Search Results (1,361)

The strategic balance between strength and electrical conductivity in Al-Mg-Si alloys is a critical challenge that must be overcome to enable their widespread adoption as viable alternatives to copper conductors in power transmission systems. To address this, the present study comprehensively investigates model alloys with Mg/Si ratios ranging from 1.0 to 2.0. A multi-faceted experimental approach was employed, combining tailored thermo-mechanical treatments (solution treatment, cold drawing, and isothermal annealing) with comprehensive microstructural characterization techniques, including electron backscatter diffraction (EBSD) and scanning electron microscopy (SEM). The results elucidate a fundamental competitive mechanism governing property optimization: excess Mg atoms concurrently contribute to solid-solution strengthening via the formation of Cottrell atmospheres around dislocations, while simultaneously enhancing electron scattering, which is detrimental to conductivity. A critical synergy was identified at the Mg/Si ratio of 1.75, which promotes the dense precipitation of fine β″ phase while facilitating extensive recovery of high dislocation density. Furthermore, EBSD analysis confirmed the development of a microstructure comprising 74.1% high-angle grain boundaries alongside a low dislocation density (KAM ≤ 2°). This specific microstructural configuration effectively minimizes electron scattering while providing moderate grain boundary strengthening, thereby synergistically achieving an optimal balance between strength and electrical conductivity. Consequently, this work elucidates the key quantitative relationships and competitive mechanisms among composition (Mg/Si ratio), processing parameters, microstructure evolution, and final properties within the studied Al-xMg-0.5Si alloy system. These findings establish a clear design guideline and provide a fundamental understanding for developing high-performance aluminum-based conductor alloys with tailored Mg/Si ratios. Full article

Methane emissions from rice paddies account for over 11% of global atmospheric CH₄, making water management practices such as Alternate Wetting and Drying (AWD) critical for climate change mitigation. Remote sensing offers an objective approach to monitoring AWD implementation and improving greenhouse gas estimation accuracy. This study investigates the backscattering mechanisms of L-band SAR for inundation/non-inundation classification in paddy fields using full-polarimetric ALOS-2 PALSAR-2 data. Field surveys and satellite observations were conducted in Ryugasaki (Ibaraki) and Sekikawa (Niigata), Japan, collecting 1360 ground samples during the 2024 growing season. Freeman–Durden decomposition was applied, and relationships with plant height and water level were analyzed. The results indicate that plant height strongly influences backscatter, with backscattering contributions from the surface decreasing beyond 70 cm, reducing classification accuracy. Random forest models can classify inundated and non-inundated fields with up to 88% accuracy when plant height is below 70 cm. However, when using this method, it is necessary to know the plant height. Volume scattering proved robust to incidence angle and observation direction, suggesting its potential for phenological monitoring. These findings highlight the effectiveness of L-band SAR for water management monitoring and the need for integrating crop height estimation and regional adaptation to enhance classification performance. Full article

The problem was recently reported that the far-zone electromagnetic momentum of light produced by scattering on a spatially anisotropic random medium can be the same at every azimuthal angle of scattering. Here, we extend the analysis to focus on the possibility of producing a rotationally symmetric spectral degree of coherence (SDOC) generated by scattering by an anisotropic process. The necessary and sufficient conditions for producing such a SDOC in the far zone are derived when a polychromatic electromagnetic plane wave is scattered by an anisotropic Gaussian Schell-model medium. We find that, unlike the generation of a rotationally symmetric momentum flow, it is not enough to simply restrict the structural characteristics of the medium and the incident light source to achieve a SDOC with rotational symmetry. An additional and essential requirement is that the azimuthal angles of scattering corresponding to the two observation points of the SDOC must be constrained to be equal. Only when all these constraints are satisfied simultaneously can a rotationally symmetric electromagnetic SDOC generated by scattering by an anisotropic process be realized. In addition, we find that although the medium parameter conditions for generating a rotationally symmetric SDOC and a rotationally symmetric momentum flow are completely different, it remains possible that the SDOC and the momentum flow produced by a spatially anisotropic medium can still simultaneously exhibit rotational symmetry, provided that the distribution of the correlation function of the scattering potential of the medium is isotropic in the plane perpendicular to the incident direction. Our results not only contribute to a deeper understanding of the far-field distribution of light scattering on an anisotropic scatterer, but also have potential applications in light-field manipulation and in the inverse scattering problem. Full article

Accurate quantification of forest aboveground biomass (AGB) is essential for monitoring terrestrial carbon stocks. While total AGB estimation is widely practiced, resolving component biomass such as canopy, branches, leaves, and trunks enhances the precision of carbon sink assessments and provides critical structural parameters for ecosystem modeling. Most studies rely on a single SAR sensor or a limited range of SAR features, which restricts their ability to represent vegetation structural complexity and reduces biomass estimation accuracy. Here, we propose a phased fusion strategy that integrates backscatter intensity, interferometric coherence, texture measures, and polarimetric decomposition parameters derived from dual-frequency ALOS-2, GF-3, and Sentinel-1A SAR data. These complementary multi-dimensional SAR features are incorporated into a Random Forest model optimized using an Adaptive Genetic Algorithm (RF-AGA) to estimate forest total and component estimation. The results show that the progressive incorporation of coherence and texture features markedly improved model performance, increasing the accuracy of total AGB to R² = 0.88 and canopy biomass to R² = 0.78 under leave-one-out cross-validation. Feature contribution analysis indicates strong complementarity among SAR parameters. Polarimetric decomposition yielded the largest overall contribution, while L-band volume scattering was the primary driver of trunk and canopy estimation. Coherence-enhanced trunk prediction increased R² by 13 percent, and texture improved canopy representation by capturing structural heterogeneity and reducing saturation effects. This study confirms that integrating coherence and texture information within the RF-AGA framework enhances AGB estimation, and that the differential contributions of multi-dimensional SAR parameters across total and component biomass estimation originate from their distinct structural characteristics. The proposed framework provides a robust foundation for regional carbon monitoring and highlights the value of integrating complementary SAR features with ensemble learning to achieve high-precision forest carbon assessment. Full article

Forest canopy near-infrared reflectance and mass-based canopy nitrogen concentration (canopy %N) have been shown to be positively correlated. While the mechanisms underpinning this relationship remain unresolved, the broad range of wavelengths involved points to structural properties that influence scattering and covary with %N. Despite this, efforts that have focused on commonly measured structural properties such as leaf area index (LAI) have failed to identify a causal mechanism. Here, we sought to understand how lidar-derived canopy traits related to additional properties of foliar arrangement and structural complexity modulate the effects of leaf spectra and leaf area index (LAI) on canopy reflectance. We developed a leaf layer spectra model to explore how canopy reflectance would change if complex foliage arrangements were removed, compressing the canopy into optically dense, uniform stacked layers while maintaining the same leaf area index. Model results showed that LAI-weighted leaf reflectance saturates at a leaf area index of approximately two for needleleaf species and four for broadleaf species. When upscaled to estimate plot-level canopy reflectance in the absence of structural complexity (NIRr_LAI), results showed a strong positive relationship with canopy %N (r² = 0.86), despite a negative relationship for individual leaves or “big-leaf” canopies with an LAI of one (NIRrL, r² = 0.78). This result implies that the relationship between canopy near-infrared reflectance and canopy %N results from the integrated effects of canopy complexity acting on differences in leaf-level optical properties. We introduced an index of relative reflectance (IRr) that shows that the relative contribution of structural complexity to canopy near-infrared reflectance (NIRr_C) is related to canopy %N (r² = 0.55), with a three-fold reduction from potential canopy near-infrared reflectance observed in stands with low %N compared to a two-fold reduction in stands with high %N. These findings support the hypothesis that the correlation between canopy %N and canopy reflectance is the result of interactions between leaf traits and canopy structural complexity. Full article

In this study, a hybrid sensor based on a defective square-truncated patch antenna (STPA) and a frequency-selective surface (FSS) was analyzed numerically and experimentally for different glucose–distilled water solutions. Here, an FSS was employed to enhance the sensitivity of the hybrid sensor. The sensing principle relies on monitoring variations in the loss tangent ($tan\delta$) and relative permittivity (${\epsilon }_r$) caused by different glucose concentrations applied to the sample under test (SUT). An open-ended coaxial probe was used to measure the complex permittivity of the solutions, which was then fitted to the Debye relaxation model. The simulated and experimental results of the novel sensor showed good agreement in a glucose concentration monitoring application. The sensor spanned the glucose range from 0 mg/dL to 5000 mg/dL, exhibiting a sensitivity of 55.44 kHz/mgdL⁻¹ and a figure of merit (FOM) of 6.23 × ${10}^{-4}$ (1/mgdL⁻¹) in the experiments and 53.60 kHz/mgdL⁻¹ and 1.71 × ${10}^{-4}$ (1/mgdL⁻¹) FOM in the simulations. When solutions with different concentrations were tested in the SUT, the resonance frequency of the antenna ($f_0$, in GHz) changed. To further characterize the sensor response, the relationship between the glucose concentration (C, in mg/dL) and $f_0$ was examined. A regression-based prediction model was constructed to map the measured scattering parameters to the glucose concentration, yielding a coefficient of determination ($R^2$) of 0.976. The high sensitivity, compact size, and compatibility with planar fabrication suggest that the proposed hybrid sensor has the potential to contribute to the development of non-invasive glucose-monitoring systems. Full article

Saccharomyces cerevisiae was cultured under the influence of static magnetic fields (SMFs) to assess their impact on the biosynthesis of silver nanoparticles (AgNPs). Cell-free media derived from SMF-exposed cultures facilitated the formation of AgNPs, with a significant reduction in nanoparticle size observed at an optimal field strength of 7 mT. AgNPs synthesized under SMF conditions exhibited smaller crystalline structures than those produced in control media, as evidenced by dynamic light scattering (DLS) and transmission electron microscopy (TEM) measurements. Over a 75-day period, SMF-exposed AgNPs demonstrated enhanced stability, as determined by DLS and polydispersity index (PDI) assessments. Further analysis through sodium dodecyl-sulfate polyacrylamide gel electrophoresis (SDS-PAGE) and Fourier transform infrared spectroscopy (FTIR) suggested the formation of a protein corona on the AgNPs in SMF-treated samples, which likely inhibits agglomeration and enhances long-term stability. These findings indicate that SMF-induced stress in S. cerevisiae triggers the secretion of specific proteins that contribute to the stabilization of AgNPs, providing a novel approach to controlling nanoparticle synthesis and stability through magnetic field exposure. Full article

Direct hydroxylation of benzene to phenol using hydrogen peroxide is a cornerstone of sustainable green chemistry. This paper presents the results of a stability study of an iron-containing mordenite catalyst in the liquid-phase hydroxylation of benzene to phenol with a 30% aqueous hydrogen peroxide solution. The study utilizes a combination of catalytic activity measurements, dynamic light scattering (DLS), and electron paramagnetic resonance (EPR) spectra. The system is initially shown to exhibit high phenol selectivity; however, over time, DLS measurements indicate aggregation of the catalyst particles with an increase in the average particle diameter from 1.8 to 2.6 μm and the formation of byproducts–dihydroxybenzenes. Iron is present predominantly as magnetite nanoparticles (Fe₃O₄) ~10 nm in diameter, stabilized on the outer surface of mordenite, with minor leaching (<10%) due to the formation of iron ion complexes with ascorbic acid as a result of the latter’s interaction with magnetite particles. Using a thermodynamic approach based on the Ulich formalism (first and second approximations), it is shown that the reaction of benzene hydroxylation H₂O₂ in the liquid phase is thermodynamically quite favorable (ΔG° = −(289–292) kJ·mol⁻¹ in the range of 293–343 K, K = 1044–1052). It is shown that ascorbic acid acts as a redox mediator (reducing Fe³⁺ to Fe²⁺) and a regulator of the catalytic medium activity. The stability of the catalytic system is examined in terms of the Lyapunov criterion: it is shown that the total Gibbs free energy (including the surface contribution) can be considered as a Lyapunov functional describing the evolution of the system toward a steady state. Ultrasonic (US) treatment of the catalytic system is shown to redisperse aggregated particles and restore its activity. It is established that the catalytic activity is due to nanosized Fe₃O₄ particles, which react with H₂O₂ to form hydroxyl radicals responsible for the selective hydroxylation of benzene to phenol. Full article

To measure temperature and pressure parameters in harsh environments such as those with high temperature and high pressure, a wireless and passive multi-grid Complementary Split-Ring Resonator and substrate integrated waveguide (MG-CSRR-SIW) structure for a temperature and pressure sensor based on microwave scattering principles and high-temperature co-fired ceramic (HTCC) technology is proposed. It can measure temperature within 25–1200 °C and pressure within 0–300 kPa. The structural design of the sensor by using high-frequency electromagnetic simulation software contributes to a linear relationship between the measured parameters and the sensor’s return loss (S11). Furthermore, the performance validation of the proposed sensor is implemented by sensor fabrication and experimentation. The test results show that the proposed sensor exhibits good performance of reliability and linearity. The temperature sensitivity is 199.33 kHz/°C and 379.75 kHz/°C in the temperature ranges of 25–475 °C and 475–1200 °C, respectively. In addition, the pressure sensitivity reaches 235.5 kHz/kPa at 800 °C. The maximum relative measurement error is 2.2% and 1.45% in regard to temperature and pressure, respectively. Full article

This study addresses the limitations of conventional highway visibility monitoring under rain–fog conditions, where fixed stations and visibility sensors provide limited spatial coverage and unstable accuracy. Considering that drivers’ visual fields are jointly affected by global fog and local spray-induced mist, a dynamic visibility recognition and risk assessment framework is proposed using roadside monocular CCTV (Closed-Circuit Television) imagery. The method integrates the Koschmieder scattering model with the dark channel prior to estimate atmospheric transmittance and derives visibility through lane-line calibration. A Monte Carlo-based coupling model simulates local visibility degradation caused by tire spray, while a safety potential field defines the low-visibility risk field force (LVRFF) combining dynamic visibility, relative speed, and collision distance. Results show that this approach achieves over 86% accuracy under heavy rain, effectively captures real-time visibility variations, and that LVRFF exhibits strong sensitivity to visibility degradation, outperforming traditional safety indicators in identifying high-risk zones. By enabling scalable, infrastructure-based visibility monitoring without additional sensing devices, the proposed framework reduces deployment cost and energy consumption while enhancing the long-term operational resilience of highway systems under adverse weather. From a sustainability perspective, the method supports safer, more reliable, and resource-efficient traffic management, contributing to the development of intelligent and sustainable transportation infrastructure. Full article

Within the field of the structural monitoring of bridges, numerous technologies and methodologies have been developed. Among these, methods based on synthetic aperture radar (SAR) which utilise satellite data from missions such as Sentinel-1 (European Space Agency-ESA) and COSMO-SkyMed (Agenzia Spaziale Italiana—ASI) to capture displacements, temperature-related changes, and other geophysical measurements have gained increasing attention. However, SAR has yet to establish its value and potential fully; its broader adoption hinges on consistently demonstrating its robustness through recurrent applications, well-defined use cases, and effective strategies to address its inherent limitations. This study presents a systematic literature review (SLR) conducted in accordance with key stages of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 framework. An initial corpus of 1218 peer-reviewed articles was screened, and a final set of 25 studies was selected for in-depth analysis based on citation impact, keyword recurrence, and thematic relevance from the last five years. The review critically examines SAR-based techniques—including Differential Interferometric SAR (DInSAR), multi-temporal InSAR (MT-InSAR), and Persistent Scatterer Interferometry (PSI), as well as approaches to integrating SAR data with ground-based measurements and complementary digital models. Emphasis is placed on real-world case studies and persistent technical challenges, such as atmospheric artefacts, Line-of-Sight (LOS) geometry constraints, phase noise, ambiguities in displacement interpretation, and the translation of radar-derived deformations into actionable structural insights. The findings underscore SAR’s significant contribution to the structural health monitoring (SHM) of bridges, consistently delivering millimetre-level displacement accuracy and enabling engineering-relevant interpretations. While standalone SAR-based techniques offer wide-area monitoring capabilities, their full potential is realised only when integrated with complementary procedures such as thermal modelling, multi-sensor validation, and structural knowledge. Finally, this document highlights the persistent technical constraints of InSAR in bridge monitoring—including measurement ambiguities, SAR image acquisition limitations, and a lack of standardised, automated workflows—that continue to impede operational adoption but also point toward opportunities for methodological improvement. Full article

This paper proposes JADEGBO, a hybrid gradient-based metaheuristic for solving complex single- and multi-constraint engineering design problems as well as cost-sensitive security optimisation tasks. The method combines Adaptive Differential Evolution with Optional External Archive (JADE), which provides self-adaptive exploration through p-best mutation, an external archive, and success-based parameter learning, with the Gradient-Based Optimiser (GBO), which contributes Newton-inspired gradient search rules and a local escaping operator. In the proposed scheme, JADE is first employed to discover promising regions of the search space, after which GBO performs an intensified local refinement of the best individuals inherited from JADE. The performance of JADEGBO is assessed on the CEC2017 single-objective benchmark suite and compared against a broad set of classical and recent metaheuristics. Statistical indicators, convergence curves, box plots, histograms, sensitivity analyses, and scatter plots show that the hybrid typically attains the best or near-best mean fitness, exhibits low run-to-run variance, and maintains a favourable balance between exploration and exploitation across rotated, shifted, and composite landscapes. To demonstrate practical relevance, JADEGBO is further applied to the following four well-known constrained engineering design problems: welded beam, pressure vessel, speed reducer, and three-bar truss design. The algorithm consistently produces feasible high-quality designs and closely matches or improves upon the best reported results while keeping computation time competitive. Full article

To solve the problems of large deformation and poor welding quality commonly observed during the double-sided welding of Q355 thin plates, this study systematically investigated the effects of single-sided ultrasonic-assisted welding on the weld formation, microstructure, mechanical properties, and residual stresses of the plates, and compared this welding process with conventional ones. Experimental results indicate that ultrasonic assistance is associated with improved weld shape and quality, contributing to a flatter weld surface and more symmetric cross-sectional profile. In contrast to conventional welds, welds produced by single-sided ultrasonic-assisted gas metal arc welding show no obvious oxide inclusions and a reduced tendency for columnar grain growth. In a single tensile test for each welding condition, the measured tensile strength was 552 MPa for conventional welding and 575 MPa for single-sided ultrasonic-assisted gas metal arc welding. These tensile results should be interpreted as indicative trends and require replication to assess scatter and statistical significance. Furthermore, single-sided ultrasonic-assisted gas metal arc welding is associated with lower welding residual stresses, with peak stress values reduced by up to 36.23% along the longitudinal path. This technique provides an engineering reference for improving weld-quality consistency during the double-sided welding of Q355 thin plates without altering the welding specifications. Full article

(1) Purpose: Incoherent processes in production of lepton pairs (dileptons) are studied for the scattering of protons on nuclei. Methods: New quantum mechanical model is constructed on the basis (1) generalization of the nuclear model of emission of photons in the proton-nucleus reactions from low to intermediate energies, (2) formalism of dilepton production. Results: (1) The coherent cross sections of dilepton production in $p+\mathrm{Be}$ at proton beam energy $E_{\mathrm{p}}$ of 2.1 GeV calculated by model are in good agreement with experimental data of DLS Collaboration. (2) Dilepton production for ⁹Be, ¹²C, ¹⁶O, ²⁴Mg, ⁴⁴Ca, ¹⁹⁷Au at $E_{\mathrm{p}}=2.1$ GeV are studied. Coherent cross sections of dilepton production are monotonously decreased with increasing mass of nuclei. (3) At larger $E_{\mathrm{p}}$ dileptons are produced more intensively. (4) Incoherent processes in production of dileptons are studied for p + ⁹Be at E_p = 2.1 GeV. Agreement between experimental data and calculated cross sections is better, in to include incoherent processes to the model. A new phenomenon of suppression of production of dileptons at low energies due to incoherent processes is observed. This is explained by dominant coherent contribution at very low energies. (5) Longitudinal amplitude of virtual photon suppresses the cross section of dilepton production a little (effect is observed for p + ⁹Be at E_p = 2.1 GeV). (6) The contribution from incoherent processes plays a leading role in the dilepton production ((the ratio between the incoherent and coherent terms is 10–100). Also our model provides the tendencies of the full spectrum for p + ⁹³Nb at E_p = 3.5 GeV in good agreement with experimental data obtained by HADES collaboration, and shows large role of incoherent processes. Conclusions: Incoherent processes are much more important than coherent ones in study of dilepton production in this reaction. Full article

This study presents a comparative analysis of the novel guided-wave-based imaging method that integrates variational Bayesian principal component analysis with time-delay strategy for detecting internal and external defects in plate-like structures. The performance of the conventional delay-and-sum imaging method deteriorates when the signal-to-noise ratio of signals is low or when other wave packets overlap with the defect scattering signal. The imaging method based on variational Bayesian principal component analysis analyzes the principal components and corresponding singular values of the time-delayed signal array, and the maximum singular value represents the contribution of the most principal component, serving as an indicator of the coherent defect-related wave packets. Thus, the defect can be highlighted by accounting for the effect of noise and wave packet interference on the time-delayed signal array. However, when defects are located outside the sensor network, the limited information available may reduce the imaging performance. Numerical simulations and experimental studies conducted on plate-like structures demonstrate the proposed method achieves higher imaging clarity and localization accuracy for the internal defect compared with the external defect, with the former exhibiting mm-level absolute localization errors. Full article