The European Physical Journal Plus最新文献

Investigations concerning nanofluid heat transfer offer advantages across many technological and industrial sectors. Despite the research on porous media, the heat transfer of nanofluid fins has received limited focus. This research work considers the mathematical model for heat transfer in stretching or shrinking fins, accounting for temperature-varying heat conductivity, internal heat generation, and the coefficient of heat transfer. It is assumed that the parameters of the nanofluid remain fixed. Heat is transferred to the atmosphere by convection and radiation, which is augmented by nanofluids. We deal with the numerical simulation of the nonlinear model using the Legendre wavelet collocation method (LWCM). This study focuses on the variation of dimensionless parameters (Ma, Omega , G, Pe, A,) and v for studying the coupled effect on the behavior of the material with nanofluids. A comparison of the obtained results has been carried out in special and full model cases from previous work, which shows a good agreement. It has been found that a tapered, exponentially shaped fin has the greatest efficiency in releasing heat. The shrinking system significantly improves the cooling effect of the fin, especially when it is moving. The outcomes of the current work are believed to be utilized in optimizing and designing the fin shape in industrial fields.

Exciton-optomechanics, which integrates cavity exciton polaritons with optomechanical systems, offers a unique platform for exploring light–matter interactions via nonlinear couplings among photons, phonons, and excitons. We present a theoretical model for the dynamic control of the photonic spin Hall effect (PSHE) in such a system, leveraging the strong spin–orbit coupling in microcavity polaritons. Our analysis shows that this coupling induces a transverse spatial separation of photons with opposite spins. The spin-dependent shift can be tuned from positive to negative values by varying the exciton–photon (EPt) and effective exciton–phonon (EPn) coupling strengths, exhibiting a strong dependence on the optical Brewster angle. Without EPt coupling, a resonant absorption profile results in a higher PSHE peak. In contrast, introducing EPt coupling generates multiple transmission peaks that suppress the PSHE magnitude. Notably, increasing the effective EPn coupling modifies the ratio of the reflection coefficients, leading to a significant enhancement of the PSHE. Furthermore, the PSHE can be controlled via probe field detuning and the beam waist. These findings establish dynamic parameter tuning as a powerful method for amplifying the PSHE, paving the way for advanced spin-photonic devices.

Green’s functions on graphs play a central role in statistical mechanics, where transport, relaxation, and response emerge from the interplay between geometry and spectral structure. In this work, we analyze the Dirichlet Green operator associated with subgraphs of complete graphs and show that, despite arising from a linear Laplacian, its behavior is driven by a fundamentally nonlinear boundary–bulk interaction. Using the Sherman–Morrison–Woodbury identity, we obtain closed-form Green functions for cliques viewed as low-rank perturbations of the complete graph, revealing how nonlinear dependence on defect size controls effective resistance, potential profiles, and energy dissipation. From a dynamical perspective, we construct absorbing random walks whose fundamental matrix provides a stochastic realization of the Green operator as a nonlinear response kernel encoding normalized visit densities before absorption. This dual algebraic–probabilistic treatment clarifies the distinction between intrinsic and ambient Green operators, shows how scalar shifts deform the spectrum, and uncovers the nonlinear scaling regime that arises as the subgraph density approaches the ambient limit. Together, these results provide a unified transport-theoretic framework for Green’s functions on subgraphs, connecting low-rank perturbation theory with nonequilibrium diffusion on networked systems.

With the wide application of video in the Internet of Things and other fields, ensuring the security of video content becomes a key issue. However, the traditional video encryption scheme may still have security vulnerabilities when facing high-intensity attacks, and the computational complexity is high. It is difficult to balance high efficiency and high security. Therefore, this paper proposes a novel video encryption scheme based on a new spatiotemporal chaotic system and a dynamic partitioning method. In this scheme, we propose a new logistic coupled sine mapping lattice (LCSML) based on the coupled mapping lattice (CML) model. The LCSML model improves the mapping method of the CML by introducing sine mapping and dynamically manipulating the original static coupling parameters, thereby endowing it with better chaotic characteristics. Secondly, we design a dynamic partitioning method. The method utilizes chaotic sequences generated by LCSML for array indexing, which enables independent partitioning for each video frame. In the pixel replacement phase, the scheme utilizes the principle of protein sequence encryption to apply multiple computation rules to different regions of the video frame. Dynamic partitioning method and protein sequence encryption effectively improve the security of video encryption scheme. Finally, we uses hash index chain and inverse chain to perform diffusion operations on the pixels. The experimental results show that the video encryption scheme based on LCSML has certain advantages in security performance. It is especially suitable for application environment with high privacy protection requirements.

Lorentz transformation equations provide us a set of relations between the spacetime coordinates as observed from two different inertial frames. In case, one of the frames is moving with a uniform rectilinear acceleration; we have Rindler’s transformation equations under such a situation. In the present work, we extend the Rindler’s equations to a situation where we have in general non-uniform acceleration. After that we consider the non-inertial frame to undergo simple harmonic motion (SHM), and as a second case, we consider the non-inertial frame to move uniformly along a circle. This set of transformation equations will have applications in various branches of Physics and in general in Astrophysics.

In this study, a generalized form of the complex Ginzburg–Landau equation incorporating various nonlinear response laws namely, the Kerr law, power law, parabolic, and dual-power nonlinearities is examined. By applying a suitable traveling wave transformation, the governing partial differential equation is reduced to a nonlinear ordinary differential equation. After additional variable shifts, the system is expressed in Hamiltonian form, from which the corresponding first integral is derived to analyze the equilibrium structure. The qualitative behavior of the system is investigated by constructing phase portraits under different parameter regimes, revealing the existence and stability characteristics of both singular and symmetric equilibria. Subsequently, the modified Kudryashov method is employed to obtain several new classes of exact solutions for the considered nonlinear models. These solutions are presented in hyperbolic, exponential, and rational function forms, corresponding to bright, dark, singular, kink, and anti-kink wave profiles. To illustrate the physical features and propagation dynamics of the obtained solutions, two-dimensional and three-dimensional graphical representations are plotted for appropriate parameter choices. The analytical and graphical results demonstrate the effectiveness of the proposed approach in describing nonlinear wave evolution across diverse nonlinear optical media.

Crystal collimation was investigated for possible deployment in the Large Hadron Collider (LHC). A prototype layout, integrated in the betatron collimation insertion (IR7), is used to assess the performance and compare it to the standard system. This was tested in different conditions with proton and lead ion beams. A special run with fully-stripped xenon ion beams at 6.5Z TeV was carried out in 2017 and provided a unique opportunity to test the crystal collimation system with a new ion species. In this paper the results recorded with Xenon beams, which show promising collimation cleaning results, are presented.

We study the coherent dynamics of a single impurity atom embedded in a self-bound, quasi-one-dimensional quantum droplet. The droplet, described by a cubic–quartic nonlinear Schrödinger equation, provides a self-generated potential in which the impurity supports an even–odd doublet of bound states forming an effective two-level system. Using a super-Gaussian variational model, semiclassical WKB analysis, and time-dependent simulations, we derive quantitative relations linking droplet geometry to impurity level splitting and Rabi frequency. The impurity undergoes intrinsic, field-free Rabi oscillations between edge-localized modes, which map directly to Bloch-sphere rotations. These results establish a minimal, self-stabilized platform for coherent matter-wave qubits, where control arises solely from the nonlinear droplet properties.

Dengue fever continues to pose a serious and persistent threat to public health and remains endemic in more than fifty countries worldwide. The disease is primarily transmitted to humans through the bite of infected Aedes mosquitoes, whose wide geographic distribution, adaptation to urban settings, and sensitivity to climatic variability contribute to sustained outbreaks. Although several prevention measures (such as vector control, environmental management, and community awareness) are widely implemented, dengue transmission remains difficult to suppress due to complex human-vector interactions, heterogeneous exposure, and limitations in controlling mosquito breeding habitats. For these reasons, epidemiological and mathematical modeling has become an essential tool for systematically describing transmission mechanisms, identifying dominant risk determinants, and assessing the expected impact of intervention strategies, thereby supporting evidence-based planning for prevention and control. In this work, we formulate a host-vector mathematical model for dengue virus transmission by coupling a mosquito Susceptible-Infected (SI) subsystem with a human Susceptible-Infected-Recovered (SIR) subsystem. The model captures the exchange of infection between vector and human populations and enables a quantitative investigation of threshold dynamics. In particular, the basic reproduction number (R_{0}) is derived using the next-generation matrix technique, providing a key threshold quantity that characterizes whether an initial infection can invade the population. We then analyze the stability properties of the equilibria: the local stability analysis shows that the disease-free equilibrium is asymptotically stable when (R_{0}<1), implying eventual elimination of dengue, whereas dengue persists and an endemic equilibrium may arise when (R_{0}>1). Furthermore, global stability results are established using a suitable Lyapunov function, which strengthens the conclusions beyond local behavior. To validate the theoretical outcomes and to explore the effect of the principal parameters that promote or mitigate dengue spread, numerical simulations are carried out in MATLAB for the relevant compartments. These simulations illustrate the temporal evolution of the human and mosquito populations under different epidemiological scenarios and parameter settings. In addition, sensitivity analysis is performed to quantify how variations in model parameters influence (R_{0}) and the overall transmission dynamics. This analysis highlights the most influential factors and provides insight into which control measures (e.g., reducing mosquito biting rate, lowering vector density, or increasing recovery) may be most effective for limiting dengue transmission.

Advancing intelligent sensors through the integration of antennal molecular assemblies and supramolecular materials represent a significant leap in precision, selectivity, and adaptability across diverse applications. These cutting-edge sensors are inspired by the extraordinary sensitivity of natural biological systems, such as insect antennae, enabling heightened molecular recognition even in complex environments. Recent developments in nanoarchitectonics and supramolecular chemistry offer transformative approaches to sensor design, facilitating the precise assembly of nanoscale structures and creating highly responsive materials. This article delves into the interdisciplinary application of these technologies, covering theoretical foundations and practical implementations across fields including environmental monitoring, biomedical diagnostics, and energy systems. By comparing various sensor architectures, the article reveals the advantages of using molecular assemblies, nanoscale surface engineering, and supramolecular interactions to address existing limitations in traditional sensors. Emphasis is placed on future research directions and innovations, such as adaptive sensing and AI integration, which hold the potential to revolutionize real-time monitoring and detection across industries. This synthesis aims to bridge current knowledge gaps, showcasing the novel possibilities in sensor technology through biomimetic inspiration and advanced material science. The sensing behaviors discussed in this work are strongly influenced by intrinsic nonlinear interactions at the molecular and nanoscale levels. These nonlinearities dictate signal amplification, stochastic response behavior, and dynamic adaptability across diverse environments. Recent advances in nonlinear physics further reinforce how nonlinear coupling, bifurcation behavior, and multistability can significantly enhance the performance of intelligent sensor materials.

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