Search Results (1,193)

To address the inefficiency of traditional concrete crack detection methods and the heavy reliance of supervised learning on extensive labeled data, in this study, an intelligent assessment method of concrete damage based on pseudo-label semi-supervised learning and fractal geometry theory is proposed to solve two core tasks: one is binary classification of pixel-level cracks, and the other is multi-category assessment of damage state based on crack morphology. Using three-channel RGB images as input, a dual-path collaborative training framework based on U-Net encoder–decoder architecture is constructed, and a binary segmentation mask of the same size is output to achieve the accurate segmentation of cracks at the pixel level. By constructing a dual-path collaborative training framework and employing a dynamic pseudo-label refinement mechanism, the model achieves an F1-score of 0.883 using only 50% labeled data—a mere 1.3% decrease compared to the fully supervised benchmark DeepCrack (F1 = 0.896)—while reducing manual annotation costs by over 60%. Furthermore, a quantitative correlation model between crack fractal characteristics and structural damage severity is established by combining a U-Net segmentation network with the differential box-counting algorithm. The experimental results demonstrate that under a cyclic loading of 147.6–221.4 kN, the fractal dimension monotonically increases from 1.073 (moderate damage) to 1.189 (failure), with 100% accuracy in damage state identification, closely aligning with the degradation trend of macroscopic mechanical properties. In complex crack scenarios, the model attains a recall rate (Re = 0.882), surpassing U-Net by 13.9%, with significantly enhanced edge reconstruction precision. Compared with the mainstream models, this method effectively alleviates the problem of data annotation dependence through a semi-supervised strategy while maintaining high accuracy. It provides an efficient structural health monitoring solution for engineering practice, which is of great value to promote the application of intelligent detection technology in infrastructure operation and maintenance. Full article

In recent years, research on plant disease detection has combined artificial intelligence, hyperspectral imaging, unmanned aerial vehicle remote sensing, and other technologies, promoting the transformation of pest and disease control in smart agriculture towards digitalization and artificial intelligence. This review systematically elaborates on the research status of non-destructive detection techniques used for plant disease identification and detection, mainly introducing the following two types of methods: spectral technology and imaging technology. It also elaborates, in detail, on the principles and application examples of each technology and summarizes the advantages and disadvantages of these technologies. This review clearly indicates that non-destructive detection techniques can achieve plant disease and pest detection quickly, accurately, and without damage. In the future, integrating multiple non-destructive detection technologies, developing portable detection devices, and combining more efficient data processing methods will become the core development directions of this field. Full article

Although Hylocereus polyrhizus pulp residues polysaccharides (HPPP) have shown potential in improving metabolic disorders and intestinal barrier function, the mechanism by which they exert their effects through regulating O-glycosylation modifications in the mucus layer remains unclear. Therefore, this study established a HFD-induced obese colitis mouse model (n = 5 per group) and combined nano-capillary liquid chromatography-tandem mass spectrometry (nanoLC-MS/MS) technology to quantitatively analyze the dynamic changes in O-glycosylation. Additionally, through quantitative O-glycosylation proteomics and whole-proteome analysis, we identified 155 specifically altered O-glycosylation sites in colon tissue, with the glycosylation modification level of the MUC2 core protein increased by approximately 2.1-fold. The results indicate that HPPP alleviates colonic mucosal damage by regulating interactions between mucus O-glycosylation. Overall, we demonstrated that HPPP increases HFD-induced O-glycosylation sites, improves intestinal mucosal structure in obese mice, and provides protective effects against obesity-induced intestinal mucosal damage. Full article

This study comprehensively compares the performance of two non-destructive testing (NDT) techniques—active thermography (AT) and digital shearography (DS)—for identifying various damage types in composite structures. Three distinct composite specimens were inspected: a carbon-fiber-reinforced polymer (CFRP) plate with flat-bottom holes, an aluminum honeycomb core sandwich plate with a circular skin-core disbond, and a CFRP plate with two low-energy impacts damage. The research highlights the significant role of post-processing methods in enhancing damage detectability. For AT, algorithms such as fast Fourier transform (FFT) for temperature phase extraction and principal component thermography (PCT) for identifying significant temperature components were employed, generally making anomalies brighter and easier to locate and size. For DS, a novel band-pass filtering approach applied to phase maps, followed by summing the filtered maps, remarkably improved the visualization and precision of damage-induced anomalies by suppressing background noise. Qualitative image-based comparisons revealed that DS consistently demonstrated superior performance. The sum of DS filtered phase maps provided more detailed and precise information regarding damage location and size compared to both pulsed thermography (PT) and lock-in thermography (LT) temperature phase and amplitude. Notably, DS effectively identified shallow flat-bottom holes and subtle imperfections that AT struggled to clearly resolve, and it provided a more comprehensive representation of the impacts damage location and extent. This enhanced capability of DS is attributed to the novel phase map filtering approach, which significantly improves damage identification compared to the thermogram post-processing methods used for AT. Full article

Aramid fibre has become a critical material for individual soft body armour due to its lightweight nature and exceptional impact resistance. To investigate its energy absorption mechanism, quasi-static and dynamic tensile experiments were conducted on Kevlar^® 29 plain-woven fabric using a universal material testing machine and a Split Hopkinson Tensile Bar (SHTB) apparatus. Tensile mechanical responses were obtained under various strain rates. Fracture morphology was characterised using scanning electron microscopy (SEM) and ultra-depth three-dimensional microscopy, followed by an analysis of microstructural damage patterns. Considering the strain rate effect, a viscoelastic constitutive model was developed. The results indicate that the tensile mechanical properties of Kevlar^® 29 plain-woven fabric are strain-rate dependent. Tensile strength, elastic modulus, and toughness increase with strain rate, whereas fracture strain decreases. Under quasi-static loading, the fracture surface exhibits plastic flow, with slight axial splitting and tapered fibre ends, indicating ductile failure. In contrast, dynamic loading leads to pronounced axial splitting with reduced split depth, simultaneous rupture of fibre skin and core layers, and fibrillation phenomena, suggesting brittle fracture characteristics. The modified three-element viscoelastic constitutive model effectively captures the strain-rate effect and accurately describes the tensile behaviour of the plain-woven fabric across different strain rates. These findings provide valuable data support for research on ballistic mechanisms and the performance optimisation of protective materials. Full article

Background: Despite distinct etiologies, type 1 diabetes (T1D) and type 2 diabetes (T2D) share chronic inflammation as a core feature. Interleukins, key immune mediators, play important yet still not fully understood roles in the development and complications of both conditions. Objective: This narrative review aims to provide a comprehensive and critical synthesis of current evidence on the role of key interleukins in T1D and T2D, highlighting their immunological functions, genetic associations, clinical correlations, and translational potential. Methods: A targeted literature search was conducted in PubMed, Google Scholar, and ScienceDirect up to January 2025, focusing on English-language clinical and experimental studies involving interleukins and their relevance to T1D and T2D. Reference lists were manually screened for additional sources. Interleukins (ILs) were reviewed individually to assess their immunobiology, disease specificity, and biomarker or therapeutic value. Findings: Pro-inflammatory cytokines such as IL-1β, IL-6, and IL-17 contribute to islet inflammation, insulin resistance, and microvascular damage in both T1D and T2D. Anti-inflammatory mediators including IL-4, IL-10, and IL-13 exhibit protective effects but vary in expression across disease stages. Less-characterized interleukins such as IL-3, IL-5, IL-9, and IL-27 demonstrate dual or context-dependent roles, particularly in shaping immune tolerance and tissue-specific complications such as nephropathy and neuropathy. Polymorphisms in IL-10 and IL-6 genes further suggest genetic contributions to interleukin dysregulation and metabolic dysfunction. Despite promising insights, translational gaps persist due to overreliance on preclinical models and limited longitudinal clinical data. Conclusions: Interleukins represent a mechanistic bridge linking immune dysregulation to metabolic derangements in both T1D and T2D. While their diagnostic and therapeutic potential is increasingly recognized, future research must address current limitations through isoform-specific targeting, context-aware interventions, and validation in large-scale, human cohorts. A unified interleukin-based framework may ultimately advance personalized strategies for diabetes prevention and treatment. Full article

As the core device for protecting the safety of the pressure-bearing system, the spring full-open safety valve is prone to various forms of valve seat sealing surface damage after long-term opening and closing impact, corrosion, and medium erosion, which may lead to internal leakage. In view of the problems that the high-frequency acoustic emission signal of the internal leakage of the safety valve has, namely, a large number of energy-overlapping areas in the frequency domain, the overall signal presents broadband characteristics, large noise content, and no obvious time–frequency characteristics. A composite denoising method, IWTD, improved wavelet threshold function with dual adjustable factors, and the improved VMD algorithm is proposed. In view of the problem that the optimal values of the dual adjustment factors a and b of the function are difficult to determine manually, an improved dung beetle optimization algorithm is proposed, with the maximum Pearson coefficient as the optimization target; the optimization is performed within the value range of the dual adjustable factors a and b, so as to obtain the optimal value. In view of the problem that the key parameters K and α in VMD decomposition are difficult to determine manually, the maximum Pearson coefficient is taken as the optimization target, and the improved dung beetle algorithm is used to optimize within the value range of K and α, so as to obtain the IVMD algorithm. Based on the IVMD algorithm, the characteristic decomposition of the internal leakage acoustic emission signal occurs after the denoising of the IWTD function is performed to further improve the denoising effect. The results show that the Pearson coefficients of all types of internal leakage acoustic emission signals after IWTD-IVMD composite noise reduction are greater than 0.9, which is much higher than traditional noise reduction methods such as soft and hard threshold functions. Therefore, the IWTD-IVMD composite noise reduction method can extract more main features out of the measured spring full-open safety valve internal leakage acoustic emission signals, and has a good noise reduction effect. Feature recognition after noise reduction can provide a good evaluation for the safe operation of the safety valve. Full article

Using common corn stalks as raw materials, a functional dense-structured carbon microsphere with good elastic deformation and certain rigid support was modified from biomass through a step-by-step hydrothermal method. The composition, thermal stability, fluid-loss reduction performance, and reservoir protection performance of the modified carbon microspheres were studied. Research indicates that after hydrothermal treatment, under the multi-level structural action of a small amount of proteins in corn stalks, the naturally occurring cellulose, polysaccharide organic compounds, and part of the ash in the stalks are adsorbed and encapsulated within the long-chain network structure formed by proteins and cellulose. By attaching silicate nanoparticles with certain rigidity from the ash to the relatively stable chair-type structure in cellulose, functional dense-structured carbon microspheres were ultimately prepared. These carbon microspheres could still effectively reduce fluid loss at 200 °C. The permeability recovery value of the cores treated with modified biomass carbon microspheres during flowback reached as high as 88%, which was much higher than that of the biomass itself. With the dense network-like chain structure supplemented by small-molecule aldehydes and silicate ash, the subsequent invasion of drilling fluid was successfully prevented, and a good sealing effect was maintained even under high-temperature and high-pressure conditions. Moreover, since this functional dense-structured carbon microsphere achieved sealing through a physical mechanism, it did not cause damage to the formation, showing a promising application prospect. Full article

Channeling in cementing causes interlayer interference, severely restricting oilfield recovery. Existing channeling plugging agents, such as cement and gels, often lead to reservoir damage or insufficient strength. Oil-soluble resin (OSR) particles show great potential in selective plugging of channeling fractures due to their excellent oil solubility, temperature/salt resistance, and high strength. However, their application is limited by the efficient filling and retention in deep fractures. This study innovatively combines the OSR particle plugging system with the mature rapid filtration loss plugging mechanism in drilling, systematically exploring the influence of particle size and sorting on their filtration, packing behavior, and plugging performance in channeling fractures. Through API filtration tests, visual fracture models, and high-temperature/high-pressure (100 °C, salinity 3.0 × 10⁵ mg/L) core flow experiments, it was found that well-sorted large particles preferentially bridge in fractures to form a high-porosity filter cake, enabling rapid water filtration from the resin plugging agent. This promotes efficient accumulation of OSR particles to form a long filter cake slug with a water content <20% while minimizing the invasion of fine particles into matrix pores. The slug thermally coalesces and solidifies into an integral body at reservoir temperature, achieving a plugging strength of 5–6 MPa for fractures. In contrast, poorly sorted particles or undersized particles form filter cakes with low porosity, resulting in slow water filtration, high water content (>50%) in the filter cake, insufficient fracture filling, and significantly reduced plugging strength (<1 MPa). Finally, a double-slug strategy is adopted: small-sized OSR for temporary plugging of the oil layer injection face combined with well-sorted large-sized OSR for main plugging of channeling fractures. This strategy achieves fluid diversion under low injection pressure (0.9 MPa), effectively protects reservoir permeability (recovery rate > 95% after backflow), and establishes high-strength selective plugging. This study clarifies the core role of particle size and sorting in regulating the OSR plugging effect based on rapid filtration loss, providing key insights for developing low-damage, high-performance channeling plugging agents and scientific gradation of particle-based plugging agents. Full article

To improve environmental sustainability and operational safety in maritime industries, the development of efficient methods for removing biofouling from submerged surfaces is critical. This study investigates the erosion mechanisms of cavitation jets as a non-contact, high-efficiency method for detaching marine organisms, including bacteria and larvae, from ship hulls and underwater infrastructure. Through erosion experiments on coated specimens, variations in jet morphology, and flow visualization using the Schlieren method, we examined how factors such as jet incident angle and nozzle configuration influence removal performance. The results reveal that erosion occurs not only at the direct jet impact zone but also in regions where cavitation bubbles exhibit intense motion, driven by pressure fluctuations and shock waves. Notably, single-hole jets with longer potential cores produced more concentrated erosion, while multi-jet interference enhanced bubble activity. These findings underscore the importance of understanding bubble distribution dynamics in the flow field and provide insight into optimizing cavitation jet configurations to expand the effective cleaning area while minimizing material damage. This study contributes to advancing biofouling removal technologies that promote safer and more sustainable maritime operations. Full article

Emergency material scheduling (EMS) is a core component of post-disaster emergency response, with its efficiency directly impacting rescue effectiveness and the satisfaction of affected populations. However, due to severe road damage, limited availability of resources, and logistical challenges after disasters, current EMS practices often suffer from uneven resource distribution. To address these issues, this paper proposes a priority-based, multi-stage EMS approach with drone coordination. First, we construct a three-level EMS network “storage warehouses–transit centers–disaster areas” by integrating the advantages of large-scale transportation via trains and the flexible delivery capabilities of drones. Second, considering multiple constraints, such as the priority level of disaster areas, drone flight range, transport capacity, and inventory capacities at each node, we formulate a bilevel mixed-integer nonlinear programming model. Third, given the NP-hard nature of the problem, we design a hybrid algorithm—the Tabu Genetic Algorithm combined with Branch and Bound (TGA-BB), which integrates the global search capability of genetic algorithms, the precise solution mechanism of branch and bound, and the local search avoidance features of Tabu search. A stage-adjustment operator is also introduced to better adapt the algorithm to multi-stage scheduling requirements. Finally, we designed eight instances of varying scales to systematically evaluate the performance of the stage-adjustment operator and the Tabu search mechanism within TGA-BB. Comparative experiments were conducted against several traditional heuristic algorithms. The experimental results show that TGA-BB outperformed the other algorithms across all eight test cases, in terms of both average response time and average runtime. Specifically, in Instance 7, TGA-BB reduced the average response time by approximately 52.37% compared to TGA-Particle Swarm Optimization (TGA-PSO), and in Instance 2, it shortened the average runtime by about 97.95% compared to TGA-Simulated Annealing (TGA-SA).These results fully validate the superior solution accuracy and computational efficiency of TGA-BB in drone-coordinated, multi-stage EMS. Full article

Intestinal inflammation involves barrier impairment, immune hyperactivation, and oxidative stress imbalance. Bioactive polysaccharides universally alleviate inflammation via anti-inflammatory, antioxidant, and microbiota-modulating effects, yet exhibit distinct core mechanisms. Elucidating these differences is vital for targeted polysaccharide applications. This research examines distinct regulatory pathways through which diverse bioactive polysaccharides mitigate lipopolysaccharide-triggered intestinal inflammation in male Kunming (KM) mice. This experiment employed Lentinula edodes polysaccharide (LNT), Auricularia auricula polysaccharide (AAP), Cordyceps militaris polysaccharide (CMP), Lycium barbarum polysaccharide (LBP), and Brassica rapa polysaccharide (BRP). The expression levels of biomarkers associated with the TLR4 signaling pathway, oxidative stress, and intestinal barrier function were quantified, along with comprehensive gut microbiota profiling. The results showed that all five polysaccharides alleviated inflammatory responses in mice by inhibiting inflammatory cytokine release, reducing oxidative damage, and modulating gut microbiota, but their modes of action differed: LBP significantly suppressed the TLR-4/MyD88 signaling pathway and its downstream pro-inflammatory cytokine expression, thereby blocking inflammatory signal transduction and reducing oxidative damage; LNT and CMP enhanced the body’s antioxidant capacity by increasing antioxidant enzyme activities and decreasing malondialdehyde (MDA) levels; AAP and BRP enriched Akkermansia (Akk.) within the Verrucomicrobia (Ver.) phylum, upregulating tight junction protein expression to strengthen the intestinal mucosal barrier and indirectly reduce oxidative damage. This research demonstrates that different polysaccharides alleviate inflammation through multi-target synergistic mechanisms: LBP primarily inhibits inflammatory pathways; AAP and BRP focus on intestinal barrier protection and microbiota modulation; and LNT and CMP exert effects via antioxidant enzyme activation. These data support designing polysaccharide blends that leverage complementary inflammatory modulation mechanisms. Full article

In order to verify the rationality and feasibility of a demountable and replaceable fabricated RC beam with bolted connection under mid-span compression, one cast-in-place RC beam and four fabricated RC beams were designed and fabricated. Through the mid-span static loading test and analysis of five full-scale RC beams, the effects of high-strength bolt specifications and stiffeners were compared, and the behavior of the fabricated RC beams with bolted connections was analyzed. The test process was observed and the test results were analyzed. The failure mode, cracking load, yield load, ultimate load, stiffness change, deflection measured value, ductility, and other indicators of the specimens were compared and analyzed. It was shown that the failure mode of the fabricated RC beam was reinforcement failure, which met the three stress stages of the normal section bending of the reinforcement beam. The failure position occurred at 10~15 cm of the concrete outside the bolt connection, and the beam support and the core area of the bolt connection were not damaged. The fabricated RC beam has good mechanical performance and high bearing capacity. In addition, comparing the test value with the simulation value, it is found that they are in good agreement, indicating that ABAQUS software of 2024 can be well used for the simulation analysis of the behavior of fabricated RC beam structure. Full article

As a core component of a fully automatic pepper transplanter, the performance of the seedling-picking mechanism is of particular significance. However, existing seedling-picking mechanisms have problems such as being prone to damaging the seedling roots and substrate, as well as having poor stability. To develop a highly efficient, stable, and minimally damaging seedling-picking mechanism, this study proposed a design scheme for a stem-clamping-and-pulling-out-type seedling-picking end actuator driven by a non-circular gear system. The specific methods and objectives include the following: (1) designing a differential non-circular gear system to replicate a manual picking trajectory accurately; (2) establishing a kinematic model and developing optimization software to determine the optimal parameter combination; (3) experimentally validating the mechanism’s performance through virtual simulations and bench tests. The bench tests showed that the mechanism could complete two seedling-picking operations per rotation, extracting an entire row (eight plants) in a single rotation at a speed of 30 r/min. The measured angles of the end effector at four key postures were highly consistent with simulation and high-speed camera data, with all key posture errors less than 1°. These results demonstrate the mechanism’s high accuracy, efficiency, and reliability. Full article

The turbine rotor is a core component in many energy conversion systems, where it is subjected to loads such as aerodynamic and centrifugal forces that make it highly susceptible to damage. Consequently, the reliability of the turbine rotor ranks among the key aspects of concern. This paper proposes an efficient approach based on the kriging model to conduct the reliability analysis of a turbine rotor. First, a parametric model of the turbine rotor was established. This parametric model was subsequently applied in a multifactor fluid–structure interaction model used to analyze the working performance of the turbine rotor. Finally, a kriging surrogate model was built and applied using these data in combination with various reliability analysis methods to analyze the structural reliability and reliability sensitivities of the turbine rotor. Furthermore, the reliability sensitivity results indicated that the outlet pressure had the greatest impact on rotor reliability. Thus, the proposed method was shown to have practical application value in the reliability analysis of the rotor structure. Full article