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bsj-3416
Role of Carbon Dioxide on the Corrosion of Carbon Steel Reinforcing Bar in Simulating Concrete Electrolyte
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The main factors that make it possible to get the corrosion of reinforcing steel in concrete are chloride ions and the absorption of carbon dioxide from the environment, and each of them works with a mechanism which destroys the stable immunity of rebar in the concrete. In this work the effect of carbon dioxide content in the artificial concrete solution on the corrosion behavior of carbon steel reinforcing bar (CSRB) was studied, potentiostatically using CO2 stream gas at 6 level of concentrations;  0.03 to 2.0  weight percent, and the effect of rising electrolyte temperature was also followed  in the range 20 to 50ᴼ C. Tafel plots and cyclic polarization procedures were obeyed to investigate the corrosion parameters and pitting susceptibility respectively. The change in the microstructure and morphology of the CSRB after polarization in the simulate concrete solution was studied using optical and atomic force microscopes. The results show that the corrosion rate of the CSRB in artificial concrete greatly increases with the existence of CO2 gas and highly depends on its concentration in the range 0.03 to 2.0% .No sign for pitting corrosion is recorded at all CO2 concentrations and the general corrosion is the main problem in the conditions under consideration.  

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Publication Date
Sun Mar 01 2009
Journal Name
Baghdad Science Journal
Synthesis and Characterization of Tripodal Tetradentate Ligand Type NS3 and its Complexes with Re(V), Ni(II), Cu(II), Zn(II), Cd(II), and Hg(II)
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This work represents the preparation of the starting material, 3-chloro-2-oxo-1,4-dithiacyclohexane (S) using a new method. This material was reacted with, 4-phenylthiosemicarbazide to give (H3NS3) as a tetradentate ligand H3L. New complex of rhenium (V) with this ligand of the formula [ReO(L)] was prepared. New complexes of the general formula [M(HL)] of this ligand when reacted with some metal ions where: M = Ni(II), Cu(II), Cd(II), Zn(II), Hg(II) have been reported. The ligand and the complexes were characterized by infrared, ultraviolet–visible, mass, 1H nuclear magnetic resonance and atomic absorption spectroscopic techniques and by (HPLC), elemental analysis, and electrical conductivity. The proposed structure for H3L with Re (V) i

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Publication Date
Fri Sep 01 2023
Journal Name
Journal Of Molecular Structure
Synthesis, spectral studies, DFT, biological evaluation, molecular docking and dyeing performance of 1-(4-((2-amino-5-methoxy)diazenyl)phenyl) ethanone complexes with some metallic ions
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Four Co(II), (C1); Ni(II), (C2); Cu(II), (C3) and Zn(II), (C4) chelates have been synthesized with 1-(4-((2-amino- 5‑methoxy)diazenyl)phenyl)ethanone ligand (L). The produced compounds have been identified by using spectral studies, elemental analysis (C.H.N.O), conductivity and magnetic properties. The produced metal chelates were studied using molar ratio as well as sequences contrast types. Rate of concentration (1 ×10􀀀 4 - 3 ×10􀀀 4 Mol/L) sequence Beer’s law. Compound solutions have been noticed height molar absorptivity. The free of ligand and metal chelates had been applied as disperse dyes on cotton fabrics. Furthermore, the antibacterial activity of the produced compounds against various bacteria had been investigated. F

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Publication Date
Fri Sep 01 2023
Journal Name
Journal Of Molecular Structure
Synthesis, spectral studies, DFT, biological evaluation, molecular docking and dyeing performance of 1-(4-((2-amino-5-methoxy)diazenyl)phenyl) ethanone complexes with some metallic ions
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Publication Date
Sat Sep 23 2017
Journal Name
Oriental Journal Of Chemistry
Synthesis and Antioxidant Ability of some new 6-amino-7H- [1,2,4]triazolo[3,4-b][1,3,4]thiadiazin-3-yl) derivatives bearing 2,6-dimethoxy-4-(methoxymethyl)phenol moiety
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Compound 4-(((6-amino-7H-[1, 2, 4] triazolo [3, 4-b][1, 3, 4] thiadiazin-3-yl) methoxy) methyl)-2, 6-dimethoxyphenol (6) was synthesized by multi steps. The corresponding acetonitrile thioalkyl (7) was cyclized by refluxing with acetic acid to afford 4-(((6-amino-7H-[1, 2, 4] triazolo [3, 4-b][1, 3, 4] thiadiazin-3-yl) methoxy) methyl)-2, 6-dimethoxyphenol (8). Two new series of 4-(((6-(3-(4-aryl) thioureido)-7H-[1, 2, 4] triazolo [3, 4-b][1, 3, 4] thiadiazin-3-yl) methoxy) methyl)-2, 6-dimethoxyphenol (9a-c) and of 4-(((6-(substitutedbenzamido) 7H-[1, 2, 4] triazolo [3, 4-b][1, 3, 4] thiadiazin-3-yl) methoxy) methyl)-2, 6-dimethoxyphenol (10a-c) were synthesized as new derivatives for fused 1, 2, 4-trizaole-thiadiazine (8). The antioxidant

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Publication Date
Wed Feb 01 2023
Journal Name
Health Science Reports
Diagnostic potential of salivary interleukin‐17, RANKL, and OPG to differentiate between periodontal health and disease and discriminate stable and unstable periodontitis: A case‐control study
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Abstract<sec><title>Background and Aims

Limitations of the conventional diagnostic techniques urged researchers to seek novel methods to predict, diagnose, and monitor periodontal disease. Use of the biomarkers available in oral fluids could be a revolutionary surrogate for the manual probing/diagnostic radiograph. Several salivary biomarkers have the potential to accurately discriminate periodontal health and disease. This study aimed to determine the diagnostic sensitivity and specificity of salivary interleukin (IL)‐17, receptor activator of nuclear factor‐κB ligand (RANKL), osteoprotegerin (OPG), RANKL/OPG for differentiating (1) periodontal health from disease and (2) stable a

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Publication Date
Wed Nov 29 2023
Journal Name
International Journal Of Advances In Scientific Research And Engineering (ijasre), Issn:2454-8006, Doi: 10.31695/ijasre
Yolo Versions Architecture: Review
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Deep learning techniques are applied in many different industries for a variety of purposes. Deep learning-based item detection from aerial or terrestrial photographs has become a significant research area in recent years. The goal of object detection in computer vision is to anticipate the presence of one or more objects, along with their classes and bounding boxes. The YOLO (You Only Look Once) modern object detector can detect things in real-time with accuracy and speed.&nbsp; A neural network from the YOLO family of computer vision models makes one-time predictions about the locations of bounding rectangles and classification probabilities for an image. In layman's terms, it is a technique for instantly identifying and recognizing

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Publication Date
Sun Jan 01 2023
Journal Name
International Journal Of Advances In Scientific Research And Engineering
Yolo Versions Architecture: Review
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Deep learning techniques are used across a wide range of fields for several applications. In recent years, deep learning-based object detection from aerial or terrestrial photos has gained popularity as a study topic. The goal of object detection in computer vision is to anticipate the presence of one or more objects, along with their classes and bounding boxes. The YOLO (You Only Look Once) modern object detector can detect things in real-time with accuracy and speed. A neural network from the YOLO family of computer vision models makes one-time predictions about the locations of bounding rectangles andclassification probabilities for an image. In layman's terms, it is a technique for instantly identifying and rec

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Publication Date
Wed Aug 17 2022
Journal Name
Applied Sciences
Predicting Fruit’s Sweetness Using Artificial Intelligence—Case Study: Orange
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The manual classification of oranges according to their ripeness or flavor takes a long time; furthermore, the classification of ripeness or sweetness by the intensity of the fruit’s color is not uniform between fruit varieties. Sweetness and color are important factors in evaluating the fruits, the fruit’s color may affect the perception of its sweetness. This article aims to study the possibility of predicting the sweetness of orange fruits based on artificial intelligence technology by studying the relationship between the RGB values of orange fruits and the sweetness of those fruits by using the Orange data mining tool. The experiment has applied machine learning algorithms to an orange fruit image dataset and performed a co

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Publication Date
Sun Jun 02 2013
Journal Name
Baghdad Science Journal
Synthesis and Spectral Studies of Co(II),Ni(II),Zn(II) and Cd(II) Complexes with Ligand 2-[4- Carboxy methyl phenyl azo] -4,5-diphenyl imidazole (4CMeI)
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A new chelate complexes of Co(II),Ni(II),Zn(II) and Cd(II) were prepared by reacting these ions with the ligand 2-[4- Carboxy methyl phenyl azo]-4,5-diphenyl imidazole (4CMeI) The preparation were conducted after fixing the optimum conditions such as (pH) and concentration .UV- visible spectra of these complex solutions were studied for a range of (pH) and concentration which obey lampert-Beers Law.The structures of complexes were deduced according to mole ratio method which were obtained from the spectroscopic studies of the complex solutions .The ratios of metal: ligand obtained were (1:2) for all complexes..(UV-Vis) absorption spectra and The infrared spectra of the chelating complexes were studied ,this may indicate that coordination be

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Publication Date
Sun Feb 03 2019
Journal Name
Iraqi Journal Of Physics
Study of charge density distributions, elastic charge form factors and root-mean square radii for 4He, 12C and 16O nuclei using Woods- Saxon and harmonic-oscillator potentials
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The nuclear charge density distributions, form factors andcorresponding proton, charge, neutron, and matter root mean squareradii for stable 4He, 12C, and 16O nuclei have been calculated usingsingle-particle radial wave functions of Woods-Saxon potential andharmonic-oscillator potential for comparison. The calculations for theground charge density distributions using the Woods-Saxon potentialshow good agreement with experimental data for 4He nucleus whilethe results for 12C and 16O nuclei are better in harmonic-oscillatorpotential. The calculated elastic charge form factors in Woods-Saxonpotential are better than the results of harmonic-oscillator potential.Finally, the calculated root mean square radii usingWoods-Saxonpotentials ho

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