Predicting particle segregation has remained challenging due to the lack of a general model for the segregation velocity that is applicable across a range of granular flow geometries. Here, a segregation-velocity model for dense granular flows is developed by exploiting force balance and recent advances in particle-scale modelling of the segregation driving and drag forces over the entire particle concentration range, size ratios up to 3 and inertial numbers as large as 0.4. This model is shown to correctly predict particle segregation velocity in a diverse set of idealised and natural granular flow geometries simulated using the discrete element method. When incorporated in the well-established advection–diffusion–segregation formulation, the model has the potential to accurately capture segregation phenomena in many relevant industrial applications and geophysical settings.

In this paper, we examine a major transparency initiative affecting tax abatements for state and local economic development in the United States that has been plagued by noncompliance. Unlike academic studies examining government compliance with transparency rules such as Freedom of Information Act (FOIA) requests, we examine government and independent auditor responses to inquiries about information already posted, or not posted, in annual financial reports. Using a pre-registered experimental approach on cities, counties, and school districts in a single large-population state (Texas), we remind entities and their external auditors of their transparency obligations as well as our ability to check their compliance with this transparency rule and ask these entities follow-up questions about their required posts. Against expectations, we found that entities were not significantly more likely to comply with our request for information when we reminded them of their disclosure obligations and we found some evidence that nudges made entities less likely to comply. We argue these results provide novel insights into the limitations of transparency initiatives.

Ice shelves affect the stability of ice sheets by supporting the mass balance of ice upstream of the grounding line. Marine ice, formed from supercooled water freezing at the base of ice shelves, contributes to mass gain and affects ice dynamics. Direct measurements of marine ice thickness are rare due to the challenges of borehole drilling. Here we assume hydrostatic equilibrium to estimate marine ice distribution beneath the Amery Ice Shelf (AIS) using meteoric ice-thickness data obtained from radio-echo sounding collected during the Chinese National Antarctic Research Expedition between 2015 and 2019. This is the first mapping of marine ice beneath the AIS in nearly 20 years. Our new estimates of marine ice along two longitudinal bands beneath the northwest AIS are spatially consistent with earlier work but thicker. We also find a marine ice layer exceeding 30 m of thickness in the central ice shelf and patchy refreezing downstream of the grounding line. Thickness differences from prior results may indicate time-variation in basal melting and freezing patterns driven by polynya activity and coastal water intrusions masses under the ice shelf, highlighting that those changes in ice–ocean interaction are impacting ice-shelf stability.

Using National Healthcare Safety Network data, an interrupted time series of intravenous antimicrobial starts (IVAS) among hemodialysis patients was performed. Annual adjusted rates decreased by 6.64% (January 2012–March 2020) and then further decreased by 8.91% until December 2021. IVAS incidence trends have decreased since 2012, including during the early COVID-19 pandemic.

We examined the association between influenza vaccination policies at acute care hospitals and influenza vaccination coverage among healthcare personnel for the 2021–22 influenza season. Mandatory vaccination and masking for unvaccinated personnel were associated with increased odds of vaccination. Hospital employees had higher vaccination coverage than licensed independent practitioners.

The dynamic behaviour of helicopter during water impact, considering variations in initial downward velocity and pitching angle, have been investigated numerically and theoretically in the present study. The air-water two-phase flows are simulated by solving unsteady Reynolds-averaged Navier-Stokes equations enclosed by standard $k - \omega $ turbulence model. A treatment for computational domain in combination with a global dynamic mesh technique is applied to deal with the relative motion between the helicopter and water. Results indicate that the initial downward velocity of helicopter exhibits behaviour similar to that of a V-shaped body impacting on water, as does the initial pitching angle. To extend the theoretical approach for predicting the kinematic parameters during helicopter ditching, a shape factor capturing the combined effect of various attributes and an average deadrise angle for asymmetric wedges are also introduced.

Mediation analysis constitutes an important part of treatment study to identify the mechanisms by which an intervention achieves its effect. Structural equation model (SEM) is a popular framework for modeling such causal relationship. However, current methods impose various restrictions on the study designs and data distributions, limiting the utility of the information they provide in real study applications. In particular, in longitudinal studies missing data is commonly addressed under the assumption of missing at random (MAR), where current methods are unable to handle such missing data if parametric assumptions are violated.

In this paper, we propose a new, robust approach to address the limitations of current SEM within the context of longitudinal mediation analysis by utilizing a class of functional response models (FRM). Being distribution-free, the FRM-based approach does not impose any parametric assumption on data distributions. In addition, by extending the inverse probability weighted (IPW) estimates to the current context, the FRM-based SEM provides valid inference for longitudinal mediation analysis under the two most popular missing data mechanisms; missing completely at random (MCAR) and missing at random (MAR). We illustrate the approach with both real and simulated data.

In the study of human dynamics, the behavior under study is often operationalized by tallying the frequencies and intensities of a collection of lower-order processes. For instance, the higher-order construct of negative affect may be indicated by the occurrence of crying, frowning, and other verbal and nonverbal expressions of distress, fear, anger, and other negative feelings. However, because of idiosyncratic differences in how negative affect is expressed, some of the lower-order processes may be characterized by sparse occurrences in some individuals. To aid the recovery of the true dynamics of a system in cases where there may be an inflation of such “zero responses,” we propose adding a regime (unobserved phase) of “non-occurrence” to a bivariate Ornstein–Uhlenbeck (OU) model to account for the high instances of non-occurrence in some individuals while simultaneously allowing for multivariate dynamic representation of the processes of interest under nonzero responses. The transition between the occurrence (i.e., active) and non-occurrence (i.e., inactive) regimes is represented using a novel latent Markovian transition model with dependencies on latent variables and person-specific covariates to account for inter-individual heterogeneity of the processes. Bayesian estimation and inference are based on Markov chain Monte Carlo algorithms implemented using the JAGS software. We demonstrate the utility of the proposed zero-inflated regime-switching OU model to a study of young children’s self-regulation at 36 and 48 months.

A growing number of social scientists have turned to differential equations as a tool for capturing the dynamic interdependence among a system of variables. Current tools for fitting differential equation models do not provide a straightforward mechanism for diagnosing evidence for qualitative shifts in dynamics, nor do they provide ways of identifying the timing and possible determinants of such shifts. In this paper, we discuss regime-switching differential equation models, a novel modeling framework for representing abrupt changes in a system of differential equation models. Estimation was performed by combining the Kim filter (Kim and Nelson State-space models with regime switching: classical and Gibbs-sampling approaches with applications, MIT Press, Cambridge, 1999) and a numerical differential equation solver that can handle both ordinary and stochastic differential equations. The proposed approach was motivated by the need to represent discrete shifts in the movement dynamics of $n=29$\documentclass[12pt]{minimal}\usepackage{amsmath}\usepackage{wasysym}\usepackage{amsfonts}\usepackage{amssymb}\usepackage{amsbsy}\usepackage{mathrsfs}\usepackage{upgreek}\setlength{\oddsidemargin}{-69pt}\begin{document}$$n= 29$$\end{document} mother–infant dyads during the Strange Situation Procedure (SSP), a behavioral assessment where the infant is separated from and reunited with the mother twice. We illustrate the utility of a novel regime-switching differential equation model in representing children’s tendency to exhibit shifts between the goal of staying close to their mothers and intermittent interest in moving away from their mothers to explore the room during the SSP. Results from empirical model fitting were supplemented with a Monte Carlo simulation study to evaluate the use of information criterion measures to diagnose sudden shifts in dynamics.

The Aerospace Integration Research Centre (AIRC) at Cranfield University offers industry and academia an open environment to explore the opportunities for efficient integration of aircraft systems. As a part of the centre, Cranfield University, Rolls-Royce, and DCA Design International jointly have developed the Future Systems Simulator (FSS) for the purpose of research and development in areas such as human factors in aviation, single-pilot operations, future cockpit design, aircraft electrification, and alternative control approaches. Utilising the state-of-the-art modularity principles in simulation technology, the FSS is built to simulate a diverse range of current and novel aircraft, enabling researchers and industry partners to conduct experiments rapidly and efficiently. Central to the requirement, a unique, user-experience-centred development and design process is implemented for the development of the FSS. This paper presents the development process of such a flight simulator with an innovative flight deck. Furthermore, the paper demonstrates the FSS’s capabilities through case studies. The cutting-edge versatility and flexibility of the FSS are demonstrated through the diverse example research case studies. In the final section, the authors provide guidance for the development of an engineering flight simulator based on lessons learned in this project.

Previous animal studies found beneficial effects of choline and betaine on maternal glucose metabolism during pregnancy, but few human studies explored the association between choline or betaine intake and incident gestational diabetes mellitus (GDM). We aimed to explore the correlation of dietary choline or betaine intake with GDM risk among Chinese pregnant women. A total of 168 pregnant women with GDM cases and 375 healthy controls were enrolled at the Seventh People’s Hospital in Shanghai during their GDM screening at 24–28 gestational weeks. A validated semi-quantitative FFQ was used to estimate choline and betaine consumption through face-to-face interviews. An unconditional logistic regression model was adopted to examine OR and 95 % CI. Compared with the controls, those women with GDM incidence were likely to have higher pre-pregnancy BMI, be older, have more parities and have higher plasma TAG and lower plasma HDL-cholesterol. No significant correlation was observed between the consumption of choline or betaine and incident GDM (adjusted OR (95 % CI), 0·77 (0·41, 1·43) for choline; 0·80 (0·42, 1·52) for betaine). However, there was a significant interaction between betaine intake and parity on the risk of GDM (Pfor interaction = 0·01). Among those women with no parity history, there was a significantly inverse correlation between betaine intake and GDM risk (adjusted OR (95 % CI), 0·25 (0·06, 0·81)). These findings indicated that higher dietary betaine intake during pregnancy might be considered a protective factor for GDM among Chinese women with no parity history.

One species-general life history (LH) principle posits that challenging childhood environments are coupled with a fast or faster LH strategy and associated behaviors, while secure and stable childhood environments foster behaviors conducive to a slow or slower LH strategy. This coupling between environments and LH strategies is based on the assumption that individuals’ internal traits and states are independent of their external surroundings. In reality, individuals respond to external environmental conditions in alignment with their intrinsic vitality, encompassing both physical and mental states. The present study investigated attachment as an internal mental state, examining its role in mediating and moderating the association between external environmental adversity and fast LH strategies. A sample of 1169 adolescents (51% girls) from 9 countries was tracked over 10 years, starting from age 8. The results confirm both mediation and moderation and, for moderation, secure attachment nullified and insecure attachment maintained the environment-LH coupling. These findings suggest that attachment could act as an internal regulator, disrupting the contingent coupling between environmental adversity and a faster pace of life, consequently decelerating human LH.

Particle segregation in dense flowing size-disperse granular mixtures is driven by gravity and shear, but predicting the associated segregation force due to both effects has remained an unresolved challenge. Here, a model of the combined gravity- and kinematics-induced segregation force on a single intruder particle is integrated with a model of the concentration dependence of the gravity-induced segregation force. The result is a general model of the net particle segregation force in flowing size-bidisperse granular mixtures. Using discrete element method simulations for comparison, the model correctly predicts the segregation force for a variety of mixture concentrations and flow conditions in both idealized and natural shear flows.

OBJECTIVES/GOALS: There is a scarcity of research examining the views of Black and Latine HIV care consumers on healthcare experiences that influence medical mistrust. The present qualitative study aims to bridge the existing gaps in the literature pertaining to the experiences of Black and Latine HIV care consumers. METHODS/STUDY POPULATION: We conducted 21 semi-structured interviews with Black and Latine HIV care consumers from November to December 2021 to explore perceptions of provider behaviors that increase or decrease HIV care consumers’ trust and mistrust, experiences of stigma, and behaviors and responses when experiencing medical mistrust. Conventional content analysis was conducted to derive meaning from the narratives shared by participants. RESULTS/ANTICIPATED RESULTS: Provider behaviors that increase HIV care consumers’ mistrust include lack of person-centered care, lack of partnership in health decision making, perceived provider incompetence, lack of adequate follow-up to care, and lack of trustworthiness of providers and organizations. Perceived experiences of intersectional stigma in healthcare included feeling judged and discriminated against by healthcare providers regarding HIV status and observing differential care outcomes and delayed care delivery by race and ethnicity. DISCUSSION/SIGNIFICANCE: Findings can inform the development of provider-level interventions to address medical mistrust.

OBJECTIVES/GOALS: Healthcare sectors are rushing to develop AI models. Yet, a dearth of coordinated practices leaves many teams struggling to implement models into practice. The Enterprise AI Translation Advisory Board uses across-disciplinary team to facilitate AI translation. METHODS/STUDY POPULATION: The Mayo Clinic Enterprise AI Translation Advisory Board was established to assess AI solutions lever aging cross-disciplinary team science to accelerate AI innovation and translation. The 23-member board reflects expertise in data science, qualitative research, user experience, IT, human factors, informatics, regulatory compliance,ethics, and clinical care, with members spanning thought leadership, decision-making, and clinical practice. Taking an approach of respectful communication, transparency, scientific debate, and open discussion, the Board has consulted onover two dozen projects at various stages of the AI life cycle. RESULTS/ANTICIPATED RESULTS: Common issues identified for projects earlier in the AI life cycle, sometimes fatal but often address able once identified, include a lack of buy-in from potential product users, a lack of planningabout integration into clinical workflow, inadequately labeled data, and attempting to use machine learning when what is desired is really a causal model for intervening. Recommendations for projects later in the AI life cycle include details of a testing plan (silent evaluation, pragmatic clinical trials), advice about clinical integration, both post-hoc and on going auditing for performance disparities, and planning for regulatory clearance. DISCUSSION/SIGNIFICANCE: Advising is more valuable for projects at the ideation phase, when multi disciplinary interrogation can identify weaknesses. But at all phases, projects have gaps related to a lack of specific disciplinary expertise. A multi disciplinary cluster like the AI Translation Advisory Board seeks to address these gaps.

To improve contact tracing for healthcare workers, we built and configured a Bluetooth low-energy system. We predicted close contacts with great accuracy and provided an additional contact yield of 14.8%. This system would decrease the effective reproduction number by 56% and would unnecessarily quarantine 0.74% of employees weekly.

Recruiting persons with dementia for clinical trials can be challenging. Building on a guide initially developed to assist primary-care-based memory clinics in their efforts to support research, a key stakeholder working group meeting was held to develop a standardized research recruitment process, with input from patients, care partners, researchers, and clinicians. Discussions in this half-day facilitated meeting focused on the wishes and needs of patients and care partners, policy and procedures for researchers, information provided to patients, and considerations for memory clinics. Patients and care partners valued the opportunity to contribute to science and provided important insights on how to best facilitate recruitment. Discussions regarding proposed processes and procedures for research recruitment highlighted the need for a new, patient-driven approach. Accordingly, a key stakeholder co-designed “Memory Clinic Research Match” program was developed that has the potential to overcome existing barriers and to increase recruitment for dementia-related research.