The stars of the Milky Way carry the chemical history of our Galaxy in their atmospheres as they journey through its vast expanse. Like barcodes, we can extract the chemical fingerprints of stars from high-resolution spectroscopy. The fourth data release (DR4) of the Galactic Archaeology with HERMES (GALAH) Survey, based on a decade of observations, provides the chemical abundances of up to 32 elements for 917 588 stars that also have exquisite astrometric data from the Gaia satellite. For the first time, these elements include life-essential nitrogen to complement carbon, and oxygen as well as more measurements of rare-earth elements critical to modern-life electronics, offering unparalleled insights into the chemical composition of the Milky Way. For this release, we use neural networks to simultaneously fit stellar parameters and abundances across the whole wavelength range, leveraging synthetic grids computed with Spectroscopy Made Easy. These grids account for atomic line formation in non-local thermodynamic equilibrium for 14 elements. In a two-iteration process, we first fit stellar labels to all 1 085 520 spectra, then co-add repeated observations and refine these labels using astrometric data from Gaia and 2MASS photometry, improving the accuracy and precision of stellar parameters and abundances. Our validation thoroughly assesses the reliability of spectroscopic measurements and highlights key caveats. GALAH DR4 represents yet another milestone in Galactic archaeology, combining detailed chemical compositions from multiple nucleosynthetic channels with kinematic information and age estimates. The resulting dataset, covering nearly a million stars, opens new avenues for understanding not only the chemical and dynamical history of the Milky Way but also the broader questions of the origin of elements and the evolution of planets, stars, and galaxies.

The theory of signal detection is convenient for measuring mnemonic ability in recognition memory paradigms. In these paradigms, randomly selected participants are asked to study randomly selected items. In practice, researchers aggregate data across items or participants or both. The signal detection model is nonlinear; consequently, analysis with aggregated data is not consistent. In fact, mnemonic ability is underestimated, even in the large-sample limit. We present two hierarchical Bayesian models that simultaneously account for participant and item variability. We show how these models provide for accurate estimation of participants’ mnemonic ability as well as the memorability of items. The model is benchmarked with a simulation study and applied to a novel data set.

We present a cognitive process model of response choice and response time performance data that has excellent psychometric properties and may be used in a wide variety of contexts. In the model there is an accumulator associated with each response option. These accumulators have bounds, and the first accumulator to reach its bound determines the response time and response choice. The times at which accumulator reaches its bound is assumed to be lognormally distributed, hence the model is race or minima process among lognormal variables. A key property of the model is that it is relatively straightforward to place a wide variety of models on the logarithm of these finishing times including linear models, structural equation models, autoregressive models, growth-curve models, etc. Consequently, the model has excellent statistical and psychometric properties and can be used in a wide range of contexts, from laboratory experiments to high-stakes testing, to assess performance. We provide a Bayesian hierarchical analysis of the model, and illustrate its flexibility with an application in testing and one in lexical decision making, a reading skill.

Human abilities in perceptual domains have conventionally been described with reference to a threshold that may be defined as the maximum amount of stimulation which leads to baseline performance. Traditional psychometric links, such as the probit, logit, and t, are incompatible with a threshold as there are no true scores corresponding to baseline performance. We introduce a truncated probit link for modeling thresholds and develop a two-parameter IRT model based on this link. The model is Bayesian and analysis is performed with MCMC sampling. Through simulation, we show that the model provides for accurate measurement of performance with thresholds. The model is applied to a digit-classification experiment in which digits are briefly flashed and then subsequently masked. Using parameter estimates from the model, individuals’ thresholds for flashed-digit discrimination is estimated.

Turfgrass managers apply nonselective herbicides to control winter annual weeds during dormancy of warm-season turfgrass. Zoysiagrass subcanopies, however, retain green leaves and stems during winter dormancy, especially in warmer climates. The partially green zoysiagrass often deters the use of nonselective herbicides due to variable injury concerns in transition and southern climatic zones. This study evaluated zoysiagrass response to glyphosate and glufosinate applied at four different growing degree day (GDD)-based application timings during postdormancy transition in different locations, including Blacksburg, VA; Starkville, MS; and Virginia Beach, VA, in 2018 and 2019. GDD was calculated using a 5 C base temperature with accumulation beginning January 1 each year, and targeted application timings were 125, 200, 275, and 350 GDD5C. Zoysiagrass injury response to glyphosate and glufosinate was consistent across a broad growing region from northern Mississippi to coastal Virginia, but it varied by application timing. Glyphosate application at 125 and 200 GDD5C can be used safely for weed control during the postdormancy period of zoysiagrass, while glufosinate caused unacceptable turf injury regardless of application timing. Glyphosate and glufosinate exhibited a stepwise increase to maximum injury with increasing targeted GDD5C application timings. Glyphosate applied at 125 or 200 GDD5C did not injure zoysiagrass above a threshold of 30%, whereas glufosinate caused greater than 30% injury for 28 and 29 d when applied at 125 and 200 GDD5C, respectively. Likewise, glyphosate application at 125 or 200 GDD5C did not affect the zoysiagrass green cover area under the progress curve per day, whereas later applications reduced it. Glyphosate and glufosinate caused greater injury to zoysiagrass when applied at greater cumulative heat units and this was attributed to increasing turfgrass green leaf density, because heat unit accumulation is positively correlated with green leaf density. Accumulated heat unit-based application timing will allow practitioners to apply nonselective herbicides with reduced injury concerns.

Evidence-based psychotherapies (EBPs) are underused in health care settings. Aligning implementation of EBPs with the needs of health care leaders (i.e., operational stakeholders) can potentially accelerate their uptake into routine practice. Operational stakeholders (such as hospital leaders, clinical directors, and national program officers) can influence development and oversight of clinical programs as well as policy directives at local, regional, and national levels. Thus, engaging these stakeholders during the implementation and dissemination of EBPs is critical when targeting wider use in health care settings. This article describes how research–operations partnerships were leveraged to increase implementation of an empirically supported psychotherapy – brief Cognitive Behavioral Therapy (brief CBT) – in Veterans Health Administration (VA) primary care settings. The partnered implementation and dissemination efforts were informed by the empirically derived World Health Organization’s ExpandNet framework. A steering committee was formed and included several VA operational stakeholders who helped align the brief CBT program with the implementation needs of VA primary care settings. During the first 18 months of the project, partnerships facilitated rapid implementation of brief CBT at eight VA facilities, including training of 12 providers who saw 120 patients, in addition to expanded program elements to better support sustainability (e.g., train-the-trainer procedures).

The purpose of this study was to determine if estimated center of pressure (COP) from plantar force data collected using three-sensor loadsol insoles was comparable to the COP from plantar pressure data collected using pedar insoles during walking and running. Ten healthy adults walked and ran at self-selected speeds on a treadmill while wearing both a loadsol and pedar insole in their right shoe. Plantar force recorded from the loadsol was used to estimate COP along mediolateral (COPx) and anteroposterior (COPy) axes. The estimated COPx and COPy were compared with the COPx and COPy from pedar using limits of agreement and Spearman’s rank correlation. There were significant relationships and agreement within 5 mm in COPx and 20 mm in COPy between loadsol and pedar at 20–40% of stance during walking and running. However, loadsol demonstrated biases of 7 mm in COPx and 10 mm in COPy compared to pedar near initial contact and toe-off.

Multifetal pregnancies are at risk of adverse maternal, neonatal and long-term health outcomes, and gestational weight gain (GWG) is a potentially modifiable risk factor for several of these. However, studies assessing the associations of GWG with long-term health in twins are rare, and studies which do assess these associations in twins often do not account for gestational age. Since longer gestations are likely to lead to larger GWG and lower risk of adverse outcomes, adjusting for gestational age is necessary to better understand the association of GWG with twin health outcomes. We aimed to explore long-term associations of GWG-for-gestational-age with twin anthropometric measures. The Peri/Postnatal Epigenetic Twins Study (PETS) is a prospective cohort study, which recruited women pregnant with twins from 2007 to 2009. Twins were followed-up at 18 months and 6 years of age. GWG-for-gestational-age z-scores were calculated from pre-pregnancy weight and weight at delivery. We fitted regression models to assess associations of GWG with twin weight, height and BMI at birth, 18 months, and 6 years. Of the 250 women in the PETS, 172 had GWG measured throughout pregnancy. Overall, higher GWG-for-gestational-age z-scores were associated with higher birthweight (β: 0.32 z-scores, 95% Confidence Interval (95% CI): 0.19, 0.45), BMI (β: 0.29 z-scores, 95% CI: 0.14, 0.43) and length (β: 0.27 z-scores, 95% CI: 0.09, 0.45). However, these associations were not observed at 18 months or 6 years of age. GWG was associated with twin length, weight and BMI at birth but not during childhood. Further research is needed to determine the long-term effects of GWG on twin health outcomes.

United States certified organic and conventional dairy farms are compared on the basis of economic, financial, and technological measures using dairy data from the 2016 USDA Agricultural Resource Management Survey. A stochastic production frontier model using an input distance function framework is estimated for U.S. dairy farms to examine technical efficiency and returns to scale (RTS) of farms of both systems and by multiple size categories. Financial and economic measures such as net return on assets and input costs, as well as technological adoption measures are compared by system and size. For both systems, size is the major determinant of competitiveness based on selected measures of productivity and RTS.

Neurodevelopment is sensitive to genetic and pre/postnatal environmental influences. These effects are likely mediated by epigenetic factors, yet current knowledge is limited. Longitudinal twin studies can delineate the link between genetic and environmental factors, epigenetic state at birth and neurodevelopment later in childhood. Building upon our study of the Peri/postnatal Epigenetic Twin Study (PETS) from gestation to 6 years of age, here we describe the PETS 11-year follow-up in which we will use neuroimaging and cognitive testing to examine the relationship between early-life environment, epigenetics and neurocognitive outcomes in mid-childhood. Using a within-pair twin model, the primary aims are to (1) identify early-life epigenetic correlates of neurocognitive outcomes; (2) determine the developmental stability of epigenetic effects and (3) identify modifiable environmental risk factors. Secondary aims are to identify factors influencing gut microbiota between 6 and 11 years of age to investigate links between gut microbiota and neurodevelopmental outcomes in mid-childhood. Approximately 210 twin pairs will undergo an assessment at 11 years of age. This includes a direct child cognitive assessment, multimodal magnetic resonance imaging, biological sampling, anthropometric measurements and a range of questionnaires on health and development, behavior, dietary habits and sleeping patterns. Data from complementary data sources, including the National Assessment Program — Literacy and Numeracy and the Australian Early Development Census, will also be sought. Following on from our previous focus on relationships between growth, cardiovascular health and oral health, this next phase of PETS will significantly advance our understanding of the environmental interactions that shape the developing brain.

The cerebellum has been hypothesized to play a role in a variety of movement timing tasks that involve the processing of temporal information on a variety of timescales. Braitenberg, Heck & Sultan propose a new theory of cerebellar function that is able to account for movement timing on the order of a couple of hundred milliseconds. However, this theory does not account for the rôle the cerebellum plays in the acquisition and retention of adaptively timed discrete movements that are on the order of 200 to 1000 milliseconds, and therefore does not account for the entire temporal range of cerebellar dependent processing.

Essential variables to consider for an efficient control strategy for invasive plants include dispersion pattern (i.e., satellite or invasion front) and patch expansion rate. These variables were demonstrated for buffelgrass [Pennisetum ciliare (L.) Link], a C4 perennial grass introduced from Africa, which has invaded broadly around the world. The study site was along a roadway in southern Arizona (USA). The P. ciliare plant distributions show the pattern of clumping associated with the satellite (nascent foci) colonization pattern (average nearest neighbor test, z-score −47.2, P<0.01). The distance between patches ranged from 0.743 to 12.8 km, with an average distance between patches of 5.6 km. Median patch expansion rate was 271% over the 3-yr monitoring period versus 136% found in other studies of established P. ciliare patches. Targeting P. ciliare satellite patches as a control strategy may exponentially reduce the areal doubling time, while targeting the largest patches may have less effect on the invasion speed.

Lithium-ion capacitors (LICs) and Hybrid LICs (H-LICs) were assembled as three-layered pouch cells in an asymmetric configuration employing Faradaic pre-lithiated hard carbon anodes and non-Faradaic ion adsorption-desorption activated carbon (AC) cathodes for LICs and lithium iron phosphate (LiFePO4-LFP)/AC composite cathodes for H-LICs. The room temperature rate performance was evaluated after the initial LIC and H-LIC cell formation as a function of the electrolyte additives. The capacity retention was measured after charging at high temperature conditions, while the design factor explored was electrolyte additive formulation, with a focus on their stability. The high temperature potential holds simulate electrochemical energy materials under extreme environments and act to accelerate the failure mechanisms associated with cell degradation to determine robust electrolyte/additive combinations.

We commend Rotolo et al. (2018) for introducing a new lens for viewing the well-known gap between industrial and organizational (I-O) psychology research and human resource (HR) practices in organizations. However, Rotolo et al.’s characterization of practitioner behavior as “anti I-O” suggests a particularly negative view of scientific research among some HR practitioners. The label implies that some HR practitioners are intentionally ignoring or actively resisting academic research. More likely, the behavior stems from a passive indifference to academia, which may be the appropriate attitude for some practitioners to adopt when a great deal of academic research is too slow, too theoretical, and too cryptically communicated to be useful in applied settings. We agree with Rotolo et al. when they say, “we are a discipline that is not geared for being cutting edge” (p. 182), and we appreciate their recommendations for addressing this lack of relevance. However, most recommendations in this broader discussion do not address the foundational problem within our field: a systemic mismatch between the incentives of practitioners and academics. To support this point, we briefly describe a typology of I-O psychologists as well as the varying contexts and incentives that drive their behavior. We then close with our own recommendations for how academia can improve its relevance to practitioners and close the gap. These changes are not easy, but we agree with Rotolo and colleagues that if any field can address such foundational problems, it is ours.

Objective: The human gut microbiota has been demonstrated to be associated with a number of host phenotypes, including obesity and a number of obesity-associated phenotypes. This study is aimed at further understanding and describing the relationship between the gut microbiota and obesity-associated measurements obtained from human participants. Subjects/Methods: Here, we utilize genetically informative study designs, including a four-corners design (extremes of genetic risk for BMI and of observed BMI; N = 50) and the BMI monozygotic (MZ) discordant twin pair design (N = 30), in order to help delineate the role of host genetics and the gut microbiota in the development of obesity. Results: Our results highlight a negative association between BMI and alpha diversity of the gut microbiota. The low genetic risk/high BMI group of individuals had a lower gut microbiota alpha diversity when compared to the other three groups. Although the difference in alpha diversity between the lean and heavy groups of the BMI-discordant MZ twin design did not achieve significance, this difference was observed to be in the expected direction, with the heavier participants having a lower average alpha diversity. We have also identified nine OTUs observed to be associated with either a leaner or heavier phenotype, with enrichment for OTUs classified to the Ruminococcaceae and Oxalobacteraceae taxonomic families. Conclusion: Our study presents evidence of a relationship between BMI and alpha diversity of the gut microbiota. In addition to these findings, a number of OTUs were found to be significantly associated with host BMI. These findings may highlight separate subtypes of obesity, one driven by genetic factors, the other more heavily influenced by environmental factors.