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Image processing is of fundamental importance for numerous modern technologies. In recent years, due to increasing demand for real-time and continuous data processing, metamaterial and metasurface based all-optical computation techniques emerged as a promising alternative to digital computation. Most of the pioneer research focused on all-optical edge detection as a fundamental step of image processing. Metasurfaces have been shown to enable real time edge detection with low to no power consumption. However, the previous demonstrations were subjected to the several limitations such as need for oblique-incidence, polarization dependence, need for additional polarizers, narrow operation bandwidth, being limited with processing in 1D, operation with coherent light only, and requiring digital post-processing. Here, we propose and experimentally demonstrate 2D isotropic, polarization-independent, broadband edge detection with high transmission efficiency under both coherent and incoherent illumination along the visible frequency range using a metasurface based on Fourier optics principles.
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http://dx.doi.org/10.1038/s41467-023-42271-w | DOI Listing |
Prog Mol Biol Transl Sci
September 2025
Division of Sleep Medicine, Louis Stokes Cleveland VA Medical Center, Cleveland, OH, United States; Division of Pulmonary, Critical Care, and Sleep Medicine, University Hospitals Cleveland Medical Center, Cleveland, OH, United States; Department of Medicine, Case Western Reserve University, Clevelan
Obstructive sleep apnea (OSA) is a pervasive disorder characterized by recurrent airway obstructions during sleep. OSA carries serious health risks, such as cardiovascular and cognitive impairments, and imposes a significant economic burden. This chapter provides a comprehensive overview of various biosensors currently employed for OSA detection, including in-lab polysomnography and flow-based home sleep apnea testing.
View Article and Find Full Text PDFCancer Res
September 2025
Morgridge Institute for Research, Madison, Wisconsin, United States.
Patient-derived cancer organoids (PDCOs) are a valuable model to recapitulate human disease in culture with important implications for drug development. However, current methods for rapidly and reproducibly assessing PDCOs are limited. Label-free imaging methods are a promising tool to measure organoid level heterogeneity and rapidly screen drug response in PDCOs.
View Article and Find Full Text PDFACS Chem Neurosci
September 2025
Chemical and Biomolecular Engineering Dept, University of California, Los Angeles, Los Angeles, California 90095, United States.
Simulations in three dimensions and time provide guidance on implantable, electroenzymatic glutamate sensor design; relative placement in planar sensor arrays; feasibility of sensing synaptic release events; and interpretation of sensor data. Electroenzymatic sensors based on the immobilization of oxidases on microelectrodes have proven valuable for the monitoring of neurotransmitter signaling in deep brain structures; however, the complex extracellular milieu featuring slow diffusive mass transport makes rational sensor design and data interpretation challenging. Simulations show that miniaturization of the disk-shaped device size below a radius of ∼25 μm improves sensitivity, spatial resolution, and the accuracy of glutamate concentration measurements based on calibration factors determined .
View Article and Find Full Text PDFRep Pract Oncol Radiother
August 2025
University Teaching Department, Chhattisgarh Swami Vivekanand Technical University, Bhilai, India.
Cervical cancer continues to pose a significant global health challenge, highlighting the urgent need for accurate and efficient diagnostic techniques. Recent progress in deep learning has demonstrated considerable potential in improving the detection and classification of cervical cancer. This review presents a thorough analysis of deep learning methods utilized for cervical cancer diagnosis, with an emphasis on critical approaches, evaluation metrics, and the ongoing challenges faced in the field.
View Article and Find Full Text PDFFront Plant Sci
August 2025
College of Engineering, Qinghai Institute of Technology, Xining, China.
The plateau pika () is a keystone species on the Qinghai-Tibet Plateau, and its population density-typically inferred from burrow counts-requires rapid, low-cost monitoring. We propose YOLO-Pika, a lightweight detector built on YOLOv8n that integrates (1) a Fusion_Block into the backbone, leveraging high-dimensional mapping and fine-grained gating to enhance feature representation with negligible computational overhead, and (2) an MS_Fusion_FPN composed of multiple MSEI modules for multi-scale frequency-domain fusion and edge enhancement. On a plateau pika burrow dataset, YOLO-Pika increases mAP50 by 3.
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