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Mental fatigue, 'brain fog', and difficulties maintaining engagement are commonly reported issues in a range of neurological and psychiatric conditions. Traditional sustained attention tasks commonly measure this capacity as the ability to detect target stimuli based on sensory features in the auditory or visual domains. However, with this approach, discrete target stimuli may exogenously capture attention to aid detection, thereby masking deficits in the ability to endogenously sustain attention over time. To address this, we developed the Continuous Temporal Expectancy Task (CTET) where individuals continuously monitor a stream of patterned stimuli alternating at a fixed temporal interval (690 ms) and detect an infrequently occurring target stimulus defined by a prolonged temporal duration (1020 ms or longer). As such, sensory properties of target and non-target stimuli are perceptually identical and differ only in temporal duration. Using the CTET, we assessed stroke survivors with unilateral right hemisphere damage (N = 14), a cohort in which sustained attention deficits have been extensively reported. Stroke survivors had overall lower target detection accuracy compared with neurologically healthy age-matched older controls (N = 18). Critically, stroke survivors performance was characterised by significantly steeper within-block performance decrements, which occurred within short temporal windows (˜3 ½ min), and were restored by the break periods between blocks. These findings suggest that continuous temporal monitoring taxes sustained attention processes to capture clinical deficits in this capacity over time, and outline a precise measure of the endogenous processes hypothesised to underpin sustained attention deficits following right hemisphere stroke.

Wildfire is a highly variable natural phenomenon, yet despite this, climate change is already making wildfire conditions measurably worse around the world; however, detailed knowledge about Aotearoa New Zealand's wildfire climate is currently limited. This study blends weather observations with regional climate model projections to assess Aotearoa New Zealand's 21st‐century wildfire climate. We find that in the 21st‐century, the emergence of a new—more severe wildfire climate will occur. Detailed analysis of observed and simulated wildfire weather finds that “very‐extreme” wildfire weather conditions matching the levels observed in Australia's 2019/2020 “Black Summer” bushfires are possible in regions formerly unaffected. While the extent of emergence is dependent on future emissions, the frequency of very‐extreme conditions for the areas affected can occur at any time and is independent of projected 21st‐century climate changes. Our findings have significant implications for many rural fire authorities, forest managers and investors, and climate mitigation and afforestation programs. Plain Language Summary Combining highly detailed climate simulations with daily observations of weather and wildfire conditions, we simulate Aotearoa New Zealand's current and future wildfire weather conditions. We find that wildfire weather conditions will increase on average, both in wildfire season length and in the intensity of fires that may take hold, with the most severe wildfire dangers in the central‐south inland areas of the South Island. We find that the wildfire weather conditions will become noticeably worse for many regions than current conditions. For the first time, we find that very‐extreme conditions that led to the devastating 2019–2020 “Black‐Summer” fires in Australia can occur in Aotearoa every 3–20 year for areas of the South Island (Mackenzie Country, Upper Otago, and Marlborough). Our findings have important implications for communities near pine forests, the Government's tree planting plan to tackle climate change, and financial investment stored in plantation forests. Key Points In the 21st‐century, the emergence of a new—more severe wildfire climate will occur We discover that “very‐extreme” wildfire weather conditions are possible in regions formerly unaffected While the extent of emergence is dependent on future emissions, the frequency of very‐extreme conditions is independent

Identification of the relative importance of within- and between-host variability in infectiousness and the impact of these heterogeneities on the transmission dynamics of infectious agents can enable efficient targeting of control measures. Cattle, a major reservoir host for the zoonotic pathogen Escherichia coli O157, are known to exhibit a high degree of heterogeneity in bacterial shedding densities. By relating bacterial count to infectiousness and fitting dynamic epidemiological models to prevalence data from a cross-sectional survey of cattle farms in Scotland, we identify a robust pattern: approximately equal to 80% of the transmission arises from the 20% most infectious individuals. We examine potential control options under a range of assumptions about within- and between-host variability in infection dynamics. Our results show that the within-herd basic reproduction ratio, R0, could be reduced to <1 with targeted measures aimed at preventing infection in the 5% of individuals with the highest overall infectiousness. Alternatively, interventions such as vaccination or the use of probiotics that aim to reduce bacterial carriage could produce dramatic reductions in R0 by preventing carriage at concentrations corresponding to the top few percent of the observed range of counts. We conclude that a greater understanding of the cause of the heterogeneity in bacterial carriage could lead to highly efficient control measures to reduce the prevalence of E. coli O157.

The start-up of the Large Hadron Collider (LHC) at CERN, Geneva, presents a huge challenge in processing and analysing the vast amounts of scientific data that will be produced. The architecture of the worldwide grid that will handle 15 PB of particle physics data annually from this machine is based on a hierarchical tiered structure. We describe the development of the UK component (GridPP) of this grid from a prototype system to a full exploitation grid for real data analysis. This includes the physical infrastructure, the deployment of middleware, operational experience and the initial exploitation by the major LHC experiments.

Monitoring temperature of aquatic waters is of great importance, with modelled, satellite and in-situ data providing invaluable insights into long-term environmental change. However, there is often a lack of depth-resolved temperature measurements. Recreational dive computers routinely record temperature and depth, so could provide an alternate and highly novel source of oceanographic information to fill this data gap. In this study, a citizen science approach was used to obtain over 7,000 scuba diver temperature profiles. The accuracy, offset and lag of temperature records was assessed by comparing dive computers with scientific conductivity-temperature-depth instruments and existing surface temperature data. Our results show that, with processing, dive computers can provide a useful and novel tool with which to augment existing monitoring systems all over the globe, but especially in under-sampled or highly changeable coastal environments.

Background/Aims: To examine the relationship of biological mediators (cytokines, stress hormones), psychosocial, obstetric history, and demographic factors in the early prediction of preterm birth (PTB) using a comprehensive logistic regression model incorporating diverse risk factors. Methods: In this prospective case-control study, maternal serum biomarkers were quantified at 9–23 weeks’ gestation in 60 women delivering at <37 weeks compared to 123 women delivering at term. Biomarker data were combined with maternal sociodemographic factors and stress data into regression models encompassing 22 preterm risk factors and 1st-order interactions. Results: Among individual biomarkers, we found that macrophage migration inhibitory factor (MIF), interleukin-10, C-reactive protein (CRP), and tumor necrosis factor-α were statistically significant predictors of PTB at all cutoff levels tested (75th, 85th, and 90th percentiles). We fit multifactor models for PTB prediction at each biomarker cutoff. Our best models revealed that MIF, CRP, risk-taking behavior, and low educational attainment were consistent predictors of PTB at all biomarker cutoffs. The 75th percentile cutoff yielded the best predicting model with an area under the ROC curve of 0.808 (95% CI 0.743–0.874). Conclusion: Our comprehensive models highlight the prominence of behavioral risk factors for PTB and point to MIF as a possible psychobiological mediator.

A novel method of assessing muscle function in the common marmoset was developed as part of a multidisciplinary long-term study. The method involved home cage presentation of a weight-pulling task. Over a 4–5 month period, 38 of 42 animals were successfully trained to displace weights of up to 920 g (mean 612±20 g). Performance, following initial training, was stable and independent of gender or body weight.

The synthesis and accumulation of proteinase inhibitor I in excised tomato leaves can be induced with oligosaccharides obtained by fungal endo-α -1,4-polygalacturonase digestion of a pectic polysaccharide (Mr5000-10,000) isolated from tomato leaves. Active oligosaccharides were also released from isolated tomato leaf cell walls by endopolygalacturonases partially purified from tomato plants. It is suggested that oligosaccharides, released from plant cell wall pectic polysaccharides by either endogenous or exogenous endopolygalacturonases at a wound or infection site, may have hormone-like roles in regulating plant defense responses in unwounded tissues many centimeters away from the site of release.

Environmental actions require a willingness to act, which, in turn, is stimulated partially by the belief that an action will yield the desired consequences. In determining whether an actor was justified in exerting the will to act, therefore, it is essential to examine the nature of evidence offered by the actor in support of any beliefs about the environment. In this paper we explore the points in environmental risk analyses at which evidence is brought to bear in support of inferences concerning environmental effects of regulatory actions. The intent is to provide a framework for discussing the manner in which evidence may provide a sufficient basis for ethically sound decisions for environmental actions.