Aim: To evaluation the effect of Lactobacillus acidophilus on Enterohemorrhagic Escherichia coli (EHEC) serotype O157:H7 with detection of some virulence factors. Methods: Two hundred and fifty specimens (stool) from children under five years for both sexes were collected from some hospitals. All isolates were diagnosed according to morphological characteristics, biochemical tests. Monoplex pattern of PCR was used also for detection different genes in (7) Escherichia coli )O157:H7 (isolates; include 16SrRNA, eae, lifA, Stx1,Stx2 that encoded for ribosomal RNA, intimin, lymphocyte inhibitory factor, shiga toxins. Three types of probiotics strains were obtained, Lactobacillus fermentum, Lactobacillus plantarum and Lactobacillus acidophilus (A

Moisture damage is a primary mode of distress occurring in hot mix asphalt (HMA) pavements in Iraq. Because of the loss of bond, or stripping, caused by the presence of moisture between the asphalt and aggregate, which is a problem in some areas and can be severe in some cases, it is requires to evaluate the design asphalt mixture to moisture susceptibility. Many factors such as aggregate characteristics, asphalt characteristics, environment, traffic, construction practices and drainage can contribute to stripping. Asphalt concrete mixes were prepared at their optimum asphalt content by superpave system and then tested to evaluate their engineering properties, which include tensile strength, resilient modulus, and perman

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

Polymer matrix composites are suitable materials for medical applications, such as denture base resin polymethyl methacrylate (PMMA). This includes light weight and high strength. This paper describes the effect of selected weight fractions (1, 2, 3, 4 & 5) % wt of nano(Alumina AL2O3, Zirconia ZrO2, Hydroxyapatite HA and Halloysite nanoClay) reinforcements on the biopolymer matrix (PMMA). Some tribology tests were used to evaluate the prepared system (impact strength, hardness surface, and wear rate) tests. The samples were fabricated by (Hand Lay-Up) with different particle reinforcement percentages. All tests were accomplished at room temperature, and samples were developed according to the ASTM standard. The weight fraction of (4% for AL

Polymer matrix composites are suitable materials for medical applications, such as denture base resin polymethyl methacrylate (PMMA). This includes light weight and high strength. This paper describes the effect of selected weight fractions (1, 2, 3, 4 & 5) % wt of nano(Alumina AL2O3, Zirconia ZrO2, Hydroxyapatite HA and Halloysite nanoClay) reinforcements on the biopolymer matrix (PMMA). Some tribology tests were used to evaluate the prepared system (impact strength, hardness surface, and wear rate) tests. The samples were fabricated by (Hand Lay-Up) with different particle reinforcement percentages. All tests were accomplished at room temperature, and samples were developed according to the ASTM standard. The weight fraction o