Purpose: Recently, some numerical and experimental studies of blood flow in large arteries have attempted to accurately replicate in vivo arterial geometries, while others have utilized simplified models. The objective of this study was to determine how much an anatomically realistic geometry can be simplified without the loss of significant hemodynamic information.
Method: A human femoral-popliteal bypass graft was used to reconstruct an anatomically faithful finite element model of an end-to-side anastomosis. Nonideal geometric features of the model were removed in sequential steps to produce a series of successively simplified models. Blood flow patterns were numerically computed for each geometry, and the flow and wall shear stress fields were analyzed to determine the significance of each level of geometric simplification.
Results: The removal of small local surface features and out-of-plane curvature did not significantly change the flow and wall shear stress distributions in the end-to-side anastomosis. Local changes in arterial caliber played a more significant role, depending upon the location and extent of the change. The graft-to-host artery diameter ratio was found to be a strong determinant of wall shear stress patterns in regions that are typically associated with disease processes.
Conclusions: For the specific case of an end-to-side anastomosis, simplified models provide sufficient information for comparing hemodynamics with qualitative or averaged disease locations, provided the "primary" geometric features are well replicated. The ratio of the graft-to-host artery diameter was shown to be the most important geometric feature. "Secondary" geometric features such as local arterial caliber changes, out-of-plane curvature, and small-scale surface topology are less important determinants of the wall shear stress patterns. However, if patient-specific disease information is available for the same arterial geometry, accurate replication of both primary and secondary geometric features is likely required.
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http://dx.doi.org/10.1115/1.2798319 | DOI Listing |
J Physiol
January 2025
Department of Neuroscience, University of Copenhagen, Copenhagen, Denmark.
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View Article and Find Full Text PDFInorg Chem
January 2025
Department of Applied Chemistry, National Chiayi University, Chiayi 60004, Taiwan.
The chemical reactivity between benzene and the "naked" acyclic carbene-like (G13X) species, having two bulky N-heterocyclic boryloxy ligands at the Group 13 center, was theoretically assessed using density functional theory computations. Our theoretical studies show that (BX) preferentially undergoes C-H bond insertion with benzene, both kinetically and thermodynamically, whereas the (AlX) analogue favors a reversible [4 + 1] cycloaddition. Conversely, the heavier carbene analogues ((GaX), (InX), and (TlX)) are not expected to engage in a reaction with benzene.
View Article and Find Full Text PDFNanoscale Adv
January 2025
School of Electrical Engineering and Computer Science, University of Ottawa Ottawa Ontario K1N 6N5 Canada
Interference of surface plasmons has been widely utilized in optical metrology for applications such as high-precision sensing. In this paper, we introduce a surface plasmon interferometer with the potential to be arranged in arrays for parallel multiplexing applications. The interferometer features two grating couplers that excite surface plasmon polariton (SPP) waves traveling along a gold-air interface before converging at a gold nanoslit where they interfere.
View Article and Find Full Text PDFIdentifying informative low-dimensional features that characterize dynamics in molecular simulations remains a challenge, often requiring extensive manual tuning and system-specific knowledge. Here, we introduce geom2vec, in which pretrained graph neural networks (GNNs) are used as universal geometric featurizers. By pretraining equivariant GNNs on a large dataset of molecular conformations with a self-supervised denoising objective, we obtain transferable structural representations that are useful for learning conformational dynamics without further fine-tuning.
View Article and Find Full Text PDFSensors (Basel)
December 2024
Intelligent Manufacturing Laboratory, Production Engineering Institute, Faculty of Mechanical Engineering, University of Maribor, Smetanova ulica 17, 2000 Maribor, Slovenia.
Direct verification of the geometric accuracy of machined parts cannot be performed simultaneously with active machining operations, as it usually requires subsequent inspection with measuring devices such as coordinate measuring machines (CMMs) or optical 3D scanners. This sequential approach increases production time and costs. In this study, we propose a novel indirect measurement method that utilizes motor current data from the controller of a Computer Numerical Control (CNC) machine in combination with machine learning algorithms to predict the geometric accuracy of machined parts in real-time.
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