The removal of Anit-Inflammatory drugs, namely; Acetaminophen (ACTP), from wastewater by bulk liquid membrane (BLM) process using Aliquat 336 (QCl) as a carrier was investigated. The effects of several parameters on the extraction efficiency were studied in this research, such as the initial feed phase concentration (10-50) ppm of ACTP, stripping phase (NaCl) concentration (0.3,0.5,0.7 M), temperature (30-50^oC), the volume ratio of feed phase to membrane phase (200-400ml/80ml), agitation speed of the feed phase (75-125 rpm), membrane stirring speed (0, 100, 150 rpm), carrier concentration (1, 5, 9 wt%), the pH of feed (2, 4, 6, 8, 10), and solvent type (CCl₄ and n-Heptane). The study shows that high ext

The removal of COD from wastewater generated by petroleum refinery has been investigated by adopting electrocoagulation (EC) combined with adsorption using activated carbon (AC) derived from avocado seeds. The process variables influencing COD removal were studied: current density (2–10 mA/cm2), pH (4–9), and AC dosage (0.2–1 g/L). Response surface methodology (RSM) based on Box–Behnken design (BBD) was used to construct a mathematical model of the EC/AC process. Results showed that current density has the major effect on the COD removal with a percent of contribution 32.78% followed by pH while AC dosage has not a remarkable effect due to the good characteristics of AC derived from avocado seeds. Increasing current density gives be

The presence of dyes in wastewater has become a major issue all over the world. The discharge of dyes in the environment is concerned for both toxicological and esthetical reasons. In this study, the removal of dyes from aqueous solution by electrocoagulation using aluminum electrodes as cathode and anode were investigated with the electrocoagulation cell of 1litter. The study included: the impact of various operating parameters on the dyes removal efficiency like pH, NaCl concentration, distance between electrodes, voltage, initial dyes concentration and type of electrodes. The dye (congo red) concentrations were (50, 100, 150, and 200 ppm), stirring speed was 120 rpm at room temperature. pH used was maintained constant

The aim of present work is to improve mechanical and fatigue properties for Aluminum alloy7049 by using Nano composites technique. The ZrO₂ with an average grain diameter of 30-40 nm, was selected as Nano particles, to reinforce Aluminum alloy7049 with different percentage as, 2, 4, 6 and 7 %. The Stir casting method was used to fabricate the Nano composites materials due to economical route for improvement and processing of metal matrix composites. The experimental results were shown that the adding of zirconium oxide (ZrO₂) as reinforced material leads to improve mechanical properties. The best percentage of improvement of mechanical properties of 7049 AA was with 4% wt. of ZrO₂ about (7.76% ) for ultim

Each phenomenon contains several variables. Studying these variables, we find mathematical formula to get the joint distribution and the copula that are a useful and good tool to find the amount of correlation, where the survival function was used to measure the relationship of age with the level of cretonne in the remaining blood of the person. The Spss program was also used to extract the influencing variables from a group of variables using factor analysis and then using the Clayton copula function that is used to find the shared binary distributions using multivariate distributions, where the bivariate distribution was calculated, and then the survival function value was calculated for a sample size (50) drawn from Yarmouk Ho

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