This study was conducted in the field of the Poultry Research Station of the animal resources Department / office of Agricultural Research / Ministry of Agriculture from the period 4th April to16th May2021.This study was aimed to investigate the effect of using avocado and chia oil and their mixture in broiler diets on the final productive performance and meat cholesterol concentration and measuring meat oxidation indicators after storing it for 60 days. 300 one-day-old (Ross308) chicks were fed on diets that used avocado oil and chia with percentages of 0, 0.2, 0.4, 0.6%, respectively, and their mixture consisting of 0.0, 0.1, 0.2, 0.3 each of avocado and chia oil (50% avocado + 50% chia oil). The experiment included 10 treatments

In the present study waste aluminium cans were recycled and converted to produce alumina catalyst. These cans contain more than 98% aluminum oxide in their structure and were successfully synthesized to produce nano sized gamma alumina under mild conditions. A comprehensive study was carried out in order to examine the effect of several important parameters on maximum yield of alumina that can be produced. These parameters were reactants mole ratios (1.5, 1.5, 2, 3, 4 and 5), sodium hydroxide concentrations (10, 20, 30, 40, 50 and 55%) and weights of aluminum cans (2, 4, 6, 8 and 10 g). The compositions of alumina solution were determined by Atomic absorption spectroscopy (AAS); and maximum yield of alumina solution was 96.3% obtain

In this work 5-methylene-yl - (2-methy –oxazole-4-one) (1H) imidazole (1) were synthesized from the reaction of L-Histidine with acetic anhydride and which converted to the of 5-methylene-yl-(2-methyl 3-amino imidazole-4-one)-1H-imidazole (2) by reaction with hydrazine hydrate. Schiff bases (3-6) were synthesized from the reaction of compound (2) with different aromatic aldehyde. Reaction of compounds (3-6) with chloroacetyl chloride gives azetidinone one derivatives (7-10). These compounds were characterized by FT-IR and some of them with 1H-NMR and 13C-NMR spectroscopy.

Reaction of,2- [( 4- amio phenyl ) diazenyl] 1,3,4- thiadiazole -5- thiol (S1) with p- chlorobenzeldehyde,3,4 – dimethoxy benzaldehyde and pyrrol-2- carbonxaldehyde gave -5- [{4-(4-chlorobenzylidene amino) phenyl} diezenyl]-1,3,4- thiadiazole-2- thiol (S2),5-[{ 4-[(3,4- dimethoxybenzyldene )amino phenyl ] diazenyl)-1,3,4- thiadiazole-2-thiol,(S3) and -5- [4-(1,H – pyrrol -2- yl- methylene)amino phenyl] diazenyl)-1,3,4- thiadiazole-2- thiol (S4) respectively as schiff's bases compounds. On the same route-2-[(4-amino-1- naphthyl ) diazenyl] -1,3,4- thiadiazole -5- thiol (S5) reacts with –p- chloro benzaldehyde and –m- nitrobenzaldehyde to give the follwing schiff's bases -5-[{ 4-(4- chloro benzylidene ) amino -1- naphthyl} diazenyl]

n this work, a series of new nucleoside analogues (β-glucose liked to pyrazoline moiety) was synthesized. In the beginning, chalcone [1-3] was formed from the reaction of acetophenone and benzaldehyde derivatives in the presence of sodium hydroxide. Pyrazolines [4-6] were obtained from the reaction of the prepared chalcones and hydrazine hydrate in the presence of ethanol absolute. These pyrazolines were treated with β-glucose pentaacetate to afford a series of desirable protected nucleoside analogues [8-10]. After that hydrolysis of protected nuclioside analogues in sodium methoxide gave free nucleoside analogues [11-13]. These new formed compounds were diagnosed by 13C-NMR and 1H- NMR for some of them and FT-IR spectroscopy.

The tetradentate N2O2 Schiff base ligand, which is produced via the condensation reaction of 2-hydroxynaphthaldehyde with phthalohydrazide, is prepared in this work with a fair yield. The prepared ligand was characterized using a microanalysis technique (C.H.N), UV-vis, FTIR, 1H-,13C-NMR, mass spectrometry, and thermal gravimetric analysis (TGA). New complexes were synthesized by a reaction between ligand (N'1E,N'2Z)-N'1,N'2-bis((1-hydroxynaphthalen-2yl)methylene)phthalohydrazide and metal chloride of Co+2, Ni+2, and Zn+2 ions in absolute ethanol. The present complexes are also characterized by techniques such as C.H.N, UV-vis, FTIR, TGA, molar conductivity, atomic absorption, and magnetic moment measurements. The in vitro antimicro

      Data mining has the most important role in healthcare for discovering hidden relationships in big datasets, especially in breast cancer diagnostics, which is the most popular cause of death in the world. In this paper two algorithms are applied that are decision tree and K-Nearest Neighbour for diagnosing Breast Cancer Grad in order to reduce its risk on patients. In decision tree with feature selection, the Gini index gives an accuracy of %87.83, while with entropy, the feature selection gives an accuracy of %86.77. In both cases, Age appeared as the  most effective parameter, particularly when Age<49.5. Whereas  Ki67  appeared as a second effective parameter. Furthermore, K- Nearest Neighbor is based on the minimu

In digital images, protecting sensitive visual information against unauthorized access is considered a critical issue; robust encryption methods are the best solution to preserve such information. This paper introduces a model designed to enhance the performance of the Tiny Encryption Algorithm (TEA) in encrypting images. Two approaches have been suggested for the image cipher process as a preprocessing step before applying the Tiny Encryption Algorithm (TEA). The step mentioned earlier aims to de-correlate and weaken adjacent pixel values as a preparation process before the encryption process. The first approach suggests an Affine transformation for image encryption at two layers, utilizing two different key sets for each layer. Th

Text based-image clustering (TBIC) is an insufficient approach for clustering related web images. It is a challenging task to abstract the visual features of images with the support of textual information in a database. In content-based image clustering (CBIC), image data are clustered on the foundation of specific features like texture, colors, boundaries, shapes. In this paper, an effective CBIC) technique is presented, which uses texture and statistical features of the images. The statistical features or moments of colors (mean, skewness, standard deviation, kurtosis, and variance) are extracted from the images. These features are collected in a one dimension array, and then genetic algorithm (GA) is applied for image clustering.