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.

Large-scale archaeogenetic studies of people from prehistoric Europe tend to be broad in scope and difficult to resolve with local archaeologies. However, accompanying supplementary information often contains useful finer-scale information that is comprehensible without specific genetics expertise. Here, we show how undiscussed details provided in supplementary information of aDNA papers can provide crucial insight into patterns of ancestry change and genetic relatedness in the past by examining details relating to a >90 per cent shift in the genetic ancestry of populations who inhabited Chalcolithic and Early Bronze Age Britain (c. 2450–1600 bc). While this outcome was certainly influenced by movements of communities carrying novel ancestries into Britain from continental Europe, it was unlikely to have been a simple, rapid process, potentially taking up to 16 generations, during which time there is evidence for the synchronous persistence of groups largely descended from the Neolithic populations. Insofar as genetic relationships can be assumed to have had social meaning, identification of genetic relatives in cemeteries suggests paternal relationships were important, but there is substantial variability in how genetic ties were referenced and little evidence for strict patrilocality or female exogamy.

Much of our current understanding about novel coronavirus disease 2019 (COVID-19) comes from hospitalised patients. However, the spectrum of mild and subclinical disease has implications for population-level screening and control. Forty-nine participants were recruited from a group of 99 adults repatriated from a cruise ship with a high incidence of COVID-19. Respiratory and rectal swabs were tested by polymerase chain reaction (PCR) for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Sera were tested for anti-SARS-CoV-2 antibodies by enzyme-linked immunosorbent assay (ELISA) and microneutralisation assay. Symptoms, viral shedding and antibody response were examined. Forty-five participants (92%) were considered cases based on either positive PCR or positive ELISA for immunoglobulin G. Forty-two percent of cases were asymptomatic. Only 15% of symptomatic cases reported fever. Serial respiratory and rectal swabs were positive for 10% and 5% of participants respectively about 3 weeks after median symptom onset. Cycle threshold values were high (range 31–45). Attempts to isolate live virus were unsuccessful. The presence of symptoms was not associated with demographics, comorbidities or antibody response. In closed settings, incidence of COVID-19 could be almost double that suggested by symptom-based screening. Serology may be useful in diagnosis of mild disease and in aiding public health investigations.

In Einstein’s special theory of relativity, all observers measure the speed of light, c, to be the same. However, this refers to the round-trip speed, where a clock at the origin times the outward and return trip of light reflecting off a distant mirror. Measuring the one-way speed of light is fraught with issues of clock synchronisation, and, as long as the average speed of light remains c, the speeds on the outward and return legs could be different. One objection to this anisotropic speed of light is that views of the distant universe would be different in different directions, especially with regard to the ages of observed objects and the smoothness of the Cosmic Microwave Background. In this paper, we explore this in the Milne universe, the limiting case of a Friedmann–Robertson–Walker universe containing no matter, radiation, or dark energy. Given that this universe is empty, it can be mapped onto flat Minkowski space-time and so can be explored in terms of the one-way speed of light. The conclusion is that the presence of an anisotropic speed of light leads to anisotropic time dilation effects, and hence observers in the Milne universe would be presented with an isotropic view of the distant cosmos.

A study of turbulent impurity transport by means of quasilinear and nonlinear gyrokinetic simulations is presented for Wendelstein 7-X (W7-X). The calculations have been carried out with the recently developed gyrokinetic code stella. Different impurity species are considered in the presence of various types of background instabilities: ion temperature gradient (ITG), trapped electron mode (TEM) and electron temperature gradient (ETG) modes for the quasilinear part of the work; ITG and TEM for the nonlinear results. While the quasilinear approach allows one to draw qualitative conclusions about the sign or relative importance of the various contributions to the flux, the nonlinear simulations quantitatively determine the size of the turbulent flux and check the extent to which the quasilinear conclusions hold. Although the bulk of the nonlinear simulations are performed at trace impurity concentration, nonlinear simulations are also carried out at realistic effective charge values, in order to know to what degree the conclusions based on the simulations performed for trace impurities can be extrapolated to realistic impurity concentrations. The presented results conclude that the turbulent radial impurity transport in W7-X is mainly dominated by ordinary diffusion, which is close to that measured during the recent W7-X experimental campaigns. It is also confirmed that thermodiffusion adds a weak inward flux contribution and that, in the absence of impurity temperature and density gradients, ITG- and TEM-driven turbulence push the impurities inwards and outwards, respectively.

Political districts may be drawn to favor one group or political party over another, or gerrymandered. A number of measurements have been suggested as ways to detect and prevent such behavior. These measures give concrete axes along which districts and districting plans can be compared. However, measurement values are affected by both noise and the compounding effects of seemingly innocuous implementation decisions. Such issues will arise for any measure. As a case study demonstrating the effect, we show that commonly used measures of geometric compactness for district boundaries are affected by several factors irrelevant to fairness or compliance with civil rights law. We further show that an adversary could manipulate measurements to affect the assessment of a given plan. This instability complicates using these measurements as legislative or judicial standards to counteract unfair redistricting practices. This paper accompanies the release of packages in C++, Python, and R that correctly, efficiently, and reproducibly calculate a variety of compactness scores.

The evolution of multiple herbicide-resistant weeds, including Palmer amaranth, has necessitated the implementation of an integrated weed management (IWM) program. Understanding weed emergence patterns is critical for developing effective IWM strategies. The objective of this study was to evaluate the effect of tillage timings and residual herbicides on cumulative emergence and emergence pattern of Palmer amaranth. Field experiments were conducted in 2015 and 2016 in a field naturally infested with photosystem (PS) II and 4-hydroxyphenylpyruvate dioxygenase (HPPD) inhibitor-resistant Palmer amaranth near Shickley, Nebraska, in a bare ground study, with no crop planted in the plots, although residues from the preceding corn crop were present on the soil surface. Treatments consisted of shallow tillage timings (early, mid, and late), three premix corn or soybean residual herbicides, and a nontreated control. The Weibull function was fitted to cumulative Palmer amaranth emergence with day of year (DOY) and thermal time (TT) as independent variables. Year by treatment interaction was significant for time to 10%, 25%, 50%, 75%, and 90% Palmer amaranth emergence and cumulative emergence. The majority of Palmer amaranth seedlings emerged early, following early tillage with 90% cumulative emergence occurring on DOY 172 compared with DOY 210 to 212 for mid- and late-tillage, and DOY 194 for the nontreated control in 2015. In 2016, 90% of cumulative emergence following early-, mid-, and late-tillage (DOYs 201 to 211) were similar, and that of the nontreated control (DOY 188) was similar to that of early tillage. Nontreated control and PRE herbicide treatments had similar DOY values for 90% emergence in both years. The number of emerged Palmer amaranth seedlings over the season was higher with shallow tillage than no tillage or with the use of PRE herbicides.

Callery pear (Pyrus calleryana Decne.) is rapidly spreading in the United States, gaining attention in the last two decades as a serious invasive pest. Recommended control methods include foliar, basal bark, cut stump, and hack-and-squirt application of herbicides, but there are few published studies with replicated data on efficacy. Four readily available herbicidal active ingredients and a combination of two active ingredients were tested for control efficacy against P. calleryana in old-field areas and loblolly pine (Pinus taeda L.) understory. Basal bark applications (triclopyr, triclopyr + aminopyralid), foliar applications (glyphosate, imazapyr), and a soil application (hexazinone) effectively killed P. calleryana with the exception of hexazinone at one site, where rainfall may not have been optimal. Foliar application of glyphosate provided the most consistent control. Our results demonstrate efficacy of registered herbicide formulations for P. calleryana control in two geographic locations and two habitat types. The need for development of integrated pest management programs for P. calleryana is discussed.

The Victorian City of London’s financial center expanded and renewed its building infrastructure virtually unimpeded by considerations of urban preservation, conservation, or public opinion. The next phase of massive rebuilding, during the long post-1945 boom, appeared likely to follow the same pattern. However, by the mid-1960s, the freedom of City office owner-occupiers and developers to do as they wished with their buildings had become substantially constrained by rising conservationist sentiment. This paper explores this process through the history of the design, building, and eventual aborted demolition of Gibson Hall, the Bishopsgate headquarters of National Provincial Bank for over a century. This paper charts the life of Gibson Hall, in particular its conception, design, and, ultimately, its attempted redevelopment. We also consider the long-term consequences of the rebalancing between economic and conservation objectives for the nature of British urban redevelopment and the adoption of a “throwaway” business headquarters style—to remove any risk of popular support for preservation.

Sentiment analysis is directly affected by compositional phenomena in language that act on the prior polarity of the words and phrases found in the text. Negation is the most prevalent of these phenomena, and in order to correctly predict sentiment, a classifier must be able to identify negation and disentangle the effect that its scope has on the final polarity of a text. This paper proposes a multi-task approach to explicitly incorporate information about negation in sentiment analysis, which we show outperforms learning negation implicitly in an end-to-end manner. We describe our approach, a cascading and hierarchical neural architecture with selective sharing of Long Short-term Memory layers, and show that explicitly training the model with negation as an auxiliary task helps improve the main task of sentiment analysis. The effect is demonstrated across several different standard English-language data sets for both tasks, and we analyze several aspects of our system related to its performance, varying types and amounts of input data and different multi-task setups.

Magnetised plasma turbulence can have a multiscale character: instabilities driven by mean temperature gradients drive turbulence at the disparate scales of the ion and the electron gyroradii. Simulations of multiscale turbulence, using equations valid in the limit of infinite scale separation, reveal novel cross-scale interaction mechanisms in these plasmas. In the case that both long-wavelength (ion-gyroradius-scale) and short-wavelength (electron-gyroradius-scale) linear instabilities are driven far from marginal stability, we show that the short-wavelength instabilities are suppressed by interactions with long-wavelength turbulence. Two novel effects contributed to the suppression: parallel-to-the-field-line shearing by the long-wavelength ${{\boldsymbol {E}} \times \boldsymbol {B}}$ flows, and the modification of the background density gradient by the piece of the long-wavelength electron adiabatic response with parallel-to-the-field-line variation. In contrast, simulations of multiscale turbulence where instabilities at both scales are driven near marginal stability demonstrate that when the long-wavelength turbulence is sufficiently collisional and zonally dominated the effect of cross-scale interaction can be parameterised solely in terms of the local modifications to the mean density and temperature gradients. We discuss physical arguments that qualitatively explain how a change in equilibrium drive leads to the observed transition in the impact of the cross-scale interactions.

Background: Rapidly identifying patients colonized with multidrug-resistant organisms (MDROs) upon ICU admission is critical to control and prevent the spread of these pathogens in healthcare facilities. Electronic health records (EHR) provide a rich source of data to predict the likelihood of MDRO colonization at admission, whereas surveillance methods are resource intensive and results are not immediately available. Our objectives were (1) to predict VRE and CRO colonization at ICU admission and (2) to identify patient subpopulations at higher risk for colonization with these MDROs. Methods: We conducted a retrospective analysis of patients aged ≥16 years admitted to any of 6 medical or surgical intensive care units (ICU) in the Johns Hopkins Hospital from July 1, 2016, through June 30, 2018. Perirectal swabs were collected at ICU unit admission and were tested for VRE and CRO. Patient demographic data, prior hospitalizations, and preadmission clinical data, including prior medication administration, prior diagnoses, and prior procedures, were extracted to develop prediction models. We employed the machine-learning algorithms logistic regression (LR), random forest (RF), and XGBoost (XG). The sum of sensitivity and specificity (ie, Youden’s index) was selected as the performance metric. Results: In total, 5,033 separate ICU visits from 3,385 patients were included, where 555 (11%) and 373 (7%) admissions tested positive for VRE and CRO, respectively. The sensitivity and specificity of our models for VRE were 78% and 80% with LR, 80% and 82% with RF, and 77% and 87% with XG. Predictions for CRO were not as precise, with LR at 73% and 53%, RF at 81% and 48%, and XG at 69% and 61%. The XG algorithm was the best-performing algorithm for both VRE and CRO. Prior VRE colonization, recent (<180 days) long-term care facility stay, and prior hospitalization >60 days were the key predictors for VRE, whereas the primary predictor for CRO colonization was prior carbapenem use. Conclusions: We demonstrated that EHR data can be used to predict >75% of VRE positive cases with a <15% false-positive rate and ~70% of CRO cases with a <40% false-positive rate. Future studies using larger sample sizes may improve the prediction accuracy and inform model generalizability across sites and thus reduce the risk of transmission of MDROs by rapidly identifying MDRO-colonized patients.

Funding: This work was funded by the Centers for Disease Control and Prevention (CDC) Epicenters Program (Grant Number 1U54CK000447) and the CDC MInD-Healthcare Program (Grant Number 1U01CK000536).

Disclosures: Aaron Milstone, BD (consulting)

Downloading a mobile health (m-health) app on your smartphone does not mean you will ever use it. Telling another person about an app does not mean you like it. Using an online intervention does not mean it has had an impact on your well-being. Yet we consistently rely on downloads, clicks, ‘likes’ and other usage and popularity metrics to measure m-health app engagement. Doing so misses the complexity of how people perceive and use m-health apps in everyday life to manage mental health conditions. This article questions commonly used behavioural metrics of engagement in mental health research and care, and proposes a more comprehensive approach to measuring in-app engagement.

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.