Large-eddy simulation (LES) is performed to study the tip vortex flow in a ducted propulsor geometry replicating the experiments of Chesnakas & Jessup (2003, pp. 257–267), Oweis et al. (2006a J. Fluids Engng 128, 751–764) and Oweis et al. (2006b J. Fluids Engng 128, 751–764). Inception of cavitation in these marine propulsion systems is closely tied to the unsteady interactions between multiple vortices in the tip region. Here LES is used to shed insight into the structure of the tip vortex flow. Simulation results are able to predict experimental propeller loads and show agreement with laser Doppler velocimetry measurements in the blade wake at design advance ratio, $J=0.98$. Results show the pressure differential across the blade produces a leakage vortex which separates off the suction side blade tip upstream of the trailing edge. The separation sheet aft of the primary vortex separation point is shown to take the form of a skewed shear layer which produces a complex arrangement of unsteady vortices corotating and counter-rotating with the primary vortex. Blade tip boundary layer vortices are reoriented to align with the leakage flow and produce instantaneous low-pressure regions wrapping helically around the primary vortex core. Such low-pressure regions are seen both upstream and downstream of the propeller blade trailing edge. The trailing edge wake is found to only rarely have a low-pressure vortex core. Statistics of instantaneous low pressures below the minimum mean pressure are found to be concentrated downstream of the blade’s trailing edge wake crossing over the primary vortex core and continue in excess of 40 % chord length behind the trailing edge. The rollup of the leakage flow duct boundary layer behind the trailing edge is also seen to produce counter-rotating vortices which interact with the primary leakage vortex and contribute to strong stretching events.

Gastrointestinal infections significantly impact African low- and middle-income countries, although, accurate data on acute gastrointestinal illness (AGI) for all ages are lacking. This study aimed to describe the epidemiology of AGI in Ethiopia, Mozambique, Nigeria, and Tanzania. A population survey was conducted in one urban and one rural site per country, from 01 October 2020 to 30 September 2021, using web-based and face-to-face tools (n = 4417). The survey tool was adapted from high-income countries, ensuring comparability through an internationally recommended AGI case definition. Ethiopia had the highest AGI incidence (0.87 episodes per person-year), followed by Mozambique (0.58), Tanzania (0.41), and Nigeria (0.34). Age-standardized incidence was highest in Mozambique (1.46) and Ethiopia (1.25), compared to Tanzania (0.58) and Nigeria (0.33). The 4-week prevalence was 6.4% in Ethiopia and 4.3% in Mozambique, compared to 3.1% in Tanzania and 2.6% in Nigeria. AGI lasted an average of 5.3 days in Ethiopia and 3.0 to 3.4 days elsewhere. Children under five had 4.4 times higher AGI odds (95% CI: 2.8, 6.7) than those aged 15-59. The study provides empirical data on the incidence and demographic determinants of AGI in these four countries.

Objectives/Goals: Methicillin-resistant Staphylococcus aureus (MRSA) is a human bacterial pathogen and is classified as a serious threat. MRSA has become resistant to most B-lactam antibiotics (penicillins and cephalosporins). The goal of this study is to identify an antibiotic adjuvant capable of resurrecting B-lactams for the treatment of MRSA infections. Methods/Study Population: A fluorescence-reporter assay was used to screen a compound library. Minimum-inhibitory concentrations were assessed for the compounds against various MSSA and MRSA strains. A common resistance mechanism to B-lactams by MRSA is by the function of the bla operon. One gene in this operon encodes for a B-lactam sensor/signal transducer protein BlaR, the primary target of this study. Inhibition of BlaR by compound 1 (best potentiator of oxacillin) was studied by nano-differential scanning fluorimetry (nanoDSF), surface plasmon resonance (SPR), scanning electron microscopy (SEM), and time-kill assays. Results/Anticipated Results: We identified 80 compound hits from a 1,974-compound NCI library. Twenty-four compounds showed potentiating ability (2- to 4,096-fold decrease in MIC for oxacillin). Seven compounds exhibited melting temperature shifts by nanoDSF of BlaR, indicating binding. SPR determined compound 1 has a binding affinity of 31 micromolar to BlaR-SD. SEM images showed disruption in the S. aureus cell wall on exposure to compound 1 and oxacillin. S. aureus N315 showed 3-log reduction in bacterial count treated with a mixture of compound 1 and oxacillin. Discussion/Significance of Impact: Compound 1 targets BlaR-SD, which restores S. aureus susceptibility to treatment by oxacillin. There are currently few antibiotics available in the clinic capable of treating MRSA infections. The combination hold promise of a treatment option for MRSA.

The need for collaborative and transparent sharing of COVID-19 clinical trial and large-scale observational study data to accelerate scientific discovery and inform clinical practice is critical. Responsible data-sharing requires addressing challenges associated with data privacy and confidentiality, data linkage, data quality, variable harmonization, data formats, and comprehensive metadata documentation to produce a high-quality, contextually rich, findable, accessible, interoperable, and reusable (FAIR) dataset. This communication explores the experiences and lessons learned from sharing National Heart Lung and Blood Institute (NHLBI) COVID-19 clinical trial (including adaptive platform trials) and cohort study datasets through the NHLBI BioData Catalyst® (BDC) ecosystem, focusing on the challenges and successes of harmonizing these datasets for broader research use. Our findings highlight the importance of establishing standardized data formats, adopting common data elements and creating and maintaining robust data governance structures that address common challenges (i.e., data privacy and data-sharing limitations resulting from informed consent). These efforts resulted in a set of comprehensive and interoperable datasets from 5 clinical trials and 13 cohort studies that will enable downstream reuse in analyses and collaborations. The principles and strategies outlined, derived through experience with consortia data, can lay the groundwork for advancing collaborative and efficient data sharing.

We conduct a laboratory experiment among male participants to investigate whether rewarding schemes that depend on work performance—in particular, tournament incentives—induce more stress than schemes that are independent of performance—fixed payment scheme. Stress is measured over the entire course of the experiment at both the hormonal and psychological level. Hormonal stress responses are captured by measuring salivary cortisol levels. Psychological stress responses are measured by self-reported feelings of stress and primary appraisals. We find that tournament incentives induce a stress response whereas a fixed payment does not induce stress. This stress response does not differ significantly across situations in which winners and losers of the tournament are publically announced and situations in which this information remains private. Biological and psychological stress measures are positively correlated, i.e. increased levels of cortisol are associated with stronger feelings of stress. Nevertheless, neither perceived psychological stress nor elevated cortisol levels in a previous tournament predict a subsequent choice between tournaments and fixed payment schemes, indicating that stress induced by incentives schemes is not a relevant criterion for sorting decisions in our experiment. Finally, we find that cortisol levels are severely elevated at the beginning of the experiment, suggesting that participants experience stress in anticipation of the experiment per se, potentially due to uncertainties associated with the unknown lab situation. We call this the novelty effect.

We conduct a laboratory experiment among male participants to investigate whether rewarding schemes that depend on work performance—in particular, tournament incentives—induce more stress than schemes that are independent of performance—fixed payment scheme. Stress is measured over the entire course of the experiment at both the hormonal and psychological level. Hormonal stress responses are captured by measuring salivary cortisol levels. Psychological stress responses are measured by self-reported feelings of stress and primary appraisals. We find that tournament incentives induce a stress response whereas a fixed payment does not induce stress. This stress response does not differ significantly across situations in which winners and losers of the tournament are publicly announced and situations in which this information remains private. Biological and psychological stress measures are positively correlated, i.e., increased levels of cortisol are associated with stronger feelings of stress. Nevertheless, neither perceived psychological stress nor elevated cortisol levels in a previous tournament predict a subsequent choice between tournaments and fixed payment schemes, indicating that stress induced by incentives schemes is not a relevant criterion for sorting decisions in our experiment. Finally, we find that cortisol levels are severely elevated at the beginning of the experiment, suggesting that participants experience stress in anticipation of the experiment per se, potentially due to uncertainties associated with the unknown lab situation. We call this the novelty effect.

In functional magnetic resonance imaging (fMRI), the blood oxygenation level dependent (BOLD) signal is often interpreted as a measure of neural activity. However, because the BOLD signal reflects the complex interplay of neural, vascular, and metabolic processes, such an interpretation is not always valid. There is growing evidence that changes in the baseline neurovascular state can result in significant modulations of the BOLD signal that are independent of changes in neural activity. This paper introduces some of the normalization and calibration methods that have been proposed for making the BOLD signal a more accurate reflection of underlying brain activity for human fMRI studies.

Functional magnetic resonance imaging (fMRI) is a noninvasive method for measuring brain function by correlating temporal changes in local cerebral blood oxygenation with behavioral measures. fMRI is used to study individuals at single time points, across multiple time points (with or without intervention), as well as to examine the variation of brain function across normal and ill populations. fMRI may be collected at multiple sites and then pooled into a single analysis. This paper describes how fMRI data is analyzed at each of these levels and describes the noise sources introduced at each level.

In the current paper, we review existing tools for solving variable selection problems in psychology. Modern regularization methods such as lasso regression have recently been introduced in the field and are incorporated into popular methodologies, such as network analysis. However, several recognized limitations of lasso regularization may limit its suitability for psychological research. In this paper, we compare the properties of lasso approaches used for variable selection to Bayesian variable selection approaches. In particular we highlight advantages of stochastic search variable selection (SSVS), that make it well suited for variable selection applications in psychology. We demonstrate these advantages and contrast SSVS with lasso type penalization in an application to predict depression symptoms in a large sample and an accompanying simulation study. We investigate the effects of sample size, effect size, and patterns of correlation among predictors on rates of correct and false inclusion and bias in the estimates. SSVS as investigated here is reasonably computationally efficient and powerful to detect moderate effects in small sample sizes (or small effects in moderate sample sizes), while protecting against false inclusion and without over-penalizing true effects. We recommend SSVS as a flexible framework that is well-suited for the field, discuss limitations, and suggest directions for future development.