The current study was designed to remove Lead, Copper and Zinc from industrial wastewater using Lettuce leaves (Lactuca sativa) within three forms (fresh, dried and powdered) under some environmental factors such as pH, temperature and contact time. Current data show that Lettuce leaves are capable of removing Lead, Copper and Zinc ions at significant capacity. Furthermore, the powder of Lettuce leaves had highest capability in removing all metal ions. The highest capacity was for Lead then Copper and finally Zinc. However, some examined factors were found to have significant impacts upon bioremoval capacity of studied ions, where best biosorption capacity was found at pH 4, at temperature 50º C and contact time of 1 hour.

Out of a total of fifty samples, thirty-five isolates were identified as Serratia marcescens. Thesediverse clinical samples were collected over a three-month period, from October 2023 to December 2023, fromseveral hospitals in Baghdad, including Fatima Al-Zahraa Hospital, Al-Sader Hospital, Ibn Al-Balady Hospital,and Al-Imam Ali Hospital. The clinical samples primarily included urine from patients with urinary tractinfections (UTIs). All isolates were cultured on nutrient agar, MacConkey agar, and blood agar, and theiridentities were confirmed through biochemical testing and the Vitek 2 compact system. Based on phenotypicvirulence factors, the S. marcescens isolates showed varying positive patterns: 32 out of 35 (91.42%) forprotease

Digital tampering identification, which detects picture modification, is a significant area of image analysis studies. This area has grown with time with exceptional precision employing machine learning and deep learning-based strategies during the last five years. Synthesis and reinforcement-based learning techniques must now evolve to keep with the research. However, before doing any experimentation, a scientist must first comprehend the current state of the art in that domain. Diverse paths, associated outcomes, and analysis lay the groundwork for successful experimentation and superior results. Before starting with experiments, universal image forensics approaches must be thoroughly researched. As a result, this review of variou

Artificial Intelligence Algorithms have been used in recent years in many scientific fields. We suggest employing flower pollination algorithm in the environmental field to find the best estimate of the semi-parametric regression function with measurement errors in the explanatory variables and the dependent variable, where measurement errors appear frequently in fields such as chemistry, biological sciences, medicine, and epidemiological studies, rather than an exact measurement. We estimate the regression function of the semi-parametric model by estimating the parametric model and estimating the non-parametric model, the parametric model is estimated by using an instrumental variables method (Wald method, Bartlett’s method, and Durbin

Water pollution has created a critical threat to the environment.‎‎ A lot of research has been done ‎recently to use surface-enhanced Raman spectroscopy (SERS) to detect multiple pollutants in water. This study aims to use Ag colloid nanoflowers as liquid SERS enhancer. Tri sodium phosphate (Na₃PO₄) was investigated as a pollutant using liquid SERS ‎based on colloidal Ag ‎nanoflowers. The chemical method was used to synthesize nanoflowers from silver ‎ions. Atomic Force Microscope (AFM), Scanning Electron Microscope (SEM), and X-ray diffractometer (XRD) were employed to characterize the silver nanoflowers. This ‎nanoflowers SERS action in detecting Na₃PO₄ was reported and analyzed

Background: Although mammography is a powerful screening tool in detection of early breast cancer, it is imperfect, particularly for women with dense breast, which have a higher risk to develop cancer and decrease the sensitivity of mammogram, Automated breast ultrasound is a recently introduced ultrasonography technique, developed with the purpose to standardize breast ultrasonography and overcome some limitations of handheld ultrasound, this study aims to evaluate the diagnostic efficacy of Automated breast ultrasound and compare it with handheld ultrasound in the detection and characterization of breast lesions in women with dense breasts. Objectives: To evaluate the diagnostic efficacy of Automated breast ultrasound and compare