Group velocity dispersion (GVD) in near-resonant hot atomic vapors is difficult to measure with standard pulse broadening or interferometric techniques, as absorption, pulse distortion and nonlinearities strongly affect the probe and reduce the signal-to-noise ratio. We introduce a simpler method using a continuous-wave laser with weak phase modulation and a slow photodetector, directly inspired by Bragg-like spectroscopy in fluids of light. During propagation, the red and blue-detuned sidebands accumulate different dispersive phase shifts, leading to oscillations in the transmitted modulation contrast as the modulation frequency is scanned. Vanishing contrast at well-defined frequencies directly yields the GVD. We apply this technique to hot rubidium vapors and observe the strong frequency dependence of the GVD across a broad detuning range of the D2 line at different temperatures.

ABSTRACT Fabry‐Pérot cavities are widely utilized in optical communication systems and laser technologies. Monolithically integrated reflectivity‐tunable Fabry‐Pérot cavities still face significant challenges, particularly in achieving low‐loss transmission and high tuning efficiency mechanisms. In this work, we demonstrate an on‐chip reflectivity‐tunable Fabry‐Pérot cavity through integration of the Mach‐Zehnder interferometer and Sagnac loop mirror on thin‐film lithium niobate substrate. This F‐P cavity achieves the Q factor of 2.5 × 10 5 at 1553.26 nm along with the reflectivity modulation contrast of 17.5 dB. These results establish a critical foundation for on‐chip high‐ performance laser.

ABSTRACT This study investigates the fidelity of high‐resolution, colorimetrically reproduced digital images in rendering the perceived gloss of real‐world objects. The methodology employed two psychophysical experiments using 24 stimuli consisting of glass, metal, and stone. The first was a direct comparison of the perceived gloss between the real objects and their initial colorimetrically reproduced images. The second was a selection task where participants matched the gloss of the real objects to a set of algorithmically processed images. The findings reveal two key results: (1) The direct comparison demonstrated that digital colorimetric reproduction significantly reduced the perceived gloss compared to the real objects. (2) The subsequent image selection experiment indicated that the contrast component of gray level co‐occurrence matrix (GLCM) features is a significant predictor of the accuracy in reproducing the real objects' gloss. These results suggest that accurate gloss reproduction in digital displays is not solely dependent on colorimetric fidelity, but can be effectively achieved through the modulation of image contrast.

We report an anomalous photoresponse in LiInP2Se6-gated monolayer MoS2 field effect transistors (FETs), driven by sub-bandgap photocarrier excitation and relaxation in LiInP2Se6. The MoS2/LiInP2Se6 heterostructure exhibits gate-tunable persistent negative photoconductivity, a rare phenomenon in 2D FET platforms. Notably, the photoconductivity change scales with incident light intensity, with weaker illumination producing slower, smaller responses and stronger illumination inducing faster, stronger suppression. Exploiting the nonlinear, intensity-dependent photoresponse of LiInP2Se6, we demonstrate an image-processing platform that enables contrast modulation directly at the sensor level. By varying two controllable parameters, namely, applied top-gate bias and light exposure time, the device response can be tuned to modify the contrast of the image. This intrinsic behavior illustrates how contrast tunability can be achieved on a chip, offering a simple and compact route toward elementary preprocessing functions in vision devices.

Peripheral defocus and image contrast modulation are key strategies in myopia control, but both inherently reduce retinal image contrast. To date, no in vivo study has directly compared these effects. This study evaluated the contrast reduction profiles of different myopia control spectacles to better understand their underlying mechanisms. Through-focus images (TFIs) were obtained with a double-pass instrument in a model eye and in human eyes wearing four spectacle designs: DIMS, Stellest, diffusion optics technology (DOT), and MyoCare. The naked eye served as a reference. Thirteen participants (mean age = 29.0 ± 3.5 years) were tested at the fovea and at 10° and 20° eccentricities in the temporal and superior fields. Lenses were decentered by 1.5 cm to assess off-axis effects. Model eye tests included only the central field. Retinal image contrast (RIC) was calculated as the coefficient of variation of pixel intensity in TFIs. In the model eye, RIC ranked from highest to lowest as follows: naked eye, DIMS, DOT, MyoCare, and Stellest. In vivo, DOT results were excluded due to a weak signal. A nonparametric test revealed significant differences in RIC among lenses at the fovea (P = 0.009) and at 10° in the temporal/superior fields (P = 0.05). Post hoc analysis showed that Stellest produced the greatest reduction in RIC, whereas MyoCare and DIMS demonstrated similar levels of contrast loss. All myopia control lenses reduced retinal image contrast, with Stellest inducing the strongest reduction. MyoCare and DIMS showed comparable effects. Lens-induced optics primarily influenced contrast in the near periphery, while ocular optics dominated at larger eccentricities.

Phase-shifting fringe projection (PSFP) is widely used in industrial inspection and three-dimensional measurement, where γ nonlinearity of the projector-camera system is traditionally treated as a phase-error source to be calibrated or compensated. In this work, γ nonlinearity is reinterpreted from an imaging perspective and shown to act as a statistical distortion mechanism that reshapes modulation stability, overexposure behavior, and defect saliency in fringe-based imaging. Building on the intrinsic DC-AC decomposition of phase-shifting demodulation, we analyze how γ nonlinearity interacts with fringe modulation and frequency-selective transfer. An analytical model reveals that γ nonlinearity simultaneously suppresses the fringe fundamental and introduces harmonic leakage, leading to systematic compression of mean modulation contrast in high-brightness regions. As a result, γ correction does not necessarily enhance mean-based defect contrast and may even reduce it, contrary to common intuition. We further demonstrate that the primary benefit of γ correction lies in statistical stabilization rather than contrast amplification. By introducing modulation-domain saliency formulations and a frequency-domain harmonic energy ratio, a physical link is established between γ nonlinearity, overexposure, and defect separability. Controlled experiments on highly reflective sheet-metal specimens confirm that while mean-contrast- and SNR-based saliency metrics often decrease after γ correction, separability-based metrics consistently improve due to reduced nonlinear- and saturation-induced variance. Cross-channel and cross-condition analyses further show that modulation and reflectance images respond differently to γ correction, yet metric-level separability exhibits consistent improvement across channels. These results clarify the true role of γ correction in fringe-based inspection and provide theoretical insight and practical guidance for robust defect imaging under nonlinear and near-overexposure conditions.

Contrast modulation (CM) stimuli have been previously used to reveal nonlinear contributions of Y-like retinal ganglion cells (RGCs) such as parasol cells to cortical responses and perception. To test whether CMs are selectively processed within the magnocellular pathway, we assessed envelope motion discrimination and detection for achromatic (yellow-black) and chromatic (red-green) CMs in the presence of luminance masking noise to disrupt luminance-based mechanisms of motion processing. Compared to achromatic CMs, perception of chromatic CMs was more sensitive to luminance masking noise, suggesting that CM envelope motion perception relied predominantly on luminance signals. Specifically, envelope motion discrimination performance was better maintained for achromatic CMs than chromatic CMs, even at high masking noise levels. Notably, luminance masking noise greatly impaired envelope direction discrimination for chromatic CMs but had minimal impact on their detection, suggesting that chromatic aberrations may enhance envelope motion perception for chromatic CMs by introducing luminance signals. These findings reinforce previous neurophysiological and psychophysical evidence that CM stimuli selectively engage the nonlinear receptive field mechanisms of Y-like/parasol RGCs within the magnocellular retinogeniculate pathway, underscoring their potential to specifically target this pathway.

Abstract This work presents a theoretical investigation into the early dynamics of ripples formation using femtosecond laser double-pulse excitation. A self-consistent multi-physics model was developed to investigate the early stage of ripples formation in highly non-equilibrium silicon. This comprehensive model accounts for the interplay between the simultaneous dynamics of optical modulation, carrier generation, and two-temperature heat transfers. We obtained the 2D dynamic evolutions of carrier density and the carrier and phonon temperatures during ripples formation induced by femtosecond laser double-pulse. The study revealed that the ripples modulation contrast of phonon temperature is significantly amplified via the second femtosecond pulse rather than the first pulse. The results are explained by the predominant enhancement of the local carrier–phonon coupling dynamics compared to the non-local dynamics of carrier ambipolar and carrier thermal diffusions following the second femtosecond pulse excitation. This study offers basic insights into the early stage of ripples formation on silicon wafers induced by femtosecond laser double-pulse, paving the way for novel surface applications in surface coloring, enhanced solar cell absorption, and surface wettability etc.

Randomized clinical trial of Diffusion Optics Technology spectacle lenses in a Chinese population (CATHAY): 12-month results

Metasurface-based optical image processing has enabled compact and low-power platforms, yet wavefront-differentiation-based metasurfaces remain fundamentally constrained by their reliance on coherent illumination and intrinsically static optical responses. Meanwhile, conventional optical microscopes rely on bulky, mechanically actuated condensers to engineer illumination numerical aperture (NA), restricting continuous tunability and preventing integration into compact or on-chip imaging systems. These limitations highlight the need for a miniaturized, electrically reconfigurable condenser capable of continuous illumination engineering under incoherent illumination within flat-optics architectures. Here, we demonstrate an electrically reconfigurable illumination-engineering (ERIE)-metalens that embeds a polyaniline (PANI) thin film within a metalens to realize a voltage-programmable condenser, enabling continuous illumination NA control and imaging-mode tuning. Leveraging the exceptional optical contrast modulation of PANI, the ERIE-metalens achieves smooth transitions between bright-field, quasi-dark-field, and dark-field imaging under incoherent light with sub-1 V operation. This continuous illumination engineering enables a quasi-dark-field regime, where transmitted and scattered light coexist in a voltage-programmable ratio, yielding hybrid contrast challenging to achieve with conventional condensers or coherent-dependent metasurfaces. Using the hybrid contrast of the quasi-dark-field, we demonstrate multimodal imaging of biological cells, simultaneously revealing overall cell morphology and fine intracellular details with a single integrated device. Our work highlights illumination engineering as an effective approach in flat optics, positioning the ERIE-metalens as an ultracompact, electrically reconfigurable, and incoherent-light-compatible platform for real-world, multifunctional optical microscopy.

Dynamic switching between daytime radiative cooling (DRC) and solar heating (SH), adapting to varying environmental conditions, offers an energy-saving and sustainable solution for all-seasonal thermal regulation of buildings and other outdoor facilities. However, many existing SH/DRC switchers can only alternate between high transmission and high reflection in the solar spectrum, hindering the effective harvesting of solar energy. Herein, by integrating the reversible metal electrodeposition technology and optical metamaterial absorber for the first time, we develop a novel device enabling in situ and active switching between SH/DRC states with a large modulation contrast of ΔAsol = 0.82, whose superior performance is further validated by outdoor temperature measurements and building level energy-saving simulations. Our work not only opens new opportunities for thermal regulation devices and materials with higher environmental adaptability but also highlights the promising role of RMED in realizing highly efficient dynamic photonic devices.

We investigate spatial localization and interference control in a three-level quantum dot (QD) system driven by two-dimensional standing-wave fields. Although QDs are embedded in solid-state environments and are heavier than natural atoms, their discrete energy levels and tunable tunneling couplings allow them to replicate atomic-like behaviors, offering greater flexibility than traditional atomic systems. Using the density matrix formalism, we calculate the optical susceptibility under the influence of a weak probe and a strong control field. This susceptibility explicitly incorporates inter-dot tunneling and phase-coherent interactions, ensuring that the resulting localization is not merely a classical field imprint but reflects quantum interference effects. Our results show that while the standing-wave fields define the spatial modulation template, the accuracy, contrast, and stability of localization are primarily determined by quantum coherence and tunneling-induced interference. Symmetric wavevector configurations lead to sharply confined, isotropic localization profiles, whereas asymmetries in wavevector alignments cause the distribution to broaden and degrade, reducing localization precision. These findings highlight the critical role of tunneling coherence and wavevector alignment in controlling localization behavior. The observations suggest that QDs, with their tunable energy levels and tailored tunneling couplings, provide versatile solid-state analogs for exploring localization phenomena. These systems hold significant potential for applications in spatially resolved quantum information processing, nanoscale sensing, and the development of coherent nanophotonic devices.

This paper reports an approach to fabricate 3D nanoscale patterns using a modified 2D DNA template in a single step of pattern transfer. Triangular‐shaped DNA origami was modified with streptavidin and used as the template for HF‐vapor etching of SiO 2 to produce negative tone triangular patterns of more than 28 nm in depth and 22 nm in width. Streptavidin molecules locally increase the rate of HF etching reaction, increasing vertical contrast of the transferred pattern by 39% but without noticeable change in the width. The result is consistent with the hypothesis that streptavidin increases adsorption of water, which is a catalyst for the HF vapor etching of SiO 2 . Our work points to a new approach to accelerate and simplify 3D nanofabrication.

Interpretable visual image representation learning to reveal image variation factors is a hot research topic in computer vision. Many existing disentanglement methods discover variation factors of images and learn disentangled representations by using extra regularization term. However, it usually leads to an imbalance between disentanglement and generative quality, which affects visual image understanding. To address this issue, a generative visual image understanding method based on disentangled representation learning is proposed in terms of interpretable variations in images. Firstly, a pre-trained Glow model is designed to acquire the latent representations of target images. Secondly, a learning strategy based on image variation is constructed from the latent representations to obtain interpretable directions of candidate traversals. Finally, the contrast module is designed under the contrastive learning perspective to simulate image variations based on the interpretable directions of candidate traversals and then extract disentangled representations. The experimental results show that better results are achieved on the popular disentanglement datasets, which are Shapes3D, MPI3D, Anime, MNIST and Cars3D, where the MIG, DCI, FactorVAE score and β-VAE score metrics reach 0.16, 0.27, 0.89 and 0.98, respectively, on the Cars3D dataset, verifying the effectiveness and feasibility of the proposed method.

Choosing the appropriate signal parameter is paramount to producing informative and reproducible findings. In EEG-based affective neuroscience, it is useful to consider that affective processes can unfold over several seconds, which can limit the utility of event-related potentials (ERPs) that are most sensitive near the onset of a stimulus. One promising solution for probing affective attention over longer time-windows is to present stimuli in flickering mode that increases the number of stimulus 'onsets' in a unit of time, an approach known as Steady-State Visually Evoked Potentials (SSVEP). In this study (N = 44), we used a barely noticeable (and therefore less disturbing) periodic contrast modulation (42.5 Hz) to probe variation in attention towards the flickering stimuli modulated by stimulus-driven (negative vs. neutral) and task-driven (unregulated viewing vs. distraction via mental imagery) mechanisms. Time-frequency analysis based on rhythmic entrainment source separation revealed sensitivity to task-driven attentional manipulation, albeit in an unexpected direction. Surprisingly, affective valence did not modulate EEG power at the tagged frequency, diverging from previous reports based on low-frequency SSVEP. Meanwhile, the late positive potential (LPP) indicated sensitivity towards both task-driven and stimulus-driven attention, although the task-driven effect proved more local and did not generalize across time in a sliding-window robustness check. Together, these findings suggest that SSVEPs and LPPs index distinct aspects of affective attention. The potential origins of these findings are discussed, with emphasis on the involvement of eye movements and imagery-driven resource competition in the brain.

Abstract Fluorescent dithienylethene (DTE) photoswitches show significant potential for applications in optical data storage, super‐resolution imaging, high‐security anti‐counterfeiting and information encryption. Nevertheless, the current systems remain constrained by several fundamental limitations, including dependence on higher‐energy excitation for photocyclization, suboptimal photoswitching kinetics, limited fluorescence modulation contrast, and incomplete ring‐closure conversion. Herein, a novel dithienylethene photoswitch (CDBT) featuring a donor‐DTE‐acceptor‐donor (D‐DTE‐A‐D') architectural motif has been rationally designed and synthesized, where the N‐phenylcarbazole and thiophene groups represent two donors (D and D'), respectively, and difluoroboron β ‐diketonate moiety serves as the acceptor (A). Leveraging The sophisticated “acceptor synergistic conjugation system” strategy, CDBT remarkably demonstrates fast photoswitching kinetics, near‐quantitative cyclization yield (up to 96.6%), exceptional fluorescence ON/OFF ratio of 2300:1 and multicolor fluorescence switching behavior within 5 seconds of irradiation with long‐wavelength green light. The proof‐of‐concept applications in information encryption, anti‐counterfeiting, and photorewritable patterns are successfully demonstrated exclusively using green/near‐infrared light. This work opens a new avenue for developing high‐performance DTE photoswitches triggered by longer‐wavelength visible light.

Fetal ultrasound standard plane recognition plays a vital role in ensuring accurate prenatal assessment but remains challenging due to intrinsic factors such as poor tissue contrast, indistinct anatomical boundaries, and variability in image quality caused by operator differences. To address these issues, we introduce a plug-and-play Adaptive Contrast Adjustment Module (ACAM), inspired by how clinicians manually adjust image contrast to highlight clearer structural cues. The proposed module integrates a lightweight, texture-aware subnetwork that learns to generate clinically meaningful contrast parameters, producing multiple contrast-enhanced representations of the same image through a differentiable transformation process. These enhanced views are then fused within subsequent classifiers to enrich discriminative features. Experiments conducted on a multi-center dataset containing 12,400 fetal ultrasound images across six anatomical planes demonstrate consistent performance gains: the accuracy of lightweight models rises by 2.02%, conventional architectures by 1.29%, and state-of-the-art models by 1.15%. The key novelty of ACAM lies in its content-adaptive and clinically aligned contrast modulation, which replaces random preprocessing with physics-guided transformations mimicking sonographers’ diagnostic workflows. By leveraging multi-view contrast fusion, our approach enhances robustness against image quality variations and effectively links low-level texture cues with high-level semantic understanding, offering a new framework for medical image analysis in realistic clinical settings. Our code is available at: https://github.com/sysll/ACAM.

Prominent cryogenic fluorescence temperature sensing and superior room-temperature photochromism in Bi/Eu codoped KNN transparent-ferroelectric ceramics

Selective targeting of coagulation factor X Gla domain by negatively charged gold nanoparticles: a novel method for controlled antithrombotic therapy

At present, some aging populations, such as those in Japan, face an underlying risk of inadequate medical resources. Using neural networks to assist doctors in locating the aorta in patients via computed tomography (CT) before surgery is a task with practical value. While UNet and some of its derived models are efficient for the semantic segmentation of optimally contrast-enhanced CT images, their segmentation accuracy on poorly or non-contrasted CT images is too low to provide usable results. To solve this problem, we propose a data-processing module based on the physical–spatial structure and anatomical properties of the aorta, which we call the Automatic Spatial Contrast Module. In an experiment using UNet, Attention UNet, TransUNet, and Swin-UNet as baselines, modified versions of these models using the proposed Automatic Spatial Contrast (ASC) Module showed improvements of up to 24.84% in the Intersection-over-Union (IoU) and 28.13% in the Dice Similarity Coefficient (DSC). Furthermore, the proposed approach entails only a small increase in GPU memory when compared with the baseline models.