The permeability is the most important parameter that indicates how efficient the reservoir fluids flow through the rock pores to the wellbore. Well-log evaluation and core measurements techniques are typically used to estimate it. In this paper, the permeability has been predicted by using classical and Flow zone indicator methods. A comparison between the two methods shows the superiority of the FZI method correlations, these correlations can be used to estimate permeability in un-cored wells with a good approximation.

In the last few years, the use of artificial neural network analysis has increased, particularly, in geotechnical engineering problems and has demonstrated some success. In this research, artificial neural network analysis endeavors to predict the relationship between physical and mechanical properties of Baghdad soil by making different trials between standard penetration test, liquid limit, plastic limit, plasticity index, cohesion, angle of internal friction, and bearing capacity. The analysis revealed that the changes in natural water content and plastic limit have a great effect on the cohesion of soil and the angle of internal friction, respectively. . On the other hand, the liquid limit has a great impact on the bearing capacity and

In the last few years, the use of artificial neural network analysis has increased, particularly, in geotechnical engineering problems and has demonstrated some success. In this research, artificial neural network analysis endeavors to predict the relationship between physical and mechanical properties of Baghdad soil by making different trials between standard penetration test, liquid limit, plastic limit, plasticity index, cohesion, angle of internal friction, and bearing capacity. The analysis revealed that the changes in natural water content and plastic limit have a great effect on the cohesion of soil and the angle of internal friction, respectively. . On the other hand, the liquid limit has a great impact on the bearing capacity and

In the last few years, the use of artificial neural network analysis has increased, particularly, in geotechnical engineering problems and has demonstrated some success. In this research, artificial neural network analysis endeavors to predict the relationship between physical and mechanical properties of Baghdad soil by making different trials between standard penetration test, liquid limit, plastic limit, plasticity index, cohesion, angle of internal friction, and bearing capacity. The analysis revealed that the changes in natural water content and plastic limit have a great effect on the cohesion of soil and the angle of internal friction, respectively. . On the other hand, the liquid limit has a great impact on the bearing capacity and

Hepatocellular carcinoma (HCC) is the third most common cause of cancer-related death. Therefore, it is critical for researchers to understand molecular biology in greater depth.  In several diseases including cancer, abnormal miRNA expression has been linked to apoptosis, proliferation, differentiation, and metastasis. Many miRNAs have been studied in relation to cancer, including miR-122, miR-223, and others. Hepatitis B and C viruses are the most important global risk factors for HCC. This study is intended to test whether serum miRNAs serve as a potential biomarker for both HCC and viral infections HBV and C. The expression of miRNA in 64 serum samples was analyzed by RT-qPCR. Compared to healthy volunteers, HCC patients' sera expre

The research aims to demonstrate the dual use of analysis to predict financial failure according to the Altman model and stress tests to achieve integration in banking risk management. On the bank’s ability to withstand crises, especially in light of its low rating according to the Altman model, and the possibility of its failure in the future, thus proving or denying the research hypothesis, the research reached a set of conclusions, the most important of which (the bank, according to the Altman model, is threatened with failure in the near future, as it is located within the red zone according to the model’s description, and will incur losses if it is exposed to crises in the future according to the analysis of stress tests

The influence of fiber orientation and water absorption on fatigue crack growth resistance for cold cure acrylic (PMMA) reinforced by chopped and woven -glass-fibers were investigated. A weight of 2 g for chopped fibers and the same weight for woven -glass-fibers (one layer) were used to prepare samples. Some of these samples would storage in dry condition; the others were immersed in water for 15 days. Fatigue test was carried out. The results shows that, for PMMA, the initial bending stress for dry specimen was 3.392 N/cm2 and the number of cycles were 1364, the initial bending stress for wet samples was 4.20 N/cm2, and the number of cycles was 2411. The samples would cut in two pieces because of the cracks would propagated fast during

To evaluate the bioactivity and the cytocompatibility of experimental Bioglass-reinforced polyethylene-based root-canal filling materials. The thermal properties of the experimental materials were also evaluated using differential scanning calorimetry, while their radiopacity was assessed using a grey-scale value (GSV) aluminium step wedge and a phosphor plate digital system. Bioglass 45S5 (BAG), polyethylene and Strontium oxide (SrO) were used to create tailored composite fibres. The filler distribution within the composites was assessed using SEM, while their bioactivity was evaluated through infrared spectroscopy (FTIR) after storage in simulated body fluid (SBF). The radiopacity of the composite fibres and their thermal properties were

Background: The daily cleaning routine of the silicone maxillofacial prostheses by the patient may cause some alteration in the materials properties. The purpose of the present study was to investigate the effect of different disinfection procedures on some properties of silicon dioxide reinforced Cosmesil M511 HTV maxillofacial silicone. Materials and Methods: One hundred and sixty (160) specimens were prepared by mixing 5% SiO2 nano particles and 0.5% intrinsic cream color into the silicone polymer according to manufacturer's instructions. Specimens were divided into 4 groups according to the performed test (tear strength, surface hardness, surface roughness and color) with 40 specimens each. Each group was further subdivided according to