Legacy and Novel Per- and Polyfluoroalkyl Substances in Juvenile Seabirds from the U.S. Atlantic Coast

Per- and polyfluoroalkyl substances (PFAS) are anthropogenic, globally distributed chemicals. Legacy PFAS, including perfluorooctane sulfonate (PFOS), have been regularly detected in marine fauna but little is known about their current levels or the presence of novel PFAS in seabirds. We measured 36 emerging and legacy PFAS in livers from 31 juvenile seabirds from Massachusetts Bay, Narragansett Bay, and the Cape Fear River Estuary (CFRE), United States. PFOS was the major legacy perfluoroalkyl acid present, making up 58% of concentrations observed across all habitats (range: 11–280 ng/g). Novel PFAS were confirmed in chicks hatched downstream of a fluoropolymer production site in the CFRE: a perfluorinated ether sulfonic acid (Nafion byproduct 2; range: 1–110 ng/g) and two perfluorinated ether carboxylic acids (PFO4DA and PFO5DoDA; PFO5DoDA range: 5–30 ng/g). PFOS was inversely associated with phospholipid content in livers from CFRE and Massachusetts Bay individuals, while δ 13C, an indicator of marine versus terrestrial foraging, was positively correlated with some long-chain PFAS in CFRE chick livers. There is also an indication that seabird phospholipid dynamics are negatively impacted by PFAS, which should be further explored given the importance of lipids for seabirds

Evaluation of individual and ensemble probabilistic forecasts of COVID-19 mortality in the United States

Short-term probabilistic forecasts of the trajectory of the COVID-19 pandemic in the United States have served as a visible and important communication channel between the scientific modeling community and both the general public and decision-makers. Forecasting models provide specific, quantitative, and evaluable predictions that inform short-term decisions such as healthcare staffing needs, school closures, and allocation of medical supplies. Starting in April 2020, the US COVID-19 Forecast Hub (https://covid19forecasthub.org/) collected, disseminated, and synthesized tens of millions of specific predictions from more than 90 different academic, industry, and independent research groups. A multimodel ensemble forecast that combined predictions from dozens of groups every week provided the most consistently accurate probabilistic forecasts of incident deaths due to COVID-19 at the state and national level from April 2020 through October 2021. The performance of 27 individual models that submitted complete forecasts of COVID-19 deaths consistently throughout this year showed high variability in forecast skill across time, geospatial units, and forecast horizons. Two-thirds of the models evaluated showed better accuracy than a naïve baseline model. Forecast accuracy degraded as models made predictions further into the future, with probabilistic error at a 20-wk horizon three to five times larger than when predicting at a 1-wk horizon. This project underscores the role that collaboration and active coordination between governmental public-health agencies, academic modeling teams, and industry partners can play in developing modern modeling capabilities to support local, state, and federal response to outbreaks

The United States COVID-19 Forecast Hub dataset

Academic researchers, government agencies, industry groups, and individuals have produced forecasts at an unprecedented scale during the COVID-19 pandemic. To leverage these forecasts, the United States Centers for Disease Control and Prevention (CDC) partnered with an academic research lab at the University of Massachusetts Amherst to create the US COVID-19 Forecast Hub. Launched in April 2020, the Forecast Hub is a dataset with point and probabilistic forecasts of incident cases, incident hospitalizations, incident deaths, and cumulative deaths due to COVID-19 at county, state, and national, levels in the United States. Included forecasts represent a variety of modeling approaches, data sources, and assumptions regarding the spread of COVID-19. The goal of this dataset is to establish a standardized and comparable set of short-term forecasts from modeling teams. These data can be used to develop ensemble models, communicate forecasts to the public, create visualizations, compare models, and inform policies regarding COVID-19 mitigation. These open-source data are available via download from GitHub, through an online API, and through R packages

Rethinking place-making: aligning placeness factors with perceived urban design qualities (PUDQs) to improve the built environment in historical district

Understanding the concept of place is critically important for urban design and place-making practice, and this research attempted to investigate the pathways by which perceived urban design qualities (PUDQs) influence placeness factors in the Chinese context. Twelve hypotheses were developed and combined in a structural equation model for validation. The Tanhualin historical district in Wuhan, China was selected for the analysis. As a result, place attachment was verified as a critical bridge factor that mediated the influence of PUDQs on place satisfaction. Among the five selected PUDQs, walkability and space quality were revealed as the most influential factors associated with place attachment and place satisfaction. Accessibility was actually indirectly beneficial to place-making via the mediation of walkability. Corresponding implications and strategies were discussed to maintain the sense of place for historic districts

Coordination polymers utilizing N-oxide functionalised host ligands

Pyridyl functionalized host molecules are oxidized to their N-oxide analogues and form a series of coordination polymers and discrete complexes with transition metal cations. Complex {[Ag3(NMP)6(L1)2]·3(ClO4)}∞ where L1 = tris(isonicotinoyl-N-oxide)cyclotriguaiacylene, NMP = N-methylpyrrolidone, is a three-dimensional (3-D) 3,6-connected coordination polymer of pyrite-like (pyr) topology and features ligand unsupported argentophilic interactions, while two-dimensional (2-D) 3,6-connected coordination polymers with the rarely reported kagome dual (kgd) topology are found for [M(L1)2]2+ where M = Zn, Cd, Cu. Ligand L2 = tris(nicotinoyl-N-oxide)cyclotriguaiacylene forms a 2-D coordination polymer with 44 (sql) grid topology in complexes {[M(L2)2(DMF)2]·2ClO4·8(DMF)}∞ M = Cd or Cu, DMF = N,N′-dimethylformamide, and a double-linked chain structure in {[Co(L2)2(DMF)2]·2NO3·4(DMF)·H2O}∞, and both types of structure feature hand-shake self-inclusion motifs either within or between the polymers. 2-D coordination networks with 63 (hcb) topologies are found in complexes {[M(L3)(NO3)2]·2(DMF)}∞ (M = Cd, Zn) and {[Cu5(L3)2Cl10(NMP)4]}∞ where L3 = tris(2-pyridylmethyl)cyclotriguaiacylene, while [Ag2(L3)2(NMP)4]·2(BF4)·2(NMP) has a discrete dimeric structure which again shows hand-shake host–guest interactions supported by π–π stacking