In this paper a new series of morpholine derivatives was prepared by reacting the morpholine with ethyl chloro acetate in the presence triethylamine as a catalyst in benzene gave morpholin-N-ethyl acetate(1) which reacted with hydrazine hydrate in ethanol, and gave morpholin-N-ethyl acetohydrazide (2) . Morpholin-N-aceto semithiocarbazide (3) were prepared by reacting compound(2) with ammonium thiocyanate , concentrated hydrochloric acid and ethanol as a solvent .Compound (3) reacted with sodium hydroxide and hydrochloric acid to give 5-(morpholin-N-methylene)-1H-1,2,4-triazole-3-thiol (4) .The new series of 1,2,4-triazol derivatives (5-8) was synthesized by reaction of compound(4) with formaldehyde , DMF as a solvent and different

        Isradipine related to dihydropyridine (DHP) class of calcium channel blockers (CCBs). It is  used to treat hypertension, angina pectoris, as well as Parkinson disease. It goes under the BCS class II drug (low solubility-high permeability). The drug will experience extensive first-pass metabolism in liver, thus, oral bio-availability will be approximately15 to 24 %. 

       The aim of the study is preparing stable oral oil in water (o/w) nanoemulsion of isradipine to promote the colloidial dispersion of isradipine in the nano range, so that it may be absorded by intestinal lymphatic transport in order to avoid hepatic first-pass metabolism (israpidi

Wellbore instability and sand production onset modeling are very affected by Sonic Shear Wave Time (SSW). In any field, SSW is not available for all wells due to the high cost of measuring. Many authors developed empirical correlations using information from selected worldwide fields for SSW prediction. Recently, researchers have used different Artificial Intelligence methods for estimating SSW. Three existing empirical correlations of Carroll, Freund, and Brocher are used to estimate SSW in this paper, while a fourth new empirical correlation is established. For comparing with the empirical correlation results, another study's Artificial Neural Network (ANN) was used. The same data t

Prediction of penetration rate (ROP) is important process in optimization of drilling due to its crucial role in lowering drilling operation costs. This process has complex nature due to too many interrelated factors that affected the rate of penetration, which make difficult predicting process. This paper shows a new technique of rate of penetration prediction by using artificial neural network technique. A three layers model composed of two hidden layers and output layer has built by using drilling parameters data extracted from mud logging and wire line log for Alhalfaya oil field. These drilling parameters includes mechanical (WOB, RPM), hydraulic (HIS), and travel transit time (DT). Five data set represented five formations gathered

Lung cancer is one of the most serious and prevalent diseases, causing many deaths each year. Though CT scan images are mostly used in the diagnosis of cancer, the assessment of scans is an error-prone and time-consuming task. Machine learning and AI-based models can identify and classify types of lung cancer quite accurately, which helps in the early-stage detection of lung cancer that can increase the survival rate. In this paper, Convolutional Neural Network is used to classify Adenocarcinoma, squamous cell carcinoma and normal case CT scan images from the Chest CT Scan Images Dataset using different combinations of hidden layers and parameters in CNN models. The proposed model was trained on 1000 CT Scan Images of cancerous and non-c

The heat transfer and flow resistance characteristics for air flow cross over circular finned tube heat exchanger has been studied numerically and experimentally. The purpose of the study was to improve the heat transfer characteristics of an annular finned-tube heat exchanger for better performance. The study has concentrated on the effect of the number of perforations and perforations shapes on the heat transfer and pressure drop across a staggered finned tube heat exchanger. The Numerical part of present study has been performed using ANSYS Fluent 14.5 using SST Turbulent model, while the experimental study consist from a test rig with different models of heat exchangers and all required measurement devices were build