The present work aimed to study the efficiency of nanofiltration (NF) and reverse osmosis (RO) process for water recovery from electroplating wastewater and study the factors affecting the performance of two membrane processes. Nanofiltration and reverse osmosis membranes are made from polyamide as spiral wound module. The inorganic materials ZnCl2, CuCl2.2H2O, NiCl2.6H2O and CrCl3.6H2O were used as feed solutions. The operating parameters studied were: operating time, feed concentrations for heavy metal ions, operating pressure, feed flow rate, feed temperature and feed pH. The experimental results showed, the permeate concentration increased and water flux decreased with increase in time from 0 to 70 min. The permeate concentrations incre

The university Service employee is considered one of the categories of public employees, However, The academic and administrative tasks duties that undertakes have made him a special importance and a distinguished legal status, Therefore, we find That the Iraqi legislatures assigned this category a special Law, it is the university Service law No (23) of 2008 as amended who dealt with some aspects related to serving this category, such as duties, right, condition for appointment and award of academic titles, and financial allocation, such as university service allocation, academic title allocations, and some other Provisions leaving other matters to the general service laws and employee discipline, among the matters that the legislator negl

Many academics have concentrated on applying machine learning to retrieve information from databases to enable researchers to perform better. A difficult issue in prediction models is the selection of practical strategies that yield satisfactory forecast accuracy. Traditional software testing techniques have been extended to testing machine learning systems; however, they are insufficient for the latter because of the diversity of problems that machine learning systems create. Hence, the proposed methodologies were used to predict flight prices. A variety of artificial intelligence algorithms are used to attain the required, such as Bayesian modeling techniques such as Stochastic Gradient Descent (SGD), Adaptive boosting (ADA), Decision Tre

Many academics have concentrated on applying machine learning to retrieve information from databases to enable researchers to perform better. A difficult issue in prediction models is the selection of practical strategies that yield satisfactory forecast accuracy. Traditional software testing techniques have been extended to testing machine learning systems; however, they are insufficient for the latter because of the diversity of problems that machine learning systems create. Hence, the proposed methodologies were used to predict flight prices. A variety of artificial intelligence algorithms are used to attain the required, such as Bayesian modeling techniques such as Stochastic Gradient Descent (SGD), Adaptive boosting (ADA), Deci

This study seeks to identify the role that the leadership trend plays in the management of health institutions in Iraq and its impact on improving the quality of the health service provided by analyzing some opinions of affiliates working in the Iraqi health sector where a survey list was used as a main tool for collecting primary data, as it was subjected to this analysis ( 60) of the medical staff, of whom (40) are doctors and (20) are affiliated with the rank of assistant physician, and (60) members of the administrative cadre have undergone their various job ranks and administrative specializations (department manager, auditor, observer, accountant, statistician, secretary). Reliance on statistical software (spss) in data ana

The effluent quality improvement being discharged from wastewater treatment plants is essential to maintain an environment and healthy water resources. This study was carried out to evaluate the possibility of intermittent slow sand filtration as a promising tertiary treatment method for the sequencing batch reactor (SBR) effluent. Laboratory scale slow sand filter (SSF) of 1.5 UC and 0.1 m/h filtration rate, was used to study the process performance. It was found that SSF IS very efficient in oxidizing organic matter with COD removal efficiency up to 95%, also it is capable of removing considerable amounts of phosphate with 76% and turbidity with 87% removal efficiencies. Slow sand filter efficiently reduced the mass of suspended

Artificial Neural Network (ANN) model's application is widely increased for wastewater treatment plant (WWTP) variables prediction and forecasting which can enable the operators to take appropriate action and maintaining the norms. It is much easier modeling tool for dealing with complex nature WWTP modeling comparing with other traditional mathematical models. ANN technique significance has been considered at present study for the prediction of sequencing batch reactor (SBR) performance based on effluent's (BOD5/COD) ratio after collecting the required historical daily SBR data for two years operation (2015-2016) from Baghdad Mayoralty and Al-Rustamiya WWTP office, Iraq. The prediction was gotten by the application of a feed-forwa

Objective: Loranthus europaeus is a parasitic plant that lives on the branches of trees. The present study aimed to evaluate the anti-inflammatory effects of two different extracts on chronic inflammation induced by cotton pellets in rats. Methods: Loranthus seed was extracted by maceration with absolute methanol, in which dry Loranthus seeds were triturated in a mortar and macerated with 500 mL of methanol. After 24 h, the mixture was filtered, and the residue was re-extracted. The filtrates were combined and dried under vacuum. The mixture was mixed with 100 mL of distilled water and fractionated by petroleum ether and ethyl acetate using 70 mL × 3 times each. The organic fractions were dried, filtered, and evaporated to dryness.