From 144 specimens of tonsillitis which were collected from patient, (children of 3 -12 year olds) there were 70 isolates beta hemolytic and 28 isolates were identified as S. pyogenes. Sensitivity of S. pyogenes isolates to antibiotics was tested, all isolates were sensitive to amoxicillin and cephaloxia while higher resistant were to erythromycin. One isolate whiche was 100 A had a stable characteristics and produce pyrogenic toxin was chosen for study and it was purified and characterized from the cell free supernatant of S. pyrogenes strain.

In this article, the solvability of some proposal types of the multi-fractional integro-partial differential system has been discussed in details by using the concept of abstract Cauchy problem and certain semigroup operators and some necessary and sufficient conditions. 

From 211 urine samples, Gram negative bacteria were isolated from only 61 urine samples with isolation percentage 28.9%. Escherichia coli were isolated percentage 70.49% while Klebsiella pneumoniae and Psendomonas aeruginosa were 8.19% and 6.55%, respectively.Proteus spp. Were isolated from 9 (14.75%), P. mirablis and P. vulgaris were isolates percentage 11.47% and 3.27%, respectively. Uroepithelial Cell Adhesin (UCA) fimbriae expression by P.mirabilis isolates was detected by the high capacity to adhesion to human uroepithetial cells, the isolate p.mirabilis U7 was adhesion to human uroepithelial cells mean no.30.2 bacteria/cell when grown on luria broth at 37C for 24h, but then grown it’s on luria agar at 37C for 24h the adhesion

Deep Learning Techniques For Skull Stripping of Brain MR Images

General Background: Deep image matting is a fundamental task in computer vision, enabling precise foreground extraction from complex backgrounds, with applications in augmented reality, computer graphics, and video processing. Specific Background: Despite advancements in deep learning-based methods, preserving fine details such as hair and transparency remains a challenge. Knowledge Gap: Existing approaches struggle with accuracy and efficiency, necessitating novel techniques to enhance matting precision. Aims: This study integrates deep learning with fusion techniques to improve alpha matte estimation, proposing a lightweight U-Net model incorporating color-space fusion and preprocessing. Results: Experiments using the AdobeComposition-1k

One of the diseases on a global scale that causes the main reasons of death is lung cancer. It is considered one of the most lethal diseases in life. Early detection and diagnosis are essential for lung cancer and will provide effective therapy and achieve better outcomes for patients; in recent years, algorithms of Deep Learning have demonstrated crucial promise for their use in medical imaging analysis, especially in lung cancer identification. This paper includes a comparison between a number of different Deep Learning techniques-based models using Computed Tomograph image datasets with traditional Convolution Neural Networks and SequeezeNet models using X-ray data for the automated diagnosis of lung cancer. Although the simple details p

A new two-way nesting technique is presented for a multiple nested-grid ocean modelling system. The new technique uses explicit center finite difference and leapfrog schemes to exchange information between the different subcomponents of the nested-grid system. The performance of the different nesting techniques is compared, using two independent nested-grid modelling systems. In this paper, a new nesting algorithm is described and some preliminary results are demonstrated. The validity of the nesting method is shown in some problems for the depth averaged of 2D linear shallow water equation.