Search Results (10,147)

Shallow-buried coal seams in western China are commonly overlain by deeply incised gully terrain, where mining is often accompanied by coal-wall spalling and abnormal increases in support resistance, which affect safe and efficient production. To investigate overburden failure during shallow-buried coal seam mining under gully terrain and to clarify the support–resistance mechanism, a typical working face was selected as the engineering background. Physical similarity simulation, 3DEC numerical simulation, and theoretical analysis were used to analyze overburden failure characteristics and the coupled evolution of the stress, displacement, and fracture fields. Mechanical models of key-stratum fracture and a support–resistance estimation model were established to reveal the influence of overburden-thickness variation on key-stratum fracture and support resistance. The results show that overburden failure in gully areas exhibits pronounced stage-dependent and asymmetric characteristics. In the similarity simulation, the initial fracture intervals of the key stratum in the downhill section were 32 m and 36 m, indicating an asymmetric fracture pattern with a shorter span on the left side and a longer span on the right side. In the uphill section, the periodic fracture interval of the key stratum decreased from 30 m to 24 m as the overburden thickness increased. During overburden failure in gully areas, the three fields exhibited a coupled relationship: stress concentration at the working face caused overburden failure and subsidence, which promoted fracture propagation, whereas stress redistribution in the goaf compacted the fractured overburden and promoted fracture closure. The overburden failure characteristics differed significantly between mining stages. During downhill mining, the key stratum behaved as a fixed-ended beam with a relatively large fracture interval, whereas during uphill mining, it formed a cantilever beam, and its fracture interval decreased with increasing overburden thickness. The loading mechanism of support resistance was shown to be jointly controlled by variations in gully overburden thickness and key-stratum fracture. During downhill mining, support loading increased gradually under the support of the fixed-ended beam key stratum. During uphill mining, support loading exhibited periodic abrupt increases under the combined effects of increasing overburden thickness and periodic fracture of the cantilever-beam key stratum. These findings provide a theoretical basis for strata pressure control at working faces in gully areas. Full article

Rapid and non-contact surface inspection is essential for quality control in modern production. Optical coherence tomography (OCT) can image a surface without contact, but turning those images into roughness parameters usually requires specialized processing software. This study examined whether a multimodal large language model (LLM) could estimate roughness parameters directly from OCT B-scans as a screening tool. The study was designed as a controlled macro-scale proof of concept using periodic, analytically defined phantoms rather than as validation on stochastic industrial micro-roughness. Five test surfaces with exactly known geometries were designed, 3D-printed, and scanned with a spectral-domain OCT system. For each surface, roughness values were computed from the theoretical shape, extracted from the OCT image using MATLAB, and also estimated by the LLM from the same image. The repeatability of the LLM was checked by running the same prompt ten times per surface. On a sawtooth profile, the LLM estimates varied by 3.8% for Ra, 4.2% for Rq, 3.5% for Rp, 2.8% for Rv, and 3.1% for Rt. Across all five surfaces, the variation in Ra and Rq was around 3–5%, and for Rt, it stayed below 5%. The results show that a generative AI approach can produce repeatable roughness estimates that are useful for comparative screening. This method offers a flexible option for surface comparison and AI-assisted quality control when calibrated measurements are not required. Full article

Studying Bingham flows in permeable media under a periodic magnetic field enhances the understanding of yield-stress fluids for applications like oil recovery and filtration. This study combines non-Newtonian behavior with porous-medium resistance and magnetic variations, facilitating the analysis of complex flow phenomena, including oscillatory yielding and improved flow control in porous structures. The viscous potential theory is employed to streamline the mathematical processes. The utilization of linear governing partial differential equations of motion, along with appropriate nonlinear boundary conditions, yields additional simplifications. The investigation yields a nonlinear Mathieu oscillator that governs the interfacial displacement. A non-perturbative method is used to convert this nonlinear ordinary differential equation into a linear equation. A non-dimensional formulation minimizes the fundamental variables required to characterize the system by establishing a collection of dimensionless physical characteristics. The study analyzes a nonlinear Mathieu oscillator with complex coefficients to explore system dynamics related to elevation. By simplifying the variable coefficients, it enhances the examination of stability and resonance behavior. Despite inherent complexities, the work effectively clarifies fundamental concepts, contributing to a more coherent understanding of the subject. The Hartman number, magnetic field, and magnetic permeability ratio exert a destabilizing effect. Conversely, the Bingham parameter, Weber number, and periodic frequency exert a stabilizing influence. Full article

Purpose: To investigate whether the season in which photorefractive keratectomy (PRK) with mitomycin C (MMC) is performed influences postoperative corneal transparency considering seasonal variations in ultraviolet (UV) exposure. Methods: This retrospective study included 100 eyes of 50 patients who underwent MMC-assisted PRK for myopic refractive error. Patients were divided into two groups based on the season of surgery: winter (November–April, low UV exposure) and summer (May–October, high UV exposure). All patients were evaluated preoperatively and at 12 months postoperatively. Corneal transparency was objectively assessed using Scheimpflug-based corneal densitometry obtained with the Pentacam system, focusing on the central (0–2 mm) and paracentral (2–6 mm) zones. Postoperative densitometry values were compared between seasonal groups. Results: Corneal densitometry values showed a significant reduction postoperatively compared with preoperative measurements in both central and paracentral zones. When comparing seasonal groups, no statistically significant differences were observed in postoperative densitometry values between eyes operated on during summer and winter months. No clinically detectable corneal haze was observed in any patient throughout the follow-up period. Conclusions: Surgical season did not significantly influence postoperative corneal densitometry or clinically detectable haze formation after MMC-assisted PRK for low-to-moderate myopia, suggesting that deferral during high-UV months may not be necessary with standard postoperative UV protection. Full article

In complex low-altitude environments, unmanned aerial vehicles (UAVs) require reliable positioning, yet Global Navigation Satellite System (GNSS) signals are vulnerable to occlusion and interference. Pseudolite-augmented cooperative localization, which combines ground base-station signals with inter-UAV relative observations, can complement GNSS in such environments. However, two practical issues remain in real-world deployment: UAV-to-base-station (U-B) and UAV-to-UAV (U-U) observations have markedly different error statistics that a unified noise adjustment cannot handle, and the conservative covariance estimates produced by Covariance Intersection (CI) fusion bias the innovation-based adaptive noise estimation in distributed architectures. To address these issues, this paper proposes a Distributed Group Covariance Compensation Adaptive Kalman Filter (DGCC-AKF) for collaborative enhancement of UAV regional localization. DGCC-AKF establishes a group adaptive mechanism that independently adjusts the noise covariance matrices of U-B and U-U observations, enabling observation-type-level adaptive weighting that suppresses anomalous U-B or U-U measurements at the group level. In addition, a bounded covariance compensation factor is incorporated to alleviate the CI-induced conservatism in the adaptive noise estimation. The proposed method is evaluated on a 2800 km² semi-physical testbed based on the Ground-based High-precision Local Positioning System (GH-LPS) pseudolite network using measured U-B observations and high-dynamic (>300 km/h) flight trajectories collected from a fixed-wing platform across three independent flight sessions. Results demonstrate that under observation fault periods, the proposed method improves 3D positioning accuracy by up to about 75% over single-UAV extended Kalman filter (EKF). Compared with two advanced algorithms in this field, variational Bayesian adaptive Kalman filter (VBAKF) and maximum correntropy criterion Kalman filter (MCC-EKF), it is the only scheme that remains accurate and stable across all UAVs and fault types. The framework provides a practical step toward field deployment for resilient multi-UAV cooperative navigation in pseudolite-augmented GNSS-denied regions. Full article

Fifty-five batik textiles produced along coastal Java in the late 19th to early 20th century were analysed to study the red dyes and the cotton fabrics. Surface-Enhanced Raman Spectroscopy (SERS) classified the dyes into six groups and identified 70% of the samples as Morinda. High-Performance Liquid Chromatography coupled with a diode array detector and tandem Mass Spectrometry (HPLC-DAD-MS/MS) confirmed the SERS results and identified synthetic dyes in the remaining samples, which were used either alone or in mixtures with Morinda or indigo. Synthetic alizarin (C.I. 58000, Mordant Red 11) was the most frequently detected synthetic dye. Auramine O (C.I. 41000, Basic Yellow 2), fuchsin (C.I. 42510, Basic Violet 14), and rhodamine B (C.I. 45170, Basic Violet 10) were occasionally detected. The results also highlighted two possible types of Morinda and two variations of synthetic alizarin. The shades obtained from mixtures of natural and synthetic dyes were visually indistinguishable from those obtained with pure natural or synthetic dye, as confirmed by colourimetry. The variety of dyes and cotton fabrics shared across batik producers makes it challenging to attribute unsigned batiks to specific workshops. Nevertheless, this study demonstrated that synthetic dye uptake during this period was limited and experimental, with natural Morinda remaining the preferred choice despite the availability of European synthetic alternatives. Full article

This study evaluates the vulnerability of Siberian larch (Larix sibirica L.) populations to future climate change using a genomic offset (GO) framework that integrates genome-wide SNP data with environmental variables. We analyzed 488 individuals from 37 populations across climatically diverse regions of Russia, genotyped by sequencing at over 20,000 SNP loci using the ddRADseq method. Gene–environment association (GEA) analyses (BayeScEnv, LFMM2, and RDA) identified candidate adaptive loci linked to six key bioclimatic variables. Based on these loci, GO was estimated using three approaches implemented in RONA–RDA, RDA, and Gradient Forest frameworks under multiple climate models (MIROC6, BCC-CSM2-MR, MRI-ESM2-0), scenarios (SSP2-4.5, SSP3-7.0, SSP5-8.5), and time periods (2041–2060, 2061–2080, and 2081–2100). Results revealed consistent spatial patterns of vulnerability, with northern and high-altitude populations, as well as populations from more continental and moisture-limited regions, exhibiting the highest GO and thus the greatest risk of maladaptation. In contrast, several central and southern populations showed relatively low vulnerability. The importance of temperature stability (isothermality) and precipitation of the driest month as key drivers of adaptive variation was highlighted. Despite differences in SNP datasets, population rankings remained highly consistent, supporting the robustness of predictions. Overall, our findings demonstrate substantial heterogeneity in climate vulnerability across the species range and provide a genomic basis for conservation strategies, including assisted gene exchange and climate-adaptive forest management. Full article

The ecological consequences of hydraulic engineering on riverine environments have intensified the need for scientifically grounded ecological flow regimes. To ensure habitat suitability during critical fish spawning periods, this study developed habitat preference curves by correlating physiological parameters with key hydro-environmental drivers. A habitat suitability index (HSI) model was established using fuzzy logic, integrated with a genetic algorithm (GA) to simultaneously optimize fuzzy membership functions and inference rules. This model was applied to simulate the relationship between the weighted usable area (WUA) and discharge for various fish egg types in the reach downstream of the Fengman Dam, ultimately facilitating the determination of an optimized ecological pulse flow hydrograph. The results reveal distinct hydro-environmental preference variations among species. Specifically, drifting eggs require specific hatching cycles supported by higher flow magnitudes and velocities. Conversely, adhesive eggs experience a significant reduction in suitable habitat area under high-flow and high-velocity conditions. These findings suggest that reservoir water resource allocation must be tailored to the life-history requirements of target species to maximize spawning success. This study provides a robust scientific framework for eco-friendly reservoir scheduling and the conservation of regulated river ecosystems. Full article

The inclusion of the cement industry into China’s national carbon emissions trading system in 2025 has fundamentally altered the compliance environment for high-emission enterprises, transforming carbon allowances from passive regulatory instruments into dynamic assets whose management directly affects financial performance. We develop a multi-scenario carbon asset management decision model tailored to the intensity-based benchmarking mechanism adopted by the national market. The model centres on the quota surplus-deficit variable EA4, which is computed from enterprise-level emission intensity relative to the industry benchmark, and decomposes the management problem into sequential selling and buying subproblems linked by coupled decision boundaries. A systematic parameter framework is constructed, and the model is applied to two cement enterprises—Enterprise A, a leading producer with a clear allowance surplus, and Enterprise B, a mid-tier producer operating near the benchmark boundary—through historical backtesting over the 2024–2025 period. Three principal findings emerge. First, the intensity benchmarking mechanism creates a dual-leverage effect whereby a 1.4% improvement in emission intensity (from 0.8112 to 0.8000 t/t) increases the quota surplus by 27%, a nonlinearity not captured by conventional compliance-cost models. Second, the model-driven strategy outperforms traditional experience-based approaches by 36.8% (baseline scenario, +95.20 vs. +69.58 MRMB) and 37.3% (risk scenario, −44.55 vs. −71.08 MRMB), with the improvement rate remaining consistent across both enterprises, suggesting that trading timing outweighs instrument selection in determining compliance cost outcomes. Third, dynamic CEA–CCER allocation captures an incremental 2.33 MRMB through the exploitation of a transient price inversion, a gain invisible to single-instrument strategies. Sensitivity analysis confirms that the relative advantage is robust to carbon price variations (±30%) and CCER offset caps (2–10%), while emission intensity and carry-over allowances represent the most consequential parameters for strategy direction, with EA4 crossing zero near the industry benchmark (I ≈ 0.85). The framework provides actionable decision support for cement and other high-emission enterprises navigating the unified carbon market, and contributes a quantitative methodology to the emerging field of environmental management accounting. This study contributes to Sustainable Development Goal 13 (Climate Action), Goal 7 (Affordable and Clean Energy), and Goal 9 (Industry, Innovation, and Infrastructure) by providing operational tools for decarbonisation in carbon-intensive industries. Full article

The aim of this study was to compare within-horse changes and between-horse differences in selected metabolic parameters in twenty draft mares, of which ten belonged to a group with a history of laminitis (LG) and ten formed the control group (CG). Measurements were conducted during four seasonal sampling periods in March (S0), May (S1), July (S2), and September (S3). Within-horse variability across the season was quantified using the coefficient of variation (CV), while differences between groups were evaluated using the t-test or the Mann–Whitney test depending on data distribution. Mares in the LG group exhibited significantly higher insulin variability compared to the CG (20.06% vs. 7.52%; p = 0.023), whereas no statistically significant differences were found for glucose (p = 0.279). Between-horse variability within individual sampling periods was analyzed using the F-test. In S0, no differences were found for glucose (p = 0.607) or insulin (p = 0.980). In S1, higher variability in the LG group was observed for insulin (p = 0.0329), while glucose did not differ between groups (p = 0.952). In S2, the LG group showed markedly higher variability for both glucose (p < 0.0001) and insulin (p = 0.0007). In S3, no differences were found for glucose (p = 0.512) or insulin (p = 0.872). Overall, mares with a history of laminitis exhibited greater seasonal fluctuations and, in some periods, higher inter-individual variability in glucose and insulin concentrations, suggesting lower metabolic stability in response to seasonal environmental conditions. Full article

The present study investigates the statistical distribution of radar reflectivity slopes [S-Ze] in the lower troposphere along the west coast of India using a C-band radar during the pre-monsoon and monsoon seasons in 2024. The study period spans a range of meteorological conditions, from a drier atmosphere during pre-monsoon months to a moist atmosphere during the monsoon months, with varying updraughts and downdraughts. To investigate the S-Ze, we calculated the difference in Ze between 4 km and 2 km altitudes in the lower troposphere. The S-Ze could be either positive or negative, where, in a positive [negative] S-Ze, the Ze decreases [increases] towards the surface. The monthly variations in S-Ze from the pre-monsoon to monsoon months are observed in the lower troposphere and are higher in monsoon months compared to pre-monsoon months, which are too near the coast. The land–ocean contrasts of the vertical profiles contributing to +ve and −ve S-Ze are lower compared to north–south gradients and higher in monsoon months. The average S-Ze shows the highest +ve and −ve S-Ze magnitude near the coast among all the months. The highest magnitude in S-Ze is observed in March and April and is associated with the lower and higher numbers of vertical Ze profiles. The increase or decrease in hydrometeor size is less during the monsoon months (June, July, August, and September) compared to pre-monsoon months, where the March–April months have the highest increase or decrease in the hydrometeor’s size in the lower troposphere. The variations in the S-Ze are the combined effect of the atmospheric, thermodynamic (relative humidity (RH) and moisture flux), and dynamic conditions (zonal, meridional, and vertical velocity). Strong updraughts that carry RH to higher altitudes make the lower atmosphere drier and contribute to a +ve S-Ze; Ze tends to decrease in the lower troposphere. However, a weaker updraught or a moderate downdraught with sufficient RH provides sufficient time for hydrometeors to grow and contributes to −ve S-Ze, and Ze tends to increase in the lower troposphere. For example, in March and April, the atmosphere is dry, and we observe the largest decrease in hydrometeors near the coastal boundary. However, we also see significantly higher negative radar reflectivity slopes, and weak downdraughts provide enough time for hydrometeors to grow. In June and July, there are strong updraughts (downdraughts) with high (low) RH, making the atmosphere more conducive to a decreasing tendency in Ze and contributing to a higher fraction of +ve S-Ze. The results presented here would be an extension of the study from the satellite-based observations, revealing the extension of climatology for the inclusion of stratiform precipitation. Full article

The study evaluated the effect of intercropping Paulownia (Paulownia spp.) with spring barley (Hordeum vulgare L., cv. KWS Thalis) on selected components of agroecosystem biodiversity under Polish conditions. A field experiment established in 2019 compared an alley cropping system with barley monoculture during the 2025 growing season. Weed infestation, soil microbial communities, mesofauna abundance, and crop yield were assessed. Weed abundance was lower in the intercropping system than in monoculture, reaching 5.6 vs. 15.6 plants m⁻² at BBCH 21 and 21 and 22.8 vs. 35.6 plants m⁻² at BBCH 75. Bacterial alpha diversity was significantly higher under intercropping conditions, with Shannon index values ranging from 5.12 to 5.25, compared with 4.98–5.09 in monoculture. Fungal diversity showed moderate differences between systems, whereas the abundance of Collembola and Acari was influenced mainly by seasonal variation rather than by cultivation system. No significant reduction in barley yield was observed under intercropping conditions. The results suggest that Paulownia-based alley cropping may reduce weed pressure and support selected soil biological properties without negatively affecting crop productivity. However, the observed responses varied depending on the analyzed parameter and sampling period, indicating the preliminary and context-dependent character of the results. Further long-term studies are required to better understand the ecological mechanisms operating in such agroforestry systems. Full article

Adhesive joints typically require high safety factors, as their mechanical performance is highly sensitive to environmental and manufacturing variations. Health monitoring can reduce these safety factors by continuously assessing the condition of the joint. While intrinsic and extrinsic sensing approaches exist, they are often based on periodic inspection or manual sensor integration, which limits their suitability for continuous in-service monitoring. This study investigates a novel sensor placement using additively manufactured strain sensors deposited by jet dispensing across the adhesive gap. Tensile lap-shear specimens were fabricated using CFRP (carbon-fiber-reinforced plastic) laminate, an epoxy adhesive, and silver-ink strain sensors placed internally within the joint and externally across the adhesive gap. Mechanical testing revealed that externally printed sensors produced an average resistance change of 65.3% near the failure stress of the adhesive joint, an order of magnitude higher than sensors embedded within the adhesive layer with 6.6% average resistance change. However, the average coefficient of variation increased as well, from 7.6% for internal to 32.6% for external. This sensor response exceeds reported environmentally induced variations in printed sensors and thus represents a promising candidate for condition monitoring. Further work is required to demonstrate actual damage detection capabilities and assess long-term stability under environmental and cyclic loading conditions. Full article

Series–series (S–S) compensated wireless power-transfer (WPT) systems are increasingly deployed where connector-free and reliable energy delivery is required, but practical monitoring becomes ambiguous when receiver-resonance drift and magnetic-coupling variation produce similar transmitter-side impedance changes. This paper addresses that ambiguity by separating the two effects without receiver-side sensing. During a low-power diagnostic interval, the receiver terminal is briefly placed in open and short states, and only the fundamental phasors of the inverter output voltage and primary current are processed together with the known compensation capacitances. After the open-state measurement identifies the primary self-impedance, the short-state residual is mapped to an affine D–${\omega }^2$ line; its zero crossing gives the receiver resonant frequency and secondary self-inductance, while its slope gives the mutual inductance and coupling coefficient. The routine is implementable as a start-up or periodic diagnostic function in WPT hardware that already measures the primary voltage and current and can impose the required receiver terminal states; it requires no receiver-side measurement, auxiliary sensing coil, short-loop resistance measurement, or iterative zero-phase search. In simulation, the coupling-coefficient error remained below $0.014\%$ under receiver-inductance tolerance and mutual-inductance variation. In a prototype, the short-state data followed the predicted linear relation with $R^2=0.9979$, and the extracted coupling coefficient agreed with the reference within about $5\%$. The identified receiver resonance was also used to guide operating-frequency adjustment in a practical power-transfer test. Full article

A 700 m pilot-scale cast iron pipeline reactor was operated for 120 days to investigate corrosion-stage evolution under reclaimed-water conveyance conditions. Sampling points were arranged at 50, 250, 450, and 650 m, and water-quality monitoring, coupon weight-loss tests, scanning electron microscopy (SEM), and high-throughput 16S rRNA sequencing were combined to characterize corrosion-rate variation, corrosion-product morphology, and microbial community succession. During transport, NH₄⁺ generally decreased while NO₃⁻ increased, indicating nitrification-related nitrogen transformation under aerobic conditions; meanwhile, PO₄³⁻ declined and DOC fluctuated, reflecting coupled physicochemical and biological processes. SEM observations showed a transition from loose porous deposits to relatively compact layered corrosion products, followed by local deterioration and renewed porous structures in the later period. The corrosion rate followed an increase–decrease–re-increase pattern rather than a monotonic trend. Therefore, corrosion acceleration (CA = dc/dt) was introduced as an auxiliary diagnostic indicator to identify whether corrosion activity was increasing, decreasing, or temporarily stabilizing. Microbial community analysis showed stage-associated variation in biofilm and nitrogen-transformation-related taxa, supporting the interpretation that corrosion evolution was jointly affected by water-quality change, corrosion-product development, and microbial succession. Overall, the combined interpretation of corrosion rate, CA, water quality, SEM morphology, and microbial succession provides a more informative basis for diagnosing corrosion-stage transitions in reclaimed-water cast iron pipelines. From a sustainability perspective, this diagnostic framework can support long-term operation, maintenance planning, and risk monitoring of urban reclaimed-water distribution infrastructure, thereby improving pipeline durability, reducing leakage and maintenance risks, and enhancing the reliability of reclaimed-water reuse systems. Full article