Objective(s): This study aims to evaluate the hardness of two commercially available cold cured acrylic resin material
(Vertex and PAN) when polymerized at different temperature in comparison to those polymerized by conventional
methods in air at 23C ± 5C.
Methodology: Eighty specimens, forty from cold cured acrylic (Vertex Type) and forty from cold cured acrylic (PAN
type) were prepared, flasking and packing procedure were done according to manufacturer direction and divided
according to processing as follow: 20 specimens (10 from Vertex type and 10 from PAN type) were processed in air for
two hours at 23C ± 5C under press (bench curing) as a control, and 60 specimens (30 from Vertex type and 30 from
PAN type) wer

Brucella melitensis isolates were obtained from human infections , and milk which obtained from aborted sheep at Mosul city vicinity . One isolate from each source was used in carrying out this study. Brucella liquid culture was added to sheep milk at 2.5 % for treatments . To first treatment 2 % of yoghurt starter ( Lactobacillus delbrueckii subsp. bulgaricus and Streptococcus salivarius subsp. thermophilus ( 1: 1 ) ) . Second treatment was carried out without addition of yoghurt starter but the pH was lowered using lactic acid in pattern similar to first treatment . Third treatment was similar to the first treatment but contained buffer to alleviate the reduction in pH , which reduced to 6.1 in comparison to 4.9 of the first treatment .

     Heavy metal ion removal from industrial wastewater treatment systems is still difficult because it contains organic contaminants. In this study, functional composite hydrogels with photo Fenton reaction activity were used to decompose organic contaminants. Fe₃O₄ Nanoparticle, chitosan (CS), and other materials make up the hydrogel. There are different factors that affected Photo-Fenton activity including (pH, H₂O₂ conc., temp., and exposure period). Atomic force microscopy was used to examine the morphology of the composite and its average diameter (AFM). After 60 minutes of exposure to UV radiation, CS/ Fe₃O₄ hydrogel composite had degraded methylene blue (M.B.)

Oil well drilling fluid rheology, lubricity, swelling, and fluid loss control are all critical factors to take into account before beginning the hole's construction. Drilling fluids can be made smoother, more cost-effective, and more efficient by investigating and evaluating the effects of various nanoparticles including aluminum oxide (Al₂O₃) and iron oxide (Fe₂O₃) on their performance. A drilling fluid's performance can be assessed by comparing its baseline characteristics to those of nanoparticle (NPs) enhanced fluids. It was found that the drilling mud contained NPs in concentrations of 0,0.25, 0. 5, 0.75 and 1 g. According to the results, when drilling fluid was used without NPs, the coeff

The pollution producing from textile industries effluents is growing since the years, due to at discharged lots of it in water without treatment. The resulting effluent is colourful, highly toxic, and poses a significant environmental hazard. This problem can be solved by using enzymic biological treatment, where the Congo red dye was used with concentrations (100,200,300,500) mg /L, pH values (3,4,5,6,7,8), and variable temperatures (25,35,45)°C, the best removal of Congo red (CR) dye  under optimum conditions for degradation was at  concentration of 100 mg/L, at (pH 6, 25 °C) with efficiency of 99.85 % using the peroxidase enzyme extracted from red radish plant, while the removal percentage decreased when increase dye concentration

 A mixture model is used to model data that come from more than one component. In recent years, it became an effective tool in drawing inferences about the complex data that we might come across in real life. Moreover, it can represent a tremendous confirmatory tool in classification observations based on similarities amongst them. In this paper, several mixture regression-based methods were conducted under the assumption that the data come from a finite number of components. A comparison of these methods has been made according to their results in estimating component parameters. Also, observation membership has been inferred and assessed for these methods. The results showed that the flexible mixture model outperformed the others

 A mixture model is used to model data that come from more than one component. In recent years, it became an effective tool in drawing inferences about the complex data that we might come across in real life. Moreover, it can represent a tremendous confirmatory tool in classification observations based on similarities amongst them. In this paper, several mixture regression-based methods were conducted under the assumption that the data come from a finite number of components. A comparison of these methods has been made according to their results in estimating component parameters. Also, observation membership has been inferred and assessed for these methods. The results showed that the flexible mixture model outperformed the