The central nervous system is the most important system and is very sensitive to any accidental infection during ontogenesis; it includes brain and spinal cord. The cerebellum is the second largest part of the brain after cerebrum and it’s very sensitive to the abnormal changes during the embryological development. This study was designed to investigate the effect of the maternal exposure of selected concentrations of suspension of nanoparticles on the ontogenesis of the rat cerebellum after embryos implanted in uterus. A total of 60 female pregnant rats were divided in to three groups, each contains 20 females. Group1 (G1) was treated orally with 2mg/kg /body weight (b. wt) of suspension of silver nanoparticles (Ag NPs). While group 2 (G

1-Objective:- Polyphenols are biochemical compounds with antioxidant activity against differences diseases related to Lipid peroxidation such as diabetes mellitus. Polyphenols distributed widely in medical plants, the aim of the study is to extract and analyze some polyphenolic compounds from grape seeds and examine their effects on (STZ) induced diabetic mice. 2-Methods:- In the present study , a group of polyphenols has been extracted from Iraq

In this golden age of rapid development surgeons realized that AI could contribute to healthcare in all aspects, especially in surgery. The aim of the study will incorporate the use of Convolutional Neural Network and Constrained Local Models (CNN-CLM) which can make improvement for the assessment of Laparoscopic Cholecystectomy (LC) surgery not only bring opportunities for surgery but also bring challenges on the way forward by using the edge cutting technology. The problem with the current method of surgery is the lack of safety and specific complications and problems associated with safety in each laparoscopic cholecystectomy procedure. When CLM is utilize into CNN models, it is effective at predicting time series tasks like iden

Recognizing speech emotions is an important subject in pattern recognition. This work is about studying the effect of extracting the minimum possible number of features on the speech emotion recognition (SER) system. In this paper, three experiments performed to reach the best way that gives good accuracy. The first one extracting only three features: zero crossing rate (ZCR), mean, and standard deviation (SD) from emotional speech samples, the second one extracting only the first 12 Mel frequency cepstral coefficient (MFCC) features, and the last experiment applying feature fusion between the mentioned features. In all experiments, the features are classified using five types of classification techniques, which are the Random Forest (RF),

In this research we study a variance component model, Which is the one of the most important models widely used in the analysis of the data, this model is one type of a multilevel models, and it is considered as linear models , there are three types of linear variance component models ,Fixed effect of linear variance component model, Random effect of linear variance component model and Mixed effect of linear variance component model . In this paper we will examine the model of mixed effect of linear variance component model with one –way random effect ,and the mixed model is a mixture of fixed effect and random effect in the same model, where it contains the parameter (μ) and treatment effect (τ_i ) which  has