This paper is concerned with combining two different transforms to present a new joint transform FHET and its inverse transform IFHET. Also, the most important property of FHET was concluded and proved, which is called the finite Hankel – Elzaki transforms of the Bessel differential operator property, this property was discussed for two different boundary conditions, Dirichlet and Robin. Where the importance of this property is shown by solving axisymmetric partial differential equations and transitioning to an algebraic equation directly. Also, the joint Finite Hankel-Elzaki transform method was applied in solving a mathematical-physical problem, which is the Hotdog Problem. A steady state which does not depend on time was discussed f

Compound 4-(((6-amino-7H-[1, 2, 4] triazolo [3, 4-b][1, 3, 4] thiadiazin-3-yl) methoxy) methyl)-2, 6-dimethoxyphenol (6) was synthesized by multi steps. The corresponding acetonitrile thioalkyl (7) was cyclized by refluxing with acetic acid to afford 4-(((6-amino-7H-[1, 2, 4] triazolo [3, 4-b][1, 3, 4] thiadiazin-3-yl) methoxy) methyl)-2, 6-dimethoxyphenol (8). Two new series of 4-(((6-(3-(4-aryl) thioureido)-7H-[1, 2, 4] triazolo [3, 4-b][1, 3, 4] thiadiazin-3-yl) methoxy) methyl)-2, 6-dimethoxyphenol (9a-c) and of 4-(((6-(substitutedbenzamido) 7H-[1, 2, 4] triazolo [3, 4-b][1, 3, 4] thiadiazin-3-yl) methoxy) methyl)-2, 6-dimethoxyphenol (10a-c) were synthesized as new derivatives for fused 1, 2, 4-trizaole-thiadiazine (8). The antioxidant

The adsorption ability of Iraqi initiated calcined granulated montmorillonite to adsorb of 4-(4-Nitrobenzeneazo) 3-Aminobenzoic Acid from aqueous solutions has been investigated through columnar method. The azo dye adsorption found to be dependent on adsorbent dosage, initial concentration and contact time. All columnar experiments were carried out at three different pH values (5.5, 7and 8) using buffer solutions at flow rate of (3 drops/ min.), at room temperature (25±2) °C. The experimental isotherm data were analyzed using Langmuir, Freundlich and Temkin equations. The monolayer adsorption capacity is 6.4066 mg Azo ligand per 1g calcined Montmorillonite. The experiments showed that highest removal rate 90.5 % for azo dye at pH 5.5.The

Compound 4-(((6-amino-7H-[1,2,4]triazolo[3,4-b][1,3,4]thiadiazin-3-yl)methoxy)methyl)- 2,6-dimethoxyphenol (6) was synthesized by multi steps. The corresponding acetonitrile thioalkyl (7) was cyclized by refluxing with acetic acid to afford 4-(((6-amino-7H-[1,2,4]triazolo[3,4- b][1,3,4]thiadiazin-3-yl)methoxy)methyl)-2,6-dimethoxyphenol (8). Two new series of 4-(((6-(3- (4-aryl)thioureido)-7H-[1,2,4]triazolo[3,4-b][1,3,4] thiadiazin-3-yl)methoxy)methyl)-2,6- dimethoxyphenol (9a-c) and of 4-(((6-(substitutedbenzamido)7H-[1,2,4]triazolo[3,4- b][1,3,4]thiadiazin-3-yl)methoxy)methyl)-2,6-dimethoxyphenol (10a-c) were synthesized as new derivatives for fused 1,2,4-trizaole-thiadiazine(8). The antioxidants of newly compounds were evaluated by DPPH

The child realize that the meals time provide golden opportunities to get the attention the child needs. However, many difficulties that may appear about eating food can be avoided, if the family used the right way in dealing with this problem. The study aims, in this case, at searching for the reasons that lies behind the child's obstinacy in eating his food and the attempt to study some variables that is related to the research topic.

The results are summed up as follows:

• The number of the sample children is 3 of both sexes between the ages of 3 to 6 years

Diabetes is one of the increasing chronic diseases, affecting millions of people around the earth. Diabetes diagnosis, its prediction, proper cure, and management are compulsory. Machine learning-based prediction techniques for diabetes data analysis can help in the early detection and prediction of the disease and its consequences such as hypo/hyperglycemia. In this paper, we explored the diabetes dataset collected from the medical records of one thousand Iraqi patients. We applied three classifiers, the multilayer perceptron, the KNN and the Random Forest. We involved two experiments: the first experiment used all 12 features of the dataset. The Random Forest outperforms others with 98.8% accuracy. The second experiment used only five att