Newly 4-amino-1,2,4-triazole-3-thione ring 2 was formed at position six of 2-methylphenol from the reaction of 6-(5-thio1,3,4-oxadiazol-2-yl)-2-methylphenol 1 with hydrazine hydrochloride in the presence of anhydrase sodium acetate. Seven newly fused heterocyclic compounds were synthesized from compound 2. First fused heterocyclic was 6-(6-(3,5-di-tertbutyl-4-hydroxyphenyl)-[1,2,4]triazolo[3,4-b][1,3,4]thiadiazol-3-yl)-2-methylphenol 3 synthesized from reaction compound 2 with 3,5-di-tert-butyl-4-hydroxybenzoic acid in POCl3. Reaction compound 2 with bromophencylbromide afford 6-(6-(4-bromophenyl)-5H-[1,2,4]triazolo[3,4-b][1,3,4]-thiadiazin-3-yl)-2-methylphenol 4. 6-(6-thio-1,7a-dihydro-[1,2,4] triazolo[3,4-b][1,3,4]-thiadiazol-3-yl)-2

Background: The skull base and the hard palate contain many anatomical features that make them rich in information which are useful in sex differentiation; in addition to that they have the ability to resist the hardest environmental conditions that support them in making sex differentiation. Three dimensional computed tomographic techniques has important role in differentiation between sex since it offers images with very accurate data and details of all anatomical structures with high resolution. This study was made to study sex variations among Iraqi sample by craniometric linear measurements of the hard palate and the skull base using 3D reconstructed Computed Tomographic scan. Materials and methods: This study composed of 100 Iraqi su

The two-neutron halo-nuclei (¹⁷B, ¹¹Li, ⁸He) was investigated using a two-body nucleon density distribution (2BNDD) with two frequency shell model (TFSM). The structure of valence two-neutron of ¹⁷B  nucleus in a pure (1d_5/2) state and in a pure (1p_1/2) state for  ¹¹L and ⁸He nuclei. For our tested nucleus, an efficient (2BNDD's) operator for point nucleon system folded with two-body correlation operator's functions was used to investigate nuclear matter density distributions, root-mean square (rms) radii, and elastic electron scattering form factors. In the nucleon-nucleon forces the correlation took account of

The study evaluated endophytic communities associated with five oil-bearing plants, including sesame, corn, sunflower, olives and castor, which were collected from Baghdad and Diyala (Iraq), evaluated their oil production capacity and identified metabolites from the lipid fraction. Out of 151 isolates were collected from 21 taxa. Aspergillus niger showed the highest frequency (6.62 %), while the genera Aspergillus and Fusarium were the most dominant endophytes. The highest oil yield was identified and recorded in Aspergillus terreus (24.12 %). While the lowest oil yield was observed in Sclerotinia spp. (3.96 %). Gas chromatography-mass spectrometry (GC-MS) analysis of A. terreus revealed a profile dominated by pentadecyl acrylate (2

The research examines the mechanism of application of )ISO 21001: 2018( in the Energy Branch- Electromechanical Engineering at the University of Technology to achieve the quality of the educational service to prepare the branch to obtain the certificate of conformity with the requirements of) ISO 21001: 2018(, the necessary data were collected Depending on the (CHEKLIST) of (ISO 21001: 2018), field interviews and records of the concerned department, The researchers reached a number of results, the most prominent of which was the adoption of high quality leadership leaders and their willingness to implement the standard requirements, The university has a basic structure that qualifies it to implement the international standard, as

Empirical and statistical methodologies have been established to acquire accurate permeability identification and reservoir characterization, based on the rock type and reservoir performance. The identification of rock facies is usually done by either using core analysis to visually interpret lithofacies or indirectly based on well-log data. The use of well-log data for traditional facies prediction is characterized by uncertainties and can be time-consuming, particularly when working with large datasets. Thus, Machine Learning can be used to predict patterns more efficiently when applied to large data. Taking into account the electrofacies distribution, this work was conducted to predict permeability for the four wells, FH1, FH2, F