ABSTRACT This work introduces a modified Chua circuit, distinguished by a hyperbolic tangent nonlinearity, designed to exhibit complex dynamics pertinent to neuromorphic engineering. The proposed system affords exceptional parametric control over attractor topology, enabling the systematic manipulation of multi‐scroll chaotic structures via a single control parameter. Furthermore, the system exhibits bistability through the coexistence of distinct attractors under specific initial conditions. Through a comprehensive bifurcation analysis, we identify and characterize the critical Hopf bifurcation points that govern the transitions between stable, periodic, and chaotic regimes. A principal contribution of this research is the identification of a well‐defined, bifurcation‐free parameter corridor. Within this zone, the system generates robust, low‐frequency oscillations analogous to neural delta rhythms while maintaining sustained chaotic behavior without secondary bifurcations, which ensures highly predictable frequency tuning. The theoretical framework is substantiated by a practical analog circuit implementation, demonstrating excellent fidelity between the mathematical model and its physical realization. A comparative performance analysis reveals that the proposed oscillator possesses superior characteristics including continuous stability windows, comprehensive delta‐band coverage, and minimal parameter sensitivity when compared to classical and contemporary designs. These findings establish the proposed circuit as a robust and versatile platform for investigating nonlinear brain dynamics, developing tunable neuromorphic oscillators, and advancing chaos‐based technologies.

ABSTRACT This work introduces a highly sensitive and reconfigurable terahertz (THz) biosensor developed for detecting liver cancer biomarkers. The proposed sensor consists of a hybrid graphene‐gold THz biosensor patterned on a dielectric substrate, ensuring strong plasmonic confinement and tunable resonance behavior. A machine learning framework employing the K‐Nearest Neighbors (KNN) algorithm was implemented to optimize the interaction among graphene's chemical potential, relaxation time, and temperature. Electromagnetic simulations combined with KNN predictions reveal outstanding sensing performance, achieving 76.36 GHz/RIU for normal liver tissue, 130.43 GHz/RIU for AFP, 187.38 GHz/RIU for DCP, and 220.41 GHz/RIU for VEGF. The structure exhibits high quality factors up to 38.85 and a figure of merit of approximately 1.69 RIU −1 , confirming its excellent capability to distinguish healthy from malignant tissues. This compact and dynamically tunable design demonstrates strong potential for real‐time, label‐free THz biomedical diagnostics, particularly in early liver cancer detection.

ABSTRACT In addressing the pattern synthesis of multiconstraint thinned planar antenna arrays, existing intelligent optimization algorithms encounter limitations such as premature convergence and insufficient solution accuracy. Therefore, we propose an adaptive mutation strategy dung beetle optimizer (AMSDBO) for optimizing thinned planar antenna arrays. The AMSDBO algorithm innovatively constructs a three‐stage collaborative optimization framework, effectively achieving high‐performance design for thinned planar arrays under the constraints of fixed aperture size and sparsity rate through a parameter adaptive adjustment mechanism. Firstly, initial solutions for the dung beetle populations are generated using a chaotic mapping reverse learning (CMRL) strategy to enhance both population diversity and the quality of the initial solutions. Next, the local mutation search (LMS) mechanism is introduced. An adaptive T ‐distribution mechanism is imposed to effectively enhance the early global search capability. Then, the Lévy flight variation strategy is employed to adaptively adjust the positions of the dung beetle population in the later stages, helping the algorithm avoid local optima and accelerating convergence. Simulation results with classical test functions demonstrate that AMSDBO offers significant advantages in convergence accuracy and robustness compared to traditional algorithms (DBO, PSO, and IWO). Additionally, two sets of typical planar thinned array experimental results indicate that the optimization performance of the AMSDBO algorithm is significantly improved compared to traditional optimization algorithms. Specifically, there is a peak sidelobe level (PSLL) reduction of 15.5% for DBO, 11.64% for PSO, and 14.56% for IWO. This confirms the effectiveness and superiority of the AMSDBO algorithm.

ABSTRACT In this paper, we investigate the resonance phenomenon in a microstrip (MS) to grounded coplanar waveguide (GCPW) to MS structure. We demonstrate that the resonance arises from the relative phase difference between two excited modes in the GCPW. Through modal analysis supported by field plots, we calculate the relative phase difference of the two modes at the start and end of the GCPW section. We show that the reflection from the GCPW‐MS discontinuity depends on the phase difference of the modes. If this phase difference is zero, the reflection is minimum due to destructive interference of the reflected waves. Therefore, the resonance in a MS‐GCWP‐MS structure can be suppressed by modifying this phase difference. An analytical analysis based on multiconductor transmission lines is employed to verify the full‐wave analysis. Two approaches are proposed to modify the relative phase difference. The first approach is to use an overlying dielectric to slow down the dominant mode. The second approach slows down the dominant mode by increasing the equivalent capacitance of this mode with periodic stubs and speeds up the common mode by removing a portion of the substrate below the coplanar grounds.

ABSTRACT The growing demand for compact and efficient dual‐band antennas in modern wireless and satellite systems motivates the need for designs that offer high gain, low cross‐polarization, and broad operational versatility. Based on concentric spiral shape, developed from square iterations, this research proposes a low‐profile linearly polarized printed fractal radiator. Both the scaling factor () and the rotation angle () control the design of the antenna, allowing it to operate in two bands with a fixed aperture. The suggested radiator attains resonance at and GHz, which correspond to X‐ and Ku‐band frequencies, using a RO‐5880 substrate with a dielectric constant 2.2. The simulated and measured findings demonstrate excellent agreement with gain of and dBi, cross‐polarization levels below dB, and radiation efficiencies over . The proposed small‐sized dual‐band antennas meet the need for efficient, innovative wireless and satellite systems. These findings confirm that the antenna is suitable for wireless and DBS applications, and they hint at its potential applicability to IoT and 5G with the minimal design up‐gradation.

ABSTRACT This study investigates the nonlinear and chaotic dynamics of a modified Hindmarsh–Rose (HR) neuron model through a unified framework based on piecewise fractional differential operators. The classical HR neuron model is widely used to describe the electrical activity of neuronal membranes; however, it does not fully account for memory effects and regime‐switching phenomena observed in real neurobiological processes. To address this limitation, we formulate a piecewise dynamical model in which the membrane potential evolves under different fractional operators, including the Caputo, Atangana–Baleanu, and Caputo–Fabrizio derivatives. A fractional order parameter is introduced to regulate the memory intensity of the system and to construct a generalized fractional‐order HR model. The piecewise structure enables the modeling of switching behaviors and crossover effects between distinct neuronal activity regimes. Numerical simulations are carried out to examine the influence of the fractional order and the piecewise operator structure on neuronal firing patterns, chaotic attractors, and complex oscillatory dynamics under external current stimulation. The numerical results clearly show that changes in the fractional order and the choice of switching thresholds have a pronounced influence on the stability properties, oscillation amplitudes, and chaotic behavior of the neuron model. Through a broad set of numerical experiments, the proposed framework is shown to reliably reproduce key features of neuronal dynamics, demonstrating that the adopted numerical schemes are well suited for capturing memory effects and regime switching. Overall, this study advances fractional and piecewise modeling approaches in neuroscience by providing both new theoretical perspectives and practical computational tools for the investigation of complex neuronal systems.

ABSTRACT This article presents a comprehensive temperature‐dependent analysis of Ferroelectric Junction‐less Surrounding‐Gate FETs (Fe‐JL‐SG FETs). To evaluate the effectiveness of ferroelectric integration, a detailed comparison between Fe‐JL‐SG FETs and conventional Junction‐less Surrounding‐Gate FETs (JL‐SG FETs) is carried out. Key device parameters—including surface potential, electric field, electron concentration, electron velocity, transconductance ( g m ), output conductance ( g d ), capacitance ( C GG ), cutoff frequency ( f t ), and I ON / I OFF ratio—are systematically investigated over a broad temperature range (100–500 K). The results demonstrate that Fe‐JL‐SG FETs exhibit superior electrical and analog performance with significantly reduced sensitivity to temperature variations compared to JL‐SG FETs. This enhanced behavior is attributed to the negative capacitance effect introduced by the ferroelectric material, which effectively reduces the subthreshold‐swing (SS) below the Boltzmann limit (60 mV/decade). However, this effect weakens as temperature increases. The simulation framework, developed using the ATLAS 3‐D device simulator, exhibits strong congruence with the proposed analytical model, thereby validating the theoretical constructs and reinforcing the predictive reliability of the developed approach.

ABSTRACT This study introduces a new formulation of the Wave Concept Iterative Process (WCIP) method in elliptic coordinates to analyze electromagnetic scattering from an infinitely long, inhomogeneous, multilayered elliptical cylinder. The foundation of this approach lies in the definition of emitted and reflected waves at the interfaces of dissimilar media, utilizing the tangential components of the electric field and current density. The unknown waves resolved from a set of two equations. The first equation, formulated in the spectral domain, characterizes the response of the environment around the structure. The second equation guarantees the continuity of the electromagnetic fields and enforces boundary conditions at the interfaces that separate different regions. The system of equations is resolved by an iterative process where a discrete angular Mathieu Transformation Algorithm is introduced to toggling between the spatial and the modal domain. The proposed approach is suitably implemented in a specific computational code to achieve a numerical solution. Some numerical results are presented, involving a structure composed of metallic strips positioned at the interfaces of four elliptical dielectric layers, which is illuminated by a transverse magnetic (TM) plane wave at an oblique angle of incidence. The result is in agreement with those published in the literature.