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jbcd-2625
The accuracy of cone-beam computed tomography in the evaluation of boney support of teeth among patients with a unilateral cleft of lip and palate among IraqiPopulation
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Background: To evaluate the bony supports of the teeth adjacent to the area of cleft in patient with unilateral cleft lip and palate and to compare these measurements with the measurements of the same teeth in non-cleft side by using CBCT. Materials and methods: The CBCT scans of 30 patients having cleft lip( unilateral) and palate(unilateral), were analyzed and the measurements of the alveolar bony support for teeth that are adjacent to the cleft area were measured with those teeth located on opposite side (non- clef) side. For each tooth, the measurements will taken for the distance between the( cementoenamel junction) (CEJ) and the bony crest (AC) at the( buccal area) was measured and the thickness of the buccal plate At zero, one, two, and four mm. Results: The thickness of the bony support of central incisor at zero and one mm apically were statistically significantly thinner in cleft regions than in the non cleft regions. The CEJ-AC distance of the central teeth that are adjacent to the area of cleft was higher significantly than those for non-cleft area. For the canine teeth at 0, 1, 2, and 4mm apically were similar to those results obtained for central teeth at 0 and 1mm levels. Also, the CEJ-AC distance of the canine teeth that are adjacent to the cleft area was higher significantly than those for non-cleft area. Conclusion: person with unilateral cleft lip and palate showed a reduced alveolar bony support of the teeth located adjacent to the area of cleft when compared with the controls and This will cause a lot of problems in the future, so professional dental control is very essential for the maintaining of good periodontal health for those patients

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Publication Date
Sun May 01 2022
Journal Name
Journal Of Engineering
Estimating Pitting Corrosion Depth and Density on Carbon Steel (C-4130) using Artificial Neural Networks
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The purpose of this research is to investigate the impact of corrosive environment (corrosive ferric chloride of 1, 2, 5, 6% wt. at room temperature), immersion period of (48, 72, 96, 120, 144 hours), and surface roughness on pitting corrosion characteristics and use the data to build an artificial neural network and test its ability to predict the depth and intensity of pitting corrosion in a variety of conditions. Pit density and depth were calculated using a pitting corrosion test on carbon steel (C-4130). Pitting corrosion experimental tests were used to develop artificial neural network (ANN) models for predicting pitting corrosion characteristics. It was found that artificial neural network models were shown to be

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Publication Date
Sat Jun 09 2018
Journal Name
Journal Of Molecular Structurs
Mesogenic materials incorporating 4H-1,2,4-triazol-3-thiol moiety: Synthesis, characterization and liquid crystals study
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Three series of monomers, polymers and thioester cyclic compounds containing 4H-1,2,4-triazol-3-thiol moiety were synthesized and examined for their liquid crystalline properties. All monomers, polymers and thioester compounds were characterized by elemental analysis and FTIR, 1 H-NMR and mass spectroscopy. The phase transition and mesomorphic properties were investigated by polarized optical microscope (POM) and differential scanning calorimetry (DSC). The monomer with terminal phenyl substituent display dimorphism nematic and smectic A (SmA) mesophases. The corresponding polymers derived from acrylic and phenyl acrylic acid monomers show nematic mesophase. The only thioester cyclic compound derived from terephtaloyl chloride show nemati

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Publication Date
Sat Oct 01 2022
Journal Name
Journal Of Composites For Construction
Near-Surface-Mounted CFRP for Strengthening Concavely Curved Soffit RC Beams: Experimental and Analytical Investigation
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Publication Date
Thu Jun 30 2022
Journal Name
International Journal Of Drug Delivery Technology
New Metal Complexes Derived from Heterocyclic Schiff-base Ligand; Preparation, Structural Investigation and Biological Activity
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The formation of a Schiff-base with N2O2 donor atoms derived from the hydrazine segment and its metal complexes are reported. The Schiff-base ligand; N’-((1R,2S,4R,5S,Z)-2,4-diphenyl-3-azabicyclo[3.3.1]nonan-9-ylidene)furan-2-carbohydrazide (HL) was prepared from the reaction of furan-2-carbohydrazide with (1R, 2R, 4R, 5S)-2,4-diphenyl-3-azabicyclo[3.3.1]nonan-9-one (M1) in ethanol medium. The reaction of the title ligand with selected metal ions Cr(III), Mn(II), Ni(II), Cu(II), Zn(II) and Cd(II) gave complexes with the general formula [M(L)Cl2], (where: M = Cr(III), Mn(II), Ni(II), Cu(II), Zn(II) and Cd(II)). Spectroscopic analyses Fourier transform infrared (FT-IR), Nuclear Magnetic Resonance (NMR) Carbon-13 nuclear magnetic res

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Publication Date
Tue Nov 19 2024
Journal Name
Discover Sustainability
Groundwater quality assessment and pollution sources identification using statistical analyses at Missan Governorate, Southeast Iraq
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The shortage in surface water quantities led to a shift in dependence on the groundwater as an alternative water source in southern parts of Iraq. The groundwater is decreasing in quantity and water quality is degrading due to different factors. Therefore, it is important to assess the groundwater quality of the Missan Governorate of the country by analyzing the physicochemical parameters and distinguishing the probable sources of contaminants in the area. The present study used water quality diagrams and statistical methods such as factor analysis and agglomerative cluster analysis to determine the sources of chemical ions in the forty-four groundwater samples collected from wells in the study area. In addition, the Water Quality Index (WQ

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Publication Date
Sat Jun 01 2019
Journal Name
Periodicals Of Engineering And Natural Sciences (pen)
Lung cancer classification using data mining and supervised learning algorithms on multi-dimensional data set
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These With recent developments in machine learning, data mining and computer vision, there is great potential for improvements in early detection of lung cancer using scans and data available. This paper details the methods and techniques used in our project, where the objective is to develop algorithms to determine whether a patient has or is likely to develop lung cancer using dataset images using data mining and machine learning for the classification and examination. We explore approaches to address the problem. Cancer is the most important cause of death globally. The disease diagnosis is a major process to treat the patients who are affected by cancer disease. The diagnosis process is more difficult comparatively known about t

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Publication Date
Wed Sep 17 2025
Journal Name
Molecular Biology Reports
Antibacterial effect and MexA efflux pump Inhibition by green-synthesized copper nanoparticles from Mentha piperita
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Publication Date
Tue May 23 2023
Journal Name
Journal Of Sensors
On-Board Digital Twin Based on Impedance and Model Predictive Control for Aerial Robot Grasping
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Aerial manipulation of objects has a number of advantages as it is not limited by the morphology of the terrain. One of the main problems of the aerial payload process is the lack of real-time prediction of the interaction between the gripper of the aerial robot and the payload. This paper introduces a digital twin (DT) approach based on impedance control of the aerial payload transmission process. The impedance control technique is implemented to develop the target impedance based on emerging the mass of the payload and the model of the gripper fingers. Tracking the position of the interactional point between the fingers of gripper and payload, inside the impedance control, is achieved using model predictive control (MPD) approach.

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Publication Date
Sun Feb 25 2024
Journal Name
Baghdad Science Journal
Early Diagnose Alzheimer's Disease by Convolution Neural Network-based Histogram Features Extracting and Canny Edge
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Alzheimer's disease (AD) increasingly affects the elderly and is a major killer of those 65 and over. Different deep-learning methods are used for automatic diagnosis, yet they have some limitations. Deep Learning is one of the modern methods that were used to detect and classify a medical image because of the ability of deep Learning to extract the features of images automatically. However, there are still limitations to using deep learning to accurately classify medical images because extracting the fine edges of medical images is sometimes considered difficult, and some distortion in the images. Therefore, this research aims to develop A Computer-Aided Brain Diagnosis (CABD) system that can tell if a brain scan exhibits indications of

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Publication Date
Wed May 10 2023
Journal Name
Biomass Conversion And Biorefinery
Lactic acid-based deep eutectic solvents and activated carbon for soap removal from crude biodiesel
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