Detecting the optimum layer for well placement, which requires a diverse assortment of tools and techniques, represents a significant challenge in petroleum studies due to its critical impact on minimizing drilling costs and time. This study aims to evaluate integrated geological, petrophysical, seismic, and geomechanical data to identify the optimum zones for well placement. Three different reservoirs were analyzed to account for lateral and vertical variations in reservoir properties. The integrated data from these reservoirs provides many tools for reservoir development, especially to detect appropriate well placement zones based on evaluations of reservoir and geomechanical quality. The Mechanical Earth Model (MEM) was construct

After baking the flour, azodicarbonamide, an approved food additive, can be converted into carcinogenic semicarbazide hydrochloride (SEM) and biurea in flour products. Thus, determine SEM in commercial bread products is become mandatory and need to be performed. Therefore, two accurate, precision, simple and economics colorimetric methods have been developed for the visual detection and quantitative determination of SEM in commercial flour products. The 1st method is based on the formation of a blue-coloured product with λmax at 690 nm as a result of a reaction between the SEM and potassium ferrocyanide in an acidic medium (pH 6.0). In the 2nd method, a brownish-green colored product is formed due to the reaction between the SEM and phosph

Abortion is a condition that occurs due to one of the pathological injuries, often one of the members of the TORCH is the real cause. The current study aimed to investigate the impact of toxoplasmosis, HSV-2 infections with abortion, and also, the identification of immunogenetics marker (interleukin-10) that may be associated with abortion. Anti-Toxoplasma IgG, IgM, Herpes simplex virus-2 IgM, human soluble leukocyte antigen class I–G and interleukin10 were estimated by ELISA technique, while the expression of IL-10 gene was investigated by using the real-time PCR. The results showed that among aborted women the rate of anti-Toxoplasma and HSV-2 IgM antibodies occurred within the age groups (21–30) years and (31–40) years 32(100.0%) a

Introduction: Inadequate pain assessment and management is a problem in hospitalized patients that impairs their wellbeing. Intensive care unit nurses’ pain practices are affected by several barriers and enablers. Objectives: The objectives of this study were to determine the level of nurses’ practices and perceived barriers related to pain assessment in critically ill patients. Methodology: A cross-sectional design study was used. Purposive sampling technique was employed, including 100 nurses recruited from 8 intensive care units in Baghdad city, Iraq. The study was conducted from September 1st to October 20th, 2022. The pain assessment and management for critically ill patients survey was used to collect data. Descriptive sta

In this study, thin film of pure zinc oxide (ZnO) and ZnO doped with Ga2O3 films with different concentrations (0, 0.03, 0.05, 0.07 and 0.09)wt% were prepared by pulsed laser deposition. The powder mixture was then sintered in a furnace at 1273 K for 5 h. The resulting powders were thoroughly ground and then pressed using a special press to form discs with a diameter of 1 cm and a thickness of 0.5 cm. The deposition was carried out under a vacuum of 2.5×10−2 mbar on various substrates, including glass for AFM measurements and n-type crystalline silicon wafers for the gas sensor. AFM results revealed a progressive increase in both grain size and roughness with moderate doping and irregularity at high doping levels. Gas-sensing meas

Background/Objectives: Early and accurate discrimination of neurological conditions, dementia, stroke and healthy aging, remains a critical clinical challenge. Electroencephalography (EEG) is a non-invasive measure of brain dynamics and entropy-based features obtained from multichannel EEG have shown strong discriminative ability. However, existing deep learning approaches do not sufficiently address the combined challenges of small clinical cohorts and high-dimensional entropy feature spaces. In this study, a novel architecture is proposed for multi-class neurological EEG classification under extreme small-sample conditions. Methods: A novel dual-branch Channel-wise Transformer and Attention-Branch Network (EEG-ChTABNet) are pr to