Epilepsy is considered as one of the common neurological disorders.About 50 million persons have affected by epilepsy .Carbamazepine is one of the common drugs used by pregnant women with epilepsy. The aim of the present study is to investigate the effect of carbamazepine on the process of brain development during day 13 of pregnancy.Fifty pregnant albino mice have been used. They were divided into two groups. The control group that had been orally drenched with normal saline. The other group was treated group that had been given 15 mgKg of Carbamazepine orally. The fetuses have been collected after killing of the mice. Boun’s solution was selected as fixative. 5-8 µm thick sections from the fetuses were cut to be stained with hematoxyli

The study aims to achieve several objectives, including follow-up scientific developments and transformations in the modern concepts of the Holistic Manufacturing System for the purpose of identifying the methods of switching to the entrances of artificial intelligence, and clarifying the mechanism of operation of the genetic algorithm under the Holonic Manufacturing System, to benefit from the advantages of systems and to achieve the maximum savings in time and cost of machines Using the Holistic Manufacturing System method and the Genetic algorithm, which allows for optimal maintenance time and minimizing the total cost, which in turn enables the workers of these machines to control the vacations in th

Contracting cancer typically induces a state of terror among the individuals who are affected. Exploring how chemotherapy and anxiety work together to affect the speed at which cancer cells multiply and the immune system’s response model is necessary to come up with ways to stop the spread of cancer. This paper proposes a mathematical model to investigate the impact of psychological scare and chemotherapy on the interaction of cancer and immunity. The proposed model is accurately described. The focus of the model’s dynamic analysis is to identify the potential equilibrium locations. According to the analysis, it is possible to establish three equilibrium positions. The stability analysis reveals that all equilibrium points consi

It has been shown recently that there is a need to design smart structures, such as smart houses, in order to be controlled in different ways. That will be in high demand due to its usefulness for some people who are incapable of reaching some control units that require direct interaction with human beings. In this paper, we propose and develop a new enhanced electroencephalography (EEG)-based smart structure setup that can be utilized to assist people, with or without disorders, to control devices in an easy and comfortable way. Ten people of a wide range of ages (20–65) and both genders actively participated in this research. Consequently, eight EEG channels are employed in this study to cover most of the brain’s regions, and the prot

Abstract—In this study, we present the experimental results of ultra-wideband (UWB) imaging oriented for detecting small malignant breast tumors at an early stage. The technique is based on radar sensing, whereby tissues are differentiated based on the dielectric contrast between the disease and its surrounding healthy tissues. The image reconstruction algorithm referred to herein as the enhanced version of delay and sum (EDAS) algorithm is used to identify the malignant tissue in a cluttered environment and noisy data. The methods and procedures are tested using MRI-derived breast phantoms, and the results are compared with images obtained from classical DAS variant. Incorporating a new filtering technique and multiplication procedure, t

The study using Nonparametric methods for roubust to estimate a location and scatter it is depending  minimum covariance determinant of multivariate regression model , due to the presence of outliear values and increase the sample size and presence of more than after the model regression multivariate therefore be difficult to find a median location .       

It has been the use of genetic algorithm Fast – MCD – Nested Extension and compared with neural Network Back Propagation of multilayer in terms of accuracy of the results and speed in finding median location ,while the best sample to be determined by relying on less distance (Mahalanobis distance)has the stu

Nowadays, the mobile communication networks have become a consistent part of our everyday life by transforming huge amount of data through communicating devices, that leads to new challenges. According to the Cisco Networking Index, more than 29.3 billion networked devices will be connected to the network during the year 2023. It is obvious that the existing infrastructures in current networks will not be able to support all the generated data due to the bandwidth limits, processing and transmission overhead. To cope with these issues, future mobile communication networks must achieve high requirements to reduce the amount of transferred data, decrease latency and computation costs. One of the essential challenging tasks in this subject

The Combined Economic Emission Dispatch (CEED) problem is crucial for optimizing power system operation by minimizing costs and emissions while ensuring grid stability and meeting demand. This paper addresses the complex, nonlinear, and nonconvex nature of CEED, arising from factors like valve-point effects and transmission losses, which necessitates efficient metaheuristic algorithms. We introduce an Improved Zebra Optimization Algorithm (IMZOA), an enhanced bio-inspired technique integrating advanced adaptive foraging and dynamic defense mechanisms, along with a cubic function for CEED modeling, to improve search efficiency and convergence. IMZOA demonstrates significant numerical improvements, achieving up to a 0.80 % cost reduction for

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In this paper, the memorization capability of a multilayer interpolative neural network is exploited to estimate a mobile position based on three angles of arrival. The neural network is trained with ideal angles-position patterns distributed uniformly throughout the region. This approach is compared with two other analytical methods, the average-position method which relies on finding the average position of the vertices of the uncertainty triangular region and the optimal position method which relies on finding the nearest ideal angles-position pattern to the measured angles. Simulation results based on estimations of the mobile position of particles moving along a nonlinear path show that the interpolative neural network approach outperf