There are many aims of this book: The first aim is to develop a model equation that describes the spread of contamination through soils which can be used to determine the rate of environmental contamination by estimate the concentration of heavy metals (HMs) in soil. The developed model equation can be considered as a good representation for a problem of environmental contamination. The second aim of this work is to design two feed forward neural networks (FFNN) as an alternative accurate technique to determine the rate of environmental contamination which can be used to solve the model equation. The first network is to simulate the soil parameters which can be used as input data in the second suggested network, while the second network simulates to estimate the concentration of heavy metals. The third aim is to develop a conceptual theory of training stage of neural networks from the perspective of functional analysis and optimization methods. Within this formulation, learning means to solve a variational problem by minimizing a performance function associated to the neural network. The choice of the objective functional depends on the particular application. On the other side, we suggest modification of the performance function to improve the generalization of the suggested networks and to treat the early stopping and local minima problems. The fourth aim is to compare the performance of aforementioned algorithms with regard to predicting ability. Then applied the suggested technique to estimate the concentration of heavy metals such as: Copper(Cu), Lead(Pb), Cadmium(Cd), Cobalt(Co), Zinc(Zn) and Nickel(Ni) in Baghdad soils. First, sixty four soil samples were selected from a phytoremediated contaminated site located in some zones in Baghdad city (residential, industrial, commercial, agricultural and main roads). Second, a series of measurements were performed on the soil samples and analyzed measuring of concentrations for heavy metals using devices such as : Atomic Absorption Spectrophotometer (AAS), X-Ray Fluorescence (XRF) and Inductively Coupled Plasma-Mass Spectrometry (ICP- MS) to get initial concentrations for those heavy metals. Third, simulate and train the suggested networks to get the concentration of heavy metals. The performance of the suggested networks was compared with the traditional laboratory inspecting using the training and test data sets. The results of this book show that the suggested networks trained on experimental measurements can be successfully applied to the rapid and accuracy estimation of concentration of heavy metals. Finally, we suggest some methods for the treatment of contaminated soil by using some herbal plants
Solvent- free thermal heating, one-pot condensation of acetophenone, ethyl cyanoacetate or malononitrle and substituted Aromatic aldehyde, ammonium acetate give, 2oxo-3-cyano-4-substituted Aryl-6-phenyl pyridine [I]a-h , or 2-amino-3-cyano-4-substituted Aryl-6-phenyl pyridine derivatives[II]a-f , respectively. Treatment of compounds 2-oxo-3-cyano-4-substituted Aryl-6-phenyl pyridine with phosphorous penta sulphide (P2S5), give 2-thioxo-3-cyano-4-substituted Aryl-6-phenyl pyridine derivatives[III]a-c . All prepared compounds
... Show MoreIn this work, a composite material was prepared from Low-density polyethylene (LDPE) with different weight percent of grain and calcinations kaolin at temperature of (850oC) using single screw extruder and a mixing machine operated at a temperature between (190-200oC). Some of mechanical and physical properties such as tensile strength, tensile strength at break, Young modulus, and elongation at break, shore hardness and water absorption were determined at different weight fraction of filler (0, 2, 7, 10 and 15%). It was found that the addition of filler increases the modulus of elasticity, elongation at break, shore hardness and impact strength; on other hand, it decreases the tensile strength and tensile strength
... Show MoreIn this paper, a cognitive system based on a nonlinear neural controller and intelligent algorithm that will guide an autonomous mobile robot during continuous path-tracking and navigate over solid obstacles with avoidance was proposed. The goal of the proposed structure is to plan and track the reference path equation for the autonomous mobile robot in the mining environment to avoid the obstacles and reach to the target position by using intelligent optimization algorithms. Particle Swarm Optimization (PSO) and Artificial Bee Colony (ABC) Algorithms are used to finding the solutions of the mobile robot navigation problems in the mine by searching the optimal paths and finding the reference path equation of the optimal
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We apply a semi classical partial-wave scattering method based on the induced density approach (IDA) model. For ion electron scattering, the transport cross section is used to calculate the energy loss. This method yields a non-perturbative exemplification of energy loss, bridging the difference among classical and quantal representations. The focus of this work is the interaction of hetero nuclear di-cluster (He-H) ions with a free gas. The results show three kinds of stopping power in (a.u) (cluster stopping power, self-stopping power and correlated stopping power) of hetero nuclear di-cluster ions (He-H) with velocity at different atomic di-cluster distances at different densities and temperatures. We find that Bragg’
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New Schiff base, namely [2-(carboxy methylene-amino)-phenyl imino] acetic acid (L) and its some metal complexes [LCo.2H2O], [LNi.2H2O], [LCu].3H2O, [LCd.2H2O], [LHg.2H2O] and [LPb.2H2O], were reported and characterized by elemental analysis, metal content, spectroscopic methods, magnetic moments and conductivity measurements, it is found that the geometrical structures of these complexes are octahedral [Co(II), Ni(II), Cd(II), Hg(II), Pb(II) and square planar Cu(II).The complexes have been found to posses 1:1 (M:L) stoichiometry
Diabetic nephropathy (DN) is the most common microvascular complication that may lead to chronic renal failure in diabetic patients. Till now microalbuminuria, with its restrictions, is the early marker of DN, appeared after the disease exacerbation. Thus, new biomarkers are required to predict the early onset of DN before the appearance of microalbuminuria. The aim of this study is to investigate the possible use of uVDBP in the early prediction of DN. Fifty diabetic patients with DN and 40 diabetic patients without DN for both types of diabetes were enrolled in this study. All patients were tested for uACR, uVDBP (measured by ELISA), and blood HbA1c. The results demonstrated a highly significant elevation of uAC
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Uropathogenic E. coli (UPEC) is problematic and still the leading cause of urinary tract infections worldwide. It is developed resistance against most antibiotics. The investigation, surveillance system, and efficient strategy will facilitate selecting an appropriate treatment that could control the bacterial distribution. The present study aims to investigate the epidemiology and associated risk factors of uropathogenic E. coli and to study their antibiotic resistance patterns. 1585 midstream urine specimens were collected from symptomatic urinary tract infections (UTI) patients (225 males and 1360 females) admitted to Zakho emergency hospital, Zakho, Kurdistan Region, Iraq from January 2016 until the end of December 2
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