Early in the COVID-19 pandemic, the World Health Organization stressed the importance of daily clinical assessments of infected patients, yet current approaches frequently consider cross-sectional timepoints, cumulative summary measures, or time-to-event analyses. Statistical methods are available that make use of the rich information content of longitudinal assessments. We demonstrate the use of a multistate transition model to assess the dynamic nature of COVID-19-associated critical illness using daily evaluations of COVID-19 patients from 9 academic hospitals. We describe the accessibility and utility of methods that consider the clinical trajectory of critically ill COVID-19 patients.

International relations scholarship concerns dyads, yet standard modeling approaches fail to adequately capture the data generating process behind dyadic events and processes. As a result, they suffer from biased coefficients and poorly calibrated standard errors. We show how a regression-based approach, the Additive and Multiplicative Effects (AME) model, can be used to account for the inherent dependencies in dyadic data and glean substantive insights in the interrelations between actors. First, we conduct a simulation to highlight how the model captures dependencies and show that accounting for these processes improves our ability to conduct inference on dyadic data. Second, we compare the AME model to approaches used in three prominent studies from recent international relations scholarship. For each study, we find that compared to AME, the modeling approach used performs notably worse at capturing the data generating process. Further, conventional methods misstate the effect of key variables and the uncertainty in these effects. Finally, AME outperforms standard approaches in terms of out-of-sample fit. In sum, our work shows the consequences of failing to take the dependencies inherent to dyadic data seriously. Most importantly, by better modeling the data generating process underlying political phenomena, the AME framework improves scholars’ ability to conduct inferential analyses on dyadic data.

The coronavirus disease 2019 (COVID-19) has greatly impacted health-care systems worldwide, leading to an unprecedented rise in demand for health-care resources. In anticipation of an acute strain on established medical facilities in Dallas, Texas, federal officials worked in conjunction with local medical personnel to convert a convention center into a Federal Medical Station capable of caring for patients affected by COVID-19. A 200,000 square foot event space was designated as a direct patient care area, with surrounding spaces repurposed to house ancillary services. Given the highly transmissible nature of the novel coronavirus, the donning and doffing of personal protective equipment (PPE) was of particular importance for personnel staffing the facility. Furthermore, nationwide shortages in the availability of PPE necessitated the reuse of certain protective materials. This article seeks to delineate the procedures implemented regarding PPE in the setting of a COVID-19 disaster response shelter, including workspace flow, donning and doffing procedures, PPE conservation, and exposure event protocols.

Good education requires student experiences that deliver lessons about practice as well as theory and that encourage students to work for the public good—especially in the operation of democratic institutions (Dewey 1923; Dewy 1938). We report on an evaluation of the pedagogical value of a research project involving 23 colleges and universities across the country. Faculty trained and supervised students who observed polling places in the 2016 General Election. Our findings indicate that this was a valuable learning experience in both the short and long terms. Students found their experiences to be valuable and reported learning generally and specifically related to course material. Postelection, they also felt more knowledgeable about election science topics, voting behavior, and research methods. Students reported interest in participating in similar research in the future, would recommend other students to do so, and expressed interest in more learning and research about the topics central to their experience. Our results suggest that participants appreciated the importance of elections and their study. Collectively, the participating students are engaged and efficacious—essential qualities of citizens in a democracy.

In a recent essay, Harker and coauthors stated that considering herbicide resistance as a wicked problem “without clear causes or solutions” ignores what weed scientists know about the biology and management of herbicide-resistant weeds. In this response, we argue that this misrepresents what is meant by “wicked” and that the wicked problem concept is valuable in understanding the multifaceted nature of herbicide resistance as a human-caused phenomenon.

Herbicides are the foundation of weed control in commercial crop-production systems. However, herbicide-resistant (HR) weed populations are evolving rapidly as a natural response to selection pressure imposed by modern agricultural management activities. Mitigating the evolution of herbicide resistance depends on reducing selection through diversification of weed control techniques, minimizing the spread of resistance genes and genotypes via pollen or propagule dispersal, and eliminating additions of weed seed to the soil seedbank. Effective deployment of such a multifaceted approach will require shifting from the current concept of basing weed management on single-year economic thresholds.

ZnO nanowire (NW) arrays were examined with Transmission Electron Microscopy (TEM) in cross-section after preparation by Focused Ion Beam (FIB) milling. This technique revealed that ZnO nanowires grown using a Au catalyzed vapor technique typically have Au particles at the NW tips, and also randomly dispersed across the base crystal growth that joins adjacent NWs. It is shown the adjacent NWs and the combined base growth is one crystal structure which can be used as a back electrical contact making fabrication of vertical array devices possible. However, the base growth displays detrimental features such as embedded Au particles and lattice defects which can affect the electrical output through depletion regions and scattering centers. In an effort to overcome these problems we investigate a growth method that is nucleated through a minor alteration of the a-plane sapphire surface roughness via a weak chemical etch. Observations of various stages of the growth show the growth nucleates as separate nanoislands that grow in c-plane alignment with Sapphire (1-210), and as growth continues these islands meet and form a polycrystalline film. Further growth initiates nanowire growth and the formation of a single crystal base layer and NW structure that can cover several square millimeter’s. This allows high quality arrays that are relatively free from defects to be formed without any metals contamination and ready for further device processing.

Low seed set is a serious problem in seed orchards of lodgepole pine (Pinus contorta var. latifolia Engelmann) in the southern interior of British Columbia. We tested the hypothesis that Leptoglossus occidentalis Heidemann is responsible for the low seed set. Cones enclosed in insect exclusion bags as part of a pollination experiment produced significantly more filled seeds per cone than cones that were not bagged. In a separate bagging experiment, cones that were enclosed with a L. occidentalis female and her progeny produced only about one filled seed per cone, compared with about 28 seeds in bagged control cones. Changes in microclimate associated with the use of bags did not appear to be responsible for the observed increase in seed set in bagged cones. Leptoglossus occidentalis was also excluded from trees using the insecticide fenvalerate. Cones on fenvalerate-treated trees produced > 11 filled seeds per cone, whereas water-treated (control) cones produced < 1.7 filled seeds. These data suggest that L. occidentalis should be considered a serious pest in lodgepole pine seed orchards.

This paper analyzes the properties of the fixed-effects vector decomposition estimator, an emerging and popular technique for estimating time-invariant variables in panel data models with group effects. This estimator was initially motivated on heuristic grounds, and advocated on the strength of favorable Monte Carlo results, but with no formal analysis. We show that the three-stage procedure of this decomposition is equivalent to a standard instrumental variables approach, for a specific set of instruments. The instrumental variables representation facilitates the present formal analysis that finds: (1) The estimator reproduces exactly classical fixed-effects estimates for time-varying variables. (2) The standard errors recommended for this estimator are too small for both time-varying and time-invariant variables. (3) The estimator is inconsistent when the time-invariant variables are endogenous. (4) The reported sampling properties in the original Monte Carlo evidence do not account for presence of a group effect. (5) The decomposition estimator has higher risk than existing shrinkage approaches, unless the endogeneity problem is known to be small or no relevant instruments exist.

Fixed effects vector decomposition (FEVD) is simply an instrumental variables (IV) estimator with a particular choice of instruments and a special case of the well-known Hausman-Taylor IV procedure. Plümper and Troeger (PT) now acknowledge this point and disown the three-stage procedure that previously defined FEVD. Their old recipe for SEs, which has regrettably been used in dozens of published research papers, produces dramatic overconfidence in the estimates. Again PT concede the point and now adopt the standard IV formula for SEs. Knowing that FEVD is an application of IV also has the benefit of focusing attention on the choice of instruments. Now it seems PT claim that the FEVD instruments are always the best choice, on the grounds that one cannot know whether any potential instrument is correlated with the unit effect. One could just as readily make the same specious claim about other estimators, such as ordinary least squares, and support it with similar Monte Carlo assumptions and evidence.