Finite element (FE) analysis is a cornerstone of orthopaedic biomechanics research. Three-dimensional medical imaging provides sufficient resolution for the subject-specific FE models to be generated from these data-sets. FE model development requires discretisation of a three-dimensional domain, which can be the most time-consuming component of a FE study. Hexahedral meshing tools based on the multiblock method currently rely on the manual placement of building blocks for mesh generation. We hypothesise that angular analysis of the geometric centreline for a three-dimensional surface could be used to automatically generate building block structures for the multiblock hexahedral mesh generation. Our algorithm uses a set of user-defined points and parameters to automatically generate a multiblock structure based on a surface's geometric centreline. This significantly reduces the time required for model development. We have applied this algorithm to 47 bones of varying geometries and successfully generated a FE mesh in all cases. This work represents significant advancement in automatically generating multiblock structures for a wide range of geometries.
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http://dx.doi.org/10.1080/10255842.2011.570338 | DOI Listing |
Molecules
December 2024
Laboratory of Chemistry and Technology of Polymers and Colors, Department of Chemistry, Aristotle University of Thessaloniki, GR-54124 Thessaloniki, Greece.
This study presents the synthesis and characterization of a series of multiblock copolymers, poly(ethylene 2,5-furandicarboxylate)-poly(ε-caprolactone) (PEF-PCL), created through a combination of the two-step melt polycondensation method and ring opening polymerization, as sustainable alternatives to fossil-based plastics. The structural confirmation of these block copolymers was achieved through Attenuated Total Reflectance Fourier Transform Infrared Spectroscopy (ATR-FTIR), ensuring the successful integration of PEF and PCL segments. X-ray Photoelectron Spectroscopy (XPS) was employed for chemical bonding and quantitative analysis, providing insights into the distribution and compatibility of the copolymer components.
View Article and Find Full Text PDFACS Nano
January 2025
Department of Chemistry, University of Minnesota, Minneapolis, Minnesota 55455, United States.
Hum Brain Mapp
December 2024
Institute of Systems Neuroscience, Heinrich Heine University Düsseldorf, Düsseldorf, Germany.
The human hippocampus is a key region in cognitive and emotional processing, but also a vulnerable and plastic region. Accordingly, there is a great interest in understanding how variability in the hippocampus' structure relates to variability in behavior in healthy and clinical populations. In this study, we aimed to link interindividual variability in subregional hippocampal networks (i.
View Article and Find Full Text PDFJ Am Chem Soc
January 2025
Polymer Synthesis Laboratory, Laboratory, Chemistry Program, KAUST Catalysis Center, Physical Sciences and Engineering Division, King Abdullah University of Science and Technology (KAUST), Thuwal 23955, Saudi Arabia.
Front Genet
November 2024
Department of Biostatistics, University of Florida, Gainesville, FL, United States.
Introduction: With the advancement of high-throughput studies, an increasing wealth of high-dimensional multi-omics data is being collected from the same patient cohort. However, leveraging this multi-omics data to predict survival outcomes poses a significant challenge due to its complex structure.
Methods: In this article, we present a novel approach, the Adaptive Sparse Multi-Block Partial Least Squares (asmbPLS) Regression model, which introduces a dynamic assignment of penalty factors to distinct blocks within various PLS components, facilitating effective feature selection and prediction.
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