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  This study is concerned with the estimation of constant  and time-varying parameters in non-linear ordinary differential equations, which do not have analytical solutions. The estimation is done in a multi-stage method where constant and time-varying parameters are estimated in a straight sequential way from several stages. In the first stage, the model of the differential equations is converted to a regression model that includes the state variables with their derivatives and then the estimation of the state variables and their derivatives in a penalized splines method and compensating the estimations in the regression model. In the second stage, the pseudo- least squares method was used to es

Abnormalities in the Lipid and lipoprotein levels are common in the general population and are considered as very important risk- factors for cardiovascular disease .In this context the effect of cholesterol, which is one of the most clinically relevant lipids is very important. Aim of the present study was to determine the levels of GLP-1 and GPCR in non- diabetic dyslipidaemic patients and compare the results with the control group, which may be used as a novel biomarker to predict heart disease in these patients. The study was also aimed to find the relationship between GLP-1 and GPCR with lipid profile and glucagon in the patient group. The study involved 90 non-diabetic dyslipidaemia patients, with 90 healthy controls. The subjects wer

The mathematical construction of an ecological model with a prey-predator relationship was done. It presumed that the prey consisted of a stage structure of juveniles and adults. While the adult prey species had the power to fight off the predator, the predator, and juvenile prey worked together to hunt them. Additionally, the effect of the harvest was considered on the prey. All the solution’s properties were discussed. All potential equilibrium points' local stability was tested. The prerequisites for persistence were established. Global stability was investigated using Lyapunov methods. It was found that the system underwent a saddle-node bifurcation near the coexistence equilibrium point while exhibiting a transcritical bifurcation

In petroleum reservoir engineering, history matching refers to the calibration process in which a reservoir simulation model is validated through matching simulation outputs with the measurement of observed data. A traditional history matching technique is performed manually by engineering in which the most uncertain observed parameters are changed until a satisfactory match is obtained between the generated model and historical information. This study focuses on step by step and trial and error history matching of the Mishrif reservoir to constrain the appropriate simulated model. Up to 1 January 2021, Buzurgan Oilfield, which has eighty-five producers and sixteen injectors and has been under production for 45 years when it started

This study is marked by: The ignorant poem and body language
 Its main objective is to reveal the manifestations of this language in the text mentioned, and accordingly, the sieve poem has been read semantic (semantic) and hermeneutic, revealing the poet's ability to employ symbols and signals (body language) in the poem chosen for this purpose; The existence of such language in pre-Islamic poetry. After a long reflection and reading, the signs and symbols of the physical movement of the body, and its feminine and aesthetic manifestations were identified, and this was achieved through the use of modern critical methodologies that directly affect this language. The study consisted of an introduction and three topics, followed by t

The objective of this study is to apply Artificial Neural Network for heat transfer analysis of shell-and-tube heat exchangers widely used in power plants and refineries. Practical data was obtained by using industrial heat exchanger operating in power generation department of Dura refinery. The commonly used Back Propagation (BP) algorithm was used to train and test networks by divided the data to three samples (training, validation and testing data) to give more approach data with actual case. Inputs of the neural network include inlet water temperature, inlet air temperature and mass flow rate of air. Two outputs (exit water temperature to cooling tower and exit air temperature to second stage of air compressor) were taken in ANN.