In this work, substantial evidence was obtained for ligand reduction in cerium tetrakis acac complexes. Also, this ligand reduction of a negatively charged ligand proved to depend far less on the nature central metal than neutral ligands does. It is supposed that in Mz(acac)z complexes the charge is distributed evenly over the whole molecule. In this work these complexes were prepared and characterized by IR and CHN analysis to indicate the purities of these complexes. The electrochemistry techniques were shown as obtained for ligand reduction. This research was carried out at School of Chemistry and Molecular Science, Sussex University, U.K.

   Singled current study on the subject of shorthand in structure designs logos (Iraqi sports clubs model), as the current study Tdmt four chapters, was in the first chapter defines the research problem and its significance, as well as the aim of the research in the know shorthand formal in structure designs logos (Iraqi sports clubs model ), and identifies Find time limits: - slogans Iraqi sports clubs for the years (1956 - 1970), because it represented the years to include designs slogans official Iraqi sports clubs that have been elected in this period for the purpose of examining the reality of the design in the current search. And it represented the spatial limits: - the Republic of Iraq - Iraqi slogans designs sports

This study was conducted in the field of the Poultry Research Station of the animal resources Department / office of Agricultural Research / Ministry of Agriculture from the period 4th April to16th May2021.This study was aimed to investigate the effect of using avocado and chia oil and their mixture in broiler diets on the final productive performance and meat cholesterol concentration and measuring meat oxidation indicators after storing it for 60 days. 300 one-day-old (Ross308) chicks were fed on diets that used avocado oil and chia with percentages of 0, 0.2, 0.4, 0.6%, respectively, and their mixture consisting of 0.0, 0.1, 0.2, 0.3 each of avocado and chia oil (50% avocado + 50% chia oil). The experiment included 10 treatments

This paper describes a new proposed structure of the Proportional Integral Derivative (PID) controller based on modified Elman neural network for the DC-DC buck converter system which is used in battery operation of the portable devices. The Dolphin Echolocation Optimization (DEO) algorithm is considered as a perfect on-line tuning technique therefore, it was used for tuning and obtaining the parameters of the modified Elman neural-PID controller to avoid the local minimum problem during learning the proposed controller. Simulation results show that the best weight parameters of the proposed controller, which are taken from the DEO, lead to find the best action and unsaturated state that will stabilize the Buck converter system performan

Wireless Multimedia Sensor Networks (WMSNs) are a type of sensor network that contains sensor nodes equipped with cameras, microphones; therefore the WMSNS are able to   produce multimedia data such as video and audio streams, still images, and scalar data from the surrounding environment. Most multimedia applications typically produce huge volumes of data, this leads to congestion. To address this challenge, This paper proposes Modify Spike Neural Network control for Traffic Load Parameter with Exponential Weight of Priority Based Rate Control algorithm (MSNTLP with EWBPRC). The Modify Spike Neural Network controller (MSNC) can calculate the appropriate traffi

This paper presents a comparative study of two learning algorithms for the nonlinear PID neural trajectory tracking controller for mobile robot in order to follow a pre-defined path. As simple and fast tuning technique, genetic and particle swarm optimization algorithms are used to tune the nonlinear PID neural controller's parameters to find the best velocities control actions of the right wheel and left wheel for the real mobile robot. Polywog wavelet activation function is used in the structure of the nonlinear PID neural controller. Simulation results (Matlab) and experimental work (LabVIEW) show that the proposed nonlinear PID controller with PSO
learning algorithm is more effective and robust than genetic learning algorithm; thi

Precise forecasting of pore pressures is crucial for efficiently planning and drilling oil and gas wells. It reduces expenses and saves time while preventing drilling complications. Since direct measurement of pore pressure in wellbores is costly and time-intensive, the ability to estimate it using empirical or machine learning models is beneficial. The present study aims to predict pore pressure using artificial neural network. The building and testing of artificial neural network are based on the data from five oil fields and several formations. The artificial neural network model is built using a measured dataset consisting of 77 data points of Pore pressure obtained from the modular formation dynamics tester. The input variables

New nanotechnology-based approaches are increasingly being investigated for enhanced oil recovery (EOR), with a particular focus on heavy oil reservoirs. Typically, the addition of a polymer to an injection fluid advances the sweep efficiency and mobility ratio of the fluid and leads to a higher crude oil recovery rate. However, harsh reservoir conditions, including high formation salinity and temperature, can limit the performance of such polymer fluids. Recently, nanofluids, that is, dispersions of nanoparticles (NPs) in a base fluid, have been recommended as EOR fluids; however, such nanofluids are unstable, even under ambient conditions. In this work, a combination of ZrO2 NPs and the polyacrylamide (PAM) polymer (ZrO2 NPs–PAM) was us