The aim of this study was to use low cost adsorbents, which consist of corn cobs as plant wastes adsorbents in treatment of Industrial waste water by fixed bed column technique and study the effect of two variables (pH value and contact time). The sample of plant waste (Corn cobs) was tested to determine its activity which gives the best performance in heavy metals removal and other pollutants (TSS, TDS and COD). Adsorption tests showed the corn cobs adsorbents had significant heavy metal removal efficiency. The best removal efficiency 95.05% of Cr was occurred at pH 5.4 and 4.18hr. Higher removal efficiency 99.90% of Ni was occurred at pH 6.5 and 2.38hr. While, lower removal efficiency 91.35% for Zn obtained at pH 6.5 and 0.15hr. Remova

Aeration system in the cultivation of Chlorella Sp. Microalgae using dairy wastewater as culture media was addressed in the current study. This research aimed to study the effect of aeration in the bubble column bioreactor on the biological synergy between microalgae and bacteria if they are present in the same place. The results show that the sterilization stage is not the dominant step in the success of microalgae cultivation in water-rich organic waste. There is a clear convergence between the growth rate of Chlorella microalgae in the sterilized and non-sterilized culture media, which gives realism if the proposal is applied industrially. Through the information obtained the aerobic bacteria in the non-sterilized me

     The main parameters and methods influencing the removal of Gentian Violet (GV) dye from aqueous media were investigated using a stachy plant in this study. The surface of the stachy plant was determined using FTIR spectra. Adsorption is influenced by the adsorbent's characteristic groups. The research took into account the usual conditions for GV dye adsorption by the stachy plant, such as the impact of contact time. Mass dosage , after 0.3 g the amount of adsorbed dye declines. Study pH and ionic strength, the results obtained showed that at pH 3 the largest adsorption of (GV) was seen, while at pH 9, the lowest adsorption was observed  at 298 K, the adsorption kinetics and equilibrium constants were achieved, and the equilibr

The last few years witnessed great and increasing use in the field of medical image analysis. These tools helped the Radiologists and Doctors to consult while making a particular diagnosis. In this study, we used the relationship between statistical measurements, computer vision, and medical images, along with a logistic regression model to extract breast cancer imaging features. These features were used to tell the difference between the shape of a mass (Fibroid vs. Fatty) by looking at the regions of interest (ROI) of the mass. The final fit of the logistic regression model showed that the most important variables that clearly affect breast cancer shape images are Skewness, Kurtosis, Center of mass, and Angle, with an AUCROC of

In this paper, the maximum likelihood estimates for parameter ( ) of two parameter's Weibull are studied, as well as white estimators and (Bain & Antle) estimators, also Bayes estimator for scale parameter ( ), the simulation procedures are used to find the estimators and comparing between them using MSE. Also the application is done on the data for 20 patients suffering from a headache disease.

Pseudomonas aeruginosa has variety of virulence factors that contribute to its pathogenicity. Therefore, rapid detection with high accuracy and specificity is very important in the control of this pathogenic bacterium. To evaluate the accuracy and specificity of Polymerase Chain Reaction (PCR) assay, ETA and gyrB genes were targeted to detect pathogenic strains of P. aeruginosa. Seventy swab samples were taken from patients with infected wounds and burns in two hospitals in Erbil and Koya cities in Iraq. The isolates were traditionally identified using phenotypic methods, and DNA was extracted from the positive samples, to apply PCR using the species specific primers targeting ETA, the gene encoding for exotoxin A, and gyrB gene. The res