Inspired by the demodulation algorithm of Fabry-Perot composite sensors in the field of fiber-optic sensing, this paper proposes a method based on a widely tunable modulated grating Y-branch (MG-Y) laser combined with the cross-correlation algorithm to achieve a highly precise measurement of the optical thickness of each layer of a multilayer optical sample. A sample consisting of a double glass stack was selected, and the interference spectrum of the stacked sample was acquired using a widely tunable MG-Y laser. A fast Fourier transform (FFT) algorithm combined with a finite impulse response (FIR) bandpass filter was utilized to separate the different frequency components of the multilayer optical sample. The normalized spectra of each layer were reconstructed using the Hilbert transform. Subsequently, a cross-correlation algorithm was employed to process the normalized spectrum and determine the optical thickness of each layer with high precision. The samples were measured at predetermined locations, with 150 consecutive measurements performed to assess the repetition of the thickness. The standard deviation of these measurements was found to be lower than 1.5 nm. The results show that the cross-correlation algorithm is advantageous in the optical thickness measurement of multilayer films.
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Parasit Vectors
January 2025
Shoklo Malaria Research Unit, Mahidol-Oxford Tropical Medicine Research Unit, Faculty of Tropical Medicine, Mahidol University, Mae Ramat, Thailand.
Background: Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) is proposed for mosquito species identification. The absence of public repositories sharing mass spectra and open-source data analysis pipelines for fingerprint matching to mosquito species limits the widespread use of this technology. The objective of this study was to develop a free open-source data analysis pipeline for Anopheles species identification with MALDI-TOF MS.
View Article and Find Full Text PDFComput Biol Med
January 2025
State Key Laboratory of Precision Measuring Technology and Instruments, Tianjin University, Tianjin, 300072, China. Electronic address:
Transmission imaging may become a possible advance for breast cancer screening with non-invasive, cost-effective, and radiation-free approaches for early detection. Frame accumulation can successfully eliminate the issue of low SNR, low grayscale and poor quality in transmission image. However, frame accumulation accuracy can be diminished because of inherent human body instability during image acquisition and the light absorption characteristics of breast tissue, resulting in distorted and misplaced image sequences.
View Article and Find Full Text PDFChaos
January 2025
Jožef Stefan Institute, Jamova cesta 39, SI-1000 Ljubljana, Slovenia.
Detecting directional couplings from time series is crucial in understanding complex dynamical systems. Various approaches based on reconstructed state-spaces have been developed for this purpose, including a cross-distance vector measure, which we introduced in our recent work. Here, we devise two new cross-vector measures that utilize ranks and time series estimates instead of distances.
View Article and Find Full Text PDFSensors (Basel)
December 2024
Department of Biomedical Engineering, University of Connecticut, Storrs, CT 06269, USA.
The field of emotion recognition from physiological signals is a growing area of research with significant implications for both mental health monitoring and human-computer interaction. This study introduces a novel approach to detecting emotional states based on fractal analysis of electrodermal activity (EDA) signals. We employed detrended fluctuation analysis (DFA), Hurst exponent estimation, and wavelet entropy calculation to extract fractal features from EDA signals obtained from the CASE dataset, which contains physiological recordings and continuous emotion annotations from 30 participants.
View Article and Find Full Text PDFInt J Comput Assist Radiol Surg
January 2025
Department of Medical Biophysics, University of Toronto, Toronto, Canada.
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