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TOTAL ORGANIC CARBON (TOC) PREDICTION FROM RESISTIVITY AND POROSITY LOGS: A CASE STUDY FROM IRAQ
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     The open hole well log data (Resistivity, Sonic, and Gamma Ray) of well X in Euphrates subzone within the Mesopotamian basin are applied to detect the total organic carbon (TOC) of Zubair Formation in the south part of Iraq. The mathematical interpretation of the logs parameters helped in detecting the TOC and source rock productivity. As well, the quantitative interpretation of the logs data leads to assigning to the organic content and source rock intervals identification. The reactions of logs in relation to the increasing of TOC can be detected through logs parameters. By this way, the TOC can be predicted with an increase in gamma-ray, sonic, neutron, and resistivity, as well as a decrease in the density log. In calculating TOC content, sonic/resistivity overlay technique was used. The results detected that the upper and lower parts (3300-3460 and 3570-3700 respectively) of the formation were the principal source rock in this location. The TOC results from logs are ranged respectively from 1-6 and 1-4 wt % for the upper and lower parts from the formation. These results are compared with TOC from (58) samples of Rock -Eval Pyrolysis, which showed a close pattern of increasing and decreasing in TOC values. This comparison was made so as to enhance the results of this technique. In addition, this tool revealed the possible lithology of the studied intervals, where the logs originally would give an indication to the lithology, as such high TOC is significant to relatively low energy environments. TOC calculation showed that the upper and lower packages represent source-seal rocks, while the middle had good reservoir properties. This relation may indicate a locally stratigraphic trap, and a need for further detailed studies.

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Publication Date
Sun Oct 15 2023
Journal Name
Bionatura
Synthesis, Characterization and Evaluation of the Biological Activity of Some New Thiazolidine Derivatives Derived from Schiff bases
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In this research, new compounds were synthesized via the reaction of dichloroacetic acid with two moles of piperidine. The novel acid 1 was converted to its ester 2. Acid hydrizide 3 was prepared by the reaction of hydrazine hydrate with new ester 2, which was later used to prepare derivatives of Schiff bases 4-13. In the last step, Schiff bases and thioglycolic acid were reacted to give thiazolidine derivatives 14-23. All these compounds were diagnosed using melting points, FTIR, 1HNMR and mass spectroscopy. Scheme 1 shows all the synthesized compounds' reaction steps and structures. Keywords: Thiazolidine; Schiff bases; biological activity; piperidine; dichloroacetic acid.

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Publication Date
Sat Jul 20 2024
Journal Name
Ibn Al-haitham Journal For Pure And Applied Science
Synthesis, Characterization of Nickel Cobaltite Nanoparticles and Its Use in Removal Methyl Green Dye from Aqueous Solution
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In this study, nickel cobaltite (NC) nanoparticles were created using the sol-gel process and used as an adsorbent to adsorb methyl green dye (MG) from aqueous solutions. The adequate preparation of nickel cobaltite nanoparticles was verified using FT-IR, SEM, and X-ray diffraction (XRD) studies. The crystalline particle size of NC nanoparticles was 10.53 nm. The effects of a number of experimental variables, such as temperature, adsorbent dosage, and contact time, were examined. The optimal contact time and adsorbent dosage were 120 minutes and 4.5 mg/L, respectively. Four kinetic models—an intraparticle diffusion, a pseudo-first-order equation, a pseudo-second-order equation, and the Boyd equation—were employed to monitor the adsorpti

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Publication Date
Sat Feb 01 2020
Journal Name
International Journal Of Computer Science And Mobile Computing
Hierarchical Fixed Prediction of Mixed based for Medical Image Compression.
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Publication Date
Sat May 01 2021
Journal Name
Journal Of Physics: Conference Series
The Prediction of COVID 19 Disease Using Feature Selection Techniques
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Abstract<p>COVID 19 has spread rapidly around the world due to the lack of a suitable vaccine; therefore the early prediction of those infected with this virus is extremely important attempting to control it by quarantining the infected people and giving them possible medical attention to limit its spread. This work suggests a model for predicting the COVID 19 virus using feature selection techniques. The proposed model consists of three stages which include the preprocessing stage, the features selection stage, and the classification stage. This work uses a data set consists of 8571 records, with forty features for patients from different countries. Two feature selection techniques are used in </p> ... Show More
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Publication Date
Mon Mar 13 2017
Journal Name
Journal Of Baghdad College Of Dentistry
Computer Assisted Immunohistochemical Score Prediction Via Simplified Image Acquisition Technique
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Background: techniques of image analysis have been used extensively to minimize interobserver variation of immunohistochemical scoring, yet; image acquisition procedures are often demanding, expensive and laborious. This study aims to assess the validity of image analysis to predict human observer’s score with a simplified image acquisition technique. Materials and methods: formalin fixed- paraffin embedded tissue sections for ameloblastomas and basal cell carcinomas were immunohistochemically stained with monoclonal antibodies to MMP-2 and MMP-9. The extent of antibody positivity was quantified using Imagej® based application on low power photomicrographs obtained with a conventional camera. Results of the software were employed

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Publication Date
Tue Sep 01 2020
Journal Name
Al-khwarizmi Engineering Journal
Prediction of Creep-Fatigue Interaction Damage for Polyamide 6,6 Composites
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    This paper aims to study the damage generated due to creep-fatigue interaction behaviors in solid polyamide 6,6 and its composites that include 1%wt of carbon nanotubes or 30% wt short carbon fiber prepared by an injection technique. The investigation also includes studying the influence of applied temperatures higher than the glass transition temperatures on mechanical properties. The obtained results showed that the addition of reinforcement materials increased all the mechanical properties, while the increase in test temperature reduced all mechanical properties, especially for polyamide 6,6. The creep-fatigue interaction resistance also improved due to the addition of reinforcement materials by inc

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Publication Date
Tue Aug 01 2023
Journal Name
Iop Conference Series: Earth And Environmental Science
Prediction of Biodegradability Possibility for Sewage of the Dairy Industry
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he dairy industry is one of the industrial activities classified within the food industries in all phases of the dairy industry, which leads to an increase in the amount of wastewater discharged from this industry. The study was conducted in the Abu Ghraib dairy factory, classified as one of the central factories in Iraq, located in the west of Baghdad governorate, with a design capacity of 22,815 tons of dairy products. The characteristics of the liquid waste generated from the factory were determined for the following parameters biological oxygen demand (BOD5), Chemical oxygen demand (COD), total suspended solids (TSS), pH, nitrate, phosphate, chloride, and sulfate with an average value of (1079, 1945, 323, 9.2, 24, 2

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Publication Date
Sun Jan 01 2023
Journal Name
8th Engineering And 2nd International Conference For College Of Engineering – University Of Baghdad: Coec8-2021 Proceedings
Prediction of consolidation due to dewatering by using MATLAB software
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Publication Date
Sun Jan 01 2023
Journal Name
Computers, Materials &amp; Continua
Hybrid Deep Learning Enabled Load Prediction for Energy Storage Systems
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Publication Date
Thu Jun 01 2023
Journal Name
Ifip Advances In Information And Communication Technology
Rapid Thrombogenesis Prediction in Covid-19 Patients Using Machine Learning
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Machine Learning (ML) algorithms are increasingly being utilized in the medical field to manage and diagnose diseases, leading to improved patient treatment and disease management. Several recent studies have found that Covid-19 patients have a higher incidence of blood clots, and understanding the pathological pathways that lead to blood clot formation (thrombogenesis) is critical. Current methods of reporting thrombogenesis-related fluid dynamic metrics for patient-specific anatomies are based on computational fluid dynamics (CFD) analysis, which can take weeks to months for a single patient. In this paper, we propose a ML-based method for rapid thrombogenesis prediction in the carotid artery of Covid-19 patients. Our proposed system aims

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