Search Results (1,446)

This paper presents a novel four-dimensional (4D) chaotic system exhibiting parametric symmetry breaking and multistability. Through equilibrium stability analysis, attractor reconstruction, Lyapunov Exponent spectra (LEs), and bifurcation diagrams, we reveal a continuous transition from symmetric period attractors to asymmetric chaotic states and rich dynamical behaviors. Additionally, considering the potential of this system in practical applications, a feedback control simulation circuit is designed and implemented to ensure its stability and effectiveness under real-world conditions. Finally, among various control strategies, this paper proposes an innovative Fixed-Time Sliding Mode Synchronization (FTSMS) strategy, determines its synchronization convergence time, and provides an important theoretical foundation for the practical application of the system. Full article

Bi₆Fe₂Ti₃O₁₈ (BFTO) ceramics were synthesized via a solid-state reaction route using stoichiometric amounts of Bi₂O₃, TiO₂, and Fe₂O₃ powders. A thermal analysis of the powder mixture was conducted to optimize the heat treatment parameters. Energy-dispersive X-ray spectroscopy (EDS) confirmed the conservation of the chemical composition following calcination. Final densification was achieved through hot pressing. The crystal structure of the sintered samples, examined via X-ray diffraction at room temperature, revealed a tetragonal symmetry for BFTO ceramics sintered at 850 °C. Electron backscatter diffraction (EBSD) provided detailed insight into the crystallographic orientation and microstructure. Broadband dielectric spectroscopy (BBDS) was employed to investigate the dielectric response of BFTO ceramics over a frequency range of 10 mHz to 10 MHz and a temperature range of −30 °C to +200 °C. The temperature dependence of the relative permittivity (ε_r) and dielectric loss tangent (tan δ) were measured within a frequency range of 100 kHz to 900 kHz and a temperature range of 25 °C to 570 °C. The impedance data obtained from the BBDS measurements were validated using the Kramers–Kronig test and modeled using the Kohlrausch–Williams–Watts (KWW) function. The stretching parameter (β) ranged from ~0.72 to 0.82 in the impedance formalism within the temperature range from 200 °C to 20 °C. Full article

Object detection in remote sensing imagery is critical in environmental monitoring, urban planning, and land resource management. However, the task remains challenging due to significant scale variations, arbitrary object orientations, and complex background clutter. To address these issues, we propose a novel orientation module (SOAM Block) that jointly models object scale and directional features while exploiting geometric symmetry inherent in many remote sensing targets. The SOAM Block is constructed upon a lightweight and efficient Adaptive Multi-Scale (AMS) Module, which utilizes a symmetric arrangement of parallel depth-wise convolutional branches with varied kernel sizes to extract fine-grained multi-scale features without dilation, thereby preserving local context and enhancing scale adaptability. In addition, a Strip-based Context Attention (SCA) mechanism is introduced to model long-range spatial dependencies, leveraging horizontal and vertical 1D strip convolutions in a directionally symmetric fashion. This design captures spatial correlations between distant regions and reinforces semantic consistency in cluttered scenes. Importantly, this work is the first to explicitly analyze the coupling between object scale and orientation in remote sensing imagery. The proposed method addresses the limitations of fixed receptive fields in capturing symmetric directional cues of large-scale objects. Extensive experiments are conducted on two widely used benchmarks—DOTA and HRSC2016—both of which exhibit significant scale variations and orientation diversity. Results demonstrate that our approach achieves superior detection accuracy with fewer parameters and lower computational overhead compared to state-of-the-art methods. The proposed SOAM Block thus offers a robust, scalable, and symmetry-aware solution for high-precision object detection in complex aerial scenes. Full article

In this work, the microstructure and mechanical properties of the FeAlCrNiV complex concentrated alloy (CCA) were studied in the as-cast and annealed states. The material was annealed at 800 °C for 16 days to test microstructure stability and phase evolution. It was found that the microstructure does not differ in the two investigated states, and the results of differential scanning calorimetry and dilatometry showed that there is almost no difference in the thermal response between the as-cast and annealed states. Both investigated states exhibit eutectic structure with bcc solid solution and ordered phase with B2 symmetry. In a single grain, several regions with B2 laths in the bcc matrix were observed. Inside the B2 laths and in the bcc matrix, bcc spheres and B2 spheres were observed, respectively. All three features—laths, matrix and spheres—are fully crystallographically coherent. Nevertheless, in the adjacent region in the grain, the crystal structure of the matrix, laths and sphere changed to the other structure, i.e., the characteristics of the microstructure feature with B2 symmetry changed to bcc, and vice versa. Compression deformation tests were performed for various temperatures from room temperature to 800 °C. The results showed that the material exhibits exceptional yield stress values, especially at high temperatures (820 MPa/800 °C), and excellent plasticity (25%). Full article

In lace textile manufacturing, the dyeing process in parallel machine environments faces challenges from sequence-dependent setup times due to color family transitions, machine eligibility constraints based on weight capacities, and probabilistic re-dyeing operations arising from quality inspection failures, which often lead to increased tardiness. To tackle this multi-constrained problem, a stochastic integer programming model is formulated to minimize total estimated tardiness. A novel symmetry-driven two-population collaborative differential evolution (TCDE) algorithm is then proposed. It features two symmetrically complementary subpopulations that achieve a balance between global exploration and local exploitation. One subpopulation employs chaotic parameter adaptation through a logistic map for symmetrically enhanced exploration, while the other adjusts parameters based on population diversity and convergence speed to facilitate symmetry-aware exploitation. Moreover, it also incorporates a symmetrical collaborative mechanism that includes the periodic migration of top individuals between subpopulations, along with elite-set guidance, to enhance both population diversity and convergence efficiency. Extensive computational experiments were conducted on 21 small-scale (optimally validated via CVX) and 15 large-scale synthetic datasets, as well as 21 small-scale (similarly validated) and 20 large-scale industrial datasets. These experiments demonstrate that TCDE significantly outperforms state-of-the-art comparative methods. Ablation studies also further verify the critical role of its symmetry-based components, with computational results confirming its superiority in solving the considered problem. Full article

A real-space renormalization group (RG) framework is formulated for classical SO(n) spin models defined on d-dimensional crystal lattices composed of corner-sharing hyper-tetrahedra, a class of geometrically frustrated crystal structures. This includes, as specific instances, the classical Heisenberg model on the kagome and pyrochlore crystals. The approach involves computing the partition function and corresponding order parameters for spin clusters embedded in the crystal, to leading order in symmetry-breaking fields generated by surrounding spins. The crystal geometry plays a central role in determining the scaling relations and the associated critical behavior. To illustrate the efficacy of the method, a reduced manifold of symmetry-allowed ordered states for isotropic nearest-neighbor interactions is analyzed. The RG flow systematically excludes the emergence of a $\overrightarrow{q}=\mathbf{0}$ ordered phase within the antiferromagnetic sector, independently of both the spatial dimensionality of the crystal and the number of spin components. Extensions to incorporate more elaborate crystal-symmetry-induced ordering patterns and fluctuation-driven phenomena—such as order-by-disorder—are also discussed. Full article

Skeleton-based action recognition is an important subject in deep learning. Graph Convolutional Networks (GCNs) have demonstrated strong performance by modeling the human skeleton as a natural topological graph, representing the connections between joints. However, most existing methods rely on non-adaptive topologies or insufficiently expressive representations. To address these limitations, we propose a Multi-view Topology Refinement Graph Convolutional Network (MTR-GCN), which is efficient, lightweight, and delivers high performance. Specifically: (1) We propose a new spatial topology modeling approach that incorporates two views. A dynamic view fuses joint information from dual streams in a pairwise manner, while a static view encodes the shortest static paths between joints, preserving the original connectivity relationships. (2) We propose a new MultiScale Temporal Convolutional Network (MSTC), which is efficient and lightweight. (3) Furthermore, we introduce a new temporal topology strategy by modeling temporal frames as a graph, which strengthens the extraction of temporal features. By modeling the human skeleton as both a spatial and a temporal graph, we reveal a topological symmetry between space and time within the unified spatio-temporal framework. The proposed model achieves state-of-the-art performance on several benchmark datasets, including NTU RGB + D (XSub: 92.8%, XView: 96.8%), NTU RGB + D 120 (XSub: 89.6%, XSet: 90.8%), and NW-UCLA (95.7%), demonstrating the effectiveness of our GCN module, TCN module, and overall architecture. Full article

In this work, we introduce a novel method to extract correlations in diagonal quantum states in multi-particle quantum systems, addressing a significant limitation of traditional approaches that require prior knowledge of the density matrices of quantum states. Instead of relying on classical information processing, our method is based on weak couplings and ancillary systems, eliminating the need for classical communication, optimization, and complex calculations. The concept of mutually unbiased bases is intrinsically linked to symmetry, as it entails the uniform distribution of quantum states across distinct bases. Within the framework of our theoretical model, mutually unbiased bases are employed to facilitate weak measurements and to function as the post-selected states. To quantify the correlations in the initial state, we employ the trace distance between the initial state and the product of its marginal states, and illustrate the feasibility and effectiveness of our approach. We generalize the approach to accommodate high-dimensional multi-particle systems for potential applications in quantum information processing and quantum networks. Full article

Based on the principle of symmetry, we propose a variable step-size FxLMS algorithm with double nonlinear functions cooperative coupling (DNVSS-FxLMS), aiming to optimize the contradiction between convergence rate and steady-state error in the active pressure pulsation control system of hydraulic systems. The algorithm innovatively couples two types of nonlinear mechanisms (rational-fractional and exponential-function-based), constructing a refined error-step mapping relationship to achieve a balance between rapid convergence and low steady-state error. Simulation experiments were conducted considering the complex time-varying operating environment of a simulation-based hydraulic system. The results demonstrate that, when the system undergoes unstable random changes, the DNVSS-FxLMS algorithm converges at least twice as fast as traditional and existing variable step size algorithms, while reducing steady-state error by 2–5 dB. The proposed DNVSS-FxLMS algorithm exhibits significant advantages in convergence rate, steady-state error reduction, and tracking capability, providing a highly efficient and robust solution for real-time active control of hydraulic system pressure pulsation under complex operating conditions. Full article

This paper addresses the problem of optimizing obesity, which has been a challenging issue in the last decade based on recent data revealed in 2024 by the World Health Organization (WHO). The current work introduces a new mathematical model of the dynamics of weight over time with embedded control parameters to optimize the number of obese, overweight, and comorbidity populations. The mathematical formulation of the model is developed under certain sufficient conditions that guarantee the positivity and boundedness of solutions over time. The model structure exhibits inherent symmetry in population group transitions, particularly around the equilibrium state, which allows the application of analytical tools such as the Routh–Hurwitz and Metzler criteria. Then, the analysis of local and global stability of the obesity-free equilibrium state is discussed based on these criteria. Based on the Pontryagin maximum principle (PMP), the deviation from the obesity-free equilibrium state is controlled. The model’s effectiveness is demonstrated through simulation using the Forward–Backward Sweeping algorithm with parameters derived from recent research in human health. Incorporating symmetry considerations in the model enhances the understanding of system behavior and supports balanced intervention strategies. Results suggest that the model can effectively inform strategies to mitigate obesity prevalence and associated health risks. Full article

A model for the flow and thermal explosion of a micropolar gas is investigated, assuming the equation of state for a real gas. This model describes the dynamics of a gas mixture (fuel and oxidant) undergoing a one-step irreversible chemical reaction. The real gas model is particularly suitable in this context because it more accurately reflects reality under extreme conditions, such as high temperatures and high pressures. Micropolarity introduces local rotational dynamic effects of particles dispersed within the gas mixture. In this paper, we first derive the initial-boundary value system of partial differential equations (PDEs) under the assumption of spherical symmetry and homogeneous boundary conditions. We explain the underlying physical relationships and then construct a corresponding approximate system of ordinary differential equations (ODEs) using the Faedo–Galerkin projection. The existence of solutions for the full PDE model is established by analyzing the limit of the solutions of the ODE system using a priori estimates and compactness theory. Additionally, we propose a numerical scheme for the problem based on the same approximate system. Finally, numerical simulations are performed and discussed in both physical and mathematical contexts. Full article

In this position paper, we argue that the conventional understanding of ‘information’ (as generally conceived in science, in a digital fashion) is overly simplistic and not consistently applicable to living systems, which are open systems that cannot be reduced to any kind of ‘portion’ (building block) ascribed to the category of quantity. Instead, it is a matter of relationships and qualities in an indivisible analogical (and ontological) relationship between any presumed ‘software’ and ‘hardware’ (information/matter, psyche/soma). Furthermore, in biological systems, contrary to Shannon’s definition, which is well-suited to telecommunications and informatics, any kind of ‘information’ is the opposite of internal entropy, as it depends directly on order: it is associated with distinction and differentiation, rather than flattening and homogenisation. Moreover, the high degree of structural compartmentalisation of living matter prevents its energetics from being thermodynamically described by using a macroscopic, bulk state function. This requires the Second Principle of Thermodynamics to be redefined in order to make it applicable to living systems. For these reasons, any static, bit-related concept of ‘information’ is inadequate, as it fails to consider the system’s evolution, it being, in essence, the organized coupling to its own environment. From the perspective of quantum field theory (QFT), where many vacuum levels, symmetry breaking, dissipation, coherence and phase transitions can be described, a consistent picture emerges that portrays any living system as a relational process that exists as a flux of context-dependent meanings. This epistemological shift is also associated with a transition away from the ‘particle view’ (first quantisation) characteristic of quantum mechanics (QM) towards the ‘field view’ possible only in QFT (second quantisation). This crucial transition must take place in life sciences, particularly regarding the methodological approaches. Foremost because biological systems cannot be conceived as ‘objects’, but rather as non-confinable processes and relationships. Full article

We present a graphical framework to represent entanglement in three-qubit states. The geometry associated with each entanglement class and type is analyzed, revealing distinct structural features. We explore the connection between this geometric perspective and the tangle, deriving bounds that depend on the entanglement class. Based on these insights, we conjecture a purely geometric expression for both the tangle and Cayley’s hyperdeterminant for non-generic states. As an application, we analyze the energy eigenstates of physical Hamiltonians, identifying the sufficient conditions for genuine tripartite entanglement to be robust under symmetry-breaking perturbations and level repulsion effects. Full article

Span-wise homogeneous supersonic cavity flows display complicated structures due to shear layer breakdown, flow acoustic resonance, and even non-linear hydrodynamic-acoustic interactions. In practical applications, such as aircraft bays, the cavity is of finite width and has doors, both of which introduce distinctive phenomena that couple with the shear layer at the cavity lip, further modulating shear layer bifurcations and tonal mechanisms. In particular, asymmetric states manifest as ‘tornado’ vortices with significant practical consequences on the design and operation. Both inward- and outward-facing leading-wedge doors, resulting in leading edge shocks directed into and away from the cavity, are examined at select opening angles ranging from $22.5°$ to $90°$ (fully open) at Mach 1.6. The computational approach utilizes the Reynolds-Averaged Navier–Stokes equations with a one-equation model and is augmented by experimental observations of cavity floor pressure and surface oil-flow patterns. For the no-doors configuration, the asymmetric results are consistent with a long-time series DDES simulation, previously validated with two experimental databases. When fully open, outer wedge doors (OWD) yield an asymmetric flow, while inner wedge doors (IWD) display only mildly asymmetric behavior. At lower door angles (partially closed cavity), both types of doors display a successive bifurcation of the shear layer, ultimately resulting in a symmetric flow. IWD tend to promote symmetry for all angles observed, with the shear layer experiencing a pitchfork bifurcation at the ‘critical angle’ ($67.5°$). This is also true for the OWD at the ‘critical angle’ ($45°$), though an entirely different symmetric flow field is established. The first observation of pitchfork bifurcations (‘critical angle’) for the IWD is at $67.5°$ and for the OWD, $45°$, complementing experimental observations. The back wall signature of the bifurcated shear layer (impingement preference) was found to be indicative of the 3D cavity dynamics and may be used to establish a correspondence between 3D cavity dynamics and the shear layer. Below the critical angle, the symmetric flow field is comprised of counter-rotating vortex pairs at the front and back wall corners. The existence of a critical angle and the process of door opening versus closing indicate the possibility of hysteresis, a preliminary discussion of which is presented. Full article

Vanillin photoinduced deprotonation was evaluated and analyzed. Vibronic states and transitions were computationally investigated. Optimizations and vertical electron transitions in the gas phase and with the continuum solvation model were computed using the time-dependent density functional theory. Static absorption and emission (photostatic optical) spectra were statistically averaged over the excited instantaneous molecular conformers fluctuating on quantum–classical molecular dynamic trajectories. Photostatic optical spectra were generated using the hybrid quantum–classical molecular dynamics for explicit solvent models. Conical intersection searching and nonadiabatic molecular dynamics simulations defined potential energy surface propagations, intersections, dissipations, and dissociations. The procedure included mixed-reference spin–flip excitations for both procedures and trajectory surface hopping for photodynamics. Insignificant structural deformations vs. hydroxyl bond cleavage followed by deprotonation were demonstrated starting from different initial structural conditions, which included optimized, transition state, and several other important fluctuating configurations in various environments. Vanillin electronic structure changes were illustrated and analyzed at the key points on conical intersection and nonadiabatic molecular dynamics trajectories by investigating molecular orbital symmetry and electron density difference. The hydroxyl group decomposed on transition to a σ-molecular orbital localized on the elongated O–H bond. Full article