Atef AbdelKader

In this work, we explore a piezoelectric neuron model in deterministic perturbations and stochastic forcing due to its use in mechanically driven sensing systems and neuromorphic sensor design. The model comprises of fast activation and slow recovery behaviors and constitutes a multiscale excitable system, converting external mechanical perturbations into nonlinear electrical responses. We initially examine the deterministic dynamics with phase-space reconstruction, basin of attraction mapping, return map analysis and sensitivity to initial conditions. These findings demonstrate stable limit-cycle oscillations and high nonlinear sensitivity that are crucial to high-resolution sensing and signal amplification. Stochastic forcing is added in order to include realistic environmental effects, and solved numerically with the Euler-Maruyama scheme. Time-series statistics, phase portraits, and recurrence quantification analysis are used to analyze the resulting ensemble dynamics, making it possible to characterize the variability and loss of predictability caused by noise. Comparison of deterministic and stochastic regimes indicates that the intensity of noise can considerably alter the firing patterns and recurrence structures.

This paper presents a detailed investigation of the deterministic and stochastic dynamics of a noise-driven forced nonlinear oscillator in a periodically driven framework. An overlap-mapping approach is used to compare multiple traveling-wave solutions and verify the structural consistency among distinct solution families. The qualitative behavior of the system is further characterized through geometric and stability-based analysis, supported by two- and three-dimensional phase portraits, time-series responses, and reconstructed three-dimensional attractors to examine periodic and chaotic regimes under varying parameters and initial conditions. The sensitivity to parameter perturbations is quantified and the distribution of final states is analyzed to identify chaotic regions in the phase space. The high-dimensional chaotic nature of the dynamics is rigorously confirmed through Lyapunov exponent estimation, Poincaré sections, and return-map analysis, collectively demonstrating strong sensitivity to initial conditions and systematic transitions induced by parameter variations. These results provide a comprehensive dynamical description of the nonlinear oscillator and contribute to a deeper understanding of noise-influenced nonlinear driven systems.

This paper examines the nonlinear behavior of the generalized stochastic intermediate dispersive velocity (SIdV) equation, which has been widely analyzed in a non-noise deterministic framework but has yet to be studied in any depth in the presence of varying forcing strength and noise types, in particular how it switches between periodic, quasi-periodic, and chaotic regimes. A stochastic wave transformation reduces the equation to simpler ordinary differential equations to make soliton overlap analysis feasible to analyze soliton robustness under deterministic and stochastic conditions. Lyapunov exponents, power spectra, recurrence quantification, correlation dimension, entropy measures, return maps, and basin stability are then used to measure the effect of white, Brownian, and colored noise on attractor formation, system stability, and spectral correlations. Order–chaos transitions as well as noise-induced complexity are more effectively described by bifurcation diagrams and by Lyapunov spectra. The results of this experiment improve the theoretical knowledge of stochastic nonlinear waves and offer information that will be useful in the fields of control engineering, energy harvesting, optical communications, and signal processing applications.

This paper presents a comprehensive dynamical analysis of a nonlinear oscillator subjected to both deterministic and stochastic excitations. Utilizing a diverse suite of analytical tools—including phase portraits, Poincaré sections, Lyapunov exponents, recurrence plots, Fokker–Planck equations, and sensitivity diagnostics—we investigate the transitions between quasi-periodicity, chaos, and stochastic disorder. The study reveals that quasi-periodic attractors exhibit robust topological structure under moderate noise but progressively disintegrate as stochastic intensity increases, leading to high-dimensional chaotic-like behavior. Recurrence quantification and Lyapunov spectra validate the transition from coherent dynamics to noise-dominated regimes. Poincaré maps and sensitivity analysis expose multistability and intricate basin geometries, while the Fokker–Planck formalism uncovers non-equilibrium steady states characterized by circulating probability currents. Together, these results provide a unified framework for understanding the geometry, statistics, and stability of noisy nonlinear systems. The findings have broad implications for systems ranging from mechanical oscillators to biological rhythms and offer a roadmap for future investigations into fractional dynamics, topological analysis, and data-driven modeling.

This work aims to investigate the structural, magnetic, electronic and optical properties of the low-dimensional antiferromagnets Cs₂CoX₄ (X [ ] Cl, Br, I) using density functional theory (DFT). These materials are scientifically intriguing due to the existence of multiple quantum interactions such as quantum entangled states, correlation and spin–orbit coupling (SOC). The optimization and exchange coupling parameter confirm that the materials are stable in antiferromagnetic (AFM) phase, which is consistent with the experiments. The difference in bond lengths and bond angles of the same halogen in the tetrahedral complex bonded to the cobalt ion confirms the existence of Jahn–Teller distortion. The computed band gaps are 4.34, 3.70, and 3.50[ ]eV, respectively, and show a direct band gap nature. The magnetic anisotropic character and binding energy make these materials suitable for spintronic applications. Cs layer acts as a spacer that confines the tetrahedral layer and has a negligible contribution in the formation of bands. Various optical properties like dielectric constant, refractive index and energy loss function are calculated for these materials along different crystal axes.

The raw materials of cement contain radioactive elements that come from natural sources. Members of the decay chains of uranium, thorium, and potassium radioisotope ⁴⁰K are the primary sources of this radioactivity. The natural radionuclide concentration levels in cement differ greatly depending on different geographic areas. To estimate the radionuclides concentration in cement specimens from twelve diverse Pakistani companies, gamma-ray spectroscopy analysis was used in the study. ²²⁶Ra, ²³²Th, and ⁴⁰K had activity concentration levels ranging from 18.08 to 43.18 Bq/kg, 16.73 to 23.53 Bq/kg, and 14.24 to 315.22 Bq/kg, respectively. The United Nations Scientific Committee on the Effects of Atomic Radiation (UNSCEAR) threshold for the ²²⁶Ra was surpassed by five of the studied samples. The indoor and outdoor dose rates as well as different radiological health hazard indices were also examined. The Indoor Absorbed Dosage (D_in) for some of the samples exceeded the permissible limit. These samples also had a high Indoor Effective Lifetime Cancer Risk (ELCR) factor, which makes them unsafe for interior construction purposes. The outdoor dosages as well as the hazard indices were well within the permitted ranges. The outdoor ELCR factor is low for all the cement brands, which makes them safe for exterior construction purposes. The findings were compared with published data from other countries around the globe. Finally, a thorough statistical analysis was performed and Pearson’s Correlation Coefficient (r) exhibited a very strong correlation between the different outdoor and indoor radiological health hazard indices.

The hydrothermal synthesis of CuO/NiO composites was conducted using banana fruit biomass waste. In this study, X-ray powder diffraction, scanning electron microscopy, and Fourier transform infrared spectroscopy were used to investigate the crystalline properties, shape structure, and functional group characterization of CuO/NiO composites. The typical morphology of the prepared materials consisted of irregular nanoparticles arranged into clusters of less than 200 nanometers in size. In spite of this, the CuO/NiO composites showed monoclinic CuO and cubic NiO phases and were therefore successfully synthesized. It was observed that rotten banana fruit juice had a significant impact on the particle size and crystal quality of CuO/NiO composites. This was due to the presence of capping, reducing, and stabilizing agents in banana fruit juice. Under alkaline conditions, the CuO/NiO composites were found to be highly electro catalytically active toward the oxidation of urea. Sample 2, which was prepared by adding 1.2 g of CuO decorated with NiO, showed a linear increase in urea detection ranging from 0.1 mM to 17 mM, with a limit of detection of 0.004 mM. Furthermore, sample 2 of the CuO/NiO composite demonstrated exceptional stability, selectivity, and reproducibility. Consequently, sample 2 of CuO/NiO could effectively detect urea in spinach, lotus root, milk, and curd. The improved performance of sample 2 of the CuO/NiO composite can be attributed to its favorable surface properties, which contain enriched active sites and a rapid charge transfer rate.