Search Results (1,449)

This article proposes, to the best of our knowledge, the first dual-port compact dual-polarized ultrawideband wearable textile antenna covering lower UHF bands for off-body communications in Internet-of-Things-based wireless body area network (IoT-based WBAN) scenarios. The antenna covers key bands for diverse services, including the 470–510 MHz LoRa WAN, 700 MHz offline emergency communication, 900 MHz NB-IoT, and 1–1.2 GHz satellite internet bands. The antenna adopts a square-ring loaded wide slot structure and a multi-mode resonant feeding structure to achieve ultrawideband operation. Moreover, it utilizes oppositely placed advanced microstrip feeding networks to excite the horizontal and vertical polarization modes, respectively, and four narrow slots around the wide slot to extend the current path, thus enabling a compact size of 0.30 × 0.28 × 0.0035 λ_l³ (where λ_l is the largest operating wavelength). Measured −10 dB impedance bandwidths are 119.1% (0.35–1.38 GHz) for Port 1 and 115.9% (0.39–1.37 GHz) for Port 2 on the human body, with more than 19 dB port isolation over the operating band. The measured average gains are about 4.21 dBi for Port 1 and 3.54 dBi for Port 2 on the human body, respectively. Specific absorption rate analysis confirms compliance with the IEEE C95.1 limit at 0.5 W input power. Wireless transmission experiments at IoT bands further validate reliable off-body links with excellent signal-to-noise ratios for both polarizations. The antenna shall be very attractive for off-body communications in IoT-based WBAN scenarios. Full article

Wave-edge milling tools can suppress chatter by introducing periodic harmonic variations along the cutting edge, which change the tooth-passing time delays between adjacent teeth. However, their stability is affected by coupled waveform parameters, such as amplitude, wavelength, and phase, making it difficult to screen suitable parameter combinations efficiently. This numerical/modeling-based study uses a previously validated multi-delay dynamic model to investigate the probabilistic relationship between pitch angle variance (PAV) and stability region area (SRA). A large number of feasible waveform-parameter combinations are generated under geometric constraints, and a PAV-based stratified sampling strategy is used to retain 54 representative parameter sets from six PAV layers for stability lobe diagram construction and SRA calculation. The results show that PAV has weak pointwise predictive capability for individual SRA values, with Pearson = 0.4234, Spearman = 0.4720, and R² = 0.179. However, the stratified statistical results reveal a clear layer-wise probabilistic tendency: the mean SRA increases from 17.962 to 20.996 in units of rpm·m, and the probability of obtaining an above-median SRA increases from 11.1% to 88.9%. The high-value tail case with PAV > 0.06 further indicates that a higher PAV does not necessarily guarantee a larger SRA for an individual parameter set. Therefore, PAV should not be used as a deterministic predictor or stand-alone tool-selection criterion, but can serve as a low-cost auxiliary probabilistic pre-screening descriptor before high-fidelity SLD/SRA evaluation. Full article

Wind power plays an important role in renewable energy generation, and the reliability of wind turbine gearboxes directly affects turbine operation and maintenance. Compound gear fault diagnosis remains challenging because multiple fault components may coexist and compound fault samples are often limited, leading to long-tailed data distributions. To address this problem, this study proposes a long-tailed multi-label diagnostic framework based on fiber Bragg grating (FBG) acceleration signals and multi-channel time-series imaging. Missing tooth, pitting, and tooth breakage faults are encoded as three independent labels to represent healthy, single-fault, double compound fault, and triple compound fault conditions. The one-dimensional FBG wavelength-shift signals are transformed into GASF-GADF-MTF three-channel images, which describe amplitude angular correlation, dynamic angular difference, and state transition information. A ResNet18-SE network trained with Focal Loss is developed to improve the recognition of minority compound fault samples. Experimental results show that the proposed method achieves an Exact Match Accuracy of 0.9950 and a Macro-F1 of 0.9980 on the Balanced dataset. Under the severe LT50 setting, it achieves an Exact Match Accuracy of 0.9739 and an F1₁₂₃ of 0.9469. These results demonstrate the effectiveness of the proposed framework for FBG-based long-tailed compound fault diagnosis. Full article

The problem of direct inverse optimization of multi-output wavelength division multiplexers (WDMs) on silicon is that these WDMS often exhibit inter-channel crosstalk, making reliable designs difficult to achieve. A cascaded WDM design on a silicon photonics platform is implemented using an inverse design approach. The key idea is to avoid the instability of direct multi-output optimization by sequentially combining several two-output units, thereby realizing a single-input three-output device within a small footprint. Full-wave FDTD simulations show that the first stage achieves effective wavelength separation with high transmission. After cascading two stages, three target wavelengths (1450 nm, 1500 nm, and 1550 nm) are successfully routed to different output ports, with a minimum transmission exceeding 0.71 and inter-channel crosstalk below −9.97 dB, within a total device footprint of 17.745 μm². These results indicate that cascaded inverse design offers a stable and practical solution for multi-channel WDM design on silicon. Full article

Nova eruptions exhibit diverse photometric and spectroscopic properties traditionally classified using empirical light-curve morphology and spectral taxonomy. However, these observational classifications do not uniquely constrain the underlying eruption physics. This review examines the coupling between light-curve evolution, spectral development, ejecta dynamics, and multi-wavelength emission in classical and recurrent novae, with particular emphasis on the role of shocks and multi-phase outflows. Recent observations across optical, radio, X-ray, and gamma-ray wavelengths demonstrate that nova ejecta are intrinsically structured, anisotropic, and dynamically interacting systems, challenging the traditional interpretation of novae as spherically symmetric thermonuclear explosions. We synthesise observational and theoretical studies that link decline timescales, spectral transitions, expansion velocities, and high-energy emission to fundamental physical parameters, including white dwarf mass, accretion rate, ejecta geometry, and shock energetics. Using a compiled multi-parameter dataset of classical, recurrent, and symbiotic novae, we demonstrate that many commonly used observational diagnostics are intrinsically degenerate, with similar observable properties arising from different physical conditions. We argue that nova diversity is better understood within a continuous multi-dimensional parameter space rather than through purely empirical classifications. The implications of this framework for mass retention efficiency and the evolution of recurrent novae toward Type Ia supernova progenitors are discussed. Finally, we outline a predictive observational framework integrating photometric, spectroscopic, and high-energy diagnostics for future nova studies. Full article

The chlorophyll fluorescence parameter Fv/Fm, representing the maximum photochemical efficiency of photosystem II, is an important indicator for evaluating plant photosynthetic performance and stress responses. However, rapid and non-destructive monitoring of Fv/Fm at the leaf scale remains challenging because conventional fluorescence measurements are time-consuming and require specialized equipment. Although spectral techniques provide an efficient alternative, existing spectral-based models mainly rely on single-source information and often lack sufficient integration of environmental conditions and physiological interpretability. Therefore, this study aimed to develop an explainable multi-source information fusion framework by integrating leaf spectral characteristics and environmental variables for accurate and interpretable estimation of grape leaf Fv/Fm. The grape cultivar ‘Queen Nina’ grown under protected cultivation was used as the experimental subject in this study. Visible–near-infrared reflectance spectra, measured Fv/Fm values, and environmental variables were synchronously collected under different water-stress conditions. Sensitive wavelengths were extracted by multiplicative scatter correction (MSC), competitive adaptive reweighted sampling (CARS), and the successive projections algorithm (SPA), and an XGBoost model incorporating both spectral and environmental features was established. The results demonstrated that: (1) the proposed multi-source fusion strategy effectively integrated spectral and environmental information for Fv/Fm prediction, with 12 sensitive wavelengths identified by MSC-CARS-SPA; (2) the XGBoost-EF model achieved R², RMSE, and MAE values of 0.906, 0.0432, and 0.0352, respectively, under vine-level five-fold cross-validation, outperforming the spectral-only XGBoost model; and (3) SHAP analysis provided an interpretable explanation of model predictions by quantifying the contributions of key spectral and environmental features, highlighting the importance of leaf temperature and red-edge wavelengths. It is concluded that the accuracy, robustness, and interpretability of non-destructive Fv/Fm monitoring in grape leaves can be substantially improved through multi-source information fusion. Full article

We demonstrate an integrated eight-wavelength high-power laser source on a 4H-silicon carbide (SiC)-based optical integration platform. Eight discrete Fabry–Perot laser diodes emitting at 445 nm, 637 nm, 789 nm, 806 nm, 846 nm, 978 nm, 1316 nm, and 1552 nm are integrated on a single SiC chip, each delivering ≥100 mW continuous-wave output power. A complete fabrication process is developed, including lift-off metallization (Ni/Ti/Pt/Au), surface hydrophilic activation bonding, and multi-step blade dicing to form SiC waveguides with a width of 500 μm and a thickness defined by the ~510 μm dicing depth, matching the output aperture of the multimode laser diodes. The resulting waveguides exhibit a facet misorientation of <1° and an approximate facet mean surface roughness of ~2 nm. The laser diodes are directly butted against the waveguide facets for edge coupling, and fixed using In₅₂Sn₄₈ solder bonding with pulse temperature control. Under controlled temperature, all eight channels operate stably with measured peak wavelengths matching the design targets. This work provides a scalable and practical solution for multi-wavelength, high-power on-chip light source integration on the SiC platform, addressing critical thermal and integration challenges for dense wavelength division multiplexing. Full article

A unified transient deterministic lubrication model is developed for the analysis of rough, starved, and coated contacts within a single, fully-coupled numerical framework capable of resolving boundary, mixed, and full-film lubrication regimes. The model is formulated with the finite volume method on a curvilinear grid and extends conventional full-film formulations through the introduction of a semi-system methodology, enabling robust treatment of complex multi-regime conditions. A key distinguishing feature of the framework is the direct resolution of thermal effects within both the lubricant and solid domains through solution of the energy equation. Unlike many existing mixed lubrication models that rely on analytical temperature approximations, the present approach captures transient, asperity-scale temperature evolution explicitly, allowing accurate representation of local thermo-mechanical interactions. Two case studies are presented to demonstrate the capabilities of the model. The first examines transient starvation in rough contacts with isotropic sinusoidal topographies of varying wavelength, as well as random machined surfaces, revealing a strong dependence of lubricant entrainment, asperity interaction, and localised heating on surface morphology. The second study investigates the role of coating thermal properties under transient starved conditions, demonstrating strong coupling between heat transport, viscosity variations, and frictional response. Overall, the proposed framework provides a robust and physically consistent platform for the simulation of transient lubrication phenomena under realistic operating conditions, enabling detailed insight into roughness, starvation, and thermal effects across regimes using a fully-coupled approach. Full article

To address the challenge of simultaneously achieving broadband absorption, multi-mechanism tunability, and angular stability in terahertz multifunctional devices, this paper proposes a MoS₂/VO₂ composite terahertz metamaterial absorber based on an asymmetric multi-nested C-shaped structure. The device adopts a three-layer configuration consisting of a MoS₂/VO₂ composite plane–SiO₂ dielectric–Au reflector layer. Unlike conventional symmetric structures, which are limited by selection rules and symmetry-protected dark modes that hinder the excitation of higher-order resonances, this design effectively breaks structural symmetry protection through geometric asymmetry. This induces strong mode hybridization between originally orthogonal dark and bright modes, enabling broadband high absorption exceeding 96.7% across the 1.88–3.52 THz frequency range (61% RBW). Notably, the device demonstrates synergistic tuning advantages: the macroscopic on/off switching of broadband absorption characteristics via the phase transition of VO₂, combined with fine blind-spot compensation and enhancement in absorption peaks using the electrical tunability of MoS₂. Furthermore, thanks to its sub-wavelength unit cell design, the structure maintains excellent performance stability over a wide incident angle range from 0° to 60°. This study reveals a synergistic enhancement mechanism combining the asymmetric unit cell and hybrid materials, providing a systematic physical solution for resolving the trade-off between bandwidth extension and dynamic reconfigurability. Full article

Agricultural production faces increasing pressure to improve efficiency while reducing chemical inputs and environmental impacts. Laser-based technologies have attracted attention because their wavelength, energy input, exposure duration, and spatial delivery can be adjusted for different biological targets and operational purposes. This review provides a stage-oriented synthesis of laser-based biostimulation, optical sensing, and targeted physical control across crop production and postharvest stages, including seed treatment and seedling establishment, field growth management, ripening and quality assessment, and postharvest preservation. Rather than treating laser-based technologies as a single uniform approach, this review focuses on technical functions, key operating parameters, possible interaction mechanisms, and evidence levels. Particular attention is given to how wavelength, power density, delivered energy dose or fluence, spot size, and exposure duration affect biological responses, sensing performance, and physical treatment efficacy. Current evidence indicates that many applications remain limited to laboratory studies, controlled-environment tests, field demonstrations, or engineering prototypes. Major challenges include parameter standardization, mechanistic validation, environmental robustness, model transferability, crop or product safety, equipment cost, and system integration. Future research should emphasize mechanism-informed dose–response assessment, adaptive sensing and control, multi-source data fusion, product-specific validation, and techno-economic evaluation. Full article

The intelligent transportation systems (ITS), including autonomous driving technologies, have increased the need for a capable communication system. The optical domain offers a promising spectrum for supporting multi-connection and high-data-rate applications. This paper proposes a dynamic resource allocation algorithm for vehicle-to-vehicle (V2V) 6G visible light communication (VLC) systems. A wavelength division multiple access (WDMA) method is utilized as a technique for supporting multiple connections. Two optimization objectives of the resource allocation are evaluated, which are referred to as Max SNR and Max spectral efficiency (SE) objectives. The best resource assignment for each vehicle is obtained by using the optimized resource allocation model. Five scenarios are examined where vehicles are moved in this work. The Max SE objective shows a fair allocation of resources based on the SNR compared to the Max SNR objective. In addition, a dynamic algorithm is developed for real-time solutions. The proposed dynamic algorithm can provide suboptimal resource allocation at 0.001 s, whereas the Max SE MILP model provides the optimal resource allocation in around 1 min. Thus, the proposed dynamic scheme can be used in real-time applications. Full article

Microplastic monitoring needs methods that operate directly in water with minimal sample handling. Conventional techniques such as infrared and Raman spectroscopy and pyrolysis–GC/MS provide polymer-specific information but require sample preparation and delayed laboratory analysis. We propose an optical sensor concept for real-time, in situ microplastic assessment, based on multispectral pulsed transmission in the visible range using synchronized laser-diode lines and the directly transmitted signal through an active sensor volume. After calibration on particle-free water, each particle event reduces to a water-normalized transmission whose deficit is set by geometrical beam–particle overlap and the wavelength-dependent extinction efficiency. The weak polymer absorption is represented by the Urbach-tail formalism, the refractive-index-related redirection of light by a Fresnel-based, surface- and orientation-averaged probability of direct transmission, and particle size and shape are decoupled through an effective optical length. The coupled nonlinear system is solved for the bounds of the polymer absorption coefficient per candidate geometry. Because each polymer occupies a bounded region in multi-wavelength absorption space fixed by its band gap and structural state, the method can, in principle, separate structural modifications of identical composition, such as low- and high-density polyethylene. This is a sensor concept with a model-based proof of concept, not full environmental validation. Experimental verification on real reference particles is reported separately; the present article establishes the measurement model and inversion scheme that this verification builds on. Full article

Indoor fire smoke degrades visible-light cameras and near-infrared Lidar through wavelength-dependent absorption and scattering, threatening robotic navigation safety. Existing path planners either ignore sensor degradation or rely on empirical penalties lacking a physical basis. To address these issues, this paper proposes Quality Cost A* (QC-A*), which maps Fire Dynamics Simulator (FDS) visibility fields to sensor perception quality via the Koschmieder and Beer–Lambert physical laws, embedding a cost function that drives paths away from high-attenuation regions. A multi-sensor fusion layer provides fault tolerance under sensor-specific failure conditions. The method is validated through FDS-based simulations across four smoke scenarios in a $20\mathrm{m}\times 6\mathrm{m}$ corridor with 21 obstacles, using 50 start–goal pairs per scenario. Perception quality derives from Beer–Lambert optical transmittance, while the hazard-zone proportion quantifies path segments with visibility below 5 m. Across the Symmetric and Asymmetric scenarios, QC-A* reduces the low-visibility hazard-zone proportion from 40.7% to 19.6% and improves worst-case perception quality from 0.067 to 0.177, with a 15.3% path length increase, while remaining close to traditional A* in light-smoke conditions. Under constructed sensor failure tests, QC-A* maintains a 96–100% planning success rate versus 48% for Camera-Only and 70% for Lidar-Only. QC-A* shifts sensor degradation modeling from empirical penalty to physical mechanism, achieving a favorable safety–efficiency balance prioritizing perceptual safety, and provides an interpretable, generalizable framework for robotic fire-environment path planning. Full article

The [O ii] $\lambda 3727$ emission line is a widely used star formation rate (SFR) tracer. However, its application to type I quasars is not straightforward, because the line can be affected by dust extinction, metallicity and contamination from the AGN narrow-line region (NLR). We test the reliability of [O ii] SFRs using a sample of 202 SDSS and PG quasars, by comparing [O ii] SFRs and reference far-infrared (FIR) SFRs derived from multiwavelength SED decomposition. We measure [O ii], [O iii], and narrow Balmer emission lines by spectral fitting. Then, we calculate [O ii] SFRs after correcting dust extinction and metallicity. We then compare these SFRs with the FIR SFRs, both with and without subtracting the AGN contribution estimated from [O iii]. After this correction, the median offset between [O ii] and FIR SFRs is $-0.20\pm 0.72$ dex for the full analysis sample and $-0.17\pm 0.69$ dex for sources with S/N $>5$ in both [O ii] and [O iii]. Without subtracting the AGN contribution, the corresponding offsets are $0.00\pm 0.69$ and $0.12\pm 0.66$ dex. We conclude that [O ii] is useful as a statistical SFR tracer for quasar host galaxies, but individual objects still require careful treatment of AGN contamination, extinction, metallicity, aperture effects, and redshift-dependent systematics. Full article

Reliable star formation rates (SFRs) are essential for studying the connection between black hole growth and quasar host galaxies. We study the far-infrared (FIR) SFRs and the host galaxy properties of 202 SDSS and PG quasars at $0.02<z\lesssim 0.8$, spanning $log({\mathrm{SFR}}_{\mathrm{FIR}}/M_{\odot }{\mathrm{yr}}^{-1})\simeq -0.45$–$2.76$, using multiwavelength spectral energy distribution (SED) decomposition. The photometry covers wavelengths from the optical to the FIR and is supplemented by JCMT/SCUBA-2 observations at 450 and 850 $\mathsf{\mu }$m. We model the SEDs with CIGALE and AGNfitter and adopt multiple cold dust templates to quantify systematic uncertainties. The median model-dependent scatter among the five FIR SFR estimates is $0.14$ dex, and AGNfitter gives FIR SFRs lower than the mean CIGALE estimate by a median of $0.09$ dex. For the 58 quasars with SCUBA-2 coverage, including SCUBA-2 data changes the adopted FIR SFR by only ∼0.01 dex on average but can affect individual sources with limited Herschel coverage or radio-loud emission. Within our FIR-constrained sample, many quasar hosts lie on or above the star-forming main sequence, but the redshift-dependent FIR selection of the SDSS subsample limits conclusions about the full quasar-host population. We find no clear correlation between the main-sequence (MS) offset and the direct Eddington ratio, while the offset is positively related to the infrared-based $L_{\mathrm{tor}}/L_{\mathrm{Edd}}$ proxy. The minimum radiation field intensity in the dust model, $U_{\min }$, increases with bolometric luminosity and dust temperature. WISE W2 (4.6 $\mathsf{\mu }$m) and W3 (12 $\mathsf{\mu }$m) combined with Herschel bands can also provide useful empirical indicators of $f_{\mathrm{AGN}}$. Full article