In this work, thiadiazole derivatives were prepared by taking advantage of active sites in (2-amino-5-mercapto-1, 3, 4-thiadiazole) as a starting material base. The main heterocyclic compounds (1, 3, 4-thiadiazole, oxazole) etc, 2-amino-5-mercapto-1,3,4-thiadiazole compound (1) was prepared by cyclic closure of thiosemicarbazide compound with anhydrous sodium carbonate and carbon disulfide. Oxidation of (1) via hydrogen peroxide, to have (2) which was treated with chloro acetyl chloride to get (3). Preparation of thiazole ring (4) was from reacting of (3) with thiourea. Synthesis of diazonium salts (5) from compound (4) using sodium nitrite and HCl. Compound (5) reacted with different ester compounds to prepare a new azo compounds (6–8).C

The aim of the work is synthesis and characterization of bidentate ligand [3-(3-acetylphenylamino)-5,5-dimethylcyclohex-3-enone][HL], from the reaction of dimedone with 3-amino acetophenone to produce the ligand [HL], the reaction was carried out in dry benzene as a solvent under reflux. The prepared ligand [HL] was characterized by FT-IR, UV-Vis spectroscopy, 1H, 13C-NMR spectra, Mass spectra, (C.H.N) and melting point. The mixed ligand complexes were prepared from ligand [HL] was used as a primary ligand while 8-hydroxy quinoline [HQ] was used as a secondary ligand with metal ion M(Π).Where M(Π) = (Mn ,Co ,Ni ,Cu ,Zn ,Cd and Pd) at reflux ,using ethanol as a solvent, KOH as a base. Complexes of the composition [M(L)(Q)] with (1

Background: Although mammography is a powerful screening tool in detection of early breast cancer, it is imperfect, particularly for women with dense breast, which have a higher risk to develop cancer and decrease the sensitivity of mammogram, Automated breast ultrasound is a recently introduced ultrasonography technique, developed with the purpose to standardize breast ultrasonography and overcome some limitations of handheld ultrasound, this study aims to evaluate the diagnostic efficacy of Automated breast ultrasound and compare it with handheld ultrasound in the detection and characterization of breast lesions in women with dense breasts. Objectives: To evaluate the diagnostic efficacy of Automated breast ultrasound and compare

This work includes preparation of Az, Qz, and Tz derivatives from the reaction of Schiff base (Sb) derivative with anthranilic acid, chloroacetyl chloride, and sodium azide, as well as, the characterization via FT-IR, 1H-NMR, and 13CNMR. The anticorrosion inhibition of these compounds was studied and the measurements of carbon steel (CS) corrosion in sodium chloride solution 3.5% (blank) and inhibitor in solutions were calculated at a temperature range of 293-323 K by the technique of electrochemical polarization. In addition, some thermodynamic and kinetic activation parameters for inhibitor and blank solutions (Ea⋇, ΔH⋇, ΔS⋇, and ΔG⋇) were determined. The results showed high inhibition efficacy for all the prepared compounds,

The aim of the work is synthesis and characterization of bidentate ligand [3-(3-acetylphenylamino)-5,5-dimethylcyclohex-3-enone][HL], from the reaction of dimedone with 3-amino acetophenone to produce the ligand [HL], the reaction was carried out in dry benzene as a solvent under reflux. The prepared ligand [HL] was characterized by FT-IR, UV-Vis spectroscopy, 'H, 8C-NMR spectra, Mass spectra, (C.H.N) and melting point. The mixed ligand complexes were prepared from ligand [HL] was used as a primary ligand while 8-hydroxy quinoline [HQ] was used as a secondary ligand with metal ion M(IT).Where M(IT) = (Mn ,Co ,Ni ,Cu ,Zn ,Cd and Pd) at reflux ,using ethanol as a solvent, KOH as a

   Predicting permeability is a cornerstone of petroleum reservoir engineering, playing a vital role in optimizing hydrocarbon recovery strategies. This paper explores the application of neural networks to predict permeability in oil reservoirs, underscoring their growing importance in addressing traditional prediction challenges. Conventional techniques often struggle with the complexities of subsurface conditions, making innovative approaches essential. Neural networks, with their ability to uncover complicated patterns within large datasets, emerge as a powerful alternative. The Quanti-Elan model was used in this study to combine several well logs for mineral volumes, porosity and water saturation estimation. This model goes be

Television white spaces (TVWSs) refer to the unused part of the spectrum under the very high frequency (VHF) and ultra-high frequency (UHF) bands. TVWS are frequencies under licenced primary users (PUs) that are not being used and are available for secondary users (SUs). There are several ways of implementing TVWS in communications, one of which is the use of TVWS database (TVWSDB). The primary purpose of TVWSDB is to protect PUs from interference with SUs. There are several geolocation databases available for this purpose. However, it is unclear if those databases have the prediction feature that gives TVWSDB the capability of decreasing the number of inquiries from SUs. With this in mind, the authors present a reinforcement learning-ba