This study includes applying chemical tests on cow, sheep and chicken bones including both hallow and flat. The results of chemical tests on bones mentioned the moisture percentage which was between 4.95-7.32 %, and it was noticed the difference in protein percentage among different kinds of bones, The highest protien percentage was 39.62 % in hallow chicken bones and the lowest was in hallow sheep bones 20.31%, at the same time, the highest Ash percentage was in hallow sheep bones48.11% , whereas the highest percentage of fat was in hallow cow bones 30%. The chemical and physical tests were conducted for extracted fat from hallow and flat bones for cows, sheeps and chicken. It was found that peroxide values (PV), and free fatty acids (FFA) tended to increase proportionally with extraction time at temperatures examined. The lowest values ware obtained after 3 hours as PVs were 0.93, 1.2, 1.0, 1.0, 1.33 and 1.46 meq/ kg oil respectively, FFA values were 0.15, 0.168, 0.187, 0.168, 0.206 and 0.225% respectively. The highest chemical indices for extracted fat from hallow and flat bones for cow and sheep was after 5 hours as PVs were 2.39, 1.8, 1.9, and 1.86 meq/ kg oil respectively, FFA values were 0.253, 0.300, 0.263 and 0.30% respectively. While, the highest chemical indices for extracted fat from hallow and flat chicken bones was after 4 hours, as PVs were 1.6 and 1.73 meq/ kg oil respectively, FFA values were 0.245 and 0.244% respectively. The obtained results showed values of smoking point tended to decrease proportionally as extraction time proceeding at different temperature used, highest values were recorded after extraction for 3 hours, smoking point values were 242.6, 231.33, 223.8, 217.66, 204.5and 204 °C respectively. The lowest physical values of fat extracted from hallow and flat bones of cow and sheep were obtained after 5 hours as the smoking point values were 230.33, 229.83, 203.4 and 204.83°C respectively. The lowest physical indices of fat extracted from hallow and flat chicken bones were obtained after 4 hours, as the smoking point values were 204 and 203.5 °C respectively.
The logistic regression model is an important statistical model showing the relationship between the binary variable and the explanatory variables. The large number of explanations that are usually used to illustrate the response led to the emergence of the problem of linear multiplicity between the explanatory variables that make estimating the parameters of the model not accurate.
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Background: Posterior superior alveolar artery (PSAA) is branch of the maxillary artery. It usually supplies the lateral wall of the sinus and overlying membrane. Evaluation and awareness of the anatomy of maxillary sinus before surgery is crucial to avoid surgical complications. The aim of this study is to examine the prevalence, location of the (PSAA) in relation to the floor of the maxillary sinus and alveolar crest using computerized tomography (CT) scans. Materials and Methods: This study included 180 Iraqi subjects (99 males and 81 females) with age more than 16 years old. CT scans for (right and left) Maxillary sinuses were done for each patient. The information obtained was assessed in a coronal multi planar reconstructions images (
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In this research, the one of the most important model and widely used in many and applications is linear mixed model, which widely used to analysis the longitudinal data that characterized by the repeated measures form .where estimating linear mixed model by using two methods (parametric and nonparametric) and used to estimate the conditional mean and marginal mean in linear mixed model ,A comparison between number of models is made to get the best model that will represent the mean wind speed in Iraq.The application is concerned with 8 meteorological stations in Iraq that we selected randomly and then we take a monthly data about wind speed over ten years Then average it over each month in corresponding year, so we g
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In this paper, Min-Max composition fuzzy relation equation are studied. This study is a generalization of the works of Ohsato and Sekigushi. The conditions for the existence of solutions are studied, then the resolution of equations is discussed.
This research deals with unusual approach for analyzing the Simple Linear Regression via Linear Programming by Two - phase method, which is known in Operations Research: “O.R.”. The estimation here is found by solving optimization problem when adding artificial variables: Ri. Another method to analyze the Simple Linear Regression is introduced in this research, where the conditional Median of (y) was taken under consideration by minimizing the Sum of Absolute Residuals instead of finding the conditional Mean of (y) which depends on minimizing the Sum of Squared Residuals, that is called: “Median Regression”. Also, an Iterative Reweighted Least Squared based on the Absolute Residuals as weights is performed here as another method to
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