Despite nearly two centuries of actively stylizing itself as above the partisan fray of banal politics, the US Supreme Court faces increasing scrutiny over its ideological nature, ethical lapses, and perceived disconnection from democratic accountability. This article explores potential reforms including ethics guidelines, public affairs offices, and term limits to enhance the Court’s legitimacy. It also examines trends in judicial decision making, the Court’s relationship with public opinion, and the influence of identity politics on judicial perceptions through an examination of the scholarship on the Court. The article concludes by emphasizing the need for ongoing research and methodological innovation to address these challenges and ensure the Court’s role in American democracy.

We present the Evolutionary Map of the Universe (EMU) survey conducted with the Australian Square Kilometre Array Pathfinder (ASKAP). EMU aims to deliver the touchstone radio atlas of the southern hemisphere. We introduce EMU and review its science drivers and key science goals, updated and tailored to the current ASKAP five-year survey plan. The development of the survey strategy and planned sky coverage is presented, along with the operational aspects of the survey and associated data analysis, together with a selection of diagnostics demonstrating the imaging quality and data characteristics. We give a general description of the value-added data pipeline and data products before concluding with a discussion of links to other surveys and projects and an outline of EMU’s legacy value.

Plateau icefields are large stores of fresh water, preconditioned to enhanced mass loss due to their gently sloping accumulation areas. Accurate modelling of their mass balance is therefore crucial for sea-level rise projections. Here, we use the COupled Snowpack and Ice surface energy and mass-balance model in PYthon (COSIPY) to simulate historical and future mass balance of the Juneau Icefield, Alaska – a high elevation (>1200 m) plateau icefield. We force the model with dynamically downscaled climate simulations, for both past and future (RCP 8.5) conditions. The icefield's mass balance decreased from a mean of −0.22 ± 0.38 m w.e. a−1 (1981–2019) to −1.52 ± 0.27 m w.e. a−1 (2031–2060), with many glaciers shifting from positive to negative mass balances at the start of the 21st century. This mass loss is attributed to projected rising air temperatures and reduced snowfall, causing the equilibrium line altitude to rise and triggering albedo and melt-elevation feedbacks. These processes exacerbate melt, potentially leading to increased glacier disconnections at icefalls.

Despite the Supreme Court’s lack of direct electoral accountability, voters may factor its outputs into their voting decisions because elected representatives can affect the Court’s powers and composition. In this paper, we uncover an ironic predicament that faces candidates running on reforming this institution. Citizens who possess higher levels of diffuse support for the Court are more likely to rank it as an important factor in their voting logic. But because this diffuse support has sorted along partisan lines, candidate messaging about reform may not motivate partisans who have lost support for the Court because they view it as less important than other pressing issues. Thus, although Democrats are sympathetic to reform, Democratic candidates may have weak incentives to promote reform given low levels of diffuse support among their constituents. This dynamic mitigates against the possibility of a public or congressional backlash against the Court, preserving the status quo.

We present a classification methodology that jointly assigns to a decision maker a best-fitting decision strategy for a set of choice data as well as a best-fitting stochastic specification of that decision strategy. Our methodology utilizes normalized maximum likelihood as a model selection criterion to compare multiple, possibly non-nested, stochastic specifications of candidate strategies. In addition to single strategy with “error” stochastic specifications, we consider mixture specifications, i.e., strategies comprised of a probability distribution over multiple strategies. In this way, our approach generalizes the classification framework of Bröder and Schiffer (2003a). We apply our methodology to an existing dataset and find that some decision makers are best fit by a single strategy with varying levels of error, while others are best described as using a mixture specification over multiple strategies.

The impact of Indigenous populations on historical fire regimes has been controversial and beset by mismatches in the geographic scale of paleofire reconstructions and the scale of land-use behaviors. It is often assumed that anthropogenic burning is linearly related to population density and not different cultural practices. Here we take an off-site geoarchaeology strategy to reconstruct variability in historical fire regimes (<1000 years ago) at geographic scales that match the archaeological, ethnohistorical, and oral tradition evidence for variability in the intensity of Indigenous land use by two different cultural groups (Ancestral Pueblo and Western Apache). We use multiple, independent proxies from three localities in ponderosa pine (Pinus ponderosa) forests in east-Central Arizona to reconstruct fire regime variability during four phases of cultural use of different intensities. Elevated charcoal with domesticate pollen (Zea spp.) but otherwise unchanged forest pollen assemblages characterized intensive land use by Ancestral Pueblo people during an early phase, suggesting fire use to support agricultural activities. By contrast, a phase of intensive pre-reservation Western Apache land use corresponded to little change in charcoal, but had elevated ash-derived phosphorus and elevated grass and ruderal pollen suggestive of enhanced burning in fine fuels to promote economically important wild plants.

Implementation assessment plans are crucial for clinical trials to achieve their full potential. Without a proactive plan to implement trial results, it can take decades for one-fifth of effective interventions to be adopted into routine care settings. The Veterans Health Administration Office of Research and Development is undergoing a systematic transformation to embed implementation planning in research protocols through the Cooperative Studies Program, its flagship clinical research program. This manuscript has two objectives: 1) to introduce an Implementation Planning Assessment (IPA) Tool that any clinical trialist may use to facilitate post-trial implementation of interventions found to be effective and 2) to provide a case study demonstrating the IPA Tool’s use. The IPA Tool encourages study designers to initially consider rigorous data collection to maximize acceptability of the intervention by end-users. It also helps identify and prepare potential interested parties at local and national leadership levels to ensure, upon trial completion, interventions can be integrated into programs, technologies, and policies in a sustainable way. The IPA Tool can alleviate some of the overwhelming nature of implementation science by providing a practical guide based on implementation science principles for researchers desiring to scale up and spread effective, clinical trial-tested interventions to benefit patients.

Genes associated with educational attainment may be related to or interact with adolescent alcohol, tobacco and cannabis use. Potential gene–environment interplay between educational attainment polygenic scores (EA-PGS) and adolescent alcohol, tobacco, and cannabis use was evaluated with a series of regression models fitted to data from a sample of 1871 adult Australian twins. All models controlled for age, age2, cohort, sex and genetic ancestry as fixed effects, and a genetic relatedness matrix was included as a random effect. Although there was no evidence that adolescent alcohol, tobacco or cannabis use interacted with EA-PGS to influence educational attainment, there was a significant, positive gene–environment correlation with adolescent alcohol use at all PGS thresholds (ps <.02). Higher EA-PGS were associated with an increased likelihood of using alcohol as an adolescent (ΔR2 ranged from 0.5% to 1.1%). The positive gene–environment correlation suggests a complex relationship between educational attainment and alcohol use that is due to common genetic factors.

A growing body of research connects Christian nationalism—a preference for a religiously conservative political regime—to social and political beliefs. This paper raises questions about the validity of a popular scale used to measure those attitudes. I begin by exploring the factor structure of the six-item Christian nationalism index. I then show how semi-supervised machine learning can be used to illustrate classification problems within that scale. Finally, I demonstrate that this index performs poorly at the interval level, a combination of measurement error and the sorting out of religious and political preferences. These attitudes have become so bound up in conventional politics that they often exhibit a threshold rather than a linear relationship to political preferences. I conclude with an appeal for care in matching theory to empirics: Christian nationalism is a prominent political theology, but research must grapple with the limitations of prevailing measurement tools when operationalizing it.

During the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) intracellular life-cycle, two large polyproteins, pp1a and pp1ab, are produced. Processing of these by viral cysteine proteases, the papain-like protease (PLpro) and the chymotrypsin-like 3C-like protease (3CL-pro) release non-structural proteins necessary for the establishment of the viral replication and transcription complex (RTC), crucial for viral replication. Hence, these proteases are considered prime targets against which anti-coronavirus disease 2019 (COVID-19) drugs could be developed. Here, we describe the expression of a highly soluble and functionally active recombinant 3CL-pro using Escherichia coli BL21 cells. We show that the enzyme functions in a dimeric form and exhibits an unexpected inhibitory profile because its activity is potently blocked by serine rather than cysteine protease inhibitors. In addition, we assessed the ability of our 3CL-pro to function as a carrier for the receptor binding domain (RBD) of the Spike protein. The co-expressed chimeric protein, 3CLpro-RBD, did not exhibit 3CL-pro activity, but its enhanced solubility made purification easier and improved RBD antigenicity when tested against serum from vaccinated individuals in ELISAs. Chimeric proteins containing the 3CL-pro could represent an innovative approach to developing new COVID-19 vaccines.

Research among non-industrial societies suggests that body kinematics adopted during running vary between groups according to the cultural importance of running. Among groups in which running is common and an important part of cultural identity, runners tend to adopt what exercise scientists and coaches consider to be good technique for avoiding injury and maximising performance. In contrast, among groups in which running is not particularly culturally important, people tend to adopt suboptimal technique. This paper begins by describing key elements of good running technique, including landing with a forefoot or midfoot strike pattern and leg oriented roughly vertically. Next, we review evidence from non-industrial societies that cultural attitudes about running associate with variation in running techniques. Then, we present new data from Tsimane forager–horticulturalists in Bolivia. Our findings suggest that running is neither a common activity among the Tsimane nor is it considered an important part of cultural identity. We also demonstrate that when Tsimane do run, they tend to use suboptimal technique, specifically landing with a rearfoot strike pattern and leg protracted ahead of the knee (called overstriding). Finally, we discuss processes by which culture might influence variation in running techniques among non-industrial societies, including self-optimisation and social learning.