Time-series cross-section (TSCS) data are prevalent in political science, yet many distinct challenges presented by TSCS data remain underaddressed. We focus on how dependence in both space and time complicates estimating either spatial or temporal dependence, dynamics, and effects. Little is known about how modeling one of temporal or cross-sectional dependence well while neglecting the other affects results in TSCS analysis. We demonstrate analytically and through simulations how misspecification of either temporal or spatial dependence inflates estimates of the other dimension’s dependence and thereby induces biased estimates and tests of other covariate effects. Therefore, we recommend the spatiotemporal autoregressive distributed lag (STADL) model with distributed lags in both space and time as an effective general starting point for TSCS model specification. We illustrate with two example reanalyses and provide R code to facilitate researchers’ implementation—from automation of common spatial-weights matrices (W) through estimated spatiotemporal effects/response calculations—for their own TSCS analyses.

Our objective was to quantify the cross-sectional associations between dietary fatty acid (DFA) patterns and cognitive function among Hispanic/Latino adults. This study included data from 8942 participants of the Hispanic Community Health Study/Study of Latinos, a population-based cohort study (weighted age 56·2 years and proportion female 55·2 %). The National Cancer Institute method was used to estimate dietary intake from two 24-h recalls. We derived DFA patterns using principal component analysis with twenty-six fatty acid and total plant and animal MUFA input variables. Global cognitive function was calculated as the average z-score of four neurocognitive tests. Survey linear regression models included multiple potential confounders such as age, sex, education, depressive symptoms, physical activity, energy intake and CVD. DFA patterns were characterised by the consumption of long-chain SFA, animal-based MUFA and trans-fatty acids (factor 1); short to medium-chain SFA (factor 2); very-long-chain n-3 PUFA (factor 3); very-long-chain SFA and plant-based MUFA and PUFA (factor 4). Factor 2 was associated with greater scores for global cognitive function (β = 0·037 (sd 0·012)) and the Digit Symbol Substitution (DSS) (β = 0·56 (sd 0·17)), Brief Spanish English Verbal Learning-Sum (B-SEVLT) (β = 0·23 (sd 0·11)) and B-SEVLT-Recall (β = 0·11 (sd 0·05)) tests (P < 0·05 for all). Factors 1 (β = 0·04 (sd 0·01)) and 4 (β = 0·70 (sd 0·18)) were associated with the DSS test (P < 0·05 for all). The consumption of short to medium-chain SFA may be associated with higher cognitive function among US-residing Hispanic/Latino adults. Prospective studies are necessary to confirm these findings.

Mass asymptomatic SARS-CoV-2 nucleic acid amplified testing of healthcare personnel (HCP) was performed at a large tertiary health system. A low period-prevalence of positive HCP was observed. Of those who tested positive, half had mild symptoms in retrospect. HCP with even mild symptoms should be isolated and tested.

Gravitational waves from coalescing neutron stars encode information about nuclear matter at extreme densities, inaccessible by laboratory experiments. The late inspiral is influenced by the presence of tides, which depend on the neutron star equation of state. Neutron star mergers are expected to often produce rapidly rotating remnant neutron stars that emit gravitational waves. These will provide clues to the extremely hot post-merger environment. This signature of nuclear matter in gravitational waves contains most information in the 2–4 kHz frequency band, which is outside of the most sensitive band of current detectors. We present the design concept and science case for a Neutron Star Extreme Matter Observatory (NEMO): a gravitational-wave interferometer optimised to study nuclear physics with merging neutron stars. The concept uses high-circulating laser power, quantum squeezing, and a detector topology specifically designed to achieve the high-frequency sensitivity necessary to probe nuclear matter using gravitational waves. Above 1 kHz, the proposed strain sensitivity is comparable to full third-generation detectors at a fraction of the cost. Such sensitivity changes expected event rates for detection of post-merger remnants from approximately one per few decades with two A+ detectors to a few per year and potentially allow for the first gravitational-wave observations of supernovae, isolated neutron stars, and other exotica.

On August 17, 2017, the LIGO/VIRGO collaboration detected the first gravitational wave signal coming from the merger of two neutron stars. This groundbreaking discovery, referred to as GW170817, revealed to us how heavy elements, such as gold and platinum, are synthesized through a mechanism known as rapid neutron capture (r-process). In order to fully understand these signals, we need to simulate the resulting accretion disk around a black hole, and its outflows. This task requires efficient computing codes that include general relativity magnetohydrodynamics (GRMHD), neutrino physics, and a model for matter at high densities. We present the implementation of a tabulated equation of state that takes care of matter at high densities and a neutrino leakage scheme that considers the impact of neutrinos into HARM3D, a GRMHD parallelized code. We also apply the tools to a magnetized torus.

Objectives: Studies of neurocognitively elite older adults, termed SuperAgers, have identified clinical predictors and neurobiological indicators of resilience against age-related neurocognitive decline. Despite rising rates of older persons living with HIV (PLWH), SuperAging (SA) in PLWH remains undefined. We aimed to establish neuropsychological criteria for SA in PLWH and examined clinically relevant correlates of SA. Methods: 734 PLWH and 123 HIV-uninfected participants between 50 and 64 years of age underwent neuropsychological and neuromedical evaluations. SA was defined as demographically corrected (i.e., sex, race/ethnicity, education) global neurocognitive performance within normal range for 25-year-olds. Remaining participants were labeled cognitively normal (CN) or impaired (CI) based on actual age. Chi-square and analysis of variance tests examined HIV group differences on neurocognitive status and demographics. Within PLWH, neurocognitive status differences were tested on HIV disease characteristics, medical comorbidities, and everyday functioning. Multinomial logistic regression explored independent predictors of neurocognitive status. Results: Neurocognitive status rates and demographic characteristics differed between PLWH (SA=17%; CN=38%; CI=45%) and HIV-uninfected participants (SA=35%; CN=55%; CI=11%). In PLWH, neurocognitive groups were comparable on demographic and HIV disease characteristics. Younger age, higher verbal IQ, absence of diabetes, fewer depressive symptoms, and lifetime cannabis use disorder increased likelihood of SA. SA reported increased independence in everyday functioning, employment, and health-related quality of life than non-SA. Conclusions: Despite combined neurological risk of aging and HIV, youthful neurocognitive performance is possible for older PLWH. SA relates to improved real-world functioning and may be better explained by cognitive reserve and maintenance of cardiometabolic and mental health than HIV disease severity. Future research investigating biomarker and lifestyle (e.g., physical activity) correlates of SA may help identify modifiable neuroprotective factors against HIV-related neurobiological aging. (JINS, 2019, 25, 507–519)

The increased use of insecticide seed treatments in rice has raised many questions about the potential benefits of these products. In 2014 and 2015, a field experiment was conducted near Stuttgart and Lonoke, AR, to evaluate whether an insecticide seed treatment could possibly lessen injury from acetolactate synthase (ALS)–inhibiting herbicides in imidazolinone-resistant (IR) rice. Two IR cultivars were tested (a hybrid, ‘CLXL745’, and an inbred, ‘CL152’), with and without an insecticide seed treatment (thiamethoxam). Four different herbicide combinations were evaluated: a nontreated control, two applications of bispyribac-sodium (hereafter bispyribac), two applications of imazethapyr, and two applications of imazethapyr plus bispyribac. The first herbicide application was to two- to three-leaf rice, and the second immediately prior to flooding (one- to two-tiller). At both 2 and 4 wk after final treatment (WAFT), the sequential applications of imazethapyr or bispyribac plus imazethapyr were more injurious to CLXL745 than CL152. This increased injury led to decreased groundcover 3 WAFT. Rice treated with thiamethoxam was less injured than nontreated rice and had improved groundcover and greater canopy heights. Even with up to 32% injury, the rice plants recovered by the end of the growing season, and yields within a cultivar were similar with and without a thiamethoxam seed treatment across all herbicide treatments. Based on these results, thiamethoxam can partially protect rice from injury caused by ALS-inhibiting herbicides as well as increase groundcover and canopy height; that is, the injury to rice never negatively affected yield.

The evolution of herbicide resistance is making it extremely difficult for US rice producers to use chemical control on weed species such as barnyardgrass and red rice. To combat herbicide resistance, it is imperative that alternative herbicide sites of action (SOAs) be incorporated into rice whenever possible. There are currently no very-long-chain fatty acid–inhibiting herbicides (WSSA Group 15) labeled for use in US rice; however, pethoxamid is one such herbicide currently under development. If appropriate rice tolerance and weed control can be established, pethoxamid would represent a unique herbicide SOA for use in US rice. We conducted field trials near Stuttgart, AR, in 2015 and near Colt and Lonoke, AR, in 2016 to assess selectivity of pethoxamid and weed control alone and in combination with other herbicides as a delayed preemergence (DPRE) application in drill-seeded rice. Pethoxamid was applied at 0, 420, or 560 g ai ha–1 alone and in combination with clomazone, imazethapyr, pendimethalin, and quinclorac. Minimal rice injury occurred with any treatment assessed. A reduction in rice shoot density and plant height compared to the nontreated control followed the use of pethoxamid; however, no decrease in yield resulted. The highest levels of barnyardgrass control followed the use of imazethapyr at 91% and quinclorac at 89% regardless of the presence of pethoxamid near Lonoke; however, pethoxamid applied at both rates in combination with clomazone and quinclorac increased barnyardgrass control compared to clomazone and quinclorac applied alone. Near Colt, barnyardgrass control of 92% and 96% resulted from pethoxamid alone, averaged over the high and low rates. Based on these data, rice can tolerate pethoxamid when applied DPRE, and adequate levels of barnyardgrass control can be achieved at the rates evaluated within a program; hence, pethoxamid appears to be a viable option for use in rice to allow for increased rotation of herbicide SOAs to combat herbicide-resistant and difficult-to-control weeds.

Each year there are multiple reports of drift occurrences, and the majority of drift complaints in rice are from imazethapyr or glyphosate. In 2014 and 2015, multiple field experiments were conducted near Stuttgart, AR, and near Lonoke, AR, to evaluate whether insecticide seed treatments would reduce injury from glyphosate or imazethapyr drift or decrease the recovery time following exposure to a low rate of these herbicides. Study I was referred to as the “seed treatment study,” and Study II was the “drift timing study.” In the seed treatment study the conventional rice cultivar ‘Roy J’ was planted, and herbicide treatments included imazethapyr at 10.5 g ai ha–1, glyphosate at 126 g ae ha–1, or no herbicide. Each plot had either a seed treatment of thiamethoxam, clothianidin, chlorantraniliprole, or no insecticide seed treatment. The herbicides were applied at the two- to three-leaf growth stage. Crop injury was assessed 1, 3, and 5 wk after application. Averaged over site-years, thiamethoxam-treated rice had less injury than rice with no insecticide seed treatment at each rating, along with an increased yield. Clothianidin-treated rice had an increased yield over no insecticide seed treatment, but the reduction in injury for both herbicides was less pronounced than in the thiamethoxam-treated plots. Overall, chlorantraniliprole was generally the least effective of the three insecticides in reducing injury from either herbicide and in protecting rice yield potential. A second experiment conducted at Stuttgart, AR, was meant to determine whether damage to rice from glyphosate and imazethapyr was influenced by the timing (15, 30, and 45 d after planting) of exposure to herbicides for thiamethoxam-treated and nontreated rice. There was an overall reduction in injury with the use of thiamethoxam, but the reduction in injury was not dependent on the timing of the drift event. Reduction in damage from physical drift of glyphosate and imazethapyr as well as increased yields over the absence of an insecticide seed treatment appear to be an added benefit.

Most agree that models of binary time-series-cross-sectional data in political science often possess unobserved unit-level heterogeneity. Despite this, there is no clear consensus on how best to account for these potential unit effects, with many of the issues confronted seemingly misunderstood. For example, one oft-discussed concern with rare events data is the elimination of no-event units from the sample when estimating fixed effects models. Many argue that this is a reason to eschew fixed effects in favor of pooled or random effects models. We revisit this issue and clarify that the main concern with fixed effects models of rare events data is not inaccurate or inefficient coefficient estimation, but instead biased marginal effects. In short, only evaluating event-experiencing units gives an inaccurate estimate of the baseline risk, yielding inaccurate (often inflated) estimates of predictor effects. As a solution, we propose a penalized maximum likelihood fixed effects (PML-FE) estimator, which retains the complete sample by providing finite estimates of the fixed effects for each unit. We explore the small sample performance of PML-FE versus common alternatives via Monte Carlo simulations, evaluating the accuracy of both parameter and effects estimates. Finally, we illustrate our method with a model of civil war onset.

Pennsylvania smartweed [Persicaria pensylvanica (L.) M. Gómez] is a common weed of rice (Oryza sativa L.) in the midsouthern United States and has recently become a concern for farmers because of reduced tillage systems. Acetolactate synthase (ALS) inhibitors have been extensively used for controlling smartweeds in imidazolinone-resistant and conventional rice. In the present study, we confirmed resistance to commonly used ALS inhibitors in rice and characterized the underlying resistance mechanism in a P. pensylvanica biotype from southeast Missouri. A dose–response experiment was conducted in the greenhouse using bensulfuron-methyl, imazethapyr, and bispyribac-sodium to determine the resistance index (resistance/susceptibility [R/S]) based on GR50 estimates. The target-site ALS gene was amplified from R and S plants, and sequences were analyzed for mutations known to confer ALS-inhibitor resistance. The P. pensylvanica biotype in question was found to be resistant to bensulfuron-methyl (R/S=2,330), imazethapyr (R/S=12), and bispyribac-sodium (R/S=6). Sequencing of the ALS gene from R plants revealed two previously known mutations (Pro-197-Ser, Ala-122-Ser) conferring resistance to sulfonylureas and imidazolinones. This is the first report of ALS-inhibitor resistance in P. pensylvanica.