In 2023 the Supreme Court of Mauritius cited human rights and public health arguments to strike down a colonial-era law criminalizing consensual same-sex sex. The parliament of Singapore recently did the same through legislative means. Are these aberrations or a shifting global consensus? This article documents a remarkable shift international legal shift regarding LGBTQ+ sexuality. Analysis of laws from 194 countries across multiple years demonstrates a clear, ongoing trend toward decriminalization globally. Where most countries criminalized same-sex sexuality in the 1980s, now two-thirds of countries do not criminalize under law. Additionally, 28 criminalizing countries in 2024 demonstrate a de facto policy of non-enforcement, a milestone towards legal change that all of the countries that have fully decriminalized since 2017 have taken. This has important public health effects, with health law lessons for an era of multiple pandemics. But amidst this trend, the reverse is occurring in some countries, with a counter-trend toward deeper, harsher criminalization of LGBTQ+ sexuality. Case studies of Angola, Singapore, India, Botswana, Mauritius, Cook Islands, Gabon, and Antigua and Barbuda show many politically- and legally-viable pathways to decriminalization and highlight actors in the executive, legislative, and judicial arenas of government and civil society engaged in legal change.

During the coronavirus disease 2019 pandemic, mathematical modeling has been widely used to understand epidemiological burden, trends, and transmission dynamics, to facilitate policy decisions, and, to a lesser extent, to evaluate infection prevention and control (IPC) measures. This review highlights the added value of using conventional epidemiology and modeling approaches to address the complexity of healthcare-associated infections (HAI) and antimicrobial resistance. It demonstrates how epidemiological surveillance data and modeling can be used to infer transmission dynamics in healthcare settings and to forecast healthcare impact, how modeling can be used to improve the validity of interpretation of epidemiological surveillance data, how modeling can be used to estimate the impact of IPC interventions, and how modeling can be used to guide IPC and antimicrobial treatment and stewardship decision-making. There are several priority areas for expanding the use of modeling in healthcare epidemiology and IPC. Importantly, modeling should be viewed as complementary to conventional healthcare epidemiological approaches, and this requires collaboration and active coordination between IPC, healthcare epidemiology, and mathematical modeling groups.

How was trust created and reinforced between the inhabitants of medieval and early modern cities? And how did the social foundations of trusting relationships change over time? Current research highlights the role of kinship, neighbourhood, and associations, particularly guilds, in creating ‘relationships of trust’ and social capital in the face of high levels of migration, mortality, and economic volatility, but tells us little about their relative importance or how they developed. We uncover a profound shift in the contribution of family and guilds to trust networks among the middling and elite of one of Europe's major cities, London, over three centuries, from the 1330s to the 1680s. We examine almost 15,000 networks of sureties created to secure orphans’ inheritances to measure the presence of trusting relationships connected by guild membership, family, and place. We uncover a profound increase in the role of kinship – a re-embedding of trust within the family – and a decline of the importance of shared guild membership in connecting Londoners who secured orphans’ inheritances together. These developments indicate a profound transformation in the social fabric of urban society.

OBJECTIVES/GOALS: Clinical indicators predictive of venous thromboembolism (VTE) in trauma patients at multiple time points are not well outlined, particularly at time of discharge. We aimed to describe and predict inpatient and post-discharge risk factors of VTE after trauma using a multi-variate regression model and best of class machine learning (ML) models. METHODS/STUDY POPULATION: In a prospective, case-cohort study, all trauma patients (pts) who arrived as level 1 or 2 trauma activations, from June 2018 to February 2020 were considered for study inclusion. A subset of pts who developed incident, first time, VTE and those who did not develop VTE within 90 days of discharge were identified. VTE were confirmed either by imaging or at autopsy during inpatient stay or post-discharge. Outcomes were defined as the development of symptomatic VTE (DVT and/or PE) within 90 days of discharge.A multi-variate Cox regression model and a best in class of a set of 5 different ML models (support-vector machine, random-forest, naives Bayes, logistic regression, neural network]) were used to predict VTE using models applied a) at 24 hours of injury date or b) on day of patient discharge. RESULTS/ANTICIPATED RESULTS: Among 393 trauma pts (ISS=12.0, hospital LOS=4.0 days, age=48 years, 71% male, 96% with blunt mechanism, mortality 2.8%), 36 developed inpatient VTE and 36 developed VTE after discharge. In a weighted, multivariate Cox model, any type of surgery by day 1, increased age per 10 years, and BMI per 5 points were predictors of overall symptomatic VTE (C-stat 0.738). Prophylactic IVC filter placement (4.40), increased patient age per 10 years, and BMI per 5 points were predictors of post-discharge symptomatic VTE (C-stat= 0.698). A neural network ML model predicted VTE by day 1 with accuracy and AUC of 0.82 and 0.76, with performance exceeding those of a Cox model. A naīve Bayesian ML model predicted VTE at discharge, with accuracy and AUC of 0.81 and 0.77 at time of discharge, with performance exceeding those of a Cox model. DISCUSSION/SIGNIFICANCE: The rate of inpatient and post-discharge VTEs remain high. Limitations: single institution study, limited number of patients, internal validation only, with the use of limited number of ML models. We developed and internally validated a ML based tool.Future work will focus on external validation and expansion of ML techniques.

Over the last 20 years, finite element analysis (FEA) has become a standard analysis tool for metal joining processes. When FEA tools are combined with design of experiments (DOE) methodologies, academic research has shown the potential for virtual DOE to allow for the rapid analysis of manufacturing parameters and their influence on final formed products. However, within the domain of bulk-metal joining, FEA tools are rarely used in industrial applications and limit DOE trails to physical testing which are therefore constrained by financial costs and time.

This research explores the suitability of an FEA-based DOE to predict the complex behaviour during bulk-metal joining processes through a case study on the staking of spherical bearings. For the two DOE outputs of pushout strength and post-stake torque, the FEA-based DOE error did not exceed ±1.2% and ± 1.5 Nm respectively which far surpasses what was previously capable from analytically derived closed-form solutions. The outcomes of this case study demonstration the potential for FEA-based DOE to provide an inexpensive, methodical, and scalable solution for modelling bulk-metal joining process

The purpose of this investigation was to expand upon the limited existing research examining the test–retest reliability, cross-sectional validity and longitudinal validity of a sample of bioelectrical impedance analysis (BIA) devices as compared with a laboratory four-compartment (4C) model. Seventy-three healthy participants aged 19–50 years were assessed by each of fifteen BIA devices, with resulting body fat percentage estimates compared with a 4C model utilising air displacement plethysmography, dual-energy X-ray absorptiometry and bioimpedance spectroscopy. A subset of thirty-seven participants returned for a second visit 12–16 weeks later and were included in an analysis of longitudinal validity. The sample of devices included fourteen consumer-grade and one research-grade model in a variety of configurations: hand-to-hand, foot-to-foot and bilateral hand-to-foot (octapolar). BIA devices demonstrated high reliability, with precision error ranging from 0·0 to 0·49 %. Cross-sectional validity varied, with constant error relative to the 4C model ranging from −3·5 (sd 4·1) % to 11·7 (sd 4·7) %, standard error of the estimate values of 3·1–7·5 % and Lin’s concordance correlation coefficients (CCC) of 0·48–0·94. For longitudinal validity, constant error ranged from −0·4 (sd 2·1) % to 1·3 (sd 2·7) %, with standard error of the estimate values of 1·7–2·6 % and Lin’s CCC of 0·37–0·78. While performance varied widely across the sample investigated, select models of BIA devices (particularly octapolar and select foot-to-foot devices) may hold potential utility for the tracking of body composition over time, particularly in contexts in which the purchase or use of a research-grade device is infeasible.

Schmid and Mullins present what they call ‘the Aloneness Argument’ for the inconsistency of four theses from classical theism: the doctrine of divine simplicity, the doctrine of divine omniscience, the claim that God is free to create or not to create, and the claim that it is possible that God and nothing but God exist. We deny that they have shown an inconsistency between these theses. We maintain that, depending on how certain premises are interpreted, one or another premise is false. We also offer a positive proposal regarding a simple God's knowledge that he is alone in a world where he doesn't create anything.

The present study reports the validity of multiple assessment methods for tracking changes in body composition over time and quantifies the influence of unstandardised pre-assessment procedures. Resistance-trained males underwent 6 weeks of structured resistance training alongside a hyperenergetic diet, with four total body composition evaluations. Pre-intervention, body composition was estimated in standardised (i.e. overnight fasted and rested) and unstandardised (i.e. no control over pre-assessment activities) conditions within a single day. The same assessments were repeated post-intervention, and body composition changes were estimated from all possible combinations of pre-intervention and post-intervention data. Assessment methods included dual-energy X-ray absorptiometry (DXA), air displacement plethysmography, three-dimensional optical imaging, single- and multi-frequency bioelectrical impedance analysis, bioimpedance spectroscopy and multi-component models. Data were analysed using equivalence testing, Bland–Altman analysis, Friedman tests and validity metrics. Most methods demonstrated meaningful errors when unstandardised conditions were present pre- and/or post-intervention, resulting in blunted or exaggerated changes relative to true body composition changes. However, some methods – particularly DXA and select digital anthropometry techniques – were more robust to a lack of standardisation. In standardised conditions, methods exhibiting the highest overall agreement with the four-component model were other multi-component models, select bioimpedance technologies, DXA and select digital anthropometry techniques. Although specific methods varied, the present study broadly demonstrates the importance of controlling and documenting standardisation procedures prior to body composition assessments across distinct assessment technologies, particularly for longitudinal investigations. Additionally, there are meaningful differences in the ability of common methods to track longitudinal body composition changes.