Search Results (668)

Background: Walking cadence is commonly adjusted in sport and rehabilitation, yet its effects on spatiotemporal gait parameters and regional plantar pressure distribution under controlled speed conditions remain incompletely characterized. Therefore, this study aimed to determine whether imposed cadence increases at a constant walking speed would (i) systematically reduce temporal gait parameters while preserving inter-limb symmetry and (ii) be associated with region-specific increases in forefoot plantar loading, representing the primary novel contribution of this work. Methods: Fifty-two adults walked at three imposed cadences (110, 120, 130 steps·min⁻¹) while maintaining a fixed treadmill speed of 1.39 m·s⁻¹ via auditory biofeedback. Spatiotemporal parameters were recorded with an OptoGait system, and plantar pressure distribution was measured using in-shoe pressure insoles. Normally distributed variables were analyzed using repeated-measures ANOVA, whereas plantar pressure metrics were assessed using the Friedman test, followed by Wilcoxon signed-rank post-hoc comparisons with false discovery rate (FDR) correction. Associations between temporal parameters and plantar loading metrics (peak pressure, pressure–time integral) were examined using Spearman’s rank correlation with FDR correction (α = 0.05). Results: Increasing cadence produced progressive reductions in gait cycle duration (~8–10%), contact time (~7–8%), and step time (all p < 0.01), while inter-limb symmetry indices remained below 2% across conditions. Peak plantar pressure increased significantly in several forefoot regions with increasing cadence (all p_FDR < 0.05), whereas changes in the first ray were less consistent across conditions. Regional forefoot pressure–time integral also increased modestly with higher cadence (p_FDR < 0.01). Spearman’s correlations revealed moderate negative associations between temporal gait parameters and global plantar loading metrics (ρ = −0.38 to −0.46, all p_FDR < 0.05). Conclusions: At a constant walking speed, increasing cadence systematically shortens temporal gait components and is associated with small but consistent region-specific increases in forefoot plantar loading. These findings highlight cadence as a key temporal constraint shaping plantar loading patterns during steady-state walking and support the existence of concurrent temporal–mechanical adaptations. Full article

Industrial-grade printed circuit boards (PCBs) exhibit high structural order and inherent geometric symmetry, where minute surface defects essentially constitute symmetry-breaking anomalies that disrupt topological integrity. Detecting these anomalies is quite challenging due to issues like scale variation and low contrast. Therefore, this paper proposes a symmetry-aware object detection framework, DAS-YOLO, based on an improved YOLOv11. The U-shaped adaptive feature extraction module (Def-UAD) reconstructs the C3K2 unit, overcoming the geometric limitations of standard convolutions through a deformation adaptation mechanism. This significantly enhances feature extraction capabilities for irregular defect topologies. A semantic-aware module (SADRM) is introduced at the backbone and neck regions. The lightweight and efficient ESSAttn improves the distinguishability of small or weak targets. At the same time, to address information asymmetry between deep and shallow features, an iterative attention feature fusion module (IAFF) is designed. By dynamically weighting and calibrating feature biases, it achieves structured coordination and balanced multi-scale representation. To evaluate the validity of the proposed method, we carried out comprehensive experiments using publicly accessible datasets focused on PCB defects. The results show that the Recall, mAP@50, and mAP@50-95 of DAS-YOLO reached 82.60%, 89.50%, and 46.60%, respectively, which are 3.7%, 1.8%, and 2.9% higher than those of the baseline model, YOLOv11n. Comparisons with mainstream detectors such as GD-YOLO and SRN further demonstrate a significant advantage in detection accuracy. These results confirm that the proposed framework offers a solution that strikes a balance between accuracy and practicality in addressing the key challenges in PCB surface defect detection. Full article

This study addresses a key limitation of conventional clay constitutive models, which often assume linear stress paths at low stress ratios and lack a systematic link between plasticity and yield surface shape. A symmetry-consistent bounding surface plasticity framework is proposed, introducing two shape parameters, Ψ and Ω, to control curvature and scaling of the yield surface under low stress ratios. The formulation preserves a unified, smooth yield function with continuous gradients, ensuring compatibility with standard numerical integration schemes. To enhance practical applicability, a three-level calibration strategy is established, ranging from direct triaxial interpretation to empirical correlations based on oedometer-derived indices. Model performance is validated against experimental data for clays with varying plasticity, demonstrating improved representation of curved stress paths without increasing formulation complexity. The proposed approach provides a transparent and reproducible extension to existing frameworks, bridging the gap between theoretical consistency and engineering-oriented calibration. Full article

Intimate relationship stability is fundamental to human wellbeing, yet its quantitative assessment faces dual challenges: the inherent subjectivity of psychological constructs and the complexity of social ecosystems. Symmetry, as a fundamental structural feature of social interaction, plays a pivotal role in shaping relational dynamics. To address these limitations, this study proposes an innovative computational framework that integrates Fuzzy Set Theory with Social Network Analysis (SNA). The framework consists of two complementary components: (1) a psychologically grounded fuzzy assessment model that employs differentiated membership functions to transform discrete subjective ratings into continuous and interpretable relationship quality indices and (2) an enhanced Fuzzy C-Means (FCM) threat detection model that utilizes Weighted Mahalanobis Distance to accurately identify and cluster potential interference sources within social networks. Empirical validation using a simulated dataset—comprising typical characteristic samples from 10 couples—demonstrates that the proposed framework not only generates interpretable relationship diagnostics by correcting biases associated with traditional averaging methods, but also achieves high precision in threat identification. The results indicate that stable relationships exhibit greater symmetry in partner interactions, whereas threatened nodes display structural and behavioural asymmetry. This study establishes a rigorous mathematical paradigm—“Subjective Fuzzification → Multidimensional Feature Engineering → Intelligent Clustering”—for relationship science, thereby advancing the field from descriptive analysis toward data-driven, quantitative evaluation and laying a foundation for systematic assessment of relational health. Full article

This study focuses on classifying electromyographic (EMG) signals to identify seven specific hand movements, including complete hand closure, individual finger closures, and a pincer grip. Accurately distinguishing these movements is challenging due to overlapping muscle activation patterns. To address this, a methodology structured in five stages was developed: placement of electrodes on specific forearm muscles to capture electrical activity during movements; acquisition of EMG signals from twelve participants performing the seven types of movements; preprocessing of the signals through filtering and rectification to enhance quality, followed by the extraction of features from three distinct types of preprocessed signals—filtered, rectified, and envelope signals—to facilitate analysis in the temporal, frequency, and time–frequency domains; extraction of relevant features such as amplitude, shape, symmetry, and frequency variance; and classification of the signals using eight machine learning algorithms: support vector machine (SVM), multiclass logistic regression, k-nearest neighbors (k-NN), Bayesian classifier, artificial neural network (ANN), random forest, XGBoost, and LightGBM. The performance of each algorithm was evaluated using different sets of features derived from the preprocessed signals to identify the most effective approach for classifying hand movements. Additionally, the impact of various signal representations on classification accuracy was examined. Experimental results indicated that some algorithms, especially when an expanded set of features was utilized, achieved improved accuracy in classifying hand movements. These findings contribute to the development of more efficient control systems for myoelectric prostheses and offer insights for future research in EMG signal processing and pattern recognition. Full article

This study presents a comprehensive structural optimization workflow for a railway motor bogie frame, aimed at developing an innovative and lightweight design compliant with the reference European standards. The methodology integrates a two-stage topology optimization process, supported by an extensive numerical simulation campaign and a dedicated sensitivity analysis to identify the most critical load scenarios. In the first optimization stage, a global evaluation of the frame performance revealed that increasing the number of optimization parameters leads to a rise of approximately 50% in solver iterations. Symmetry constraints proved essential for simplifying both the optimization and the subsequent geometric reconstruction. The minimum feasible feature dimension strongly affected the final solution, modifying the material distribution and enabling a mass reduction of about 18%. The second optimization stage, focused on the cross beams, highlighted the relevance of manufacturing constraints in guiding the solver toward practical configurations. Static and fatigue assessments confirmed stress distributions consistent with the original frame, providing designers with a reliable basis for future material upgrades. Finally, the dynamic analysis showed a first natural frequency above 60 Hz, with variations in the first eigenvalue within 1% and preservation of the local flexural mode shape, ensuring full compatibility with the original frame interfaces and enabling seamless replacement with the optimized configuration. Full article

Multimessenger constraints tightly bound the gravitational-wave speed to be luminal, posing a strong filter for modified gravity. This paper develops a symmetry-selected Palatini framework with torsion in which exact luminality at quadratic order is achieved by construction rather than by parameter tuning. Two ingredients shape the observable sector: (i) a scalar PT projector that keeps scalar densities real and parity-even, and (ii) projective invariance implemented via a non-dynamical Stueckelberg compensator that enters only through its gradient. Under an explicit posture (A1–A6), we establish three structural results: (C1) algebraic uniqueness of torsion to a pure-trace form aligned with the compensator gradient; (C2) bulk equivalence, modulo improvements, among a rank-one determinant route, a closed-metric deformation, and a PT-even CS/Nieh–Yan route; and (C3) a coefficient-locking identity that enforces $K=G$ for tensor modes on admissible domains; hence, $c_T=1$ with two propagating polarizations. Beyond leading order, the framework yields a distinctive, falsifiable next-to-leading correction $\delta c_T^2\left(k\right)=b{k}^2/{\mathrm{\Lambda }}^2$ (for $k\ll \mathrm{\Lambda }$), predicting slope 2 in log–log fits across frequency bands (PTA/LISA/LVK). The analysis is formulated to be reproducible, with a public repository providing figure generators, coefficients, and tests that directly validate (C1)–(C3). Full article

The para-positronium system $\left({}^{1}S_{0}Ps\right)$ is described by means of specially constructed coherent states (CSs) in the Klauder–Perelomov sense. It is analyzed from the physical point of view and from the geometry underlying the relevant symmetry group establishing the dynamics of the processes. In this new theoretical context, the possibility of a gamma-ray laser emission is investigated within a QFT context, showing explicitly that, in addition to the oscillator solution based only on a Bogoliubov approximation for the condensate, there is a second phase or “squeezed” stage by which physical features beyond the classical ones appear. Explicitly, while the generated photons are in the active medium (e.g., Ps-BEC), the evolution is described by a Heisenberg–Weyl coherent state with displacement operators dependent on the interaction time, which is related to the condensate shape. After the interaction time has elapsed, we explicitly demonstrate that the displacement operator of the ${}^{1}S_{0}Ps$ is transformed into a squeezed operator of the photonic fields modulated by the matrix element of the Positronium decay ${\mathcal{M}}_{{}^{1}S_{0}Ps}\to 2\gamma$. We also show that this squeezed operator (belonging to the Metaplectic group) generates a non-classical radiation state spanning only even (s = 1/4) levels in the number of photons. The implications in astrophysical systems of interest, considering gamma-ray coherent emission and the possibility of an ${}^{1}S_{0}Ps-BEC$ in the context of pulsars, blazars, and quasars, are briefly discussed. Full article

Nanoscopic quantum dots exhibit discrete energy spectra and size- and shape-dependent thermal properties that cannot always be adequately described within the conventional Boltzmann–Gibbs statistical framework. In systems with strong confinement, finite size, and reduced symmetry, deviations from extensivity may emerge, affecting the occupation of energy levels and the resulting thermodynamic response. In this context, this work elucidates how GaAs quantum dot geometry, external electric fields, and nonextensive statistical effects jointly influence the thermal response of quantum dots with different geometries—cubic, cylindrical, ellipsoidal, and pyramidal. These energy levels are calculated by solving the Schrödinger equation under the effective mass approximation, employing the finite element method for numerical computation. These energy levels are then incorporated into an iterative numerical procedure to calculate the specific heat for different values of the nonextensivity parameter, thereby enabling exploration of both extensive (Boltzmann–Gibbs) and nonextensive regimes. The results demonstrate that the shape of the quantum dots strongly influences the energy spectrum and, consequently, the thermal properties, producing distinctive features such as Schottky-type anomalies and geometry-dependent shifts under an external electric field. In subextensive regimes, a discrete behavior in the specific heat emerges due to natural cutoffs in the accessible energy states. In contrast, in superextensive regimes, a smooth, saturation-like behavior is observed. These findings highlight the importance of geometry, external-field effects, and nonextensive statistics as complementary tools for tailoring the energy distribution and thermal response in nanoscopic quantum systems. Full article

Pediatric pneumonia detection faces the challenge of pathological asymmetry, where immature lung tissues present blurred boundaries and lesions exhibit extreme scale variations (e.g., small viral nodules vs. large bacterial consolidations). Conventional detectors often fail to address these imbalances. In this study, we propose YOLO-SMD, a detection framework built upon a symmetrical design philosophy to enforce balanced feature representation. We introduce three architectural innovations: (1) DySample (Content-Aware Upsampling): To address the blurred boundaries of pediatric lesions, this module replaces static interpolation with dynamic point sampling, effectively sharpening edge details that are typically smoothed out by standard upsamplers; (2) SAC2f (Cross-Dimensional Attention): To counteract background interference, this module enforces a symmetrical interaction between spatial and channel dimensions, allowing the model to suppress structural noise (e.g., rib overlaps) in low-contrast X-rays; (3) SDFM (Adaptive Gated Fusion): To resolve the extreme scale disparity, this unit employs a gated mechanism that symmetrically balances deep semantic features (crucial for large bacterial shapes) and shallow textural features (crucial for viral textures). Extensive experiments on a curated subset of 2611 images derived from the Chest X-ray Pneumonia Dataset demonstrate that YOLO-SMD achieves competitive performance with a focus on high sensitivity, attaining a Recall of 86.1% and an mAP@0.5 of 84.3%, thereby outperforming the state-of-the-art YOLOv12n by 2.4% in Recall under identical experimental conditions. The results validate that incorporating symmetry principles into feature modulation significantly enhances detection robustness in primary healthcare settings. Full article

In this study, equidistant ruled surfaces generated by the Darboux vector, which has significant kinematic importance and characterizes the instantaneous rotation of a moving frame, are investigated specifically for the Frenet frame. By establishing a structural relationship between a surface and its equidistant ruled surface, transition formulas are provided for shape operators, Gaussian and mean curvatures, and fundamental forms, revealing that the equidistant surface is a scaled transformation of the original one. The obtained results demonstrate that both surfaces are developable and that the geometric properties of the equidistant ruled surfaces can be expressed dependently on each other. Furthermore, it is shown that the geometric character of the equidistant surface, including the invariance of asymptotic lines and the preservation of umbilical points under constant angle conditions, is determined by the rotational dynamics of the base curve. These findings constitute a theoretical foundation for cases involving the use of Darboux axes of different frames in higher dimensions or the investigation of similar structures in different geometric spaces. The geometric interpretation of this theoretical framework is elucidated through the fundamental properties of the surfaces. Finally, a concrete example is presented, where the symmetry of the central planes of the equidistant ruled surfaces at appropriate points is visualized using Maple 2017 software. Full article

This paper proposes a symmetrized extrinsic information transfer (S-EXIT) chart analysis for probabilistic shaped (PS) systems to optimize the joint decoding of low-density parity-check (LDPC) codes and constant composition distribution matchers (CCDMs). A major challenge in analyzing PS systems is the non-uniform channel input caused by shaping, which invalidates the all-zero assumption of traditional EXIT charts, coupled with the three-node structure of the joint decoder (variable nodes, check nodes, and shaping nodes) that exceeds the two-decoder framework of conventional EXIT analysis. To resolve these issues, we first prove the symmetry of the joint decoder and introduce a “symmetrized density” transformation to render the channel output symmetric, thereby enabling the extension of EXIT chart analysis to PS systems. We then approximate the EXIT function of the shaping node decoder via polynomial fitting and integrate it with the variable node decoder into a unified model (VSND) for threshold analysis. On one hand, the proposed S-EXIT chart provides a theoretical threshold for the joint decoder, which is crucial for guiding system design. On the other hand, it enables the joint optimization of LDPC code rates and CCDM rates, unlocking additional performance gains. Simulations over additive white Gaussian noise (AWGN) channels demonstrate that short-blocklength CCDMs (e.g., blocklength 20) achieve up to 1.2 dB gain over uniform systems via S-EXIT-based rate optimization. This work addresses the performance limitations of short-blocklength CCDMs in high-speed optical transmissions, offering a practical and efficient analytical tool for PS system design. Full article

Symmetry and asymmetry jointly govern the dynamics and surface integrity of thin-wall AA7075 end milling. In this work, a symmetry-aware simulation and experimental framework is developed to connect process parameters with milling forces, dynamic response, surface quality, and through-thickness residual stress. A mechanistic milling-force model is first established for multi-tooth end milling, where the periodically repeated tooth-order excitation provides a nominally symmetric load pattern along the tool path. The predicted forces are then used as input for finite-element modal and harmonic-response analysis of a thin-walled component, revealing how symmetric and anti-symmetric mode shapes interact with the tooth-order excitation to generate locally amplified, asymmetric vibration of the compliant wall. Orthogonal and single-factor milling experiments on AA7075 thin-wall specimens are performed to calibrate and validate the force model, and to quantify the influence of feed per tooth, axial depth of cut, spindle speed, and radial width of cut on deformation, surface roughness, and geometric accuracy. Finally, a thermo-mechanically coupled finite-element model is employed to evaluate the residual-stress field, showing a characteristic pattern in which an initially symmetric thermal–mechanical loading produces depth-wise symmetry breaking between tensile surface layers and compressive subsurface zones. The proposed symmetry-aware framework, which combines milling-force theory, finite-element simulation, and systematic experiments, provides practical guidance for selecting parameter windows that suppress vibration, control residual stress, and improve the machining quality of thin-wall AA7075 components. Full article

This study addressed the issue of insufficient lubrication in the thrust washer of the planetary gear reducer during operation. Numerical simulations were performed under fixed operating conditions, combined with sequential optimization strategy, to systematically investigate the influence of V-shaped texture distribution and geometric parameters on lubrication characteristics during unidirectional rotation. The results revealed that, under the examined texture parameters, the oil film pressure increased significantly with increasing radial velocity from inner to outer radius and lubricant viscosity, with area density being the key parameter influencing load-carrying capacity. Moreover, selectively enhancing the texture density in the outer ring region effectively alleviated wear caused by stress concentration in that area. The optimal V-shaped texture parameters were determined as follows: a length ratio of 5, an angle of 30°, an area density of 24.52%, and a depth of 0.02 mm. The symmetry axis of the texture was oriented opposite to the fluid velocity, and the texture distribution exhibited radial densification. This study will inform the design of surface textures and enhance the lubrication performance of mechanical components in thrust washers and similar rotational operating conditions. Full article

Over the last decade, numerical simulations and experiments have confirmed the existence of a novel class of vibrationally excited solid-particle attractors in cubic cavities containing a fluid in non-isothermal conditions. The diversity of emerging particle structures, in both morphology and multiplicity, depends strongly on the uni- or multi-directional nature of the imposed temperature gradients. The present study seeks to broaden this theoretical framework by further increasing the complexity of the thermal “information” coded along the external boundary of the fluid container. In particular, in place of the thermal inhomogeneities located in the center of otherwise uniformly cooled or heated walls, here, a cubic cavity with temperature boundary conditions satisfying the D₂h (in Schoenflies notation) or “mmm” (in Hermann–Mauguin notation) symmetry is considered. This configuration, equivalent to a bipartite vertex coloring of a cube leading to a total of 24 thermally controlled planar surfaces, possesses three mutually perpendicular twofold rotation axes and inversion symmetry through the cube’s center. To reduce the problem complexity by suppressing potential asymmetries due to fluid-dynamic instabilities of inertial nature, the numerical analysis is carried out under the assumption of dilute particle suspension and one-way solid–liquid phase coupling. The results show that a kaleidoscope of new particle structures is enabled, whose main distinguishing mark is the essentially one-dimensional (filamentary) nature. These show up as physically disjoint or intertwined particle circuits in striking contrast to the single-curvature or double-curvature spatially extended accumulation surfaces reported in earlier investigations. Full article