Wastewater projects are one of the most important infrastructure projects, which require developing strategic plans to manage these projects. Most of the wastewater projects in Iraq don’t have a maintenance plan. This research aims to prepare the maintenance management plan (MMP) for wastewater projects. The objective of the research is to predict the cost and time of maintenance projects by building a model using ANN. The research sample included (15) completed projects in Wasit Governorate, where the researcher was able to obtain the data of these projects through the historical information of the Wasit Sewage Directorate. In this research artificial neural networks (ANN) technique was used to build two models (cost

The research focuses on determination of best location of high elevated tank using the required head of pump as a measure for this purpose. Five types of network were used to find the effect of the variation in the discharge and the node elevation on the best location. The most weakness point was determined for each network. Preliminary tank locations were chosen for test along the primary pipe with same interval distance. For each location, the water elevation in tank and pump head was calculated at each hour depending on the pump head that required to achieve the minimum pressure at the most weakness point. Then, the sum of pump heads through the day was determined. The results proved that there is a most economical lo

The convolutional neural networks (CNN) are among the most utilized neural networks in various applications, including deep learning. In recent years, the continuing extension of CNN into increasingly complicated domains has made its training process more difficult. Thus, researchers adopted optimized hybrid algorithms to address this problem. In this work, a novel chaotic black hole algorithm-based approach was created for the training of CNN to optimize its performance via avoidance of entrapment in the local minima. The logistic chaotic map was used to initialize the population instead of using the uniform distribution. The proposed training algorithm was developed based on a specific benchmark problem for optical character recog

Epithelial mesenchymal transition (EMT) is a process comprising cellular and molecular events which result in cells shifting from an epithelial to a mesenchymal phenotype. Periodontitis is a destructive chronic disease of the periodontium initiated in response to a dysbiotic microbiome, and dominated by Gram-negative bacteria in the subgingival niches accompanied by an aberrant immune response in susceptible subjects. Both EMT and periodontitis share common risk factors and drivers, including Gram-negative bacteria, excess inflammatory cytokine production, smoking, oxidative stress and diabetes mellitus. In addition, periodontitis is characterized by down-regulation of key epithelial markers such as E-cadherin together with up-regulation of

A UV-Vis spectrophotometry method was developed for the determination of metoclopramide hydrochloride in pure and several pharmaceutical preparations, such as Permosan tablets, Meclodin syrups, and Plasil ampoules. The method is based on the diazotization reaction of metoclopramide hydrochloride with sodium nitrate and hydrochloric acid to yield the diazonium salt, which is then reacted with 3,5-dimethyl phenol in the presence of sodium hydroxide to form a yellow azo dye. Calibration curves were linear in the range from 0.3 to 6.5 µg/mL, with a correlation coefficient of 0.9993. The limits of detection and quantification were determined and found to be 0.18 and 0.61 µg/mL, respectively. Accuracy and precision were also determined b