The nuclear structure of ³⁸Ar, ⁵⁹Co, ¹²⁴Sn, ¹⁴⁶Nd, ¹⁵³Eu and ²⁰³Tl target nuclei used in technology for nuclear batteries have been investigation, in order that, these nuclei are very interesting for radioisotope thermo-electric generator (RTG) space studies and for betavoltaic battery microelectronic systems. The single particle radial density distribution, the corresponding root mean square radii (rms), neutron skin thicknesses and binding energies have been investigated within the framework of Hartree-Fock Approximation with Skyrme interaction. The bremsstrahlung spectrums produced by absorption of beta particles in betavoltaic process and backscattered p

In this study, biodiesel was prepared from chicken fat via a transesterification reaction using Mussel shells as a catalyst. Pretreatment of chicken fat was carried out using non‐catalytic esterification to reduce the free fatty acid content from 36.28 to 0.96 mg KOH/g oil using an ethanol/ fat mole ratio equal to 115:1. In the transesterification reaction, the studied variables were methanol: oil mole ratio in the range of (6:1 ‐ 30:1), catalyst loading in the range of (9‐15) wt%, reaction temperature (55‐75 °C), and reaction time (1‐7) h. The heterogeneous alkaline catalyst was greenly synthesized from waste mussel shells throughout a calcin

In this work, we have developed a model that describes the relationships between top predators (such as tigers, hyenas, and others), crop raiders (such as baboons, warthogs, and deer), and prey (such as deer) in the coffee forests of southwest Ethiopia. Various potential equilibrium points are identified. Additionally, the model's stability in the vicinity of these equilibrium points is examined. An investigation of the model's Hopf bifurcation is conducted concerning several significant parameters. It is found that prey species may be extinct due to a lower growth rate and consumption by top predators in the absence of human interference in the carrying capacity of prey. It is observed that top predators may be extinct due to human interfe

This paper presents a comparative study of two learning algorithms for the nonlinear PID neural trajectory tracking controller for mobile robot in order to follow a pre-defined path. As simple and fast tuning technique, genetic and particle swarm optimization algorithms are used to tune the nonlinear PID neural controller's parameters to find the best velocities control actions of the right wheel and left wheel for the real mobile robot. Polywog wavelet activation function is used in the structure of the nonlinear PID neural controller. Simulation results (Matlab) and experimental work (LabVIEW) show that the proposed nonlinear PID controller with PSO
learning algorithm is more effective and robust than genetic learning algorithm; thi