The map of permeability distribution in the reservoirs is considered one of the most essential steps of the geologic model building due to its governing the fluid flow through the reservoir which makes it the most influential parameter on the history matching than other parameters. For that, it is the most petrophysical properties that are tuned during the history matching. Unfortunately, the prediction of the relationship between static petrophysics (porosity) and dynamic petrophysics (permeability) from conventional wells logs has a sophisticated problem to solve by conventional statistical methods for heterogeneous formations. For that, this paper examines the ability and performance of the artificial intelligence method in perme

The historical center cities were exposed to change, which included its social and economical structures, Which led to sweeping changes in land use, causing a change in the result, in urban fabric and the physical structure and therefore to see visual. We have attracted these centers as a result of pressure from urban development and contemporary reflection of the agents of change which have been hit during the late period a development residential newly not sympathize mostly with the content of the historical and at the expense of removing large parts of the urban fabric and replace it with patterns of structural and styles of architecture has not been connected with reality. Which led to the loss of some historical and architec

The aim of this research is to identify the level of health services provided in the health centers operating in the family medicine system in Baghdad, and to determine the extent to which these health centers are applied to the internationally recognized standards , "Defining the quality of service gap between health care centers operating in the family medicine system and the standards adopted by the corresponding international centers (Al-Shabab Model Family Medicine Center, Al-Jahad Family Health Center, Al-Adhamiya Family Health Center, Al-Zawiya Family Health Center), and in view of what our health institutions are facing. The family of primary health care centers has difficulties, obstacles and challenges such as the diffi

Genetic polymorphisms of genes whose products are responsible for activities, such as xenobiotic metabolism, mutagen detoxification and DNA-repair, have been predicted to be associated with the risk of developing lung cancer (LC). The association of LC with tobacco smoking has been extensively investigated, but no studies have focused on the Arab ethnic- ity. Previously, we examined the association between genetic polymorphisms among Phase I and Phase II metabolism genes and the risk of LC. Here, we extend the data by examining the correlation of OGG1 Ser326Cys combined with CYP1A1 (Ile462Val and MspI) and GSTP1 (Ile105Val and Ala103Val) polymorphisms with the risk of LC. Polymerase chain reaction- restriction fragment length polymorphism (

Glutathione-S-transferases (GSTs) play a role in the detoxification of environmental chemicals and mutagens, such as those inhaled during tobacco smoking. There have been conflicting reports concerning GST polymorphisms as risk factors in the development of lung cancer. No studies focused on Arab populations exposed to Waterpipe (WP) tobacco smoke have been undertaken. Here Polymerase Chain Reaction-Restriction Fragment Length Polymorphism (PCR-RFLP) and gene sequenc- ing were applied to analyze allelic variations in GSTP1-rs1695 and -rs1138272 amongst 123 lung cancer patients and 129 controls. The data suggest that WP smoking raised the risk of lung cancer more than three-fold (OR 3.6; 95% CI 2.1–6.0; p < 0.0001). However, there was no s

Abstract: The utility of DNA sequencing in diagnosing and prognosis of diseases is vital for assessing the risk of genetic disorders, particularly for asymptomatic individuals with a genetic predisposition. Such diagnostic approaches are integral in guiding health and lifestyle decisions and preparing families with the necessary foreknowledge to anticipate potential genetic abnormalities. The present study explores implementing a define-by-run deep learning (DL) model optimized using the Tree-structured Parzen estimator algorithm to enhance the precision of genetic diagnostic tools. Unlike conventional models, the define-by-run model bolsters accuracy through dynamic adaptation to data during the learning process and iterative optimization