Search Results (148)

Transverse shear deformation plays a non-negligible role in lightweight periodic-core structures and motivates the use of shear-corrected reduced-order plate and beam models. However, the shear correction factor $k_s$ is often treated as a constant despite its strong dependence on cross-sectional heterogeneity and geometry. This work quantifies the global sensitivity of $k_s$ in corrugated paperboard by combining an energy-consistent pixel-based identification of the effective shear stiffness $\left(GA{)}_{\mathrm{e}\mathrm{f}\mathrm{f}}\right.$ with a space-filling exploration of the parameter domain. Representative three-ply (single-wall) and five-ply (double-wall) configurations are generated directly in the pixel domain using sinusoidal fluting descriptions and non-overlapping liner bands. The effective shear stiffness is obtained from a heterogeneous shear-energy equivalence, where a normalized two-dimensional shear-stress shape function is computed from pixel-based sectional descriptors and integrated with spatially varying shear moduli. Latin Hypercube Sampling is employed to explore wide ranges of flute period, height, and thickness, liner thicknesses, and liner–flute shear-modulus contrasts. Global sensitivity is reported using unit-free normalized indices, including log-elasticities (based on the slope of $\ln k_s$ versus $\ln x$) and partial rank correlation coefficients. The results demonstrate that flute geometry is the primary driver of $k_s$ variability, while material contrast significantly modulates shear-energy localization, particularly in double-wall boards with two distinct flutings. The proposed framework enables high-throughput shear correction assessment and supports robust parameterized reduced-order models for corrugated structures. Full article

Background: Self-esteem plays a central role in adolescent psychological health and may be shaped by everyday health behaviors such as eating patterns and engagement in physical activity. However, evidence from Eastern European youth remains comparatively limited. Lower levels of self-worth during adolescence have been linked to increased vulnerability to maladaptive behaviors, including substance use. The present study aimed to explore preliminary associations between lifestyle behaviors, nutritional practices, and self-esteem in a sample of Romanian adolescents. Methods: A cross-sectional design was used, involving 113 participants aged 14–18 years. Self-esteem was assessed using the Rosenberg Self-Esteem Scale, while lifestyle behaviors were evaluated through a standardized questionnaire. Body mass index was calculated based on self-reported height and weight. Statistical analyses included Pearson correlation coefficients and multiple linear regression models. Results: Higher self-esteem scores were strongly associated with greater participation in physical activity and adherence to a balanced diet, while inverse relationships were observed with unhealthy dietary habits and higher BMI values. Physical activity emerged as the most influential predictor of self-esteem, accounting for over three-quarters of the variance in Rosenberg scale scores. Conclusions: In this preliminary analysis, physical activity and healthier dietary behaviors were associated with higher self-esteem scores among adolescents. Given the exploratory nature of the study, these findings should be interpreted with caution. They primarily serve to generate hypotheses and highlight the need for future studies with validated instruments, larger samples, and appropriate control for potential confounding factors to better elucidate the relationship between lifestyle behaviors and adolescent self-esteem. Full article

Soil spatial variability is an inherent feature of natural strata, and random field theory provides an effective framework for quantifying it, aiding accurate deformation prediction. This study focuses on the tunnel section between Kepugongyuan and Gangduhuayuan Stations on Wuhan Metro Line 12. Its novelty focuses on analyzing dual-line shield-induced ground response with explicit consideration of multi-layer soil spatial variability. It examines the effects of the coefficient of variation and the horizontal/vertical spatial correlation distances of cohesion, internal friction angle, and elastic modulus—considering multilayer soil variability—on ground disturbance induced by twin-tunnel shield construction. The main findings include the following: (1) In cross-section, the settlement trough transitions from a “W”-shaped double trough to a “V”-shaped single trough as excavation advances, with the settlement center moving toward the midpoint between the tunnels. Longitudinally, soil heaves ahead of the shield and settles behind. (2) Ignoring spatial variability results in underestimated deformations; nearly 80% of stochastic simulations produced larger maximum surface settlements compared to deterministic analysis. (3) Ground loss and shield thrust disturbance are categorized into four zones based on tunnel diameter (D): Disturbance Zone, Secondary Zone, Transition Zone, and Undisturbed Zone. These findings provide practical guidance for predicting ground deformation and managing settlement-related risks in urban dual-line shield projects. Full article

Water-saving agricultural irrigation systems depend heavily on the hydraulic stability of pressure-compensating (PC) emitters, whose performance is fundamentally shaped by internal flow-path geometry. This study analyzes six commercial PC emitters (E1–E6) operated under pressures of 0.8–2.0 bar to quantify how key geometric descriptors influence hydraulic parameters critical for efficient water use, including actual discharge (q_act), discharge coefficient (k), pressure exponent (x), emission uniformity (EU), and flow variability. All emitters had discharge deviations within ±7% of nominal values. Longer and more tortuous labyrinths enhanced compensation stability, while emitters with wider cross-sections and shorter paths produced higher throughput but weaker regulation efficiency. Linear mixed-effects modeling showed that effective flow area increased k, whereas normalized path length and tortuosity reduced both k and x. Predictive equations derived from geometric indicators closely matched measured values, with deviations below ±0.05 L/h for k and ±0.05 for x. These results establish a geometry-based hydraulic framework that supports emitter selection and design in water-saving agricultural irrigation, aligning with broader Agricultural Water–Land–Plant System Engineering objectives and contributing to more efficient and sustainable water-resource utilization. Full article

This study examines the social determinants of the digital divide in pre-service teacher education through the design and validation of the Digital Hospitality Scale (DSBD-HD-FID). The instrument was developed to diagnose social inequalities across six key dimensions: socioeconomic status, geographic location, gender, age, disability status, and interculturality. These dimensions are understood as structural factors shaping access to, use of, and participation in digital environments within teacher education. The research followed a non-experimental, quantitative, and cross-sectional design, including content validation through expert judgment and statistical analysis based on a pilot sample of education students from Chile and Portugal. An exploratory factor analysis was conducted, and internal consistency was assessed using Cronbach’s alpha coefficient. The results confirm strong content and construct validity, as well as high reliability (α = 0.93). Empirical findings indicate that socioeconomic status and geographic location significantly condition access to connectivity and digital literacy, while gender differences emerge mainly in recreational uses and frequency of digital training. Beyond these results, the study highlights the relevance of addressing digital inequalities in teacher education through inclusive and equity-oriented training policies. The findings support the integration of digital hospitality, human rights education, and the Sustainable Development Goals into initial teacher training curricula as measurable and evaluable dimensions, providing an evidence-based framework to inform future teacher education policies aimed at reducing digital divides and promoting social cohesion. Full article

L-shaped concrete-filled steel tubular (CFST) columns have attracted increasing attention in recent years due to their favorable seismic performance and their ability to reduce column protrusions into interior wall surfaces. Existing studies on L-shaped CFST columns have mainly focused on a specific cross-section form, and the mechanical behavior of L-shaped CFST columns with different limb length ratios and inter-limb angles has not yet been sufficiently investigated. To further examine the axial compressive performance of L-shaped CFST columns, this study designed and tested eight L-shaped CFST columns by considering the cross-section form, limb-length ratio, and inter-limb angle as key parameters. In addition, a simplified formula for predicting the axial load capacity of L-shaped CFST columns was proposed based on the unified theory. The test results indicated that the cross-section form significantly affects both load-carrying capacity and ductility. For the equal-limb specimens, the peak load of the C-type specimen was 8% and 9% higher than that of the A-type and B-type specimens, respectively, whereas the displacement ductility coefficient of the A-type specimen was 48% and 47% higher than that of the B-type and C-type specimens, respectively. Compared with the unequal limb specimens, the equal limb specimens exhibited an increase in peak load of more than 20%; moreover, the displacement ductility coefficients of the A-type and B-type specimens increased by 48% and 61%, respectively. Increasing the inter-limb angle enhanced the peak load but reduced the ductility, and it led to a gradual shift in the failure mode from local buckling of the steel tube to overall bending. The findings of this study contribute to a more comprehensive understanding of the mechanical behavior of L-shaped CFST columns and can provide reference for their design and optimization. Full article

This study introduces a systematic methodology for modelling the radius of curvature of the arc-shaped section $\stackrel{⌢}{\mathrm{BC}}$ in a Michell–Banki cross-flow turbine blade. The method combines geometric modeling in polar coordinates with nonlinear regression, using both two- and three-parameter formulations estimated through the Ordinary Least Squares (OLS) method. Model performance is assessed through two complementary criteria: the coefficient of determination ($R^2$) and the computed arc length, ensuring that statistical accuracy aligns with geometric fidelity. The methodology was validated on digital measurements obtained from CATIA, using datasets with $N=187$ and a reduced subset of $N=48$ points. Results demonstrate that even with fewer data points, the regression model maintains high predictive accuracy and geometric consistency. The best-performing three-parameter model achieved $R^2=0.958$, with a five-point Gauss–Legendre quadrature yielding an arc length of approximately $145\mathrm{mm}$, representing 98.8% agreement with the reference value of $146.78\mathrm{mm}$. By representing the arc as a single smooth exponential function rather than a piecewise mapping, the approach simplifies analysis and enhances reproducibility. Coupling regression precision with arc-length verification provides a robust and reproducible basis for curvature modeling. This methodology supports turbine blade design, manufacturing, and quality control by ensuring that the blade geometry is validated with high statistical confidence and physical accuracy. Future research will focus on deriving analytical arc-length integrals and integrating the procedure into automated design and inspection workflows. Full article

The wandering reach of the Yellow River has long been a pivotal area of research due to its drastic fluctuations in water-sediment dynamics, frequent shifts in the main channel, and complex river regime evolution. Studies on the main-channel morphological evolution in this reach have focused on the analysis of parameters related to the overall oscillation or have only analyzed a certain reach within the wandering reach, with a lack of detailed studies based on the different characteristics of each area. Therefore, taking the Xiaolangdi Reservoir–Gaocun reach as the research area, by constructing a two-dimensional water-sediment dynamic model, the erosion–deposition characteristics of different sub-reaches and the morphological evolution characteristics of key cross-sections were quantified and analyzed. Based on measured hydrological, sediment, and topographic data, the temporal and spatial changes in the bankfull area and fluvial facies coefficient of typical sections before and after the construction of Xiaolangdi Reservoir were analyzed. By interpreting remote sensing images, the spatio-temporal variation characteristics of the migration distance and bending coefficient of different reaches before and after the construction of Xiaolangdi Reservoir were calculated, and the key factors influencing the evolution of river morphology parameters were identified. The results showed that after the Xiaolangdi Reservoir operation, the overall erosion of the Huayuankou–Jiahetan reach is greater than the deposition, and the erosion is more obvious in dry years. The river course direction and control engineering play a significant role in controlling the morphological evolution of the main channel during the process, causing the R2 reach to significantly swing to the north bank and the R3 reach to the south bank. When the sediment transport coefficient values were between 0 and 0.005 kg.s.m⁻⁶, water-sediment had a positive effect on shaping and evolving the main-channel morphology. The long-term low-sand discharge of Xiaolangdi Reservoir and the continuous improvement of river regulation projects are the main reasons for the above changes. The results can provide support for controlling the evolution of the main channel and improving river regulation projects. Full article

We establish a general, device-oriented procedure to extract absolute pump-band metrics from room-temperature UV–Vis (ultraviolet–visible) absorbance—including the absorption coefficient α(λ), per-active-ion cross-section ${\sigma }_{\mathrm{e}\mathrm{f}\mathrm{f}}\left(\lambda \right)$, the effective per-active-ion absorption cross section ${\sigma }_{\mathrm{e}\mathrm{f}\mathrm{f}}\left(\lambda \right)$ and derivative-based line-shape descriptors. As a representative case study, the procedure is applied to nanocrystalline Er³⁺/Ho³⁺:Y₃Ga₅O₁₂ over the 350–700 nm spectral range. After baseline correction and line-shape inspection assisted by the numerical second derivative of the absorbance, we extract conservative peak positions and the full width at half maximum across the visible 4f–4f manifolds. At the technologically relevant pump wavelengths near 406 nm (Er-addressing) and 473 nm (Ho-addressing) bands, resulting absorption coefficients are α = 0.313 ± 0.047 cm⁻¹ and α = 0.472 ± 0.071 cm⁻¹, respectively. The corresponding per-active-ion ${\sigma }_{\mathrm{e}\mathrm{f}\mathrm{f}}$ of (3.62 ± 0.54) × 10⁻²² cm² and (5.46 ± 0.82) × 10⁻²² cm², referenced to the measured optical path length L = 0.22 ± 0.03 mm (approximately 15% propagated relative uncertainty; explicit 1/L rescaling). Cross sections are reported per total active-ion density (Er³⁺ + Ho³⁺). The spectra exhibit Stark-type substructure only partially resolved at room temperature; the second derivative highlights hidden components, and we report quantitative descriptors (component count, mean spacing, curvature-weighted prominence, and pump detuning) that link line-shape structure to absolute pump response. These device-grade metrics enable rate-equation modelling (pump thresholds, detuning tolerance), optical design choices (path length, single/multi-pass or cavity coupling), and host-to-host benchmarking at 295 K. The procedure is general and applies to any rare-earth-doped material given an absorbance spectrum and path length. Full article

Microchannels can create disturbed flow patterns by altering pressure gradients, shear forces, and flow symmetry, which are essential in the design of microfluidic devices and, hence, blood-contacting devices. The effect of asymmetric stenosis on pressure, wall shear stress, and velocity in rectangular and circular microchannels with same operating conditions was analyzed in this study using three-dimensional (3D) steady laminar computational fluid dynamics (CFD) simulations. Asymmetric flow patterns induced by asymmetric stenosis are of particular importance and remain underexplored, especially in the context of multiple constrictions. This is, to our knowledge, is the first systematic CFD comparison of multiple asymmetric stenoses in circular microchannels directly contrasted with rectangular and single-stenosis cases under identical settings. Several parameters, such as wall shear stress (WSS), pressure, and velocity distributions, were analyzed in various stenotic and non-stenotic geometries. These microchannel models, while not reflecting real blood vessels themselves nor exhibiting wall compliance, pulsatility, or non-Newtonian rheology, replicate important mechanical characteristics of stenosis-mediated flow disturbance. Single and multiple asymmetric stenoses create flow patterns that are similar to those of vascular pathologies. For this reason, these channels should be considered as simplified device-scale models of vascular phenomena as opposed to realistic, in vitro vascular models. The results showed that asymmetric stenosis creates asymmetric velocity peaks and elevated WSS, which are more evident in the case of circular configurations with double asymmetric stenosis. The findings will help design microfluidic devices that mimic unstable flow characteristics that occur in stenotic conditions, and assist in testing clinical devices. In this study, two fabrication-ready microchannel designs under fixed operating conditions (identical inlet velocity and fluid properties) that reflect common microfluidic use were compared. Consequently, all pressure, velocity, and WSS outcomes are interpreted as device-scale responses under fixed velocity, rather than a fundamental isolation of cross-section shape, which would require matched hydraulic diameters or flow rates. This study is explicitly device-oriented, representing a fixed operating point rather than a strict geometric isolation. Accordingly, the results are also expressed with dimensionless loss coefficients (Ktot and Klocal) to enable scale-independent, device-level comparison. Full article

Traditional radar cross-section (RCS) prediction methods struggle with dynamically uncertain shapes of flexible targets, because they cannot disentangle intrinsic geometry from transient deformation, leading to degraded accuracy and prohibitive computational cost. To bridge this gap, we propose a dual-branch deep learning architecture that explicitly separates static geometric features from dynamic deformation characteristics, suppressing deformation noise in target identity representation. Training data are generated by coupling non-uniform rational B-spline (NURBS) parametric modeling with computational electromagnetics. The dynamic branch employs a one-dimensional convolutional neural network-long short-term memory-Transformer (1D-CNN-LSTM-Transformer) to extract temporal deformation features, while the static branch encodes baseline geometry via fully connected layers; their fused outputs deliver high-fidelity RCS predictions. Trained and tested on 1000 deformed metasurface samples, the proposed method achieves mean squared error (MSE) = 0.0541, root mean squared error (RMSE) = 0.2326 and coefficient of determination (R²) = 0.9997. The results demonstrate end-to-end accurate prediction under shape uncertainty, extending RCS modeling for flexible targets beyond recent studies that focus on static scenarios, and offering a reliable tool for flexible stealth design and high-resolution radar target recognition. Full article

The core of ocean thermal energy conversion (OTEC) is the transfer and conversion of heat energy, and the heat exchanger is a key component of the heat transfer between the surface warm seawater and the lower cold seawater. The working fluid has a significant impact on the efficiency of the entire cycle in the temperature difference cycle. This study aimed to improve heat exchange efficiency. The article studied heat exchangers, used R134a as the circulating medium, and applied ANSYS-FLUENT 2020R2 simulation software to analyze the variation in heat transfer coefficients. We obtained the trend in the heat transfer coefficient of the heat exchanger with the shape of an elliptical tube under the condition of ocean temperature difference cycles. Then we used a long short-term memory network and Adam optimization algorithm to establish the prediction model. The NSGA-II 11 algorithm was used to realize optimization objectives of the highest heat transfer efficiency and the smallest cross-sectional area of heat transfer tubes along the X and Y directions. Finally, the parameters of the evaporator and condenser ultimately resulted in three optimal solutions. The results of this study can provide a certain theoretical basis and reference value for the efficiency analysis, structure optimization, and experimental research of the subsequent ocean differential circulation heat transfer. Full article

This study investigated how banks’ balance sheet fundamentals shape their credit growth using panel co-integration methods and two estimation methods—pooled mean group (PMG) and dynamic fixed effects (DFE). Both approaches yielded consistent core results. First, weaker asset quality, proxied by higher non-performing loans (NPLs), was strongly and negatively related to credit growth: PMG produced a large negative long-run coefficient, and DFE’s error-correction form confirmed a significant adverse effect, consistent with higher provisioning, thinner capital buffers, and lower risk-taking. Second, capitalization (equity to assets) supported long-run growth under PMG, while DFE—imposing common slopes—did not, suggesting heterogeneous capitalization effects across banks that PMG captured but DFE muted. Third, operating expense intensity showed a positive long-run association with credit growth in both models, consistent with expansionary spending accompanying durable lending rather than costs causing lending. Long-run effects for liquidity and market-risk sensitivity were weaker or mixed: liquidity’s role was imprecise, and market-risk sensitivity was positive in PMG but not significant in DFE, again pointing to cross-sectional heterogeneity. Error-correction terms were large, negative, and highly significant in both models, indicating rapid convergence—near full adjustment within one period, with slight overshooting in DFE. Short-run results showed that higher liquidity and temporary cost spikes dampened contemporaneous growth. Policy implications emphasize sustained oversight of asset quality and prudent capital planning to support long-run credit supply. Full article

The rolling process is one of the most efficient methods for manufacturing long products with both regular and more complex cross-sectional shapes, the latter requiring the development of geometrically complex roll passes. Railway rails are one such product, manufactured at ArcelorMittal Poland S.A., Huta Królewska plant. During the rolling process, the roll passes are subject to wear due to several concurrent phenomena, such as mechanical fatigue, abrasive wear, and thermal fatigue. The determination of roll wear can be based on the experience of personnel and statistical data from previous production runs. It is also possible to determine roll wear through numerical modelling using Archard’s wear model. The aim of this paper is to define a methodology for the quantitative and qualitative determination of roll wear, as well as to establish a wear coefficient dependent on the type of plastic forming process. This will enable the development of a new roll pass design for railway rails that takes into account the durability of the roll passes. Full article

Aiming at the challenges of high dimensionality in both design variables and optimization objectives, along with high computational resource consumption in the multi-disciplinary optimization of aerodynamic and stealth performance for an unmanned aerial vehicle (UAV) S-shaped inlet, this paper proposes a multi-objective optimization method that integrates design variable dimensionality reduction and a Co-Kriging multi-fidelity surrogate model. First, the S-shape inlet was defined by utilizing parametric modeling with a total of 11 design variables. Simulations were performed to obtain a subset of samples, and Sobol’ sensitivity analysis was applied to eliminate parameters with minor influence on performance, thereby achieving design variable dimensionality reduction. Subsequently, a Co-Kriging surrogate model was constructed. Based on the Multi-Objective Evolutionary Algorithm Based on Decomposition (MOEA/D) algorithm, multi-objective optimization was carried out with the total pressure recovery coefficient, total pressure distortion coefficient, and the average forward radar cross-section (RCS) as the optimization objectives, yielding a Pareto front solution set. Finally, three optimized inlets were selected from the Pareto front and compared with the original inlet to evaluate their aerodynamic and stealth performance. The results demonstrate that the proposed optimization method balances efficiency and accuracy effectively, significantly increasing the total pressure recovery coefficient while markedly reducing the total pressure distortion coefficient and RCS of the optimized inlet. Full article