Search Results (1,282)

The electrical arcs generated by high-speed dynamic separation between pantograph and catenary systems pose a significant threat to the operational safety of high-speed railways. Environmental factors, particularly relative humidity and airflow, critically influence arc characteristics. This study establishes a two-dimensional pantograph–catenary arc model based on magnetohydrodynamic theory, validated through a self-developed experimental platform. Research findings demonstrate that as relative humidity increases from 25% to 100%, the core arc temperature decreases from 10,500 K to 9000 K due to enhanced heat dissipation in humid air and electron capture by water molecules; the peak arc voltage rises from 37.25 V to 48.17 V resulting from accelerated deionization processes under high humidity conditions; the average arc energy in polar regions increases from 2.5 × 10⁻⁴ J/m³ to 3.5 × 10⁻⁴ J/m³, exhibiting a saddle-shaped distribution; and the maximum arc pressure declines from 5.3 Pa to 3.7 Pa. Under airflow conditions of 10–30 m/s, synergistic effects between airflow and humidity further modify arc behavior. The most pronounced temperature fluctuations and most frequent arc root migration occur at 100% humidity with 30 m/s airflow, while the shortest travel distance and longest persistence are observed at 25% humidity with 10 m/s airflow, as airflow accelerates heat dissipation and promotes arc root alternation. Experimental measurements of arc radiation intensity and temperature distribution show excellent agreement with simulation results, verifying the model’s reliability. This study quantitatively elucidates the influence patterns of humidity and airflow on arc characteristics, providing a theoretical foundation for enhancing pantograph–catenary system reliability. Full article

This study evaluated the potential of silibinin linoleate (SL), a natural derivative of silibinin, as an antioxidant to improve the thermal stability of sunflower oil (SF). SL was synthesized through green technology by enzymatic esterification, using mild reaction conditions. SL was added to high-oleic SF samples at three concentrations (200, 400, and 600 ppm), and the oils were subjected to heating at 180 °C for 4 and 8 h. Oxidative stability, fatty acid composition, and nutritional indices were analyzed. The results showed that 600 ppm SL provided the strongest antioxidant effect, significantly reducing oxidation parameters after 8 h of heating, in addition to the following values: peroxide value (PV) 14.22 ± 0.31 meq O₂/kg, p-anisidine value (p-AV) 22.85 ± 0.34, inhibition of oxidation (IO) 56.41 ± 0.31%, and total oxidation value (TOTOX) 51.30 ± 0.39. FTIR spectroscopy confirmed that SL effectively protected the triglyceride structure and limited the formation of oxidation by-products. SL demonstrated a protective effect against thermal oxidation in sunflower oil, with its efficacy being clearly dose-dependent. At 600 ppm, SL showed comparable or superior activity to BHT. However, this effect was specific to the highest tested concentration and does not indicate superiority across all concentrations. These findings suggest that SL has potential as a natural antioxidant for improving oil stability, but further studies are needed to validate SL as a practical and scalable alternative to synthetic antioxidants in the food industry. Full article

Well cementing is an important step in oil and gas development. It uses cement to seal the formation and the casing, preventing fluid leakage. However, when conducting offshore oil well cementing operations, deep-water formations are usually weakly consolidated soils, and it is difficult to form a good cementation between the cement and formation. Therefore, enhancing the strength of the formation is one of the effective measures. This study uses the microbial-induced carbonate precipitation technology to cement sandy formations containing clay minerals. The triaxial tests were conducted to evaluate the consolidation effectiveness in the presence of three clay minerals: montmorillonite, illite, and kaolinite. X-ray computed tomography was utilized to characterize microscopic pore parameters, while thermogravimetric analysis, X-ray diffraction, and surface potential measurements were applied to analyze the mechanisms of clay minerals affecting microbial consolidation. The results showed that microbial mineralization mainly affects the cohesion of the samples. The cohesion of the montmorillonite sample increased from 20 kPa to 65.4 kPa, an increase of up to 3.27 times. The other two samples (illite and kaolinite) had increases of only 0.33 times and 1.82 times. Although the strength of the montmorillonite sample increased the most, unexpected large pores appeared with a diameter of over 120 µm, accounting for 7.1%. This is mainly attributed to the mineral expansion property. The expansion of the minerals will trap more microorganisms in the sample, thereby generating more calcium carbonate. And it also reduced the gaps between sand particles, creating favorable conditions for the connection of calcium carbonate. Although the surface charge of the minerals also affects the attachment of microorganisms, all three minerals have negative charges and a difference of no more than 0.84 mV (pH = 9). Therefore, the expansion property of the minerals is the dominant factor affecting the mechanical and microstructure of the sample. Full article

Structural variation (SV) serves as a fundamental driver of phenotypic diversity and environmental adaptation in plants and animals, significantly influencing key agronomic traits in crops. Common wheat (Triticum aestivum L.), an allohexaploid species, harbors extensive chromosomal SVs and distant hybridization-induced recombination events that provide critical resources for genetic improvement. This study utilizes non-denaturing fluorescence in situ hybridization (ND-FISH) and oligonucleotide multiplex probe-based FISH (ONPM-FISH) to analyze the karyotypes of 153 BC₁F₄–BC₁F₆ lines derived from the hybrid line Xiaoyan 7430 and common wheat Yannong 1212. The results revealed that Xiaoyan 7430 carries 8 alien chromosome pairs and 20 wheat chromosome pairs (lacking 6B), and Yannong 1212 contains 21 pairs of wheat chromosomes. The parental lines exhibited presence/absence variations (PAVs) on chromosomes 2A, 6A, 5B, 1D, and 2D. Chromosomal variations, including numerical chromosomal variation (NCV), structural chromosomal variation (SCV), and complex chromosomal variation (CCV), were detected in the progeny lines through ONPM-FISH analysis. The tracking of alien chromosomes over three consecutive generations revealed a significant decrease in transmission frequency, declining from 61.82% in BC₁F₄ to 26.83% in BC₁F₆. Telosomes were also lost during transmission, declining from 21.82% in BC₁F₄ to 9.76% in BC₁F₆. Alien chromosome 1J^S, 4J, and 6J exhibited the highest transmission stability and were detected across all three generations. Association analysis showed that YN-PAV.2A significantly affected the length/width ratio (LWR) and grain diameter (GD); YN-PAV.6A, XY-PAV.6A, and PAV.5B increased six grain traits (+2.25%~15.36%); YN-PAV.1D negatively affected grain length (GL) and grain circumference (GC); and XY-PAV.2D exerted positive effects on thousand-grain weight (TGW). Alien chromosomes differentially modulated grain characteristics: 1J^S and 6J both reduced grain length and grain circumference; 1J^S increased LWR; and 4J negatively impacted TGW, grain width (GW), GD, and grain area (GA). Meanwhile, increasing alien chromosome numbers correlated with progressively stronger negative effects on grain traits. These findings elucidate the genetic mechanisms underlying wheat chromosomal variations induced by distant hybridization and their impact on wheat grain traits, and provide critical intermediate materials for genome design breeding and marker-assisted selection in wheat improvement. Full article

Introduction: Clear aligner therapy has become a mainstream alternative to fixed orthodontics due to its versatility. However, the variability in thermoforming and the limited validation of digital workflows remain major barriers to reproducibility and predictability. Methods: This study addresses that gap by presenting a proof-of-concept digital workflow for clear aligner manufacturing by integrating additive manufacturing (AM), thermoforming simulation, and finite element analysis (FEA). Dental models were 3D-printed and thermoformed under clinically relevant pressures (400 kPa positive and −90 kPa negative). Results and Discussion: Geometric accuracy was quantified using CloudCompare v2.13.0, showing that positive-pressure thermoforming reduced maximum deviations from 1.06 mm to 0.4 mm, with all deviations exceeding the expanded measurement uncertainty. Thickness simulations of PETG sheets (0.5 and 0.75 mm) showed good agreement with experimental values across seven validation points, with errors <10% and overlapping 95% confidence intervals. Stress analysis indicated that force transmission was localized at the aligner–attachment interface, consistent with expected orthodontic mechanics. Conclusion: By quantifying accuracy and mechanical behavior through numerical and experimental validation, this framework demonstrates how controlled thermoforming and simulation-guided design can enhance aligner consistency, reduce adjustments, and improve treatment predictability. Full article

Objectives: This study focuses on the regulatory mechanism of Schisandrin B (Sch B) on the lipid metabolism and apoptosis of AML-12 liver cells, with a particular emphasis on its potential therapeutic effect and mechanism of action in preventing and treating metabolic-associated fatty liver disease (MAFLD) by activating the PPARγ signaling pathway. Methods: An MAFLD cell model was established by inducing AML-12 cells with a mixture of oleic acid (OA) and palmitic acid (PA) (2:1). AML-12 cells were divided into a control group, a model group, and 20 μM and 40 μM Sch B groups. The cells were lysed and prepared into the cell suspension, then the cell suspension was centrifuged to obtain its supernatant, and the levels of total cholesterol (TC), triglycerides (TG), alanine aminotransferase (ALT), and aspartate aminotransferase (AST) in the supernatant were detected according to the instructions of the kits. Effects of Sch B on the pathological changes of AML-12 cells were observed by Oil Red O staining. The key targets were screened through network pharmacology, and relevant targets were verified through molecular docking simulation. The activity of PPARγ was detected using a dual luciferase reporter plasmid, and the level of cell apoptosis was detected using the Annexin V-FITC/PI double staining method. The Western blot method was used to analyze the expression of genes related to lipid metabolism and apoptosis pathways. Results: Sch B could regulate lipid metabolism disorders in OA+PA-induced MAFLD cell model. The activation of PPARγ-PCK1/Aspase is a key step in the action of Sch B, which can effectively block fatty acid synthesis, improve fatty acid oxidation, and reduce lipid droplet aggregation in liver cells, thereby alleviating lipid metabolism abnormalities in the MAFLD cell model and inhibiting cell apoptosis. Conclusions: This finding may lay an important theoretical foundation and open a new research direction for the deep development and application of Schisandra chinensis. Full article

Surface roughness influences biofilm adhesion on denture base materials, impacting oral health. Despite advances in polymeric denture materials, the effects of common cleaning protocols on their surface texture remain inadequately characterized. This study investigated the influence of toothbrush abrasion on the surface texture of dimethyl methacrylate-based (DMA, printed: V-Print dentbase), polymethyl methacrylate (PMMA, milled: VITA Vionic Base, pressed: IvoBase Hybrid), polyamide (PA, pressed: Bre.flex), and polyether ether ketone (PEEK, milled: Juvora Disc). The specimens were fabricated as polished discs. The Vickers and Martens hardness, indentation modulus, elastic and plastic part of indentation work, and indentation creep were determined. Toothbrushing simulation and surface texture analysis were conducted in three steps: 1800, 1800, and 3600 cycles using water, dish detergent, or toothpaste slurry. The surface texture parameters Sa, Sal, Sdr, Sku, and Ssk were determined using confocal laser scanning microscopy and suitable filtering (S-F and S-L surface). Sa, Sal, and Sdr showed significant changes depending on the choice of medium and the material used. The duration had a small effect (three-way ANOVA; all p < 0.001). DMA showed minor surface changes. Milled and pressed PMMA exhibited similar surface deformities due to wide valleys that were not considered critical for biofilm adhesion. PA showed the lowest and PEEK the highest Vickers and Martens hardness. However, both PA and PEEK exhibited surface changes that could promote biofilm development. These findings suggest that denture cleaning recommendations should remain material-specific. Regular surface inspections and repolishing are necessary to reduce the risk of biofilm formation on PA or PEEK-containing dentures. Full article

Bacterial cellulose, a biopolymer synthesised by microorganisms, exhibits remarkable structural, optical, and electronic properties. This study utilised a range of photon- and electron-based techniques, including X-ray diffraction, proton nuclear magnetic resonance (¹H-NMR), photoacoustic spectroscopy, and scanning electron microscopy, to thoroughly characterise BC. While XRD and NMR directly employ photons to probe the structure and composition, PAS indirectly converts absorbed photons into phonons to evaluate optoelectronic features. SEM revealed a dense nanofibrillar network with fibrils measuring 10–75 nm in diameter. XRD confirmed the crystalline nature of BC, identifying characteristic peaks associated with cellulose Iα. ¹H-NMR relaxation analysis differentiated between the ordered and disordered cellulose regions. PAS determined an optical bandgap of 2.97 eV and identified defect states between 3.6 and 2.9 eV, including a prominent peak at 3.35 eV, likely resulting from oxygen vacancies, hydroxyl modifications, or UV-induced rearrangements. These defects modify BC’s electronic structure, suggesting potential for bandgap engineering. The integration of these complementary techniques provides a multidimensional understanding of BC’s morphology, crystallinity, and electronic behaviour, underscoring its potential in bioelectronics, advanced composites, and biomedical applications. Full article

The plant microbiome plays a pivotal role in host development and resilience against biotic and abiotic stresses. In perennial crops like peach, microbial communities inhabiting dormant buds—critical yet vulnerable organs—may influence disease outcomes and plant fitness. This study characterized the bacterial and fungal communities associated with the buds of three peach cultivars differing in susceptibility to Twig Canker and Shoot Blight (TCSB). Amplicon-based profiling revealed distinct microbiome signatures across cultivars, shaped by host genotype. The highly tolerant ‘Catherina’ harbored a structured and relatively diverse community enriched in beneficial bacterial genera such as Pseudomonas, Sphingomonas, and Curtobacterium, alongside protective yeasts including Aureobasidium and Cladosporium. In contrast, the susceptible cultivar ‘Pavoro^®-Pav 1605’ hosted a less balanced microbiome, marked by enrichment of opportunistic pathogens such as Alternaria and Diaporthe, as well as the bacterial lineage 1174-901-12. The intermediate cultivar ‘Lami^®.COM’ displayed a transitional profile enriched in Sphingomonas, Pelomonas, and Vishniacozyma. Differential abundance analyses confirmed cultivar-specific enrichment patterns, underscoring the influence of genotype in shaping microbiota composition and potential disease outcomes. These findings support the integration of microbiome-based approaches into sustainable disease management via beneficial microbial promotion, early detection of harmful consortia, and microbiome-informed breeding to foster resilient, low-input peach cultivation systems. Full article

Due to the exceptional corrosion resistance, chemical stability, and dense microstructure, carbon-based thin films are extensively employed in hydrogen energy systems. This study employed magnetron sputtering to fabricate amorphous carbon (a-C) films on SS316L substrates, aiming to improve the corrosion resistance of bipolar plates (BPs) in proton exchange membrane fuel cells (PEMFCs). Using a Taguchi design, the effects of working pressure, sputtering power, substrate bias, and deposition time on film properties were systematically examined and optimized. Films were examined via field emission scanning electron microscopy (FE-SEM), contact angle measurements, and electrochemical tests. Comprehensive evaluation by the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method identified optimal conditions of 1.5 Pa pressure, 150 W radio frequency (RF) power, −250 V bias voltage, and 60 min deposition, yielding dense, uniform films with a corrosion current density of 1.61 × 10⁻⁶ A·cm⁻² and a contact angle of 106.36°, indicative of lotus leaf-like hydrophobicity. This work enriches the theoretical understanding of a-C film process optimization, offering a practical approach for modifying fuel cell bipolar plates to support hydrogen energy applications. Full article

Grassland classification via remote sensing is essential for ecosystem monitoring and precision management, yet conventional satellite-based approaches are fundamentally constrained by coarse spatial resolution. To overcome this limitation, we harness high-resolution UAV multi-sensor data, integrating multi-scale image fusion with deep learning to achieve fine-scale grassland classification that satellites cannot provide. First, four categories of UAV data, including RGB, multispectral, thermal infrared, and LiDAR point cloud, were collected, and a fused image tensor consisting of 10 channels (NDVI, VCI, CHM, etc.) was constructed through orthorectification and resampling. For feature-level fusion, four deep fusion networks were designed. Among them, the MultiScale Pyramid Fusion Network, utilizing a pyramid pooling module, effectively integrated spectral and structural features, achieving optimal performance in all six image fusion evaluation metrics, including information entropy (6.84), spatial frequency (15.56), and mean gradient (12.54). Subsequently, training and validation datasets were constructed by integrating visual interpretation samples. Four backbone networks, including UNet++, DeepLabV3+, PSPNet, and FPN, were employed, and attention modules (SE, ECA, and CBAM) were introduced separately to form 12 model combinations. Results indicated that the UNet++ network combined with the SE attention module achieved the best segmentation performance on the validation set, with a mean Intersection over Union (mIoU) of 77.68%, overall accuracy (OA) of 86.98%, F1-score of 81.48%, and Kappa coefficient of 0.82. In the categories of Leymus chinensis and Puccinellia distans, producer’s accuracy (PA)/user’s accuracy (UA) reached 86.46%/82.30% and 82.40%/77.68%, respectively. Whole-image prediction validated the model’s coherent identification capability for patch boundaries. In conclusion, this study provides a systematic approach for integrating multi-source UAV remote sensing data and intelligent grassland interpretation, offering technical support for grassland ecological monitoring and resource assessment. Full article

Ecofriendly flame-retardant polystyrene (PS) composites were developed using the synergistic effects of phytic acid (PA), polyethyleneimine (PEI), and expandable graphite (EG). PA was chemically hybridized with PEI, and the hybrid (PAE) was incorporated into PS together with EG. The flame-retardant performances of the resulting composites were evaluated using the limiting oxygen index (LOI), UL-94 vertical burning test, and cone calorimetry test. The strong interaction between EG and PAE provided an effective barrier against heat and oxygen, thereby improving the flame retardancy. The best-performing composite (PA:PEI:EG = 1:1:1 (w/w/w), total flame-retardant loading = 10 parts per 100 parts of PS) exhibited an LOI of 27.7% and a UL-94 V-0 rating. The peak heat release rate (148.8 kW/m²) and total heat release (91.2 MJ/m²) of this composite were lower than those of pure PS by 79.2% and 34.0%, respectively. This study provides guidelines for the production of flame-retardant PS and other polymeric materials. Full article

Background/Objectives: This study examined the efficacy of a physical activity (PA) intervention augmented by a non-immersive Virtual Reality (VR) gaming system (i.e., Virtual Reality-infused Movement and Activity Program; V-MAP) on physical activity (i.e., sedentary behavior, moderate-to-vigorous PA [MVPA], vigorous PA [VPA]) and cognitive skills (i.e., response error, movement latency and reaction time) in Head Start preschoolers. Methods: Using a repeated-measure with 1-month follow-up design, a sample of 13 Head Start preschoolers (Mage = 67.08 ± 4.32 months; 36.2% boys) engaged in a 6-week V-MAP intervention (30-min session; 8 sessions) that focused on non-immersive VR based movement integration. The Cambridge Neuropsychological Test Automated Battery (CANTAB) was used to measure cognition; school-based PA and sedentary behavior were assessed by ActiGraph accelerometer. Pedometers were used to monitor real time engagement and implementation over eight intervention sessions. Results: On average, children obtained 1105 steps during the 30-min intervention (36.85 steps/min). There was a significant increase in VPA after the V-MAP intervention, whereas no significant changes in MVPA or sedentary behavior were observed (ps > 0.05). Although we did not observe significant improvement in studied cognitive function variables (ps > 0.05) after the V-MAP intervention, some delayed effects were observed in the follow-up test (Cohen’s d ranges from −0.41 to −0.73). Conclusions: This efficacy trial provides preliminary support that implementing V-MAP in recess may help Head Start preschoolers achieve or accumulate the recommended daily 60-min MVPA guideline during preschool years. The findings also provide insights that VR-based PA for as little as 30 min per day may benefit cognitive capability. Full article

Slope instability in open-pit coal mines threatens safety and infrastructure. Displacement phenomena (cracks, deflection, heaving) signal potential failure. While counterweight backfilling stabilizes slopes, site-specific protocols for heterogeneous settings, such as Indonesia’s Barito Basin (Warukin Formation), lack standardization. This study addresses this gap at PT. Bhumi Rantau Energi’s Mahoni Pit by integrating high-resolution displacement monitoring (Leica Nova TM50), geotechnical analysis (RQD, RMR), and numerical modeling (SLIDE 7.0, RS2 v11). The objectives were to characterize the displacement mechanisms, quantify the counterweight effectiveness, and optimize the geometry. The results show “warning”-level velocities (>10 mm.h⁻¹) across points, with peak displacement (907 mm.day⁻¹ at IPD_MHN_26) driven by pore pressure in weak fill/mud layers (c′: 2–20 kPa; thickness: 71–100 m). Counterweights significantly increased the Factor of Safety (FoS) from critical levels (e.g., 0.960, PF = 74.4%) to stable values (e.g., 1.160, PF = 1.8%), representing 20–35% improvements. RS2 identified fill material as the primary displacement zone (max: 2.10 m). Optimized designs featured phased backfilling (200 k–10 M BCM) with a 50 m width and 11° inclination. Tailored counterweight deployment effectively mitigated the instability in slopes underlain by weak strata. The integrated approach provides a validated framework for optimizing designs in similar sedimentary basins, enhancing safety and reducing costs. Full article

The optimization model of intelligent identification for bridge cracks based on dual-parameter error indexes’ feedback mechanism is studied here. An interdisciplinary evaluation system of geometric morphology and fracture mechanics is proposed and established. The weighted average of two parameters is proposed as the index to evaluate the crack information model. The two parameters are as follows: (1) effective crack width index (ECWI), which reflects the geometric error of crack information vector graphics; (2) the tip curvature radius error (TCRE), which reflects the stress concentration degree of structural cracks. The aforementioned dual-parameter error evaluation indexes are processed by weighted averaging with reference to current specifications, and the recognition errors of cracks identified by the lightweight semantic segmentation model MobileNetV2-DeepLabv3+ are comprehensively evaluated. The above errors are fed back to the model training code, and parameters such as crack training hyperparameters and data augmentation parameters are adjusted for retraining. After iterative optimization from Version 1 to Version 5, the model’s prediction accuracy is improved: the Dice coefficient is increased by 3.5~32.4%, IoU by 5.3~56.5%, and PA by 0.42~1.33%, finally iterating to an optimized crack recognition model. This combined evaluation system of geometric morphology and fracture mechanics can optimize the information model through error feedback. Meanwhile, by virtue of this method, the disease photos from bridge inspections during the maintenance phase can be identified and converted into an information model of bridge diseases, which holds significant theoretical significance and engineering value for promoting digital maintenance. Full article