Toxic substances have been released into water supplies in recent decades because of fast industrialization and population growth. Fenton electrochemical process has been addressed to treat wastewater which is very popular because of its high efficiency and straightforward design. One of the advanced oxidation processes (AOPs) is electro-Fenton (EF) process, and electrode material significantly affects its performance. Nickel foam was chosen as the source of electro-generated hydrogen peroxide (H2O2) due to its good characteristics. In the present study, the main goals were to explore the effects of operation parameters (FeSO4 concentration, current density, and electrolysis time) on the catalytic performance that was optimized by r

    In this research, CNRs have been synthesized using pyrolysis of plastic waste(pp) at 1000 ° C for one hour in a closed reactor made from stainless steel, using magnesium oxide (MgO) as a catalyst. The resultant carbon nano rods were purified and characterized using energy dispersive X-ray spectroscopy (EDX), X-ray powder diffraction (XRD). The surface characteristics of carbon rods were observed with the Field emission scanning electron microscopy (FESEM). The carbon was evenly spread and had the highest concentration from SEM-EDX characterization. The results of XRD and FESEM have shown that carbon Nano rods (CNRs) were present in Nano figures, synthesized at 1000 ° C and with pyrolysis temperature 400° C. One of t

The emergence of SARS-CoV-2, the virus responsible for the COVID-19 pandemic, has resulted in a global health crisis leading to widespread illness, death, and daily life disruptions. Having a vaccine for COVID-19 is crucial to controlling the spread of the virus which will help to end the pandemic and restore normalcy to society. Messenger RNA (mRNA) molecules vaccine has led the way as the swift vaccine candidate for COVID-19, but it faces key probable restrictions including spontaneous deterioration. To address mRNA degradation issues, Stanford University academics and the Eterna community sponsored a Kaggle competition.This study aims to build a deep learning (DL) model which will predict deterioration rates at each base of the mRNA

The study aims to predict Total Dissolved Solids (TDS) as a water quality indicator parameter at spatial and temporal distribution of the Tigris River, Iraq by using Artificial Neural Network (ANN) model. This study was conducted on this river between Mosul and Amarah in Iraq on five positions stretching along the river for the period from 2001to 2011. In the ANNs model calibration, a computer program of multiple linear regressions is used to obtain a set of coefficient for a linear model. The input parameters of the ANNs model were the discharge of the Tigris River, the year, the month and the distance of the sampling stations from upstream of the river. The sensitivity analysis indicated that the distance and discharge

Survival analysis is widely applied to data that described by the length of time until the occurrence of an event under interest such as death or other important events. The purpose of this paper is to use the dynamic methodology which provides a flexible method, especially in the analysis of discrete survival time, to estimate the effect of covariate variables through time in the survival analysis on dialysis patients with kidney failure until death occurs. Where the estimations process is completely based on the Bayes approach by using two estimation methods: the maximum A Posterior (MAP) involved with Iteratively Weighted Kalman Filter Smoothing (IWKFS) and in combination with the Expectation Maximization (EM) algorithm. While the other

         International companies are striving to reduce their costs and increase their profits, and these trends have produced many methods and techniques to achieve these goals. these methods is heuristic and the other Optimization.. The research includes an attempt to adapt some of these techniques in the Iraqi companies, and these techniques are to determine the optimal lot size using the algorithms Wagner-Whitin under the theory of constraints. The research adopted the case study methodology to objectively identify the problem of research, namely determining lot size optimal for each of the products of electronic measurement laboratory in Diyala and in light of the bottlenecks in w

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Future generations of wireless networks are expected to heavily rely on unmanned aerial vehicles (UAVs). UAV networks have extraordinary features like high mobility, frequent topology change, tolerance to link failure, and extending the coverage area by adding external UAVs. UAV network provides several advantages for civilian, commercial, search and rescue applications. A realistic mobility model must be used to assess the dependability and effectiveness of UAV protocols and algorithms.  In this research paper, the performance of the Gauss Markov (GM) and Random Waypoint (RWP) mobility models in multi-UAV networks for a search and rescue scenario is analyzed and evaluated. Additionally, the two mobility models GM and RWP are descr

  This study  focused on a fundamental issue which was represented by ability of Iraqi central bank in facing the difficulty of determining  the optimal ratio of liquidity in the Iraqi banks in terms of the balancing between its obligations to the depositors and borrowers, and liquidate their funds on one hand and the risks on the other hand.the search aimed  for achieving the goals which represented by identifying the possibility of Iraqi banks to apply the regulations rules and  instructions  issued by central bank  of  Iraq in determining  ratio  of  liquidity and  its  appropriate with Iraqi  banks  action to implement  a  reasonable  profit to&

In the petroleum industry, multiphase flow dynamics within the tubing string have gained significant attention due to associated challenges. Accurately predicting pressure drops and wellbore pressures is crucial for the effective modeling of vertical lift performance (VLP). This study focuses on predicting the multiphase flow behavior in four wells located in the Faihaa oil field in southern Iraq, utilizing PIPESIM software. The process of selecting the most appropriate multiphase correlation was performed by utilizing production test data to construct a comprehensive survey data catalog. Subsequently, the results were compared with the correlations available within the PIPESIM software. The outcomes reveal that the Hagedorn and Brown (H