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Correlation for fitting multicomponent vapor-liquid equilibria data and prediction of azeotropic behavior
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Correlation equations for expressing the boiling temperature as direct function of liquid composition have been tested successfully and applied for predicting azeotropic behavior of multicomponent mixtures and the kind of azeotrope (minimum, maximum and saddle type) using modified correlation of Gibbs-Konovalov theorem. Also, the binary and ternary azeotropic point have been detected experimentally using graphical determination on the basis of experimental binary and ternary vapor-liquid equilibrium data.

            In this study, isobaric vapor-liquid equilibrium for two ternary systems: “1-Propanol – Hexane – Benzene” and its binaries “1-Propanol – Hexane, Hexane – Benzene and 1-Propanol – Benzene” and the other ternary system is “Toluene – Cyclohexane – iso-Octane (2,2,4-Trimethyl-Pentane)” and its binaries “Toluene – Cyclohexane, Cyclohexane – iso-Octane and Toluene – iso-Octane” have been measured at 101.325 KPa. The measurements were made in recirculating equilibrium still with circulation of both the vapor and liquid phases. The ternary system “1-Propanol – Hexane – Benzene” which contains polar compound (1-Propanol) and the two binary systems “1-Propanol – Hexane and 1-Propanol – Benzene” form a minimum azeotrope, the other ternary system and the other binary systems do not form azeotrope.

            All the data passed successfully the test for thermodynamic consistency using McDermott-Ellis test method (McDermott and Ellis, 1965).

            The maximum likelihood principle is developed for the determination of correlations parameters from binary and ternary vapor-liquid experimental data which provides a mathematical and computational guarantee of global optimality in parameters estimation for the case where all the measured variables are subject to errors and the non ideality of both vapor and liquid phases for the experimental data for the ternary and binary systems have been accounted.

            The agreement between prediction and experimental data is good. The exact value should be determined experimentally by exploring the concentration region indicated by the computed values.

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Publication Date
Tue Oct 01 2019
Journal Name
Journal Of Engineering
Mechanisms of Plant-Correlation Phytoremediation of Al-Daura Iraqi Refinery Wastewater Using Wetland Plant from Tigris River
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In developing countries, conventional physico-chemical methods are commonly used for removing contaminants. These methods are not efficient and very costly. However, new in site strategy with high treatment efficiency and low operation cost named constructed wetland (CW) has been set. In this study, Phragmites australis was used with free surface batch system to estimate its ability to remediate total
petroleum hydrocarbons (TPH) and chemical oxygen demand (COD) from Al-Daura refinery wastewater. The system operated in semi-batch, thus, new wastewater was weekly added to the plant for 42 days. The results showed high removal percentages (98%) of TPH and (62.3%) for COD. Additionally, Phragmites australis biomass increased significant

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Publication Date
Mon Mar 31 2025
Journal Name
International Journal Of Advanced Technology And Engineering Exploration
Breast cancer survival rate prediction using multimodal deep learning with multigenetic features
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Breast cancer is a heterogeneous disease characterized by molecular complexity. This research utilized three genetic expression profiles—gene expression, deoxyribonucleic acid (DNA) methylation, and micro ribonucleic acid (miRNA) expression—to deepen the understanding of breast cancer biology and contribute to the development of a reliable survival rate prediction model. During the preprocessing phase, principal component analysis (PCA) was applied to reduce the dimensionality of each dataset before computing consensus features across the three omics datasets. By integrating these datasets with the consensus features, the model's ability to uncover deep connections within the data was significantly improved. The proposed multimodal deep

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Publication Date
Thu Oct 31 2024
Journal Name
Iraqi Geological Journal
Artificial Neural Network Application to Permeability Prediction from Nuclear Magnetic Resonance Log
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Reservoir permeability plays a crucial role in characterizing reservoirs and predicting the present and future production of hydrocarbon reservoirs. Data logging is a good tool for assessing the entire oil well section's continuous permeability curve. Nuclear magnetic resonance logging measurements are minimally influenced by lithology and offer significant benefits in interpreting permeability. The Schlumberger-Doll-Research model utilizes nuclear magnetic resonance logging, which accurately estimates permeability values. The approach of this investigation is to apply artificial neural networks and core data to predict permeability in wells without a nuclear magnetic resonance log. The Schlumberger-Doll-Research permeability is use

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Publication Date
Fri Jun 30 2017
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Waste Water Treatment by Liquid-Solid Adsorption Using Calcined Sand-Clay Mixture Adsorbent
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Effluent from incompetent wastewater treatment plants (WWTPs) contains a great variety of pollutants so support water treatments are essential. The present work studies the removal of phosphate species from aqueous solutions by adsorption on to spherical Calcined Sand -Clay mixture (CSCM) used a natural, local and low-cost adsorbent. Batch experiments were performed to estimate removal efficiency of phosphate. The adsorption experiments were carried out as function of pH, dose of adsorbent, initial concentration, temperature and time of adsorption. The efficient removal was accomplished for pH between 10 and 12. The experimental results also showed that the removal of phosphate by (CSCM) was rapid (the % removal 98.9%, 92%, 90%, 89% in 6

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Publication Date
Wed Aug 30 2023
Journal Name
Baghdad Science Journal
Hepatocellular Carcinoma Prediction and early Diagnosis of Hepatitis B and C viral infection using miR-122 and miR-223 in a sample of Iraqi patients.
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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

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Publication Date
Thu Jan 01 2009
Journal Name
Arab Journal Of Gasteroenterology
Serum HCV-RNA levels in patients with chronic hepatitis C: correlation with histological features.
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Publication Date
Wed Dec 14 2016
Journal Name
Journal Of Baghdad College Of Dentistry
Correlation between Periodontal Health Status and Salivary Matrix Metalloproteinase-9 Levels in Smoker and Non-Smoker Chronic Periodontitis Patients (A Comparative Study)
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Background: Periodontal diseases are inflammatory diseases affecting the supporting tissues of the teeth. One of the leading environmental factors that are closely related not only to the risk but also to the prognosis of periodontitis is smoking. This study aimed to evaluate the influence of smoking on periodontal health status and to measure the levels of matrix metalloproteinase-9 in smokers and nonsmokers chronic periodontitis patients, also it aimed to test the correlation between the levels of matrix metalloproteinase-9 and the clinical periodontal parameters. Materials and Methods: Five milliliters samples of un-stimulated whole saliva and full-mouth clinical periodontal recordings (plaque index, gingival index, bleeding on probing,

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Publication Date
Sat Oct 01 2016
Journal Name
2016 2nd International Conference On Science In Information Technology (icsitech)
Cloud computing sensitive data protection using multi layered approach
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Publication Date
Sun Dec 31 2023
Journal Name
International Journal On Technical And Physical Problems Of Engineering
A Multiple System Biometric System Based on ECG Data
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A Multiple System Biometric System Based on ECG Data

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Publication Date
Thu Oct 01 2015
Journal Name
Journal Of Economics And Administrative Sciences
Estimation Multivariate data points in spatial statistics with application
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This paper  deals  to how to estimate points non measured spatial data when the number of its terms (sample spatial) a few, that are not preferred for the estimation process, because we also know that whenever if the data is large, the estimation results of the points non measured to be better and thus the variance estimate less, so the idea of this paper is how to take advantage of the data other secondary (auxiliary), which have a strong correlation with the primary data (basic) to be estimated single points of non-measured, as well as measuring the variance estimate, has been the use of technique Co-kriging in this field to build predictions spatial estimation process, and then we applied this idea to real data in th

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