The European Physical Journal Plus最新文献

Influenza is a transmissible respiratory disease that has proven catastrophic throughout history. Its rapid spread poses serious challenges to public health, as existing vaccines often provide limited protection. Mathematical modeling serves as a vital quantitative tool for predicting the dynamics and control of such epidemics. In this study, a Susceptible–Vaccinated–Exposed–Infected–Recovered (SVEIR) model is developed and analyzed for influenza transmission. The model guarantees the positivity and boundedness of all state variables, ensuring biological feasibility. Two equilibrium points, the influenza-free equilibrium (IFE) and influenza-endemic equilibrium (IEE), are established, and the basic reproduction number (mathcal {R}_{0}) is derived to assess disease persistence. Analytical results show that the IFE and IEE are locally and globally stable when (mathcal {R}_{0}<1) and (mathcal {R}_{0}>1), respectively. Sensitivity analysis indicates that the vaccination rate for newborns is the most influential parameter; a 25–30(%) increase in this rate leads to an approximately (40) (%) reduction in infection prevalence. Bifurcation analysis confirms a forward (supercritical) bifurcation, implying that maintaining (mathcal {R}_{0}) below unity ensures disease elimination. Numerical simulations, performed using the Nonstandard Finite Difference (NSFD) scheme, validate the analytical findings and illustrate how increasing vaccination rates significantly reduce the susceptible and infected populations.

This document sets out the intention of the strong-field QED community to carry out, both experimentally and numerically, high-statistics parametric studies of quantum electrodynamics in the non-perturbative regime, at fields approaching and exceeding the critical or ‘Schwinger’ field of QED ((F_{textsf {qed}}= m^2c^3/ehbar approx 1.3 times 10^{18}) V/m) in the rest frame of a charged particle. In this regime, several exotic and fascinating phenomena are predicted to occur that have never been directly observed in the laboratory. These include Breit–Wheeler pair production, vacuum birefringence, and quantum radiation reaction. This experimental programme will also serve as a stepping stone towards studies of elusive phenomena such as elastic scattering of real photons and the conjectured perturbative breakdown of QED at extreme fields. State-of-the-art high-power laser facilities in Europe and beyond are starting to offer unique opportunities to study this uncharted regime at the intensity frontier, which is highly relevant also for the design of future multi-TeV lepton colliders. A transition from qualitative observational experiments to quantitative and high-statistics measurements can only be performed with large-scale collaborations and with systematic experimental programmes devoted to the optimisation of several aspects of these complex experiments, including detector developments, stability and tolerances studies, and laser technology.

The motion of light in a dust-filled weakly Bianchi I Universe is analytically investigated. The anisotropic expansion causes a specific proper motion of comoving sources (an often neglected effect). We provide in this paper this proper motion in terms of usual cosmological parameters and observables. This specific “anisotropic proper motion” is also converted into local velocity, which yields a surprisingly simple expression for cosmological sources, that allows a direct comparison with (true) expected local physical velocities. While the Bianchi I solution depends on two parameters K and (delta), it turns out that the amplitude of this anisotropic motion through the whole sky only marginally depends on (delta) , ie is essentially mastered by K. Constraining K with the Planck mission data, it is found that this induced local velocity is below the (mathrm{km}/mathrm{s}) range for cosmological sources with (zle 20), which makes the related cosmological and astrometric effects a priori hard to disentangle from local proper motions in the foreseeable future.

The design of efficient, durable and affordable electrocatalysts for the oxygen evolution reaction (OER) remains a central challenge for sustainable water-splitting technologies. Alkaline metal delafossite-based (AMD) oxides have appeared as promising applicants owing to their layered structure, favorable electronic properties and high conductivity. In this study, pristine NaCrO₂ (NCO) was produced via a simple solid-state method and further combined with polyaniline (PANI) to form a NaCrO₂@PANI (NCO@PANI) composite. The composite exhibited a reduced crystalline size of 9.55 nm and a large surface area, both of which favor the exposure of active sites. Electrochemical evaluation under 1 M KOH revealed that NCO@PANI needed an overpotential (η) of 198 mV to attain (j) current density (10 mA/cm²), compared with pristine NCO (258 mV). Similarly, the Tafel plot reduced significantly from 52 mV/dec for NCO to 32 mV/dec for NCO@PANI, indicating improved charge-transfer kinetics, supported by a reduced solution resistance (R_s = 1.83 Ω). The hybrid also demonstrated remarkable stability over 50 h of operation. The superior activity is credited to the combined effect between the delafossite core and conducting polymer, which enhances electron transport and active sites. This work offers a rational approach for developing scalable alkaline metal delafossite (AMD)-based electrocatalysts for efficient alkaline water splitting.

Accurate modelling of plasma turbulence is essential for predicting transport and energy confinement in fusion reactors. However, traditional discretised MHD solvers are computationally expensive and often fail to generalise across reactor configurations, motivating the use of AI-based surrogate approaches. Although recent progress in physics-informed neural networks (PINNs) and neural operators is encouraging, they are usually either not scalable or provide poor generalisation or accuracy in turbulent dynamics, which calls for more advanced approaches. To address these challenges, we present TurbulAI-Fusion, an AI-based surrogate modelling framework in which a physics-informed neural operator, termed PINet-Turb, serves as its core, learning spatiotemporal plasma dynamics under physical constraints. It employs Fourier-inspired neural operator layers and a hybrid loss function comprising data-driven, PDE residual, and boundary-condition terms, ensuring physical correctness while being more general and better. We test the proposed system using multiple metrics—mean absolute error (MAE), root mean square error (RMSE), PDE residual error, and inference time—on high-resolution synthetic plasma turbulence data. We demonstrate, through experiments, that TurbulAI-Fusion consistently achieves significantly higher predictive accuracy and greater adherence to physical principles than baseline models (reducing MAE by more than 20%), while remaining robust against unseen turbulence configurations. As shown by the qualitative analysis, the model captures many of the critical a priori known physical features, such as eddies, filaments, and magnetic flux contours. Here, we present a new physics-based surrogate framework for turbulence modelling in fusion systems that is highly scalable and interpretable. This makes the framework particularly attractive for connecting real-time diagnostic and control applications for future fusion reactors.

After the postponement of the 2020 edition, the 5th International Conference on Innovation in Art Research and Technology - inArt 2022 was held from June 28th to July 1st, 2022, in Paris. Authors of the 47 oral presentations and 119 posters presented were invited to submit articles for publication in EPJ+. This EPJ+ Focus Point on “Scientific Research in Cultural Heritage” brings together 33 papers resulting from this process. These articles illustrate the wide range of topics covered at the conference, which fall within the scope of archaeometry or conservation science. This editorial briefly presents these articles, which have been brought together under the following three thematic headings: comprehension of materials and techniques involved in Cultural Heritage; degradation mechanisms and conservation strategies and in situ experiments and mobile instrumentation. Bearing in mind that this is only a way of presenting the articles and not a formal classification of their content, given the overlap of these different aspects in several of the studies presented.

The affine quantization of a Hamiltonian operator in quantum Newtonian cosmology allows us to find exact solutions to the Schrödinger equation. In parallel, we developed an alternative approach to Newtonian quantum mechanics in phase space, enabling us to derive analytical expressions for Wigner’s distribution functions of moments associated with position and momentum operators of higher orders. Our study also explores the properties of the position operator and the general formula for the oscillation frequency for each state in the quantum Newtonian cosmology. Furthermore, we verify the Dirac commutation relation and the generality of Heisenberg’s uncertainty principle.

We present a new model for the accurate calculation of neutron thick target yields with the p+(^9)Be reaction at low energy (E(le)5 MeV) for BNCT applications. The model is based on the available experimental data for the total yield and on calculations with state-of-art codes for the (p,n) reaction. A new data-driven parametrization for the (p,p(^prime)n) channel is introduced to reproduce experimental results for the yield: neutron energy and angle distributions are validated with existing data at low energies (E(le)5 MeV) and preliminary new estimates are provided up to 10 MeV. The result is relevant for the design of an accurate neutron source module to be used in full MC simulations of p+(^9)Be BNCT beamlines.

This article presents a novel approach for detecting the adulteration level of diesel based on the variations in the shape of ultrashort pulses transmitted through a hollow-core photonic crystal fiber (HC-PCF) sensor. The proposed technique leverages the fiber’s nonlinear and dispersion characteristics to evaluate how the shape of an ultrashort pulse evolves when propagating through a diesel-filled HC-PCF sensor. For each sample, the proposed sensor demonstrates distinct pulse compression for input pulses of picosecond duration. To quantify the observed shape variations, two key performance parameters, compression sensitivity and power upsurge, have been introduced. The proposed method achieves a minimum compression sensitivity of 16% and a maximum power upsurge of 648.072 W. Furthermore, the sensor exhibits a wide tunability range with respect to input pulse power (300–500 W) and pulse duration (1–3 ps), optimized across nine distinct input configurations. These findings demonstrate the potential of the proposed HC-PCF-based system as an efficient and tunable optical sensing platform for fuel adulteration detection.

Poly (vinyl chloride) (PVC) is one of the most widely used synthetic polymers due to its flexibility, low density, and ability to be reinforced with fillers to enhance its physical properties. In this study, PVC polymer films were reinforced with varying concentrations of Bi₂O₃ and Bi₂O₃ + Dy₂O₃ nanoparticles to investigate their mechanical and radiation shielding properties. The nanocomposite polymer films were fabricated using the hot compression molding technique. Structural and chemical analyses were performed using X-ray diffraction (XRD) and Fourier transform infrared spectroscopy (FTIR) to confirm the uniform dispersion and chemical interaction of the nanoparticles within the PVC matrix. The influence of nanoparticle concentration and gamma irradiation dose on the mechanical properties of the polymer films was evaluated through tensile strength and elongation tests. Results revealed that increasing the nanoparticle content slightly improved the tensile strength, while gamma exposure enhanced mechanical performance with minimal effect on elongation. The radiation shielding capability of the prepared PVC/Bi₂O₃ and PVC/Bi₂O₃ + Dy₂O₃ polymer films was assessed experimentally using a Cs-137 gamma source (5 μCi) and a ²⁴¹Am–Be neutron source (185 GBq). The linear attenuation coefficients and neutron attenuation parameters were measured as a function of nanoparticle weight fraction. Monte Carlo simulations (MCNPX) and Phy-X software were used to validate the experimental data. The results showed excellent agreement between experimental and simulated values, confirming that the polymer film containing 15 wt% Bi₂O₃ exhibited superior radiation shielding performance. These findings suggest that PVC polymer films reinforced with Bi₂O₃/Dy₂O₃ nanoparticles are promising candidates for flexible and lightweight radiation protection materials suitable for medical and industrial applications.