Significance This paper compares the probabilistic accuracy of short-term forecasts of reported deaths due to COVID-19 during the first year and a half of the pandemic in the United States. Results show high variation in accuracy between and within stand-alone models and more consistent accuracy from an ensemble model that combined forecasts from all eligible models. This demonstrates that an ensemble model provided a reliable and comparatively accurate means of forecasting deaths during the COVID-19 pandemic that exceeded the performance of all of the models that contributed to it. This work strengthens the evidence base for synthesizing multiple models to support public-health action.

A host supramolecular structure consisting of bis-(2,2':6',2' '-terpyridine)-4'-oxyhexadecane (BT-O-C16) is shown to respond to guest molecules in dramatic ways, as observed by using scanning tunneling microscopy (STM) on a highly oriented pyrolytic graphite surface under ambient conditions. It is observed that small linear molecules can be encapsulated within the host supramolecular lattice. The characteristics of the host structure were nearly unaffected by the encapsulated guest molecules of terphthalic acid (TPA) dimers, whereas appreciable changes in cavity dimension can be observed with azobenzene-4,4'-dicarboxylic acid. The STM study and density functional theory (DFT) analysis reveal that intermolecular hydrogen bonding interaction plays an essential role in forming the assembling structures. The difference in guest molecule length is considered the important cause for the different guest-host complexes.

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 multi-model ensemble forecast that combined predictions from dozens of different research 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-week horizon 3-5 times larger than when predicting at a 1-week 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. Significance Statement This paper compares the probabilistic accuracy of short-term forecasts of reported deaths due to COVID-19 during the first year and a half of the pandemic in the US. Results show high variation in accuracy between and within stand-alone models, and more consistent accuracy from an ensemble model that combined forecasts from all eligible models. This demonstrates that an ensemble model provided a reliable and comparatively accurate means of forecasting deaths during the COVID-19 pandemic that exceeded the performance of all of the models that contributed to it. This work strengthens the evidence base for synthesizing multiple models to support public health action.

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Pyridyl-substituted oxalamides, L 1 (4-pyCH 2 NHCOCONHCH 2 py-4), L 2 (3-pyCH 2 NHCOCONHCH 2 py-3), and L 3 (2-pyCH 2 NHCOCONHCH 2 py-2), with HgI 2 and/or CuBr 2 , form three new supramolecular complexes, [Hg 3 L, and [Hg(L 3 ) 2 I 2 ] ∞ (3), respectively. The complexes 1-3 are aligned by the oxalamide-oxalamide N-H • • • O hydrogen bonds between layers, and their crystal structures have been determined by single-crystal X-ray diffraction. Complex 1 forms a two-dimensional (2D) zigzag sheet architecture extending along the c-direction bridged by L 1 ligand and HgI 2 . Complex 2 forms an interesting planar 2D (4,4) network with the uncoordinated Branions and H 2 O molecules located in the cavities. Complex 3 forms [2 + 2] metallomacrocycles, which are linked with the µ 2 -bridged I atom and stacked together by intermolecular oxalamide-oxalamide hydrogen bonds and by edge-to-face π-stacking between the pyridyl rings to form the desired supramolecular tubular structure along the a-axis. After the removal of the solvent molecules, solid 2 exhibits a permanent porosity verified by a N 2 sorption isotherm with a N 2 uptake of approximately 1258 cm 3 /g (STP) and a Langmuir surface area of 2102 m 2 /g.