This work presents an optical fiber dynamic light scattering sensor capable of simultaneously assessing concentration and flow speed of nanofluids. Silica nanoparticles (189 nm) in water were tested, yielding a sensitivity of 0.78288 × 10³ s for static conditions. Then, the sensor was submitted to situations that simulate spatial concentration changes, offering better results than those obtained by traditional mathematical models. Finally, in flow tests, the light backscattered by the nanoparticles were collected by a fiber probe placed parallel to the streamline, whereas intensity values were processed by artificial neural networks. The sensor provides average errors of 0.09 wt% and 0.26 cm/s for concentration and speed measurements, respectively, and can be further applied to assess different types of nanofluids and inline processes.
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http://dx.doi.org/10.3390/s20030707 | DOI Listing |
Anal Chem
January 2025
Hunan Provincial Key Laboratory of Micro & Nano Materials Interface Science, College of Chemistry and Chemical Engineering, Central South University, Changsha 410083, China.
Microelectrodes offer exceptional sensitivity, rapid response, and versatility, making them ideal for real-time detection and monitoring applications. Photoelectrochemical (PEC) sensors have shown great value in many fields due to their high sensitivity, fast response, and ease of operation. Nevertheless, conventional PEC sensing relies on cumbersome external light sources and bulky electrodes, hindering its miniaturization and implantation, thereby limiting its application in real-time disease monitoring.
View Article and Find Full Text PDFJ Biomed Opt
January 2025
The Johns Hopkins University, Department of Biomedical Engineering, Baltimore, Maryland, United States.
Significance: Laparoscopic surgery presents challenges in localizing oncological margins due to poor contrast between healthy and malignant tissues. Optical properties can uniquely identify various tissue types and disease states with high sensitivity and specificity, making it a promising tool for surgical guidance. Although spatial frequency domain imaging (SFDI) effectively measures quantitative optical properties, its deployment in laparoscopy is challenging due to the constrained imaging environment.
View Article and Find Full Text PDFUnlabelled: Accurate localization of white matter pathways using diffusion MRI is critical to investigating brain connectivity, but the accuracy of current methods is not thoroughly understood. A fruitful approach to validating accuracy is to consider microscopy data that have been co-registered with MRI of post mortem samples. In this setting, structure tensor analysis is a standard approach to computing local orientations for validation.
View Article and Find Full Text PDFClin Ophthalmol
January 2025
Department of Ophthalmology, Manhattan Eye, Ear, and Throat Hospital/Northwell Health, New York, NY, USA.
Purpose: To assess the diagnostic capability of pattern electroretinography (PERG) and varying circumpapillary optical coherence tomography (OCT) scan diameters in glaucoma suspects (GS).
Methods: This is a prospective, cross-sectional study. Circumpapillary retinal nerve fiber layer thickness (RNFLT) was measured using spectral domain OCT in 49 eyes from 26 patients (36 normal, 13 GS) in three circle diameters (3.
Cureus
December 2024
Cornea and Refractive Surgery, Al-Shifa Trust Eye Hospital, Rawalpindi, PAK.
Background: Glaucoma, particularly open-angle glaucoma (OAG), is a leading cause of irreversible blindness, associated with optic nerve damage, retinal ganglion cell death, and visual field defects. Corneal biomechanical properties and cellular components, such as corneal nerve and keratocyte densities assessed by in vivo confocal microscopy (IVCM), may serve as biomarkers for glaucoma progression. This study aimed to explore the relationship between corneal nerve parameters, keratocyte density, and optical coherence tomography (OCT)-derived retinal nerve fiber layer (RNFL) thickness in primary open-angle glaucoma (POAG) patients and controls.
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