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http://dx.doi.org/10.1080/02701367.1989.10607467 | DOI Listing |
Sci Rep
January 2025
Department of Geomorphology and Quaternary Geology, Faculty of Oceanography and Geography, University of Gdańsk, Bażyńskiego 4, 80-952, Gdańsk, Poland.
This study introduces a novel methodology for estimating and analysing coastal cliff degradation, using machine learning and remote sensing data. Degradation refers to both natural abrasive processes and damage to coastal reinforcement structures caused by natural events. We utilized orthophotos and LiDAR data in green and near-infrared wavelengths to identify zones impacted by storms and extreme weather events that initiated mass movement processes.
View Article and Find Full Text PDFNat Commun
January 2025
State Key Laboratory of Chemical Resource Engineering, College of Chemistry, Beijing University of Chemical Technology, Beijing, China.
Introduction: Cerebral oximetry measurement using near-infrared spectroscopy (NIRS) has been highlighted as a technology that can provide noninvasive information on regional cerebral oxygen saturation (rSO2) during CPR even though its effectiveness has not been fully confirmed. The research focuses on the use of NIRS to predict the return of spontaneous circulation (ROSC) and neurological outcomes.
Objectives: The purpose of the study is to evaluate the validity of using regional cerebral oxygen saturation (rSO2) measurement compared to ETCO2 during CPR to and its association with ROSC, as well as to evaluate the neuroprognostic value of NIRS.
Sci Rep
December 2024
Department of Computer Engineering, Marwadi University, Rajkot, 360003, India.
The contributed absorber design in graphene addition with the displacement of three materials for resonator design in Aluminum (Al), the middle substrate position with Titanium nitride (TiN), and the ground layer deposition by Iron (Fe) respectively. For the absorption validation highlight, the best four absorption wavelengths (µm) of 0.29, 0.
View Article and Find Full Text PDFSpectrochim Acta A Mol Biomol Spectrosc
December 2024
Centre for Nutrition and Food Sciences (CNAFS), Queensland Alliance for Agriculture and Food Innovation (QAAFI), Brisbane, Queensland 4072, Australia. Electronic address:
The black soldier fly larvae (BSFL) are well known to utilise a wide variety of organic waste streams, delivering a product rich in protein (30-50%) and lipids (15-49%) and other micronutrients. The objective of this study was to evaluate the ability of NIR spectroscopy combined with chemometrics to predict the concentration of fatty acids in BSFL reared in different commercial waste streams. Intact BSFL samples were analysed using a bench top NIR instrument where calibration models for fatty acids were developed using partial least squares (PLS) regression.
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