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Effect of surface treatments and thermocycling on shear bond strength of various artificial teeth with different denture base materials
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Background: Separation and deboning of artificial teeth from denture bases present a major clinical and labortory problem which affect both the patient and the dentist. The optimal bond strength of artificial teeth with denture base reinforced with nanofillers and flexible denture bases and the effect of thermo cycling should be evaluated. This study was conducted to evaluate and compare the shear bond strength of artificial teeth (acrylic and porcelain) with denture bases reinforced by 5% Zirconium oxide nanofillers and flexible bases under the effect of different surface treatments and thermo cycling and comparing the results with conventional water bath cured denture bases. Material and methods: Two types of artificial teeth; acrylic and porcelain were used and prepared for this study. Five specimens of each tooth type were processed to each denture base materials after the application of different surface treatments; these teeth were bonded to heat polymerized, nano composite resin and flexible denture bases. Specimens were thermo cycled and tested for bond strength until fracture with an Instron universal testing machine. Data were analyzed with analysis of variance and student T-test. Photomicrographic examinations were used to identify adhesive and cohesive failures within debonded specimens. Results: The mean force required to fracture the specimens were obviously larger for nanocomposite specimens compared with the heat cured and flexible specimens. The most common failure was cohesive within the tooth or the denture base. With each base material, the artificial teeth which were treated with thinner exhibited highest shear bond strength. Thermocycling had deleterious effect on the flexible denture base specimens. In general, nanocomposite and heat cured groups failed cohesively within the artificial tooth. While the valplastic groups failed adhesively at the tooth denture base interface. Conclusions: Within the limitations of this study, the type of denture base materials and surface treatments of the tooth selected for use may influence the shear bond strength of the tooth to the base. Selection of more compatible combinations of base and artificial teeth may reduce the number of prosthesis fractures and resultant repairs. Key words: acrylic teeth, porcelain teeth, Nano composite denture base, thermo cycling, flexible denture, thinner,

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Publication Date
Sun Dec 05 2010
Journal Name
Baghdad Science Journal
Effect of Granulocyte-colony stimulating factor with or without Moxifloxcacin therapy on capsulated Staphylococcus aureus infection in neutropenic mice
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Twenty bacterial isolates were identified as Staphylococcus aureus collected from wounds and catheters related infections. A capsulated S. aureus isolate was chosen after performing serum soft agar test, for this study Neutropenic mice were challenged with capsulated S. aureus ,and the effect of G-CSF with or without moxifloxacin was studied. The results indicated that the addition of G-CSF to moxifloxacin therapy have a synergistic effect in the killing of the bacteria, while when each G-CSF and moxifloxacin were used seperately have a similar effect on bacterial killing. It was found that the moxifloxacin has the same activity as G_CSF but is less costly than the latter one.

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Publication Date
Sun Apr 01 2018
Journal Name
Journal Of Educational And Psychological Researches
The effect of teaching design in accordance with cluster thinking strategies on First-grade-intermediate students’ achievement in science
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The current study aims to develop a teaching design in accordance with cluster thinking strategies and explore the effect of this teaching design on students’ achievement in science. To this end, the null hypothesis was adopted: there is no statistically significant difference at the level of (0, 05) between experimental group who adopted the teaching design in learning science and control group who follow the traditional method in learning the same subject. To test the null hypothesis, total of (74) students from Al-Alaama Hussain Mahfooth intermediate school were selected intentionally for the academic year 2016-2017. The sample divided into two equal groups when all the variables (age, prior achievement of science,

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Publication Date
Sat Apr 20 2024
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Studying Sex Effect on CTGF, TGF-B1 Levels and Some Relevant Parameters in Iraqi Diabetic Patients with Glomeruli and Renal Tubules Fibrosis
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Due to high blood sugar over long periods, the incidence and prevalence of type 2 diabetes are increasing throughout the world. Diabetic complications include microvascular and macrovascular complications that target the kidneys, nerves, eyes, and heart. Hence, the current study aimed to investigate the levels of (CTGF) and (TGF-β1) for both men and women and to demonstrate the effect of sex on it. In addition, some related biochemical factors in patients with diabetes and diabetic nephropathy are compared with those in healthy controls. The study included 120 males and females with an age range of (30-65) years old. Ninety patients with type 2 diabetes were subdivided into three groups on the basis of ACR criteria. All the individ

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Publication Date
Mon Jan 01 2018
Journal Name
Journal Of Global Pharma Technology
Molecular Investigation of Curli Fimbriae Genes in Enterobacter cloacae Isolated from Various Clinical Sources in Baghdad, Iraq
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Thirteen isolates were collected from various clinical sources during the periodfrom 22/10/2017 to 22/12/2017. All the isolates were diagnosed based on the microscopic and biochemical propertiesby Vitek-2 Compact system. All isolates formed biofilm 100%, with 30% of isolatesbiofilm produced strongly and 70% on medium. The results of the present study have shown the presence of Curli fimbriae genes in E. cloacae bacteria from cases of urinary tract infections, infected patient with blood bacteremia and inflammation of wounds. Curli fimbriae is considered to be an important factor in the virulence of E.cloacae bacteria, which plays an important role in adhering and combining cells on solid surfaces to form the biofilmand helps in the adhesion

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Scopus (2)
Scopus
Publication Date
Sat Aug 15 2015
Journal Name
Chemistry And Materials Research
Synthesis and Characterization of 3, 5-Dimethyl-2-(4-nitrophenyl azo)-Phenol Complexes with Co (II) and Ni (II) and Study Its Effect on the Activity of Ach Enzyme (invitro)
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Publication Date
Tue Feb 01 2022
Journal Name
Methods And Objects Of Chemical Analysis
Spectrophotometric Analysis of Quaternary Drug Mixtures using Artificial Neural network model
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Novel artificial neural network (ANN) model was constructed for calibration of a multivariate model for simultaneously quantitative analysis of the quaternary mixture composed of carbamazepine, carvedilol, diazepam, and furosemide. An eighty-four mixing formula where prepared and analyzed spectrophotometrically. Each analyte was formulated in six samples at different concentrations thus twentyfour samples for the four analytes were tested. A neural network of 10 hidden neurons was capable to fit data 100%. The suggested model can be applied for the quantitative chemical analysis for the proposed quaternary mixture.

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Publication Date
Tue Sep 06 2022
Journal Name
Methods And Objects Of Chemical Analysis
Spectrophotometric Analysis of Quaternary Drug Mixtures using Artificial Neural network model
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A Novel artificial neural network (ANN) model was constructed for calibration of a multivariate model for simultaneously quantitative analysis of the quaternary mixture composed of carbamazepine, carvedilol, diazepam, and furosemide. An eighty-four mixing formula where prepared and analyzed spectrophotometrically. Each analyte was formulated in six samples at different concentrations thus twenty four samples for the four analytes were tested. A neural network of 10 hidden neurons was capable to fit data 100%. The suggested model can be applied for the quantitative chemical analysis for the proposed quaternary mixture.

Scopus (2)
Scopus
Publication Date
Mon Oct 01 2018
Journal Name
Iraqi Journal Of Physics
Classification of brain tumors using the multilayer perceptron artificial neural network
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Information from 54 Magnetic Resonance Imaging (MRI) brain tumor images (27 benign and 27 malignant) were collected and subjected to multilayer perceptron artificial neural network available on the well know software of IBM SPSS 17 (Statistical Package for the Social Sciences). After many attempts, automatic architecture was decided to be adopted in this research work. Thirteen shape and statistical characteristics of images were considered. The neural network revealed an 89.1 % of correct classification for the training sample and 100 % of correct classification for the test sample. The normalized importance of the considered characteristics showed that kurtosis accounted for 100 % which means that this variable has a substantial effect

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Crossref (3)
Crossref
Publication Date
Sat Jan 01 2022
Journal Name
Methods And Objects Of Chemical Analysis
Spectrophotometric Analysis of Quaternary Drug Mixtures using Artificial Neural network model
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A Novel artificial neural network (ANN) model was constructed for calibration of a multivariate model for simultaneously quantitative analysis of the quaternary mixture composed of carbamazepine, carvedilol, diazepam, and furosemide. An eighty-four mixing formula where prepared and analyzed spectrophotometrically. Each analyte was formulated in six samples at different concentrations thus twentyfour samples for the four analytes were tested. A neural network of 10 hidden neurons was capable to fit data 100%. The suggested model can be applied for the quantitative chemical analysis for the proposed quaternary mixture.

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Scopus (2)
Scopus Clarivate Crossref
Publication Date
Mon Mar 30 2009
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Prediction of bubble size in Bubble columns using Artificial Neural Network
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In the literature, several correlations have been proposed for bubble size prediction in bubble columns. However these correlations fail to predict bubble diameter over a wide range of conditions. Based on a data bank of around 230 measurements collected from the open literature, a correlation for bubble sizes in the homogenous region in bubble columns was derived using Artificial Neural Network (ANN) modeling. The bubble diameter was found to be a function of six parameters: gas velocity, column diameter, diameter of orifice, liquid density, liquid viscosity and liquid surface tension. Statistical analysis showed that the proposed correlation has an Average Absolute Relative Error (AARE) of 7.3 % and correlation coefficient of 92.2%. A

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