The present study was conducted to investigate the antimicrobial activity of the hot water and the hot ethanolic extracts of Thuja orientalis against some pathogenic microorganisms (Staphylococcus aureus, Pseudomonas aeruginosa, Eschericha coli, Proteus mirrablis, Salmonilla typhi, Klebsiella pneumoniae, Bacillus cereus, Bacillus subtilus, Acinobacter, Staphylococcus epidermidis and Candida albicans). Results showed that both the water and alcoholic extracts of this plant exert marked inhibitory effect against all the bacterial isolates and yeast and at different ratio, and it was shown that ethanolic extract was more effective in microbial inhibition than the water extract. Maximum inhibition (16 mm) was recorded against Staphylococcus aur

Gas adsorption phenomenon on solid surface has been used as a mean in separation and purification of gas mixture depending on the difference in tendencies of each component in the gas mixture to be adsorbed on the solid surface according to its behaviour. This work concerns to study the possibilities to separate the gas mixture using adsorption-desorption phenomenon on activated carbon. The experimental results exhibit good separation factor at temperature of -40 .

Segmented regression consists of several sections separated by different points of membership, showing the heterogeneity arising from the process of separating the segments within the research sample. This research is concerned with estimating the location of the change point between segments and estimating model parameters, and proposing a robust estimation method and compare it with some other methods that used in the segmented regression. One of the traditional methods (Muggeo method) has been used to find the maximum likelihood estimator in an iterative approach for the model and the change point as well. Moreover, a robust estimation method (IRW method) has used which depends on the use of the robust M-estimator technique in

Problem: Cancer is regarded as one of the world's deadliest diseases. Machine learning and its new branch (deep learning) algorithms can facilitate the way of dealing with cancer, especially in the field of cancer prevention and detection. Traditional ways of analyzing cancer data have their limits, and cancer data is growing quickly. This makes it possible for deep learning to move forward with its powerful abilities to analyze and process cancer data. Aims: In the current study, a deep-learning medical support system for the prediction of lung cancer is presented. Methods: The study uses three different deep learning models (EfficientNetB3, ResNet50 and ResNet101) with the transfer learning concept. The three models are trained using a

In Iraqi patients with acromegaly the present investigation included 40 control group and 70 patients with acromegaly divided 35 patients with Diabetic while another 35 patients without Diabetic, with ages between (29-72) years for the identification of GST activity polymorphisms by present and absent GSTM1, GSTT1, and PCR-RFLP, enzymatic digestions were carried out using BsmAI (Biolabs. England, UK) for GSTP1b and AciI (Biolabs, England, UK) for GSTP1c.the association GSTActivity with GST genotype were investigated in a cohort of Iraq acromegaly patients comparing with the healthy control group. The results show a non-significant change in GSTP1b gene in both groups, while show high significantly in GSTP1c in diabetic and non-diabetic acro

In this work Different weight of pure Zinc powder suspended particles in 4ml base engine Oil were used.
Intensity of Kα Line was measured for the suspended particles ,also for mixture which consist from Zinc particle blended with Engine base Oil. Calibration Curve was drawn between Ikα line Intensity and Zinc concentration at different operation condition. The Lower Limit detection (LLD) and Sensitivity (m) of Spectrometer were determined for different Zinc Concentration (Wt%). The results of LLD and m for Samples were analyzed at Operation Condition of 30KV,17mA is best from Samples were analyzed at Operation Condition of 25KV,15mA

     A new colorimetric-flow injection method has been developed and validated for the detection of Cefotaxime sodium in pharmaceutical formulations. This method stands out for its rapid and sensitive nature. The formation of a brown-colored complex between Cefotaxime sodium and the Biuret reagent in a highly alkaline environment serves as the basis for the detection. The intensity of this colored complex is measured using a custom-built Continuous Flow Injection Analyzer, enabling accurate quantification of Cefotaxime sodium. Optimization studies of the chemical and physical parameters such as dilution of Biuret reagent, effect of the medium basicity, flow rate, sample loop and others have been investigated. The calibration gra