Water produced from power plants is one of the most important sources of water pollution, especially for areas like Baghdad, Contaminated industrial wastewater is a major environmental challenge due to the rapid growth of industries, leading to increased accumulation of harmful pollutants in water resources, the work is intended to study the impact of water generated from a power plant in the south on the level of heavy metals before and after the treatment process and after its discharge to the Tigris River. Objective is to determine the extent of heavy metals such as iron, copper, chromium, and zinc concentration in water extracted from various points and subsequently study the monthly variations of these elements with a view to assessmen

The preparation of low cost activated carbon from date stones and microwave method by using K₂CO₃ as chemical activator were investigated.

   The prepared activated carbon was used to remove fluoroquinolones antibiotics from aqueous solution. The characterizations of the activated carbon is represented by surface area, pore volume, ash content, moisture content, bulk density, and iodine number. The adsorbed fluoroquinolones antibiotics are Ciprofloxcin (CIP), Norfloxcin (NOR) and Levofloxcin (LEVO). Different variables as pH, initial concentrations and contact time were studied to show the efficieny of prepared activated carbon. The experimental adsorption data were analyzed by Lungmuir, Freundlich

Morphologies of ceramic hollow fiber membranes prepared by a combined phase-inversion and sintering method were studied. The organic binder spinning solution containing suspended Al₂O₃ powders was spun to a hollow fiber precursor, which was then sintered at elevated temperatures( 300 ˚C, 1400 ˚C, 25 ˚C) in order to obtain the Al₂O₃ hollow fiber membranes. The spinning solution consisted of polyether sulfone (PES), N-methyl-2-pyrrolidone (NMP), which were used as polymer binder, solvent, respectively. The prepared Al₂O₃ hollow fiber membranes were characterized by a scanning electron microscope (SEM). It is believed that finger-like void formation in asymmetric ceramic membranes is initiated by hydrodynamically unstable vis

Isolation and identification fungi of Emericella nidulans and Aspergillus flavus from a pinkish and yellowish artificial clay, by using potato dextrose agar (PDA). Results revealed that E. nidulans was the best for degrading anthracene (92.3%) with maximum biomass production (3.7gm/l), compared to A. flavus with the rate of degradation (89%) and biomass production of (1.2gm/l), when methylene blue was used as redox indicator after incubating in a shaker incubator 120rpm at 30Co for 8days. Results indicated that E. nidulans has a high ability of anthracene degradation with the rate of (84%), while A. flavus showed the lower level with (77%) by using HPLC.

In this contribution, density functional theory-based calculations have been carried out to assess the electronic, photocatalytic and optical properties of Ce1-xTixO2 system. Ti incorporation leads to a decrease of Ce 4f states and enhancement of Ti 3d states in the bottom of conduction band. Furthermore, it was found that doping ceria with Ti-like transition metals could evidently shift the absorption of pure CeO2 towards higher wavelength range. These findings can provide some new insights for designing CeO2-based photocatalysts with high photocatalytic performance. To the best of our knowledge, this investigation calculates Mullikan’s charge transfer of Ce1-xTixO2 system for the first time. Charge transfer reveals an ionic bond between

KA Sharquie, AA Al-Nuaimy, Annals of Saudi Medicine, 2002 - Cited by 48

The COVID-19 pandemic has necessitated new methods for controlling the spread of the virus, and machine learning (ML) holds promise in this regard. Our study aims to explore the latest ML algorithms utilized for COVID-19 prediction, with a focus on their potential to optimize decision-making and resource allocation during peak periods of the pandemic. Our review stands out from others as it concentrates primarily on ML methods for disease prediction.To conduct this scoping review, we performed a Google Scholar literature search using "COVID-19," "prediction," and "machine learning" as keywords, with a custom range from 2020 to 2022. Of the 99 articles that were screened for eligibility, we selected 20 for the final review.Our system