This study was performed to assess the correlation of serum interleukins (ILs) levels with anthropometric data and lipid profile status in blood samples obtained from 100 Iraqi obese women with polycystic ovary syndrome PCOS. Obese non PCOS healthy women (n=75) matching in age (19-38 years) and body mass index(29.9-33.4kg/m²) served as a control group. The samples were collected from Kamal Al-Samurai Teaching hospital during the period of December 2017- June 2018.ELISA kits were used to measure serum levels of IL-6,IL-10,IL-18, IL-29,IL-33,tumor necrotic factor (TNF-α),high sensitive C-reactive protein (hsCRP),  insulin, total testosterone, and sex hormone binding globulin(SHBG).The biochemical measure

In recent years, the Global Navigation Satellite Services (GNSS) technology has been frequently employed for monitoring the Earth crust deformation and movement. Such applications necessitate high positional accuracy that can be achieved through processing GPS/GNSS data with scientific software such as BERENSE, GAMIT, and GIPSY-OSIS. Nevertheless, these scientific softwares are sophisticated and have not been published as free open source software. Therefore, this study has been conducted to evaluate an alternative solution, GNSS online processing services, which may obtain this privilege freely. In this study, eight years of GNSS raw data for TEHN station, which located in Iran, have been downloaded from UNAVCO website

     Investigation of geotechnical vulnerability (liquefaction) and Zonation of the southern region of the Caspian Sea is my most important aim in terms of destructive earthquakes hazard potential. Past geologic events on the south coast of Caspian Sea indicates that destructive earthquakes lead to the death of numbers in this area. Remained evidence of seismic events happening indicates extensive landslides, liquefaction and soil subsidence in the residential and even natural area. Therefore, in this study determination of geotechnical vulnerability (liquefaction) intensity in southern coast of Caspian Sea against natural forces resulting from earthquakes and coastal construction via geographical information system e

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.

      In this research, the nonparametric technique has been presented to estimate the time-varying coefficients functions for the longitudinal balanced data that characterized by observations obtained through (n) from the independent subjects, each one of them is measured repeatedly by group of  specific time points (m). Although the measurements are independent among the different subjects; they are mostly connected within each subject and the applied techniques is the Local Linear kernel LLPK technique. To avoid the problems of dimensionality, and thick computation, the two-steps method has been used to estimate the coefficients functions by using the two former technique. Since, the two-

In this research, a qualitative seismic processing and interpretation is made up
through using 3D-seismic reflection data of East-Baghdad oil field in the central part
of Iraq. We used the new technique, this technique is used for the direct hydrocarbons
indicators (DHI) called Amplitude Versus Offset or Angle (AVO or AVA) technique.
For this purposes a cube of 3D seismic data (Pre-stack) was chosen in addition to the
available data of wells Z-2 and Z-24. These data were processed and interpreted by
utilizing the programs of the HRS-9* software where we have studied and analyzed
the AVO within Zubair Formation. Many AVO processing operations were carried
out which include AVO processing (Pre-conditioning for gathe

Unconfined Compressive Strength is considered the most important parameter of rock strength properties affecting the rock failure criteria.  Various research have developed rock strength for specific lithology to estimate high-accuracy value without a core.  Previous analyses did not account for the formation's numerous lithologies and interbedded layers. The main aim of the present study is to select the suitable correlation to predict the UCS for hole depth of formation without separating the lithology. Furthermore, the second aim is to detect an adequate input parameter among set wireline to determine the UCS by using data of three wells along ten formations (Tanuma, Khasib, Mishrif, Rumaila, Ahmady, Maudud, Nahr Um

     The objective of this research is to select the most suitable drilling location of new groundwater exploration wells, with a decision-making tool from Geographic Information System (GIS). The optimum location will be evaluated base on the hydro-geoelectrical parameter derived from Vertical Electrical Sound (VES) including Longitudinal Conductance, the thickness of the aquifer, the apparent resistivity and Transmissivity. From the Geo-electrical method (VES) the finds shows that the aquifers in the study area have Apparent Resistivity ranging from 0.32 to 40.24 Ωm, Thickness between 0.21 m to 15.06 m, Longitudinal Conductance ranging from 0.006 to 10.246Ω^-1 and Transmissivity ranging from 0.14 to

This work represents study the rock facies and flow unit classification for the Mishrif carbonate reservoir in Buzurgan oil Field, which located n the south eastern Iraq, using wire line logs, core samples and petrophysical data (log porosity and core permeability). Hydraulic flow units were identified using flow zone indicator approach and assessed within each rock type to reach better understanding of the controlling role of pore types and geometry in reservoir quality variations. Additionally, distribution of sedimentary facies and Rock Fabric Number along with porosity and permeability was analyzed in three wells (BU-1, BU-2, and BU-3). The interactive Petrophysics - IP software is used to assess the rock fabric number, flow zon

This study sought to investigate the impacts of big data, artificial intelligence (AI), and business intelligence (BI) on Firms' e-learning and business performance at Jordanian telecommunications industry. After the samples were checked, a total of 269 were collected. All of the information gathered throughout the investigation was analyzed using the PLS software. The results show a network of interconnections can improve both e-learning and corporate effectiveness. This research concluded that the integration of big data, AI, and BI has a positive impact on e-learning infrastructure development and organizational efficiency. The findings indicate that big data has a positive and direct impact on business performance, including Big