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Resistance of bonded premolars to four artificial ageing models post enamel conditioning with a novel calcium-phosphate paste
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Background: This in vitro study compares a novel calcium-phosphate etchant paste to conventional 37% phosphoric acid gel for bonding metal and ceramic brackets by evaluating the shear bond strength, remnant adhesive and enamel damage following water storage, acid challenge and fatigue loading. Material and Methods: Metal and ceramic brackets were bonded to 240 extracted human premolars using two enamel conditioning protocols: conventional 37% phosphoric acid (PA) gel (control), and an acidic calcium-phosphate (CaP) paste. The CaP paste was prepared from β-tricalcium phosphate and monocalcium phosphate monohydrate powders mixed with 37% phosphoric acid solution, and the resulting phase was confirmed using FTIR. The bonded premolars were exposed to four artificial ageing models to examine the shear bond strength (SBS), adhesive remnant index (ARI score), with stereomicroscopic evaluation of enamel damage. Results: Metal and ceramic control subgroups yielded significantly higher (p ˂ 0.05) SBS (17.1-31.8 MPa) than the CaP subgroups (11.4-23.8 MPa) post all artificial ageing protocols, coupled with higher ARI scores and evidence of enamel damage. In contrast, the CaP subgroups survived all artificial ageing tests by maintaining adequate SBS for clinical performance, with the advantages of leaving unblemished enamel surface and bracket failures at the enamel-adhesive interface. Conclusions: Enamel conditioning with acidic CaP pastes attained adequate bond strengths with no or minimal adhesive residue and enamel damage, suggesting a suitable alternative to the conventional PA gel for orthodontic bonding.

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Publication Date
Wed Mar 20 2024
Journal Name
Journal Of Angiotherapy
Nanoparticle-Mediated Plasmid Curing in Combating Antibiotic Resistance in Pathogenic Bacteria
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Background: Nanotechnology has emerged as a pivotal domain in material science research with extensive applications across various sectors including biotechnology and medicine. Nanoparticles offer unique properties facilitating advancements in nanobiotechnology, particularly in nanomedicine, to combat bacterial infections and antibiotic resistance. This study aimed to determine the application of nanoparticles, specifically nano-TiO2, in treating plasmid-mediated antibiotic resistance in both Gram-negative and Gram-positive bacteria. Method: We evaluated antibiotic and nanomaterial sensitivity through disc diffusion and broth microdilution assays. Plasmid curing experiments were conducted using varying concentrations of nano-TiO2 an

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Publication Date
Tue Mar 01 2011
Journal Name
Journal Of Economics And Administrative Sciences
Study of the marketing supply chain of the fuel oil productUsing transport models
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The marketing logistic chain, as an integrated system aimed to balance the achievement of its main opposite objectives which represented in the access to the best service presented to the customer with lowest possible logistic costs especially the transportation costs, where encourages the researcher to choose the second objective as a field of this study in order to reduce the transportation costs in the final link of marketing logistic chain which related to delivering of fuel oil to the customer that falls within organizational responsibilities of the company under consideration (Oil Marketing Company) and also known in a brief name by (SOMO) through two methods, the first is by functioning quantative techniques by using trans

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Publication Date
Thu May 14 2009
Journal Name
Journal Of Kerbala University
Synthesis and Characterization of Novel Macrocyclic ligand and its complexes with (Co(II) ,Ni(II) ,Cu(II) ,Zn(II) , and Cd(II) ) ions.
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A new Macrocyclic Schiff base ligand Bis[4-hydroxy(1,2-ethylene-dioxidebenzylidene) pheylenediamine] [H2L] and its complexes with (Co(II) , Ni(II) , Cu(II) , Zn(II) and Cd(II)) are reported . The ligand was prepared in two steps,in the first step a solution of (o-phenylene diamine) in methanol react under reflux with (2,4-dihydroxybenzylaldeyed) to give an (intermediatecompound) [Bis-1,2 (2,4-dihydroxybenzylediene)pheylinediamine] which react in the second step with (1,2- dichloro ethane) giving the mentioned ligand.Then the complexes were synthesis of adding of corresponding metal salts to the solution of the ligand in methanol under reflux with 1:1 metal to ligand ratio. On the basis of, molar conductance, I.R., UV-Vis, chloride content a

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Publication Date
Tue Mar 19 2024
Journal Name
Baghdad Science Journal
Synthesis, Spectroscopic, and Characterization of Novel Nano Sized Mannich Base Complexes with Pt (IV) and Au (III) Ions and Assessing Their Antioxidants Activity
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في هذا البحث تم تحضير المركبات المعدنية النانوية الجديدة لأيونات البلاتين 4+و الذهب 3+ مع ليكاند قاعدة مانخ جديد مشتق من السيبروفلوكساسين بطريقة الموجات فوق الصوتية. تم تشخيص المعقدات النانوية والليكاند الجديد بأستخدام  تقنيات فيزيائية و كيميائية مختلفة مثل أطياف الاشعة تحت الحمراء، حيود الاشعة السينية ، المجهر الالكتروني الماسح ، المجهر الالكتروني النافذ و مجهر القوة الذرية.  تم تحديد نشاط مضادات الأك

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Publication Date
Sat Apr 01 2023
Journal Name
Heliyon
A comprehensive review on modelling the adsorption process for heavy metal removal from waste water using artificial neural network technique
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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
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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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.

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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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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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