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In this research, we used mathematical models in the investigation of incompressible non-Newtonian fluid flow through a lipid-concentrated cylindrical channel with the effect of metabolic heat and magnetic treatment. The nonlinear partial differential equations were scaled into linear partial differential equations and then solved using the Laplace method to obtain the exact solutions. The numerical simulation was carried out using Wolfram Mathematica, version 12, where graphical results were obtained showing the variation of various pertinent parameters and their effects on the velocity profile of the fluid. The graphs revealed the effects of the parameters such as the metabolic heat, Grashof parameter, magnetic field; Prandtl number, pressure gradient, and porosity parameter have on the flow profile. The significance of this study is in the therapeutic investigation of hyperthermia, especially on the regulation of blood flow and lipids in the blood.

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This paper proposed an enhanced Top-k query processing in a real time distributed database system. The system employs a Particle Swarm Optimizer (PSO) based Geno-Generative iSWAN Model technique that enhances and allows multi-task concurrent query processing in a real time co-simulation data acquisition platform and as part of refinement to an existing Top-k query processing Technique. In this paper, the proposed system is compared for efficiency with the Top-K Query Algorithm, which is emerging as an alternative to more conventional technique for real time query processing in distributed databases. Dynamic simulations were performed with a real time small testbed comprising of physical and non-physical devices to test and evaluate the performance and efficiency of the two systems. Considering the estimated and expected temperatures, the result of simulation study proves that the Intelligent Swarming Network (iSWAN) Geno-Generative Model is more preferred over Top-K Query Algorithm due to its 70% accuracy over the Top-K Model, which reported a lower accuracy level of 40%.