The study included the extraction of volatile oil from Mentha piperita which was 1.3 % in the leaves and flowers . Volatile oil of the Mentha piperita leaves had special aromatic odour, pale yellow color, slightly pungent taste . The specific gravity and refractive index were (0.9794) and ( 1.464) respectively. The inhibition activity of the Mentha piperita Volatile oil extracts were studied on some pathogenic microorganisms like Staphylococcus aureus, Salmonella typhi, Escherichia coli, Proteus sp, and Klebsiella pneumoniae . The result showed that the volatile oil had an inhibition effect on the growth of all microorganisms, and it gave the higher inhibition effect on the growth of S. aureus in which the inhibition zone reached to 2

Background and Objectives: Urinary tract infections (UTIs), among a wide range of microbial infections, are of a double-edged worry with health-care and economic implications. They are serious diseases that can influence various parts of the urinary tract. The aim of this study was characterization of the enteric bacteria isolated from urine of human UTIs and studying their antimicrobial sensitivity. Materials and methods: A total of 50 urine samples were collected from patients with UTIs of both genders. The isolates identification was done using routine diagnostic methods and confirmed by Vitek2. Antimicrobial susceptibility was done against 10 antimicrobials. Results: Both genders of human were found to suffer from urinary tract problems

Introduction: The association between acute stroke and
renal function is well known. The aim of this study is to
know which group of patients with acute stroke is more
likely to have undiagnosed Chronic Kidney Disease and
which risk factors are more likely to be associated with.
Methods:We studied 77 patients who were diagnosed to
have an acute stroke.Patients were selected between
April2011andJune 2011 using the " 4-variable
Modification of
Diet in Renal Disease Formula " which estimates
Glomerular Filtration Rate using four variables :serum
creatinine ,age ,race and gender.
Results :The study included 38 male and 39 females
patients ,aged (35-95) years. Glomerular Filtration Rate in
patients wi

Background: Obesity and diabetes mellitus are the common health problems,and obesity is common cause of the insulin resistance. Aim of studv: Aim of the study is to find any correlation between obesity (insulin resistance) and type I diabetes in children. Patients and methods: This study included (40) children with type I diabetes, in addition to (40) children as control.The age of all studied groups ranged from (8-18) years.This study was attemted from Ibn AlBalady Hospital during from 20 August to 9 Novembar,2008. The subjects wrer divided into (4) groups according to their BMI:- * Obese children,diabetes,n=2O,BMI>30. * Non obese children, diabetes, n=20,BMI<25. Obese children, non diabetes, n=20,BMI>30. * Non obese children,non diabetes

There is no adopt in the importance of the optical communications in scientific civil and military applications because of it’s simplicity in manufacturing and it's low cost. The method of optical communication depends upon bearing the light beam the translated informations by a method called the light modulation. This method depends upon changing some light properties as frequency, amplitude and pulse duration according to the translating informations. The changes in the first two properties are concerned optically with the analog modulation while the third one concern at most with digital modulation. All past methods are expensive with low efficiency and needs electrical or magnetic fields. In this technique the source of voice used

During COVID-19, wearing a mask was globally mandated in various workplaces, departments, and offices. New deep learning convolutional neural network (CNN) based classifications were proposed to increase the validation accuracy of face mask detection. This work introduces a face mask model that is able to recognize whether a person is wearing mask or not. The proposed model has two stages to detect and recognize the face mask; at the first stage, the Haar cascade detector is used to detect the face, while at the second stage, the proposed CNN model is used as a classification model that is built from scratch. The experiment was applied on masked faces (MAFA) dataset with images of 160x160 pixels size and RGB color. The model achieve

A nano-sensor for nitrotyrosine (NT) molecule was found by studying the interactions of NT molecule with new B24N24 nanocages. It was calculated using density functionals in this case. The predicted adsorption mechanisms included physical and chemical adsorption with the adsorption energy of −2.76 to −4.60 and −11.28 to −15.65 kcal mol−1, respectively. The findings show that an NT molecule greatly increases the electrical conductivity of a nanocage by creating electronic noise. Moreover, NT adsorption in the most stable complexes significantly affects the Fermi level and the work function. This means the B24N24 nanocage can detect NT as a Φ–type sensor. The recovery time was determined to be 0.3 s. The sensitivity of pure BN na

The meniscus has a crucial function in human anatomy, and Magnetic Resonance Imaging (M.R.I.) plays an essential role in meniscus assessment. It is difficult to identify cartilage lesions using typical image processing approaches because the M.R.I. data is so diverse. An M.R.I. data sequence comprises numerous images, and the attributes area we are searching for may differ from each image in the series. Therefore, feature extraction gets more complicated, hence specifically, traditional image processing becomes very complex. In traditional image processing, a human tells a computer what should be there, but a deep learning (D.L.) algorithm extracts the features of what is already there automatically. The surface changes become valuable when

During COVID-19, wearing a mask was globally mandated in various workplaces, departments, and offices. New deep learning convolutional neural network (CNN) based classifications were proposed to increase the validation accuracy of face mask detection. This work introduces a face mask model that is able to recognize whether a person is wearing mask or not. The proposed model has two stages to detect and recognize the face mask; at the first stage, the Haar cascade detector is used to detect the face, while at the second stage, the proposed CNN model is used as a classification model that is built from scratch. The experiment was applied on masked faces (MAFA) dataset with images of 160x160 pixels size and RGB color. The model achieve