BACKGROUND: Femoral shaft fracture is a common fracture in pediatric age group reaching 62% of all fracture shaft femur in children in spite of rapid union rate and successful conservative treatment but some cases need surgical intervention and one of the methods using plate and screw by the lateral approach. AIM: This study aims to compare functional outcome fixation of mid-shaft femur fracture in children by plate and screws between (subvastus lateralis and transvastus lateralis) regarding infection, union, and limitation of knee movement. PATIENT AND METHOD: The study was done on 30 children who had diaphyseal fracture femur in Al-Kindy Teaching Hospital in period (April 2018–April 2020) with 6 months follow-up, and the pa

Background: Antimicrobial agents have been considered as having potential for the prevention of dental caries. This study aimed to test the effect of different concentrations of cardamom and black tea extracts on the sensitivity and growth of salivary mutans streptococci in comparison to chlorhexidine gluconate (0.2%) in vitro. Materials and methods: In this study. Mutans streptococci were isolated from saliva of 34 healthy people (aged between 22-40yrs). The bacteria was isolated, purifiedand diagnosed according to morphologicalcharacteristic and biochemical tests. Aqueous extracts of cardamom and black tea were prepared. Different concentrations of extracts were prepared and estimated in gm/ 100ml deionized water. The agar diffusion techn

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

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

يسعى البحث إلى الاهتمام بإحدى الوظائف المهمة في إدارة الموارد البشرية وهي تقويم الأداء التي تواجه مجموعة من الانتقادات والآراء السلبية، اذ ظهر في الأّونة الأخيرة أنموذج جديد يمكن إن يتجاوز تلك السلبيات وهو أنموذج التغذية العكسية المتعدد المصادر درجة .وقد حاول الباحثان توظيف هذا المفهوم في اثنتين من المنظمات العامة العراقية هما (دائرة كهرباء الوسط) التابعة لوزارة الكهرباء
و (دائرة الماء والمجاري) ال

Security concerns in the transfer of medical images have drawn a lot of attention to the topic of medical picture encryption as of late. Furthermore, recent events have brought attention to the fact that medical photographs are constantly being produced and circulated online, necessitating safeguards against their inappropriate use. To improve the design of the AES algorithm standard for medical picture encryption, this research presents several new criteria. It was created so that needs for higher levels of safety and higher levels of performance could be met. First, the pixels in the image are diffused to randomly mix them up and disperse them all over the screen. Rather than using rounds, the suggested technique utilizes a cascad

The electrospun nanofibers membranes (ENMs) have gained great attention due to their superior performance. However, the low mechanical strength of ENMs, such as the rigidity and low strength, limits their applications in many aspects which need adequate strength, such as water filtration. This work investigates the impact of electrospinning parameters on the properties of ENMs fabricated from polyacrylonitrile (PAN) solved in N, N-Dimethylformamide (DMF). The studied electrospinning parameters were polymer concentration, solution flow rate, collector rotating speed, and the distance between the needle and collector. The fabricated ENMs were characterized using scanning electron microscopy (SEM) to understand the surface morphology and es

Experimental measurements of viscosity and thermal conductivity of single layer of graphene . based DI-water nanofluid are performed as a function of  concentrations (0.1-1wt%) and temperatures between (5 to 35ºC). The result reveals that the thermal conductivity of GNPs nanofluids was increased with increasing the nanoparticle weight fraction concentration and temperature, while the maximum enhancement was about 22% for concentration of 1 wt.% at
35ºC. These experimental results were compared with some theoretical models and a good agreement between Nan’s model and the experimental results was observed. The viscosity of the graphene nanofluid displays Newtonian and Non-Newtonian behaviors with respect to nanoparticles concen