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In this paper, a chemo-mechanically coupled behavior of Nafion 212 is investigated through predictive multiphysics modeling and experimental validation. Fuel cell performance and durability are critically determined by the mechanical and chemical degradation of a perfluorosulfonic acid (PFSA) membrane. However, how the degree of chemical decomposition affects the material constitutive behavior has not been clearly defined. To estimate the degradation level quantitatively, fluoride release is measured. The PFSA membrane in tensile testing shows nonlinear behavior, which is modeled by plasticity-based material modeling. The material parameters, which contain hardening parameters and Young's modulus, are characterized in terms of fluoride release levels by inverse analysis. In the sequel, membrane modeling is performed to investigate the life prediction due to humidity cycling. A continuum-based pinhole growth model is adopted in response to mechanical stress. As a result, validation is conducted in comparison with the accelerated stress test (AST) by correlating the size of the pinhole with the gas crossover generated in the membrane. This work provides a dataset of degraded membranes for performance and suggests the quantitative understanding and prediction of fuel cell durability with computational simulation.
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http://dx.doi.org/10.1021/acsami.2c15451 | DOI Listing |
Am J Emerg Med
September 2025
University of Toronto, Rotman School of Management, Canada.
Study Objective: Accurately predicting which Emergency Department (ED) patients are at high risk of leaving without being seen (LWBS) could enable targeted interventions aimed at reducing LWBS rates. Machine Learning (ML) models that dynamically update these risk predictions as patients experience more time waiting were developed and validated, in order to improve the prediction accuracy and correctly identify more patients who LWBS.
Methods: The study was deemed quality improvement by the institutional review board, and collected all patient visits to the ED of a large academic medical campus over 24 months.
PLoS One
September 2025
School of Computer Science and Technology, Huaiyin Normal University, Huai'an, Jiangsu, China.
Previous studies have demonstrated that metric learning approaches yield remarkable performance in the field of kinship verification. Nevertheless, a prevalent limitation of most existing methods lies in their over-reliance on learning exclusively from specified types of given kin data, which frequently results in information isolation. Although generative-based metric learning methods present potential solutions to this problem, they are hindered by substantial computational costs.
View Article and Find Full Text PDFPediatr Infect Dis J
September 2025
From the Paediatric Emergency Service and Infectious Diseases Unit, Hospital Pediátrico de Coimbra, Unidade Local de Saúde de Coimbra, Coimbra, Portugal.
Background And Objectives: Respiratory syncytial virus (RSV) is recognized as a major cause of wintertime illness in children. Two forms of immunization to protect infants against severe infection have recently been approved. Information on the effects of infections on health-related quality of life (HRQoL) supports well-informed policy decisions.
View Article and Find Full Text PDFEur J Trauma Emerg Surg
September 2025
French Military Medical Service Academy - École du Val-de-Grâce, Paris, France.
Background: Delivering intensive care in conflict zones and other resource-limited settings presents unique clinical, logistical, and ethical challenges. These contexts, characterized by disrupted infrastructure, limited personnel, and prolonged field care, require adapted strategies to ensure critical care delivery under resource-limited settings.
Objective: This scoping review aims to identify and characterize medical innovations developed or implemented in recent conflicts that may be relevant and transposable to intensive care units operating in other resource-limited settings.
Diabetologia
September 2025
Walther Straub Institute of Pharmacology and Toxicology, LMU Munich, Munich, Germany.
Aims/hypothesis: Unimolecular peptides targeting the receptors for glucagon-like peptide-1 (GLP-1), glucose-dependent insulinotropic polypeptide (GIP) and glucagon (GCG) have been shown to improve glycaemic management in both mice and humans. Yet the identity of the downstream signalling events mediated by these peptides remain to be elucidated. Here, we aimed to assess the mechanisms by which a validated peptide triagonist for GLP-1/GIP/GCG receptors (IUB447) stimulates insulin secretion in murine pancreatic islets.
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