomes. These findings have implications for the design of more effective future PN intervention studies and for tailored nutritional advice in public health and clinical settings.