Dentures that are not cleaning and maintained properly may prone to contamination by different microbial pathogens that result in several oral conditions. This study was design to compare the antimicrobial effect of different denture cleansers oxalic, tartaric, citric acids and alkaline peroxide with microwave irradiation on the growth of Candida albicans and Staphylococcus aureus respectively. Microwave oven used to disinfect specimens of heat-activated acrylic resin and soft linear. Oxalic, citric, tartaric acids, and alkaline peroxide were also used. Microorganisms that tested were Candida albicans and Staphylococcus aureus separately. Treatment with microwave or tartaric acid could achieve sterilization of both hot cured acrylic resins

A total of 41 patients with gastro duodenal symptoms (show signs of inflammation with or without duodenal ulcer) . 21 males (51.2%) and 20 female (48.8%) with an average age 0f  (20 – 80) years old under  going gastrointestinal endoscopy at Baghdad teaching hospital in internal disease clinical laboratory , between (February – June)  2009 . Biopsies specimen of antrum , gastric fundus ,& duodenal bulb were examined by the following methods (rapid urease test , Giemsa stain section to detect bacteria , & Haematoxilin and Eosin stained section for pathological study which are considered the gold standard methods , sera or plasma from these patients were tested by immunochromotography (ICM),serological m

this study aimed to study the effect of Cordia myxa extract on the growth and activities of the following types of bacteria : Escherichia coli , Pseudomonas aeruginosa, Proteus Spp., Klebsiella pneumoniae , Staphylococcus aureus, Streptococcus pyogenes , Bacillus subtilus, and the yeast Candida albicans .the results showed an inhibitory effect of the methanol extract on both the growth and activity of the tested microbes .this was reflected by the minimum inhibitory concentration ( MIC ) of different type of bacteria and the yeast.

Summary The aim of this study is the evaluation the resistance of S. marcescence obtained from soil and water to metals chlorides (Zn+2, Hg+2, Fe+2, Al+3, and Pb+2). Four isolates, identified as Serratia marcescence and S. marcescena (S4) were selected for this study according to their resistance to five heavy metals. The ability of S. marcescena (S4) to grow in different concentrations of metals chloride (200-1200 µg/ml) was tested, the highest concentration that S. marcescence (S4) tolerate was 1000 µg/ml for Zn+2, Hg+2, Fe+2, AL+3, pb+2 and 300 µg/ml for Hg+2 through 24 hrs incubation at 37 Co. The effects of temperature and pH on bacteria growth during 72 hrs were also studied. S. marcescence (S4) was affected by ZnCl2, PbCl2, FeC12

In this study, six square reinforced concrete flat plates with dimensions of (1500×1500×100) mm were tested under a concentrated load applied on a column located at the center of the slabs. One of these slabs was the control specimen, whereas, in the others, steel angles (steel collars) were used, fixed at the connection region between the slab and the column to investigate the effect of the presence of these collars on punching shear strength. Five thicknesses were used (4, 5, 6, 8, 10mm) with constant legs of angles (75×75) mm of the steel collars to investigate the effects on the punching shear resistance with respect to the control slab. The results of the experimental study show that the punching shear resistance increased b

In recent years, the field of research around the congestion problem of 4G and 5G networks has grown, especially those based on artificial intelligence (AI). Although 4G with LTE is seen as a mature technology, there is a continuous improvement in the infrastructure that led to the emergence of 5G networks. As a result of the large services provided in industries, Internet of Things (IoT) applications and smart cities, which have a large amount of exchanged data, a large number of connected devices per area, and high data rates, have brought their own problems and challenges, especially the problem of congestion. In this context, artificial intelligence (AI) models can be considered as one of the main techniques that can be used to solve ne