Three-Dimensional Scanning Virtual Aperture Imaging with Metasurface.

Metasurface-based imaging is attractive due to its low hardware costs and system complexity. However, most of the current metasurface-based imaging systems require stochastic wavefront modulation, complex computational post-processing, and are restricted to 2D imaging. To overcome these limitations, we propose a scanning virtual aperture imaging system.

Timing of Resistance Exercise and Cardiometabolic Outcomes in Adults with Prediabetes: A Secondary Analysis.

The objective of this study was to explore if the time of day (AM vs PM) resistance exercise is performed influences glucose and insulin concentrations, body composition, and muscular strength in adults with prediabetes. A secondary data analysis was conducted using data from the "Resist Diabetes" study, a phase II exercise intervention. Participants (Age:59.

Chlamydia psittaci pneumonia - evolutionary aspects on chest CT.

Purpose: To present the different findings of Chlamydia psittaci (C. psittaci) pneumonia on computed tomography (CT) according to the progression of the disease, to improve diagnostic accuracy, guide early clinical diagnosis, evaluate treatment efficacy, and reduce the mortality associated with the disease.

Methods: In total, 80 cases of C.

Inverse design of metalenses with polarization and chromatic dispersion modulation via transfer learning.

Polarization and wavelength multiplexed metalenses address the bulkiness of traditional imaging systems. However, despite progress with numerical simulations and parameter scanning, the engineering complexity of classical methods highlights the urgent need for efficient deep learning approaches. This paper introduces a deep learning-driven inverse design model for polarization-multiplexed metalenses, employing propagation phase theory alongside spectral transfer learning to address chromatic dispersion challenges.

Raman Spectral Feature Enhancement Framework for Complex Multiclassification Tasks.

Raman spectroscopy enables label-free clinical diagnosis in a single step. However, identifying an individual carrying a specific disease from people with a multi-disease background is challenging. To address this, we developed a Raman spectral implicit feature augmentation with a Raman Intersection, Union, and Subtraction augmentation strategy (RIUS).