The ice shelves buttressing the Antarctic ice sheet determine the rate of ice-discharge into the surrounding oceans. Their geometry and buttressing strength are influenced by the local surface accumulation and basal melt rates, governed by atmospheric and oceanic conditions. Contemporary methods quantify one of these rates, but typically not both. Moreover, information about these rates is only available for recent time periods, reaching at most a few decades back since measurements are available. We present a new method to simultaneously infer the surface accumulation and basal melt rates averaged over decadal and centennial timescales. We infer the spatial dependence of these rates along flow line transects using internal stratigraphy observed by radars, using a kinematic forward model of internal stratigraphy. We solve the inverse problem using simulation-based inference (SBI). SBI performs Bayesian inference by training neural networks on simulations of the forward model to approximate the posterior distribution, therefore also quantifying uncertainties over the inferred parameters. We validate our method on a synthetic example, and apply it to Ekström Ice Shelf, Antarctica, for which independent validation data are available. We obtain posterior distributions of surface accumulation and basal melt averaging over up to 200 years before 2022.

Ice rises hold valuable records revealing the ice dynamics and climatic history of Antarctic coastal areas from the Last Glacial Maximum to today. This history is often reconstructed from isochrone radar stratigraphy and simulations focusing on Raymond arch evolution beneath the divides. However, this relies on complex ice-flow models where many parameters are unconstrained by observations. Our study explores quad-polarimetric, phase-coherent radar data to enhance understanding near ice divides and domes, using Hammarryggen Ice Rise (HIR) as a case study. Analysing a 5 km profile intersecting the dome, we derive vertical strain rates and ice-fabric properties. These align with ice core data near the summit, increasing confidence in tracing signatures from the dome to the flanks. The Raymond effect is evident, correlating with surface strain rates and radar stratigraphy. Stability is inferred over millennia for the saddle connecting HIR to the mainland, but dome ice-fabric appears relatively young compared to 2D model predictions. In a broader context, quad-polarimetric measurements provide valuable insights into ice-flow models, particularly for anisotropic rheology. Including quad-polarimetric data advances our ability to reconstruct past ice flow dynamics and climatic history in ice rises.

Compacted MX-80 bentonite is a potential backfill material in radioactive-waste repositories. Pore space in MX-80 has been the subject of considerable debate. 3D reconstructions of the pore space based on tomographic methods could provide new insights into the nature of the pore space of compacted bentonites. To date, few such reconstructions have been done because of problems with the preparation of bentonite samples for electron microscopy. The nanoscale intergranular pore space was investigated here by cryo-Focused Ion Beam nanotomography (FIB-nt) applied to previously high-pressure frozen MX-80 bentonite samples. This approach allowed a tomographic investigation of the in situ microstructure related to different dry densities (1.24, 1.46, and 1.67 g/cm3). The FIB-nt technique is able to resolve intergranular pores with radii >10 nm. With increasing dry density (1.24–1.67 g/cm3) the intergranular porosity (>10 nm) decreased from ~5 vol.% to 0.1 vol.%. At dry densities of 1.24 and 1.46 g/cm3, intergranular pores were filled with clay aggregates, which formed a mesh-like structure, similar to the honeycomb structure observed in diagenetic smectite. Unlike ‘typical’ clay gels, the cores of the honeycomb structure were not filled with pure water, but instead were filled with a less dense material which presumably consists of very fine clay similar to a colloid. In the low-density sample this honeycomb-structured material partly filled the intergranular pore space but some open pores were also present. In the 1.46 g/cm3 sample, the material filled the intergranular pores almost completely. At the highest densities investigated (1.67 g/cm3), the honeycomb-structured material was not present, probably because of the lack of intergranular pores which suppressed the formation of the honeycomb framework or skeleton consisting of clay aggregates.

Appropriateness of transmission-based precautions after positive result for a non-SARS-CoV-2 virus was evaluated. Most patients (77.2%) lacked appropriate precautions within 3 hours of virus detection; 36.9% remained without appropriate precautions during their stay. With recent cessation of universal masking, adherence to infection control best practices is needed to optimize safety.

Diagnosing the evolution of laser-generated high energy density (HED) systems is fundamental to develop a correct understanding of the behavior of matter under extreme conditions. Talbot–Lau interferometry constitutes a promising tool, since it permits simultaneous single-shot X-ray radiography and phase-contrast imaging of dense plasmas. We present the results of an experiment at OMEGA EP that aims to probe the ablation front of a laser-irradiated foil using a Talbot–Lau X-ray interferometer. A polystyrene (CH) foil was irradiated by a laser of 133 J, 1 ns and probed with 8 keV laser-produced backlighter radiation from Cu foils driven by a short-pulse laser (153 J, 11 ps). The ablation front interferograms were processed in combination with a set of reference images obtained ex situ using phase-stepping. We managed to obtain attenuation and phase-shift images of a laser-irradiated foil for electron densities above ${10}^{22}\;{\mathrm{cm}}^{-3}$. These results showcase the capabilities of Talbot–Lau X-ray diagnostic methods to diagnose HED laser-generated plasmas through high-resolution imaging.

The shape of depth-limited breaking-wave overturns is important for turbulence injection, bubble entrainment and sediment suspension. Overturning wave shape depends on a nonlinearity parameter $H/h$, where $H$ is the wave height, and $h$ is the water depth. Cross-shore wind direction (offshore/onshore) and magnitude affect laboratory shoaling wave shape and breakpoint location $X_{{bp}}$, but wind effects on overturning wave shape are largely unstudied. We perform field-scale experiments at the Surf Ranch wave basin with fixed bathymetry and $\approx 2.25$ m shoaling solitons with small height variations propagating at $C=6.7\ \mathrm {m}\ \mathrm {s}^{-1}$. Observed non-dimensional cross-wave wind $U_w$ was onshore and offshore, varying realistically ($-1.2 < U_{w}/C < 0.7$). Georectified images, a wave staff, and lidar are used to estimate $X_{{bp}}$, $H/h$, overturn area $A$ and aspect ratio for 22 waves. The non-dimensionalized $X_{{bp}}$ was inversely related to $U_{w}/C$. The non-dimensional overturn area and aspect ratio also were inversely related to $U_{w}/C$, with smaller and narrower overturns for increasing onshore wind. No overturning shape dependence on the weakly varying $H/h$ was seen. The overturning shape variation was as large as prior laboratory experiments with strong $H/h$ variations without wind. An idealized potential air flow simulation on steep shoaling soliton shape has strong surface pressure variations, potentially inducing overturning shape changes. Through wave-overturning impacts on turbulence and sediment suspension, coastal wind variations could be relevant for near-shore morphology.

The amount of information in our society and its opportunities have given rise to Big Data research. The systems supplier industry needs suitable tools and methods to ensure the harvest and utilization of Big Data in their product development. This paper used Systems Thinking to analyze the current state in the industry and suggested leverage points for further research direction. The findings suggest that the research project should emphasize the industry cases, the collaboration between the companies and academia, develop a Big Data systems architecture, and maintain a socio-technical view.

Nonsuicidal self-injury (NSSI) is a common but poorly understood phenomenon in adolescents. This study examined the Sustained Threat domain in female adolescents with a continuum of NSSI severity (N = 142). Across NSSI lifetime frequency and NSSI severity groups (No + Mild NSSI, Moderate NSSI, Severe NSSI), we examined physiological, self-reported and observed stress during the Trier Social Stress Test; amygdala volume; amygdala responses to threat stimuli; and resting-state functional connectivity (RSFC) between amygdala and medial prefrontal cortex (mPFC). Severe NSSI showed a blunted pattern of cortisol response, despite elevated reported and observed stress during TSST. Severe NSSI showed lower amygdala–mPFC RSFC; follow-up analyses suggested that this was more pronounced in those with a history of suicide attempt for both moderate and severe NSSI. Moderate NSSI showed elevated right amygdala activation to threat; multiple regressions showed that, when considered together with low amygdala–mPFC RSFC, higher right but lower left amygdala activation predicted NSSI severity. Patterns of interrelationships among Sustained Threat measures varied substantially across NSSI severity groups, and further by suicide attempt history. Study limitations include the cross-sectional design, missing data, and sampling biases. Our findings highlight the value of multilevel approaches in understanding the complexity of neurobiological mechanisms in adolescent NSSI.

Consumption of sugar-sweetened beverages (SSB) by infants and young children are less explored in Asian populations. The Growing Up in Singapore Towards healthy Outcomes cohort study examined associations between SSB intake at 18 months and 5 years of age, with adiposity measures at 6 years of age. We studied Singaporean infants/children with SSB intake assessed by FFQ at 18 months of age (n 555) and 5 years of age (n 767). The median for SSB intakes is 28 (interquartile range 5·5–98) ml at 18 months of age and 111 (interquartile range 57–198) ml at 5 years of age. Association between SSB intake (100 ml/d increments and tertile categories) and adiposity measures (BMI standard deviation scores (sd units), sum of skinfolds (SSF)) and overweight/obesity status were examined using multivariable linear and Poisson regression models, respectively. After adjusting for confounders and additionally for energy intake, SSB intake at age 18 months were not significantly associated with later adiposity measures and overweight/obesity outcomes. In contrast, at age 5 years, SSB intake when modelled as 100 ml/d increments were associated with higher BMI by 0·09 (95 % CI 0·02, 0·16) sd units, higher SSF thickness by 0·68 (95 % CI 0·06, 1·44) mm and increased risk of overweight/obesity by 1·2 (95 % CI 1·07, 1·23) times at age 6 years. Trends were consistent with SSB intake modelled as categorical tertiles. In summary, SSB intake in young childhood is associated with higher risks of adiposity and overweight/obesity. Public health policies working to reduce SSB consumption need to focus on prevention programmes targeted at young children.

Over the past decade, advances in the interdisciplinary field of network science have provided a framework for understanding the intrinsic structure and function of human brain networks. A particularly fruitful area of this work has focused on patterns of functional connectivity derived from noninvasive neuroimaging techniques such as functional magnetic resonance imaging. An important subset of these efforts has bridged the computational approaches of network science with the rich empirical data and biological hypotheses of neuroscience, and this research has begun to identify features of brain networks that explain individual differences in social, emotional, and cognitive functioning. The most common approach estimates connections assuming a single configuration of edges that is stable across the experimental session. In the literature, this is referred to as a static network approach, and researchers measure static brain networks while a subject is either at rest or performing a cognitively demanding task. Research on social and emotional functioning has primarily focused on linking static brain networks with individual differences, but recent advances have extended this work to examine temporal fluctuations in dynamic brain networks. Mounting evidence suggests that both the strength and flexibility of time-evolving brain networks influence individual differences in executive function, attention, working memory, and learning. In this review, we first examine the current evidence for brain networks involved in cognitive functioning. Then we review some preliminary evidence linking static network properties to individual differences in social and emotional functioning. We then discuss the applicability of emerging dynamic network methods for examining individual differences in social and emotional functioning. We close with an outline of important frontiers at the intersection between network science and neuroscience that will enhance our understanding of the neurobiological underpinnings of social behavior.

Let X1, X2, . . . be independent copies of a random vector X with values in ℝd and a continuous distribution function. The random vector Xn is a complete record, if each of its components is a record. As we require X to have independent components, crucial results for univariate records clearly carry over. But there are substantial differences as well. While there are infinitely many records in the d = 1 case, they occur only finitely many times in the series if d ≥ 2. Consequently, there is a terminal complete record with probability 1. We compute the distribution of the random total number of complete records and investigate the distribution of the terminal record. For complete records, the sequence of waiting times forms a Markov chain, but unlike the univariate case now the state at ∞ is an absorbing element of the state space.

An accurate knowledge of the thermal properties of firn and ice within a glacier is essential for any reliable mathematical model of heat transfer. This paper considers the problem of determining the thermal properties of firn at Dome C, Antarctica, for use in such a model.

First, the difficulties in accurately determining thermal properties are discussed. Then a physical experiment which can be performed under field conditions, but which will yield a well-posed mathematical problem for determining the unknown properties, is presented. Next, two different numerical techniques for solving the mathematical problem are discussed. Finally, some numerical approximations and error estimates are presented for the results of applying our numerical procedure to data from Dome C. Although insufficient data were obtained to test our methods fully, we have established a measurement procedure and a method of analysis which appear to be promising.

The effect of ethametsulfuron on populations of canola was evaluated in field and laboratory trials. Three canola populations (TR4, CB9604, and BC86-18) and the open-pollinated canola cv. ‘AC Parkland’ were treated with several doses of ethametsulfuron at the two- to four-leaf stage. In the field experiment, plant densities were determined before spraying and again at plant maturity. Density reductions during the growing season were observed for all populations (6 to 17%), but reductions due to ethametsulfuron above 0.3 g ha−1 depended on year, being noted for TR4 in 1997 (40 to 65%) only. In laboratory trials, only TR4 demonstrated sensitivity to ethametsulfuron, up to 49% visual damage averaged over all plants. The response was binary, with about 40% of plants at any given herbicide rate surviving unharmed and the remaining 60% of plants exhibiting > 90% visual damage. It is concluded that TR4 is sensitive to ethametsulfuron and further work, including a comprehensive genetic study, is required to determine the inheritance of sensitivity.

Declines in populations of the Critically Endangered Spoon-billed Sandpiper Calidris pygmaeus have been rapid, with the breeding population now perhaps numbering fewer than 120 pairs. The reasons for this decline remain unresolved. Whilst there is evidence that hunting in wintering areas is an important factor, loss of suitable habitat on passage and wintering areas is also of concern. While some key sites for the species are already documented, many of their wintering locations are described here for the first time. Their wintering range primarily stretches from Bangladesh to China. Comprehensive surveys of potential Spoon-billed Sandpiper wintering sites from 2005 to 2013 showed a wide distribution with three key concentrations in Myanmar and Bangladesh, but also regular sites in China, Vietnam and Thailand. The identification of all important non-breeding sites remains of high priority for the conservation of the species. Here, we present the results of field surveys of wintering Spoon-billed Sandpipers that took place in six countries between 2005 and 2013 and present species distribution models which map the potential wintering areas. These include known and currently unrecognised wintering locations. Our maximum entropy model did not identify any new extensive candidate areas within the winter distribution, suggesting that most key sites are already known, but it did identify small sites on the coast of eastern Bangladesh, western Myanmar, and the Guangxi and Guangdong regions of China that may merit further investigation. As no extensive areas of new potential habitat were identified, we suggest that the priorities for the conservation of this species are habitat protection in important wintering and passage areas and reducing hunting pressure on birds at these sites.

Although infection by the pathogenic bacterium Listeria monocytogenes is relatively rare, consequences can be severe, with a high case-fatality rate in vulnerable populations. A quantitative, probabilistic risk assessment tool was developed to compare estimates of the number of invasive listeriosis cases in vulnerable Canadian subpopulations given consumption of contaminated ready-to-eat delicatessen meats and hot dogs, under various user-defined scenarios. The model incorporates variability and uncertainty through Monte Carlo simulation. Processes considered within the model include cross-contamination, growth, risk factor prevalence, subpopulation susceptibilities, and thermal inactivation. Hypothetical contamination events were simulated. Results demonstrated varying risk depending on the consumer risk factors and implicated product (turkey delicatessen meat without growth inhibitors ranked highest for this scenario). The majority (80%) of listeriosis cases were predicted in at-risk subpopulations comprising only 20% of the total Canadian population, with the greatest number of predicted cases in the subpopulation with dialysis and/or liver disease. This tool can be used to simulate conditions and outcomes under different scenarios, such as a contamination event and/or outbreak, to inform public health interventions.

Little is known about the influence of meal timing and energy consumption patterns throughout the day on glucose regulation during pregnancy. We examined the association of maternal feeding patterns with glycaemic levels among lean and overweight pregnant women. In a prospective cohort study in Singapore, maternal 24-h dietary recalls, fasting glucose (FG) and 2-h postprandial glucose (2HPPG) concentrations were measured at 26–28 weeks of gestation. Women (n 985) were classified into lean (BMI<23 kg/m2) or overweight (BMI≥23 kg/m2) groups. They were further categorised as predominantly daytime (pDT) or predominantly night-time (pNT) feeders according to consumption of greater proportion of energy content from 07.00 to 18.59 hours or from 19.00 to 06.59 hours, respectively. On stratification by weight status, lean pNT feeders were found to have higher FG than lean pDT feeders (4·36 (sd 0·38) v. 4·22 (sd 0·35) mmol/l; P=0·002); however, such differences were not observed between overweight pDT and pNT feeders (4·49 (sd 0·60) v. 4·46 (sd 0·45) mmol/l; P=0·717). Using multiple linear regression with confounder adjustment, pNT feeding was associated with higher FG in the lean group (β=0·16 mmol/l; 95 % CI 0·05, 0·26; P=0·003) but not in the overweight group (β=0·02 mmol/l; 95 % CI −0·17, 0·20; P=0·879). No significant association was found between maternal feeding pattern and 2HPPG in both the lean and the overweight groups. In conclusion, pNT feeding was associated with higher FG concentration in lean but not in overweight pregnant women, suggesting that there may be an adiposity-dependent effect of maternal feeding patterns on glucose tolerance during pregnancy.