We studied the effect of certain environmental conditions for removing heavy metal elements from contaminated aqueous solutions (Cd, Cu, Pb, Fe, Zn, Ni, Cr) using the bacterium Bacillus subtilis to appoint the optimal conditions for removal ,The best optimum temperature range for two isolate was 30-35○C while the hydrogen number for the maximum mineral removal range was 6-7. The best primary mineral removal was 100 mg/L, while the maximum removal for all minerals was obtained after 6 hrs of Cu element time and the maximum removal efficiency was obtained after 24 hrs of Cu element. The results have proved that the best aeration for maximum removal was obtained at rotation speed of 150 rpm/minute. Inoculums of 5ml/100ml which contained 1

A new Schiff base (4-chlorophenyl)(phenyl methanimine (6R,7R)-3-methyl-8-oxo-7-(2-phenylpropanamido)-5-thia-1-azabicyclo[4.2.0]oct-2-ene-2-carboxylate=HL=C29H24ClN3O4S) has been synthesized from β-lactam antibiotic (cephalexin mono hydrate (CephH)=(C16H19N3O5S.H2O) and 4- chlorobenzophenone. Metal mixed ligand complexes of the Schiff base were prepared from chloride salt of Fe(II), Co(II), Ni(II), Cu(II), Zn(II) and Cd(II), in 50% (v/v) ethanol – water medium in aqueous ethanol(1:1) and Saccharin(C7H5NO3S) containing sodium hydroxide. Several physical tools in particular; IR, C:H:N , 1H NMR,13C NMR for ligand, melting point, molar conductance, magnetic moment. and determination of the percentage of the metal in the complexes by flame(AAS

new Schiff base 4-chlorophenyl)methanimine (6R,7R)-3-methyl-8-oxo-7-(2-phenylpropanamido)-5-thia-1-azabicyclo[4.2.0]oct-2-ene-2-carboxylate= (HL)= C23H20 ClN3O4S) has been synthesized from β-lactam antibiotic (cephalexin mono hydrate(CephH)=(C16H19N3O5S.H2O) and 4-chlorobenzaldehyde . Figure(1) Metal mixed ligand complexes of the Schiff base were prepared from chloride salt of Fe(II),Co(II),Ni(II),Cu(II),Zn(II) and Cd (II), in 50% (v/v) ethanol –water medium (SacH ) .in aqueous ethanol(1:1) containing and Saccharin(C7H5NO3S) = sodium hydroxide. Several physical tools in particular; IR, CHN, 1H NMR, 13C NMR for ligand and melting point molar conductance, magnetic moment. and determination the percentage of the metal in the complexes by fl

This experiment was carried out at the Field of Poultry, Department of Animal Resources, College of Agriculture, University of Baghdad, during the period from 1/5/2011 until 5/7/2011 to study the effect of adding arginine to laying hens diet on certain blood traits. A total of 100 Brown Lohmann laying hen chickens, 38 weeks of age, were randomly distributed into four treatment groups, with 25 hens for each treatment. Treatment groups were: T1: bird-fed diet with no additional arginine (control group); T2, T3, and T4: bird-fed diet supplemented with 0.4, 0.7, and 0.9%, respectively. Therefore, the total amounts of arginine in the four treatments (T1, T2, T3, and T4) become 1.1, 1.5, 1.8, and 2.0%, respectively. Results of this experiment rev

The objectives of this study were to review the literature covering the perceptions about influenza vaccines in the Middle East and to determine factors influencing the acceptance of vaccination using Health Belief Model (HBM).

The objectives of this study were to review the literature covering the perceptions about influenza vaccines in the Middle East and to determine factors influencing the acceptance of vaccination using Health Belief Model (HBM).

In recent years, Bitcoin has become the most widely used blockchain platform in business and finance. The goal of this work is to find a viable prediction model that incorporates and perhaps improves on a combination of available models. Among the techniques utilized in this paper are exponential smoothing, ARIMA, artificial neural networks (ANNs) models, and prediction combination models. The study's most obvious discovery is that artificial intelligence models improve the results of compound prediction models. The second key discovery was that a strong combination forecasting model that responds to the multiple fluctuations that occur in the bitcoin time series and Error improvement should be used. Based on the results, the prediction acc

. In recent years, Bitcoin has become the most widely used blockchain platform in business and finance. The goal of this work is to find a viable prediction model that incorporates and perhaps improves on a combination of available models. Among the techniques utilized in this paper are exponential smoothing, ARIMA, artificial neural networks (ANNs) models, and prediction combination models. The study's most obvious discovery is that artificial intelligence models improve the results of compound prediction models. The second key discovery was that a strong combination forecasting model that responds to the multiple fluctuations that occur in the bitcoin time series and Error improvement should be used. Based on the results, the prediction a

This study had succeeded in producing a new graphical representation of James abacus called nested chain abacus. Nested chain abacus provides a unique mathematical expression to encode each tile (image) using a partition theory where each form or shape of tile will be associated with exactly one partition.Furthermore, an algorithm of nested chain abacus movement will be constructed, which can be applied in tiling theory.