This paper deals with the Magnetohydrodynyamic (Mill)) flow for a viscoclastic fluid of the generalized Oldroyd-B model. The fractional calculus approach is used to establish the constitutive relationship of the non-Newtonian fluid model. Exact analytic solutions for the velocity and shear stress fields in terms of the Fox H-function are obtained by using discrete Laplace transform. The effect of different parameter that controlled the motion and shear stress equations are studied through plotting using the MATHEMATICA-8 software.

Metal nanoparticles can serve as an efficient nano-heat source with confinement photothermal effects. Thermo-plasmonic technology allows researchers to control the temperature at a nanoscale due to the possibility of precise light propagation. The response of opto-thermal generation of single gold-silica core-shell nanoparticle immersed in water and Poly-vinylpyrrolidone surrounding media is theoretically investigated. Two lasers (CW and fs pulses) at the plasmonic resonance (532 nm) are utilized. For this purpose, finite element method is used via COMSOL multiphysics to find a numerical computation of absorption cross section for the proposed core –shell NP in different media. Thermo-plasmonic response for both lasers is studied. The

This paper presents a new azo dye 3-[2-(1H-indol-2-yl)ethyldiazenyl]quinolin-2-ol] from the reaction of the diazonium salt derived from tryptamine and 2-hydroxyquinoline. Azo dye was used to prepare a series of complexes with the chlorides of Ni(II), Pt(IV), Pd(II), Cd(II), and Zn(II). Compounds were analyzed and characterized using elemental analysis, magnetic measurement, UV-vis, IR, MS, NMR, and conductivity. The findings demonstrated that the ligand acts as ionic in complex form, O-bidentate, supporting the proposed formula. The complexes generally exhibited tetrahedral and octahedral geometries, except the palladium complex, which adopted a square planar geometry. TGA was used to investigate the thermal characteristics of compo

In this paper, The transfer function model in the time series was estimated using different methods, including parametric Represented by the method of the Conditional Likelihood Function, as well as the use of abilities nonparametric are in two methods  local linear regression and cubic smoothing spline method, This research aims to compare those capabilities with the nonlinear transfer function model by using the style of simulation and the study of two models as output variable and one model as input variable in addition t

We investigate mathematical models of the Hepatitis B and C viruses in the study, considering vaccination effects into account. By utilising fractional and ordinary differential equations, we prove the existence of equilibrium and the well-posedness of the solution. We prove worldwide stability with respect to the fundamental reproduction number. Our numerical techniques highlight the biological relevance and highlight the effect of fractional derivatives on temporal behaviour. We illustrate the relationships among susceptible, immunised, and infected populations in our epidemiological model. Using comprehensive numerical simulations, we analyse the effects of fractional derivatives and highlight solution behaviours. Subsequent investigatio

An increasing trend to use probiotic and study their effects on the pathogens has been conductor where they are defined as live micro-organisms that give a health benefit to the host when ingested in sufficient quantities, including the yeast Saccharomyces boulardii In addition research show that a magnetic field (MF) has a biological effect. This study aims to investigate the effects of magnetic field on the inhibitory action of Saccharomyces boulardii against bacteria isolated from urinary tract infection, Study the sensitivity of bacterial isolates to antibiotics after diagnosis by microscopic, Cultural and biochemical examinations as well as Api20 E examinations were used gram negative bacteria , Most isolates were resistant to an

It is important that real time stability in smart grids is ensured as the integration of renewables and the complexity of the systems grows. In this paper, we provide a solid architecture, which combines a Residual CNNLSTM deep neural network predictor, FPGA-accelerated Model Predictive Control (MPC), and SHAP-based explainability. The proposed method predicted with 99.8% accuracy using the Electrical grid Stability Simulated Dataset (UCI) and minimized the instability rates surpassing 85 percent in all operating conditions. Meeting real-time operating needs, FPGA deployment on a Xilinx Zynq UltraScale+ provided 3.1 ms latency and 5 times reduced energy consumption against CPU processing. By emphasizing bus voltage and frequency as major in