Search Results (50,267)

The functional performance and structural integrity of natural rock materials under fluctuating environmental stressors are pivotal for their advanced applications. As a non-ionizing and radiation-free technology, terahertz (THz) spectroscopy offers a safe and promising alternative for non-destructive testing (NDT), uniquely capable of being deployed in open and unshielded environments. However, limited penetration depth, exacerbated by both the dense geological matrix and the extreme sensitivity of THz waves to moisture states, has long hindered its widespread application in rock characterization. This study establishes a quantitative Terahertz Time-Domain Spectroscopy (THz-TDS) framework to characterize four lithologies under drying–wetting cycles. Exponential signal attenuation across thicknesses was quantified based on the Beer–Lambert law, with attenuation coefficients ranging from 0.15 to 0.74 per millimeter. Planar transmission imaging successfully visualizes lithologic and moisture-dependent heterogeneity: limestone exhibits a dense, homogeneous structure with stable amplitude distribution; sandstone and purple sandstone show parallel statistical trends, reflecting uniform pore networks; and granite demonstrates the most pronounced imaging contrast under varying moisture states, driven by complex grain-boundary scattering. The findings reveal that THz transmission is dictated by the synergistic effects of mineral compositions and pore structures: scattering at grain boundaries and fractures leads to significant energy dissipation, whereas clay-rich lithologies exhibit the highest sensitivity to moisture variations due to water adsorption and interfacial polarization effects. As an exploration of THz technology in the non-destructive evaluation of rock materials, these findings establish an analytical framework for the quantitative assessment of microstructure evolution. Full article

Snow cover plays an important role in ecological stability and seasonal water regulation in the western Greater Khingan Mountains of Inner Mongolia, a cold-region transitional zone where climate warming may intensify environmental vulnerability and sustainability challenges. Using long-term remote sensing, meteorological, and topographic datasets, this study examined the spatiotemporal changes in snow cover and assessed the relative influences of climatic and geographic factors. The results showed pronounced spatial heterogeneity, with greater snow depth and longer snow cover duration occurring in the northeastern, high-altitude, gentle-slope, and north-facing areas. Snow depth showed a slight but marginally significant declining trend during 1982–2024 at a rate of 0.026 cm a⁻¹, while snow cover days decreased by 0.39 d a⁻¹ during 1982–2020. Snow cover onset exhibited a slight but significant delay, whereas snowmelt timing showed strong interannual variability. Compared with precipitation, temperature showed stronger and more persistent associations with snow cover variations, and climatic factors explained a larger proportion of snow-depth variability than geographic factors. Overall, the results suggest that regional warming has played a leading role in recent snow cover decline. These findings improve understanding of climate-sensitive snow dynamics and provide useful evidence for ecological conservation, seasonal water-resource adaptation, and sustainable regional management in cold-region landscapes of northern China. Full article

The construction of green mines is a core strategy for promoting ecological civilization in China’s mining sector, yet its long-term ecological effects require quantitative assessment. Using a cement-grade limestone mine operated by Linyi Zhonglian Cement Co., Ltd. in Shandong Province as an illustrative case, we employed Landsat 8 OLI/TIRS imagery acquired in 2015, 2020, and 2025 to develop a five-indicator framework for assessing ecological environment quality. The selected indicators comprised greenness (NDVI), wetness, dryness (NDBSI), land surface temperature (LST), and dust concentration (MECDI). These five indicators were subsequently integrated via principal component analysis to generate the Mine Ecological Quality Index (Mine-EQI). Using this index, we applied the Theil–Sen median slope estimator alongside zonal statistics to examine ecological change trajectories across the full study area and three functional zones—the industrial square, haul roads, and active mining area—over the 2015–2025 period. The ecological outcomes attributable to the green mine policy were then quantified. The results show that (1) the mean Mine-EQI of the study area decreased from 0.3713 in 2015 to 0.3460 in 2025, exhibiting a slight overall decline. However, the rate of decline decreased from −6.1% during 2015–2020 to −0.7% during 2020–2025, yielding a Temporal Change Intensity index (TCI) of +88.5%, indicating that the ecological degradation trend has been effectively curbed. (2) Significant spatial heterogeneity was observed. The industrial square showed substantial improvement (Theil–Sen slope = +0.0726), while the haul roads (slope = −0.0705) and mining area (slope = −0.0408) continued to exhibit degradation trends. The improved areas (9.7% of the study area) were spatially coincident with green mine engineering projects. (3) The dust indicator (MECDI) decreased by 24.7% during 2020–2025, and the vegetation index (NDVI) increased by 19.5% over the decade, representing the dominant contributors to ecological improvement. This study reveals that China’s green mine policy has yielded remarkable ecological improvements in relatively stable functional zones such as industrial squares. In contrast, ecological restoration within persistently disturbed areas, including haul roads and mining pits, demands long-term sustained investment and governance. By integrating remote sensing techniques with policy analysis, this research establishes a replicable framework for evaluating progress toward sustainable mining practices. The findings directly support the monitoring of SDG 12 (Responsible Consumption and Production) and SDG 15 (Life on Land), providing a quantitative pathway to balance mineral resource extraction with ecological protection—a core sustainability challenge for resource-dependent regions. Full article

Penetration rate effects and partial drainage can govern piezocone (CPTu) response in intermediate permeability geomaterials, but field testing at a fixed standard rate limits systematic evaluation. This study presents the development and laboratory validation of a miniature piezocone system and testing framework to investigate rate-dependent penetration response in laboratory-prepared silty sand. Baseline dry and flooded specimens were tested using a triaxial-based configuration at penetration velocities of 9.6, 0.28, 0.10, and 0.03 mm/s, including selected holding periods for dissipation. A dedicated servo-controlled penetration system was then implemented for slurry-prepared specimens, enabling continuous constant-velocity penetration over a wider velocity range (0.004–15 mm/s). Cone resistance was interpreted using normalized net resistance (Q) and normalized velocity (V_h), and pore pressure using normalized excess pore pressure (Δu₂/σ′_v0). The results show a monotonic rate dependency, with Q increasing as V_h decreases, while Δu₂/σ′_v0 progressively decreases toward zero at intermediate-to-low V_h; at the lowest rates, pore-pressure readings were affected by instrument signal limitations. A hyperbolic-cosine backbone fitted to the normalized response provided good agreement for resistance (R² = 0.99, RMSE = 3.41) and more limited agreement for pore pressure (R² = 0.30, RMSE = 0.23). The drainage transition for the tested material occurs in an interval of approximately V_h ≈ 0.3~30. The study provides a reproducible laboratory approach—combining miniature instrumentation, controlled specimen preparation, and variable-rate penetration—to generate normalized drainage-transition trends for rate-effect investigations in intermediate geomaterials. Full article

To improve the efficiency of comparative process-window screening in selective laser melting (SLM), this study developed a finite element simulation-driven machine learning framework for 316L stainless steel. A simulation dataset covering laser power (LP), scanning speed (SS), heat-source diameter (HSD), and substrate preheating temperature (SPH) was generated using ANSYS and used to train nine regression models. In the present work, the primary machine learning target was defined as the simulated average thermal stress, σ_avg, which is used as a simulation-derived comparative thermal stress indicator for ranking process conditions within the investigated parameter window rather than as a direct prediction of the final residual-stress field. Among the evaluated models, the Backpropagation Neural Network (BPNN) showed the best predictive performance and was selected as the representative surrogate model because of its strong predictive accuracy, stable behavior, and direct applicability to the present structured tabular dataset. Shapley additive explanations (SHAP) and partial dependence plots (PDPs) indicated that LP is the dominant variable governing the σ_avg-based response, followed by SPH, whereas SS and HSD mainly affect the response through secondary or coupled effects. Within the investigated parameter window, conditions near 180–200 W corresponded to a relatively lower predicted σ_avg level. Experimental observations provided limited but meaningful trend-level support for the simulation-guided screening results: metallographic examination showed improved forming quality near 200 W, while XRD-derived macroscopic stress estimates exhibited a similar variation trend to the simulated σ_avg values under the tested LP–SS conditions. These results suggest that the proposed framework can serve as an efficient surrogate-based tool for comparative parameter screening in SLM-fabricated 316L stainless steel within the assumptions and parameter range of the present model. Full article

Background: Physical inactivity among Saudi Arabian adolescents is a critical public health concern due to its contribution to the rising prevalence of overweight, obesity, and non-communicable diseases. Despite this, the motivational profiles and perceived barriers that differentiate athletic from non-athletic adolescents remain understudied in the Saudi literature, particularly within the school Physical Education (PE) context. Grounded in Self-Determination Theory (SDT), the present study examined the factors preventing and motivating Saudi adolescents to engage in physical activity (PA) and discusses findings in terms of their implications for PE teachers and school-based intervention. Method: A cross-sectional study was conducted with 124 male high school students in Riyadh (mean age: 16.79 ± 0.66 years). Participants were categorized as either athletes (n = 70) or non-athletes (n = 54) based on pre-defined engagement criteria: athletes were required to report vigorous-intensity sport participation on three or more days per week for a minimum of 60 min per session. Anthropometric measurements, lifestyle behaviors (diet, screen time, sleep), motivations, and barriers were assessed using the validated Arab Teens Lifestyle Study (ATLS) questionnaire. Independent samples t-tests and chi-square tests were used to compare between-group differences; effect sizes are reported. Result: Non-athletes had a significantly higher mean BMI (29.40 ± 6.77 kg/m²) and waist circumference (98.65 ± 21.63 cm) compared to athletes (BMI: 22.19 ± 4.44 kg/m²; waist: 78.84 ± 9.51 cm; both p < 0.001). No significant differences were observed in screen time, sleep duration, or dietary habits. The primary motivations for PA among athletes were health benefits (27.1%), recreation (25.7%), and competition (20.0%), reflecting an autonomous motivational profile consistent with SDT. Among non-athletes, the predominant barriers were the lack of suitable facilities (25.9%) and the absence of an exercise partner (22.2%); reflecting unmet SDT needs for competence and relatedness respectively, while only 9.3% cited having a lack of time. Conclusions: Non-athletic participants face a significant health disadvantage characterized by higher rates of overweight and central obesity. In contrast to global trends, where academic commitments dominate barriers to PA, the principal barriers in this population are environmental and social, reflecting unmet psychological needs that PE teachers are uniquely positioned to address. Rather than focusing solely on infrastructure, PE promoters should implement need-supportive teaching practices, including competence-building tasks and cooperative peer structures, to foster the intrinsic motivational profile observed in the athletes and promote long-term PA adherence among non-athletic students, in alignment with the health objectives of Saudi Vision 2030. Full article

Background: Previous research on diet and age-related macular degeneration (AMD) has emphasized primarily particular nutrients or foods, and the influence of comprehensive dietary patterns that represent actual eating behaviors is largely unknown. Objective: The aim of this study was to assess the association between dietary patterns and the odds of AMD. Methods: A case–control study involving 246 participants with AMD and 246 controls are individually matched by age and gender. Dietary patterns were identified through principal component analysis using a validated food frequency questionnaire. Multivariable conditional logistic regression models were applied to examine the association between the extracted dietary patterns and the likelihood of AMD. Results: Three major dietary patterns were found, accounting for 50.59% of the total variance explained. The prudent dietary pattern represented a high intake of vegetables, fruits, soybeans and its products, edible fungi and algae, and nuts were associated with reduced odds ratios (ORs) of the highest tertile compared to the lowest tertile (OR, 0.29, 95% confidence interval [CI], 0.14−0.59, p for trend = 0.001). The estimated likelihood for AMD in the highest tertile of egg and milk dietary pattern intake, which is characterized by a high intake of eggs, milk and dairy products, and refined grains, was 0.40 (95% CI, 0.23−0.67, p for trend <0.001) compared with those in the lowest tertile. No association with AMD was identified for the animal dietary pattern (p > 0.05). Conclusions: Adherence to dietary patterns rich in fruits, vegetables, nuts, refined grains, eggs, milk and dairy products is associated with reduced odds of AMD, emphasizing the potential relevance of dietary habits to visual health among middle-aged and elderly adults. Full article

The modern world is confronting critical environmental and biomedical challenges, underscoring the urgent need for the development of multifunctional materials—an inherently interdisciplinary field, bridging materials science and engineering, environmental science and biomedicine. Titanium dioxide (TiO₂) is widely recognized for its photocatalytic and antiviral properties, enabling the degradation of pollutants and mitigation of viral contamination under solar irradiation. Nevertheless, it exhibits certain limitations, such as wide band gap and high recombination rate of photogenerated electron–hole pairs. To address these limitations, TiO₂ prepared by a co-precipitation method was modified with N-Doped Carbon Dots (N-CDs) via a hydrothermal treatment, which extend light absorption into the visible region and enhance charge separation. Further functionalization with silver nanoparticles (Ag NPs)—well known for their antimicrobial properties—via a simple thermal process under ambient conditions, introduced additional reactive oxygen species generation, creating a synergistic effect. The as-prepared TiO₂, TiO₂/N-CDs and TiO₂/N-CDs/Ag samples were characterized via several techniques, such as XRD, micro-Raman, FT-IR, TEM and UV-Vis. In addition, their photocatalytic and antiviral activity against methylene blue (MB) and nitrogen oxide (NO_x) pollutants, as well as SARS-CoV-2, was evaluated. Based on the results of liquid-phase photocatalysis, TiO₂, TiO₂/N-CDs and TiO₂/N-CDs/Ag presented a degradation efficiency of 78%, 85% and 95%, respectively, whereas different trends were observed under gaseous-phase conditions. The TiO₂/N-CDs/Ag hybrid material demonstrated superior antiviral activity against SARS-CoV-2 (IC₅₀: 1.24 ± 0.34 g/L), compared to both TiO₂ (IC₅₀: 1.78 ± 0.30 g/L) and TiO₂/N-CDs (IC₅₀: >2.5 g/L), highlighting its potential as an effective multifunctional material. Finally, TiO₂/N-CDs/Ag was incorporated onto a paper substrate, demonstrating antiviral activity, showing promising scalability for application across a wide range of future substrates. To the best of our knowledge, this is the first study presenting TiO₂/N-CDs/Ag with dual photocatalytic and antiviral activity. Full article

Sustainable management of peatlands is one of the key global strategies for mitigating climate change. The balance between carbon (C) sequestration and emission in peatlands reflects environmental conditions over time and can provide insight into long-term ecosystem dynamics. However, current methods for estimating greenhouse gas (GHG) fluxes are often labor-intensive, costly, and site-specific. In this study, we propose a simplified and cost-efficient method to estimate long-term carbon balance in peatlands based on the inorganic (mineral) content of drill core samples. The approach uses exponential decay equations to approximate peat accumulation and decomposition processes over time. A conceptual model is applied that accounts for both anaerobic transformation of organic matter of varying molecular complexity and enhanced aerobic decomposition resulting from anthropogenic drainage during the last century. The model was applied to more than 100 drill cores from four peatland systems in Estonia. The resulting trends were compared qualitatively with known climatic fluctuations of the last millennium, including periods associated with the Little Ice Age. The results suggest that, in many cases, carbon losses from decomposition in deeper peat layers may exceed carbon accumulation in upper layers, even in peatlands that appear to be well preserved. The proposed method provides a rapid, low-cost, first-order approximation of peatland carbon dynamics and may serve as a complementary tool for large-scale assessments where detailed process-based models are not feasible. Full article

Soybean (Glycine max) is a vital food and oil crop in China, yet its yield and quality are severely threatened by piercing–sucking damage caused by Riptortus pedestris (Hemiptera: Alydidae) to soybean pods. Under global climate warming and expanded soybean cultivation, temperature has become a key environmental factor driving the spread of and aggravated damage caused by R. pedestris. We investigated the effects of temperature (32, 36, 40, 42, and 44 °C) and exposure duration (1–4 h) on the energy substances and antioxidant enzyme activities in adult R. pedestris. These two factors also had significant effects on the pest’s energy substances and antioxidant defense. Under short-term high-temperature stress, the water loss rate and fat, total sugar, and glycogen contents increased significantly, while protein content showed a fluctuating upward trend, with distinct sexual differences in these responses; the water loss and energy substance levels within the lethal high-temperature range, around 44 °C, were generally higher than those in the sublethal range (36–42 °C). R. pedestris showed physiological changes consistent with enhanced heat tolerance and adaptability, including water balance regulation, carbohydrate and lipid accumulation, and modulation of protein synthesis and degradation. In the sublethal high-temperature range, antioxidant enzyme activity patterns were altered, and SOD activity was increased; meanwhile, the MDA content also rose, and POD and CAT activities decreased. In the lethal high-temperature range, the overall antioxidant enzyme activities were lower than in the suitable temperature range, with the POD activities and MDA content still rising. These results suggest that the dynamic adjustment of antioxidant enzyme activities may contribute to alleviating oxidative damage and rapid adaptation to temperature-induced oxidative stress in R. pedestris. These findings indicate that R. pedestris possesses physiological plasticity to cope with sublethal heat stress through metabolic reallocation and antioxidant defense activation, but extreme temperatures cause severe physiological disruption. This study provides insights into the thermal biology and heat resistance mechanisms of this pest under climate warming scenarios. Full article

Immersive technologies—such as virtual reality (VR), augmented reality (AR), mixed reality (MR), and extended reality (XR)—are increasingly adopted in cultural heritage settings to support education, public engagement, and digital preservation. This scoping review systematically maps existing research on immersive learning within cultural heritage contexts, identifying major trends, pedagogical approaches, and reported outcomes. Following the PRISMA-ScR framework, nineteen studies were selected from 235 publications published between 2016 and 2025 across four databases: ACM Digital Library, Web of Science, ProQuest, and Scopus. Findings reveal a predominant focus on enhancing learner motivation, engagement, and the perceived authenticity of immersive experiences. However, empirical validation of learning outcomes—particularly regarding sustained knowledge retention, critical reflection, and inclusive participation—remains scarce. Persistent gaps are also evident in accessibility and scalability, alongside ethical concerns related to cultural sensitivity, power asymmetries, and the representation of diverse heritage voices. By foregrounding participatory and co-creation approaches, this review highlights how collaborative design processes can enhance learner engagement and support the sustainable digital preservation of cultural heritage. Full article

Psoriasis, a chronic inflammatory skin disease affecting men and women equally, presents distinct gender-based differences in severity and treatment response. While molecular mechanisms underlying psoriasis are well-studied, sex-specific differences remain largely unexplored. To address this, we conducted a comprehensive analysis of transcriptomic data from lesional psoriasis skin and healthy controls, comparing male and female cohorts. Our findings reveal 2760 overlapping differentially expressed genes (DEGs) between sexes, highlighting shared pathways like IL-17 signaling and Th17 differentiation. However, sex-specific pathways emerged, including male-enriched PI3K-Akt signaling and chemokine receptor activity, and female-enriched glycolysis and AHR-NRF2 pathways. Upstream regulator analysis identified sex-specific drivers, including VEGFA activation and CFTR inhibition in males, and AHR activation and FGF21 inhibition in females. Notably, Regulatory T cells (Tregs) and neutrophil abundance differed by sex, aligning with disease severity trends. These results highlight sex-associated molecular and cellular disparities that may be relevant to understanding differences in disease manifestation and treatment response. As an exploratory, hypothesis-generating transcriptomic analysis, this study lays the groundwork for future experimental and clinical validation of sex-specific mechanisms in psoriasis. Full article

Mechanized harvesting in the industrial tomato sector is currently bottlenecked by excessive mechanical injuries and elevated levels of foreign materials generated during electro-mechanical combine harvesting operations. To combat these limitations, this comprehensive review explores recent breakthroughs in harvester-mounted smart grading systems engineered specifically for complex, open-field conditions. Rather than relying solely on conventional optical inspection, the study examines the transition toward advanced, heterogeneous edge-computing frameworks—incorporating FPGAs and embedded GPUs—deployed within electro-mechanical harvesting platforms. This architectural evolution plays a crucial role in mitigating unpredictable processing delays caused by intense operational vibrations, although achieving absolute real-time stability under extreme field conditions remains an ongoing challenge. To minimize bruising and physical deterioration, our analysis synthesizes findings from multi-scale explicit dynamic finite element simulations, unpacking the underlying microstructural failure modes of the crop. We illustrate how regulating applied forces via soft robotic effectors can help approach a ‘damage-free’ handling threshold, though empirical results vary depending on fruit maturity and dynamic operational speeds. Furthermore, coupling multi-modal sensor fusion with Convolutional Neural Networks (CNNs) shows promising potential for non-destructive internal property evaluation under the vibration, dust, and throughput constraints of electro-mechanical harvesters, pending broader validation across diverse field datasets. Ultimately, by projecting future trends in onboard electro-mechanical harvester separation and advocating for a closer synergy between agronomic practices and machine engineering, this paper delivers a comprehensive blueprint for building next-generation, highly resilient, and gentle sorting machinery. Full article

Industry 4.0 (I4.0) is transforming industrial systems through interconnected, data-driven technologies, raising questions about how these developments affect Occupational Health and Safety (OHS). This study investigates research trends, thematic structures, and knowledge gaps at the intersection of I4.0 and OHS using a multilevel bibliometric framework applied to Scopus records published from 2011 to 2025. The analysis moves from a broad overview of the I4.0 landscape to more focused examinations of specific I4.0–OHS publications, prevention-oriented studies, and emerging-risk research. The results show that OHS has limited visibility in the general I4.0 literature and is more prominent mainly in targeted subsets, where digital sensing, artificial intelligence, machine learning, and immersive technologies drive prevention-focused research. Conversely, emerging risks such as cognitive load, psychosocial stressors, and human–autonomy interaction appear in smaller, more dispersed clusters. Overall, the findings suggest that the relationship between I4.0 and OHS is unevenly developed, with established prevention mechanisms and early-stage conceptualization of new risks. Strengthening this field will require integrating human factors with digital indicators, better characterizing emerging risks, and ensuring that digital transformation supports SDG 8 by fostering safe and healthy working environments. Full article

A thorough understanding of the resistivity response characteristics of ethanol-contaminated soil is of great significance for the development of non-destructive geophysical detection techniques and for supporting contaminated site investigation and assessment. This experimental study aims to systematically investigate the resistivity behavior of ethanol-contaminated sandy soils, with a focus on the coupled mechanisms of multiple factors, including water content, ethanol concentration, particle size distribution, and contamination time. It is hypothesized that water content serves as the dominant factor controlling resistivity, whereas ethanol concentration and contamination time regulate resistivity by altering the physicochemical properties of the pore fluid. Under laboratory conditions, silt, fine sand, and medium sand were selected as the test materials. Resistivity was systematically measured using a Miller Soil Box with increasing water content, Wenner array configuration across varying water contents (3–24%), ethanol concentrations (40–98%), and contamination durations (0–144 h). The experimental results indicate the following: (1) Regardless of the presence of ethanol contamination, the resistivity of sandy soil decreases with increasing water content following a power-law relationship. The decrease is most pronounced at low water contents (3–9%), and gradually stabilizes at higher water contents. The results show that, at a constant water content, resistivity systematically and consistently follows the order: silt > medium sand > fine sand. (2) The influence of ethanol concentration on resistivity is constrained by water content levels, and the overall increase in resistivity is primarily attributed to ion dilution and the obstruction of conductive pathways. (3) Over time, resistivity exhibits a two-stage increasing trend, associated with ethanol volatilization and water loss. Resistivity changes in fine sand samples contaminated with ethanol at concentrations ranging from 75% to 95% follow a two-stage pattern. The initial phase of growth is characterized by a gradual increase over a period of 0–48 h, followed by a more rapid increase during the subsequent phase, which extends from 48 to 144 h. The results show that higher initial ethanol concentrations enhance the sensitivity of resistivity to temporal changes. Comprehensive analysis indicates that the resistivity variation mechanism under multi-factor coupling conditions can be summarized as follows: the water content is the dominant factor in the regulation of the conductive pathways; the particle size distribution determines pore structure and the characteristics of the particle interface; ethanol concentration and contamination time dynamically alter pore fluid properties, collectively regulating the resistivity response. Although the experiments were conducted under controlled laboratory conditions and the results have certain limitations, they provide a preliminary reference for interpreting resistivity responses in relatively homogeneous sandy contaminated sites and offer theoretical support for the application of resistivity methods in contamination identification and dynamic monitoring. Full article