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.
Water quality planning relies on Biochemical Oxygen Demand BOD. BOD testing takes five days. The Particle Swarm Optimization (PSO) is increasingly used for water resource forecasting. This work designed a PSO technique for estimating everyday BOD at Al-Rustumiya wastewater treatment facility inlet. Al-Rustumiya wastewater treatment plant provided 702 plant-scale data sets during 2012-2022. The PSO model uses the daily data of the water quality parameters, including chemical oxygen demand (COD), chloride (Cl-), suspended solid (SS), total dissolved solids (TDS), and pH, to determine how each variable affects the daily incoming BOD. PSO and multiple linear regression (MLR) findings are compared, and their performance is evaluated usin
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A mathematical method with a new algorithm with the aid of Matlab language is proposed to compute the linear equivalence (or the recursion length) of the pseudo-random key-stream periodic sequences using Fourier transform. The proposed method enables the computation of the linear equivalence to determine the degree of the complexity of any binary or real periodic sequences produced from linear or nonlinear key-stream generators. The procedure can be used with comparatively greater computational ease and efficiency. The results of this algorithm are compared with Berlekamp-Massey (BM) method and good results are obtained where the results of the Fourier transform are more accurate than those of (BM) method for computing the linear equivalenc
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Rationale, aims and objectives: A review of studies published over the last six years gives update about this hot topic. In the middle of COVID-19 pandemic, this study findings can help understand how population may perceive vaccinations. The objectives of this study were to review the literature covering the perceptions about influenza vaccines and to determine factors influencing the acceptance of vaccination using Health Belief Model (HBM). Methods: A comprehensive literature search was performed utilizing PubMed and Google Scholar databases. Three keywords were used: Influenza vaccine, perceptions, and Middle East. Empirical studies that dealt with people/ HCW perceptions of influenza vaccine in the Middle East and writt
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The valley Dwiridj of drainage basins task that lies east of Iraq and thus we have in this study the application of tow models athletes on the three basins of the valley to get Mor e values accurate to Estimate the volume of runoff and peak discharge and time climax and through the use of Technology remote sensing (GIS),has been show through the application of both models, that the maximum value for the amount of Dwiridj valley of (1052/m3/s) According to Equation (SCS-CN) and about (1370.2/m3/s)by approach (GIUH) that difference is the amount of discharge to the Equation (SCS-CN) ar not accurate as(GIUH) approaches Equation ecalling the results of the Field ces Department of damand reservoirs that the volume of runoff to the valley wase
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Free Radical Copolymerization of Styrene/ Methyl Methacrylate were prepared chemically under Nitrogen ,which was investigated, in the present of Benzoyl Peroxide as Initiator at concentration of 2 × 10-3 molar at 70 °C, which was carried out in Benzene as solvent to a certain low conversion . FT-IR spectra were used for determining of the monomer reactivity ratios ,which was obtained by employing the conventional linearization method of Fineman-Ross (F-R) and Kelen-Tüdos (K- T). The experimental results showed the average value for the Styrene r1 / Methyl Methacrylate r2 system, Sty r1 = 0.45 , MMA r2 = 0.38 in the (F–R) Method and r1 = 0.49 , r2 = 0.35 in the (K–T) Method, The Results of this indicated show the random distri
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Codes of red, green, and blue data (RGB) extracted from a lab-fabricated colorimeter device were used to build a proposed classifier with the objective of classifying colors of objects based on defined categories of fundamental colors. Primary, secondary, and tertiary colors namely red, green, orange, yellow, pink, purple, blue, brown, grey, white, and black, were employed in machine learning (ML) by applying an artificial neural network (ANN) algorithm using Python. The classifier, which was based on the ANN algorithm, required a definition of the mentioned eleven colors in the form of RGB codes in order to acquire the capability of classification. The software's capacity to forecast the color of the code that belongs to an ob
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