Electrospinning enables simple and cost-effective production of polymer nanofibers from different polymer materials. Drug delivery systems are capable of achieving maximum drug treatment benefits by significantly reducing adverse complications. Electrospun nanofibers have recently attracted considerable attention owing to their distinctive properties, including flexibility and biocompatibility. The implementation of functional constituents within nanostructure fibers blends is an effective technique for the administration of a variety of drugs in animal research, broadening the nanofiber capability and reliability. The nanofibrous mesh and its various application purposes are discussed in terms of a summary of recent research, emphasizing the ease of streaming and a large number of combinations of this approach, which could lead to a breakthrough in targeted therapy.

This paper addresses the critical challenge of optimizing the energy efficiency of induction motors, which are pivotal components across diverse industrial sectors due to their substantial energy consumption. Given the non-measurable internal parameters of induction motors, parameter identification becomes a complex, multidimensional optimization problem characterized by highly nonlinear and multimodal error surfaces. Traditional optimization algorithms often weaken, yielding suboptimal results due to an inadequate balance between the exploration and exploitation phases. To overcome these limitations, this study introduces an Adaptive Weight Grey Wolf Optimizer (AWGWO) to enhance the accuracy and reliability of induction motor parameter estimation. The AWGWO incorporates an adaptive weight mechanism that dynamically adjusts the exploration and exploitation balance, effectively mitigating issues such as premature convergence to local optima. Extensive simulation validation was conducted across various induction motor models, including eight commercial motors, and demonstrated that AWGWO consistently outperforms state-of-the-art algorithms in terms of convergence speed, solution accuracy, and robustness in multimodal optimization landscapes. The AWGWO consistently exhibited faster convergence, significantly reducing premature convergence. Moreover, the adaptive weight mechanism enabled a more effective balance between exploration and exploitation, leading to higher accuracy in parameter estimation. Comparative analyses reveal that AWGWO outperforms existing algorithms not only in achieving lower error rates, but also in maintaining stability. This study significantly contributes to progress in the field by providing an effective tool for induction motor parameterization, thereby offering potential improvements in energy efficiency.

This article presents a novel four-port DC–DC converter designed to integrate photovoltaics, fuel cells, and supercapacitors with one DC charging single-output port with a reduced component count. The proposed converter ensures an efficient power management strategy to manage the load power demand and optimize the power flow from the sources. The power management controller helps enhance the performance of the system by dynamically prioritizing the sources based on their availability and the demand of the load. A comprehensive reliability analysis is conducted to measure the converter’s robustness under varying load conditions, proving its suitability for real-world applications. The proposed topology’s performance was validated in three different scenarios for 1 kW using a simulation tool, and experiments in the laboratory were conducted. The failure rate and efficiency of the system are analyzed, and the converter promises a 96.5% efficiency for 1 kW and a failure rate of 4.6216 × 10⁶ failures per hour. The simulation and experimental results validate the converter’s performance, highlighting its superior efficiency, reliability, and scalability.

This study investigates the influence of periodic heat flux and viscous dissipation on magnetohydrodynamic (MHD) flow through a vertical channel with heat generation. A theoretical approach is employed. The channel is exposed to a perpendicular magnetic field, while one side experiences a periodic heat flow, and the other side undergoes a periodic temperature variation. Numerical solutions for the governing partial differential equations are obtained using a finite difference approach, complemented by an eigenfunction expansion method for analytical solutions. Visualizations and discussions illustrate how different variables affect the flow velocity and temperature fields. This offers comprehensive insights into MHD flow behavior and its interactions with the magnetic field, heat flux, viscous dissipation, and heat generation. The findings hold significance for engineering applications concerning fluid dynamics and heat transfer, offering valuable knowledge in this field. The study concludes that the transient velocity and temperature profiles exhibit periodic patterns under periodic heat flow conditions. A temperature reduction is observed with an increase in the wall temperature phase angle. In contrast, an increase in the heat flux phase angle values raises the temperature values.

An analysis is carried out in order to examine the effects of non-uniform heat source and thermal radiation on the transient free convective MHD flow past a vertical plate. In this model, an inclined magnetic field with periodic heat flux along the wall is included. The governing equations (in non-dimensional shape) are solved numerically by a fully implicit finite difference scheme. A parametric study is performed in order to illustrate the influences of the model dimensionless parameters, namely, the magnetic parameter, the heat source term, the Grashof number, the Prandtl number, and the radiation parameter. The velocity field and the temperature field are evaluated for several amounts of these parameters. The obtained numerical results are compared with the analytical solution in case of constant heat flux with no heat source, and a full agreement was found.