Search Results (1,342)

Lignite particles generate considerable dust during drying due to structural damage, which increases the dust removal costs of the drying system, pollutes the environment, and raises the risk of combustion and explosion, thereby posing a threat to the safety of the drying system. Moisture plays a crucial role in the structural damage of lignite particles during drying. In this study, lignite samples with moisture contents of 60%, 36%, and 18% were prepared and dried in hot air at 200 °C. The transfer behavior of moisture in the pore structure was investigated, and the evolution of the pore structure was observed. The relationship between pore structure evolution and moisture transfer behavior was correlated, and the mechanism of structural damage under the action of moisture during the drying process was proposed. The results demonstrated that the moisture in large pores was transported rapidly in the form of a gas–liquid mixture; the liquid moisture in the pores boiled into water vapor, and the water vapor pressure was the main reason for the destruction of the pore structure. For raw lignite, the total pore volume decreased sharply from 0.92 to 0.37 mL/g within the first 360 s of drying, and the fractal dimension dropped from 2.701 to 2.545, indicating severe pore collapse. However, the moisture in small pores migrated by molecular diffusion, which is nondestructive to the lignite structure. Full article

Detecting changes in the permittivities of materials has important applications in electronic information, materials science, biomedicine, and many other fields. However, existing detection methods are limited by factors such as sample thickness and resonance intensity, making it difficult to achieve sensitive dielectric constant detection at desired frequency bands. This paper proposes a method for detecting the dielectric constant changes in samples based on destructive interference of spoof surface plasmon polaritons (SSPPs) in a dual-path transmission structure, which forms a characteristic absorption peak at the SSPPs’ cutoff frequency. Specifically, by utilizing the dependence of the SSPPs’ phase on the periodic unit, a constant π phase difference is formed at the cutoff frequency through the periodic unit number difference between the two paths, resulting in a cutoff frequency absorption peak. When the sample is coated on the SSPPs’ dual-path structure, the boundary conditions are altered, leading to a cutoff frequency shift, thereby enabling dielectric constant detection at the specified frequency. Simulation results show that, with proper structural design, the normalized characteristic frequency shift reaches 10.8%/${\epsilon }_S$ and further demonstrates dramatic robustness against initial phase difference, sample thickness and sample loss. In summary, this work provides a novel high-precision and high-robustness method for detecting dielectric constant changes in samples at specified frequencies. Full article

The paper deals with the concept of how to regulate structure formation in the interfacial transition zone (ITZ) between the Ordinary Portland Cement (OPC) matrix and basalt to ensure the durability of basalt fiber-reinforced concretes. It has been demonstrated that the alkali–silica reaction (ASR) can be transformed from a destructive (negative) process into a constructive one in OPC concrete through activation by sodium water glass combined with the incorporation of an Al₂O₃-containing additive, namely metakaolin. Alkaline activation increased the compressive strength of OPC basalt fiber-reinforced concrete by 1.6–1.9 times. The formation of stable zeolite-like hydration products within the Na₂O-CaO-Al₂O₃-SiO₂-H₂O system promoted self-healing of the ITZ. This resulted in a 5.6-fold increase in ITZ microhardness compared to the cement matrix, as well as transforming expansion into shrinkage of concrete with a final value of 0.01 mm/m after 360 days. The structure-forming processes in the ITZ ensured a 1.14-fold increase in the compressive strength of 180-day alkali-activated OPC basalt fiber-reinforced concrete compared to its 30-day strength, in contrast to a 0.92-fold decrease in the strength of the non-modified OPC analog under conditions accelerating the development of ASR. Full article

Identifying primary ceramic forming techniques is often problematic when surface traces are altered or erased by secondary shaping on the potter’s wheel, particularly in vessels combining hand-building and wheel use. This study aims to develop a quantitative, non-destructive method to distinguish wheel-throwing and wheel-coiling techniques by analyzing internal fabric features. Experimental replicas of Middle Minoan handleless conical cups (18th cent. BC), produced using wheel-throwing-off-the-hump and wheel-coiling techniques, were investigated using X-ray micro-computed tomography (µCT). Macropores were segmented from complete 3D µCT datasets and their shape preferred orientation was quantitatively assessed through ellipsoid fitting, orientation distribution functions, and pole figure analysis. The results reveal systematic and reproducible differences between the two forming techniques: wheel-coiled vessels show predominantly horizontal pore elongation, expressed as equatorial girdle textures and vertically clustered short axes, whereas wheel-thrown vessels display inclined pore orientations, forming displaced girdles and ring-like short-axis distributions. These contrasting orientation patterns reflect distinct deformation fields imposed during vessel shaping. The study demonstrates that quantitative 3D analysis of pore orientation in whole vessels provides reliable criteria for identifying ceramic forming techniques and confirms previous qualitative observations. This approach offers a robust framework for technological analysis of ceramics and can be applied to both complete vessels and suitably oriented fragments. Full article

This study aims to evaluate the therapeutic efficacy of emodin (EMO) in rheumatoid arthritis (RA) and to verify whether its underlying mechanism involves the blockade of pathological angiogenesis via the inhibition of the nuclear factor-kappa B (NF-κB)/hypoxia-inducible factor-1α (HIF-1α)/vascular endothelial growth factor (VEGF) signaling axis. Bovine type II collagen-induced arthritis (CIA) mouse models and lipopolysaccharide (LPS)-stimulated EA.hy926 endothelial cells were utilized in this study. The effects of EMO on joint pathological alterations, the expression of NF-κB/HIF-1α/VEGF axis proteins, inflammatory cytokines (tumor necrosis factor-alpha (TNF-α), interleukin-6 (IL-6), and interleukin-1 beta (IL-1β)), and angiogenic capacity were assessed using histopathological analysis, Western blotting, immunohistochemistry (IHC), immunofluorescence, and tube formation assays. Furthermore, small interfering RNA (siRNA) interference targeting key molecules was employed to validate the molecular mechanisms underlying the therapeutic effects of EMO. In the CIA model group, the ankle joints of mice exhibited pronounced inflammatory infiltration, synovial hyperplasia, and bone destruction. Compared with the model group, both the EMO and methotrexate (MTX) treatment groups demonstrated attenuated synovial hyperplasia and cartilage destruction, along with significantly downregulated expression levels of key NF-κB pathway proteins, HIF-1α, and VEGF in joint tissues (p < 0.001). In vitro experiments revealed that EMO treatment significantly reduced the LPS-induced secretion of pro-inflammatory cytokines (TNF-α, IL-6, and IL-1β) (p < 0.001), and decreased both the number and total length of tubular structures formed by endothelial cells compared to the control (p < 0.001). Notably, siRNA-mediated knockdown of p65 resulted in decreased intracellular protein levels of HIF-1α and VEGF, accompanied by a significant reduction in tube formation (p < 0.001). This study demonstrates that EMO alleviates pathological damage in RA by inhibiting the activation of the NF-κB signaling pathway, which subsequently downregulates pathological angiogenesis and inflammatory responses mediated by the HIF-1α/VEGF axis. These findings provide a robust experimental basis for the potential application of EMO as a therapeutic agent for RA. Full article

Perovskite solar cells (PSCs) have quickly achieved certified energy conversion efficiency reaching a certified record of 27.3% for single-junction cells, while having a low mass, thin-film form factor and high specific power, which are attractive for space energy systems. However, their long-term reliability in extraterrestrial environments is not adequately ensured by terrestrial qualification routes, and standardized space-related test protocols remain insufficiently developed. This review critically summarizes the current understanding of the degradation of PSCs under the influence of key environmental factors in space—ionizing and non-ionizing radiation, thermal vacuum exposure and thermal cycling, and ultraviolet radiation AM0, as well as atmospheric oxygen in low orbits. The central task of the work is to develop and justify the need to create specialized PSCs test protocols for space applications, since existing ground standards do not reflect the multifactorial nature and extreme orbital loads. It has been shown that thermal vacuum accelerates ion migration, interphase reactions, and degassing, while AM0 UV and atomic oxygen introduce additional photochemical and oxidative mechanisms of destruction; at the same time, stressors often act synergistically and are not detected by single-factor tests. Next, the limitations of the current IEC and ISOS are discussed and an approach to their expansion is formulated through the ISOS-T-Space and ISOS-LC-Space protocols, which integrate high vacuum, AM0 lighting, extended temperature ranges and controlled particle irradiation. It is concluded that the development and interlaboratory validation of such space-oriented protocols is a key condition for the correct qualification of PSCs and targeted optimization of materials and interfaces to meet the requirements of space energy. Full article

Remote sensing enables the analysis of landscape dynamics; however, catastrophic disturbances create new surface conditions that are not adequately captured by retrospectively defined land-cover classes. This study addresses the challenge of temporally matching unsupervised classifications to monitor post-catastrophic floodplain dynamics on Khortytsia Island following the destruction of the Kakhovka Reservoir. Multi-temporal Sentinel-2 Level-2A data from 2022 to 2025 were processed using spectral indices, standardised within a common predictor space, and classified through unsupervised clustering. Cluster solutions from individual dates were then matched based on spectral similarity and spatial continuity, with their temporal interpretation guided by concepts of landscape memory and landscape perception. Higher-order spatiotemporal units were subsequently derived through contextual superclustering. The analysis identified 16 clusters across the study period, with 4 to 12 clusters represented on individual dates. Their temporal coordination enabled the distinction of higher-order units exhibiting contrasting dynamics, including directional trend, seasonal, and mixed types. The proposed framework facilitates the identification of newly formed surface states, their temporal coordination, and their integration into a hierarchical spatiotemporal model of post-catastrophic landscape change. Full article

To address the difficulty of directionally cutting thick, hard key strata in gob-side entry retaining using conventional blasting or hydraulic fracturing, this paper proposes a high-pressure water-jet slotting-induced pre-cracked weakening belt (PCWB) roof-cutting technology. Several finite-length PCWBs are arranged within the key stratum and designed to coalesce into a plane, inducing through-going roof failure along a pre-determined path. A fixed–fixed key strata beam model combined with linear elastic fracture mechanics shows that the double-belt configuration forces the bending moment and shear force to concentrate in a thin rock bridge, where bending and shear stresses are amplified by about 1.5–2.8 times and 1.2–1.7 times, respectively, for 2–4 m thick key strata, providing a mechanical basis for preferential tensile–shear failure. Two-dimensional RFPA2D simulations reveal “width-dominated, length-assisted” control of cutting performance and identify an optimal weakening belt geometry of about 400 mm in width and 200 mm in length. Three-dimensional numerical modeling of parallel slot pairs indicates that intra-pair spacing of about 40 mm produces a continuous, directional weakening belt, whereas smaller or larger spacing causes, respectively, destructive interference or loss of connectivity. High-pressure water-jet tests (320 MPa, 0.33 mm nozzle, 1.30 mm/s traverse speed) on limestone blocks confirm that single slots can penetrate the full thickness and that cracks from adjacent slots coalesce through the rock bridge, forming a wide, straight fracture band. Field application in the Dongjiang Mine (3.5 m limestone key stratum, ~400 m depth) shows that the first weighting is advanced from the 7th to the 3rd day, peak support resistance is reduced from 8.8 to 7.4 MPa, and periodic weighting becomes more frequent and smoother. The PCWB technology is therefore suitable for panels with 2–4 m thick hard key strata at similar depths, offering precise key stratum severance, active stress relief, and safe, controllable construction. Full article

Tornado is a localized, small-scale severe convective weather phenomenon characterized by extreme destructiveness. Tornado detecting and warning mainly rely on Doppler weather radar, which identifies and tracks tornadoes by recognizing the tornado vortex signature and supercells in radar data. Artificial intelligence technology has been applied to tornado recognition in recent years. However, existing monitoring methods, especially those using unsupervised learning algorithms, still have limited recognition accuracy and timely warning, and usually struggle to strike a balance between detection accuracy and false alarm rate. A novel tornado detection algorithm TDA-DARKNet has been proposed to address the aforementioned issues. The algorithm integrates a dual attention mechanism, dense residual connections, and Kolmogorov–Arnold network (KAN). A tornado dataset suitable for deep learning has been formed, which utilizes features including radial velocity, reflectivity, velocity spectrum width, differential reflectivity, and correlation coefficient in radar data. The TDA-DARKNet algorithm was trained and tested using the tornado dataset, and evaluated in tornado cases. The experimental results show that TDA-DARKNet improves the detection probability and extends the lead time to a maximum of 42 min in strong tornado situations, while achieving 97.11% accuracy, 95.08% precision, indicating strong overall identification performance. In addition, by directly leveraging radar-based data for tornado identification, the algorithm eliminates the need for manual feature engineering, simplifies data processing, reduces complexity, and further enhances detection effectiveness. Full article

Since September 2021, numerous seismic events with spectral peaks below 1 Hz occurred on the island of Vulcano, Italy, 131 years after its last eruption. The local monitoring network recorded microseismicity mostly in the form of months-long swarms, concurrent with anomalous values of other geophysical and geochemical parameters. By applying a machine learning technique (Self-Organizing Maps, SOMs), we obtained an inventory of ~6600 seismic signals, identifying and separating exogenous signals (anthropic noise) from distinct families of events. These families were located below La Fossa Crater (where the last eruption of the volcano happened) from the surface to a depth of 2.2 km b.s.l. Based on the seismic signature and source location of these events, we hypothesize unsealed/sealed processes through a network of shallow fractures favored by fluid pressure. After the return to background values of geochemical and geophysical parameters in 2023, a resumption of microseismicity occurred between May and June 2024. A test application of the SOM to the new data confirmed the non-destructive source of the new recorded signals, which shared families, location, and depths with our previous inventory. This test showed that SOM can be an effective tool for supporting real-time monitoring and warning of future unrest at Vulcano. Full article

Dam-break flows over erodible beds represent a complex fluid–solid interaction problem characterized by extreme turbulence and rapid morphological changes. This study investigates the dynamics of such flows over inclined granular beds by integrating an advanced Moving Particle Semi-implicit (MPS) method. To accurately resolve the transition between static and kinetic granular regimes, I introduce a state-dependent tangential friction model that explicitly distinguishes between sticking and sliding conditions based on local force balance. Furthermore, the momentum exchange between the fluid and solid phases is rigorously modeled using the porosity-dependent drag formulation. The numerical results demonstrate a distinct regime shift in energy dissipation: while low-inclination beds (0–$4\%$) promote distributed sediment transport, steep-inclination beds (8–$12\%$) trigger a localized “Shielding Effect”. In this regime, the surge’s horizontal kinetic energy is rapidly converted into vertical potential energy and frictional work, forming a deep sacrificial scour hole that acts as a topographical energy sink. This mechanism effectively mitigates the destructive potential of the surge in downstream areas. The proposed method provides a robust tool for predicting morphological feedback and designing topographical countermeasures for disaster mitigation in hydraulic and coastal environments. Full article

The Historical Lateral Mobility Zone (HLMZ) represents the portion of the alluvial plain occupied by the river channel over the last decades or centuries and represents the most flood-prone sector of the floodplain. Mapping Land-Use–Land Cover (LULC) changes within HLMZs helps reconstruct human-driven land-use dynamics and identify the areas potentially exposed to the highest flood risk. Among the rivers of Southern Italy, the Sele River is characterized by one of the largest mean annual discharges and has experienced extreme and destructive floods, such as those from 1935 and 2010. Over the last 150 years, it has also undergone remarkable channel adjustments, consisting of narrowing up to ~120 m, morphological changes, and riverbed degradation. In this study, LULC changes that occurred between 1988 and 2023 within the HLMZ of the Sele River, formed over the last 150 years, were analyzed and mapped in a GIS environment. Active channels were digitized from historical maps, topographic maps, and orthophotos to map the HLMZ. LULC changes were assessed through visual interpretation of orthophotos and Google Earth imagery in a GIS environment. Results show a transition, over 35 years towards more pristine conditions, with forest expansion, reduction in agricultural areas, and absence of further artificialization. LULC dynamics appear to be strictly controlled by an increased awareness of the high flood hazard within the HLMZ, with positive implications in terms of flood risk, which, however, should be further assessed quantitatively in future studies and, possibly, reduced, given the high proneness of the Sele River to destructive floods. Full article

Background: Respiratory syncytial virus (RSV) causes severe lung infections in infants and the elderly. The conserved central domain (CCD) of the RSV G protein is a key antigenic fragment for inducing protective antibodies. In this study, we used the hepatitis B surface antigen (HBsAg) as a platform to present this RSV G CCD fragment. Methods: We first sequenced and compared several HBsAg genotypes from clinical samples and selected one as an expression candidate for further development. The RSV G CCD was then inserted into the selected candidate to generate a recombinant expression construct. Subviral particles (SVPs) were produced using both CHO cells and yeast expression systems. Particle assembly was examined using electron microscopy. Finally, the safety and immunogenicity of the recombinant vaccine were evaluated in mice. Results: We successfully identified HBsAg38 as a potential recombinant vaccine expression candidate due to its abundant expression and secretion. The RSV G CCD fragment was inserted into the candidate and efficiently expressed in both CHO cells and yeast. The expressed protein was effectively secreted and formed uniform, spherical particles. The resulting vaccine candidate was safe for mice, causing no detectable weight loss or organ damage. Immunization with the recombinant SVPs elicited antibody responses against both HBsAg and the RSV G CCD. Upon intranasal RSV challenge, vaccinated mice exhibited markedly reduced RSV F protein and mRNA levels in lung tissues compared to PBS controls, with the yeast-derived SVP group showing the most pronounced reduction. Histopathological analysis further revealed that immunized mice had significantly less alveolar destruction and inflammatory cell infiltration than the control group, confirming that the vaccine conferred effective protection against RSV-induced lung pathology. Conclusions: We successfully developed a novel antigen-displaying HBsAg platform for generating vaccines targeting multiple pathogens. The RSV G CCD-expressing HBsAg induced a strong antibody response and provided effective protection against RSV infection. This platform offers a promising new approach for the development of next-generation vaccines. Full article

The concept of self-healing polymers has been prevalent over the last few decades. However, their performance and behaviour in structural applications in the form of layered composites have not been studied extensively. In this study, an attempt has been made to evaluate the recovery of the mechanical properties of Carbon Fibre-Reinforced Polymer composites (CFRPs) with an intrinsically healable polymeric resin system. Destructive tests, including static tensile, compression, and flexural tests, are carried out to evaluate their ability to recover mechanical compliance after healing. Nondestructive tests based on the Acousto-Ultrasonic (AU) approach are carried out to establish and distinguish the state of these composites. The results show that the tested self-healing CFRPs can recover their mechanical properties, particularly their flexural and compressive properties, after unstable matrix damage. On the other hand, the AU approach, supported by Machine Learning (ML) models, demonstrates that the damaged states and the heal states of these composites can be distinguished from the virgin state. Full article

In the field of forensic document examination, accurately determining the chronological sequence of intersecting lines between seal ink and handwriting is a crucial technical step for verifying document authenticity, identifying contract tampering, and detecting forged signatures. This technique analyzes the physical superimposition relationship formed by the deposition of the two media on the paper substrate to provide objective scientific evidence for judicial practice. Although traditional methods such as microscopic imaging and mass spectrometry analysis have achieved some progress, they still suffer from common limitations including high equipment costs, complex operation, and potential damage to samples. This study proposes and validates an innovative non-destructive determination method that integrates structured light 3D reconstruction technology with deep learning algorithms. The research captures the microscopic 3D morphological features of the ink intersection area using a high-precision structured light scanning system and effectively eliminates noise interference caused by paper substrate undulation through Gaussian flattening technology. Subsequently, a multimodal fusion strategy combines 2D texture images with 3D depth information to construct a dataset rich in features. On this basis, a deep learning model based on an improved Residual Neural Network (ResNet) is designed, incorporating the ELU activation function and an EMA mechanism to enhance the model’s feature extraction capability and convergence stability. Experimental results demonstrate that the proposed method achieves a recognition accuracy of 94.39% on the test set, fully validating its effectiveness and application potential in the non-destructive determination of ink stroke sequencing. Full article