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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 Mar 05 2017
Journal Name
Baghdad Science Journal
Adsorption of Congo Red Dye from Aqueous Solution onto Natural and Modified Bauxite Clays
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The adsorption behavior of congo red dye from its aqueous solutions was investigated onto natural and modified bauxite clays. Both bauxite and modified bauxite are primarily characterized by using, FTIR, SEM, AFM, and XRD. Several variables are studied as a function of adsorption including contact time, adsorbent weight, pH, ionic strength, particle size and temperature under batch adsorption technique. The absorbance of the solution before and after adsorption was measured spectrophotometrically. The equilibrium data fit with Langmuir model of adsorption and the linear regression coefficient R2 is found to be 0.9832 and 0.9630 for natural and modified bauxite respectively at 37.5°C which elucidate the best fitting isotherm model. The gene

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Publication Date
Thu Aug 01 2013
Journal Name
Biochemistry
Mechanistic Insights from the Binding of Substrate and Carbocation Intermediate Analogues to Aristolochene Synthase
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Publication Date
Wed Feb 01 2023
Journal Name
Journal Of Ecological Engineering
Chlorpyrifos Removal from Aqueous Solutions by Emulsion Liquid Membrane – Stability, Extraction, and Stripping Studies
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Publication Date
Sun Jun 01 2014
Journal Name
Baghdad Science Journal
Biosorption of Lead, Cadmium and Nickle from Industrial Wast water by Using Dried Macroalgae
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Biosorpion of lead (Pb), Cadmium (Cd) and Nickl(Ni) by dried biomass of Chara sp. for sample of BMP was used as alternative approach of conventional method. The range of removal percentages was between 92-97%, 70-98.7% and 46.6-96.6% for Pb, Cd and Ni respectively at 3h.Treatment time, with 300-500 mg dried weight from Chara sp. powder at pH 4, with 60 rpm at shaker. FTIR analysis showed the active groups which are responsible for sequestration of heavy metals represented by carboxyl, hydroxyl alkyl, amine and amide. The Biosorption equilibrium experiment for elements showed that the highest sorption percentage for three elements was, Pb 96.6% after 30 minute, for Cd was 100% after 15 minute and 40% to Ni after 75 minute, while the biosorp

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Publication Date
Fri Jul 07 2017
Journal Name
International Journal Of Science And Research (ijsr)
Automatic brain tumor segmentation from MRI Images using superpixels based split and Merge algorithm
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RA Ali, LK Abood, Int J Sci Res, 2017 - Cited by 2

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Publication Date
Tue Mar 31 2015
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Production and Evaluation of Liquid Hydrocarbon Fuel from Thermal Pyrolysis of Virgin Polyethylene Plastics
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   Pyrolysis of virgin polyethylene plastics was studied in order to produce hydrocarbon liquid fuel. The pyrolysis process carried out for low and high-density polyethylene plastics in open system batch reactor in temperature range of 370 to 450°C.

   Thermo-gravimetric analysis of the virgin plastics showed that the degradation ranges were between 326 and 495 °C. The results showed that the optimum temperature range of pyrolysis of polyethylene plastics that gives highest liquid yield (with specific gravity between 0.7844 and 0.7865) was 390 to 410 °C with reaction time of about 35 minutes. Fourier Transform Infrared spectroscopy gave a quite evidence that the produced hydrocarbon liquid fuel consisted ma

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Publication Date
Sat Sep 25 2021
Journal Name
International Journal Of Drug Delivery Technology
Metal Complexes of Ligand Derived from Amine Compound: Formation, Spectral Characterization, and Biological Evaluation
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A new set of metal complexes by the general formula [M(C)2(H2O)2]Cl2 has been prepared through the interaction of the new Ligand [N1, N4-bis(4-chlorophenyl)succinamide] (C) derived from succinyl chloride with 4-Chloroaniline with the transition metal ions Mn(II), Co(II), Ni(II), Hg(II), Cu(II) and Cd(II). Compounds diagnosed by TGA, 1 H, 13CNMR and Mass spectra (for (C)), Fourier-transform infrared and Electronic spectrum, Magnetic measurement, molar conduct, (%M, %C, %H, %N). These measurements indicate that (C) is associated with the metal ion in a bi-dentate fashion by nitrogen atoms (the amide group) and the octahedral composition of these complexes is suggested. The anti-bacterial action of the compounds towards three types of bacteria

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Publication Date
Tue Aug 15 2023
Journal Name
Sumer 1
Biologically synthesized Copper Nanoparticles from S. epidermidis on resistant S. aureus and cytotoxic assay
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The risk of significant concern is resistance to antibiotics for public health. The alternative treatment of metallic nanoparticles (NPs), such as heavy metals, effects on antibiotic resistance bacteria with different types of antibiotics of - impossible to treat using noval eco-friendly synthesis technique nanoparticles copper oxide (CuO NPs) preparation from S. epidermidis showed remarkable antimicrobial activity against S.aureus Minimum inhibitory concentra range (16,32,64,256,512) µg/ml via well diffusion method in vitro, discover those concentrations effected in those bacteria and the best concentration is 64 µg/ml, characterization CuO NPs to prove this included atomic force microscope, UV, X-ray Diffraction and TEM, and ant

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Publication Date
Mon Jan 12 2026
Journal Name
Babcock University Medical Journal
Evaluation and effectiveness of sulfur nanoparticles against colon cancer prepared from capsicum plant extract
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Objective: Using green chemistry, an effective, inexpensive, and environmentally safe method, sulfur nanoparticles with specific properties can be prepared and used in nanotechnology. This research aimed to prepare sulfur nanoparticles from chilli pepper extract and determine their effectiveness against colon cancer. Method: Chilli pepper extract obtained from local markets was treated with aqueous sodium thiosulfate (Na2S2O7.5H2O). After mixing, it was continuously stirred, heated, and filtered. NaBH4 was then added, resulting in a yellow precipitate. The precipitate was centrifuged, purified, and dried at 250°C. Results: Standardised tests such as UV-Vis, XRD, SEM, TEM, AFM, and EDX were used, resulting in sulfur nanoparticles with an av

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Publication Date
Fri Mar 29 2024
Journal Name
Iraqi Journal Of Science
Evaluating the Performance and Behavior of CNN, LSTM, and GRU for Classification and Prediction Tasks
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     Deep learning (DL) plays a significant role in several tasks, especially classification and prediction. Classification tasks can be efficiently achieved via convolutional neural networks (CNN) with a huge dataset, while recurrent neural networks (RNN) can perform prediction tasks due to their ability to remember time series data. In this paper, three models have been proposed to certify the evaluation track for classification and prediction tasks associated with four datasets (two for each task). These models are CNN and RNN, which include two models (Long Short Term Memory (LSTM)) and GRU (Gated Recurrent Unit). Each model is employed to work consequently over the two mentioned tasks to draw a road map of deep learning mod

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