As with many other musical traits, the social environment is a key influence on the development of singing ability. While the familial singing environment is likely to be formative, its role relative to other environmental influences such as training is unclear. We used structural equation modeling to test relationships among demographic characteristics, familial environmental variables (early and current singing with family), vocal training, and singing ability in a large, previously documented sample of Australian twins (N = 1163). Notably, early singing with family, and to a lesser extent vocal training, predicted singing ability, whereas current singing with family did not. Early familial singing also mediated the relationship between sex and singing ability, with men who sang less with family during childhood showing poorer ability. Bivariate twin models between early familial singing and singing ability showed the phenotypic correlation was largely explained by shared environmental influences. This raises the possibility of a sensitive period for singing ability, with sociocultural expectations around singing potentially differentiating the developmental trajectories of this skill for men and women.

Health equity gaps persist across minoritized groups due to systems of oppression affecting health-related social needs such as access to transportation, education and literacy, or food and housing security. Consequently, disparities in the prevalence of multidrug-resistant infections, infectious disease outcomes, and inappropriate antimicrobial use have been reported across minoritized populations. The Joint Commission and Centers for Medicare and Medicaid Services (CMS) have formally acknowledged the importance of integrating health equity-focused initiatives into existing hospital quality improvement (QI) programs. Here, we review documented disparities in antimicrobial stewardship and offer a framework, derived from components of existing health equity and QI tools, to guide clinicians in prioritizing equity in antimicrobial stewardship efforts (EASE).

OBJECTIVES/GOALS: This work aims to explore how citizen science serves as a transformative frame work to bridge scientific knowledge, focusing on its potential to enhance transdisciplinary learning in artificial intelligence (AI) biomedical and clinical sciences by facilitating near-peer mentoring. METHODS/STUDY POPULATION: Our group of eight friends comprise a multicultural and multidisciplinary cohort including students from the USA, Philippines, Indonesia, and Guatemala pursuing PhD degrees in electrical and computer engineering, epidemiology, physics, and MD, PharmD, and DMD degrees. We engage in shared online courses, collaborative projects, and abstract submissions. Employing our collective knowledge, we design interactive learning experiences, support each other’s initiatives, and collaboratively develop lectures and presentations. We in tend to expand collaborations in biomedical AI education while fostering principles of experiential and collaborativelearning, constructivism, and authentic inquiry. RESULTS/ANTICIPATED RESULTS: Our recent successes include submittedconference abstracts on data science and AI education in pharmacy and the facilitation of a guest lecture in health informatics. Additionally, we are currently collaborating on seven biomedical machine learning projects in radio frequency engineering, aiming for conference submissions. Moving forward, our goal is to expand our group, support the formation of similar communities, and promote data science and AI literacy in biomedical and clinical contexts. We aspire to extend this knowledge to families, classmates, and eventually patients, facilitating a broader understanding of the role of AI in healthcare. DISCUSSION/SIGNIFICANCE: We believe diverse expertise and pedagogical theories can help demonstrate the potential of citizen science to democratize scientific experience. By nurturing collaborative networks our efforts aim to bridge gaps between disciplines and enhance the broader public’s understanding of AI in healthcare.

Todorokite is a common Mn oxide mineral in terrestrial and ocean-floor environments, and it is commonly synthesized from layered Na-buserite. Pyrophosphate, which is known to form strong complexes with Mn(III) at a pH range of 1–8, was added to a suspension of Na-buserite in order to sequester the available Mn(III) in Na-buserite. No Mn(III)-pyrophosphate complex was formed in solution at pH 10, and the treated Na-buserites were converted completely to todorokite. Significant transformation reductions were observed when Na-buserite was treated with pyrophosphate solution at pH 7. The presence of Mn(III) within the MnO6 octahedral sheets of Na-buserite is critical for the transformation from layered buserite to tunnel-structured todorokite at atmospheric pressure. At lower pH, two effects are combined to reduce the amount of Mn(III) in the layers: (1) the complexing power of pyrophosphate is increased; and (2) the transformation from Na-buserite to H-birnessite, which is concomitant with the migration of Mn(III) from layers to the interlayer, and the partial disproportionation of Mn(III). The results showed that Mn(III) played a key role in the transformation of layered Na-buserite to tunnel-structured todorokite at atmospheric pressure.

Objectives: HCWs are recommended to wipe the computers with alcohol wipes before clinical use. Compliance assessment by direct observation is resource intensive. We used ATP measurement as a surrogate to assess the compliance to preutilization cleaning of computers. Methods: We conducted a pilot study to determine the median relative light unit (RLU) value reflective of preutilization cleaning of the computers. We identified values of <250, 250–500, and >500 RLU to reflect cleaned, probably cleaned, and not cleaned computers, respectively. Subsequently, we conducted a cross-sectional study of the computers in the inpatient wards in Tan Tock Seng Hospital and National Centre for Infectious Diseases. Using 3M Clean-Trace ATP swabs, we tested 5 computers in each ward: 2 computers on wheels, 2 from the nursing station, and 1 at the patients’ room entrance. All analyses were conducted using STATA version 15 software. Results: Between October 4 and 10, 2021, we collected 219 samples from 219 computers. Among them, 44 (20.1%) were cleaned, 49 (22.4%) were probably cleaned, and 126 (57.5%) computers were not cleaned. Higher compliance to computer cleaning was observed in COVID-19 wards [85 ATP samples; cleaned, 37 (43.5%); probably cleaned, 26 (30.6%); not cleaned, 22 (25.9%)] compared with non–COVID-19 wards [134 ATP samples; cleaned, 7 (5.2%); probably cleaned, 23 (17.2%); not cleaned, 104 (77.6%)] (P < .01). No significant difference was observed in compliance with cleaning computers between the ICU [30 ATP samples; cleaned, 7 (23.3%); probably cleaned, 4 (13.3%); not cleaned, 19 (63.3%)] and general wards [189 ATP samples; cleaned, 37 (19.6%); probably cleaned, 45 (23.8%); not cleaned, 107 (56.6%)] (P = .47). Conclusions: ATP swab tests can be used as a surrogate marker to assess compliance to pre-utilization cleaning of computers. Enhanced awareness of environmental hygiene may explain the higher compliance to computer cleaning observed in COVID-19 wards.

Objectives: In healthcare facilities, environmental reservoirs of CPE are associated with CPE outbreaks. In the newly built NCID building, we studied the introduction of CPE in the aqueous environment. Methods: We sampled the aqueous environments (ie, sink, sink strainer, and shower drain-trap with Copan E-swabs and sink P-trap water) of 4 NCID wards (ie, 2 multidrug-resistant organism (MDRO) wards and 2 non-MDRO wards). Two sampling cycles (cycle 1, June–July 2019 and cycle 2, September–November 2019) were conducted in all 4 wards. Cycle 3 (November 2020) was conducted in 1 non-MDRO ward to investigate CPE colonization from previous cycles. Enterobacterales were identified using MALDI-TOF MS and underwent phenotypic (mCIM and eCIM) and confirmatory PCR tests for CPE. Results: We collected 448, 636, and 96 samples in cycles 1, 2, and 3, respectively. MDRO and non-MDRO wards were operational for 1 and 7 months during the first sampling cycle. The CPE prevalence rates in MDRO wards were 1.67% (95% CI, 0.46% – 4.21%) in cycle 1 and 1.76% (95% CI, 0.65% – 3.80%) in cycle 2. In the aqueous environments in MDRO wards, multiple species were detected (cycle 1: 2 K. pneumoniae, 1 E. coli, and 1 S. marcescens; cycle 2: 5 K. pneumoniae and 1 R. planticola), and multiple genotypes were detected (cycle 1: 3 blaOXA48; cycle 2: 5 blaOXA48 and 1 blaKPC). The CPE prevalence in non-MDRO wards was 1.92% (95% CI, 0.53%–4.85%) in cycle 1. The prevalence rate increased by 5.51% (95% CI, 1.99%–9.03%) to 7.43% (95% CI, 4.72%–11.04%; P = .006) in cycle 2, and by another 2.98% (95% CI, −3.82% to 9.79%) to 10.42% (95% CI, 5.11% – 18.3%; P = .353) in cycle 3. Only blaOXA48 S. marcescens were detected in all cycles (except 1 blaOXA48 K. pneumoniae in cycle 2) in the non-MDRO ward. Conclusions: CPE established rapidly in the aqueous environment of NCID wards, more so in MDRO wards than non-MDRO wards. Longitudinal studies to understand the further expansion of the CPE colonization and its impact on patients are needed.

Eating disorders have the highest mortality rate of any psychiatric condition. Since the COVID-19 pandemic, the number of patients who have required medical stabilisation on paediatric wards has increased significantly. Likewise, the number of patients who have required medical stabilisation against their will as a lifesaving intervention has increased. This paper highlights a fictional case study aiming to explore the legal, ethical and practical considerations a trainee should be aware of. By the end of this article, readers will be more aware of this complex issue and how it might be managed, as well as the impact it can have on the patient, their family and ward staff.

COVID-19 vaccines are likely to be scarce for years to come. Many countries, from India to the U.K., have demonstrated vaccine nationalism. What are the ethical limits to this vaccine nationalism? Neither extreme nationalism nor extreme cosmopolitanism is ethically justifiable. Instead, we propose the fair priority for residents (FPR) framework, in which governments can retain COVID-19 vaccine doses for their residents only to the extent that they are needed to maintain a noncrisis level of mortality while they are implementing reasonable public health interventions. Practically, a noncrisis level of mortality is that experienced during a bad influenza season, which society considers an acceptable background risk. Governments take action to limit mortality from influenza, but there is no emergency that includes severe lockdowns. This “flu-risk standard” is a nonarbitrary and generally accepted heuristic. Mortality above the flu-risk standard justifies greater governmental interventions, including retaining vaccines for a country's own citizens over global need. The precise level of vaccination needed to meet the flu-risk standard will depend upon empirical factors related to the pandemic. This links the ethical principles to the scientific data emerging from the emergency. Thus, the FPR framework recognizes that governments should prioritize procuring vaccines for their country when doing so is necessary to reduce mortality to noncrisis flu-like levels. But after that, a government is obligated to do its part to share vaccines to reduce risks of mortality for people in other countries. We consider and reject objections to the FPR framework based on a country: (1) having developed a vaccine, (2) raising taxes to pay for vaccine research and purchase, (3) wanting to eliminate economic and social burdens, and (4) being ineffective in combating COVID-19 through public health interventions.

In this article, we discuss the backgrounds and technical details about several smart manufacturing projects in a tier-one electronics manufacturing facility. We devise a process to manage logistic forecast and inventory preparation for electronic parts using historical data and a recurrent neural network to achieve significant improvement over current methods. We present a system for automatically qualifying laptop software for mass production through computer vision and automation technology. The result is a reliable system that can save hundreds of man-years in the qualification process. Finally, we create a deep learning-based algorithm for visual inspection of product appearances, which requires significantly less defect training data compared to traditional approaches. For production needs, we design an automatic optical inspection machine suitable for our algorithm and process. We also discuss the issues for data collection and enabling smart manufacturing projects in a factory setting, where the projects operate on a delicate balance between process innovations and cost-saving measures.

We propose an automatable data-driven methodology for robust nonlinear reduced-order modelling from time-resolved snapshot data. In the kinematical coarse-graining, the snapshots are clustered into a few centroids representing the whole ensemble. The dynamics is conceptualized as a directed network, where the centroids represent nodes and the directed edges denote possible finite-time transitions. The transition probabilities and times are inferred from the snapshot data. The resulting cluster-based network model constitutes a deterministic–stochastic grey-box model resolving the coherent-structure evolution. This model is motivated by limit-cycle dynamics, illustrated for the chaotic Lorenz attractor and successfully demonstrated for the laminar two-dimensional mixing layer featuring Kelvin–Helmholtz vortices and vortex pairing, and for an actuated turbulent boundary layer with complex dynamics. Cluster-based network modelling opens a promising new avenue with unique advantages over other model-order reductions based on clustering or proper orthogonal decomposition.