Search Results (391)

This study presents a comparative performance analysis of three sensor technologies—microphone, magnetic pickup, and laser Doppler vibrometer—for capturing string vibration under varied excitation conditions: striking, plectrum plucking, and wire plucking. Two different magnetic pickups are included in the comparison. Measurements were taken at multiple excitation levels on a simplified electric guitar mounted on a stable platform with repeatable excitation mechanisms. The analysis focuses on each sensor’s capacity to resolve fine-scale waveform features during the initial attack while also taking into account its capability to measure general changes in instrument dynamics and timbre. We evaluate their ability to distinguish vibro-acoustic phenomena resulting from changes in excitation method and strength as well as measurement location. Our findings highlight the significant influence of sensor choice on observable string vibration. While the microphone captures the overall radiated sound, it lacks the required spatial selectivity and offers poor SNR performance 34 dB lower then other methods. Magnetic pickups enable precise string-specific measurements, offering a compelling balance of accuracy and cost-effectiveness. Results show that their low-pass frequency characteristic limits temporal fidelity and must be accounted for when analysing general sound timbre. Laser Doppler vibrometers provide superior micro-temporal fidelity, which can have critical implications for physical modeling, instrument design, and advanced audio signal processing, but have severe practical limitations. Critically, we demonstrate that the required optical target, even when weighing as little as 0.1% of the string’s mass, alters the string’s vibratory characteristics by influencing RMS energy and spectral content. Full article

Accurate determination of opacity is critical for understanding radiation transport in both astrophysical and laboratory plasmas. We employ atomic data from R-Matrix calculations to investigate radiative properties in high-energy-density (HED) plasma sources, focusing on opacity variations under extreme plasma conditions. Specifically, we analyze environments such as the base of the convective zone (BCZ) of the Sun ($2\times {10}^6$ K, $N_e={10}^{23}$/cc), and radiative opacity data collected using the inertial confinement fusion (ICF) devices at the Sandia Z facility ($2.11\times {10}^6$ K, $N_e=3.16\times {10}^{22}$/cc) and the Lawrence Livermore National Laboratory National Ignition Facility. We calculate Rosseland Mean Opacities (RMO) within a range of temperatures and densities and analyze how they vary under different plasma conditions. A significant factor influencing opacity in these environments is line and resonance broadening due to plasma effects. Both radiative and collisional broadening modify line shapes, impacting the absorption and emission profiles that determine the RMO. In this study, we specifically focus on electron collisional and Stark ion microfield broadening effects, which play a dominant role in HED plasmas. We assume a Lorentzian profile factor to model combined broadening and investigate its impact on spectral line shapes, resonance behavior, and overall opacity values. Our results are relevant to astrophysical models, particularly in the context of the solar opacity problem, and provide insights into discrepancies between theoretical calculations and experimental measurements. In addition, we investigate the equation-of-state (EOS) and its impact on opacities. In particular, we examine the “chemical picture” Mihalas–Hummer–Däppen EOS with respect to level populations of excited levels included in the extensive R-matrix calculations. This study should contribute to improving opacity models of HED sources such as stellar interiors and laboratory plasma experiments. Full article

Space-based infrared (IR) detection, with wide coverage, all-time operation, and stealth, is crucial for aerial target surveillance. Under low signal-to-noise ratio (SNR) conditions, however, its small target size, limited features, and strong clutters often lead to missed detections and false alarms, reducing stability and real-time performance. To overcome these issues of energy-integration imaging in perceiving dim targets, this paper proposes a biomimetic vision-inspired Infrared Temporal Differential Detection (ITDD) method. The ITDD method generates sparse event streams by triggering pixel-level radiation variations and establishes an irradiance-based sensitivity model with optimized threshold voltage, spectral bands, and optical aperture parameters. IR sequences are converted into differential event streams with inherent noise, upon which a lightweight multi-modal fusion detection network is developed. Simulation experiments demonstrate that ITDD reduces data volume by three orders of magnitude and improves the SNR by 4.21 times. On the SITP-QLEF dataset, the network achieves a detection rate of 99.31%, and a false alarm rate of $1.97\times {10}^{-5}$, confirming its effectiveness and application potential under complex backgrounds. As the current findings are based on simulated data, future work will focus on building an ITDD demonstration system to validate the approach with real-world IR measurements. Full article

Ultraviolet radiation (UVR) is a well-established risk factor for ocular diseases; however, the ultraviolet-blocking properties of daily disposable contact lenses remain insufficiently characterized. This study evaluated thirteen commercially available lenses to determine their spectral transmittance across UV-B, UV-A, and visible light ranges using a UV–visible spectrophotometer. The oxygen permeability, central thickness, water content, and FDA material classification of each lens were documented, and oxygen transmissibility was subsequently calculated. A generalized linear mixed model (GLMM) was applied to identify predictors of spectral transmittance. All lenses demonstrated high visible light transmittance (>88%), but exhibited substantial variation in UV attenuation. While several lenses effectively blocked most UV radiation, others transmitted more than 70%. The analysis revealed that lens power was the most consistent predictor of spectral transmittance, with higher minus powers associated with reduced UV-blocking efficacy. Moisture content and material classification also influenced UV protection but had minimal effect on visible light transmission. In conclusion, daily disposable contact lenses vary considerably in their UV-blocking capabilities, and although lens power cannot be altered, consideration of material composition and UV transmittance properties may assist in selecting lenses that provide optimal ocular protection. Full article

Low-carbon chemical fires pose significant hazards, and remote sensing of high-temperature gas emissions from these fires is a critical method for identifying and assessing their environmental impact. Analyzing the spectral characteristics of gases produced by low-carbon chemical pool fires and developing spectral radiation models can establish a foundation for remote pollution monitoring. However, such studies remain scarce. Using a custom-built high-temperature gas spectroscopy platform, this study extracts spectral features of gases emitted by low-carbon chemical pool fires. We investigate spectral interference mechanisms among combustion products and develop a high-precision spectral radiation model to support remote fire pollution monitoring. Experimental results reveal distinct spectral bands for key gases: CO₂ peaks near 2.7 μm and 4.35 μm, SO₂ at 4.05 μm, 7.5 μm, and 9.0 μm, NO at 5.5 μm, and NO₂ at 3.6 μm and 6.3 μm. The proposed spectral radiation model accurately simulates the position and shape of spectral peaks. For carbon disulfide and acetonitrile combustion products, the model achieves prediction accuracies of 83.4–96.9% and 79.2–95.3%, respectively. Full article

Unmanned aerial vehicle (UAV) hyperspectral remote sensing imaging systems have demonstrated significant potential for water quality monitoring. However, accurately obtaining water-leaving reflectance from UAV imagery remains challenging due to complex atmospheric radiation transmission above water bodies. This study proposes a method for water-leaving reflectance inversion based on air–ground collaborative correction. A fully connected neural network model was developed using TensorFlow Keras to establish a non-linear mapping between UAV hyperspectral reflectance and the measured near-water and water-leaving reflectance from ground-based spectral. This approach addresses the limitations of traditional linear correction methods by enabling spatiotemporal synchronization correction of UAV remote sensing images with ground observations, thereby minimizing atmospheric interference and sensor differences on signal transmission. The retrieved water-leaving reflectance closely matched measured data within the 450–900 nm band, with the average spectral angle mapping reduced from 0.5433 to 0.1070 compared to existing techniques. Moreover, the water quality parameter inversion models for turbidity, color, total nitrogen, and total phosphorus achieved high determination coefficients (R² = 0.94, 0.93, 0.88, and 0.85, respectively). The spatial distribution maps of water quality parameters were consistent with in situ measurements. Overall, this UAV hyperspectral remote sensing method, enhanced by air–ground collaborative correction, offers a reliable approach for UAV hyperspectral water quality remote sensing and promotes the advancement of stereoscopic water environment monitoring. Full article

Operating range is an important indicator for determining the detection capability of an infrared search and track (IRST) system. To address the deficiencies of a traditional range model, such as excessive parameters and calculations, a noise-equivalent temperature difference (NETD)-based range optimization model for staring IRST systems is derived, offering a new solution method. Compared with traditional range models, the proposed model uses fewer parameters, fully considers the spectral radiation characteristics of the object and background and separately fits the integral part into a function related only to the range, which simplifies calculation and improves accuracy. The proposed operating range model is applied to a flying object for sample calculation, and the accuracy of the model is verified by field experiments. Full article

Lithium fluoride (LiF) crystals are widely employed both as optical windows transparent in the ultraviolet spectral region and as efficient personal dosimeters, with their application scope recently expanding into lithium-ion technologies. Moreover, as an alkali halide crystal (AHC), LiF serves as a model system for studying and simulating radiation effects in solids. This work identifies radiation-induced defects formed in lithium fluoride upon irradiation with swift heavy ion beams (N, O, Kr, U) and intense pulsed electron beams, investigates their thermal stability, and performs computer modeling of annealing processes. The theoretical analysis of existing experimental kinetics for $F$-centers induced by electron and heavy ion irradiation reveals considerable differences in the activation energies for interstitial migration. A strong correlation between the activation energy $E_a$ and the pre-exponential factor $X$($E_a$) is observed; notably, $X$($E_a$) is no longer constant but closely matches the potential function Ea. Indeed, with increasing irradiation dose, both the migration energy $E_a$ and pre-exponential factor $X$ decrease simultaneously, leading to an effective increase in the defect diffusion rate. Full article

The high-redshift blazars are important cosmological probes for exploring the early universe and unraveling the fundamental emission processes and the structure of the active galactic nuclei. The high-energy GeV gamma-ray emissions of 38 high-redshift blazars (z > 2.5) observed by Fermi-LAT were analyzed. Along with the Archive multiwavelength data, we employ one-zone leptonic external Compton (EC) models to reproduce the spectral energy distributions (SEDs) of 38 sources. Both the external photons from the molecular torus (MT) and the broad-line region (BLR) are considered. We obtained the best-fitting parameters for describing the characteristics of the jets and accretion disks. The results indicate that high-redshift blazars exhibit higher $\gamma$-ray luminosities, energy densities, jet powers, kinetic powers, accretion disk luminosities, black hole (BH) masses, radiation efficiencies, and mass accretion rates compared to low-redshift blazars. For high-redshift blazars, the influence of the accretion rate on jet power appears to weaken, and in most cases, the jet power exceeds the total accretion power. We speculate that for high-redshift blazars, rapid accretion may lead to magnetic field saturation, thereby reducing the effectiveness of the Blandford–Payne (BP) process. Consequently, the Blandford–Znajek (BZ) process is likely to play a more dominant role in powering jets in high-redshift blazars compared to low-redshift blazars. Naturally, we acknowledge that selection effects cannot be fully eliminated. Full article

To enhance the field calibration capability of ground-based lunar observation instruments for long-term continuous monitoring and to optimize the stability and traceability of lunar observation data, this manuscript presents the development of a SI traceable Portable Self-calibrating Absolute Radiation Source (PSARS) based on an electrical substitute radiometer. A self-calibrating radiation transfer model has been established. The system features a “+” structure layout centered around an integrating sphere, which ensures uniformity of the light source while improving system integration. Preliminary performance testing results indicate that PSARS achieves excellent radiative planar uniformity and angular uniformity within the targeted area, both exceeding 99%. During the self-calibration cycle of PSARS, the detector demonstrates high measurement stability for the built-in light source. Ultimately, through comparative validation and uncertainty assessment, the self-calibration accuracy of spectral irradiance for PSARS in the 400–1000 nm wavelength range is better than 2%, meeting the demands for high-frequency, high-stability, and high-precision real-time on-site radiometric calibration under ground-based lunar observation field test conditions. This provides technical support for the construction of high-precision lunar models and the widespread application of lunar calibration technologies. Full article

Monitoring and accurately forecasting ultraviolet (UV) radiation is of great importance especially due to its adverse effects on human health. In this study, we develop a numerical model to estimate the UV surface solar radiation with the overarching goal of providing a fully automated UV forecasting tool in the region of Epirus, Greece, and especially at the city of Ioannina. The UV surface solar radiation (SSR) is estimated based on detailed radiative transfer (RT) calculations. To ensure their accuracy, we employ the well-established UVSPEC model included in the libRadtran RT routines. LibRadtran provides a variety of options to set up and modify an atmosphere with molecules, aerosol particles, water and ice clouds and a surface as the lower boundary. As a first step, we performed a sensitivity study of the surface solar UV radiation with respect to ozone, precipitable water, aerosol optical properties and surface albedo. Our calculations are performed initially under clear-sky conditions to eliminate the uncertainties induced by clouds. All our calculations are performed spectrally within the UV spectral range, for a specific date and time at Ioannina, Epirus. Full article

This study investigates the non-equilibrium radiation characteristics during the high-speed re-entry of a lunar-return-type capsule under rarefied atmospheric conditions. A line-by-line spectral model was developed to compute atomic emission and absorption coefficients for excited nitrogen and oxygen atoms. Coupled with the Direct Simulation Monte Carlo (DSMC) method, the Photon Monte Carlo (PMC) method was employed to solve the radiative energy transport equation. The model was validated against the FIRE II flight experiment at 1631 s and 1634 s, showing improved agreement with experimental heat flux data compared to previous numerical results. A detailed sensitivity analysis was conducted to examine the influence of spectral discretization and the number of emitted photons per computational cell. Results indicate that low spectral resolution can cause non-physical fluctuations in wall heat flux, while increasing the number of photons improves local smoothness. Optimal parameters were identified as 50,000 spectral points and 5000 photons per cell. The model was further applied to a lunar-return-type capsule re-ntering at 90 km and 95 km altitudes. It was found that radiative heating is spatially decoupled from aerodynamic heating and primarily governed by excited species concentration and line-of-sight geometry. At 90 km, radiative heating accounted for over $15.31\%$ of the aerodynamic heating, more than double that at 95 km. These results underscore the necessity of considering radiation effects in the design of thermal protection systems, particularly at high re-entry velocities and large angles of attack. Full article

To model the response of neural networks to electromagnetic radiation in real-world environments, this study proposes a memristive dual-wing fractional-order Hopfield neural network (MDW-FOMHNN) model, utilizing a fractional-order memristor to simulate neuronal responses to electromagnetic radiation, thereby achieving complex chaotic dynamics. Analysis reveals that within specific ranges of the coupling strength, the MDW-FOMHNN lacks equilibrium points and exhibits hidden chaotic attractors. Numerical solutions are obtained using the Adomian Decomposition Method (ADM), and the system’s chaotic behavior is confirmed through Lyapunov exponent spectra, bifurcation diagrams, phase portraits, and time series. The study further demonstrates that the coupling strength and fractional order significantly modulate attractor morphologies, revealing diverse attractor structures and their coexistence. The complexity of the MDW-FOMHNN output sequence is quantified using spectral entropy, highlighting the system’s potential for applications in cryptography and related fields. Based on the polynomial form derived from ADM, a field programmable gate array (FPGA) implementation scheme is developed, and the expected chaotic attractors are successfully generated on an oscilloscope, thereby validating the consistency between theoretical analysis and numerical simulations. Finally, to link theory with practice, a simple and efficient MDW-FOMHNN-based encryption/decryption scheme is presented. Full article

This study presents a semi-empirical approach to generalizing the acoustic radiation generated by serrated airfoil configurations, based on small-scale aerodynamic/acoustic experiments and functional regression techniques. In the context of passive noise reduction strategies, such as leading-edge and trailing-edge serrations, acoustic measurements are performed in a controlled subsonic wind tunnel environment. Sound pressure level (SPL) spectra and acoustic power metrics are acquired for various geometric configurations and flow conditions. These spectral data are then analyzed using regression-based modeling techniques—linear, quadratic, logarithmic, and exponential forms—to capture the dependence of acoustic emission on key geometric and flow-related variables (e.g., serration amplitude, wavelength, angle of attack), without relying explicitly on predefined nondimensional numbers. The resulting predictive models aim to describe SPL behavior across relevant frequency bands (e.g., broadband or 1/3 octave) and to extrapolate acoustic trends for configurations beyond those tested. The proposed methodology allows for the identification of compact functional relationships between configuration parameters and acoustic output, offering a practical tool for the preliminary design and optimization of low-noise serrated profiles. The findings are intended to support both physical understanding and engineering application, bridging experimental data and parametric acoustic modeling in aerodynamic noise control. Full article

The intensification of the urban thermal environment has brought attention to urban land surface temperature (ULST). Complex building geometry and manmade material lead to significant thermal radiation directionality (TRD) of the urban canopy, and the TRD effect directly influences the accuracy of ULST retrieval algorithms. Therefore, it is essential to understand and eliminate the TRD effect to achieve high-accuracy ULST. In this context, the hemispherical brightness temperature maximum–minimum discrepancy (BTD) was quantitatively analyzed via different spectral bands, component temperature thresholds, urban geometries, and component temperature differences. Meanwhile, the DART simulations database was used to systematically evaluate 1 single-kernel- and 30 dual-kernel-driven models (KDMs), which were combined from 5 base-shape kernels (RossThick, Vinnikov, uea, RossThin, and LSF) and 6 hotspot kernels (RL, Roujean, Vinnikov, LiSparseR, LiDense, and Chen). Results show that the BTD discrepancy (ΔBTD) can reach up to 0.91 K with different band emissivities, whereas the ΔBTD is over 10 K with different component temperature differences. The building density and ratio between building heights and road widths (H/W) also exhibit their importance over urban regions. In addition, the RossThick–/Vinnikov–Roujean dual-kernel KDMs demonstrate better performance with an overall RMSE of 1.12 K. The RL-series KDMs can describe the hotspot distribution well, but the uea-series KDMs outperform at the solar principal plane (SPP) and cross-solar principal plane (CSPP). Specifically, the performance of all KDMs is sensitive to the H/W and component temperature thresholds, and urban geometry can affect the TRD RMSE with increasing H/W and a depletion of high building density. The quantitative TRD analysis and comparison provide a comprehensive reference for understanding the distribution of thermal radiation, which is also a reliable basis for developing the new TRD model over urban regions. Full article