Search Results (172)

Banana Fusarium wilt, caused by Fusarium oxysporum f. sp. cubense tropical race 4 (Foc TR4), poses a significant threat to global banana production; however, effective and sustainable control strategies remain limited. Extracellular self-DNA (esDNA), which functions as a damage-associated molecular pattern (DAMP), has recently been identified as a crucial regulator of plant innate immunity. Nonetheless, it is unclear whether the immune regulatory function of esDNA varies with disease progression. In this study, we examined the effects of esDNA derived from banana leaves exhibiting different disease severities on plant resistance to Fusarium wilt. Hydroponic experiments revealed that esDNA displayed a distinct disease-stage-dependent regulatory pattern. EsDNA from mildly diseased tissues significantly suppressed Foc TR4 colonization, supported plant growth, and mitigated oxidative damage, whereas esDNA from severely dise ased tissues lost protective effects and even intensified cellular stress. Physiological analyses indicated that beneficial esDNA effectively reduced H₂O₂ and malondialdehyde accumulation while enhancing antioxidant enzyme activities and phenylpropanoid metabolism. Transcriptome profiling further demonstrated that esDNA extensively altered pathogen-induced gene expression, with enrichment of pathways involved in metabolic and redox homeostasis. These transcriptional changes correlate with the observed reduction in oxidative damage and improved plant growth, suggesting that restoration of homeostasis may contribute to esDNA-mediated resistance. Our findings collectively demonstrate that esDNA serves as a dynamic DAMP signal, exhibiting effects that depend on the disease stage. This study offers new insights into the role of plant self-DNA in mediating immunity and presents a promising strategy for developing environmentally sustainable control measures against banana Fusarium wilt. Full article

Dissolved gas analysis (DGA) is an essential technique for the fault diagnosis and condition monitoring of oil-immersed power transformers. Among various characteristic gases, acetylene (C₂H₂) is a key indicator of high-energy discharge and arc faults. In this work, a high-sensitivity dissolved acetylene detection system is developed based on clamp-type quartz-enhanced photoacoustic spectroscopy (QEPAS). A specially designed clamp-type quartz tuning fork (Clamp-type QTF) is employed as the acoustic transducer to improve acoustic coupling efficiency and optical alignment tolerance. Compared with conventional standard quartz tuning forks, the clamp-type structure exhibits enlarged acoustic interaction volume, lower damping loss, and higher signal collection capability. A near-infrared distributed feedback (DFB) laser operating at 1531.6 nm is used as the excitation source. The dissolved gas is extracted from transformer oil using a headspace degassing module and introduced into the QEPAS cell for real-time measurement. Experimental results showed that the developed system achieves a 1σ-based SNR-estimated detection limit of 17 ppb at a 50 s integration time, derived from the continuous measurement of 0.75 ppm C₂H₂, with excellent linearity in the concentration range from 100 ppm to 500 ppm. The measured concentration of dissolved acetylene in transformer oil is in good agreement with gas chromatography (GC), validating the effectiveness and practical applicability of the proposed system. Full article

In the classical Stochastic Subspace Identification (SSI) method, mode selection is primarily based on frequency stability, damping stability, and mode shape similarity using the Modal Assurance Criterion (MAC). However, these criteria are often insufficient for reliable modal identification in high-noise environments. This study advances beyond the classical approach by introducing a multi-criteria optimization framework for mode evaluation. In addition to the conventional frequency and damping assessments utilized in the classical SSI method, the proposed approach incorporates a range of supplementary structural metrics. These include Density, Cosine Similarity Difference (CSD), Damping Stability (DS), Spatial Roughness (SR), Mode Shape Complexity (MSC), Signal Energy Coherence (SEC), and Normalized Modal Difference (NMD). These metrics are computed within specifically optimized windows on the stabilization diagram. By integrating spatial, phase, and energy-based characteristics of mode shapes alongside traditional metrics such as the MAC, the method enables a more comprehensive and robust mode selection process that surpasses the limitations of relying solely on frequency and damping stability. Compared to the classical SSI, the optimized window approach provides a significant advantage by enabling the reliable selection of consistent modes by considering the continuity and multi-criteria coherence of modes across window transitions. As a result, the elimination of noise modes and the reliable separation of structural modes are established on a more systematic basis. To achieve this, a two-stage optimization strategy is implemented: the first stage determines the optimal frequency window width and minimum mode count threshold, while the second stage utilizes a Multi-Criteria Decision Making (MCDM) framework based on the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) algorithm to assign optimized weights to the structural metrics and rank the candidate windows accordingly. As a result, the ideal frequency window is identified based on its TOPSIS score and subsequently validated using the MAC, confirming that the selected window corresponds to reliable structural modes. The framework is validated using long-term in situ measurements from a Roller Compacted Concrete (RCC) dam operating under significant environmental and operational noise. The dataset comprises continuous, high-resolution (200 Hz) vibration recordings collected between 1 July 2023 and 30 October 2024. While the calendar duration is limited to several weeks, the uninterrupted 24 h measurements yield a high-density time-series dataset with substantial information content, enabling a statistically meaningful and robust evaluation of modal identification performance under real-world and noisy conditions. The results reveal that relying solely on traditional selection criteria such as pole density and the MAC can often lead to the identification of spurious modes, particularly in noisy environments. In contrast, the proposed TOPSIS-based multi-criteria decision-making framework incorporates a broader range of structural indicators, balancing frequency, damping, spatial, and energy-related metrics to enhance the consistency and reliability of mode selection. This approach proved effective even under high-noise conditions, successfully distinguishing true structural modes from artificial ones. Application of the TOPSIS method to RCC dam data revealed consistent fundamental frequencies at approximately 5–10 Hz, 10 Hz, and 15 Hz, confirming its robustness and suitability for complex structural monitoring tasks. Full article

As core vibration-damping components in rail transportation and aerospace, elastic supports are vital to equipment operational safety and maintenance cost control. Addressing the offline cumbersomeness and insufficient accuracy of traditional methods, as well as the poor adaptability of existing models to nonlinear damage and small samples, this study proposes a high-precision life prediction method based on a self-constructed full-life dataset and optimized random forest (RF). A self-developed triaxial vibration test bench was used to conduct accelerated aging tests on rubber–metal composite elastic supports, constructing a unique full-life dataset (412 valid samples) by collecting vibration signals via accelerometers and eddy current sensors. After extracting features like acceleration RMS and natural frequency, core damage-sensitive features were screened through PCA and Pearson correlation coefficients. The RF was optimized with a time-decaying factor and feature and parameter joint optimization to capture temporal degradation and resist overfitting. Experimental results show that the model achieves RMSE = 0.026 and R² = 0.988, significantly outperforming Gray Prediction, BP Neural Network, and XGBoost. It accurately captures the life evolution law of elastic supports, providing reliable technical support for online life prediction and predictive maintenance. Full article

Sunflower downy mildew, caused by Plasmopara halstedii, remains one of the most destructive diseases worldwide. The genetic diversity of P. halstedii populations continues to challenge resistance breeding efforts. This study evaluates the effectiveness of key resistance genes against P. halstedii isolates collected in Hungary. Eight isolates were tested using the sunflower differential lines HA-335, RHA-419, and RHA-340, with the resistance genes Pl6, Pl_Arg, and Pl8, respectively. Disease development was assessed by observing sporulation and symptoms including stunting, chlorosis, damping-off, and abnormal development at three time points after inoculation. Plant height was also measured to evaluate growth responses. The Pl6 resistance gene (HA-335) did not provide effective protection against any of the tested isolates, indicating that Pl6 does not confer reliable resistance against the Hungarian isolates examined in this study. The resistance conferred by Pl8 was not uniformly effective against the Hungarian isolates tested. This study provides the first report of Pl8-virulent P. halstedii isolates identified in both Hungary and Central Europe. The resistance gene Pl_Arg (RHA-419) conferred resistance to all tested P. halstedii isolates. These findings highlight the changing virulence profiles of P. halstedii populations in Hungary, emphasizing the need for ongoing pathogen monitoring and strategic use of resistance genes. Full article

Noble metal nanostructures provide versatile platforms for light manipulation through localized surface plasmon resonances (LSPRs). Among them, triangular silver nanoplates (AgNPTs) exhibit strong field-enhancement and spectral tunability, yet assembling them reproducibly on solids is challenging. We report a two-step functionalization strategy for constructing ordered AgNPT dimers on silica substrates, combining 3-aminopropyltriethoxysilane (APTES) anchoring with 1,4-butanedithiol bridging. AFM reveals face-to-face dimers with well-defined sub-nanometer gaps. Large-area AFM statistics collected over multiple regions (N = 80 nanoplates per condition) confirm reproducible and selective vertical dimerization. Extinction spectroscopy reveals sequential dielectric and coupling effects: thiol adsorption red-shifts the main resonance from 700 to 780 nm because of increased local refractive index and near-field damping, whereas dimerization partially restores it to ≈750 nm, consistent with plasmon hybridization within rigid ∼0.7 nm molecular gaps, where nonclassical moderation may occur but classical hybridization fully explains the observed shifts. Concomitantly, the extinction intensity doubles, following an exponential growth toward saturation during assembly. Surface-enhanced Raman scattering (SERS) measurements using 4-mercaptobenzoic acid (4-MBA) confirm a fourfold increase in the SERS enhancement factor from monolayer to bilayer, consistent with near-field coupling and hotspot formation at interplate junctions. Quantitative plasmon sensitivity analysis yields comparable results between experiments and finite-difference-time-domain simulations, confirming that the observed spectral shifts arise from near-field coupling and dielectric modulation rather than ensemble effects. This reproducible methodology enables precise tuning of NPT orientation, spacing, and optical response, providing a robust platform for enhanced sensing, SERS, and nanophotonic device engineering. Full article

Atractylodes macrocephala (A.M.) is a traditional Chinese medicinal and edible herb renowned for its spleen-tonifying, dampness-resolving, diuretic, and antiperspirant properties. Its primary bioactive constituents are terpenoids, which have demonstrated anti-inflammatory, antitumor, and immunomodulatory activities. However, transcriptomic studies focusing on terpenoid biosynthesis in A.M. from different geographical origins remain limited. To investigate the molecular mechanisms underlying differential sesquiterpenoid production, we performed transcriptome sequencing on samples collected from four distinct regions in China. Sesquiterpenoid biosynthesis predominantly proceeds through the mevalonate (MVA) and methylerythritol phosphate (MEP) pathways. Comparative analysis revealed four key enzyme-encoding genes—HMGCR, ISPF, GCPE, and FDPS—whose differential expression patterns were further validated by quantitative real-time PCR (qRT-PCR). Samples from Shaanxi exhibited the highest upregulation of biosynthetic genes and the greatest enrichment of terpene-related metabolites, suggesting enhanced pharmacological potential. In contrast, samples from Fujian, Anhui, and Hebei displayed relatively lower activity, with only FDPS upregulated in the Hebei sample. High-performance liquid chromatography (HPLC) quantification confirmed regional differences in the levels of major terpenoids—including atractylodin, atractylenolide I, and atractylenolide III—which correlated well with the observed gene expression profiles. This study compared conspecific A.M. from different geographical regions and further revealed that the variation in terpenoid metabolites is closely related to environmental factors. These findings provide a theoretical basis for the further discovery of functional genes and offer important implications for the quality control of A.M. Full article

The mechanical vibrations that occur in agricultural machinery, arising from terrain irregularities or the moving parts of the machine, can harm the operators when they are subjected to work for many hours daily over a period of many years. Excessive exposure to mechanical vibrations often causes low back pain and musculoskeletal problems, and may harm some organs in the human body. In this way, the present research includes the monitoring of four data collection points, considering the front and rear axles of a sprayer, the operator cabin floor and the operator seat in a self-propelled sprayer. The vibration transmissibility between these points is used to measure the vibration severity to which the operator is exposed under different forward speeds and tire inflation pressure conditions. The RMS acceleration levels for both the cabin floor and the operator’s seat were classified as “uncomfortable” and “very uncomfortable” for a workload of 8 h according to the ISO 2631-1, which indicates that the vibration levels that affect the agricultural machinery operator should be reduced. The vibration transmissibility was greater than 1 when measured between the rear axle and the floor of the operating cabin. The vibration transmissibility from the floor to the seat was lower than 1 in all scenarios evaluated, which indicates that seat damping is effective since the vibration severity that affects the operator seat is lower than the vibration severity of the cabin floor. Full article

This study investigates the vibration response and energy transfer characteristics of walnut trees in mechanical vibration harvesting, aiming to improve fruit detachment efficiency and reduce structural damage. Three walnut tree architectures were classified based on branching height, trunk stiffness, canopy size, and geometric regularity. A dynamic model of the trunk was established, modeled as an equivalent conical beam with Rayleigh damping, and the clamping point was simplified to a single-degree-of-freedom system. To quantify energy transfer, three indicators were introduced: energy transfer coefficient, energy attenuation rate, and trunk overload index (OLI). Sweep-frequency experiments (9–17 Hz) were conducted at a clamping height of 80 cm. Triaxial acceleration responses were measured, and branch kinetic energy was calculated. The model-predicted natural frequencies matched the experimental acceleration peaks well, identifying a frequency-sensitive band between 15 and 17 Hz. Significant differences in energy distribution were observed among the three tree architectures. Tree 1 exhibits intense energy concentration near the trunk, with rapid energy decay along branches and the highest canopy vibration index (OLI: 6.13), indicating the highest trunk overload risk. Tree 2 demonstrates whole-tree coordinated vibration and the lowest OLI value (2.10). Tree 3 possesses two sensitive frequency bands with relatively uniform energy distribution and an OLI of 2.89. Trunk stiffness, branching height, canopy structure, and geometric irregularities collectively determine energy distribution within resonance bands and overload risk. The proposed energy metrics and OLI provide quantitative guidance for selecting excitation frequencies and controlling operational duration during walnut vibration harvesting. Full article

Viscoelastic (VE) dampers are widely used for structural response control, but broader engineering adoption is often constrained by temperature- and amplitude-dependent properties and limited full-scale evidence on reliable performance when deformation demands exceed the conventional 300% shear-strain design domain. This study experimentally characterizes a full-scale TRCS-type VE damper (TRCS500T-10) employing a styrene–olefin thermoplastic elastomer, with an emphasis on large-deformation and beyond-design behavior. Four nominally identical specimens were tested in a temperature-controlled chamber using sinusoidal, displacement-controlled loading at target shear strains of 300% (≈30 mm) and 450% (≈45 mm). Effective engineering parameters were obtained from stable hysteresis loops using a Kelvin–Voigt-based reduction, including effective stiffness K_eff, effective damping coefficient C_eff, effective damping ratio ξ_eff, and dissipated energy per cycle W_d. At 300% shear strain, the dampers exhibited stable hysteresis with acceptable specimen-to-specimen variability and only modest changes in K_eff, C_eff, and W_d over an ambient-temperature interval of approximately 20–33 °C, while ξ_eff remained around 0.40–0.42. Beyond-design tests at 450% shear strain maintained stable force–displacement loops with substantial load capacity (peak forces ≈ 435–492 kN) and increased per-cycle energy dissipation (approximately 4.0 × 10⁴ kN·mm). Manufacturer-provided polynomial relations were used to standardize the measured properties to a reference condition and to compile a parameter-estimation table for preliminary engineering application. A monotonic ultimate test on specimen TRC500T-05 indicated an ultimate shear deformation capacity of approximately 850% without interface debonding. Collectively, the results provide full-scale evidence of a widened usable deformation range and a practical, design-oriented parameterization for thermoplastic VE dampers under large deformation demands. Full article

Under extreme fault conditions or during maintenance restarts, DC collection wind farms may experience a total blackout due to protective isolation. Addressing the black-start challenges arising from the unidirectional power flow structure and weak damping characteristics inherent to DC step-up collection wind farms, this paper proposes a sequential black-start control scheme predicated on grid-source coordination. A representative topology and an equivalent black-start model of the DC collection system are established to analyze the start-up mechanism and to design an active voltage build-up strategy with virtual impedance for the grid-side Modular Multilevel Converter (MMC). Meanwhile, generator-side permanent-magnet direct-drive wind turbines exploit their self-excitation capability and optimized pitch control to realize islanded self-bootstrapping and stable rotational speed. In addition, we develop a two-stage soft cut-in strategy that combines open-loop voltage scanning for pre-synchronization with closed-loop constant-current ramping of DC/DC converters, together with control logic for sequentially connecting multiple units to the DC grid. Simulation results show that the proposed approach smoothly restores the system from a zero-energy state to the rated operating point without external power sources, confirming the feasibility of full-farm start-up using the grid-side converter station and unit self-bootstrapping. Full article

Grid-forming converters have gained significant attention for their ability to form grid voltage and provide essential grid-supportive services. However, managing harmonics generated by nonlinear loads remains a critical challenge in weak grids. A single grid-forming converter active power filter offers limited compensation capacity, and under heavy nonlinear loading its performance is restricted by converter ratings, leading to reduced stability margins, higher harmonic distortion, and weakened voltage/frequency regulation. To overcome these limitations, this paper presents a novel distributed control approach for multiple-parallel grid-forming converters active power filters that integrates voltage and frequency regulation with scalable harmonic attenuation. The proposed method extracts harmonic components at the point of common coupling and generates harmonic voltage commands to each unit so the parallel units collectively create a near short-circuit impedance for harmonics, preventing harmonic currents from propagating into the grid. Beyond improved harmonic performance, the multi-unit system enhances effective inertia, damping, and short-circuit capacity while avoiding complex parameter tuning, enabling a simple and scalable deployment. Simulation results demonstrate effective harmonic attenuation at the point of common coupling and accurate active/reactive power sharing. Full article

Macrophages are key innate immune cells in the host defense against pathogens. Ionizing radiation can impair macrophage functions such as phagocytosis and activate them, potentially exacerbating tissue injury. Macrophage extracellular traps (METs) are formed upon stimulation of macrophages with PAMPs or DAMPs. We hypothesized that macrophages exposed to ionizing radiation can release extracellular traps. Peritoneal macrophages were collected from C57BL/6 mice and subjected to 5 Gy radiation. We performed assays to detect METs, including the immunofluorescence of citrullination of histone H3 and cell-free DNA measurement in cell culture medium as well as cell death. The exposure of ionizing radiation killed a significant number of mouse peritoneal macrophages through pyroptosis, which was mediated by Gasdermin D (GSDMD). The onset of pyroptosis eventually caused METs by suicidal METosis via pyroptosis and vital METosis occurring in the cells surviving after exposure to radiation. We found that exposure of peritoneal macrophages to 5 Gy radiation significantly increased METosis, as revealed by increased levels of citrullinated histone H3 and an increased surface area of extracellular DNA surrounding the cells. We discovered that peptidyl arginine deiminase (PAD) 2 and 4 are required for peritoneal macrophages to generate extracellular traps in response to radiation exposure. Our data demonstrate that the ionizing radiation induces METs via the activation of GSDMD, and we confirmed the requirement of PADs for METosis after exposure to the ionizing radiation. Targeting METs may direct a new therapeutic strategy for mitigating radiation-induced tissue injury. Full article

To reduce the adverse effects of stern-shaft system vibration on ship performance, this work combined hydrodynamic excitations calculated for a semi-submerged propeller and established a multibody dynamics (MBDs) model of the stern shaft system that included a flexible shaft, propeller, and elastically damped support bearings. The MBDs model’s accuracy was verified through comparison between experimentally identified modal parameters and those computed by the model. It was found that the bearing stiffness and the hydrodynamic excitation frequency collectively determine the vibration amplitude and modal shape of the shaft system, based on an analysis of varied bearing stiffness and damping. Bearing displacement had a significant impact on shafting vibration. And the tie rod with a stiffness of 2.5 × 10⁷ N/m provided a noticeable vibration damping effect. The findings offered theoretical support for mitigating stern-shaft vibration in high-speed vessels subjected to hydrodynamic excitation from semi-submerged propellers. Full article

Alcohol-associated liver disease (ALD) contributes substantially to the global burden of cirrhosis and liver-related mortality, driven by ethanol metabolism, oxidative stress, and dysregulated immune signaling. Despite rapidly growing evidence implicating interferon regulatory factors (IRFs) in ALD pathogenesis, an integrated framework linking ethanol-induced danger signals to cell-type-specific IRF programs is lacking. In this comprehensive review, we summarize current knowledge on IRF-centered signaling networks in ALD, spanning DAMP–PAMP sensing, post-translational IRF regulation, and downstream inflammatory, metabolic, and fibrogenic outcomes across various cell types in the liver, including hepatocytes and immune-related cells such as Kupffer cells, monocyte-derived macrophages, dendritic cells, T cells, hepatic stellate cells (HSC), and neutrophils. We also focus on how ethanol-driven DAMP and PAMP signals activate TLR4, TLR9, and cGAS–STING pathways to engage a coordinated network of IRFs—including IRF1, IRF3, IRF4, IRF5, IRF7, and IRF9—that collectively shape inflammatory, metabolic, and cell-fate programs across hepatic cell populations. We further highlight emerging therapeutic strategies such as STING/TBK1 inhibition, NETosis blockade, IL-22-based epithelial repair, and JAK-STAT modulation that converge on IRF pathways. In summary, this review outlines how IRFs contribute to ALD pathogenesis and discusses the potential implications for the development of targeted therapies. Full article