The European Physical Journal Plus最新文献

The interaction of nucleic acids with metallic ions is crucial for DNA function. Mg²⁺ can bond directly or indirectly via water. We explored Mg²⁺ interaction with Dickerson DNA at varying Mg²⁺ concentrations with fixed NaCl concentration. Analysing the correlation function, we mapped Mg²⁺ density around DNA regions. We found that the Mg²⁺ interaction decreased with rising Mg²⁺ concentrations. Mg²⁺ also displayed a higher affinity for the Phosphate group over grooves. We explored the variation of stacking parameters by varying Mg²⁺ concentrations, indicating slight structural changes which have not been explored yet. Our study reflects that the Mg²⁺ concentrations had almost minimal impact on Dickerson-DNA structure, instead stabilizing it.

A focused microbeam system with ion beams at MeV energies is a unique tool for material science, biomedical applications, and space risk evaluation. Microbeam system design traditionally relies on experienced knowledge of microbeam optics and many elaborate calculation procedures. In this work, an ion optics design code, CADAIT, is developed to design microbeam systems automatically. For a given microbeam layout, it allows for the automatic optimization of focusing conditions, the calculation of optical parameters, and the size of the focused beam through ray tracing. CADAIT enables the automatic optical design of microbeam layouts under input parameters and the selection of microbeam layouts with high performance. The accuracy of the CADAIT is verified with ion optics software packages (WinTRAX, Zgoubi, and FANM), which show good agreement. The evaluation of the performance of existing microbeam facilities with CADAIT and the application of CADAIT in the automatic design of a 12 MeV proton microbeam system are discussed. Thanks to its high efficiency in the optical design of microbeam systems, the CADAIT code is used to train artificial intelligence (AI) models for the intelligent design of microbeam systems with tremendous CADAIT-generated data. The artificial intelligence trained model, Artificial Intelligence Microbeam Producer (AIMP), is demonstrated to be capable of generating microbeam systems with superior performance and robust layouts within one minute. The above results show that CADAIT can significantly decrease the complexity and duration of microbeam optical design and prove the feasibility of intelligent microbeam design.

Accurate segmentation of medical images can provide foundations for clinical and disease diagnosis. Inaccurate segmentation boundaries often result from limited contextual information and insufficient discriminating feature maps after consecutive pooling and upsampling operations in most existing methods. In this paper, we present a novel boundary-aware medical image segmentation network (BSNet) for resolving the multi-objective segmentation problem. We exploit a backbone network to extract multi-scale feature representations and design an adaptive contrast boundary-aware module (ACB), which uses the method of combining nonlinear filters with deep learning to extract high-quality boundary maps. We then build a feature fusion (FF) module to fuse multi-scale features with boundary maps, providing decoder with rich multi-scale features enhanced with boundary information, and facilitating cross-channel interactions. To further enhance the uncertain regions of the boundaries, we utilize the boundary spatial enhancement (BSE) module to learn the feature map of boundary locations with the assistance of the Sobel operator. We conducted experiments with three challenging public datasets to evaluate the effectiveness of BSNet. Simulation results on various datasets show that the present model outperforms state-of-the-art segmentation methods, obtaining up to 2.73% improvement in Dice coefficient (DICE) score. BSNet opens new ways of designing better boundary-aware segmentation network.Please confirm the corresponding author is correctly identified.No problem.

The InAs/GaAs quantum dot intermediate band solar cells (QD-IBSCs) have the potential for high conversion efficiency. In practice, their efficiencies have not reached 20%. In this study, the confined energy levels, interband absorption coefficients, and absorbed sub-bandgap photocurrent densities are calculated with QD size using equal effective mass and effective mass mismatch for the box-shaped InAs/GaAs QD system. The four-band k(cdot )p model was applied to the InAs/GaAs QD system. The energy of IB levels with the effective mass mismatch decreased compared with the equal effective mass. The interband photocurrent density increased with effective mass mismatch since more confined energy states contributed to interband absorption. If the in-plane QD density raised from (4times 10^{10}) (hbox {cm}^{-2}) to (4times 10^{11} ,hbox {cm}^{-2}), the interband photocurrent density increased from 0.58 to 5.19 (hbox {mA/cm}^{2}) for equal effective mass and 0.99 to 8.38 (hbox {mA/cm}^{2}) for the effective mass mismatch with 16 nm (times ) 16 nm (times ) 6 nm of QD size, under one sun concentration. Increasing the QD size also allows additional IB states within the forbidden band; thus, the interband photocurrent increases with QD size. The interband photocurrent density for 10 nm and 16 nm QD widths is 0.39 (hbox {mA/cm}^{2}) and 0.99 (hbox {mA/cm}^{2}), respectively.

In this paper, we explore non-local effects in electrodynamics in the presence of external sources and a material boundary. Specifically, we consider a model where Maxwell’s electrodynamics is modified by a specific non-local term, which describes the phenomenological Cornell’s confining potential. First, we study the interaction between stationary field sources, describing point-like charges, Dirac strings, and point-like dipoles. In this analysis, we demonstrate that the ground state energy of the hydrogen atom and also the dipole-dipole interaction are modified by these non-local effects, which contributions are used to set a stringent bounds upon the model’s parameter (measuring the non-locality effects). Moreover, we show that the non-locality stems an interaction between Dirac strings, which is absent in the Maxwell theory. In a complementary study, we investigate this model in the presence of a conducting plate. In this case, we calculate the propagator for the gauge field and the interaction force between the conducting plate and a point-like charge. It is shown that the image method is not valid for this non-local theory.

The relaxation dynamics of a mixed spin-1/2 and spin-1 ferrimagnetic Ising system with random anisotropy has been investigated using Onsager’s theory of irreversible thermodynamics. The magnetic Gibbs energy production, arising due to irreversible processes, is computed using the equilibrium mean-field Gibbs energy, based on the variational principle and the Gibbs–Bogoliubov inequality. In the framework of linear response theory, the time derivatives of the sublattice magnetizations are treated as fluxes conjugate to their corresponding generalized forces. Two relaxation times are computed, and their dependence on temperature and crystal field variances is examined near phase transition points for four distinct topologies, each corresponding to different phase diagrams. These phase diagrams emerge from random anisotropy drawn from a bimodal probability distribution: ( P(Delta _{i}) = frac{1}{2}left[ delta (Delta _{i} - Delta (1+alpha )) + delta (Delta _{i} - Delta (1-alpha ))right] . ) One of the relaxation times, denoted as (tau _1), increases rapidly and diverges near the critical and tricritical points separating the ferrimagnetic and paramagnetic phases. For (alpha ge 0), critical slowing down, characterized by the divergence of (tau _1), is observed near the isolated ordered critical points between the ferrimagnetic and disorder-induced ferrimagnetic phases. Finally, the variance of the relaxation times is analyzed across regions of crystal field and temperature, as well as the values of (alpha ) at which re-entrant phenomena occur, due to the competing interactions in the random system.

Rumor spreading not only disrupts internet order and damages economic interests, but also seriously affects social stability. The social positive reinforcement mechanism was introduced to integrate social media with a positive reinforcement effect into the process of rumor propagation, and an improved rumor propagation model was established. The model’s dynamics are analyzed using mean field theory, revealing a close relationship between the propagation threshold and social positive reinforcement. According to the Hurwitz criterion and LaSalle invariant principle, the stability of the rumor free equilibrium is proved, and the existence of rumor spread equilibrium is proved. To combat rumor spreading under social positive reinforcement, a real-time optimal control method is proposed, incorporating science popularization education for susceptible individuals, enhancing management of rumor spreading individuals, and strengthening the restriction on social media with positive reinforcement effect. Numerical simulations verify the theoretical results, the results show that social positive reinforcement is conducive to rumor propagation, and the control strategies can effectively curb the rumor propagation. Finally, the validity of the model was verified by fitting the model parameters using the least square method. Compared with similar studies, the results of the experiments show that the improved rumor propagation model has a stronger predictive ability.