Soil amelioration via strategic deep tillage is occasionally utilized within conservation tillage systems to alleviate soil constraints, but its impact on weed seed burial and subsequent growth within the agronomic system is poorly understood. This study assessed the effects of different strategic deep-tillage practices, including soil loosening (deep ripping), soil mixing (rotary spading), or soil inversion (moldboard plow), on weed seed burial and subsequent weed growth, compared with a no-till control. The tillage practices were applied in 2019 at Yerecoin and Darkan, WA, and data on weed seed burial and growth were collected during the following 3-yr winter crop rotation (2019 to 2021). Soil inversion buried 89% of rigid ryegrass (Lolium rigidum Gaudin) and ripgut brome (Bromus diandrus Roth) seeds to a depth of 10 to 20 cm at both sites, while soil loosening and mixing left between 31% and 91% of the seeds in the top 0 to 10 cm of soil, with broad variation between sites. Few seeds were buried beyond 20 cm despite tillage working depths exceeding 30 cm at both sites. Soil inversion reduced the density of L. rigidum to <1 plant m−2 for 3 yr after strategic tillage. Bromus diandrus density was initially reduced to 0 to 1 plant m−2 by soil inversion, but increased to 4 plants m−2 at Yerecoin in 2020 and 147 plants at Darkan in 2021. Soil loosening or mixing did not consistently decrease weed density. The field data were used to parameterize a model that predicted weed density following strategic tillage with greater accuracy for soil inversion than for loosening or mixing. The findings provide important insights into the effects of strategic deep tillage on weed management in conservational agricultural systems and demonstrate the potential of models for optimizing weed management strategies.

We present a deep probabilistic convolutional neural network (PCNN) model for predicting local values of small-scale mixing properties in stratified turbulent flows, namely the dissipation rates of turbulent kinetic energy and density variance, $\varepsilon$ and $\chi$. Inputs to the PCNN are vertical columns of velocity and density gradients, motivated by data typically available from microstructure profilers in the ocean. The architecture is designed to enable the model to capture several characteristic features of stratified turbulence, in particular the dependence of small-scale isotropy on the buoyancy Reynolds number $Re_b:=\varepsilon /(\nu N^2)$, where $\nu$ is the kinematic viscosity and $N$ is the background buoyancy frequency, the correlation between suitably locally averaged density gradients and turbulence intensity and the importance of capturing the tails of the probability distribution functions of values of dissipation. Empirically modified versions of commonly used isotropic models for $\varepsilon$ and $\chi$ that depend only on vertical derivatives of density and velocity are proposed based on the asymptotic regimes $Re_b\ll 1$ and $Re_b\gg 1$, and serve as an instructive benchmark for comparison with the data-driven approach. When trained and tested on a simulation of stratified decaying turbulence which accesses a range of turbulent regimes (associated with differing values of $Re_b$), the PCNN outperforms assumptions of isotropy significantly as $Re_b$ decreases, and additionally demonstrates improvements over the fitted empirical models. A differential sensitivity analysis of the PCNN facilitates a comparison with the theoretical models and provides a physical interpretation of the features enabling it to make improved predictions.

Knowledge graphs have become a common approach for knowledge representation. Yet, the application of graph methodology is elusive due to the sheer number and complexity of knowledge sources. In addition, semantic incompatibilities hinder efforts to harmonize and integrate across these diverse sources. As part of The Biomedical Translator Consortium, we have developed a knowledge graph–based question-answering system designed to augment human reasoning and accelerate translational scientific discovery: the Translator system. We have applied the Translator system to answer biomedical questions in the context of a broad array of diseases and syndromes, including Fanconi anemia, primary ciliary dyskinesia, multiple sclerosis, and others. A variety of collaborative approaches have been used to research and develop the Translator system. One recent approach involved the establishment of a monthly “Question-of-the-Month (QotM) Challenge” series. Herein, we describe the structure of the QotM Challenge; the six challenges that have been conducted to date on drug-induced liver injury, cannabidiol toxicity, coronavirus infection, diabetes, psoriatic arthritis, and ATP1A3-related phenotypes; the scientific insights that have been gleaned during the challenges; and the technical issues that were identified over the course of the challenges and that can now be addressed to foster further development of the prototype Translator system. We close with a discussion on Large Language Models such as ChatGPT and highlight differences between those models and the Translator system.

The U.S. Department of Agriculture–Agricultural Research Service (USDA-ARS) has been a leader in weed science research covering topics ranging from the development and use of integrated weed management (IWM) tactics to basic mechanistic studies, including biotic resistance of desirable plant communities and herbicide resistance. ARS weed scientists have worked in agricultural and natural ecosystems, including agronomic and horticultural crops, pastures, forests, wild lands, aquatic habitats, wetlands, and riparian areas. Through strong partnerships with academia, state agencies, private industry, and numerous federal programs, ARS weed scientists have made contributions to discoveries in the newest fields of robotics and genetics, as well as the traditional and fundamental subjects of weed–crop competition and physiology and integration of weed control tactics and practices. Weed science at ARS is often overshadowed by other research topics; thus, few are aware of the long history of ARS weed science and its important contributions. This review is the result of a symposium held at the Weed Science Society of America’s 62nd Annual Meeting in 2022 that included 10 separate presentations in a virtual Weed Science Webinar Series. The overarching themes of management tactics (IWM, biological control, and automation), basic mechanisms (competition, invasive plant genetics, and herbicide resistance), and ecosystem impacts (invasive plant spread, climate change, conservation, and restoration) represent core ARS weed science research that is dynamic and efficacious and has been a significant component of the agency’s national and international efforts. This review highlights current studies and future directions that exemplify the science and collaborative relationships both within and outside ARS. Given the constraints of weeds and invasive plants on all aspects of food, feed, and fiber systems, there is an acknowledged need to face new challenges, including agriculture and natural resources sustainability, economic resilience and reliability, and societal health and well-being.

Changes in executive function (EF) occur during adolescence with several factors (e.g., parenting styles, socioeconomic status) influencing the development of EF abilities. These changes are important as EF has been strongly linked with a range of outcomes including academic achievement, job performance, and social–emotional well-being. However, few studies have examined variability in EF trajectories during this critical developmental period, or trajectories in samples known to have specific impairments with EF, such as adolescents diagnosed with attention-deficit/hyperactivity disorder (ADHD). The present study examined differential trajectories of three domains of parent-rated EF in 302 adolescents (167 males; Mage = 13.17 years) with and without ADHD (53.6% with ADHD) from grade 8 to 10. The study also explored whether adolescent ADHD, parent ADHD, and parents’ own EF predicted EF trajectories in addition to the longitudinal relation between trajectories and academic outcomes. Findings suggest that adolescence is marked by significant variability in EF development due to factors such as ADHD status, parent ADHD, and parent EF ability. Additionally, adolescents who displayed poor EF abilities throughout middle and high school had significantly lower grade point averages and poorer parent-, teacher-, and self-reported academic outcomes. Implications for interventions targeting EF deficits among adolescents with and without ADHD are discussed.

Ambient seismic recordings taken at broad locations across Ross Ice Shelf and a dense array near West Antarctic Ice Sheet (WAIS) Divide, Antarctica, show pervasive temporally variable resonance peaks associated with trapped seismic waves in near-surface firn layers. These resonance peaks feature splitting on the horizontal components, here interpreted as frequency-dependent anisotropy in the firn and underlying ice due to several overlapping mechanisms driven by ice flow. Frequency peak splitting magnitudes and fast/slow axes were systematically estimated at single stations using a novel algorithm and compared with good agreement with active source anisotropy measurements at WAIS Divide determined via active sources recorded on a 1 km circular array. The approach was further applied to the broad Ross Ice Shelf (RIS) array, where anisotropy axes were directly compared with visible surface features and ice shelf flow lines. The near-surface firn, depicted by anisotropy above 30 Hz, was shown to exhibit a novel plastic stretching mechanism of anisotropy, whereby the fast direction in snow aligns with accelerating ice shelf flow.

The identification of volatile pheromones attractive to and produced by many species within the family Cerambycidae (Coleoptera) has spurred development of synthetic pheromone lures that can be used to assess cerambycid populations and to monitor for invasive and rare species. We applied this method of trapping to examine cerambycid attraction to pheromone compounds and to initiate an analysis of the cerambycid communities within western Idaho, United States of America. A total of 8195 cerambycids, representing 67 species, 17 tribes, and 42 genera within six subfamilies of the Cerambycidae, were captured. Thirteen volatile pheromone lures were tested over three years, and a significant treatment effect was detected for nine cerambycid species. No significant differences were found among sites for species richness, diversity, or evenness. No significant differences were found among lures for species richness or diversity, but a significant difference was detected among lures for species evenness. We propose a method for designing a multicomponent lure, based on data from the target region, to maximise the number of species captured and to target specific cerambycid species within a targeted region.

Repeated antigen testing of 12 severe acute respiratory coronavirus virus 2 (SARS-CoV-2)–positive nursing home residents using Abbott BinaxNOW identified 9 of 9 (100%) culture-positive specimens up to 6 days after initial positive test. Antigen positivity lasted 2–24 days. Antigen positivity might last beyond the infectious period, but it was reliable in residents with evidence of early infection.

Substantial progress has been made in the standardization of nomenclature for paediatric and congenital cardiac care. In 1936, Maude Abbott published her Atlas of Congenital Cardiac Disease, which was the first formal attempt to classify congenital heart disease. The International Paediatric and Congenital Cardiac Code (IPCCC) is now utilized worldwide and has most recently become the paediatric and congenital cardiac component of the Eleventh Revision of the International Classification of Diseases (ICD-11). The most recent publication of the IPCCC was in 2017. This manuscript provides an updated 2021 version of the IPCCC.

The International Society for Nomenclature of Paediatric and Congenital Heart Disease (ISNPCHD), in collaboration with the World Health Organization (WHO), developed the paediatric and congenital cardiac nomenclature that is now within the eleventh version of the International Classification of Diseases (ICD-11). This unification of IPCCC and ICD-11 is the IPCCC ICD-11 Nomenclature and is the first time that the clinical nomenclature for paediatric and congenital cardiac care and the administrative nomenclature for paediatric and congenital cardiac care are harmonized. The resultant congenital cardiac component of ICD-11 was increased from 29 congenital cardiac codes in ICD-9 and 73 congenital cardiac codes in ICD-10 to 318 codes submitted by ISNPCHD through 2018 for incorporation into ICD-11. After these 318 terms were incorporated into ICD-11 in 2018, the WHO ICD-11 team added an additional 49 terms, some of which are acceptable legacy terms from ICD-10, while others provide greater granularity than the ISNPCHD thought was originally acceptable. Thus, the total number of paediatric and congenital cardiac terms in ICD-11 is 367. In this manuscript, we describe and review the terminology, hierarchy, and definitions of the IPCCC ICD-11 Nomenclature. This article, therefore, presents a global system of nomenclature for paediatric and congenital cardiac care that unifies clinical and administrative nomenclature.

The members of ISNPCHD realize that the nomenclature published in this manuscript will continue to evolve. The version of the IPCCC that was published in 2017 has evolved and changed, and it is now replaced by this 2021 version. In the future, ISNPCHD will again publish updated versions of IPCCC, as IPCCC continues to evolve.

Clostridioides difficile infection rates from 7 facilities that used nucleic acid amplification testing (NAAT) alone for 12 months then switched to NAAT plus toxin enzyme immunoassay (EIA) and reported the latter result for 12 months were compared to 70 facilities that used NAAT alone for all 24 months. There was no significant difference in rates between facility groups over the first 12 months (P = .21, linear regression), but we detected a decrease in rates for the facilities that changed to NAAT+EIA (P < .0001).

Dementia-related psychosis (DRP) is prevalent across dementias and typically manifests as delusions and/or hallucinations. The mechanisms underlying psychosis in dementia are unknown; however, neurobiological and pharmacological evidence has implicated multiple signaling pathways and brain regions. Despite differences in dementia pathology, the neurobiology underlying psychosis appears to involve dysregulation of a cortical and limbic pathway involving serotonergic, gamma-aminobutyric acid ergic, glutamatergic, and dopaminergic signaling. Thus, an imbalance in cortical and mesolimbic excitatory tone may drive symptoms of psychosis. Delusions and hallucinations may result from (1) hyperactivation of pyramidal neurons within the visual cortex, causing visual hallucinations and (2) hyperactivation of the mesolimbic pathway, causing both delusions and hallucinations. Modulation of the 5-HT2A receptor may mitigate hyperactivity at both psychosis-associated pathways. Pimavanserin, an atypical antipsychotic, is a selective serotonin inverse agonist/antagonist at 5-HT2A receptors. Pimavanserin may prove beneficial in treating the hallucinations and delusions of DRP without worsening cognitive or motor function.