A model for characterizing the spectral response of the passband of Wavelength Selective Switches (WSS) is presented. We demonstrate that, in contrast to the commonly used supergaussian model, the presented model offers a more complete match to measured results, as it is based on the physical operation of the optical system. We also demonstrate that this model is better suited for calculation of WSS channel bandwidths, as well as predicting the final bandwidth of cascaded WSS modules. Finally, we show the utility of this model in predicting channel shapes in flexible bandwidth WSS channel plans.
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http://dx.doi.org/10.1364/OE.19.008458 | DOI Listing |
Plant Cell Environ
January 2025
Remote Sensing Laboratory, Institute of Environment and Sustainable Development, Banaras Hindu University, Varanasi, India.
The generation of spectral libraries using hyperspectral data allows for the capture of detailed spectral signatures, uncovering subtle variations in plant physiology, biochemistry, and growth stages, marking a significant advancement over traditional land cover classification methods. These spectral libraries enable improved forest classification accuracy and more precise differentiation of plant species and plant functional types (PFTs), thereby establishing hyperspectral sensing as a critical tool for PFT classification. This study aims to advance the classification and monitoring of PFTs in Shoolpaneshwar wildlife sanctuary, Gujarat, India using Airborne Visible/Infrared Imaging Spectrometer-Next Generation (AVIRIS-NG) and machine learning techniques.
View Article and Find Full Text PDFSci Rep
January 2025
Research Unit of Health Sciences and Technology, University of Oulu, Oulu, Finland.
Optical techniques, such as functional near-infrared spectroscopy (fNIRS), contain high potential for the development of non-invasive wearable systems for evaluating cerebral vascular condition in aging, due to their portability and ability to monitor real-time changes in cerebral hemodynamics. In this study, thirty-six healthy adults were measured by single channel fNIRS to explore differences between two age groups using machine learning (ML). The subjects, measured during functional magnetic resonance imaging (fMRI) at Oulu University Hospital, were divided into young (age ≤ 32) and elderly (age ≥ 57) groups.
View Article and Find Full Text PDFJ Chromatogr B Analyt Technol Biomed Life Sci
January 2025
Université Clermont Auvergne, Institut Universitaire de Technologie, UMR INSERM-UCA, U1240, Imagerie Moléculaire et Stratégies Théranostiques (IMoST), 5 Avenue Blaise Pascal, 63000 Clermont-Ferrand, France.
A method using high-performance liquid chromatography coupled with fluorescence detection (HPLC-FLD) was developed and validated to quantify the innovative tool LightSpot®-FL-1, a selective permeability-glycoprotein (P-gp)-targeted fluorescent conjugate used to measure P-gp expression in cell samples. Quantifying P-gp is a major challenge in oncology as its overexpression in many cancer cells results in Multidrug Resistance (MDR) associated with chemotherapy failure. To develop the method reported herein, both sample preparation and analysis parameters were investigated.
View Article and Find Full Text PDFACS Nano
January 2025
State Key Laboratory of Polymer Materials Engineering, Polymer Research Institute of Sichuan University, Chengdu 610065, China.
Daytime radiative cooling (DRC) materials offer a sustainable, pollution-free passive cooling solution. Traditional DRC materials are usually white to maximize solar reflectance, but applications like textiles and buildings need more aesthetic options. Unfortunately, colorizing DRC materials often reduce cooling efficiency due to colorant sunlight absorption.
View Article and Find Full Text PDFSensors (Basel)
January 2025
United States Department of Agriculture-Agriculture Research Service, Grassland Soil and Water Research Laboratory, Temple, TX 76502, USA.
Efficient and reliable corn ( L.) yield prediction is important for varietal selection by plant breeders and management decision-making by growers. Unlike prior studies that focus mainly on county-level or controlled laboratory-scale areas, this study targets a production-scale area, better representing real-world agricultural conditions and offering more practical relevance for farmers.
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