Abstract Background: The novel coronavirus 2 (SARS?CoV?2) pandemic is a pulmonary disease, which leads to cardiac, hematologic, and renal complications. Anticoagulants are used for COVID-19 infected patients because the infection increases the risk of thrombosis. The world health organization (WHO), recommend prophylaxis dose of anticoagulants: (Enoxaparin or unfractionated Heparin for hospitalized patients with COVID-19 disease. This has created an urgent need to identify effective medications for COVID-19 prevention and treatment. The value of COVID-19 treatments is affected by cost-effectiveness analysis (CEA) to inform relative value and how to best maximize social welfare through evidence-based pricing decisions. O

Abstract

Background: The novel coronavirus 2 (SARS?CoV?2) pandemic is a pulmonary disease, which leads to cardiac, hematologic, and renal complications. Anticoagulants are used for COVID-19 infected patients because the infection increases the risk of thrombosis. The world health organization (WHO), recommend prophylaxis dose of anticoagulants: (Enoxaparin or unfractionated Heparin for hospitalized patients with COVID-19 disease. This has created an urgent need to identify effective medications for COVID-19 prevention and treatment. The value of COVID-19 treatments is affected by cost-effectiveness analysis (CEA) to inform relative value and how to best maximize social welfare through eviden

It is well known that the rate of penetration is a key function for drilling engineers since it is directly related to the final well cost, thus reducing the non-productive time is a target of interest for all oil companies by optimizing the drilling processes or drilling parameters. These drilling parameters include mechanical (RPM, WOB, flow rate, SPP, torque and hook load) and travel transit time. The big challenge prediction is the complex interconnection between the drilling parameters so artificial intelligence techniques have been conducted in this study to predict ROP using operational drilling parameters and formation characteristics. In the current study, three AI techniques have been used which are neural network, fuzzy i

Visualization of subsurface geology is mainly considered as the framework of the required structure to provide distribution of petrophysical properties. The geological model helps to understand the behavior of the fluid flow in the porous media that is affected by heterogeneity of the reservoir and helps in calculating the initial oil in place as well as selecting accurate new well location. In this study, a geological model is built for Qaiyarah field, tertiary reservoir, relying on well data from 48 wells, including the location of wells, formation tops and contour map. The structural model is constructed for the tertiary reservoir, which is an asymmetrical anticline consisting of two domes separated by a saddle. It is found that

The aim of this study is interpretation well logs to determine Petrophysical properties of tertiary reservoir in Khabaz oil field using IP software (V.3.5). The study consisted of seven wells which distributed in Khabaz oilfield. Tertiary reservoir composed from mainly several reservoir units. These units are : Jeribe, Unit (A), Unit (A'), Unit (B), Unit (BE), Unit (E),the Unit (B) considers best reservoir unit because it has good Petrophysical properties (low water saturation and high porous media ) with high existence of hydrocarbon in this unit. Several well logging tools such as Neutron, Density, and Sonic log were used to identify total porosity, secondary porosity, and effective porosity in tertiary reservoir. For

The aim of this study is to propose reliable equations to estimate the in-situ concrete compressive strength from the non-destructive test. Three equations were proposed: the first equation considers the number of rebound hummer only, the second equation consider the ultrasonic pulse velocity only, and the third equation combines the number of rebound hummer and the ultrasonic pulse velocity. The proposed equations were derived from non-linear regression analysis and they were calibrated with the test results of 372 concrete specimens compiled from the literature. The performance of the proposed equations was tested by comparing their strength estimations with those of related existing equations from literature. Comparis

The haplotype association analysis has been proposed to capture the collective behavior of sets of variants by testing the association of each set instead of individual variants with the disease.Such an analysis typically involves a list of unphased multiple-locus genotypes with potentially sparse frequencies in cases and controls.It starts with inferring haplotypes from genotypes followed by a haplotype co-classification and marginal screening for disease-associated haplotypes.Unfortunately,phasing uncertainty may have a strong effects on the haplotype co-classification and therefore on the accuracy of predicting risk haplotypes.Here,to address the issue,we propose an alternative approach:In Stage 1,we select potential risk genotypes inste

Vitamin K-dependent protein (VKDP) contributes to the development of lung cancer. The purpose of this research was to better understanding of the role of blood matrix Gla protein (MGP), VKDPs, Malondialdehyde (MDA), Superoxide dismutase (SOD) and Vitamin K (Vit K) in Iraqi patients with lung cancer before and after the first cycle of chemotherapy. Blood samples were collected from Al amal National Hospital for cancer treatment from October 2021 to May 2022, and a total of 80 samples were collected, divided into two groups (40 patient before taking a chemotherapy and 40 patients after taking chemotherapy), ranging in age from 20 to 45 years old. The results showed that although there were highly statistically significant differences in MD