Relating Use of Effective Responsive, Structure, and Non-Directive Control Vegetable Parenting Practices to Subscales from the Model of Goal Directed Behavior

Parents may positively influence children’s vegetable consumption through effective vegetable parenting practices (VPP). Research has demonstrated three dimensions of effective VPP: Effective Responsiveness, Structure, and Non-Directive Control, but there is limited research investigating each separately. This study presents the modeling of Effective Responsive, Structure, and Non-Directive Control VPP using constructs from the Model of Goal Directed Vegetable Parenting Practices (MGDVPP). Parents (n=307) completed a survey on demographics, MGDVPP constructs, and effective VPP. Block regression modeling tested three models: one for each dimension of effective VPP as the dependent variable. Independent variables included validated subscales representing MGDVPP constructs: Intention, Desire, Perceived Barriers, Autonomy, Relatedness, Self-Efficacy, Habit, Anticipated Emotions, Perceived Behavioral Control, Attitudes, and Norms. Participants were racially diverse, and a majority was female, of higher socioeconomic status, and with a male child. Effective Responsive VPP was positively related to a Habit subscale. Effective Structure VPP was positively related to a Barrier, two Habit, and an Attitude subscales. Effective Non-Directive Control VPP was positively related to being a high school or GED graduate, having younger children, a Habit, and two Intentions subscales, and negatively related to an Intentions and a Perceived Behavioral Control subscales. The adjusted R2 for the Effective Responsive, Structure, and Non-Directive Control VPP models were 0.432, 0.310, and 0.515, respectively. This was the first study to relate constructs from a theoretical model to effective VPP dimensions. Research is needed to longitudinally assess the MGDVPP and test its utility in vegetable-related interventions

Multi-Scale Stellar Associations across the Star Formation Hierarchy in PHANGS-HST Nearby Galaxies: Methodology and Properties

We develop a method to identify and determine the physical properties of stellar associations using Hubble Space Telescope (HST) NUV-U-B-V-I imaging of nearby galaxies from the PHANGS-HST survey. We apply a watershed algorithm to density maps constructed from point source catalogues Gaussian smoothed to multiple physical scales from 8 to 64 pc. We develop our method on two galaxies that span the distance range in the PHANGS-HST sample: NGC 3351 (10 Mpc), NGC 1566 (18 Mpc). We test our algorithm with different parameters such as the choice of detection band for the point source catalogue (NUV or V), source density image filtering methods, and absolute magnitude limits. We characterise the properties of the resulting multi-scale associations, including sizes, number of tracer stars, number of associations, photometry, as well as ages, masses, and reddening from Spectral Energy Distribution fitting. Our method successfully identifies structures that occupy loci in the UBVI colour-colour diagram consistent with previously published catalogues of clusters and associations. The median ages of the associations increases from log(age/yr) = 6.6 to log(age/yr) = 6.9 as the spatial scale increases from 8 pc to 64 pc for both galaxies. We find that the youngest stellar associations, with ages < 3 Myr, indeed closely trace H ii regions in H$\alpha$ imaging, and that older associations are increasingly anti-correlated with the H$\alpha$ emission. Owing to our new method, the PHANGS-HST multi-scale associations provide a far more complete census of recent star formation activity than found with previous cluster and compact association catalogues. The method presented here will be applied to the full sample of 38 PHANGS-HST galaxies.Comment: Submitted to MNRAS. Referee report received with minor comments, and "request to clarify if the smaller associations are always included in the larger ones and how this may affect the photometric fitting of the larger association if the groups have different ages." Revision in progres

PHANGS: Constraining Star Formation Timescales Using the Spatial Correlations of Star Clusters and Giant Molecular Clouds

In the hierarchical view of star formation, giant molecular gas clouds (GMCs) undergo fragmentation to form small-scale structures made up of stars and star clusters. Here we study the connection between young star clusters and cold gas across a range of extragalactic environments by combining the high resolution (1") PHANGS-ALMA catalogue of GMCs with the star cluster catalogues from PHANGS-HST. The star clusters are spatially matched with the GMCs across a sample of 11 nearby star-forming galaxies with a range of galactic environments (centres, bars, spiral arms, etc.). We find that after 4-6 Myr the star clusters are no longer associated with any gas clouds. Additionally, we measure the autocorrelation of the star clusters and GMCs as well as their cross-correlation to quantify the fractal nature of hierarchical star formation. Young ($\leq$ 10 Myr) star clusters are more strongly autocorrelated on kpc and smaller spatial scales than the >10 Myr stellar populations, indicating that the hierarchical structure dissolves over time.Comment: 15 pages, 11 figures, 4 tables. Accepted to MNRAS Sept 6 202

SeamlessM4T-Massively Multilingual & Multimodal Machine Translation

What does it take to create the Babel Fish, a tool that can help individuals translate speech between any two languages? While recent breakthroughs in text-based models have pushed machine translation coverage beyond 200 languages, unified speech-to-speech translation models have yet to achieve similar strides. More specifically, conventional speech-to-speech translation systems rely on cascaded systems that perform translation progressively, putting high-performing unified systems out of reach. To address these gaps, we introduce SeamlessM4T, a single model that supports speech-to-speech translation, speech-to-text translation, text-to-speech translation, text-to-text translation, and automatic speech recognition for up to 100 languages. To build this, we used 1 million hours of open speech audio data to learn self-supervised speech representations with w2v-BERT 2.0. Subsequently, we created a multimodal corpus of automatically aligned speech translations. Filtered and combined with human-labeled and pseudo-labeled data, we developed the first multilingual system capable of translating from and into English for both speech and text. On FLEURS, SeamlessM4T sets a new standard for translations into multiple target languages, achieving an improvement of 20% BLEU over the previous SOTA in direct speech-to-text translation. Compared to strong cascaded models, SeamlessM4T improves the quality of into-English translation by 1.3 BLEU points in speech-to-text and by 2.6 ASR-BLEU points in speech-to-speech. Tested for robustness, our system performs better against background noises and speaker variations in speech-to-text tasks compared to the current SOTA model. Critically, we evaluated SeamlessM4T on gender bias and added toxicity to assess translation safety. Finally, all contributions in this work are open-sourced and accessible at https://github.com/facebookresearch/seamless_communicatio

Robust estimation of bacterial cell count from optical density

Optical density (OD) is widely used to estimate the density of cells in liquid culture, but cannot be compared between instruments without a standardized calibration protocol and is challenging to relate to actual cell count. We address this with an interlaboratory study comparing three simple, low-cost, and highly accessible OD calibration protocols across 244 laboratories, applied to eight strains of constitutive GFP-expressing E. coli. Based on our results, we recommend calibrating OD to estimated cell count using serial dilution of silica microspheres, which produces highly precise calibration (95.5% of residuals &lt;1.2-fold), is easily assessed for quality control, also assesses instrument effective linear range, and can be combined with fluorescence calibration to obtain units of Molecules of Equivalent Fluorescein (MEFL) per cell, allowing direct comparison and data fusion with flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data

Height and body-mass index trajectories of school-aged children and adolescents from 1985 to 2019 in 200 countries and territories: a pooled analysis of 2181 population-based studies with 65 million participants

Summary Background Comparable global data on health and nutrition of school-aged children and adolescents are scarce. We aimed to estimate age trajectories and time trends in mean height and mean body-mass index (BMI), which measures weight gain beyond what is expected from height gain, for school-aged children and adolescents. Methods For this pooled analysis, we used a database of cardiometabolic risk factors collated by the Non-Communicable Disease Risk Factor Collaboration. We applied a Bayesian hierarchical model to estimate trends from 1985 to 2019 in mean height and mean BMI in 1-year age groups for ages 5–19 years. The model allowed for non-linear changes over time in mean height and mean BMI and for non-linear changes with age of children and adolescents, including periods of rapid growth during adolescence. Findings We pooled data from 2181 population-based studies, with measurements of height and weight in 65 million participants in 200 countries and territories. In 2019, we estimated a difference of 20 cm or higher in mean height of 19-year-old adolescents between countries with the tallest populations (the Netherlands, Montenegro, Estonia, and Bosnia and Herzegovina for boys; and the Netherlands, Montenegro, Denmark, and Iceland for girls) and those with the shortest populations (Timor-Leste, Laos, Solomon Islands, and Papua New Guinea for boys; and Guatemala, Bangladesh, Nepal, and Timor-Leste for girls). In the same year, the difference between the highest mean BMI (in Pacific island countries, Kuwait, Bahrain, The Bahamas, Chile, the USA, and New Zealand for both boys and girls and in South Africa for girls) and lowest mean BMI (in India, Bangladesh, Timor-Leste, Ethiopia, and Chad for boys and girls; and in Japan and Romania for girls) was approximately 9–10 kg/m2. In some countries, children aged 5 years started with healthier height or BMI than the global median and, in some cases, as healthy as the best performing countries, but they became progressively less healthy compared with their comparators as they grew older by not growing as tall (eg, boys in Austria and Barbados, and girls in Belgium and Puerto Rico) or gaining too much weight for their height (eg, girls and boys in Kuwait, Bahrain, Fiji, Jamaica, and Mexico; and girls in South Africa and New Zealand). In other countries, growing children overtook the height of their comparators (eg, Latvia, Czech Republic, Morocco, and Iran) or curbed their weight gain (eg, Italy, France, and Croatia) in late childhood and adolescence. When changes in both height and BMI were considered, girls in South Korea, Vietnam, Saudi Arabia, Turkey, and some central Asian countries (eg, Armenia and Azerbaijan), and boys in central and western Europe (eg, Portugal, Denmark, Poland, and Montenegro) had the healthiest changes in anthropometric status over the past 3·5 decades because, compared with children and adolescents in other countries, they had a much larger gain in height than they did in BMI. The unhealthiest changes—gaining too little height, too much weight for their height compared with children in other countries, or both—occurred in many countries in sub-Saharan Africa, New Zealand, and the USA for boys and girls; in Malaysia and some Pacific island nations for boys; and in Mexico for girls. Interpretation The height and BMI trajectories over age and time of school-aged children and adolescents are highly variable across countries, which indicates heterogeneous nutritional quality and lifelong health advantages and risks

The first 20 months of the COVID-19 pandemic: Mortality, intubation and ICU rates among 104,590 patients hospitalized at 21 United States health systems

Main objective There is limited information on how patient outcomes have changed during the COVID-19 pandemic. This study characterizes changes in mortality, intubation, and ICU admission rates during the first 20 months of the pandemic. Study design and methods University of Wisconsin researchers collected and harmonized electronic health record data from 1.1 million COVID-19 patients across 21 United States health systems from February 2020 through September 2021. The analysis comprised data from 104,590 adult hospitalized COVID-19 patients. Inclusion criteria for the analysis were: (1) age 18 years or older; (2) COVID-19 ICD-10 diagnosis during hospitalization and/or a positive COVID-19 PCR test in a 14-day window (+/- 7 days of hospital admission); and (3) health system contact prior to COVID-19 hospitalization. Outcomes assessed were: (1) mortality (primary), (2) endotracheal intubation, and (3) ICU admission. Results and significance The 104,590 hospitalized participants had a mean age of 61.7 years and were 50.4% female, 24% Black, and 56.8% White. Overall risk-standardized mortality (adjusted for age, sex, race, ethnicity, body mass index, insurance status and medical comorbidities) declined from 16% of hospitalized COVID-19 patients (95% CI: 16% to 17%) early in the pandemic (February-April 2020) to 9% (CI: 9% to 10%) later (July-September 2021). Among subpopulations, males (vs. females), those on Medicare (vs. those on commercial insurance), the severely obese (vs. normal weight), and those aged 60 and older (vs. younger individuals) had especially high mortality rates both early and late in the pandemic. ICU admission and intubation rates also declined across these 20 months. Conclusions Mortality, intubation, and ICU admission rates improved markedly over the first 20 months of the pandemic among adult hospitalized COVID-19 patients although gains varied by subpopulation. These data provide important information on the course of COVID-19 and identify hospitalized patient groups at heightened risk for negative outcomes. Trial registration ClinicalTrials.gov Identifier: NCT04506528 (https://clinicaltrials.gov/ct2/show/NCT04506528)