The text of the US Constitution appears to require that individual states, to the extent that they are ever allowed to conclude agreements with foreign governments, must obtain congressional approval. In practice, however, states conclude many agreements with foreign governments, including with Canada and its provinces, and they almost never seek congressional approval. This practice is an illustration of both the importance of federalism in US foreign relations and the significant role played by historical practice in informing US constitutional interpretation. The phenomenon of state international agreements assumed new prominence in 2019 when the Trump administration sued to challenge a climate change agreement that the state of California had made with Québec. Despite this challenge, for the most part, neither Congress nor the executive branch has resisted the growth in state international agreements. This acquiescence could change as countries like China target US states in an effort to work around strained relations with the US national government and as states become more assertive in resisting the national government’s foreign policies. In any event, the practice of state international agreements unapproved by Congress rests in part on a distinction between binding and non-binding agreements that deserves greater scrutiny under both domestic and international law.

The problems with polygenic scores (PGSs) have been understated. The fact that they are ancestry-specific means that biases related to sociodemographic factors would be impossible to avoid. Additionally, the requirement to obtain DNA would have profound impacts on study design and required resources, as well as likely introducing recruitment bias. PGSs are unhelpful for social science research.

One of the largest contributors to uncertainty in predictions of sea-level rise from ice-sheet models is a lack of knowledge about the bed topography beneath ice sheets. Bed topography maps are normally made by interpolating between linear radar surveys using methods that include kriging, mass conservation and flowline diffusion, all of which may miss influential mesoscale (2–30 km) bedforms. Previous works have explored an Ice-Flow Perturbation Analysis (IFPA) approach for estimating bed topography using the surface expression of these mesoscale bedforms. Using regions of Pine Island Glacier that have been intensively surveyed by ice-penetrating radar as test sites, and a refined IFPA methodology, we find that IFPA detects bedforms capable of influencing ice flow which are not represented in Bedmachine Antarctica and other interpolated bed products. We further explore the ability of IFPA to estimate relative bed slipperiness, finding higher slipperiness in the main trunk and tributaries. Alongside other methods which estimate ice thickness, bed topography maps from IFPA have the potential to constrain projections of future sea-level rise, especially where radar data are sparse.

A wall-mounted, far-ultraviolet-C light technology reduced aerosolized bacteriophage MS2 by >3 log10 plaque-forming units within 30 minutes. Vegetative bacterial pathogens on steel disk carriers in the center of the room were reduced by >3 log10 after 45 minutes of exposure, but Candida auris and Clostridioides difficile spores were not.

We tested the effectiveness of 23 disinfectants used in healthcare facilities against isolates from the 4 major clades of Candida auris. Sporicidal disinfectants were consistently effective, whereas quaternary-ammonium disinfectants had limited activity. Quaternary-ammonium–alcohol and hydrogen-peroxide–based disinfectants varied in effectiveness against C. auris.

Polarization makes it difficult to form positive relationships across existing groups. Decreasing polarization may improve political discourse around the world. Polarization can be modeled on a social network as structural balance, where the network is composed of groups with positive links between all individuals in the group and negative links with all others. Previous work shows that incorporating attributes of individuals usually makes structural balance, and hence polarization, harder to achieve. That work examines only a limited number and types of attributes. We present a generalized model and a simulation framework to analyze the effect of any type of attribute, including analytically as long as an expected value can be written for the type of attribute. As attributes, we consider people’s (approximately) immutable characteristics (e.g., race, wealth) and such opinions that change more slowly than relationships (e.g., political preferences). We detail and analyze five classes of attributes, recapitulating the results of previous work in this framework and extending it. While it is easier to prevent than to destabilize polarization, we find that usually the most effective at both are continuous attributes, followed by ordered attributes and, finally, binary attributes. The effectiveness of unordered attributes varies depending on the magnitude of negative impact of having differing attributes but is smaller than of continuous ones. Testing the framework on network structures containing communities revealed that destroying polarization may require introducing local tensions. This model could be used by policymakers, among others, to prevent and design effective interventions to counteract polarization.