The transfer of chemical pollutants from bottled water into water due to heat, sunlight and poor storage is one of the most serious threats to human health around the world, the objective of this study was to estimate the pH value and the transport of heavy metals from plastic bottles to water, for this purpose, 30 bottles of water for 10 local brands were collected and divided into three groups, the first was left at room temperature 25°C, The second was placed in a heat oven at 25°C and the third in another oven at 50°C for two weeks. The results showed significant differences at (P<0.05) between water samples, pH value and concentrations of heavy metals (Sb, Pb, Ni, Cu, Cr, Cd and Fe) we

The results shows existence of metals such as copper, iron, Cadmium, lead and zinc in most of examined samples , the highest concentration are up to (2.26, 40.82, 282.5, 31.02, 19.26, 4.34) Part per million) ppm) in pasta hot (Zer brand), Indomie with chicken, granule (Zer brand), brand (Zer brand), and rice (mahmood brand) respectively, with presence nickel in spaghetti( Zer brand), granule, Zer brand with concentration reached to 4.34 ppm and 1.06 ppm respectively.
The results of cereals group and its products show that two kinds of fungi, Aspergillus spp. and Penicillin spp. were found in rice (Mahmood brand) with numbers got to 1.5×103 Colony Forming Unit/ gram (c.f.u./g),while Bacillus cereus and Staphylococcus aureus were isola

This study assessed the advantage of using earthworms in combination with punch waste and nutrients in remediating drill cuttings contaminated with hydrocarbons. Analyses were performed on day 0, 7, 14, 21, and 28 of the experiment. Two hydrocarbon concentrations were used (20000 mg/kg and 40000 mg/kg) for three groups of earthworms number which were five, ten and twenty earthworms. After 28 days, the total petroleum hydrocarbon (TPH) concentration (20000 mg/kg) was reduced to 13200 mg/kg, 9800 mg/kg, and 6300 mg/kg in treatments with five, ten and twenty earthworms respectively. Also, TPH concentration (40000 mg/kg) was reduced to 22000 mg/kg, 10100 mg/kg, and 4200 mg/kg in treatments with the above number of earthworms respectively. The p

This study investigates the treatment of used lubricating oils from AL-Mussaib Gas Power Station Company-Iraq, which was treated with different extractive solvents (heptane and 2-propanol). The performance activity of these solvents in the extraction process was examined and evaluated experimentally. Operating parameters were solvent to oil ratios of (1:2, 1:4, 1:6, and 1:8), mixing time (20, 35, 50, and 65 min), temperatures (30, 40, 50, and 60 ºC), and mixing speed (500 rpm). These parameters were studied and analyzed. The quality is determined by the measuring and assessment of important characteristics specially viscosity, viscosity index, specific gravity, pour point, flash point, and ash content. The results confirm that the solve

The -multiple mixing ratios of γ-transitions from levels of populated in the are calculated in the present work by using the a2-ratio methods. We used the experimental coefficient (a2) for two γ-transitions from the same initial state, the statistical tensor, which is related to the a2-coefficient would be the same for the two transitions. This method was used in a previous work for pure transitions or which can be considered pure. In these cases the multiple mixing ratios for the second transition ( ) equal zero, but in our work we applied this method for mixed γ-transitions and then the multiple mixing ratio ( ) is known for one transition. Then we calculate the ( ) value and versareversa. The weight average of the -values calcu

Attention-Deficit Hyperactivity Disorder (ADHD), a neurodevelopmental disorder affecting millions of people globally, is defined by symptoms of hyperactivity, impulsivity, and inattention that can significantly affect an individual's daily life. The diagnostic process for ADHD is complex, requiring a combination of clinical assessments and subjective evaluations. However, recent advances in artificial intelligence (AI) techniques have shown promise in predicting ADHD and providing an early diagnosis. In this study, we will explore the application of two AI techniques, K-Nearest Neighbors (KNN) and Adaptive Boosting (AdaBoost), in predicting ADHD using the Python programming language. The classification accuracies obtained w