The study of Shiranish Formation rocks in southern part of Iraq at Ansab area well (KH-6)
were carried out. The formation is tongued with tayarat formation, which bounded from top
and bottom, the upper tongue at thickness 49m. and tongued at depth (476-525m.) the lower
tongue at thickness 4m. tongued at (541-537m.).
The rocks of this formation were divided into three sedimentary microfacies:
1- Dolomitized formininferal Wackestone facies.
2- Dolomitized formininferal Mudstone facies.
3- Dolostone facies.
34 slides were investigated depending on mineralogical, compositional and biological
processes and compared diagenesis which reflect open marine shelf at lower part of formation
(F.Z.2) (S.M.F.8), but at the

Iron oxide (Fe3O4) nanoparticles were synthesized via an eco-friendly green approach by adding Phoenix dactylifera extract to the aqueous solution of ferric chloride. The effect of annealing temperature (Ta) (100-150) °C on particle size was studied. X-ray diffraction (XRD), UV-visible spectroscopy, atomic force microscopy (AFM), and field emission scanning electron microscopy (FESEM) were used to evaluate the produced nanoparticles. According to XRD spectra, the crystallite size of the samples was determined using the Scherrer formula. AFM and FE-SEM were used to determine surface morphology. A UV-Vis optical spectroscopic examination was carried out to determine the band gap energy of the iron oxide nanoparticles. It was found th

The research of three-based financial indicators to create value for shareholders, have been identified research problem in a number of the questions revolved around the extent to which it can express its based performance metrics to create value for the essence and the reality of the surveyed enterprises performance, Can the departments surveyed companies to choose the scale or the most harmonizing index and an expression of the actual performance of the company, has the goal of research is to diagnose the strengths and weaknesses in the performance of the surveyed enterprises through the use of a number of based on the concept of creating economic value and the search for the most suitable indicator to the reality of the perfor

Advanced strategies for production forecasting, operational optimization, and decision-making enhancement have been employed through reservoir management and machine learning (ML) techniques. A hybrid model is established to predict future gas output in a gas reservoir through historical production data, including reservoir pressure, cumulative gas production, and cumulative water production for 67 months. The procedure starts with data preprocessing and applies seasonal exponential smoothing (SES) to capture seasonality and trends in production data, while an Artificial Neural Network (ANN) captures complicated spatiotemporal connections. The history replication in the models is quantified for accuracy through metric keys such as m

In this paper, third order non-polynomial spline function is used to solve 2nd kind Volterra integral equations. Numerical examples are presented to illustrate the applications of this method, and to compare the computed results with other known methods.

The erythrocyte aggregation is an important physiological phenomenon in the circulation of blood. It is a basic characteristic of normal blood that plays a major role in the cardiovascular system, especially in the microcirculation. This study explained the kinetics of single cells rouleaux formation one- dimensional aggregate and three- dimensional aggregate, during simultaneous, and the effect of hematocrit on the process of aggregation and sedimentation. The present study was done on forty one healthy subjects. Laser light is passed through a well mixed sample of blood and the forward scattered light intensities recorded continuously. The samples were prepared with different hematocrit, (10%, 15%, 20%, and 25%). Increasing

KE Sharquie, AA Noaimi, SA Galib, Journal of Cosmetics, Dermatological Sciences and Applications, 2013 - Cited by 4

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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