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
Advanced strategies for production forecasting, operational optimization, and decision-making enhancement have been employed through reservoir management and machine learning (ML) techniques. A hybrid model is established to predict future gas output in a gas reservoir through historical production data, including reservoir pressure, cumulative gas production, and cumulative water production for 67 months. The procedure starts with data preprocessing and applies seasonal exponential smoothing (SES) to capture seasonality and trends in production data, while an Artificial Neural Network (ANN) captures complicated spatiotemporal connections. The history replication in the models is quantified for accuracy through metric keys such as m
... Show More
(1)
Background: The world is in front of two emerging problems being scarceness of virgin re-sources for bioactive materials and the gathering of waste production. Employment of the surplus waste in the mainstream production can resolve these problems. The current study aimed to prepare and characterize a natural composite CaO-SiO2 based bioactive material derived from naturally sustained raw materials. Then deposit this innovative novel bioactive coating composite materials overlying Yttria-stabilized tetragonal zirconia substrate. Mate-rials and method; Hen eggshell-derived calcium carbonate and rice husk-derived silica were extracted from natural resources to prepare the composite coating material. The manufac-tured powder was characterized
... Show More
(7)
(8)
Activated carbon derived from Ficus Binjamina agro-waste synthesized by pyro carbonic acid microwave method and treated with silicon oxide (SiO2) was used to enhance the adsorption capability of the malachite green (MG) dye. Three factors of concentration of dye, time of mixing, and the amount of activated carbon with four levels were used to investigate their effect on the MG removal efficiency. The results show that 0.4 g/L dosage, 80 mg/L dye concentration, and 40 min adsorption duration were found as an optimum conditions for 99.13% removal efficiency. The results also reveal that Freundlich isotherm and the pseudo-second-order kinetic models were the best models to describe the equilibrium adsorption data.
(5)
(3)
Date palm silver nanoparticles are a green synthesis method used as antibacterial agents. Today,
there is a considerable interest in it because it is safe, nontoxic, low costly and ecofriendly. Biofilm bacteria
existing in marketed local milk is at highly risk on population health and may be life-threatening as most
biofilm-forming bacteria are multidrug resistance. The goal of current study is to eradicate biofilm-forming
bacteria by alternative treatment green synthesis silver nanoparticles. The biofilm formation by bacterial
isolates was detected by Congo red method. The silver nanoparticles were prepared from date palm
(khestawy) fruit extract. The formed nanoparticles were characterized with UV-Vis
(15)
(3)
(136)
(116)
(12)
(11)
(8)
(8)
The current study used extracts from the aloe vera (AV) plant and the hibiscus sabdariffa flower to make Ag-ZnO nanoparticles (NPs) and Ag-ZnO nanocomposites (NCs). Ag/ZnO NCs were compared to Ag NPs and ZnO NPs. They exhibited unique properties against bacteria and fungi that aren't present in either of the individual parts. The Ag-ZnO NCs from AV showed the best performance against E. coli, with an inhibition zone of up to 27 mm, compared to the other samples. The maximum absorbance peaks were observed at 431 nm and 410 nm for Ag NPs, at 374 nm and 377 nm for ZnO NPs and at 384 nm and 391 nm for Ag-ZnO NCs using AV leaf extract and hibiscus sabdariffa flower extract, respectively. Using field emission-scanning electron microscopes (FE-
... Show More
(1)
ABSTRACT Background: Viral hepatitis places a heavy burden on the health care. Large number of patient with bleeding disorders has chronic hepatitis C infection, while few are chronic carriers of hepatitis B virus. Aims of study: evaluate the prevalence of HBV, HCV infection among patient with Von Willebrand disease and to find factors that associated with the chance of getting the infection.