new six mixed ligand complexes of some transition metal ions Manganese (II), Cobalt(II), Iron (II), Nickel (II) , and non transition metal ion zinc (II) And Cadmium(II) with L-valine (Val H ) as a primary ligand and Saccharin (HSac) as a secondary ligands have been prepared. All the prepared complexes have been characterized by molar conductance, magnetic susceptibility infrared, electronic spectral, Elemental microanalysis (C.H.N) and AA . The complexes with the formulas [M(Val)2(HSac)2] M= Mn (II) , Fe (II) , Co(II) ,Ni(II), Cu (II),Zn(II) and Cd(II) L- Val H= (C5H11NO2) , C7H5NO3S The study shows that these complexes have octahedral geometry; The metal complexes have been screened for their in microbiological activities against bacteria.

In this work , the ligand [N-(4-Methoxybenzoyl amino)-thioxomethyl] Methionine acid  has been synthesized by the reaction of 4- Methoxybenzoyl isothiocyanate with methionine acid . The metal complexes were prepared through the reaction of metals chlorides of Co(II) , Ni(II), Cu(II), Zn(II) and Cd(II) in ethanol as solvent . The ligand (MbM) and its metal complexes have been characterized by elemental analysis (CHNS), IR, 1H-13CNMR and UV- Vis spectra, magnetic susceptibility measurements, molar conductivity, melting points and atomic absorption. The metal-ligand ratio was determined by mole ratio method. The suggested structures for the Co(II), Ni(II), Cd(II) and Zn(II) complexes are tetrahedral geometry and  the Cu(II) complex

The present study aims to establish an empirical correlation between biochemical oxygen demand (BOD5) and chemical oxygen demand (COD) of the sewage flowing in Al-Diwaniyah wastewater treatment plant. The strength of the wastewater entering the plant varied from medium to high. High concentrations of BOD5 and COD in the effluent were obtained due to the poor performance of the plant. This was observed from the BOD5 /COD ratios that did not confirm with the typical ratios for the treated sewage. Regression equations for BOD5 and COD removal percentages were suggested which can be used to evaluate rapid effluent assessment after the treatment processes or optimal process control to improve the performance of wastewater treatment plants.

In this paper, we consider a new approach to solve type of partial differential equation by using coupled Laplace transformation with decomposition method to find the exact solution for non–linear non–homogenous equation with initial conditions. The reliability for suggested approach illustrated by solving model equations such as second order linear and nonlinear Klein–Gordon equation. The application results show the efficiency and ability for suggested approach.

 

    The combination of wavelet theory and neural networks has lead to the development of wavelet networks. Wavelet networks are feed-forward neural networks using wavelets as activation function. Wavelets networks have been used in classification and identification problems with some success.

  In this work we proposed a fuzzy wavenet network (FWN), which learns by common back-propagation algorithm to classify medical images. The library of medical image has been analyzed, first. Second, Two experimental tables’ rules provide an excellent opportunity to test the ability of fuzzy wavenet network due to the high level of information variability often experienced with this type of images.

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PC-based controller is an approach to control systems with Real-Time parameters by controlling selected manipulating variable to accomplish the objectives. Shell and tube heat exchanger have been identified as process models that are inherently nonlinear and hard to control due to unavailability of the exact models’ descriptions. PC and analogue input output card will be used as the controller that controls the heat exchanger hot stream to the desired temperature.
The control methodology by using four speed pump as manipulating variable to control the temperature of the hot stream to cool to the desired temperature.
In this work, the dynamics of cross flow shell and tube heat exchanger is modeled from step changes in cold water f

Acute lymphoblastic leukemia (ALL) is one of the most common diseases , so in this study the serum level of malondialdehyde and its relationship with metanephrine was investigated in acute lymphoblastic leukemia patients over one month of treatment. Some biochemical parameters (serum glucose , total serum protein , malondialdehyde ,vitamin C, and metanephrine) changed as well as white blood cell count and blood hemoglobinlevelswere analyzed in sixty patients diagnosed with acute lymphoblastic leukemia over one month of treatment compared to healthy control group.Statistically significant increases (p<0.01) in white blood cell (WBC) count, mean concentrations of malondialdehyde (MDA) (p< 0.05) and metanephrine (p< 0.001) were observed in

Binuclear copper, nickel, cobalt, manganese and mercury complexes of the Schiff base H2L (C40H28N2O4) obtained by condensation of 2-benzoyl benzoic acid with benzidine.  The Schiff base and their complexes have been subjected to[ FT-IR, elemental analysis ,UV-Vis, 1H and 13C NMR ] spectral studies, molar conductivity, magnetic moment and HPLC measurements. All the complexes showed tetrahedral geometries with the general structure [M2(L)2].  Generality of the synthesized components offer antibacterial efficiency to (Staphylococcu saureus), (Escherichia coli),(Bacillus subtilis) and(Pseudomonas aeruginosa).
 

In this paper, integrated quantum neural network (QNN), which is a class of feedforward

neural networks (FFNN’s), is performed through emerging quantum computing (QC) with artificial neural network(ANN) classifier. It is used in data classification technique, and here iris flower data is used as a classification signals. For this purpose independent component analysis (ICA) is used as a feature extraction technique after normalization of these signals, the architecture of (QNN’s) has inherently built in fuzzy, hidden units of these networks (QNN’s) to develop quantized representations of sample information provided by the training data set in various graded levels of certainty. Experimental results presented here show that

Ghrelin and leptin are hunger hormones related to type 2 diabetes mellitus (T2DM), and the pathogenesis of T2DM is the abnormality in insulin secretion and insulin resistance (IR). The aim of this study is to evaluate ghrelin and leptin concentrations in blood and to specify the relationship of these hormones as dependent variables with some biochemical and clinical measurements in T2DM patients. In this study, forty one T2DM and forty three non-diabetes mellitus (non-DM) subjects, aged between 40-60 years and with normal weight, were enrolled. Fasting serum ghrelin and leptin were estimated by enzyme-linked immunosorbent assay (ELISA). In our results ghrelin was significantly increased, and leptin was significantly decreased, in T2DM pa