Search Results (409)

This work develops and validates a high-order, three-dimensional Carrera Unified Formulation (CUF) framework for coupled structural–acoustic eigenanalysis, aiming at accurate low-frequency modal characterization of interior cavity-structure systems with significantly reduced degrees of freedom. The proposed approach employs high-order polynomial expansions to discretize both the structural and fluid domains. The methodology integrates fully coupled fluid-structure analyses into a unified variational formulation, enabling the systematic assembly of global stiffness and mass matrices via sophisticated numerical integration techniques. Validation against a Comsol Multiphysics benchmark model confirms that the CUF-based high-order frameworks converge with significantly fewer degrees of freedom and reliably capture the intricate interactions at the fluid–structure interface. In addition, the approach is versatile, accommodating a range of boundary conditions and material models, underscoring its broad applicability in modern engineering design. Overall, this work advances the state of the art in vibroacoustic analysis by offering a robust tool for predicting natural frequencies and mode shapes, and it lays the groundwork for future extensions to nonlinear, transient, and data-driven applications. Full article

This paper explores the application of the generalized beam theory (GBT) in analyzing the buckling behavior of isotropic and composite thin-walled beams with open cross-sections, both with and without branching. The composite beams are composed of orthotropic laminate layers arranged in arbitrary symmetrical orientations. By integrating GBT with the Ritz method and solving the associated generalized eigenvalue problem (GEP), an efficient and robust semi-analytical framework is developed to assess the stability of such isotropic and orthotropic members. The novelty of this work is not the GBT cross-sectional formulation itself, but its implementation at the beam level using a Ritz formulation leading to a generalized eigenvalue problem for the critical buckling loads and mode shapes that capture coupled global, local, and distortional modes in isotropic and orthotropic composite members. This makes the method suitable for early-stage design studies and parametric investigations, where many design variants (geometry, laminate lay-up, and aspect ratios) must be screened quickly without building large-scale high-fidelity finite element (FE) models for each case. The preliminary outcomes, when compared with those obtained using FE, confirm the approach’s effectiveness in evaluating buckling responses, particularly for open-section composite beams. Ultimately, the combined use of GBT and the Ritz method delivers both physical insight and computational efficiency, allowing engineers and researchers to address complex stability issues that were previously difficult to solve. In summary, the methodology can be correctly used for stability assessment of thin-walled composite members prone to interacting global–local–distortional buckling, especially when rapid, mechanistically transparent predictions are required rather than purely numerical FE output. Full article

Background: Bletilla striata is a medicinal orchid, whose bioactive constituent militarine has therapeutic interest but limited natural availability. Suspension culture coupled with transcriptomics offers a scalable production route and a means to uncover biosynthetic regulators. Methods: Four B. striata landraces were evaluated. Single-factor experiments and response surface methodology optimized sucrose, NH₄NO₃, and agitation to maximize biomass and militarine yield. Militarine and four related metabolites were quantified by HPLC-UV. For transcriptomics, RNA from high- and low-producing landraces was sequenced on Illumina HiSeq, assembled de novo, and analyzed with RSEM (FPKM) and DESeq2 to identify DEGs. Results: The landrace SMPF-NL achieved the highest militarine yield (33.06 mg/g) under optimized conditions (sucrose, 35 g/L; NH₄NO₃, 625 mg/L; agitation, 135 rpm; and half-strength MS medium with 1.0 mg/L of 6-BA, 3.0 mg/L of 2,4-D, and 0.5 mg/L of NAA). Transcriptomic profiling highlighted candidate biosynthetic and regulatory genes, including SuSy2, SUS, ALDO, AOC3, Comt, GOT2, MAOB, BGLU20, and BGLU22. Conclusions: We present an optimized suspension culture system and transcriptomic leads that lay the groundwork for the functional validation and scale-up of controlled militarine production. Full article

Piston pair is a key friction pair of the axial piston pump, but the influence of elastic deformation and the structure design method is not clear. To reveal the real performance of piston pair, a new fluid–solid coupling calculation method is proposed. With the method, the oil film pressure and thickness field, elastic deformation, axial viscous friction and leakage of the piston pair are studied. The influences of the elastic deformation of the piston pair on oil film pressure, axial viscous friction, and leakage were revealed. To reduce the impact brought by deformation, a new piston with hollow piston structure (piston B) is designed. Compared with the traditional structure (piston A), piston B is featured with small elastic deformation, small leakage, large peak pressure, and large viscous friction force. The new fluid–solid coupling calculation method and hollow piston structure of this paper lay the foundation for the piston pair design of the axial piston pump. Full article

Graphene, owing to its exceptional mechanical properties and interfacial modulation capability, is considered an ideal material for enhancing the interfacial strength and damage resistance during the fabrication of ultra-thin lithium foils. Although previous studies have demonstrated the reinforcing effects of graphene on lithium metal interfaces, most analyses have been restricted to single-temperature or idealized substrate conditions, lacking systematic investigations under practical, multi-temperature environments. Consequently, the influence of graphene coatings on lithium-ion conductivity and mechanical stability under real thermal conditions remains unclear. To address this gap, we employ LAMMPS-based molecular dynamics simulations to construct atomic-scale models of pristine lithium and graphene-coated lithium (C/Li) interfaces at three representative temperatures. Through comprehensive analyses of dislocation evolution, root-mean-square displacement, frictional response, and lithium-ion diffusion, we find that graphene coatings synergistically alleviate interfacial stress, suppress crack initiation, reduce friction, and enhance ionic conductivity, with these effects being particularly pronounced at elevated temperatures. These findings reveal the coupled mechanical and electrochemical regulation imparted by graphene, providing a theoretical basis for optimizing the structure of next-generation high-performance lithium metal anodes and laying the foundation for advanced interfacial engineering in battery technologies. Full article

Eight diffusion couples were fabricated to systematically investigate the composition-dependent interdiffusion behavior in hcp Dy-Y, Dy-Nd, Sm-Nd, and Sm-Tb binary alloys. The interdiffusion coefficients were determined at two representative temperatures using the Sauer–Freise method based on concentration–distance profiles measured by electron probe microanalysis (EPMA). These experimentally obtained diffusivities, together with available thermodynamic data, were subsequently employed to assess the atomic mobilities of each system by means of the CALTPP (CALculation of Thermo Physical Properties) program within the CALPHAD (CALculation of PHAse Diagrams) framework. The optimized mobility parameters provide a reliable description of the diffusion behavior in all investigated alloys. This reliability is confirmed by the close agreement between the calculated and experimentally measured interdiffusion coefficients, as well as by the strong consistency between the model-predicted and experimental concentration profiles. The present work thus establishes the first set of critically evaluated atomic mobility parameters for these hcp rare-earth binary systems. These results fill an important gap in the kinetic database of rare-earth alloys and lay a robust foundation for future multi-component CALPHAD-based simulations, thereby supporting the design and optimization of advanced rare-earth permanent magnets with improved coercivity and thermal stability. Full article

As global Marine resource development continues to expand into deep-sea and ultra-deep-sea domains, the intelligent and green transformation of deep-sea aquaculture equipment has become a key direction for high-quality development of the Marine economy. Large deep-sea cages are considered essential equipment for deep-sea aquaculture. However, there are significant challenges associated with ensuring their structural integrity and long-term monitoring capabilities in the complex Marine environments characteristic of deep-sea aquaculture. The present study focuses on large deep-sea cages, addressing their dynamic response challenges and long-term monitoring power supply needs in complex Marine environments. The present study investigates the nonlinear vibration characteristics of flexible net structures under complex fluid loads. To this end, a multi-field coupled dynamic model is constructed to reveal vibration response patterns and instability mechanisms. A self-powered sensing system based on triboelectric nanogenerator (TENG) technology has been developed, featuring a curved surface adaptive TENG array for the real-time monitoring of net vibration states. This review aims to focus on the research of optimizing the design of curved surface adaptive TENG arrays and deep-sea cage monitoring. The present study will investigate the mechanisms of energy transfer and cooperative capture within multi-body coupled cage systems. In addition, the biomechanics of fish–cage flow field interactions and micro-energy capture technologies will be examined. By integrating different disciplinary perspectives and adopting innovative approaches, this work aims to break through key technical bottlenecks, thereby laying the necessary theoretical and technical foundations for optimizing the design and safe operation of large deep-sea cages. Full article

The pericarp of Macadamia integrifolia represents a promising but underexplored source of functional flavonoids. To systematically elucidate their biosynthesis and enhance the industrial potential of this by-product, we conducted integrated transcriptomic and metabolomic profiling of pericarps across five developmental stages (50, 80, 110, 140, and 170 days after flowering). Our analysis reveals, for the first time, a distinct temporal shift in both gene expression and metabolite accumulation. Early stages were characterized by high expression of PAL, 4CL, CHS, and FLS, coupled with abundant flavonols and anthocyanins. In contrast, late stages exhibited upregulation of CHI and F3’5’H, redirecting the metabolic flux toward flavanones and isoflavones. This dynamic profile was closely associated with jasmonate and gibberellin signaling pathways and was likely regulated by key transcription factors (MYB, NAC, bHLH). These findings provide a multi-omics framework that elucidates the temporal flavonoid biosynthesis in macadamia pericarp, thereby laying the groundwork for its future industrial valorization. Full article

N-Acetylaspartate (NAA) plays a critical role in neuronal function, metabolism, and neurotransmitter release. Evidence from magnetic resonance spectroscopy indicates diminished NAA levels in individuals diagnosed with schizophrenia and bipolar disorder; however, this process is time-consuming, expensive, and not viable in individuals with acute illness exacerbation. In order to address these limitations, we developed a novel method for the quantification of plasma NAA based on tandem mass spectrometry coupled to liquid chromatography (HPLC-MS). Our study aimed to assess whether plasma NAA levels change during hospitalization and whether these changes correlate with symptomatic improvement in patients experiencing acute psychiatric exacerbations. We recruited 31 inpatients with acute symptoms of psychotic (48.39%) and/or mood (51.61%) disorders. Symptom severity was assessed using the brief psychiatric rating scale, Positive and Negative Syndrome Scale, and Clinical Global Impression Scale. Plasma NAA was measured at admission and discharge. We observed a significant decrease in symptom scores and a significant increase in plasma NAA levels between admission and discharge. The initiation of therapy with lithium salts significantly influenced plasma NAA changes. Our study shows that our HPLC-MS method can detect clinically meaningful changes in plasma NAA levels. These results might lay the groundwork for future research exploring the relationship between plasma NAA levels and cerebral NAA levels measured by MRS. Full article

Short-range forces enable peridynamics to simulate impact, yet it demands a computationally expensive contact search and includes no intrinsic damping. A significantly more efficient solution is the coupled dual-horizon peridynamics–discrete element method approach, which provides a robust framework for modeling fracture. The peridynamics component handles the nonlocal continuum mechanics capabilities to predict material damage and fracture, while the discrete element method captures discrete particle behavior. Whereas existing peridynamics–discrete element method approaches assign discrete element method particles to many or all surface peridynamics points, the proposed method integrates dual-horizon peridynamics with a single discrete element particle representing each object. Contact forces are computed once per discrete element pair and mapped to overlapping peridynamics points in proportion to shared volume, conserving linear momentum. Benchmark sphere-on-plate impact demonstrates prediction of peak contact force, rebound velocity, and plate deflection within 5% of theoretical results found in the literature, while decreasing neighbour-search cost by more than an order of magnitude. This validated force-transfer mechanism lays the groundwork for future extension to fully resolved fracture and fragmentation. Full article

Agricultural green development cannot be achieved without effective financial support. Based on panel data from 30 provinces in China from 2014 to 2023, this paper uses a coupling coordination model to measure and analyse the degree of coordination between digital inclusive finance and green finance; this further constructs a comprehensive evaluation system for agricultural green development, and on this basis uses a fixed-effect model and a threshold regression model to systematically examine the impact of the coordination between the two on agricultural green development. The findings are as follows: first, the coordination between digital inclusive finance and green finance shows an upward trend over time, shifting spatially from a high trend in the east to a low trend in the west to regional convergence; second, the coordination between the two has a substantial and favourable impact on green agricultural development, which is a conclusion that persists after robustness tests; third, the effect is heterogeneous, with more pronounced promotion effects in non-grain-producing regions, regions with high agricultural technology levels, and low levels of financial exclusion; fourth, the effect exhibits nonlinear characteristics, with coordination and agricultural industrial agglomeration each forming a single-threshold effect. This research lays down a foundational framework for financial coordination in supporting agricultural green development. It suggests promoting a dual-wheel coordination mechanism to effectively empower agricultural green development by strengthening technological empowerment, regional linkage, and designing differentiated policies. Full article

Frequent channel migrations of the Yellow River, coupled with increasing human disturbances, have driven significant land cover changes in the Yellow River Delta (YRD) over time. Accurate estimation of aboveground biomass (AGB) and clarification of the impact of land cover changes on AGB are crucial for monitoring vegetation dynamics and supporting ecological management. However, field-based biomass samples are often time-consuming and labor-intensive, and the quantity and quality of such samples greatly affect the accuracy of AGB estimation. This study developed a robust AGB estimation framework for the YRD by synthesizing 4717 field-measured samples from the published scientific literature and integrating two critical ecological indicators: leaf area index (LAI) and length of growing season (LGS). A random forest (RF) model was employed to estimate AGB for the YRD from 2001 to 2022, achieving high accuracy (R² = 0.74). The results revealed a continuous spatial expansion of AGB over the past two decades, with higher biomass consistently observed in western cropland and along the Yellow River, whereas lower biomass levels were concentrated in areas south of the Yellow River. AGB followed a fluctuating upward trend, reaching a minimum of 204.07 g/m² in 2007, peaking at 230.79 g/m² in 2016, and stabilizing thereafter. Spatially, western areas showed positive trends, with an average annual increase of approximately 10 g/m², whereas central and coastal zones exhibited localized declines of around 5 g/m². Among the changes in land cover, cropland and wetland changes were the main contributors to AGB increases, accounting for 54.2% and 52.67%, respectively. In contrast, grassland change exhibited limited or even suppressive effects, contributing −6.87% to the AGB change. Wetland showed the greatest volatility in the interaction between area change and biomass density change, which is the most uncertain factor in the dynamic change in AGB. Full article

This study developed a rapid, non-destructive method for the quantitative detection of protein in cottonseed by integrating near-infrared (NIR) fiber spectroscopy with chemometric machine learning. The establishment of this method holds significant importance for the rational and efficient utilization of cottonseed resources, advancing research on the genetic improvement of cottonseed nutritional quality, and promoting the development of equipment for raw cottonseed protein detection. Fuzzy cottonseed samples from three varieties were collected, and their NIR fiber-optic spectra were acquired. Reference protein contents were measured using the Kjeldahl method. Spectra were denoised through preprocessing, after which informative wavelengths were selected by combining Uninformative Variable Elimination (UVE) with Competitive Adaptive Reweighted Sampling (CARS) and the Random Frog (RF) algorithm. Partial least squares regression (PLSR), least-squares support vector machine (LSSVM), and support vector regression (SVR) models were then constructed to predict protein content. Model performance was assessed using the coefficient of determination (R²), root-mean-square error (RMSE), residual predictive deviation (RPD), and range error ratio (RER). The results indicate that the standard normal variate (SNV) is the most effective preprocessing step. The best performance was achieved by the LSSVM model coupled with UVE + CARS, yielding R² = 0.8571, RMSE = 0.0033, RPD = 2.7078, and RER = 10.72, outperforming the PLSR and SVR counterparts. These findings provide technical support for the rapid detection of fuzzy cottonseed protein and lay the groundwork for the development of related detection equipment. Full article

While insulator integrity is critical for power grid stability, prevailing detection algorithms often rely on computationally intensive models incompatible with resource-constrained edge devices like unmanned aerial vehicles (UAVs). Key limitations—including redundant feature interference, inadequate sensitivity to small targets, rigid fusion weights, and sample imbalance—further restrict practical deployment. To address those problems, this study presents a lightweight insulator anomaly detection algorithm, LAI-YOLO. First, the SqueezeGate-C3k2 (SG-C3k2) module, equipped with an adaptive gating mechanism, is incorporated into the Backbone network to reduce redundant information during feature extraction. Secondly, we propose a High-level Screening–Feature Weighted Feature Pyramid Network (HS-WFPN) to replace FPN+PAN via selective weighted feature fusion, enabling dynamic cross-scale integration and enhanced small-target detection. Then, a reconstructed lightweight detection head coupled with Slide Weighted Focaler Loss (SWFocalerLoss) mitigates performance degradation from sample imbalance. Ultimately, the layer adaptation for the magnitude-based pruning (LAMP) technique slashes computational demands without sacrificing detection prowess. Experimental results on our insulator anomaly dataset demonstrate that the improved model achieves higher efficacy in identifying insulator anomalies, with mAP@0.5 increasing from 88.2% to 91.1%, while model parameters and FLOPs are diminished to 45.7% and 53.9% of the baseline, respectively. This efficiency facilitates the deployment of edge devices and highlights the method’s considerable application potential. Full article

Composite pressure vessels have attracted significant attention in recent years owing to their lightweight characteristics and superior mechanical performance. However, analyzing composite layers remains challenging due to complex filament-winding (FW) pattern structures and the associated high computational costs. This study introduces a homogenization method to achieve cross-scale modeling of carbon fiber-reinforced plastic (CFRP) layers, accounting for both lay-up sequence and in-plane FW diamond-shaped form. The stacking sequence in an FW Type IV composite pressure vessel is numerically investigated through ply modeling and cross-scale homogenization. The composite tank structure, featuring a polyamide PA66 liner, is designed for a working pressure of 70 MPa and comprises 12 helical winding layers and 17 hoop winding layers. An FW cross-undulation representative volume element (RVE) is developed based on actual in-plane mesostructures, suggesting an equivalent laminate RVE effective elastic modulus. Furthermore, six different lay-up sequences are numerically compared using ply models and fully and partially homogenized models. The structural displacements in both radial and axial directions are validated across all modeling approaches. The partial homogenization method successfully captures the detailed fiber-direction stress distribution in the innermost two hoop or helical layers. By applying the Hashin tensile failure criterion, the burst pressure of the composite tank is evaluated, revealing 7.56% deviation between the partial homogenization model and the ply model. Fatigue life analysis of the Type IV composite pressure vessel is conducted using ABAQUS^® coupled with FE-SAFE, incorporating an S-N curve for polyamide PA66. The results indicate that the fatigue cycles of the liner exhibit only 0.28% variation across different stacking sequences, demonstrating that homogenization has a negligible impact on liner lifecycle predictions. The proposed cross-scale modeling framework offers an effective approach for multiscale simulation of FW composite pressure vessels, balancing computational efficiency with accuracy. Full article