Abstract: Word sense disambiguation (WSD) is a significant field in computational linguistics as it is indispensable for many language understanding applications. Automatic processing of documents is made difficult because of the fact that many of the terms it contain ambiguous. Word Sense Disambiguation (WSD) systems try to solve these ambiguities and find the correct meaning. Genetic algorithms can be active to resolve this problem since they have been effectively applied for many optimization problems. In this paper, genetic algorithms proposed to solve the word sense disambiguation problem that can automatically select the intended meaning of a word in context without any additional resource. The proposed algorithm is evaluated on a col

Diarrhea is one of the most commonly encountered minor ailments in the community pharmacies. It is associated with significant morbidity and mortality. However, the majority of pharmacists in Iraq did not manage diarrheal cases in a proper way. Therefore, the current study aimed to evaluate the benefit of a new mobile application (diarrhea management step by step) to improve the pharmacist's role in the management of diarrhea. The study was conducted from 21th September to 21th October 2021 using a pre-post design via a simulated patient (SP) technique. A validated diarrhea scenario was presented to each pharmacist by the SP twice, once before and the other after giving the mobile application to the pharmacist. Furthermore, pharmaci

      The aim of the present study is to compare the biochemical action of the three vaccines taken in Iraq: Pfizer Biontech, AstraZeneca Oxford and Sinopharm based on biochemical parameters. Seventy COVID-19 Iraqi patients ( males and females ) were participated in the present study and classified into 7 groups : Gc :  COVID-19 patients ( without vaccine ) , Gp₁: COVID-19 patients took one dose of Pfizer Biontech, Gp₂ : COVID-19 patients took two doses of Pfizer Biontech, Ga₁ : patients took one dose of AstraZeneca Oxford vaccine , Ga₂: patients took two doses of AstraZeneca Oxford vaccine , Gs₁ : patients took one dose of Sinopharm vaccine and Gs₂:

This case series aims to evaluate patients affected with post COVID‐19 mucormycosis from clinical presentation to surgical and pharmacological treatment to improve the disease prognosis.

This study aims to identify maternal death cases caused by Coronavirus infection 2019 pneumonia, including disease progression, fetal consequences, and the fatality cause.

Patients and methodology: A retrospective case collection of Iraqi pregnant women in their second and third trimesters diagnosed with COVID-19 pneumonia and died due to it.

The four cases were all of a young age, had a brief complaint period, and had no comorbidities. Fever, dyspnea, and fatigue were the most common symptoms. Hypoxia was present in all cases and was the cause of mortality in three cases, with thromboembolism being a potential cause in the fourth. Prelabour membrane breakup, fetal growth restriction, and fetal death are al

The Coronavirus Disease (COVID-19) has recently emerged as a human pathogen caused by SARS-CoV-2 virus was first reported from Wuhan, China, on 31 December 2019. Upon study, it has been used molecular docking to binding affinity between COVID-19 protease enzyme and flavonoids with evaluations based on docking scores calculated by AutoDock Vina. Results showed that naringin suppressed COVID-19 protease, as it has the highest binding value than other flavonoids including quercetin, hesperetin, garcina and naringenin. An important finding in this study is that naringin with neighboring poly hydroxyl groups can serve as inhibitors of COVID-19 protease bind to the S pocket of protein, it is shown that residues His163, Glu166, Asn142, His41and

Empirical and statistical methodologies have been established to acquire accurate permeability identification and reservoir characterization, based on the rock type and reservoir performance. The identification of rock facies is usually done by either using core analysis to visually interpret lithofacies or indirectly based on well-log data. The use of well-log data for traditional facies prediction is characterized by uncertainties and can be time-consuming, particularly when working with large datasets. Thus, Machine Learning can be used to predict patterns more efficiently when applied to large data. Taking into account the electrofacies distribution, this work was conducted to predict permeability for the four wells, FH1, FH2, F

Advanced strategies for production forecasting, operational optimization, and decision-making enhancement have been employed through reservoir management and machine learning (ML) techniques. A hybrid model is established to predict future gas output in a gas reservoir through historical production data, including reservoir pressure, cumulative gas production, and cumulative water production for 67 months. The procedure starts with data preprocessing and applies seasonal exponential smoothing (SES) to capture seasonality and trends in production data, while an Artificial Neural Network (ANN) captures complicated spatiotemporal connections. The history replication in the models is quantified for accuracy through metric keys such as m

Objective: To assess role of obesity in Covid-19 patients on antibodies production, diabetes development, and treatment of this disease. Methodology: This observational study included 200 Covid-19 patients in privet centers from January 1, 2021 to January 1, 2022. All patients had fasting blood sugars and anti-Covid-19 antibodies. Anthropometric parameters were measured in all participants. Results: The patients were divided into two groups according to body weight; normal body weight (50) and excess body weight (150). There was a significant difference between them regarding age. Diabetes mellitus developed in 20% of normal weight patients while 80% of excess weight patients had diabetes (p=0.0001). Antibodies production (IgM and

Objective: To assess role of obesity in Covid-19 patients on antibodies production, diabetes development, and treatment of this disease. Methodology: This observational study included 200 Covid-19 patients in privet centers from January 1, 2021 to January 1, 2022. All patients had fasting blood sugars and anti-Covid-19 antibodies. Anthropometric parameters were measured in all participants. Results: The patients were divided into two groups according to body weight; normal body weight (50) and excess body weight (150). There was a significant difference between them regarding age. Diabetes mellitus developed in 20% of normal weight patients while 80% of excess weight patients had diabetes (p=0.0001). Antibodies production (IgM and