Modern Physics Letters B

Electromagnetic induction and autapse play important roles in regulating the electric activities, excitability, and bistable structure of neurons. The firing activities and global bifurcation patterns of a four-dimensional (4D) hybrid neuron model that combines the fast dynamic variables of the Wilson model and the slow feedback variables of the Hindmarsh–Rose (HR) model and magnetic flux are investigated based on the Matcont software and numerical calculation. The effect of electrical autapse on the dynamic evolution of the system is also discussed emphatically. Upon encountering electromagnetic induction, the hybrid neuron model exhibits complex global stability, Hopf bifurcation, and saddle-node bifurcation. Intriguingly, the system presents initial sensitivity and a bistable structure consisting of quiescent and period-1 spiking near the Hopf bifurcation point. It is worth noting that the feedback type of electrical autapse, including positive and negative feedback, has completely different effects on this bistable structure. Notably, the negative feedback autapse can expand and change the bistable region, so that the system generates a new bistable structure consisting of quiescent and periodic bursting states, and its bursting activities are also promoted. Moreover, extensive numerical results show that the system generally maintains a comb-shaped chaotic structure, abundant bifurcation patterns, and multistability. It should be noted that electrical autapse feedback types and time delays do not change the regular bifurcation structures but operate a complex regulatory mechanism for the coexistence of multiple attractors. These results will provide useful insights into the neuron’s dynamics under the atmosphere of electromagnetic induction and also electrical autapse.

In this paper, modulational instability (MI) of information via membrane potential is studied analytically and numerically in an improved Izhikevich neural network under electromagnetic induction. By applying the powerful discrete multiple scale expansion method, a spatiotemporal nonlinear amplitude differential-difference equation governing the information dynamics is derived from the generic model. Linear stability of plane impulse wave solution is then performed on the latter and the impact of electromagnetic induction feedback through the memristor couplings is portrayed on the growth rate diagram. From the diagram, it is found that negative memristor coupling parameter decreases the critical amplitude while positive parameter increases the critical amplitude. To support our analytical predictions, numerical simulations are performed and data selected from the unstable zone of MI lead to the formation of localized solitonic energy patterns, related to the energy coding patterns in the nervous system. Furthermore, the sampled time series for membrane potential under the influence of memristor coupling revealed the breakdown of action potential into multiple impulse-wave trains for high parameter values thus confirming an analytical prediction. Our results provide a potential way to manipulate information coding in the brain.

Exploring the next generation of invincible energy materials with fascinating properties is vital in the challenge of energy crisis. In this paper, we extract T-carbon as a potential candidate and have an insight into the electronic and optical properties by means of first principles. It is found that S1 position doping system is relatively more stable with the formation energy of 0.323 eV, and has the smallest bandgap value of 1.228 eV. Charge density difference maps show that the electron loss is obvious near the S atom and the covalent bond is weakened. The population analysis shows that the S atom will obtain electrons through competition, while the Se atom will lose electrons. Additionally, the peak values of $𝜀$2 in the doped systems decrease significantly, especially for S2 doping system, indicating that S2 doping can effectively improve the service life in related devices. Compared with the instinct system, the absorption coefficient is lower in the UV region and greater in the visible region. The peak of energy loss spectrum reduces after doping, especially for Se1 doping. The results provide a theoretical basis for the industrial application of T-carbon in the energy microdevice fields.

This paper discusses the existence of the tracking technique for a two-dimensional Brownian particle on a planar surface. The tracking process starts from the origin of the plane (intersection point of $x$ and $y$ axes). Accordingly, we derive the conditions that make the expected value of the first meeting time between the sensor and the particle finite. Also, we calculate the approximated expected value of the first meeting time.

In this work, we study the effects of geometric confinement on random walks and diffusion processes in systems of reduced dimensionality. Extensive Monte Carlo simulations of Gaussian random walks were performed on rectangular strips of infinite length. A special emphasis is made on the crossover from two- to one-dimensional diffusion in the Fickian regime. We found that the crossover behavior is controlled by the ratio of the strip width to the standard deviation of the walker step length distribution. Specifically, the characteristic time of crossover behavior scales quadratically with this ratio. Furthermore, the time dependence of the number of effective spatial degrees of freedom of the random walker on the strip is found to obey an ansatz characterized by the universal power-law exponent. This allows us to formulate the diffusion equation with the time dependent number of effective spatial degrees of freedom in the quasi-one-dimensional system.

Positive ions confined in a solid state lattice might be driven to low energy reactions by exploring, through quantum control, the 3-body wave function enhancements of the scar effect.

Antenna fingerprinting is critical for a range of physical-layer wireless security protocols to prevent eavesdropping. The fingerprinting process exploits manufacturing defects in the antenna that cause small imperfections in signal waveform, which are unique to each antenna and hence device identity. It is an established process for physical-layer wireless authentication with proven usage systems in terrestrial systems. The premise relies on accurate signal feature discovery from a large set of similar antennas and stable fingerprint patterns over the operational life of the antenna. However, in space, many low-cost satellite antennas suffer degradation from atomic oxygen (AO). This is particularly a problem for nano-satellites or impromptu temporary space antennas to establish an emergency link, both of which are designed to operate for a short time span and are currently not always afforded protective coating. Current antenna fingerprinting techniques only use Support Vector Machine (SVM) and Convolutional Neural Networks (CNNs) to take a snap-shot fingerprint before degradation, and hence fail to capture temporal variations due to degradation. Here, we show how we can perform robust antenna fingerprinting (99.34% accuracy) for up to 198 days under intense AO degradation damage using Recurrent Neural Networks (RNNs). We compare our RNN results with CNNs and SVM techniques using different signal features and for different Low-Earth Orbit (LEO) satellite scenarios. We believe this initial research can be further improved and has real-world impact on physical-layer security of short-term nano-satellite antennas in space.

Ranging from computer network to traffic network, complex networks are ubiquitous in our lives. How to control congestion to make network operate more effectively is one of the most essential issues in complex network research. At present, a large number of studies on traffic dynamics mainly focus on single-layer networks. However, in fact, many complex systems are coupled by multiple networks. In this paper, we propose a resource allocation strategy for three-layer network with which the limited total delivery capacity can be reasonably allocated to each node of physical layer based on the degree of nodes in two logical layers. Compared with the average allocation of delivery capacity, the traffic capacity is improved and the network has better transmission performance in average traveling time and average throughput with our strategy.

Two-dimensional 1T-ZrO₂ material is investigated via first-principles calculations based on density functional theory (DFT) method. The band gap of cubic, tetragonal and monoclinic ZrO₂ is 6.095 eV, 5.784 eV and 5.835 eV respectively obtained in the paper also. $\mathrm{\text{GGA}}+{\mathrm{\text{U}}}^{\mathrm{\text{d}}}+{\mathrm{\text{U}}}^{\mathrm{\text{p}}}$ method is determined to adopt to study two-dimensional 1T-ZrO₂ in the paper. The results show that the band gap of 1T-ZrO₂ material is 7.513 eV and it is an indirect wide band gap semiconductor structure. At the same time, it can be seen from the density of states (DOS) that the valence band of the 1T-ZrO₂ material is mainly due to the contribution of 2p electron of O atom. 4p, 4d and 5s electron of Zr atom also contributes a little to the valence band. 4p, 4d, 5s electron of Zr atom and 2s, 2p electron of O atom contribute to the conduction band, but main contribution has come from 4d of Zr atom. These results are in good agreement with the electron orbitals diagram. 1T-ZrO₂ material has maximum reflectivity of 11.61% and refractive index of 1.62. It has high absorption coefficient and energy loss in this region. The peak of dielectric function may be mainly caused by the inter-band transition from electron-occupied state to non-occupied state. The real part of the photoconductivity tends to zero in the visible region with low energy and the maximum conductivity of 2.087 corresponds to the peak of other photoelectric properties of 1T-ZrO₂ material.

The new features of the bound state’s formation due to the defect nonlinearity and stepwise medium nonlinearity are found. The Schrödinger equation containing two terms of different nonlinearity types is solved analytically. The exact solution found is described as the bound state near the nonlinear defect in the nonlinear medium. Properties of the bound state are analyzed in dependence on defect and medium parameters. The bound state existing only near nonlinear defect only is found. It is shown that the influence of a change in the effective defect power is qualitatively equivalent to a change in the defect power up to renormalization, and the effect of the defect nonlinearity is opposite.

This work attempts to apply the Lie symmetry approach to an updated (2+1)-dimensional KdV equation, recently updated in A.-M. Wazwaz, Nucl. Phys. B 954 (2020) 115009. The equation can be considered as one of the famous examples of the soliton equation. The infinitesimal generators for the governing equation have been found using the invariance property of Lie groups. The commutator table, adjoint table, invariant functions and one-dimensional optimal system of subalgebras are then derived using Lie point symmetries. Some group invariant solutions are derived based on various subalgebras, symmetry reductions and an optimal system. To demonstrate the physical acceptability of the results, the obtained solutions are evaluated using numerical simulation.

Based on the Hirota bilinear method, we study some kinds of novel interaction solutions of the new integrable $(2+1)$-dimensional extended shallow water wave equation. Using the symbolic computations, we obtain a rich variety of exact solutions such as the lump solutions, lump-kink solutions, breather solutions and two-kink solutions and these exact solutions are shown analytically and graphically by selecting the proper parameters. These new exact solutions contribute us to our understanding of the physical phenomena of the integrable nonlinear shallow water wave model.