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A novel, to the best of our knowledge, balanced air-biased coherent detection scheme for capturing ultrabroadband terahertz (THz) waveforms is implemented. The balanced detection scheme allows for coherent detection at the full repetition rate of the laser system without requiring bias modulation, signal generators, or lock-in amplifiers while doubling the dynamic range and quadrupling the signal-to-noise ratio compared to conventional air-biased coherent detection. These advantages are achieved by rotating the bias electrodes by 90° relative to the conventional scheme. With a 1 kHz driving laser, the scheme enables sub-second, high-fidelity waveform acquisition with a continuously moving delay stage, demonstrated by collecting 200 waveforms in 100 s. The balanced detection scheme paves the way for much faster and higher quality 2D ultrabroadband terahertz spectroscopy.
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http://dx.doi.org/10.1364/OL.533336 | DOI Listing |
Phys Rev Lett
August 2025
State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China.
Using e^{+}e^{-} collision data collected with the BESIII detector operating at the Beijing electron positron collider, the cross section of e^{+}e^{-}→π^{+}π^{-}h_{c} is measured at 59 points with center-of-mass energy sqrt[s] ranging from 4.009 to 4.950 GeV with a total integrated luminosity of 22.
View Article and Find Full Text PDFInvest Ophthalmol Vis Sci
September 2025
Division of Biomedical Physics, Office of Science and Engineering Laboratories, Center for Devices and Radiological Health, U.S. Food and Drug Administration, Silver Spring, Maryland, United States.
Purpose: To assess macular choriocapillaris (CC) metrics in healthy volunteers (HVs) without ocular disease and demonstrate CC variations in patients with inherited retinal dystrophies (IRDs) using adaptive optics optical coherence tomography angiography (AO-OCTA).
Methods: Twenty-one HVs and three IRD patients were imaged. Macular variation in 20 HVs in CC metrics (CC density, CC diameter, CC tortuosity, void diameter, void area, lobule count, lobule area, and RPE-CC distance) were assessed by imaging a 28° strip of overlapping AO-OCTA volumes (3° × 3°) from the optic nerve head to the temporal macula.
Cell Rep Methods
August 2025
Department of Biomedical Engineering and Computational Biology Program, OHSU, Portland, OR, USA; Knight Cancer Institute, OHSU, Portland, OR, USA. Electronic address:
We present UniFORM, a non-parametric, Python-based pipeline for normalizing multiplex tissue imaging (MTI) data at both the feature and pixel levels. UniFORM employs an automated rigid landmark registration method tailored to the distributional characteristics of MTI, with UniFORM operating without prior distributional assumptions and handling both unimodal and bimodal patterns. By aligning the biologically invariant negative populations, UniFORM removes technical variation while preserving tissue-specific expression patterns in positive populations.
View Article and Find Full Text PDFRetina
September 2025
Department of Ophthalmology, Inselspital, Bern University Hospital, University of Bern, Freiburgstrasse 15, CH-3010.
Purpose: To evaluate inter-grader variability in posterior vitreous detachment (PVD) classification in patients with epiretinal membrane (ERM) and macular hole (MH) on spectral-domain optical coherence tomography (SD-OCT) and identify challenges in defining a reliable ground truth for artificial intelligence (AI)-based tools.
Methods: A total of 437 horizontal SD-OCT B-scans were retrospectively selected and independently annotated by six experienced ophthalmologists adopting four categories: 'full PVD', 'partial PVD', 'no PVD', and 'ungradable'. Inter-grader agreement was assessed using pairwise Cohen's kappa scores.
Clin Exp Ophthalmol
September 2025
Centre for Eye Research Australia, Royal Victorian Eye and Ear Hospital, East Melbourne, Victoria, Australia.
Background: Reticular pseudodrusen (RPD) signify a critical phenotype driving vision loss in age-related macular degeneration (AMD). This study sought to develop and externally test a deep learning (DL) model to detect RPD on optical coherence tomography (OCT) scans with expert-level performance.
Methods: RPD were manually segmented in 9800 OCT B-scans from individuals enrolled in a multicentre randomised trial.