Search Results (4,701)

Exploring public awareness, participation, and emotional inclination toward intangible cultural heritage (ICH) clarifies public attitudes and demands toward traditional culture, providing a crucial basis for targeted ICH protection and inheritance. Based on ICH text big data collected from China’s mainstream social media platform Weibo, this study improves the TF-IDF algorithm, integrates LDA topic analysis for semantic feature mining, and trains a new sentiment analysis model to explore public emotional attitudes and their formation mechanisms. The study is geographically limited to China and covers the entire year of 2023. The results show that: (1) Public ICH perception is multi-dimensional, with close attention to crafts like paper-cutting and traditional Chinese medicine; action-oriented terms reflect dynamic inheritance demands. Public discussions focus on three dimensions: ICH inheritance and development (39%), introduction and promotion (45%), and public experience and participation (16%), with the latter accounting for a low proportion. (2) Public sentiment toward ICH is predominantly positive, with all regions scoring above 0.730 (full score = 1), and Zhejiang (0.751) and Jiangsu (0.750) ranking significantly higher. (3) Spatial econometric analysis reveals marked regional differences in ICH sentiment distribution, mainly affected by three key factors—the number of ICH projects, the number of inheritors, and regional GDP—with regression coefficients of 0.699, 0.632, and 0.458 (p < 0.01). This finding provides a basis for formulating targeted ICH protection strategies. Full article

A nonlinear ultrasonic time-domain identification method based on chaos sensitivity was proposed in this study. The Duffing chaotic system was introduced into the weak second harmonic identification to realize early detection and quantitative evaluation of fatigue damage in U71Mn steel. First, to ensure the reliability of nonlinear ultrasonic testing, a probe-pressure monitoring device was designed. Through pressure-stability experiments, 16 N was determined as the optimal pressure, which effectively suppresses contact nonlinearity interference and ensures coupling stability. Subsequently, the Duffing chaos detection system was established. The signal-system frequency-matching problem was resolved through time-scale transformation. Simultaneously, the issue of unknown initial phases was resolved using phase traversal compensation. Based on the chaotic system’s sensitivity to specific frequency signals and immunity to noise, the amplitudes of the fundamental wave and second harmonics in the target signals were quantified to calculate the nonlinear coefficient. Experimental results demonstrate that the proposed method can extract these amplitudes directly in the time domain, thereby effectively overcoming the spectral leakage inherent in traditional frequency-domain methods. The nonlinear coefficient of U71Mn steel exhibits a “double-peak” characteristic as fatigue damage increases. Specifically, the first peak appears at approximately 50% of fatigue life, while the second occurs at approximately 80%. This phenomenon is closely correlated with the distinct stages of internal fatigue crack propagation, reflecting a complex damage-evolution mechanism. This study not only provides a novel method for the precise extraction of weak nonlinear signals but also establishes a critical theoretical and experimental foundation for accurate fatigue life prediction for U71Mn rail steel. Full article

With the acceleration of the global energy transition, the photovoltaic industry has become a significant force in the promotion of green development, and photovoltaic raw materials play a crucial role in this process. In this paper, 177 countries during the period of 2001 to 2024 were taken as the research subjects, with a focus on polysilicon and silicon wafers as components of upstream photovoltaic raw materials. Through a combination of the evolutionary analysis of nodes, the overall structure, and the three-dimensional structure with an exponential random graph model, the evolution and dynamic mechanisms of the global photovoltaic raw material trade network are explored. The study reveals the following: (1) The global PV raw material trade volume tended to increase from 2001 to 2024. (2) The global photovoltaic raw material trade network showed a tendency towards the “enhanced dominance of core countries and denser trade connections,” with the trade volume between core countries continuously expanding and the network density, average clustering coefficient, and connection efficiency increasing annually, which is a reflection of the globalization and regional cooperation of the global photovoltaic industry. (3) From the weighted out-degree and in-degree ranking evolution of the global photovoltaic raw materials trade network, it can be seen that China consolidated its core position, while Southeast Asian countries tended to transfer their processing and manufacturing links. The status of the United States and traditional industrial powers gradually declined, which is a reflection of the restructuring of the global industrial chain along with regional geopolitical agglomeration effects. (4) Internal attributes such as the national economic level, population size, and urbanization rate, as well as external network effects such as common language and geographical proximity, significantly influence the formation path of the photovoltaic raw material trade network. Moreover, the network exhibits distinct heterogeneous complementarity mechanisms and path dependence characteristics, with a structural evolution that tends toward stability and cooperative relationships showing significant time inertia. Overall, the global trade volume of photovoltaic raw materials continues to grow, and the core positions of major countries such as China, the United States, and Germany remain prominent but show a transitional trend towards Southeast Asian countries. The strengthening of the level of coordination and cooperation among global photovoltaic raw material producers to ensure supply chain stability, promote resource sharing and technological progress, and achieve the sustainable development of green energy policies is necessary. Full article

Ambient fine particulate matter (PM2.5) is associated with increased mortality at concentrations below current regulatory standards. Studies of low-level exposure often rely on large administrative cohorts whose geographic and demographic composition may influence observed associations. In a prior analysis, we observed an association between long-term PM2.5 and all-cause mortality among Native American Medicare beneficiaries living in zip codes within the lowest decile of PM2.5 exposure. The present study, a case–control analysis of 1,713,399 low-PM2.5-exposed beneficiaries enrolled in traditional Medicare during 2015–2016, evaluated whether this association could be explained by geographic context, socioeconomic position (SEP), or baseline health status. We used principal components analysis to summarize area-level SEP indicators and beneficiary-level chronic disease diagnoses. In fully adjusted pooled models, PM2.5 was more strongly associated with mortality among Native American beneficiaries (odds ratio, OR = 1.12 per ug/m³; 95% CI 1.06–1.18) than among non-Native American beneficiaries (OR = 1.01 per ug/m³; 95% CI 1.001–1.02). Sequential adjustment among Native Americans showed that state-level geographic clustering accounted for most attenuation of the PM2.5 coefficient, with additional modest attenuation after adjustment for SEP and chronic disease patterns. These findings suggest that PM2.5–mortality associations observed in low-exposure populations may partly reflect geographic composition and underlying health differences within these large cohorts. Full article

Drought is one of the major disasters constraining crop production. The accurate identification of the dominant environmental factors that drive drought stress at different growth stages of maize is essential for developing stage-specific and precise water management strategies, enhancing drought resistance, and ensuring food security. However, a key challenge is quantifying the nonlinear interactions among multiple environmental factors. This study focuses on the rain-fed agricultural region of Northwest China. To address the limited availability of drought event samples in this region and the inadequacy of traditional statistical methods in capturing complex inter-factor relationships, we integrate a small-sample modeling framework based on an improved Conditional Generative Adversarial Network (CGAN) with an attribution framework that employs SHapley Additive exPlanations (SHAP) for interpretability analysis. We incorporate ten environmental factors derived from multi-source remote sensing: temperature (T_max, T_min, T_mean), precipitation (P), evapotranspiration (ET), soil moisture at 0–10 cm (SM_0–10) and at 10–40 cm (SM_10–40), and solar-induced chlorophyll fluorescence (SIF_max, SIF_min, SIF_mean). Sample sets were established for different maize phenological stages. The CGAN model was employed to achieve high-precision estimation of maize drought severity levels, while the SHAP method was used to quantitatively analyze the dominant factors and their contributions at each phenological stage. The results show that the CGAN model achieved coefficients of determination (R²) of 0.963, 0.972, and 0.979 for the seedling, jointing–tasseling, and maturity stages, respectively, demonstrating excellent nonlinear modeling capability under small samples. SHAP analysis reveals a clear dynamic evolution of dominant factors across phenological stages. Evapotranspiration (ET) dominated in the seedling stage, reflecting the primary role of surface water–heat balance, while the jointing–tasseling stage transitioned to a co-dominance of ET, topsoil moisture (SM_0–10), and minimum SIF, indicating intensified crop transpiration and physiological stress under the meteorological drought framework, and the maturity stage shifted to an absolute dominance centered on mean temperature (T_mean), highlighting the critical impact of heat stress. This study provides a data-driven quantitative perspective for understanding maize drought mechanisms and offers a scientific basis for formulating differentiated drought management strategies for different growth stages. Furthermore, it demonstrates the potential of integrating CGAN with SHAP for agricultural remote sensing and drought attribution research in data-scarce regions. Full article

The stability of underground building foundations in fractured rock masses is a critical concern in geotechnical engineering, particularly for urban projects situated in complex geological settings. In such environments, the interaction between weak planes, groundwater seepage, and in situ stress plays a decisive role in controlling deformation and failure mechanisms. This study presents a novel weak plane–seepage–stress coupling model specifically developed to evaluate the stability of underground excavations and foundation walls under these challenging conditions. Unlike conventional approaches that often assume isotropy or consider isolated factors, the proposed model integrates multiple interacting variables—including weak plane orientation, seepage coefficient, and excavation direction—to systematically assess their combined influence on stress redistribution and failure pressure. A key innovation lies in the quantitative evaluation of the permeability-sealing coefficient, which reflects the effectiveness of waterproofing measures, and its coupling with weak plane characteristics. The results demonstrate that weak planes significantly alter the surrounding stress field, inducing directional instability. The optimal excavation orientation for minimizing instability is identified within the range of 200° to 280°. Moreover, increasing δ from 0 to 1 leads to a substantial reduction in the required supporting pressure, underscoring the critical role of effective sealing and waterproofing in enhancing foundation stability. While the current model is based on a single weak plane assumption and focuses on short-term mechanical responses, it provides a foundational framework for understanding coupled instability mechanisms. Future work will extend the model to incorporate multi-set weak planes, time-dependent degradation, and dynamic excavation processes. This research offers both theoretical insights and practical guidance for optimizing geotechnical design in fractured rock environments, contributing to more resilient and sustainable underground construction. Full article

Some windowless semiconductor photodiodes can detect not only photons but also charged particles, cover a wide spectral range including a part of the ionizing radiation region and, thus, play important roles for synchrotron radiation experiments. To understand the spectral, angular and polarizing properties of semiconductor photodiodes, complex amplitude coefficients of transmittance or reflectance are calculated based on rigorous formulation using Fresnel equations with complex optical constants of the composing materials, whose validity was verified by comparison with experiments. Concrete examples of the behavior on the complex plane are shown as a function of complex optical constants, film thickness, angle of incidence and the wavelength. The results show that the optical properties of the layered system are sensitive to its layer thickness, the angle of incidence and the wavelength in the ultraviolet region where optical indices of the composing materials steeply change. It has been shown that oblique incidence photodiodes are useful as polarization-sensitive devices, and that the graphical technique using the amplitude coefficients expressed on the complex plane is effective and powerful to search for optimal conditions for complex optical constants, film thickness and/or angle of incidence. Full article

Background/Objectives: Endometriosis is a chronic inflammatory disease with a heterogeneous clinical presentation, in which pain represents the predominant symptom. The association between pain severity and intraoperative disease stage remains unclear, particularly with regard to the rASRM and #ENZIAN classifications. This study aimed to evaluate the relationship between pain intensity at different anatomical sites and the stage of endometriosis according to the rASRM and #ENZIAN systems. Methods: A total of 138 patients with advanced endometriosis undergoing surgical treatment between May 2024 and August 2025 were included. Pain intensity was assessed using a 10-point Numerical Rating Scale (NRS) for pelvic pain, pain during defecation, pain during micturition, and pain during or after sexual intercourse. The stage of endometriosis was evaluated intraoperatively according to the rASRM and #ENZIAN classifications. Non-parametric statistical tests and Spearman’s rank correlation coefficient were applied. A p-value < 0.05 was considered statistically significant. Results: No significant correlation was found between overall pelvic pain intensity and disease stage according to the rASRM classification. However, significant differences in pain during micturition were observed depending on rASRM stage (p = 0.004). In the #ENZIAN-based analysis, significant associations were identified between selected anatomical areas and specific pain symptoms, particularly pain during micturition, defecation, and sexual intercourse. Conclusions: Pain severity in advanced endometriosis does not consistently correlate with overall disease stage according to rASRM. The anatomical localization of lesions defined by the #ENZIAN classification may better reflect the type and distribution of pain symptoms. These findings should be interpreted in the context of a selected cohort of surgically treated patients with advanced disease and may not be generalizable to patients with milder or non-surgically managed endometriosis. Full article

This paper develops an intelligent Enhanced Starfish Optimization (ESFO) algorithm for optimizing a secure wireless communication infrastructure. The Starfish Optimization (SFO) algorithm is inspired by starfish biology, using the integrated modeling of the arm-based exploration, preying, and regeneration behaviors of starfish. To further enhance the exploitation capability of the standard Starfish Optimization (SFO), the proposed Enhanced Starfish Optimization (ESFO) integrates a fitness-based interacting mechanism within the exploitation phase. This innovative modification improves local search accuracy, preserves population diversity, and mitigates premature convergence without introducing additional control parameters. Moreover, the proposed Enhanced Starfish Optimization (ESFO) is designed for secure wireless transmission, which is considered one of the main topics in next-generation wireless network infrastructure. The investigated network addresses the use of Simultaneously Transmitting and Reflecting RIS (STAR-RIS) in the security of the physical layer. This implemented STAR-RIS has a coupled phase shift to create reflected and transmission links, unlike traditional Reconfigurable Intelligent Surface (RIS). In this regard, we create a safe beamforming architecture that optimizes both Base Station (BS) precoding vectors and STAR-RIS transmission/reflection coefficients. In order to validate the efficiency of the proposed Enhanced Starfish Optimization (ESFO) algorithm, it is compared to several benchmark optimizers such as standard Starfish Optimization (SFO), Dhole Optimizer (DO), Neural Network Algorithm (NNA), Crocodile Ambush Optimization Algorithm (CAOA), and white shark Optimizer (WSO). These comparisons include several scenarios based on the transmitted power threshold which is varied in the range of 20 to 70 dBm with step of 5 dBm. The simulation results show that the proposed Enhanced Star Fish Optimization (ESFO) algorithm consistently outperforms existing benchmark approaches. This study supports future intelligent communication infrastructures in terms of secrecy and achievable rates over a range of transmit power levels. In particular, ESFO improves performance by up to 20–25% while converging 40–50% faster than traditional optimization algorithms, demonstrating its usefulness and resilience in STAR-RIS-assisted secure communication systems. The suggested ESFO-enabled architecture outperforms standard RIS-based systems in terms of secrecy capacity, according to numerical studies, and low-resolution STAR-RIS phase-shifters are sufficient to ensure robust secrecy performance. Full article

This paper considers design optimization for an active reconfigurable intelligent surface (active RIS)-aided cognitive multigroup multicast communication system. To minimize the sum of the weighted power of the cognitive radio base station (CRBS) and active RIS, the joint design problem of CRBS matrix and active RIS reflection coefficients is discussed, satisfying the constraints of the received signal-to-interference-plus-noise ratio (SINR), the maximum gain constraints of the active RIS, and the interference constraints on the primary users (PUs). Due to the complex coupling and non-convex nature of decision variables in the objective function and constraints, the decision variables were decoupled using the alternate optimization (AO) method, and then methods such as the successive convex approximation (SCA), Schur complement, and penalty convex–concave procedure (PCCP) were utilized to transform the non-convex constraints into tractable convex forms. Finally, an efficient algorithm based on AO for the cognitive multigroup multicast system was proposed, which can reduce total system power consumption by at least 9% compared to a passive RIS (P-RIS). Numerical results identify the system parameter conditions under which the designed system and the proposed algorithm outperform the benchmarks and portray how the system performance is affected by changes to the system parameters. Full article

In this paper, we demonstrate the first sustainable soil moisture sensor based on a fully recyclable antenna. The antenna is fabricated using recyclable liquid metal and biodegradable polylactic acid (PLA), achieving a recycling efficiency of over 98%. The soil moisture is detected through the antenna’s reflection coefficient and the transmission coefficient between the proposed antenna and a receiving horn antenna. The antenna has been recycled and refabricated. The reflection and transmission coefficient of the antenna is read out by a benchtop VNA. The reflection coefficient of the dried antenna has maintained bandwidth before and after the antenna has been recycled. The reflection coefficient of the dried antenna varies within the acceptable bandwidth. The transmission coefficient was continuously readout in a 500 s period; the S21 is significantly changed with the changing of the soil moisture. Full article

The reflectivity of the bare soil surface (BSS) is influenced by soil type, moisture, salinity, tillage, erosion, and other factors. To investigate the direct impact of erosion on the spectral characteristics of the BSS (SCBSS), a study site in the forest-steppe zone (Mtsensk district, Oryol Oblast, Russia), unaffected by salinity, carbonates, gypsum, and other factors, was selected. To suppress the influence of moisture and tillage, a multitemporal soil line (MSL) construction method was selected, which averages the influence of these factors, using the effect of big data. It was possible to reduce the influence of various factors on the SCBSS to two: zonal soil types and the extent of soil degradation from erosion (erosion degree). Soil types and erosion degree were determined by a ground survey with excavation of 488 pits/soil profiles. It was found that the relationship of soil types on the SCBSS has the form of a second-degree polynomial with a determination coefficient of R² = 0.95. Spectral reflectance decreases across the zonal series of soils: sod-podzolic, light gray forest, gray forest, dark gray forest, podzolized chernozem, leached chernozem, typical chernozem, and meadow-chernozem soils. The influence of erosion leads to a linear increase in reflectance for each soil type in the following erosion degree series: non-eroded, slightly eroded, moderately eroded, and strongly eroded. Superimposing two functional relationships yields a distribution in the form of a polynomial ladder. This distribution maintains the general trend of a polynomial decrease in soil reflectance across the zonal series with stepwise deviations at the erosion degree. The polynomial ladder allows us to demonstrate how the erosion degree can change the spectral characteristics of one soil type to those of another. Full article

This paper examines the market maturation hypothesis in cryptocurrency markets through a three-stage analysis of the evolution of tail risk in Bitcoin (BTC) and Ethereum (ETH). Using daily closing prices from January 2015 to February 2026 for BTC (n = 4058) and November 2017 to February 2026 for ETH (n = 3015), we employ 365-day rolling windows—reflecting the continuous 24/7 operation of cryptocurrency markets—to trace the temporal dynamics of Value-at-Risk (VaR), Conditional Value-at-Risk (CVaR), and Maximum Drawdown (MDD). The empirical strategy combines (i) Newey–West trend tests on rolling risk metrics, (ii) regime-conditional analysis across market states (Bull, Bear, or Neutral) and volatility regimes (high/low uncertainty), and (iii) exceedance correlation analysis to capture asymmetric BTC–ETH tail dependence. The results are consistent with the market maturation hypothesis: all ten trend coefficients across both assets are statistically significant (p < 0.001), with linear time trends explaining up to 46.8% (BTC VaR₁%) and 67.5% (ETH VaR₁%) of variation in rolling tail risk. Sub-period comparisons confirm economically meaningful declines—BTC VaR₁% fell by 22.0% and ETH VaR₁% by 26.6% between the early and late subsamples. However, maturation is markedly asymmetric across uncertainty regimes: tail-risk reductions concentrate in low-uncertainty periods, whereas BTC MDD in high-uncertainty regimes shows no significant improvement (+1.0%, p = 0.176). Excess correlation analysis reveals a persistent and widening downside asymmetry (ρ⁻ = 0.847 vs. ρ⁺ = 0.246 at the 90th percentile), with late-period upper-tail correlation turning negative (ρ⁺ = −0.175 at the 95th percentile), implying that portfolio diversification within the cryptocurrency asset class remains illusory during market stress. These findings carry direct implications for institutional risk management, stress-testing frameworks, and prudential regulation of digital assets. Full article

Cr₂O₃-based ceramic coatings are widely used in wear-critical applications; however, their tribological performance under dry sliding conditions can be limited by brittleness and frictional instability. In heavy-duty vehicles, the king pin–bushing contact operates under severe dry sliding conditions, motivating the investigation of composite Cr₂O₃–nTiO₂ coatings as a potential surface engineering solution. In this study, Cr₂O₃–TiO₂ coatings containing 0, 10, 20, 30, and 40 wt% TiO₂ were deposited by atmospheric plasma spraying (APS) from mechanically mixed powders. Phase composition was analyzed by X-ray diffraction using an X’Pert PRO MRD diffractometer, while microstructure and elemental distribution were examined by scanning electron microscopy (SEM) coupled with energy-dispersive X-ray spectroscopy (EDS) on a FEG Quattro C microscope. Mechanical properties were evaluated by Vickers microhardness, instrumented indentation and scratch testing, while dry sliding wear behavior was assessed by pin-on-disc tests performed on a CETR UMT-2 tribometer against a bronze counterbody, with continuous monitoring of the coefficient of friction (COF). The results show that plasma spraying produces lamellar composite coatings with intrinsic porosity and locally modified phase composition. Cr₂O₃-rich coatings exhibit higher hardness (1198 HV2 compared with 877 HV2 for Cr₂O₃–40TiO₂ corresponding to an increase of approximately 36%) and improved resistance to indentation, reflected by lower penetration depths and higher elastic modulus values (134 GPa for S0 compared with 77 GPa for S2). These coatings also exhibit a more stable friction response and reduced material transfer from the bronze counterbody, as confirmed by the lower mass loss of the pins (0.0295 g for S0 compared with 0.0473 g for S4, corresponding to a reduction of about 38%). Increasing TiO₂ content leads to changes in friction stability and wear behavior associated with microstructural heterogeneity. These findings indicate that the sliding wear performance of Cr₂O₃–nTiO₂ coatings is governed by elastic–plastic stability under localized contact loading and support their applicability for dry sliding king pin–bushing systems in heavy-duty vehicles. Full article

This study proposes a high-isolation four-port wideband MIMO antenna array designed for sub-6 GHz 5G, IoT, and radar applications. The array is fabricated on a polycarbonate substrate with overall dimensions of 500 × 500 mm² (ε_r = 2.8, h = 1 mm). Four orthogonally arranged modified circular patches with triangular ground planes and optimized inter-element spacing (D₁ = 90 mm) are employed in the antenna’s design to achieve an impedance bandwidth of 0.7–7.0 GHz (Fractional Bandwidth (FBW) > 163.63%) with |S_ii| < −10 dB across all ports. The measurement results indicate that the inter-port isolation is better than 15 dB (worst-case) across the 0.7–7 GHz band, exceeding 25 dB over 63.5% of the bandwidth (with a peak of approximately 50 dB); the envelope correlation coefficient (ECC) is ultra-low (<0.008); the total active reflection coefficient (TARC) is less than −10 dB for primary multi-port excitations; the mean effective gain (MEG) is balanced (≈−3 dB); and the group delay is consistent (~0.5 ns). With a maximum realized gain of 10 dBi, the antenna exhibits omnidirectional radiation patterns, showing a significant correlation between the simulation (CST Microwave Studio) and measurement results. The proposed antenna is particularly well-suited for use in high-throughput sub-6 GHz 5G base stations and wideband wireless systems, offering superior port isolation through multi-mode resonance without the need for metamaterials and outperforming existing four-port designs. Full article