Search Results (606)

This paper presents a symmetry-guided multi-elite Gekko Japonicus Algorithm, termed MIGJA, for global optimization and multi-threshold image segmentation. The method modifies the original GJA from three aspects. In the movement stage, a success-rate feedback mechanism is used to adapt the Lévy-flight probability and step-size coefficient according to recent search behavior, allowing the population to switch more flexibly between exploration and exploitation. In the guidance stage, several elite individuals are combined to form a weighted collaborative center, which reduces the excessive dependence on a single best solution and provides a more balanced search direction. In the reconstruction stage, historical memory and differential information are introduced into the tail reconstruction process to help inferior or stagnant individuals move out of local regions during the later search phase. The proposed MIGJA is tested on the CEC2017 and CEC2020 benchmark suites and further applied to Otsu-based multi-threshold image segmentation. The numerical results show that MIGJA performs competitively in terms of convergence accuracy and stability. According to the Friedman mean-rank results, MIGJA ranks first in all test settings, with mean-rank reductions of about 78.8–84.5% compared with the original GJA and 66.7–76.1% compared with the strongest competitor. In the segmentation experiments, MIGJA also obtains favorable objective function values and image quality metrics, including PSNR, FSIM, and SSIM. These findings suggest that the proposed algorithm is suitable for both benchmark optimization and multi-threshold image segmentation tasks. Full article

Carbon nanotubes (CNTs) serve as exceptional multifunctional supports for metal phthalocyanine (MPc)-based electrocatalysts, effectively addressing the inherent limitations of molecular catalysts such as poor conductivity and aggregation. This review systematically summarizes the recent advances in engineering the interface between MPcs and CNTs to optimize performance in sustainable energy conversion and environmental remediation. We categorize the engineering strategies into three synergistic dimensions: (1) dispersion and modification engineering, introducing the most direct physical anchoring dispersion strategy via non-covalent interactions and targeted modifications to yield highly active catalysts; (2) chemical bonding engineering, in which robust axial coordination or covalent grafting creates stable, well-defined active sites and prevents leaching; and (3) geometric and spatial engineering, which exploits CNTs’ unique curvature, atomic defects, inner cavities and one-dimensional architecture to induce strain, symmetry breaking, and nanoconfinement, thereby steering reaction pathways or to construct conductive nanocomposites. These strategies highlight that CNTs are not merely passive scaffolds but active regulators that geometrically and electronically modulate MPcs. By balancing molecular dispersion, charge transfer, and mass transport, CNT-supported MPcs exhibit superior activity, selectivity, and stability for critical electrochemical reactions, including the oxygen reduction reaction (ORR), CO₂ reduction reaction (CO₂RR), and nitrate reduction reaction (NO₃RR), demonstrating substantial potential for advancing sustainable energy technologies and environmental applications. Full article

This study reports the synthesis of low-defect Prussian blue analogues (PBAs) using a single iron-source method and systematically investigates the influence of atmospheric components, particularly water and oxygen, on their oxidative decomposition. Our findings demonstrate that the oxidative degradation of PBAs is governed synergistically by moisture and oxygen, with ambient humidity identified as the primary factor determining both the extent and kinetics of their decomposition. Notably, a pure oxygen environment by itself does not trigger material degradation, while oxygen markedly accelerates the decomposition only in the presence of moisture. As a result of the oxidation, enhanced Coulombic interaction between sodium ions and cyano groups induces structural modifications in the lattice framework, driving a phase transformation from monoclinic to cubic symmetry, accompanied by changes in its unit cell volume. Furthermore, in high-humidity environments, atmospheric moisture promotes the gradual deintercalation of sodium ions from the Prussian blue framework, resulting in the conversion of sodium-rich Prussian blue to the sodium-deficient form. Concurrently, an increase in lattice defect density leads to partial structural collapse, inducing the release of free ferrocyanide ions, which may subsequently react with the deintercalated sodium ions to form the sodium ferrocyanide impurity phase. We also find that the preferential decomposition of low-spin iron over high-spin iron within the framework leads to a further reduction in its electrochemical capacity. In contrast, potassium Prussian blue exhibits minimal interaction with water molecules and can effectively repel them through steric hindrance. Therefore, partial substitution of sodium with potassium ions is proposed as a viable strategy to enhance the structural stability of the Prussian blue framework, improve the storage performance of sodium Prussian blue (NaPB), and mitigate water ingress. This work offers fundamental insights into the storage characteristics and oxidative degradation mechanisms of PBAs. Full article

Flow interference among bluff bodies can strongly amplify or suppress unsteady aerodynamic forces and induced vibrations thereof. However, the behaviour of tandem square-cylinder interference and its passive control in the laminar regime remains insufficiently quantified, particularly near the known critical tandem spacing ratio (L/D ≈ 4.5). This study systematically analysed and determined how a splitter plate placed downstream of the second cylinder modulates the aerodynamic forces, symmetry of vortex shedding, wake topology, and associated wake metrics in two-dimensional incompressible laminar flows. Unsteady finite-volume numerical simulations were conducted using ANSYS Fluent (2022 R1) at Re = 150. The tandem cylinder spacing (L) was varied over L/D = 2–6 (D, the cylinder side length), and the splitter gap (G) was varied over G/D = 1–6. The splitter plate acted as a strong wake stabiliser at small gaps (G/D = 1), where vortex shedding was largely suppressed and lift fluctuations were minimal (for example, C_l,rms ≈ 0.055), and the DC experienced negative drag (C_d ≈ −0.13), consistent with elongated and weakly rolled-up shear layers and extended recirculation. The splitter plate acted as a sharp control “switch” at a critical splitter gap G/D ≈ 2, where the wake transitioned to unsteady shedding, the Strouhal number (St) jumped to values that remained nearly constant for G/D = 2–6, and the wake metrics indicated earlier roll-up (reduced vortex formation length and recirculation length) and greater lateral spreading (increased wake width). The outcome was influenced by the tandem regimes: for 1.5 < L/D < 4, persistent shielding and negative downstream drag predominated. However, near the critical gap (L/D ≈ 4.5), the restoration of shear-layer impingement at G/D ≥ 2 resulted in a downstream drag surpassing the isolated-cylinder baseline (C_d,SC ≈ 1.49) by approximately 3–8%. In the co-shedding regime, when L/D = 5, there was a notable increase in drag, approximately 12.3% more than that on an isolated cylinder. Conversely, when L/D = 6, the system approached aerodynamic independence without any amplification (approaching the single-cylinder value). The interference metrics showed a maximum combined drag reduction of ~68.6% at L/D = 4.5 and G/D = 1, whereas the upstream cylinder drag was only weakly affected. The results of the present study establish splitter placement as an effective passive control method for suppressing or recovering interference-driven unsteadiness, thereby supporting designs in bluff-body aerodynamics, heat-transfer equipment, and vibration-mitigation systems. Full article

Background: Normalized strength outcomes and limb symmetry indices (LSIs) are widely used but poorly characterized across testing conditions, and it is unclear if these vary by sex. This study aimed, first, to investigate sex-related differences in normalized knee flexor strength and LSI values across multiple strength-testing conditions in healthy recreational athletes, and, second, to descriptively examine associations among strength outcomes obtained under different testing conditions within female and male participants. Methods: In this cross-sectional study, 52 healthy, recreationally active adults (26 females and 26 males) underwent bilateral knee flexor strength testing using three force plate-based isometric assessments, one static dynamometer-based isometric assessment, and three isokinetic dynamometer-based assessments. Differences were analyzed with a mixed analysis of variance (ANOVA), and associations were assessed using Pearson correlations. Results: Males showed higher normalized knee flexor strength than females across all testing conditions (main effect of sex: p < 0.001; partial η² = 0.334–0.371), with the magnitude of these sex-related differences varying across testing conditions (sex-by-testing condition interaction: p < 0.001; partial η² = 0.215–0.230). LSI values did not differ by sex (p = 0.896) and remained consistent across testing conditions (p = 0.385). Correlations were generally stronger within force plate-based and isokinetic dynamometer-based assessments (r = 0.528–0.922) than between different testing conditions. Conclusions: Sex-related differences were observed for normalized knee flexor strength but not for LSI values. Strength outcomes obtained under different testing conditions should not be considered directly interchangeable. Full article

We study a special case of the extended Korteweg–de Vries (eKdV) equation, arising in the description of weakly nonlinear long waves with higher-order dispersive effects. The model incorporates both third- and fifth-order dispersion and quadratic nonlinearity and describes steeper and shorter waves than the classical KdV equation. First, we determine the Lie point symmetry algebra of the equation and show that it reduces to space–time translations, which in turn motivates a traveling-wave reduction. The reduced fifth-order ODE is then analyzed by means of a calibrated $(G^{\prime }/G)$-expansion ansatz. Although homogeneous balance suggests a degree $M=4$ for exact solutions, a degree-$M=2$ truncation already yields three coherent families of traveling waves—hyperbolic (solitary), trigonometric (periodic), and rational—distinguished by the discriminant of the auxiliary linear equation. Using the direct multiplier method, we construct four conservation laws, corresponding to mass, momentum, energy, and a higher-order dispersion invariant, with all ${\alpha }^2$ contributions retained. Direct substitution and numerical diagnostics demonstrate that, once the algebraic wave speed is imposed, the $M=2$ profiles satisfy the PDE with residuals of order ${10}^{-3}$ and preserve the conserved quantities to machine precision (below ${10}^{-13}\%$ relative variation) over extended integration domains. These results extend the known solution structure of the special eKdV equation and illustrate the effectiveness of the $(G^{\prime }/G)$ framework for higher-order dispersive models. Full article

Background and Objectives: Robotic-assisted total knee arthroplasty (rTKA) is being increasingly used to improve surgical precision, soft-tissue balancing, and functional recovery. However, evidence comparing rTKA with conventional manual TKA (mTKA) across functional, patient-reported, neuromotor, and safety outcomes remains heterogeneous. Materials and Methods: This narrative (non-systematic) review synthesises studies evaluating functional outcomes, patient-reported outcome measures (PROMs), joint awareness, range of motion (ROM), neuromotor recovery, and complications following rTKA versus mTKA. Study inclusion was based on author judgement and data accessibility. The reviewed evidence included five randomised controlled trials, 9 retrospective studies, six prospective non-randomised studies, two meta-analyses, one cross-sectional study, and one umbrella review, covering CT-based and imageless robotic platforms, including semi-active and active systems such as MAKO, NAVIO, CORI, ROSA, ROBODOC, CUVIS Joint, SkyWalker, TSolution One, AKEC, JIANJIA, and YUANHUA. Results: rTKA consistently demonstrated outcomes comparable to mTKA in PROMs (OKS, KOOS, WOMAC, KSS), with some studies reporting modest early improvements in pain and function. Joint awareness and patient satisfaction showed the most consistent early advantages for rTKA. Early postoperative ROM and neuromotor recovery, including balance and gait symmetry, were improved with rTKA, likely due to enhanced alignment and soft-tissue balancing; however, mid- and long-term outcomes were similar. Complication rates were low and comparable, with robotic-specific issues being rare and self-limited. Conclusions: rTKA provides small but reproducible early benefits in joint awareness, neuromotor function, and patient satisfaction, without clear long-term superiority. These early advantages may translate into meaningful population-level benefits, including faster recovery and potential healthcare cost reduction. Further high-quality studies are needed to assess long-term clinical and economic outcomes. Full article

Group equivariant convolutional neural networks (G-CNNs) achieve superior sample efficiency by encoding symmetry into network architecture, yet their computational overhead (up to 3.78× slower inference and 4.63× more multiply–accumulate operations) hinders deployment on resource-constrained edge devices. Existing pruning methods cannot be applied directly: arbitrarily removing weights breaks the group representation structure and degrades equivariance. We characterize the complete design space of equivariance-preserving compression, proving that exactly two axes leave a convolutional layer equivariant: irrep-bundle pruning, which reduces irreducible-representation multiplicities, and orbit-wise pruning, which removes complete spatial orbits from kernel supports; via Schur’s lemma, no third structure-preserving axis exists. This completeness result, rather than the use of representation theory itself, is our central contribution. We turn it into practice through direct sub-filter extraction, which yields real convolutional parameter reduction (up to 83%) and 1.4–2.9× measured inference speedup, unlike masking, which gives no real speedup. Across three datasets (MNIST, CIFAR-10, EuroSAT) and three symmetry groups (C₄, D₄, SO(2)), compression is nearly lossless on strongly symmetric data: the 4-layer EuroSAT model drops only 1.07% at 83% reduction. On weakly symmetric data (CIFAR-10), the pruned model can even gain 2.6 points, but our analysis attributes this to relaxing a mismatched equivariance constraint rather than to pruning itself; the value of pruning over from-scratch training scales with the data’s symmetry strength. Full article

This study investigates the role of symmetric probabilistic models in predicting financial distress in the automotive industry, with a focus on companies operating in the Slovak Republic. Financial distress prediction represents a binary classification problem characterized by an inherent symmetry between healthy and distressed firms. To capture this structure, two widely used symmetric models—logit and probit—are applied and systematically compared. The modeling framework incorporates LASSO regression for variable selection, enabling dimensionality reduction while preserving the most informative financial indicators. The empirical analysis is conducted on a dataset of 351 manufacturing enterprises. The results indicate that both models achieve comparable predictive performance, with the logit model reaching an accuracy of 78.9% and the probit model 77.8%. The area under the ROC curve further confirms the strong discriminatory power of both approaches. The findings highlight that the symmetric nature of the applied link functions contributes to model stability, interpretability, and balanced classification behavior. This study extends existing research by explicitly linking symmetry concepts with financial distress prediction in a sector-specific context. The proposed approach provides a transparent and practically applicable framework for early risk identification in industrial enterprises. Full article

This work presents a Fourier-domain encryption scheme for multiplexed image databases that integrates virtual-optical multiplexing with chaotic diffusion. By combining chaotic encryption with spectral-domain symmetry reduction, the proposed approach secures large multiplexed image datasets while reducing memory requirements and preserving reconstruction fidelity. A dataset of 2025 grayscale images ($512\times 512$ pixels) is multiplexed and encrypted using linear chaotic transformations applied separately to the amplitude (A) and phase ($\varphi$) components. To improve storage efficiency, the symmetry conditions of both spectral components are exploited, allowing a reduced portion of the Fourier plane to be stored while preserving accurate reconstruction. A performance landscape relating the correlation coefficient (CC), memory consumption, and the retained Fourier-plane percentage (FPP) is constructed to identify stable operating regions that balance reconstruction fidelity and compression under increasing multiplexing load. The encryption key consists of a 22-symbol ASCII string from which 84 seed parameters for a deterministic pseudorandom chaotic map are derived. Security and sensitivity analyses demonstrate strong key dependence and resistance to statistical attacks, while maintaining high reconstruction fidelity. The proposed scheme provides an efficient and scalable solution for secure large-scale image repositories. Full article

Determining the safe thickness of a boundary crown pillar is critical during the transition from open-pit to underground mining, as it directly affects both mining safety and resource recovery. Crown pillar instability is commonly associated with asymmetric stress redistribution, nonuniform deformation, and progressive plastic failure. In this study, the Kumusayi Li-Nb-Ta mine in Xinjiang, China, was selected as an engineering case to optimize the boundary crown pillar thickness and evaluate its deformation characteristics. Four theoretical methods, namely the load transfer intersection method, span-to-thickness ratio method, simplified structural beam method, and Rubeneeite formula method, were first used to determine the feasible thickness range. The calculated thicknesses were 19.99, 14.00, 29.81, and 10.41 m, respectively, yielding an engineering design interval of 14.00–29.81 m. Based on this interval, four thickness schemes of 15, 20, 25, and 30 m were evaluated using FLAC3D simulations in terms of stress redistribution, displacement evolution, surface movement, plastic-zone development, and deformation symmetry. The results show that the 15 m pillar exhibits pronounced stress concentration, asymmetric deformation, and through-going plastic failure, indicating insufficient stability. Although the 20 m pillar improves the load-bearing capacity, a potential connected failure path remains. At 25 m, the high-stress zone becomes localized, the plastic zone no longer penetrates the pillar, and the maximum vertical displacement decreases by approximately 27.0% compared with the 15 m scheme. Increasing the thickness to 30 m provides limited additional improvement, with less than a 2% reduction in maximum vertical displacement compared with the 25 m scheme. Physical similarity model tests further confirm that a 20.8 cm model pillar, corresponding to a 25 m prototype pillar, effectively prevents through-going cracking and overall slope sliding. Therefore, a 25 m boundary crown pillar is recommended for the Kumusayi mine. Full article

This manuscript proves the global existence and uniqueness of helically symmetric weak solutions to the 3D time-dependent Ginzburg–Landau model of superconductivity in ${\mathbb{R}}^3$ with $L^2$ initial data and supports the choice of the Lorentz gauge. For this, we define helical symmetry using cylindrical coordinates $(r,\theta ,z)$ and a helical variable $\xi =n\theta +\alpha z$, where n is an even integer and $\alpha >0$. This reduction allows the 3D system to be treated with specific geometric constraints. The imposition of helical symmetry effectively reduces the dimension of the problem, thereby making $L^2$ the new critical space. Full article

Reliable short-term wind power forecasting is crucial for smart grid stability. However, high-dimensional noise and stochastic fluctuations in wind sequences often degrade the accuracy of traditional forecasting models. Moreover, wind power time series typically exhibit asymmetric rising and decaying patterns, which further complicate accurate modeling. To address these challenges, this study proposes a hybrid intelligent system that integrates three components: data preprocessing, heterogeneous ensemble learning, and probabilistic interval forecasting. First, we build a multi-stage preprocessing workflow. Adaptive DBSCAN and Local Outlier Factor (LOF) remove spatial and density anomalies. Then multivariate variational mode decomposition (MVMD) synchronously separates multi-scale oscillatory patterns while preserving cross-channel correlations and frequency-domain symmetry across input variables. SHAP analysis quantifies feature importance, ensuring interpretability. The selected features are fed into a heterogeneous ensemble model consisting of Transformer, BPNN, ELM, XGBoost, and QRLSTM, which collectively capture multi-scale temporal dependencies and diverse data patterns. The ensemble weights are dynamically optimized by a modified multi-objective dragonfly algorithm (MMODA) that balances forecast accuracy and stability. Based on this ensemble, we apply MMODA to tune kernel density estimation for generating high-quality forecast intervals, maximizing coverage while minimizing interval width. Experiments on two wind farms in Shandong show that our MMODA-optimized ensemble reduces mean absolute percentage error by about 44.7% compared to single models, and ablations confirm that MVMD preprocessing adds a further 10.7% reduction. The proposed system provides an interpretable and reliable decision-support tool for sustainable grid operations. Full article

Background/Objectives: Posterior endoscopic cervical foraminotomy is an established motion-preserving procedure for selected patients with unilateral cervical radiculopathy. However, isolated foraminal decompression may be insufficient in cases with concomitant foraminal stenosis and lateral soft disk herniation. This preliminary study evaluated clinical outcomes and quantitative MRI changes after combined posterior endoscopic cervical diskectomy and foraminotomy (CEDF) and explored the relationship between postoperative foraminal enlargement and clinical improvement. Methods: This retrospective single-center exploratory cohort study included 15 consecutive patients with single-level unilateral cervical radiculopathy caused by combined foraminal stenosis and lateral soft disc herniation who were treated between 2021 and 2023. All patients underwent CEDF using a posterior full-endoscopic approach. Clinical outcomes were assessed preoperatively, at 6 weeks, and at 12 months using the Visual Analog Scale for arm and neck pain, the Neck Disability Index, and modified MacNab criteria. Quantitative MRI assessment included minimal foraminal diameter, Foraminal Symmetry Index (FSI), and Quantitative Cervical Expansion (QCE). Correlations between radiological and clinical outcomes were analyzed as exploratory, hypothesis-generating analyses. Results: Mean minimal foraminal diameter increased from 1.9 ± 0.7 mm preoperatively to 4.1 ± 0.8 mm postoperatively, with improvement in FSI from 0.40 ± 0.12 to 0.89 ± 0.11. Significant clinical improvement was observed across all outcome measures. Mean arm pain decreased from 7.2 ± 1.3 preoperatively to 1.3 ± 1.4 at final follow-up, while NDI improved from 48.0 ± 14.0% to 18.3 ± 12.0%. The minimum clinically important difference for arm pain reduction was achieved in 14 of 15 patients. A moderate positive exploratory association was observed between foraminal enlargement and reduction in arm pain severity. No major neurological complications, postoperative instability, or revision procedures were observed in this small cohort during the available follow-up. Conclusions: In this preliminary retrospective single-center cohort, CEDF was associated with clinical improvement and measurable postoperative foraminal enlargement in carefully selected patients with unilateral cervical radiculopathy caused by combined foraminal stenosis and lateral soft disc herniation. The observed association between foraminal enlargement and arm pain reduction should be interpreted cautiously because of the small sample size and exploratory design. QCE and FSI should be regarded as preliminary quantitative radiological indices rather than validated markers of decompression adequacy or clinical response. Larger prospective comparative studies are required to validate these findings and define the role of CEDF among established cervical decompression procedures. Full article