In this article Silver nanoparticles have been synthesized through physical method where the Nd-YAG laser has been used.The antimicrobial activities of these silver nanoparticles were investigated on two types of bacteria Escherichia coli and Staphylococcus aureus. These bacteria were used as representatives of Gram-negative and Gram-positive bacteria, respectively. Two experiments have been made The first one was to test the effectiveness of silver nanoparticles as an antimicrobial agent on Gram negative bacteria Escherichia coli and Gram positive bacteria Staphylococcus aureus, while the other one (susceptibility Test) was to evaluate antimicrobial agents effective against bacteria resistant to multiple antibiotics. This study showed t

The objective of this study is to investigate the application of advanced oxidation processes (AOPs) in the treatment of wastewater contaminated with furfural. The AOPs investigated is the homogeneous photo-Fenton (UV/H₂O₂/Fe⁺²) process. The experiments were conducted by using cylindrical stainless steel batch photo-reactor. The influence of different variables: initial concentration of H₂O₂ (300-1300mg/L), Fe⁺²(20-70mg/L), pH(2-7) and initial concentration of furfural (50-300 mg/L) and their relationship with the mineralization efficiency were studied.

 Complete mineralization for the system UV/H₂O₂/Fe⁺² was achieved at: initi

Four samples were collected from the wastewater of State Battery Manufacturing Company (SBMC); Babylon 2 factory in AL-Waziriya district, as triplicates. Physical and chemical measurements were carried out such as temperature, pH, Lead concentrations and their ranges were: (19.5-34.5) °C, (6.1-6.4) and (4.5-6.5) mg/L, respectively. Six dominant Bacillus spp. isolates were isolated from these samples; namely, Bacillus subtilis N1, Bacillus subtilis N2, Bacillus subtilis N3, Bacillus cereus N4, Bacillus cereus N5 , Bacillus cereus N6. These isolates were capable of removing Lead from aqueous solutions in a capacity reached 27.6 ± 1.4, 10.1 ± 1.7, 74.5 ± 0.7, 8.93 ± 2.8, 8.1 ± 3.5, 1.6± 0.7 mg/L, respectively. Whereas cell walls,

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