Search

Your search keyword '"Hendy, Ahmed"' showing total 370 results
Start Over Author "Hendy, Ahmed"
370 results on '"Hendy, Ahmed"'

7. Advancing drug delivery: Neural network perspectives on nanoparticle-mediated treatments for cancerous tissues

Author

Islam Nazrul, Akhtar Yasmeen, Ahmad Shabbir, Junjua Moin-ud-Din, Hendy Ahmed S., Alballa Tmader, and Khalifa Hamiden Abd El-Wahed

Subjects
drug delivery, cardiovascular system, nanofluidics, machine learning, cancer tissues, Technology, Chemical technology, TP1-1185, Physical and theoretical chemistry, QD450-801
Abstract

The article introduces a machine learning-based approach to enhance drug delivery to cancerous tissues via the human cardiovascular system. It addresses the need for improved drug transport in the presence of cardiovascular obstacles, such as foamy structures, which are implicated in cardiovascular diseases. By examining the impact of nanoparticles on drug transport and biomarkers like hydrogen peroxide, the study refines drug delivery strategies. The motivation is to understand how nanoparticles not only facilitate drug delivery to cancer cells but also mitigate hydrogen peroxide concentration in the blood. This study explores the interaction between nanoparticle behavior, hydrogen peroxide concentration, and drug delivery using machine learning techniques. The integration of modern-day approaches, mainly the Levenberg–Marquardt neural network (LM-NN), offers a healthy assessment of drug delivery systems. Blood flow is exhibited numerically as pulsatile flow in a parallel plate channel, incorporating the properties of foamy structures modeled as porous media. Nanostructures are treated as drug carriers by a concentration equation that considers diffusion, convection, and reaction dynamics in the blood flow. The investigation reveals that nanostructures serve a dual function by augmenting drug delivery to cancer cells and reducing hydrogen peroxide levels in the blood. Machine learning techniques, particularly the LM-NN, identify vital factors affecting drug delivery efficiency, offering insights into optimizing physiological parameters, drug properties, and patient-specific variables. This research presents a novel approach by integrating machine learning, specifically LM-NN, to optimize nanoparticle-mediated drug delivery. It exclusively combines modeling blood flow as pulsatile within a parallel plate channel with the contemplation of foamy structures as porous media. This dual-focus approach advances up-to-date methodologies by providing an inclusive understanding of the interplay between drug carriers and biomarkers, leading to potential enhancements in cancer treatment strategies.

Published
2024
Full Text
View/download PDF

8. A penta-hybrid approach for modeling the nanofluid flow in a spatially dependent magnetic field

Author

Ahmad Shabbir, Junjua Moin-ud-Din, Aryanfar Yashar, Ragab Adham E., Hendy Ahmed S., Alcaraz Jorge Luis Garcia, Keçebaş Ali, Khan Mohammad Arsalan, Mursaleen Mohammad, and Soudagar Manzoore Elahi M.

Subjects
vortex dynamics, magnetic field, penta-hybrid nanofluid, flow pattern, Technology, Chemical technology, TP1-1185, Physical and theoretical chemistry, QD450-801
Abstract

The penta-hybrid nanofluid is a nanofluid that contains five different types of nanoparticles. It can achieve higher heat transfer rates than conventional hybrid nanofluids due to the synergistic effects of the nanoparticles. It also has more diverse physical and thermal properties, which make it more adaptable for various applications. Therefore, this research examines the influence of localized magnetic fields on the vortex dynamics in a penta-hybrid nanofluidic flow in a vertical cavity with an aspect ratio of 1:10, driven by a top and bottom lid moving in the opposite direction. The stream-vorticity formulation is used to solve the dimensionless governing partial differential equation. A confined magnetic field in the form of horizontal and vertical strips has been applied instead of a uniform magnetic field throughout the flow domain, which is more realistic. Moreover, MATLAB codes developed by the authors are used to investigate how these parameters affect the flow and thermal properties of the nanofluids. The results suggest that magnetic fields have an impact on how stress, flow patterns, and temperature are distributed. Moreover, the presence of a magnetic field influences the spacing of isotherms, indicating a more even temperature distribution. It has also been observed that stress distribution is affected by the magnetic field, with higher stress levels near walls and regions with velocity-induced stress. However, in certain areas, the magnetic field can decrease shear stress depending on its strength and orientation. These study findings have implications for designing and operating nanofluidic devices. For instance, utilizing a magnetic field can help regulate flow patterns, temperature distribution, and stress distribution within nanofluidic channels. This capability could prove beneficial for a range of applications, such as cell separation, drug delivery, and nanofluidic heat exchange systems.

Published
2024
Full Text
View/download PDF

10. On the Rothe-Galerkin spectral discretisation for a class of variable fractional-order nonlinear wave equations

Author

Van Bockstal, Karel, Zaky, Mahmoud A., and Hendy, Ahmed S.

Subjects
Mathematics - Numerical Analysis, Mathematics - Analysis of PDEs, 35A01, 35A02, 35A15, 35R11, 65M12, 65M60, 33E12
Abstract

In this contribution, a wave equation with a time-dependent variable-order fractional damping term and a nonlinear source is considered. Avoiding the circumstances of expressing the nonlinear variable-order fractional wave equations via closed-form expressions in terms of special functions, we investigate the existence and uniqueness of this problem with Rothe's method. First, the weak formulation for the considered wave problem is proposed. Then, the uniqueness of a solution is established by employing Gr\"onwall's lemma. The Rothe scheme's basic idea is to use Rothe functions to extend the solutions on single-time steps over the entire time frame. Inspired by that, we next introduce a uniform mesh time-discrete scheme based on a discrete convolution approximation in the backward sense. By applying some reasonable assumptions to the given data, we can predict a priori estimates for the time-discrete solution. Employing these estimates side by side with Rothe functions leads to proof of the solution's existence over the whole time interval. Finally, the full discretisation of the problem is introduced by invoking Galerkin spectral techniques in the spatial direction, and numerical examples are given.

Published
2023
Full Text
View/download PDF

11. A robust alternating direction numerical scheme in a shape optimization setting for solving geometric inverse problems

Author

Rabago, Julius Fergy Tiongson, Hadri, Aissam, Afraites, Lekbir, Hendy, Ahmed S., and Zaky, Mahmoud A.

Subjects
Mathematics - Optimization and Control
Abstract

The alternating direction method of multipliers within a shape optimization framework is developed for solving geometric inverse problems, focusing on a cavity identification problem from the perspective of non-destructive testing and evaluation techniques. The rationale behind this method is to achieve more accurate detection of unknown inclusions with pronounced concavities, emphasizing the aspect of shape optimization. Several numerical results to illustrate the applicability and efficiency of the method are presented for various shape detection problems. These numerical experiments are conducted in both two- and three-dimensional settings, with a focus on cases involving noise-contaminated data. The main finding of the study is that the proposed method significantly outperforms conventional shape optimization methods in reconstructing unknown cavity shapes., Comment: 23 pages; results were first presented at CoMFoS22: Mathematical Aspects of Continuum Mechanics 2022

Published
2023

13. A two-grid temporal second-order scheme for the two-dimensional nonlinear Volterra integro-differential equation with weakly singular kernel

Author

Chen, Hao, Zaky, Mahmoud A., Hendy, Ahmed S., and Qiu, Wenlin

Subjects
Mathematics - Numerical Analysis
Abstract

In this paper, a two-grid temporal second-order scheme for the two-dimensional nonlinear Volterra integro-differential equation with weakly singular kernel is proposed to reduce the computation time and improve the accuracy of the scheme developed by Xu et al. (Applied Numerical Mathematics 152 (2020) 169-184). The proposed scheme consists of three steps: First, a small nonlinear system is solved on the coarse grid using fix-point iteration. Second, the Lagrange's linear interpolation formula is used to arrive at some auxiliary values for analysis of the fine grid. Finally, a linearized Crank-Nicolson finite difference system is solved on the fine grid. Moreover, the algorithm uses a central difference approximation for the spatial derivatives. In the time direction, the time derivative and integral term are approximated by Crank-Nicolson technique and product integral rule, respectively. With the help of the discrete energy method, the stability and space-time second-order convergence of the proposed approach are obtained in $L^2$-norm. Finally, the numerical results agree with the theoretical analysis and verify the effectiveness of the algorithm.

Published
2022

Catalog

Books, media, physical & digital resources
See catalog results