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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 used to train the model, where the model prediction result is validated with core permeability. Seven oil well logs were used as input parameters, and the model was constructed with Techlog software. The predicted permeability with the model compared with Schlumberger-Doll-Research permeability as a cross plot, which results in the correlation coefficient of 94%, while the predicted permeability validated with the core permeability of the well, which obtains good agreement where R2 equals 80%. The model was utilized to forecast permeability in a well that did not have a nuclear magnetic resonance log, and the predicted permeability was cross-plotted against core permeability as a validation step, with a correlation coefficient of 77%. As a result, the low percentage of matching was due to data limitations, which demonstrated that as the amount of data used to train the model increased, so did the precision.

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Publication Date
Wed Aug 01 2018
Journal Name
Journal Of Research In Medical And Dental Science
Evaluation of Bond Strength of Acrylic Artificial Teeth with Unreinforced and Nano Silica Reinforced Denture Base Material after Chemical Disinfection
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Soaking dentures with disinfection solutions is an effective way of keeping dentures in a healthy status; however, immersions in these solutions have a negative effect on the bond strength of denture base and denture teeth. The aim of this study was to evaluate the bond strength between denture acrylic teeth and heat-cured Poly (methyl methacrylate) denture base material (with and without nano silica) after disinfection with different chemical disinfectants for a simulated period of six months. One hundred specimens of maxillary central incisors attached to PMMA were divided into two groups; 50 specimens of PMMA without nano silica and 50 specimens of PMMA reinforced with 5 wt% of nano silica. Specimens of each group were immersed in five i

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Publication Date
Mon Jul 01 2024
Journal Name
Ecological Engineering & Environmental Technology
Use of Nano Co-Ni-Mn Composite and Aluminum for Removal of Artificial Anionic Dye Congo Red by Combined System
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The removal of congo red (CR) is a critical issue in contemporary textile industry wastewater treatment. The current study introduces a combined electrochemical process of electrocoagulation (EC) and electro-oxidation (EO) to address the elimination of this dye. Moreover, it discusses the formation of a triple composite of Co, Mn, and Ni oxides by depositing fixed salt ratios (1:1:1) of these oxides in an electrolysis cell at a constant current density of 25 mA/cm2. The deposition ended within 3 hours at room temperature. X-ray diffractometer (XRD), field emission scanning electron microscopy (FESEM), atomic force microscopy (AFM), and energy dispersive X-ray (EDX) characterized the structural and surface morphology of the multi-oxide sedim

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Publication Date
Wed Feb 21 2024
Journal Name
Al-rafidain Journal Of Medical Sciences ( Issn 2789-3219 )
Perceptions of Senior Pharmacy Students Towards the Impact of Artificial Intelligence on University Education and Scientific Writing: A Qualitative Study
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Background: The roles of AI in the academic community continue to grow, especially in the enhancement of learning outcomes and the improvement of writing quality and efficiency. Objectives: To explore in depth the experience of senior pharmacy students in using artificial intelligence for academic purposes. Methods: This qualitative study included face-to-face individual interviews with senior pharmacy students from March to May 2023 using a pre-planned interview guide of open-ended questions. All interviews were audio-recorded. Thematic analysis was used to analyze the data. Results: The results were obtained from 15 in-depth face-to-face interviews with senior pharmacy students (5th and 4th years). Eight participants were male, and seven

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Publication Date
Sun Dec 18 2022
Journal Name
Journal Of The College Of Languages (jcl)
The Challenges of Translation from Persian to Arabic In Light of the Equivalence Theory of Mona Baker; Equivalence at the Word Level
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This dissertation studies the application of equivalence theory developed by Mona Baker in translating Persian to Arabic. Among various translation methodologies, Mona Baker’s bottom-up equivalency approach is unique in several ways. Baker’s translation approach is a multistep process. It starts with studying the smallest linguistic unit, “the word”, and then evolves above the level of words leading to the translation of the entire text. Equivalence at the word level, i.e., word for word method, is the core point of Baker’s approach.

This study evaluates the use of Baker’s approach in translation from Persian to Arabic, mainly because finding the correct equivalence is a major challenge in this translation. Additionall

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Publication Date
Fri Aug 28 2020
Journal Name
International Journal Of Molecular Sciences
Δ9-Tetrahydrocannabinol Prevents Mortality from Acute Respiratory Distress Syndrome through the Induction of Apoptosis in Immune Cells, Leading to Cytokine Storm Suppression
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Acute Respiratory Distress Syndrome (ARDS) causes up to 40% mortality in humans and is difficult to treat. ARDS is also one of the major triggers of mortality associated with coronavirus-induced disease (COVID-19). We used a mouse model of ARDS induced by Staphylococcal enterotoxin B (SEB), which triggers 100% mortality, to investigate the mechanisms through which Δ9-tetrahydrocannabinol (THC) attenuates ARDS. SEB was used to trigger ARDS in C3H mice. These mice were treated with THC and analyzed for survival, ARDS, cytokine storm, and metabolome. Additionally, cells isolated from the lungs were used to perform single-cell RNA sequencing and transcriptome analysis. A database analysis of human COVID-19 patients was also performed t

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Publication Date
Tue Dec 01 2015
Journal Name
Journal Of Al-nahrain University-science
Synthesis of Polyacrylamides from Derivatives 2-Aminobenzothiazole and also Preparation of Dibutylphthalate as a Plasticizer to Estimate Plasticization Behaviour for Prepared Polymers
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Publication Date
Tue Jan 01 2019
Journal Name
Journal Of Global Pharma Technology
Study of the genetic diversity in three species belonging to family: Daphniidae (Crustaceae, Cladocera) collected from different regions in Baghdad Province/Iraq
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Publication Date
Tue Mar 01 2016
Journal Name
Journal Of Engineering
Prediction of Raw Water Turbidity at the Intakes of the Water Treatment Plants along Tigris River in Baghdad, Iraq using Frequency Analysis
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Different frequency distributions models were fitted to the monthly data of raw water Turbidity at water treatment plants (WTPs) along Tigris River in Baghdad. Eight water treatment plants in Baghdad were selected, with raw water turbidity data for the period (2008-2014). The frequency distribution models used in this study are the Normal, Log-normal, Weibull, Exponential and two parameters Gamma type. The Kolmogorov-Smirnov test was used to evaluate the goodness of fit. The data for years (2008-2011) were used for building the models. The best fitted distributions were Log-Normal (LN) for Al-Karkh, Al-Wathbah, Al-Qadisiya, Al- Dawrah and, Al-Rashid WTPs. Gamma distribution fitted well for East Tigris and Al-Karamah WTPs. As for Al-

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Publication Date
Fri Dec 23 2022
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
Descriptive, Prospective Observational Study- Studying Possible Prediction Factors for Disease Severity and Progression among a Sample of COVD 19 Patients in Iraq
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Abstract

Coronavirus has affected many people around the world and caused an increase in the number of hospitalized patients and deaths. The prediction factor may help the physician to classify whether the patient needs more medical attention to decrease mortality and worsening of symptoms. We aimed to study the possible relationship between C reactive protein level and the severity of symptoms and its effect on the prognosis of the disease. And determine patients who require closer respiratory monitoring and more aggressive supportive therapies to avoid poor prognosis. The data was gathered using medical record data, the patient's medical history, and the onset of symptoms, as well as a blood sample to test the

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Publication Date
Tue Mar 01 2016
Journal Name
Journal Of Engineering
Prediction of Raw Water Turbidity at the Intakes of the Water Treatment Plants along Tigris River in Baghdad, Iraq using Frequency Analysis
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Different frequency distributions models were fitted to the monthly data of raw water Turbidity at water treatment plants (WTPs) along Tigris River in Baghdad. Eight water treatment plants in Baghdad were selected, with raw water turbidity data for the period (2008-2014). The frequency distribution models used in this study are the Normal, Log-normal, Weibull, Exponential and two parameters Gamma type. The Kolmogorov-Smirnov test was used to evaluate the goodness of fit.  The data for years (2008-2011) were used for building the models. The best fitted distributions were Log-Normal (LN) for Al-Karkh, Al-Wathbah, Al-Qadisiya, Al-Dawrah and, Al-Rashid WTPs. Gamma distribution fitted well for East Tigris and Al-Karamah

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