There is emerging evidence linking fruit and vegetable consumption and cognitive function. However, studies focusing on the nutrients underlying this relationship are lacking. We aim to examine the association between plasma nutrients and cognition in a population at risk for cognitive decline with a suboptimal diet. The Mediterranean-DASH Intervention for Neurodegenerative Delay (MIND) trial is a randomized controlled intervention that examines the effects of the MIND diet to prevent cognitive decline. The primary outcome is global cognition. A multivariate linear model was used to investigate the association between blood nutrients and global and/or domain-specific cognition. The model was adjusted for age, sex, education, study site, smoking status, cognitive activities and physical activities. High plasma α-carotene was associated with better global cognition. Participants in the highest tertile of plasma α-carotene had a higher global cognition z score of 0⋅17 when compared with individuals in the lowest tertile (P 0⋅002). Circulating α-carotene levels were also associated with higher semantic memory scores (P for trend 0⋅007). Lutein and zeaxanthin (combined) was positively associated with higher semantic memory scores (P for trend 0⋅009). Our study demonstrated that higher α-carotene levels in blood were associated with higher global cognition scores in a US population at risk for cognitive decline. The higher α-carotene levels in blood reflected greater intakes of fruits, other types of vegetables and lesser intakes of butter and margarine and meat. The higher circulating levels of lutein plus zeaxanthin reflected a dietary pattern with high intakes of fruits, green leafy, other vegetables and cheese, and low consumption of fried foods. Objective nutrient markers in the blood can better characterize dietary intake, which may facilitate the implementation of a tailored dietary intervention for the prevention of cognitive decline.

Recent research in American politics demonstrates that despite gender-based partisan sorting, gender gaps in policy preferences persist within political parties—particularly among Republicans. Republican women report significantly more moderate views than their male counterparts across a range of policy areas. These gaps are largely attributable to gender differences in beliefs about the appropriate scope of government and attitudes toward gender-based inequality. Arguably, gender has become a more salient feature of American elections in recent years, and this heightened salience raises questions about whether these within-party gender gaps are stable over time or vary across campaign contexts. We use survey data from the 2012 and 2016 American National Election Study to evaluate whether gender gaps in policy preferences are stable across elections or if the 2016 election context affected the magnitude of gender differences in policy preferences. We find that gender gaps in policy preferences within political parties are fairly stable across the two electoral periods.

This Research Reflection provides an overview of three interrelated topics: (i) lameness in dairy cows, demonstrating the underpinning importance of the condition, (ii) dairy farmer detection, diagnosis and treatment of lameness and associated foot lesions as well as dairy farmer perceptions towards the condition and (iii) lameness detection technologies, and their potential application on farm to automate the detection of lameness in commercial dairy herds. The presented literature clearly demonstrates that lameness is a major health issue in dairy herds, compromising dairy cow welfare and productivity, and resulting in significant economic implications for dairy farmers. Despite this, dairy farmers fail to perceive lameness as a serious threat to their dairy business. This restricted perception of the importance of lameness may be a product of limited ability to detect lame cows. Many automated lameness detection technologies have been proposed to assist dairy farmers in managing their herds. However, limitations such as cost, performance and dairy farmer perception of the usefulness of these technologies, has lead to poor uptake. It can, therefore, be concluded that there is a need to more thoroughly evaluate the effectiveness of these technologies under on-farm conditions, potentially in the form of a demonstration farm network. This will allow generation of the necessary data required to show dairy farmers that these technologies are reliable and are economically rational for their dairy business.

The search for life in the Universe is a fundamental problem of astrobiology and modern science. The current progress in the detection of terrestrial-type exoplanets has opened a new avenue in the characterization of exoplanetary atmospheres and in the search for biosignatures of life with the upcoming ground-based and space missions. To specify the conditions favourable for the origin, development and sustainment of life as we know it in other worlds, we need to understand the nature of global (astrospheric), and local (atmospheric and surface) environments of exoplanets in the habitable zones (HZs) around G-K-M dwarf stars including our young Sun. Global environment is formed by propagated disturbances from the planet-hosting stars in the form of stellar flares, coronal mass ejections, energetic particles and winds collectively known as astrospheric space weather. Its characterization will help in understanding how an exoplanetary ecosystem interacts with its host star, as well as in the specification of the physical, chemical and biochemical conditions that can create favourable and/or detrimental conditions for planetary climate and habitability along with evolution of planetary internal dynamics over geological timescales. A key linkage of (astro)physical, chemical and geological processes can only be understood in the framework of interdisciplinary studies with the incorporation of progress in heliophysics, astrophysics, planetary and Earth sciences. The assessment of the impacts of host stars on the climate and habitability of terrestrial (exo)planets will significantly expand the current definition of the HZ to the biogenic zone and provide new observational strategies for searching for signatures of life. The major goal of this paper is to describe and discuss the current status and recent progress in this interdisciplinary field in light of presentations and discussions during the NASA Nexus for Exoplanetary System Science funded workshop ‘Exoplanetary Space Weather, Climate and Habitability’ and to provide a new roadmap for the future development of the emerging field of exoplanetary science and astrobiology.

Spherical coordinate systems, which are ubiquitous in astronomy, cannot be shown without distortion on flat, two-dimensional surfaces. This poses challenges for the two complementary phases of visual exploration—making discoveries in data by looking for relationships, patterns, or anomalies—and publication—where the results of an exploration are made available for scientific scrutiny or communication. This is a long-standing problem, and many practical solutions have been developed. Our allskyVR approach provides a workflow for experimentation with commodity virtual reality head-mounted displays. Using the free, open source s2plot programming library, and the A-FrameWebVR browser-based framework, we provide a straightforward way to visualise all-sky catalogues on a user-centred, virtual celestial sphere. The allskyVR distribution contains both a quickstart option, complete with a gaze-based menu system, and a fully customisable mode for those who need more control of the immersive experience. The software is available for download from https://github.com/cfluke/allskyVR.

Spring tillage is a component of an integrated weed management strategy for control of early emerging glyphosate-resistant weeds such as common ragweed; however, the effect of tillage on common ragweed emergence pattern is unknown. The objectives of this study were to evaluate whether spring tillage during emergence would influence the emergence pattern or stimulate additional emergence of common ragweed and to characterize common ragweed emergence in southeast Nebraska. A field experiment was conducted for three years (2014 to 2016) in Gage County, Nebraska in a field naturally infested with glyphosate-resistant common ragweed. Treatments consisted of a no-tillage control and three spring tillage timings. The Soil Temperature and Moisture Model (STM2) software was used to estimate soil temperature and moisture at a 2-cm depth. The Weibull function was fit to total common ragweed emergence (%) with day of year (DOY), thermal time, and hydrothermal time as independent variables. Tillage treatments and year had no effect on total common ragweed emergence (P=0.88 and 0.35, respectively) and time to 10, 25, 50, 75, and 90% emergence (P=0.31). However, emergence pattern was affected by year (P=<0.001) with 50% total emergence reached on May 5 in 2014, April 20 in 2015, and April 2 in 2016 and 90% total emergence reached on May 12, 2014, May 8, 2015, and April 30, 2016. According to the corrected information-theoretic model comparison criterion (AICc), the Weibull function with thermal time and base temperature of 3 C best explained the emergence pattern over three years. This study concludes that spring tillage does not stimulate additional emergence; therefore, after the majority of the common ragweed has emerged and before the crop has been planted, tillage could be used as an effective component of an integrated glyphosate-resistant common ragweed management program in Nebraska.

Women earn 40% of new PhDs in political science; however, once they enter the profession, they have strikingly different experiences than their male counterparts—particularly in the small but influential field of political methodology. For several years, the Society for Political Methodology, with support from the National Science Foundation, has attempted to address this gender gap through the Visions in Methodology (VIM) program. VIM features an annual conference that brings women together to present and discuss their research and to participate in professional-development sessions. Do programs like VIM have the desired impact? Using an original survey of political scientists, this study provides insights into the ways that bringing women together in small-group settings like VIM might facilitate networking and enhance productivity. In particular, the study finds that women who attend the VIM conference are better networked and more productive in terms of publication.

Salmonella is a leading cause of bacterial foodborne illness. We report the collaborative investigative efforts of US and Canadian public health officials during the 2013–2014 international outbreak of multiple Salmonella serotype infections linked to sprouted chia seed powder. The investigation included open-ended interviews of ill persons, traceback, product testing, facility inspections, and trace forward. Ninety-four persons infected with outbreak strains from 16 states and four provinces were identified; 21% were hospitalized and none died. Fifty-four (96%) of 56 persons who consumed chia seed powder, reported 13 different brands that traced back to a single Canadian firm, distributed by four US and eight Canadian companies. Laboratory testing yielded outbreak strains from leftover and intact product. Contaminated product was recalled. Although chia seed powder is a novel outbreak vehicle, sprouted seeds are recognized as an important cause of foodborne illness; firms should follow available guidance to reduce the risk of bacterial contamination during sprouting.

The western Antarctic Peninsula (WAP) is a hotspot of rapid recent regional ‘climate change’. This has resulted in a 0.4°C rise in sea temperature in the last 50 years, five days of sea ice lost per decade and increased ice scouring in the shallows. The WAP shallows are ideal for studying the biological response to physical change because most known Antarctic species are benthic, physical change occurs mainly in the shallows and most research stations are coastal. Studies at Rothera Station have found increased benthic disturbance with losses of winter sea ice and assemblage-level changes coincident with this ice scouring. Such studies are difficult to scale up as they depend on SCUBA diving – a very spatially limited technique. Here we report attempts to broaden the understanding of benthic ecosystem responses to physical change by replicating the Rothera experimental grids at Carlini Station through collaboration between the UK, Argentina and Germany across Signy, Rothera and Carlini stations. We argue that such collaborations are the way forward towards understanding the big picture of biota responses to physical climate changes at a regional scale.

We compare the results of using a Random Forest Classifier with the results of using Nonparametric Discriminant Analysis to classify whether a filament channel (in the case of a filament eruption) or an active region (in the case of a flare) is about to produce an event. A large number of descriptors are considered in each case, but it is found that only a small number are needed in order to get most of the improvement in performance over always predicting the majority class. There is little difference in performance between the two classifiers, and neither results in substantial improvements over simply predicting the majority class.