To test the effect of 4 levels of nitrogen (i.e. 0, 45, 90 and 135 Kg N ha^-1) as urea (46% N) and 3 levels of phosphorus (i.e. 0, 17.5 and 35 Kg P ha^-1) as triple superphosphate (21.8% P) on yield and concentration of dill (Anethum graveolens L. local cultivar) seed oil this experiment was carried out during winter season of 1999 - 2000 at the experimental field of Agriculture College, Abu-Ghraib.

 Both fertilizers were applied in two equal splits, first at seeds sowing and the second was added one month after emergence. Dried and ground seed samples were subjected to water distillation for extraction of volatile oils

 Result indicated that fertilization of dill plants with 90 Kg N

The specifications of lubricating oil are fundamentally the final product of materials that have been added for producing the desired properties. In this research, spherical nanoparticles copper oxide (CuO) and titanium oxides (TiO₂) are added to SAE 15W40 engine oil to study the thermal conductivity, stability, viscosity of nano-lubricants, which are prepared at different concentrations of 0.1%, 0.2%, 0.5%, and 1% by weight, and also their pour point, and flash point as five quality parameters. The obtained results show that CuO nanoparticles in all cases, give the best functionality and effect on engine oil with respect to TiO₂. With 0.1 wt. % concentration, the thermal conductivity of CuO/oil and TiO₂/

Effect of copper doping and thermal annealing on the structural and optical properties of Zn0.5Cd0.5S thin films prepared by chemical spray pyrolysis have been studied. Depositions were done at 250°C on glass substrate. The structural properties and surface morphology of deposited films were studied using X-ray diffraction (XRD) and photomicroscope (PHM) techniques. XRD studies reveal that all films are crystalline tetragonal structure. The film crystallinity are increased with 1% Cu-doping concentration and also increased for the films annealed at 300°C than the other studied cases. The lattice constant 'a' and 'c' varies with doping concentrations from 5.487Å to 5.427Å and 10.871Å to 10.757Å respectively. The grain size attained

Background: The goal of a root canal treatment is three dimensional obturation with a complete seal of the root canal system. The aim of this study was to evaluate and compare the effect of two warm obturation techniques, warm vertical compaction (WVC) and, carrier based obturation technique Gutta Core (GC), versus two cold obturation techniques, cold lateral compaction (CLC) and, single cone (SC) on push-out bond strength of bioceramic sealer (Total Fill) at three different root levels. Materials and Methods: Forty extracted maxillary first molars teeth with a straight round palatal root canal and mature apices were selected for this study. After sectioning the palatal roots to 11 mm from the root apex, the canals were prepared wit

Background: The goal of a root canal treatment is three dimensional obturation with a complete seal of the root canal system. The aim of this study was to evaluate and compare the effect of two warm obturation techniques, warm vertical compaction (WVC) and, carrier based obturation technique Gutta Core (GC), versus two cold obturation techniques, cold lateral compaction (CLC) and, single cone (SC) on push-out bond strength of bioceramic sealer (Total Fill) at three different root levels. Materials and Methods: Forty extracted maxillary first molars teeth with a straight round palatal root canal and mature apices were selected for this study. After sectioning the palatal roots to 11 mm from the root apex, the canals were

Novel artificial neural network (ANN) model was constructed for calibration of a multivariate model for simultaneously quantitative analysis of the quaternary mixture composed of carbamazepine, carvedilol, diazepam, and furosemide. An eighty-four mixing formula where prepared and analyzed spectrophotometrically. Each analyte was formulated in six samples at different concentrations thus twentyfour samples for the four analytes were tested. A neural network of 10 hidden neurons was capable to fit data 100%. The suggested model can be applied for the quantitative chemical analysis for the proposed quaternary mixture.

A Novel artificial neural network (ANN) model was constructed for calibration of a multivariate model for simultaneously quantitative analysis of the quaternary mixture composed of carbamazepine, carvedilol, diazepam, and furosemide. An eighty-four mixing formula where prepared and analyzed spectrophotometrically. Each analyte was formulated in six samples at different concentrations thus twenty four samples for the four analytes were tested. A neural network of 10 hidden neurons was capable to fit data 100%. The suggested model can be applied for the quantitative chemical analysis for the proposed quaternary mixture.

This study uses an Artificial Neural Network (ANN) to examine the constitutive relationships of the Glass Fiber Reinforced Polymer (GFRP) residual tensile strength at elevated temperatures. The objective is to develop an effective model and establish fire performance criteria for concrete structures in fire scenarios. Multilayer networks that employ reactive error distribution approaches can determine the residual tensile strength of GFRP using six input parameters, in contrast to previous mathematical models that utilized one or two inputs while disregarding the others. Multilayered networks employing reactive error distribution technology assign weights to each variable influencing the residual tensile strength of GFRP. Temperatur