In order to investigate the performance of two different algorithms for retrieving temperature from Rayleigh-Brillouin (RB) line shapes, RB scattering measurements have been performed in air at a wavelength of 403 nm, for a temperature range from 257 K to 330 K, and atmospherically relevant pressures from 871 hPa to 1013 hPa. One algorithm, based on the Tenti S6 line shape model, shows very good accordance with the reference temperature. In particular, the absolute difference is always less than 2 K. A linear correlation yields a slope of 1.01 ± 0.02 and thus clearly demonstrates the reliability of the retrieval procedure. The second algorithm, based on an analytical line shape model, shows larger discrepancies of up to 9.9 K and is thus not useful at its present stage. The possible reasons for these discrepancies and improvements of the analytical model are discussed. The obtained outcomes are additionally verified with previously performed RB measurements in air, at 366 nm, temperatures from 255 K to 338 K and pressures from 643 hPa to 826 hPa [Appl. Opt. 52, 4640 (2013)]. The presented results are of relevance for future lidar studies that might utilize RB scattering for retrieving atmospheric temperature profiles with high accuracy.
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http://dx.doi.org/10.1364/OE.22.029655 | DOI Listing |
Cureus
December 2024
Emergency, Hospital de Braga, Braga, PRT.
Pericardial effusion refers to the accumulation of fluid within the pericardial sac, the double-layered membrane surrounding the heart. It can be caused by various medical conditions and may lead to serious complications if not diagnosed and managed promptly. Point-of-care ultrasound (POCUS) has emerged as a valuable tool in the clinical evaluation of pericardial effusions, offering real-time visualization and aiding in the assessment of its size, characteristics, and potential hemodynamic impact.
View Article and Find Full Text PDFFront Plant Sci
January 2025
Institute of Crop Science, Huzhou Academy of Agriculture Sciences, Huzhou, China.
With the rapid advancement of plant phenotyping research, understanding plant genetic information and growth trends has become crucial. Measuring seedling length is a key criterion for assessing seed viability, but traditional ruler-based methods are time-consuming and labor-intensive. To address these limitations, we propose an efficient deep learning approach to enhance plant seedling phenotyping analysis.
View Article and Find Full Text PDFElectronics (Basel)
December 2024
Department of Mechanical Engineering, City College of New York, New York, NY 10031, USA.
Cardiovascular disease is a leading cause of death worldwide. The differentiation of human pluripotent stem cells (hPSCs) into functional cardiomyocytes offers significant potential for disease modeling and cell-based cardiac therapies. However, hPSC-derived cardiomyocytes (hPSC-CMs) remain largely immature, limiting their experimental and clinical applications.
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November 2024
Viterbi Family Department of Ophthalmology, Shiley Eye Institute, University of California, San Diego, La Jolla, California.
Objective: To quantitatively assess the retinal vascular tortuosity of patients with sickle cell disease (SCD) and retinopathy (SCR) using an automated deep learning (DL)-based pipeline.
Design: Cross-sectional study.
Subjects: Patients diagnosed with SCD and screened for SCR at an academic eye center between January 2015 and November 2022 were identified using electronic health records.
Arch Bone Jt Surg
January 2025
Orthopedic Research Center, Department of Orthopedic Surgery, Mashhad University of Medical Sciences, Mashhad, Iran.
Artificial Intelligence (AI) is rapidly transforming healthcare, particularly in orthopedics, by enhancing diagnostic accuracy, surgical planning, and personalized treatment. This review explores current applications of AI in orthopedics, focusing on its contributions to diagnostics and surgical procedures. Key methodologies such as artificial neural networks (ANNs), convolutional neural networks (CNNs), support vector machines (SVMs), and ensemble learning have significantly improved diagnostic precision and patient care.
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