Liquefied petroleum gases (LPG) consist of hydrocarbons obtained by refining crude oil, either from propane or butane or a mixture of the two. There are often other components such as propylene, butylene or other hydrocarbons, but they are not the main component. The study aims to review previous studies dealing with designing an LPG system to deliver gas to residential campuses and buildings. LPG is extracted from natural gas NG by several processes, passing through fractionation towers and then pressuring into CNG storage tanks. Gas contains several problems, including gas leakage through the pipes and leads to fires or explosions in LPG storage and distribution tanks, so safety conditions were taken in the design and implementation. T

ABSTRACT This paper has a three-pronged objective: offering a unitary set of semantic distinctive features to the analysis of nominal “hatred synonyms” in the lexicon of both English and Standard Arabic (SA), applying it procedurally to test its scope of functionality crosslinguistically, and singling out the closest noun synonymous equivalents among the membership of the two sets in this particular lexical semantic field in both languages. The componential analysis and the matching procedures carried have been functional in identifying ten totally matching equivalents (i.e. at 55.6%), and eight partially matching ones (i.e. at %44.4%). This result shows that while total matching equivalences do exist in the translation of certain Eng

This paper deals with numerical study of the flow of stable and fluid Allamstqr Aniotina in an area surrounded by a right-angled triangle has touched particularly valuable secondary flow cross section resulting from the pressure gradient In the first case was analyzed stable flow where he found that the equations of motion that describe the movement of the fluid

A total of 33 Iraq male positive for Toxoplasmosis and Iraq male negative for Toxoplasmosis (controls) were studies to Evaluation of some biochemical and immunological parameters changes.The parameters included lipid profile such as (Cholesterol(C), Triglycerides(TG), High-Density Lipoprotein (HDL), Low-Density Lipoprotein (LDL) and very Low-Density Lipoprotein (VLDL) and complement component C3 and C4. The results revealed significant decrease in the total cholesterol, Triglycerides, LDL and non-significant in vLDL (129.96±1.63, 130.69± 2.80, 87.19±1.97, 29.24± 0.83 mg/dl respectively) and non-significant increase in HDL(24.22 ±0.62) mg/dl compared with control group(152.07± 1.63, 156.48± 6.55, 99.26 ±1.39, 31.49± 1.30 and 21.31±

Diagnosing heart disease has become a very important topic for researchers specializing in artificial intelligence, because intelligence is involved in most diseases, especially after the Corona pandemic, which forced the world to turn to intelligence. Therefore, the basic idea in this research was to shed light on the diagnosis of heart diseases by relying on deep learning of a pre-trained model (Efficient b3) under the premise of using the electrical signals of the electrocardiogram and resample the signal in order to introduce it to the neural network with only trimming processing operations because it is an electrical signal whose parameters cannot be changed. The data set (China Physiological Signal Challenge -cspsc2018) was ad