The aim of this study is to know the effect of different percentages of chitosan added to drinking water on the weight and quality of quail meat, physical anatomy in terms of (the body of the long carcass, the girth of the chest, the length of the thigh bones, the thigh racket, the fullness of the chest), chemical analysis (protein, moisture, fat and ash) and sensory evaluation of quail meat. It was purchased 320 Iraqi-origin birds of quail and one day old. Chicks were randomly distributed to three equal groups' treatments and treated with chitosan and added to the drinking water: the first treatment (0.1 gm./L water only as a control treatment), the second treatment (0.2 gm./L of chitosan was added to the drinking water) and the

With its rapid spread, the coronavirus infection shocked the world and had a huge effect on billions of peoples' lives. The problem is to find a safe method to diagnose the infections with fewer casualties. It has been shown that X-Ray images are an important method for the identification, quantification, and monitoring of diseases. Deep learning algorithms can be utilized to help analyze potentially huge numbers of X-Ray examinations. This research conducted a retrospective multi-test analysis system to detect suspicious COVID-19 performance, and use of chest X-Ray features to assess the progress of the illness in each patient, resulting in a "corona score." where the results were satisfactory compared to the benchmarked techniques.  T

Many biological tests were done to study the effect of the crude alcoholic leaves extracts on the biological characteristics at the larvae fruit fly Ceratitis capitata with different concentrations of the extracts exposed 1,2,3,5 and 7.5 % at constant laboratory conditions includes the temperature and the relative humidity (27±2C0&70±5 % respectively). The results of the experiments showed that the alcoholic extracts of the plant effected the growth and the development of the larvae and pupae according to the concentrations . The alcoholic extracts proved to have the highest mortality tend to 66.76 % in larva treated with alcoholic at concentration 7.5 % the

          A histological study showed the wall of the stomach in Pica pica and Herpestes javanicus consists of four layers: mucosa, submucosa, muscularis externa and serosa. Also, the present study showed many  differences in the histological structures of the stomach for each in both types. The stomach of P. pica consists of two portions: the proventiculus and gizzard, while the stomach of H. javanicus consists of three portions: cardiac, fundic and pyloric regions. The mucosa layer formed short gastric folds, named plicae. In the proventiculus of P. pica, sulcus is found between each two plicae, but the folds called gastric pits in the gizzard, which are full with koilin. Lamina properia in both types contained gastric g

          A histological study showed the wall of the stomach in Pica pica and Herpestes javanicus consists of four layers: mucosa, submucosa, muscularis externa and serosa. Also, the present study showed many  differences in the histological structures of the stomach for each in both types. The stomach of P. pica consists of two portions: the proventiculus and gizzard, while the stomach of H. javanicus consists of three portions: cardiac, fundic and pyloric regions. The mucosa layer formed short gastric folds, named plicae. In the proventiculus of P. pica, sulcus is found between each two plicae, but the folds called gastric p

Several correlations have been proposed for bubble point pressure, however, the correlations could not predict bubble point pressure accurately over the wide range of operating conditions. This study presents Artificial Neural Network (ANN) model for predicting the bubble point pressure especially for oil fields in Iraq. The most affecting parameters were used as the input layer to the network. Those were reservoir temperature, oil gravity, solution gas-oil ratio and gas relative density. The model was developed using 104 real data points collected from Iraqi reservoirs. The data was divided into two groups: the first was used to train the ANN model, and the second was used to test the model to evaluate their accuracy and trend stability