Background: Proximal femoral fractures are an important clinical and public health issue associated with substantial morbidity and early mortality. Artificial intelligence might offer improved diagnostic accuracy for these fractures, but typical approaches to testing of artificial intelligence models can underestimate the risks of artificial intelligence-based diagnostic systems.
Methods: We present a preclinical evaluation of a deep learning model intended to detect proximal femoral fractures in frontal x-ray films in emergency department patients, trained on films from the Royal Adelaide Hospital (Adelaide, SA, Australia).
We examine the impact of COVID-19 on the federal budget outlook. We find substantial but temporary effects on spending and revenues, with more moderate but permanent effects on the long-term projections. We project that the debt-to-GDP ratio, currently 98%, will rise to 190% in 2050 under current law, compared to a CBO pre-COVID projection of 180%.
View Article and Find Full Text PDFDrought frequently occurs during wheat (Triticum aestivum L.) grain filling. The objectives of this study were (i) to investigate the effect of post-anthesis drought on programmed cell death (PCD) in wheat endosperm cells and (ii) to examine the role of ethylene (ETH) receptors and abscisic acid (ABA) in regulating wheat endosperm PCD.
View Article and Find Full Text PDFTransp Porous Media
December 2017
Hysteresis in the saturation versus capillary pressure curves of neutrally wettable fibrous media was simulated with a random pore network model using a Voronoi diagram approach. The network was calibrated to fit experimental air-water capillary pressure data collected for carbon fibre paper commonly used as a gas diffusion layer in fuel cells. These materials exhibit unusually strong capillary hysteresis, to the extent that water injection and withdrawal occur at positive and negative capillary pressures, respectively.
View Article and Find Full Text PDF