Data from a national survey of 348 U.S. sports field managers were used to examine the effects of participation in Cooperative Extension events on the adoption of turfgrass weed management practices. Of the respondents, 94% attended at least one event in the previous three years. Of this 94%, 97% reported adopting at least one practice as a result of knowledge gained at an Extension turfgrass event. Half of the respondents adopted four or more practices; a third adopted five or more practices. Non-chemical, cultural practices were the most-adopted practices (65% of respondents). Multiple regression analysis was used to examine factors explaining practice adoption and Extension event attendance. Compared to attending one event, attending three events increased total adoption by an average of one practice. Attending four or more events increased total adoption by two practices. Attending four or more events (compared to one event) increased the odds of adopting six individual practices by 3- to 6-fold, depending on the practice. This suggests practice adoption could be enhanced by encouraging repeat attendance among past Extension event attendees. Manager experience was a statistically significant predictor of the number of Extension events attended, but a poor direct predictor of practice adoption. Experience does not appear to increase adoption directly, but indirectly, via its impact on Extension event attendance. In addition to questions about weed management generally, the survey asked questions about annual bluegrass management, specifically. Respondents were asked to rank seven sources of information for their helpfulness in managing annual bluegrass. There was no single dominant information source, but Extension was ranked as the most helpful more than any other source (by 22% of the respondents) and was ranked among the top three by 53%, closely behind field representative/local distributor sources at 54%.

The Eighth World Congress of Pediatric Cardiology and Cardiac Surgery (WCPCCS) will be held in Washington DC, USA, from Saturday, 26 August, 2023 to Friday, 1 September, 2023, inclusive. The Eighth World Congress of Pediatric Cardiology and Cardiac Surgery will be the largest and most comprehensive scientific meeting dedicated to paediatric and congenital cardiac care ever held. At the time of the writing of this manuscript, The Eighth World Congress of Pediatric Cardiology and Cardiac Surgery has 5,037 registered attendees (and rising) from 117 countries, a truly diverse and international faculty of over 925 individuals from 89 countries, over 2,000 individual abstracts and poster presenters from 101 countries, and a Best Abstract Competition featuring 153 oral abstracts from 34 countries. For information about the Eighth World Congress of Pediatric Cardiology and Cardiac Surgery, please visit the following website: [www.WCPCCS2023.org]. The purpose of this manuscript is to review the activities related to global health and advocacy that will occur at the Eighth World Congress of Pediatric Cardiology and Cardiac Surgery.

Acknowledging the need for urgent change, we wanted to take the opportunity to bring a common voice to the global community and issue the Washington DC WCPCCS Call to Action on Addressing the Global Burden of Pediatric and Congenital Heart Diseases. A copy of this Washington DC WCPCCS Call to Action is provided in the Appendix of this manuscript. This Washington DC WCPCCS Call to Action is an initiative aimed at increasing awareness of the global burden, promoting the development of sustainable care systems, and improving access to high quality and equitable healthcare for children with heart disease as well as adults with congenital heart disease worldwide.

Over the past decade, transdiagnostic indicators in relation to neurobiological processes have provided extensive insight into youth’s risk for psychopathology. During development, exposure to childhood trauma and dysregulation (i.e., so-called AAA symptomology: anxiety, aggression, and attention problems) puts individuals at a disproportionate risk for developing psychopathology and altered network-level neural functioning. Evidence for the latter has emerged from resting-state fMRI studies linking mental health symptoms and aberrations in functional networks (e.g., cognitive control (CCN), default mode networks (DMN)) in youth, although few of these investigations have used longitudinal designs. Herein, we leveraged a three-year longitudinal study to identify whether traumatic exposures and concomitant dysregulation trigger changes in the developmental trajectories of resting-state functional networks involved in cognitive control (N = 190; 91 females; time 1 Mage = 11.81). Findings from latent growth curve analyses revealed that greater trauma exposure predicted increasing connectivity between the CCN and DMN across time. Greater levels of dysregulation predicted reductions in within-network connectivity in the CCN. These findings presented in typically developing youth corroborate connectivity patterns reported in clinical populations, suggesting there is predictive utility in using transdiagnostic indicators to forecast alterations in resting-state networks implicated in psychopathology.

The present study examines whether neuroticism is predicted by genetic vulnerability, summarized as polygenic risk score for neuroticism (PRSN), in interaction with bullying, parental bonding, and childhood adversity. Data were derived from a general population adolescent and young adult twin cohort. The final sample consisted of 202 monozygotic and 436 dizygotic twins and 319 twin pairs. The Short Eysenck Personality questionnaire was used to measure neuroticism. PRSN was trained on the results from the Genetics of Personality Consortium (GPC) and United Kingdom Biobank (UKB) cohorts, yielding two different PRSN. Multilevel mixed-effects models were used to analyze the main and interacting associations of PRSN, childhood adversity, bullying, and parental bonding style with neuroticism. We found no evidence of gene–environment correlation. PRSN thresholds of .005 and .2 were chosen, based on GPC and UKB datasets, respectively. After correction for confounders, all the individual variables were associated with the expression of neuroticism: both PRSN from GPC and UKB, childhood adversity, maternal bonding, paternal bonding, and bullying in primary school and secondary school. However, the results indicated no evidence for gene–environment interaction in this cohort. These results suggest that genetic vulnerability on the one hand and negative life events (childhood adversity and bullying) and positive life events (optimal parental bonding) on the other represent noninteracting pathways to neuroticism.

We present the third data release from the Parkes Pulsar Timing Array (PPTA) project. The release contains observations of 32 pulsars obtained using the 64-m Parkes “Murriyang” radio telescope. The data span is up to 18 years with a typical cadence of 3 weeks. This data release is formed by combining an updated version of our second data release with ∼ 3 years of more recent data primarily obtained using an ultra-wide-bandwidth receiver system that operates between 704 and 4032 MHz. We provide calibrated pulse profiles, flux-density dynamic spectra, pulse times of arrival, and initial pulsar timing models. We describe methods for processing such wide-bandwidth observations, and compare this data release with our previous release.

Over the past 2 decades, several categorizations have been proposed for the abnormalities of the aortic root. These schemes have mostly been devoid of input from specialists of congenital cardiac disease. The aim of this review is to provide a classification, from the perspective of these specialists, based on an understanding of normal and abnormal morphogenesis and anatomy, with emphasis placed on the features of clinical and surgical relevance. We contend that the description of the congenitally malformed aortic root is simplified when approached in a fashion that recognizes the normal root to be made up of 3 leaflets, supported by their own sinuses, with the sinuses themselves separated by the interleaflet triangles. The malformed root, usually found in the setting of 3 sinuses, can also be found with 2 sinuses, and very rarely with 4 sinuses. This permits description of trisinuate, bisinuate, and quadrisinuate variants, respectively. This feature then provides the basis for classification of the anatomical and functional number of leaflets present. By offering standardized terms and definitions, we submit that our classification will be suitable for those working in all cardiac specialties, whether pediatric or adult. It is of equal value in the settings of acquired or congenital cardiac disease. Our recommendations will serve to amend and/or add to the existing International Paediatric and Congenital Cardiac Code, along with the Eleventh iteration of the International Classification of Diseases provided by the World Health Organization.

Prior research finds that liberals and conservatives process information differently. Predispositions toward intuitive versus reflective thinking may help explain this individual level variation. There have been few direct tests of this hypothesis and the results from the handful of studies that do exist are contradictory. Here we report the results of a series of studies using the Cognitive Reflection Test (CRT) to investigate inclinations to be reflective and political orientation. We find a relationship between thinking style and political orientation and that these effects are particularly concentrated on social attitudes. We also find it harder to manipulate intuitive and reflective thinking than a number of prominent studies suggest. Priming manipulations used to induce reflection and intuition in published articles repeatedly fail in our studies. We conclude that conservatives—more specifically, social conservatives—tend to be dispositionally less reflective, social liberals tend to be dispositionally more reflective, and that the relationship between reflection and intuition and political attitudes may be more resistant to easy manipulation than existing research would suggest.

EU legislation stipulates that unfit broilers may not be transported, but no guidelines for fitness-for-transport assessment are provided. Moreover, the impact of pre-slaughter conditions (eg crate stocking density) may depend on broiler fitness. We aimed to evaluate a fitness-assessment method and test physiological responses to the pre-slaughter phase with different stocking densities. Broilers (41 days; n = 1,939) were transported for 45 min at ‘high’ (160 cm2 per kg), ‘medium’ (190 cm2 per kg) or ‘low’ (220 cm2 per kg) stocking density, and were subjected to a commercially representative pre-slaughter phase duration of ≈ 16 h. Pre-loading, lameness, illness, hock burns, foot-pad dermatitis, lesions, physical defects, cleanliness and cachexia were scored on a sample, for categorisation as fit (n = 49) or unfit (n = 25). Blood was collected before and after the pre-slaughter phase for determination of plasma levels of corticosterone (CORT), lactate, glucose and thiobarbituric acid-reactive substances (TBARS). Lameness, foot-pad dermatitis, lesions, illness, defects, and cachexia scores were, or tended to be, correlated with ≥ 1 physiological stress indicators. Unfit chickens tended to show or showed lower pre-transport glucose and lactate levels than fit chickens. Post-lairage, unfit chickens had higher TBARS and lower lactate levels compared to fit chickens. At high and low stocking densities, unfit chickens showed higher CORT levels than fit chickens. Furthermore, CORT levels of unfit chickens increased more at low stocking density. The results show that our method potentially identifies chickens experiencing additional stress during the pre-slaughter phase, due to poor physical condition. High and low stocking density proved a stressor for all, and especially for unfit chickens, with detrimental implications for their welfare.

The purpose of this investigation was to expand upon the limited existing research examining the test–retest reliability, cross-sectional validity and longitudinal validity of a sample of bioelectrical impedance analysis (BIA) devices as compared with a laboratory four-compartment (4C) model. Seventy-three healthy participants aged 19–50 years were assessed by each of fifteen BIA devices, with resulting body fat percentage estimates compared with a 4C model utilising air displacement plethysmography, dual-energy X-ray absorptiometry and bioimpedance spectroscopy. A subset of thirty-seven participants returned for a second visit 12–16 weeks later and were included in an analysis of longitudinal validity. The sample of devices included fourteen consumer-grade and one research-grade model in a variety of configurations: hand-to-hand, foot-to-foot and bilateral hand-to-foot (octapolar). BIA devices demonstrated high reliability, with precision error ranging from 0·0 to 0·49 %. Cross-sectional validity varied, with constant error relative to the 4C model ranging from −3·5 (sd 4·1) % to 11·7 (sd 4·7) %, standard error of the estimate values of 3·1–7·5 % and Lin’s concordance correlation coefficients (CCC) of 0·48–0·94. For longitudinal validity, constant error ranged from −0·4 (sd 2·1) % to 1·3 (sd 2·7) %, with standard error of the estimate values of 1·7–2·6 % and Lin’s CCC of 0·37–0·78. While performance varied widely across the sample investigated, select models of BIA devices (particularly octapolar and select foot-to-foot devices) may hold potential utility for the tracking of body composition over time, particularly in contexts in which the purchase or use of a research-grade device is infeasible.

The advent of modern, high-speed electron detectors has made the collection of multidimensional hyperspectral transmission electron microscopy datasets, such as 4D-STEM, a routine. However, many microscopists find such experiments daunting since analysis, collection, long-term storage, and networking of such datasets remain challenging. Some common issues are their large and unwieldy size that often are several gigabytes, non-standardized data analysis routines, and a lack of clarity about the computing and network resources needed to utilize the electron microscope. The existing computing and networking bottlenecks introduce significant penalties in each step of these experiments, and thus, real-time analysis-driven automated experimentation for multidimensional TEM is challenging. One solution is to integrate microscopy with edge computing, where moderately powerful computational hardware performs the preliminary analysis before handing off the heavier computation to high-performance computing (HPC) systems. Here we trace the roots of computation in modern electron microscopy, demonstrate deep learning experiments running on an edge system, and discuss the networking requirements for tying together microscopes, edge computers, and HPC systems.