Background: Bacteriocin is a peptidic toxin has many advantages to bacteria in their ecological niche and has strong antibacterial activity. Objective: The aim of this study was to evaluation of bacteriocin using Streptococcus sanguinis isolated from human dental caries.

Subjects and Methods: Thirty five streptococcus isolates were diagnosed and tested for their production of bacteriocin, and then the optimal conditions for production of bacteriocin were determined.  After that, the purification of bacteriocin was made partially by ammonium sulfate at 95% saturation levels, followed by and gel filtration chromatography

Forty lower premolars with single root canals prepared with ProtaperNext files to size 25, and obturated with GP/sealer using lateral compaction. Teeth divided randomly into four groups (group n=10). Protaper universal retreatment kit (PUR), D-Race desobturation files (DRD), R-Endo retreatment kit (RE) and Hedstrom (H) files (control) were used to remove GP/sealer in each group. Removal effectiveness assessed by measuring the GP /sealer remnants in the roots after sectioning them into two halves. Stereomicroscope with a digital camera used to capture digital images. Images processed by ImageJ software to measure the percentage of GP/sealer remnants surface area in total, coronal, middle and apical areas of the canal. In the coronal area,

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

Nowadays, cloud computing has attracted the attention of large companies due to its high potential, flexibility, and profitability in providing multi-sources of hardware and software to serve the connected users. Given the scale of modern data centers and the dynamic nature of their resource provisioning, we need effective scheduling techniques to manage these resources while satisfying both the cloud providers and cloud users goals. Task scheduling in cloud computing is considered as NP-hard problem which cannot be easily solved by classical optimization methods. Thus, both heuristic and meta-heuristic techniques have been utilized to provide optimal or near-optimal solutions within an acceptable time frame for such problems. In th

Sequence covering array (SCA) generation is an active research area in recent years. Unlike the sequence-less covering arrays (CA), the order of sequence varies in the test case generation process. This paper reviews the state-of-the-art of the SCA strategies, earlier works reported that finding a minimal size of a test suite is considered as an NP-Hard problem. In addition, most of the existing strategies for SCA generation have a high order of complexity due to the generation of all combinatorial interactions by adopting one-test-at-a-time fashion. Reducing the complexity by adopting one-parameter- at-a-time for SCA generation is a challenging process. In addition, this reduction facilitates the supporting for a higher strength of cove

Sewer system plays an essential task in urban cities by protecting public health and the environment. The operation, maintenance, and rehabilitation of this network have to be sustainable and scientifically. For this purpose, it is crucial to support operators, decision makers and municipalities with performance evaluation procedure that is based on operational factors. In this paper, serviceability and performance indicator (PI) principles are employed to propose methodology comprising two enhanced PI curves that can be used to evaluate the individual sewers depending on operational factors such as flowing velocity and wastewater level in the sewers. To test this methodology; a case study of al-Rusafa in Baghdad city is

A series of laboratory model tests has been carried out to investigate the using of pomegranate sticks mat as reinforcement to increase the bearing capacity of footing on loose sand. The influence of depth and length of pomegranate sticks layer was examined. In the present research single layer of pomegranate sticks reinforcement was used to strengthen the loose sand stratum beneath the strip footing. The dimensions of the used foundation were 4*20 cm. The reinforcement layer has been embedded at depth 2, 4 and 8 cm under surcharge stresses . Reinforcing layer with length of 8 and 16 cm were used. The final model test results indicated that the inclusion of pomegranate sticks reinforcement is very effective in improvement the loading cap