Search Results (364)

Accurate identification of mango varieties holds substantial significance for the elevation of product added value and the facilitation of market differentiation through quality-based pricing. Near-infrared (NIR) spectral analysis offers a rapid, non-destructive solution for mango variety identification. To address the challenges in fine-grained classification of NIR spectra, namely, high spectral similarity and severe overlap of absorption peaks, which make it difficult to extract nonlinear features using chemometrics, as well as the excessive complexity of existing deep learning models, a lightweight multi-scale spatial global context network is proposed. One-dimensional NIR spectra are converted into two-dimensional images through the Gramian angular difference field. Multi-scale partial convolution, coordinate-aware global context, efficient multi-scale attention, and structural re-parameterization are integrated to capture local spectral features and long-range band correlations effectively. Evaluated on two mango spectral datasets with different distributions, the proposed model achieves variety identification accuracies of 99.46% and 97.83%, with only 19.08 M parameters. Computational complexity, throughput, and latency reach 120.29 M FLOPs, 2848.5 FPS, and 0.351 ms, respectively, realizing a balance between classification accuracy and computational speed. Ablation and robustness experiments demonstrate that the accuracy of the model is improved by 5.91% and 2.15% compared with one-dimensional convolutional neural network and FasterNet, respectively. Important wavelengths obtained by threshold screening of activation maps exhibit consistency with the majority of conclusions from analysis of variance and VIP methods, while the remainder represent newly identified important bands. Validation across different temperature and batch scenarios reveals strong generalization capability. Future refinement will be pursued through increased sample diversity. Overall, high-precision identification is attained by the model at comparatively low computational overhead, indicating potential for advancing the practical application of NIR spectroscopy in agricultural quality inspection. Full article

Local drug delivery increasingly relies on injectable hydrogels that form directly at the x‘administration site, among which light-cured systems are of particular interest: irradiation converts a liquid precursor into a depot and can trigger drug release with high spatiotemporal resolution. The aim of this critical narrative review is to systematize the key design elements of such systems and to assess their path toward the clinic. We analyze the mechanisms of photoactivation, the role of wavelength, the natural, synthetic, and hybrid polymer matrices together with their tuning parameters, and the photoinitiators. The clinical and preclinical experience in dentistry, ophthalmology, regenerative medicine, and oncology is then considered separately. Finally, we address standardization through the Quality by Design concept. We show that, despite an extensive preclinical base, no photocrosslinkable injectable depot for drug delivery has yet been approved, whereas photopolymerization itself and the photoinitiators employed are already accepted in the clinic in adjacent fields. We conclude that clinical translation is defined by three tractable tasks: qualifying photoinitiators for the injectable route of administration, overcoming the limited depth of light activation, and standardizing characterization on the basis of Quality by Design. Full article

Internal responses of multilayer pavement structures are difficult to characterize using surface-based inspection alone. This study investigates a scaled multilayer pavement model instrumented with embedded quasi-distributed fiber Bragg grating (FBG) sensing lines to obtain baseline internal strain responses and FBG-derived relative vertical displacement distributions under controlled loading. Central single-point stepwise loading, symmetric two-point loading, and asymmetric two-point loading were applied, and FBG wavelength responses were converted into temperature-compensated strain and then into line-wise relative vertical displacement through strain–curvature conversion, curvature integration, and linear baseline correction. During loading, the ambient temperature ranged from 22.70 to 23.40 °C, and the maximum relative shift of the T-sensor was 0.008297 nm. Under 686 N central loading, SAL1 reached a maximum temperature-compensated strain of 1459.39 με and a maximum relative vertical displacement of 1.079 mm, whereas SAL2 reached 793.13 με and 0.583 mm. Under approximately 490 N asymmetric two-point loading, SAT2 reached 1699.48 με and 0.761 mm. Soil-base responses were substantially lower. Because no independent displacement measurement was acquired, the reconstructed quantity is interpreted as an FBG-derived relative deformation measure rather than an absolute displacement. The results establish intact baseline data for future, separately validated comparisons with abnormal conditions. Full article

Underwater images often suffer from color distortion, low contrast, and structural blurring caused by wavelength-dependent absorption and scattering, which degrade both visual observation and downstream perception. Existing underwater image enhancement methods usually learn image-level restoration mappings, while the relationships among semantic regions, degradation patterns, and restoration responses are not fully exploited. In this paper, we propose a Semantic Guidance Network with Degradation Consistency for Underwater Image Enhancement (SGDC-UIE). Specifically, SGDC-UIE first extracts dense semantic responses from a frozen DINOv3 prior and converts them into foreground, boundary, and background region gates. These gates are then used to guide pseudo-physical degradation estimation, producing attenuation-like, transmission-like, illumination, structure, and background-light priors for region-aware restoration. These pseudo-physical priors are learned, bounded conditioning variables rather than calibrated estimates of underwater optical parameters. Based on these degradation conditions, a dual-branch restoration network corrects low-frequency color and illumination degradation while recovering high-frequency structural details through semantic-aware wavelet restoration. The color-restored and structure-restored outputs are further integrated by a degradation-consistent fusion gate, which adaptively balances visual fidelity and task-relevant structure preservation. In addition, grouped supervision with quality-anchor replay stabilizes task-aware fine-tuning and reduces visual-quality drift. Extensive experiments on paired and no-reference underwater enhancement benchmarks, semantic segmentation, and underwater object detection show that SGDC-UIE achieves competitive restoration quality and improves the usability of enhanced images for downstream perception. Full article

Ultracold neutrons (UCNs) are free neutrons with kinetic energies so low that their equivalent thermal temperature lies below 3.5 mK (below 3 × 10⁻⁷ eV). At these extreme energies, neutrons exhibit de Broglie wavelengths on the order of hundreds of angstroms and move slowly enough to be confined in material, magnetic, and gravitational traps through total internal reflection. For context, this is about three orders of magnitude colder than the 1 K regime used in superfluid helium UCN sources, which underscores why these neutrons are called “ultracold”: their equivalent thermal energy is comparable to millikelvin physics, even though UCN sources themselves typically operate at 0.8–5 K and produce UCN through superthermal downscattering rather than thermal equilibrium. Over the past several decades, substantial progress in ultracold-neutron source technology has been achieved through the transition from mechanical neutron turbines to superthermal converters based on solid deuterium and superfluid helium. This review provides a comprehensive analysis of modern reactor-based (ILL, PNPI, TRIGA) and spallation-driven (PSI, TRIUMF, SNS, ESS) UCN sources, together with next-generation facilities targeting UCN densities of 10³–10⁴ cm⁻³. Particular attention is devoted to anomalous neutron losses during storage. It is shown that hydrogen-containing surface contaminants, inelastic scattering processes, and wall-induced depolarization contribute significantly to losses beyond those predicted for ideal materials. Current approaches for loss reduction are discussed, including diamond-like carbon coatings, magnetron sputtering techniques, optimization of the ortho–para ratio in neutron converters, and purification of superfluid ⁴He from trace concentrations of ³He impurities. The review further examines key precision experiments that drive advances in UCN technology, including investigations of the neutron lifetime discrepancy and searches for the neutron electric dipole moment at sensitivities approaching 10⁻²⁷–10⁻²⁸ e·cm as probes of CP violation and baryon asymmetry of the Universe. Finally, future directions for increasing UCN density, extending storage times, and enhancing the sensitivity of fundamental physics experiments are discussed. Full article

Junction temperature (T_j) is a key parameter that directly governs the optical performance and operational reliability of light-emitting diodes (LEDs), which have become indispensable in modern illumination and display systems. Accurate real-time T_j monitoring is critical for ensuring device longevity and consistent light output. Although the forward voltage method (FVM) remains the industry benchmark, its practical implementation is hindered by the need for costly high-speed switching modules and ultra-low-current calibration sources, restricting its deployment in real-time and cost-sensitive scenarios. To overcome these limitations, we introduce and experimentally validate a non-contact optical method for T_j determination that leverages the normalized integral width (NIW) of the LED emission spectrum as a temperature-sensitive spectral parameter. The underlying principle is that spectral broadening—arising from enhanced carrier thermal excitation and temperature-induced bandgap shrinkage—exhibits a robust and quantifiable linear correlation with T_j. Both theoretical analysis and experimental data confirm that this mechanism underpins the excellent linear correlation between NIW and T_j observed across a wide range of LED types, including monochromatic (red, green, blue) and phosphor-converted white LEDs. A rigorous theoretical analysis establishes the mathematical framework linking NIW to T_j. Experimentally, a measurement system centered on a modified commercial spectrometer was constructed. Extensive testing on a diverse array of power LEDs consistently demonstrates an excellent linear correlation (R² > 0.998) between NIW and T_j under normal drive conditions (e.g., typical operating currents). A comparative analysis against the benchmark FVM, conducted using a Mentor Graphics T3Ster system, demonstrates that the proposed method achieves comparable measurement accuracy, with a maximum deviation of merely 2.1 °C, while substantially reducing system cost and complexity. Validation across diverse LED types confirmed excellent linearity and high repeatability. A comparative analysis with established optical methods (e.g., peak wavelength, blue-white ratio, Raman thermography) further underscores the advantages of the NIW method in terms of cost-effectiveness, measurement speed, and broader applicability. Subsequent evaluation of critical factors, including self-heating, ambient light interference, and spectrometer resolution, demonstrates its robustness. Consequently, the NIW method presents a practical solution for real-time, non-intrusive thermal monitoring, well-suited for industrial LED production and quality control. Full article

Self-absorption limits efficiency and causes spectral redshift in quantum dot color conversion (QDCC) films, yet it is usually inferred indirectly rather than measured. In this study, we extract the self-absorption probability quantitatively from film photoluminescence (PL) spectra using the correction method of Ahn et al. The films span a wide thickness range at two quantum dot (QD) concentrations, with and without TiO₂. The converted emission peak wavelength scales linearly with the extracted self-absorption probability. For a given TiO₂ condition, this relation is independent of QD concentration. The self-absorption probability increases with both film thickness and QD concentration, reflecting longer optical path lengths and more reabsorption events. The intrinsic quantum yield from the same analysis is thickness-independent within each condition, supporting the extracted values. The addition of TiO₂ increases blue light absorption and lowers the extracted self-absorption probability of the converted emission, consistent with enhanced light scattering. With TiO₂, the remaining self-absorption is concentrated toward shorter wavelengths, producing a larger peak shift at comparable self-absorption probability. The external quantum efficiency increases with thickness at the lower concentration but not at the higher one, reflecting the competition between blue absorption and self-absorption. Full article

Residual stress in brittle films on compliant substrates is routinely inferred from fragmentation experiments by combining an elastic stress-transfer model with a fracture strength criterion. This inversion is inherently coupled because the observed crack spacing depends jointly on the residual stress and the film fracture strength. Conventional closed-form estimators typically rely on a single feature, such as the cracking onset strain, and prescribe the fracture strength a priori, often at its bulk value. This practice discards most of the information encoded in the full crack-spacing evolution. It also obscures two sources of uncertainty: the intrinsic variability of thin-film fracture strength and the limited sensitivity of any single observable to individual parameters. Here, we recast the inversion as a Bayesian physics-informed neural network (B-PINN) in which the entire measured curve of the mean crack spacing versus applied strain is likely to occur. Stochastic gradient Langevin dynamics then sample the joint posterior of residual stress and fracture strength. A central finding is that crack-spacing data alone constrain only the difference between fracture strength and residual stress, confining the posterior to a one-dimensional manifold in parameter space and leaving each quantity individually unresolved. A single substrate curvature measurement, which, through the Stoney relation, depends on the residual stress but not on the fracture strength, provides the missing orthogonal constraint and collapses the posterior to a tight, well-resolved region. We further derive an identifiability condition under which buckle-wavelength observations serve as a third independent channel for recovering interface adhesion energy, and provide a synthetic proof-of-concept of this three-channel extension on DLC/Si and Mo/Si datasets; an experimental validation of the adhesion channel is identified as the natural next step but lies beyond the present scope. Requiring only standard fragmentation measurements and a single non-destructive curvature scan, the framework converts a point-estimate procedure into a posterior-quantified inverse method that makes explicit what can, and cannot, be learned from thin-film mechanics experiments. Full article

To address the structural complexity, limited detection sensitivity, and environmental susceptibility of the stable operating point in conventional fiber-optic current transformers for low-current detection, this study proposes a fiber-optic current transformer based on the coupling of an extrinsic Fabry–Perot interferometer (EFPI) and a lead zirconate titanate piezoelectric ceramic (PZT). In the proposed sensor, a toroidal magnetic core and an induction winding are used as the current pickup unit to convert the measured alternating current into an induced voltage. This induced voltage directly drives the PZT to generate axial displacement, causing periodic variations in the length of the air Fabry–Perot cavity formed between the fiber end face and the coated quartz diaphragm. As a result, the current signal is converted into an optical interference intensity signal. To prevent the static operating point from deviating from the optimal linear region during EFPI intensity demodulation, a DC-component-feedback-based operating point control method is proposed. By adjusting the driving voltage of the fiber Fabry–Perot tunable filter, the center wavelength of the incident narrowband demodulation light can track the optimal operating point of the interference spectrum, thereby improving the stability of the intensity demodulation process. Experimental results show that the fabricated sensor can generate a stable reflected interference spectrum and exhibits a relatively flat frequency response within the range of 0–7 kHz, indicating its potential for power-frequency current detection under the present laboratory conditions. When the measured current is 0.13 mA, the sensor can still produce a distinguishable sinusoidal output signal. When the measured current increases to 75 mA, obvious nonlinear distortion appears in the output signal, indicating that the sensor is approaching the boundary of its linear detection range. Within the linear operating region, the output peak-to-peak value shows good linearity with the measured current. The results indicate that the proposed EFPI-PZT fiber-optic current transformer has the advantages of a relatively simple structure, clear low-current response, and adjustable structural parameters, providing a reference for the miniaturized design and further development of new fiber-optic current sensors. Full article

The safety profile for bio-derived phenols post-oxidation and their related antioxidant/redox potential remain largely under-explored. Oxidation by fungi, in terms of environmental impacts via fungal oxidation by enzymes, remains an attractive strategy under milder conditions, since it is one route by which many naturally occurring lignocellulosic phenols are modified; thus, an immediate need still exists for characterizing the effects that these modified phenolic compounds may have. Methodology: We examined four different biomass-derived phenolics—vanillin, ferulic acid, syringaldehyde and guaiacol—that were oxidized with fungal laccase and characterized their effects on normal human lung fibroblasts and levels of cellular oxidative stress. Laccase activity was evaluated via the ABTS method and through simple observation and UV-Vis spectroscopic scanning of the phenolics in question, and compared with the untreated version of each phenolic. In addition to assessing the cytotoxic effect and oxidative stress generated by the phenols alone, an ELISA-based measurement assay was used to investigate the relative abundance of malondialdehyde (MDA), superoxide dismutase (SOD), catalase (CAT), glutathione peroxidase (GPx) and reduced glutathione (GSH) in the human normal lung fibroblast cell line under varying treatment regimes, complemented by phase-contrast microscopy. Scores integrating the biomarkers were analyzed via clustering, PCA, radar and Pearson correlation analyses, to discern distinct trends in antioxidant potential after laccase conversion. Observations: Each of the four tested phenolics demonstrated the presence of laccase activity, leading to substantial differences in visible appearance compared with the control and characteristic absorbance shifts at differing wavelengths from the original molecule. Cell viability dropped dramatically as phenol concentration was increased and the untreated phenolics resulted in diminished confluence and induced greater levels of oxidative damage, from guaiacol and syringaldehyde. Laccase treatment resulted in higher MTT reduction activity and improved cellular morphology compared with the corresponding untreated phenolic compounds. Untreated phenols induced the highest levels of MDA, while decreasing SOD, CAT, GPx and GSH levels. Post-oxidation with laccase, there were lower amounts of lipid peroxidation, along with improved levels of antioxidant activity compared with the control phenol. Multi-technique analyses show clear distinctness between the untreated and laccase-converted phenolic groups. Clustering with multivariate techniques separated all cell groups in line with control samples, grouping the laccase-converted treatments towards the middle and displaying an inverse relationship between MDA and the antioxidant markers. Conclusions: Laccase conversion markedly decreases the adverse effects that bio-derived phenols have on normal cell viability and induces fewer detrimental effects on the cellular redox balance. This is a critical discovery in terms of finding greener methods by which to upgrade bio-derived substances as we research these lignocellulosic phenols. By employing ELISA-based measurements along with multiple analysis techniques, we present a suitable paradigm for studying biological effects in all bio-based goods intended for pharmaceuticals, packaging materials, nutraceuticals or a host of different applications. Full article

This work presents an enhanced photomechanical optical sensor inspired by our previously reported bio-inspired uncooled infrared detector. Performance improvement is achieved by strengthening the interfacial bond between the photothermal dendrite—polydopamine nanoparticle (PDA NP)/polydimethylsiloxane (PDMS) composite—and the piezoresistive laser-induced nanocarbon film, with a flexible PDMS substrate that provides both thermal insulation and mechanical stability. The resulting sensor exhibits a responsivity of 51.6 W⁻¹ under 808 nm irradiation, an order-of-magnitude enhancement over the unmodified device. Wavelength-dependent characterization (455–1550 nm) shows responsivity decreasing from 93.1 W⁻¹ at 455 nm to 14.4 W⁻¹ at 1550 nm, with response times on the order of seconds across this range. Extending this trend into the longer-wavelength region of blackbody radiation, the mechanism transitions to a predominantly bolometric mode. The device also demonstrates stable detection of several hundred microwatts and robust durability at 455 nm. These results validate interface engineering strategy as a viable pathway toward high-performance uncooled optical detection, advancing bio-inspired detectors from functional mimicry toward an application-ready platform. These findings confirm PDA NPs as effective photothermal converters primarily at shorter wavelengths, while the wavelength-dependent response suggests future tailoring of spectral sensitivity using long-wavelength-absorbing materials. Full article

We propose a loss-managed BIC-derived GSST metasurface for robust phase-change-tunable mid-infrared transmission suppression. The metasurface consists of a SiO₂ substrate, a Si grating layer, and an upper Si/Ge₂Sb₂Se₄Te₁ (GSST)/Si trilayer with an off-centered air slot. The slot plays a dual role: it breaks the mirror symmetry of the unit cell to convert a symmetry-protected bound state in the continuum into an externally accessible high-Q resonance, while reducing the effective GSST filling region to limit material-loss participation. Lossless eigenmode analysis confirms the BIC-derived origin of the resonance, with the quality factor following $Q\propto x_{\mathrm{disp}}^{-1.993}$. A crystalline-state loss-channel analysis further identifies $x_{\mathrm{disp}}=40\mathrm{nm}$ as a finite-coupling operating point that preserves good up/down radiation balance, a large resonant amplitude factor, and a moderate-high quality factor under the fully crystalline GSST condition. Full-wave simulations show that the transmission-dip wavelength shifts from about $3.9568\mathsf{\mu }\mathrm{m}$ to about $3.9740\mathsf{\mu }\mathrm{m}$ as GSST evolves from the amorphous to the crystalline state, while the extracted quality factor remains in the range of 483–780 and the transmission minimum stays deeply suppressed throughout the phase-change trajectory. A two-port temporal coupled-mode theory analysis reveals that this persistent low-transmission state originates from destructive interference between the resonant and background transmission channels. Fabrication tolerance analysis shows that $\pm 5\%$ variations in GSST thickness and slot width, as well as moderate variations in the slot displacement, preserve the deep transmission suppression across GSST phase states, although the absolute resonance wavelength shifts with geometry. These results provide a practical strategy for balancing radiative coupling and material-loss participation in phase-change high-Q metasurfaces. Full article

This paper reports on the performance of an optical voltage transducer (MVT) module after undergoing lightning impulse withstand tests. The device was designed to monitor the output voltage of a dedicated capacitive voltage divider (CVD) to facilitate a voltage sensor dedicated for 132-kV high voltage (HV) networks. Hard piezoelectric transducer (PZT) and fiber Bragg grating (FBG) technologies were combined in the module to serve as a voltage-to-strain-to-wavelength converter. The FBG peak wavelength shifts were calibrated against the input voltage to provide precise measurements of the network voltage. The module was subjected to lightning impulse withstand tests as per the requirements of the IEC 60044-7 and IEC 60060-1 standards, and the impact of the lightning impulses on the performance of the MVT module was evaluated based on the accuracy tests performed before and after the lightning impulse tests. The experimental results demonstrated that the MVT module successfully withstood the lightning impulse tests without any disruptive discharges or voltage collapses. The performance of the module was not affected by the lightning impulse tests within the practical constraints of the reference measuring equipment: its amplitude and phase errors remained within the original limits of ±0.1% and ±0.1° at 80–120% of the rated voltage, and below ±4% and ±2° at 2% of the rated voltage, respectively. Full article

Ultrafast physical random bit generators (PRBGs) are essential components for modern applications in secure communication, quantum cryptography, encrypted optical fiber sensing and artificial intelligence. While optical chaos-based PRBGs offer high-speed capabilities, conventional systems often rely on discrete components that suffer from system complexity and environmental instability. This paper proposes and experimentally demonstrates a robust, integrated solution using a two-section mutual injection DFB laser. The device was fabricated using the reconstruction equivalent chirp (REC) technique, which provides precise control over grating phase variation while utilizing low-cost, high-volume fabrication methods. The laser sections, each measuring 450 μm in length, were designed with a free-running wavelength difference of 0.3 nm to ensure a flat optical spectrum and enhanced chaotic dynamics. By optimizing the bias currents, we achieved a chaos RF bandwidth of 20.1 GHz. Notably, the resulting chaotic signal lacks time-delayed signatures, which simplifies the randomness extraction process. To generate random bits, the chaotic waveform was sampled by an 8-bit analog-to-digital converter at 100 GSa/s. Following post-processing through delay-subtracting and the extraction of the four least significant bits (4-LSBs), we realized a total physical random bit rate of 400 Gb/s. The randomness of the generated sequence was successfully verified using the NIST SP 800-22 statistical test suite. This approach offers a compact, energy-efficient, and high-performance integrated chaotic source suitable for secure communication and high-performance computation. Full article

A reflective plasmonic humidity sensor based on an Au–PVA–Au nanohole sandwich structure is investigated. The device consists of a periodic gold nanohole array, a poly(vinyl alcohol) (PVA) spacer, and a continuous gold film. A humidity-dependent model considering both the refractive-index decrease and thickness swelling of PVA is established to analyze the optical response and resonance-modulation mechanism. Within the relative humidity range of 20–98%RH, the reflection resonance dip exhibits a continuous blueshift with a total wavelength shift of approximately 135 nm. Piecewise linear fitting shows sensitivities of 1.3857 nm/%RH in the 20–74%RH range and 2.5000 nm/%RH in the 74–98%RH range. At approximately 74%RH, the resonance wavelength, full width at half maximum, and quality factor are about 830 nm, 19 nm, and 43.7, respectively. Decoupling analysis confirms that both PVA refractive-index reduction and thickness swelling contribute to the blueshift, while their combined effect produces the largest response. These results demonstrate that the proposed structure converts humidity-induced optical and geometric variations in PVA into a pronounced wavelength response, providing a mechanism-guided design route for reflective nanoplasmonic humidity sensors based on polymer-assisted cavity modulation. Full article