Search Results (3,074)

This study investigated the relationship between the surface microstructure of pearlite steel wheels and the formation of fatigue cracks during the braking process by using a full-size wheel braking test rig. After fatigue failure, the surface microstructural evolution and fatigue crack initiation and propagation of the wheel sample were systematically analyzed by optical microscope (OM), scanning electron microscope (SEM), and transmission electron microscope (TEM). The results showed that after braking of 1572 cycles, a large number of fatigue cracks formed at the wheel tread, which caused the wheel to break. After fatigue failure, some dark areas formed at the wheel tread, which were composed of Fe₃O₄ compounds. This indicates that severe oxidation was produced at the wheel tread during braking due to the high temperature. After fatigue failure, a continuous thermal white etching layer (T-WEL) was formed in some areas of the wheel tread, while crescent-shaped T-WEL was found in other areas. The microstructure of the T-WEL was composed of martensite phase. The rapid increase and decrease in temperature at the wheel tread during the braking process caused martensitic transformation at the wheel tread. The hardness of the sample reached to about 900 HV in WEL and it reduced with the increase in distance from the surface. The cracks were initiated from the surface and gradually propagated into the matrix. However, the crack propagation mode in the continuous T-WEL and crescent-shaped T-WEL was different. In the continuous T-WEL, the continuous T-WEL of the wheel can be peeled off during the braking wear process, and then the crack was gradually propagated into the matrix in the T-WEL peeled area. As for the crescent-shaped T-WEL, due to the large hardness difference between T-WEL and pearlite, the crack initiated at the interface between the T-WEL and pearlite and gradually propagated into the matrix. Full article

Background: Systemic risk in heterogeneous multi-subsystem settings has been addressed by composite stress indices, spectral entropy of correlation matrices, and regime-switching copula models; none directly measures structural divergence between regime-conditional coupling matrices under an explicit hidden-regime model. Methods: We embed whitened subsystem indicators in a two-regime Gaussian-copula hidden Markov process and define the coupling divergence as the matrix relative entropy between regime-conditional correlation matrices. We establish non-negativity, reduction to scalar Kullback–Leibler divergence between sorted eigenvalue distributions under commutativity, orthogonal invariance, and vanishing under the no-regime-switching null. Results: On stylized simulation, the framework separates regime-switching from single-regime null cases at an operating window T ∈ [250, 1000]; it isolates eigenbasis-rotation signals invisible to any sorted-eigenvalue method, with 99.9% of the divergence in the rotation regime residing in the non-commutative component; it tolerates Gaussian-copula misspecification under heavy-tailed processes with a quantifiable upward bias; and expectation–maximization convergence behavior serves as an auxiliary null-identification diagnostic. Conclusions: The framework composes existing primitives into a regime-to-regime structural divergence and isolates a compositional mode of regime change beyond scalar methods. Results are internal-validity claims on synthetic data; external validation on real multi-subsystem data is an open question. Full article

Driven by the growing demand for functional textiles featuring excellent waterproofness, moisture permeability and mechanical robustness in outdoor sportswear, medical protection and technical apparel, traditional pongee—despite its desirable softness, high wrinkle resistance and good stability as an ideal substrate fabric—is severely restricted in further application by its intrinsically poor hydrostatic pressure resistance in extremely wet environments. Accordingly, we developed a modified waterborne polyurethane (WPU) coating for pongee substrates to fabricate functional textiles that maintain high hydrostatic pressure resistance while possessing good mechanical properties and increased UV absorption. In this study, by using the sol–gel method, an amorphous silicon dioxide (SiO₂) coating layer was constructed on the surface of titanium dioxide (TiO₂) particles, forming silica-modified titania particles (SiO₂/TiO₂). These SiO₂-modified particles were subsequently physically blended with an anionic waterborne polyurethane system that had been previously modified with a polyester-type modifier A to enhance its hydrostatic pressure resistance. The resulting composite coating was designed to combine the high hydrostatic pressure resistance inherited from the modified WPU matrix, the mechanical reinforcement and increased UV absorption contributed by SiO₂/TiO₂, and satisfactory water repellency on fabric substrates. The results indicate that the incorporation of an appropriate amount of modifier A into the prepolymer system significantly enhances hydrostatic pressure resistance while maintaining high elongation at break. At a SiO₂/TiO₂ loading of 0.2 wt%, the composite film exhibits optimal comprehensive performance, characterized by superior mechanical properties, low water absorption, and static water contact angles exceeding 100° for coated fabrics. SiO₂/TiO₂ composite WPU coatings substantially improve hydrostatic pressure resistance across various fabrics, with 380T polyester taffeta demonstrating the best performance. This resistance remains remarkably stable after standard washing, indicating excellent wash fastness and practical applicability. Full article

This paper investigates the magnetization reversal processes in spring-exchange magnetic composites featuring irregular, dendritic structures. A disorder-based cluster Monte Carlo method combined with a Diffusion-Limited Aggregation (DLA) algorithm was used to model a fractal-like soft magnetic phase (Fe) embedded in a high-coercivity hard matrix (Fe-Nb-B-Dy). A multiparameter analysis was performed by varying the soft phase volume fraction (10–30%), intergrain exchange coupling via contact bridges (25–100%), system scale factors (1–20), surface-to-volume anisotropy ratios (K_S/K_V = 1–20), and the degree of random anisotropy contribution (RAC = 0–100%). The simulations reveal that highly branched fractal structures enhance the interfacial contact area, which accelerates the nucleation of domain reversal driven by the soft phase, paradoxically lowering the overall coercivity compared to compact morphologies. Furthermore, a lack of easy magnetization axis coherent alignment triggers a cascading reversal mechanism through local “weak links”, severely degrading the coercive field from approximately 4.2 T to below 0.4 T in extreme cases (at 30% Fe, 25% coupling and high K_S/K_V ratio). These findings suggest potentially the most important factors and their impact that should be taken into account in the design and optimization of next-generation powder-sintered permanent magnets. Full article

Synthetic Aperture Radar (SAR) is widely used for marine oil spill surveillance due to its all-weather capabilities and sensitivity to sea surface roughness. However, oil slicks often appear as dark formations that can be confounded with visually similar “look-alikes”, making automated detection and boundary delineation challenging. This study proposes a two-stage deep learning framework for oil spill mapping in Sentinel-1 SAR imagery. First, a ConvNeXt-T classifier screens image patches for likely slick presence, reducing the search space for dense prediction. Second, spill boundaries are extracted with a domain-adapted Segment Anything Model (SAM) configured for prompt-free, single-shot segmentation. The input representation is enhanced by combining preprocessed Sentinel-1 VV backscatter with Gray-Level Co-occurrence Matrix (GLCM) texture measures (homogeneity and variance) to better separate oil from heterogeneous background sea at the segmentation level. Quantitative evaluation against established segmentation baselines demonstrates that our adapted SAM achieves the highest overall accuracy, reaching an F1-score of 0.86. This outperforms traditional models such as UNet and CBDNet (0.83), as well as DeepLabV3, SegNeXt, and OFCNet (all at 0.82). Furthermore, an analysis of the wind speed on the test set shows that wind speed affects detectability but does not by itself determine segmentation quality. The results indicate that combining transformer-based screening with efficient foundation-model adaptation can provide accurate and scalable oil spill mapping for operational SAR monitoring. Full article

Gases are prone to accumulating in mines. Untimely gas drainage can easily trigger gas outbursts, which may further lead to gas explosions, directly endangering personnel lives and mine safety. Therefore, gas control during gob-side entry driving (roadway excavation adjacent to the goaf) in high-gas mines is crucial to ensuring successful and safe mining and excavation. The 110505 track haulage gateway is a typical high-gas gob-side driving gateway. The measured maximum gas content of the lower No.5 coal seam is 6.0289 m³/t. At present, without a scientific basis for optimizing core parameters, such as the spacing and diameter of gas drainage boreholes, gas drainage is incomplete, and triangular gas pressure zones are likely to form between boreholes. As a result, the risk of gas accumulation is high. This not only exacerbates the danger of unpredicted gas outbursts but also seriously hinders the rapid excavation of the gateway and the progress of mining and further excavation. Based on a mechanical framework coupling coal seam and methane migration, and focusing on the relationships between factors such as borehole spacing, borehole aperture, methane drainage duration, and overall gas drainage efficiency, a model incorporating dual pore distribution and unified permeability characteristics was constructed. Numerical modeling was performed using the COMSOL Multiphysics platform to examine the influences of different borehole spacings and apertures on underground gas drainage in coal seams. The results indicate that reducing borehole spacing contributes to a more pronounced decline in gas pressure and a lower peak pressure between neighboring boreholes. When an interval spacing of 0.3 m was adopted for the drilling layout arrangement, the peak gaseous potential within the surrounding rock matrix dropped to 0.48 MPa following continuous drainage over a duration of 20 days, a reduction of 44%, and there was no obvious triangular zone of pressure. In contrast, borehole diameter had a minor effect on gas drainage efficiency, and the maximum gas pressure after 20 days was less than 0.52 MPa under different borehole diameters. This work establishes a theoretical foundation and offers practical guidance for high-efficiency gas drainage during gob-side entry driving, which is of vital importance for achieving safe and rapid excavation in high-gas mines. Full article

Background/Objectives: Vision Transformers (ViTs) have demonstrated impressive performance in dealing with large-scale natural image datasets. They have started to be used in medical image classification problems as well. However, how they behave under real-world conditions, such as data scarcity and extreme class imbalance, has not been well investigated. In this study, we examine the feasibility of using a standard Vision Transformer Base model that learned from scratch how to classify skin lesion images into multiple classes using the ISIC 2019 dataset. Methods: The Vision Transformer architecture was trained from scratch using stratified splitting of the data, class-balanced cross-entropy loss, multi-seed initialization, and control of hyperparameters such as patch size and dropout rate. The evaluation of the Vision Transformer architecture was performed using a hold-out test set with metrics such as accuracy, macro-F1, weighted-F1, and analysis of the confusion matrix. Results: Across all configurations, the training exhibited substantial instability and consistent overfitting behavior, with an average accuracy gap between validation and test sets of 22.7%. Test accuracy ranged from 8.0% to 37.8%, showing high sensitivity to initialization. For minority classes, the F1-score remained very low (F1 < 0.05) even though the classes were balanced in the loss function. Conclusions: The results indicate that a standard ViT-Base model trained from scratch can exhibit pronounced instability and a tendency toward majority-class bias when applied to multi-class skin lesion classification under conditions of extreme class imbalance and data scarcity. The findings point to the limitations of using simple transformer models without pre-training or other forms of inductive bias in scarce data settings. Full article

The present study evaluated the stability of candidate reference genes during adipogenic differentiation of 3T3-L1 cells cultured on different extracellular matrices. The aim was to investigate the effects of matrix composition and differentiation stage on the expression of candidate housekeeping genes and to compare validation strategies in dynamic in vitro models. Eleven candidate reference genes (18S, Actb, B2m, Gapdh, Hmbs, Hprt, Nono, Ppia, Rplp0, Tbp, and Ywhaz) were analyzed by RT-qPCR in 3T3-L1 cells cultured on TC, collagen, gelatin, and Matrigel at Days 7 and 14 of differentiation. Gene stability was assessed using geNorm, NormFinder, RefFinder, comparative ΔCt, BestKeeper, generalized linear model (GLM), linear mixed model (LMM), and correlation analyses with the adipogenic markers Pparg and Fasn. The results demonstrated that the expression of most housekeeping genes was influenced by matrix composition, differentiation stage, or their interaction. Actb and 18S exhibited the strongest condition-dependent variability and pronounced matrix sensitivity. Gapdh and Hprt showed significant correlations with both Pparg and Fasn, while Hmbs correlated with Fasn, suggesting that these reference genes may not be fully independent of adipogenic status. Ppia demonstrated markedly contrasting rankings across analytical approaches, highlighting limitations of single-method stability assessment. The findings confirm that universal housekeeping genes are unlikely to exist across different matrix conditions and differentiation stages. The results highlight the need for multi-level validation strategies and experimentally validated normalization panels to minimize normalization bias and avoid misleading RT-qPCR expression profiles. Functional validation identified B2m and Rplp0 as the most suitable two-gene normalization panel for the experimental model evaluated, whereas Tbp remained a strong complementary reference gene candidate. Full article

Bone loss in the maxillofacial region arises from multiple causes, including periodontal disease, trauma, surgical procedures, infection, congenital anomalies, and cancer. Traditional treatment relies on bone grafting, either alone or in combination with biomaterials. Advances in tissue engineering have introduced synthetic or natural scaffolds to mimic the mineralized bone matrix. Natural scaffolds offer excellent biocompatibility and similarity to native tissue but often lack sufficient mechanical strength and exhibit poor degradation rates. Synthetic scaffolds provide tunable porosity and mechanical stability; however, their biological inertness makes them poor sources of osteogenic signaling. A key factor in the success of any scaffold is its interaction with the host immune system. Upon implantation, the innate immune response is initiated, with neutrophils and macrophages being the first cells to contact the scaffold. Macrophage polarization toward proinflammatory (M1) or anti-inflammatory (M2) phenotypes determines whether the microenvironment favors inflammation or remodeling. The adaptive immune response also plays a critical role: T and B lymphocytes may promote tolerance and integration through Th2/Treg pathways and antibody-mediated regulation, or they may trigger chronic inflammation and rejection through Th1/Th17 activation. This review examines the natural and synthetic materials used for bone remodeling and their biological properties. It then outlines the sequence of immune events occurring from the moment a scaffold is implanted to its potential integration or failure. Finally, this study highlights the relevance of cellular models and in vitro assays for the early evaluation of immunogenicity and biocompatibility, which are essential for optimizing scaffold design and improving outcomes in maxillofacial bone regeneration. Full article

Background/Objectives: Dioscorea batatas Decne (yam), which contains various bioactive compounds, has been utilized in the cosmetics industry, while most of the peel of D. batatas (DBP) is discarded without further use. Recent studies have shown that DBP contains higher levels of bioactive substances than the rhizome flesh. The aim of this study was to evaluate the skin biological activities of DBP extracts obtained using 70% ethanol (70% EtOH DBP), 95% ethanol (95% EtOH DBP), and ethyl acetate (EA DBP), with particular attention to their antioxidant-associated protective effects. Methods: Skin-related bioactivities of DBP extracts prepared using ultrasonic extraction were evaluated using in vitro tyrosinase and matrix metalloproteinase-1 (MMP-1) assays, alpha-melanocyte-stimulating hormone (α-MSH)-induced melanogenesis in B16F10 cells, ultraviolet B (UVB)-irradiated HaCaT viability assays, and Western blot analysis of pro-collagen type I alpha 1(Pro-COL1A1) and MMP-1 in HDF cells. In addition, the ABTS and DPPH radical scavenging activities of DBP extracts and representative DBP derivatives were assessed. Results: DBP extracts inhibited tyrosinase activity in vitro and reduced melanogenesis in B16F10 cells. DBP extracts also protected skin cells from UVB by increasing the viability of UVB-irradiated HaCaT cells. In UVB-irradiated HDF cells, DBP extracts restored Pro-COL1A1 expression and suppressed MMP-1 levels. Additionally, DBP extracts inhibited MMP-1 activity in a concentration-dependent manner. The DBP extracts themselves exhibited ABTS and DPPH radical scavenging activities, with EA DBP showing the highest vitamin C equivalent antioxidant capacity among the tested extracts. Representative DBP-derived phenanthrene compounds also showed radical scavenging activities, supporting the antioxidant potential of peel-derived phytochemicals. Conclusions: These findings indicate that DBP extracts possess skin-whitening and anti-photoaging effects and suggest that these protective activities may be associated with the antioxidant potential of both DBP extracts and DBP derivatives. Full article

Buildings are the primary energy consumption layer of Renewable Energy Communities (RECs) and a key target for net-zero policy under the EPBD recast. This scoping review applies the PRISMA-ScR framework to map Digital Twin (DT) architectures for building-scale and community-scale energy management in REC configurations. A Scopus search yielded a final analytical corpus of 102 studies, coded through an eight-dimensional thematic matrix covering lifecycle phases, digitalization objectives, enabling technologies, DT capability dimensions, and data realism. DT is the dominant enabling technology (55.9%), followed by IoT (23.5%) and machine learning (22.5%). Research is concentrated in the Planning and Design phase (77.5%) and markedly underrepresented in Implementation and Commissioning (16.7%). Notably, only 10.8% of studies integrate real-time operational data, exposing a significant gap between simulation-based research and the deployment conditions required under current EPBD mandates. The evidence base supports building energy monitoring, demand forecasting, and flexible grid operation but remains limited for retrofit verification, standardized net-zero KPIs, and operational workflows in existing stock. Critical DT capability gaps persist in Data Services (7.8%) and User Experience (18.6%). Overall, DT architectures show genuine potential for grid-interactive, net-zero building management, yet the field presents unresolved structural challenges for large-scale real-world deployment. Full article

High-speed permanent magnet synchronous motors (PMSMs) used in electric pump-fed liquid rocket engines require stator shielding sleeves to prevent corrosive propellants from causing harm under cyclic pressure. However, metallic sleeves suffer significant losses due to eddy currents. Conversely, pure carbon fiber reinforced polymer (CFRP) sleeves have failed when exposed to 98% H₂O₂. Micro-CT analysis of a failed pump sleeve reveals a four-stage failure mechanism. Manufacturing defects caused matrix cracking, which propagated under pressure and thermal cycling. This progression resulted in the formation of through-thickness leakage paths, which ultimately triggered catalytic decomposition and explosion. To address these issues, an improved dual-layer sleeve is proposed, featuring a 2.5 mm PEEK 450G liner and a 2.0 mm T700S/epoxy CFRP overwrap. Finite Element Analysis (FEA) indicates peak von-Mises stresses of 86.25 MPa and 112.16 MPa, yielding Tsai–Wu safety factors of 2.9 and 1.7. Furthermore, various tests, including immersion, fatigue, burst, hydraulic, and thermal evaluations, demonstrate a burst margin of 2.37× at 7.12 MPa, with only 0.19% increase in mass. This design effectively eliminates leakage pathways while preserving zero eddy-current loss and ensuring a low weight. Full article

With the standardization of the Module-Lattice-Based Key Encapsulation Mechanism (ML-KEM) in NIST FIPS 203 (2024), efficient hardware support for polynomial ring operations has become critical for practical post-quantum cryptography deployment. The dominant computational workload of ML-KEM arises from matrix–vector multiplications over polynomial rings, which involve repeated Number Theoretic Transform (NTT), pointwise multiplication, and modular addition operations. This work proposes an ML-KEM polynomial ring accelerator leveraging Open Intellectual Property (Open IP) and integrates it into an open hardware Chipyard RISC-V System on Chip (SoC) via a Memory-Mapped I/O (MMIO) interface. The design incorporates an NTT-based datapath with multiplier and adder arrays, and employs a scratchpad memory to enable intermediate data reuse and reduce memory access overhead. The proposed architecture is implemented on a Genesys 2 FPGA development board featuring a Kintex-7 XC7K325T Field Programmable Gate Array (FPGA) (Digilent Inc., Pullman, WA, USA) and evaluated at both kernel and system levels. Experimental results show that the accelerator reduces matrix–vector multiplication latency to 7372 cycles, achieving up to 40× speedup over a software baseline. At the SoC level, the complete ML-KEM implementation achieves performance improvements of 1.6× to 2.1× across different parameter sets. These results demonstrate that integrating Open IP within an open hardware SoC provides an effective and reproducible approach for accelerating ML-KEM. Full article

Background: Overexpression of immune cell populations leads to self-amplifying cytokine loops, contributing to chronic inflammation in both allograft rejection and autoimmune conditions. Tacrolimus (TAC), despite being a potent immunosuppressant, has limitations; its systemic adverse effects include nephrotoxicity, neurotoxicity, and high variability in tissue exposure in patients. Currently available therapeutic options are limited by the lack of targeted and localized drug delivery systems, resulting in ineffective control over drug-release behavior. Moreover, TAC being highly lipophilic poses challenges for formulation development. To address these gaps, this study focuses on developing a thermoresponsive hydrogel platform comprising distinct nanocarriers for localized delivery of TAC. The nanocarriers include nanoemulsion (NE) and micelles as TAC carriers, and their particle sizes are specifically engineered at the nanoscale for differential release behavior and to support immune cell targeting (macrophages and T-cells). Incorporation into a thermoresponsive hydrogel matrix enables it to act as a local depot at the injection site and deliver TAC with a slow, extended-release profile. Methods: TAC was loaded into a coconut-rich lipid-phase-based NE via high-pressure microfluidization. Simultaneously, TAC-loaded micelles were optimized using a full-factorial design of experiments (DoE) and manufactured via the thin-film hydration method. Both nanocarriers were evaluated for long-term colloidal stability assessments. Hydrogels were produced maintaining aseptic conditions for sterile batch production. Rheological characterization was performed to assess sol-gel transition, thermoreversibility, and injectability, and in vitro release studies were conducted to evaluate TAC diffusion from the developed nanoformulations. Results: Developed nanocarriers resulted in distinct particle sizes in NE (80–85 nm) and micelles (15–17 nm) with successful TAC loading maintaining long-term colloidal stability. The developed TAC-loaded dual-nanocarrier hydrogel (Dual-HG) showed thermoresponsive behavior and gelation at 37 °C, forming as a local depot. In vitro release studies showed slow and extended tacrolimus release from hydrogels and demonstrated particle size-dependent release behavior between the NE and micelle. Conclusions: Therefore, our study highlights a novel dual nanocarrier hydrogel platform combining TAC-NE and TAC-micelle for localized delivery. The findings support that nanocarriers can be engineered to modulate drug diffusion behavior. Notably, the dual nanocarrier within a thermoresponsive hydrogel platform can be used to deliver one or multiple drugs locally, minimizing systemic exposure when sustained local immunosuppression is required. The 25 mL scale sterile batch production of hydrogels emphasizes their suitability for future translational applications. Full article

Dendrobium officinale has attracted increasing attention as a functional food because of its diverse biological activities; however, the photoprotective potential of its protein-derived peptides remains poorly understood. In this study, D. officinale protein hydrolysates were fractionated by ultrafiltration according to molecular weight, and their protective effects against ultraviolet B (UVB)-induced photoaging were systematically evaluated in HaCaT keratinocytes. Among the tested fractions, low-molecular-weight peptide fractions exhibited relatively stronger antioxidant activity and effectively reduced intracellular reactive oxygen species (ROS) accumulation in UVB-irradiated cells. In addition, the peptide fractions alleviated UVB-induced inflammatory responses and decreased matrix metalloproteinase (MMP) expression, which was associated with modulation of mitogen-activated protein kinase (MAPK) and nuclear factor kappa B (NF-κB) signaling pathways. Higher-molecular-weight fractions showed relatively stronger effects on maintaining skin barrier-related functions and were associated with regulation of transforming growth factor-β/Smad (TGF-β/Smad) signaling and collagen-related protein expression. Overall, these findings demonstrate functional differences among Dendrobium officinale peptide fractions and suggest their potential application as natural photoprotective ingredients in functional foods and cosmeceutical products. Full article