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Barriers facing emergency physicians in providing urgent care to pediatric patients in Saudi Arabia - a cross-sectional study.
J Med Life
December 2024
King Fahad Armed Forces Hospital, Jeddah, Kingdom of Saudi Arabia.
Efforts to improve healthcare services have been ongoing, particularly in equipping emergency departments (EDs) to handle pediatric cases. However, many EDs continue to lack specialized equipment and adequately trained personnel, exposing children to significant health risks. This study aimed to identify self-reported barriers among emergency physicians in managing pediatric patients and assess their confidence levels in pediatric care.
View Article and Find Full Text PDFSpatiotemporal analysis of the effects of exercise on the hemodynamics of the aorta in hypertensive rats using fluid-structure interaction simulation.
J Transl Int Med
February 2024
Department of Cardiology and Institute of Vascular Medicine, Peking University Third Hospital; State Key Laboratory of Vascular Homeostasis and Remodeling, Peking University; NHC Key Laboratory of Cardiovascular Molecular Biology and Regulatory Peptides, Peking University; Beijing Key Laboratory of Cardiovascular Receptors Research, Beijing 100191, China.
Background And Objective: Hemodynamic changes that lead to increased blood pressure represent the main drivers of organ damage in hypertension. Prolonged increases to blood pressure can lead to vascular remodeling, which also affects vascular hemodynamics during the pathogenesis of hypertension. Exercise is beneficial for relieving hypertension, however the mechanistic link between exercise training and how it influences hemodynamics in the context of hypertension is not well understood.
View Article and Find Full Text PDFRate equations and numerical simulations relying on complex mathematical and physical principles are typically used to model directly modulated lasers (DMLs) but have difficulty simulating dynamic DML behavior in real-time under varying conditions due to their high complexity. Here, we introduce a data-driven deep learning method to model DMLs, aiming to achieve high accuracy with reduced computational complexity. This approach employs bidirectional long short-term memory (BiLSTM) enhanced by advanced feature recalibration and nonlinear fitting techniques.
View Article and Find Full Text PDFWe propose an alternative data-free deep learning method using a physics-informed neural network (PINN) to enable more efficient computation of light diffraction from 3D optical metasurfaces, modeling of corresponding polarization effects, and wavefront manipulation. Our model learns only from the governing physics represented by vector Maxwell's equations, Floquet-Bloch boundary conditions, and perfectly matched layers (PML). PINN accurately simulates near-field and far-field responses, and the impact of polarization, meta-atom geometry, and illumination settings on the transmitted light.
View Article and Find Full Text PDFPerovskites attract significant attention as a coating material in optical fiber sensing, but challenges remain due to the limited discovery of suitable materials and the high trial-and-error costs, resulting in only a few perovskites being used in optical sensing experiments. Addressing this issue, a novel systematic computational screening strategy for perovskites is established. This strategy is demonstrated to accelerate the discovery of perovskite coating materials that can enhance optical sensing sensitivity.
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