By measuring Adropin, fasting blood glucose (FBG), cholesterol, high-density lipoprotein (HDL), triglycerides (TG), low-density lipoprotein (LDL), and very low-density lipoprotein (VLDL) in the sera of Iraqi patients with MetS and type 2 diabetes mellitus (T2DM), the current study was designed to compare some crucial markers in metabolic syndrome (MetS) sera and diabetic patients (T2DM) with control. Twenty female subjects were divided into three groups: group I=40 with MetS and group II=40 with T2DM, and 40 healthy subjects were employed as a control group. Compared to the control group, Adropin levels in the Mets group and T2DM group decreased significantly (p < 0.05). In contrast, none of the patient groups (MetS and T2DM)

The advertisement is important in maximizing the resources of journalistic institutions. It helps them to perform their duties and also establishes their independence. However, this type of communication has often overlapped with other types of communication, including media and publicity.

Those in charge of the press bear responsibility in this regard, as some of them harness the advertisement for personal purposes; or detrimental to media content. Many communication authorities have drawn attention to the danger of confusing the concepts and levels of the three activities and have moved towards establishing rules to reduce overlap between them.

The aim of this research is to try to disengage the concept of advertising,

A skin condition known as chronic spontaneous urticaria (CSU), which lacks an obvious triggering factor, is characterized by recurrent transient wheals, angioedema, or both for longer than six weeks. the current study was focused to study compared and diagnosis CSU by using heamatological and immunological parameters as (White blood cell count, eosinophils (EO), IL-6  and Total-IgE, in Chronic Urticaria patients were Clinically diagnosed by dermatologists in Specialized Center of Allergy in Baghdad/Al-Rusafa with age ranged between (11-60), as well as a control group included 40 with age ranged between (11-60). The results of demographic and clinical characteristics displayed  the rate of female patients was higher than male which repr

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

Average per capita GDP income is an important economic indicator. Economists use this term to determine the amount of progress or decline in the country's economy. It is also used to determine the order of countries and compare them with each other. Average per capita GDP income was first studied using the Time Series (Box Jenkins method), and the second is linear and non-linear regression; these methods are the most important and most commonly used statistical methods for forecasting because they are flexible and accurate in practice. The comparison is made to determine the best method between the two methods mentioned above using specific statistical criteria. The research found that the best approach is to build a model for predi

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

In the petroleum industry, multiphase flow dynamics within the tubing string have gained significant attention due to associated challenges. Accurately predicting pressure drops and wellbore pressures is crucial for the effective modeling of vertical lift performance (VLP). This study focuses on predicting the multiphase flow behavior in four wells located in the Faihaa oil field in southern Iraq, utilizing PIPESIM software. The process of selecting the most appropriate multiphase correlation was performed by utilizing production test data to construct a comprehensive survey data catalog. Subsequently, the results were compared with the correlations available within the PIPESIM software. The outcomes reveal that the Hagedorn and Brown (H

Total dissolved solids are at the top of the parameters list of water quality that requires investigations for planning and management, especially for irrigation and drinking purposes. If the quality of water is sufficiently predictable, then appropriate management is possible. In the current study, Multiple Linear Regression (MLR) and Artificial Neural Network (ANN) models were used as indicators of water quality and for the prediction of Total Dissolved Solids (TDS) along the Tigris River, in Baghdad city. To build these models five water parameters were selected from the intakes of four water treatment plants on the Tigris River, for the period between 2013 and 2017. The selected water parameters were Total Dissolved Solids (TDS