We demonstrate the interest of combining finite element calculations with the vector partial wave formulation (used in T-matrix and Mie theory) in order to characterize the electromagnetic scattering properties of isolated individual scatterers. This method consists of individually feeding the finite element problem with incident vector partial waves in order to numerically determine the T-matrix elements of the scatterer. For a sphere and a spheroid, we demonstrate that this method determines the scattering matrix to high accuracy. Recurrence relations for a fast determination of the vector partial waves are given explicitly, and an open-source code allowing the retrieval of the presented numerical results is provided.
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http://dx.doi.org/10.1364/JOSAA.35.001401 | DOI Listing |
Molecules
January 2025
Neuroscience and Signalling Group, Institute of Biomedicine (iBiMED), Department of Medical Sciences, University of Aveiro, 3810-193 Aveiro, Portugal.
Alzheimer's disease is a challenge in modern healthcare due to its complex etiology and increasing prevalence. Despite advances, further understanding of Alzheimer's disease pathophysiology is needed, particularly the role of Aβ neurotoxic peptide. Fourier transform infrared spectroscopy (FTIR) has shown potential as a screening tool for several pathologies, including Alzheimer's disease.
View Article and Find Full Text PDFMicromachines (Basel)
January 2025
Research Center for Novel Computing Sensing and Intelligent Processing, Zhejiang Lab, Hangzhou 311100, China.
General matrix multiplication (GEMM) in machine learning involves massive computation and data movement, which restricts its deployment on resource-constrained devices. Although data reuse can reduce data movement during GEMM processing, current approaches fail to fully exploit its potential. This work introduces a sparse GEMM accelerator with a weight-and-output stationary (WOS) dataflow and a distributed buffer architecture.
View Article and Find Full Text PDFFoods
January 2025
College of Biosystems Engineering and Food Science, Key Laboratory of Agro-Products Postharvest Handling of Ministry of Agriculture and Rural Affairs, Zhejiang University, Hangzhou 310058, China.
Volatile organic compounds (VOCs) are closely associated with the maturity and variety of strawberries. However, the complexity of VOCs hinders their potential application in strawberry classification. This study developed a novel classification workflow using strawberry VOC profiles and machine learning (ML) models for precise fruit classification.
View Article and Find Full Text PDFFood Res Int
February 2025
State Key Laboratory of Food Science and Resources, Jiangnan University, Wuxi, Jiangsu Province, China; School of Food Science and Technology, Jiangnan University University, Wuxi, Jiangsu Province, China; Collaborative Innovation Center of Food Safety and Quality Control in Jiangsu Province, Jiangnan University, China. Electronic address:
The aim of this study was to explore application of visible and near-infrared (Vis/NIR) spectroscopy combined with machine learning models for SSC and TA prediction of hybrid citrus. The Vis/NIR spectra of samples including navel-region, equator-region and multi-region combination spectra in navel-region and equator-region were collected using a benchtop equipment. The performance of SSC and TA prediction models with different region spectra, including partial least squares (PLS), random forest (RF), k-nearest neighbors (KNN), support vector machine (SVM) and multilayer feedforward neural network (MFNN), was assessed.
View Article and Find Full Text PDFHear Res
December 2024
Bionics Institute, East Melbourne, Victoria 3002, Australia; Department of Medical Bionics, The University of Melbourne, Fitzroy, Victoria 3065, Australia; Department of Surgery (Otolaryngology), University of Melbourne, The Royal Victorian Eye and Ear Hospital, East Melbourne, Victoria 3002, Australia. Electronic address:
In the adult mammalian cochlea, hair cell loss is irreversible and causes deafness. The basic helix-loop transcription factor Atoh1 is essential for normal hair cell development in the embryonic ear. Over-expression of Atoh1 in the adult cochlea by gene therapy can convert supporting cells (cells that underlie hair cells) into a hair cell lineage.
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