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Numerical Prediction of Bond-Slip Behavior in Simple Pull-out Concrete Specimen
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In this study the simple pullout concrete cylinder specimen reinforced by a single steel bar was analyzed for bond-slip behavior. Three-dimension nonlinear finite element model using ANSYS program was employed to study the behavior of bond between concrete and plain steel reinforcement. The ANSYS model includes eight-noded isoperimetric brick element (SOLID65) to model the concrete cylinder while the steel reinforcing bar was modeled as a truss member (LINK8). Interface element (CONTAC52) was used in this analysis to model the bond between concrete and steel bar. Material nonlinearity due to cracking and/or crushing of concrete, and yielding of the steel reinforcing bar were taken into consideration during the analysis. The accuracy of this model is investigated by comparing the finite element numerical behavior with that predicted from experimental results of three pullout specimens. Good agreement between the finite element solution and experimental results was obtained.

Publication Date
Sun Jan 01 2023
Journal Name
Dental Hypotheses
Effect of Dentin Surface Pretreatment With Chitosan Nanoparticles on Immediate and Prolonged Shear Bond Strength of Resin Composite: An in Vitro Study
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Publication Date
Fri Jun 13 2025
Journal Name
Journal Of Baghdad College Of Dentistry
An in vitro evaluation of shear bond strength of chemical and light-cured bonding materials with stainless steel, ceramic, and sapphire brackets
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Publication Date
Tue Dec 15 2020
Journal Name
Journal Of Baghdad College Of Dentistry
Effect of ageing media on shear bond strength of metal orthodontic brackets bonded with different adhesive systems (A comparative in-vitro study)
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Background: The aim of this study was to evaluate the shear bond strength (SBS) and adhesive remnant index (ARI) of different orthodontic adhesive systems after exposure to aging media (water storage and acid challenge). Materials and methods: Eighty human upper premolar teeth were extracted for orthodontic purposes and randomly divided into two groups (40 teeth each): the first group in which the bonded teeth were stored in distilled water for 30 days at 37°C, and the second group in which the bonded teeth were subjected to acid challenge. Each group was further subdivided into four subgroups (10 teeth each) according to the type of adhesive system that would be bonded to metal brackets: either non-fluoride releasing adhesive (NFRA),

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Publication Date
Sun Jan 01 2023
Journal Name
Dental Hypotheses
Assessment of the Impact of Adhesive and Wires Types on the Tensile Bond Strength of Fixed Lingual Retainers Used in Orthodontics: An In Vitro Study
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Introduction: We aimed to assess the impact of adhesive and wires types on the tensile bond strength of fixed lingual retainers. Methods: A total of 160 intact bovine teeth were collected, cleaned, stored in 25% sodium hypochlorite, and randomly assigned to two groups based on the adhesive type: a two-step adhesive and a one-step adhesive. Each group was further divided into four subgroups based on the type of lingual retainer wire, which included (A) 8-strand braided stainless steel wire, (B) three-strand titanium retainer wire, (C) stainless steel chain, and (D) fiber-reinforced retainer. A tensile bond strength test was conducted using a universal testing machine at a controlled speed of 10 mm/min. Result: The 8-strand braided stainles

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Publication Date
Thu Mar 31 2016
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Permeability Prediction in One of Iraqi Carbonate Reservoir Using Hydraulic Flow Units and Neural Networks
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Permeability determination in Carbonate reservoir is a complex problem, due to their capability to be tight and heterogeneous, also core samples are usually only available for few wells therefore predicting permeability with low cost and reliable accuracy is an important issue, for this reason permeability predictive models become very desirable.

   This paper will try to develop the permeability predictive model for one of  Iraqi carbonate reservoir from core and well log data using the principle of Hydraulic Flow Units (HFUs). HFU is a function of Flow Zone Indicator (FZI) which is a good parameter to determine (HFUs).

   Histogram analysis, probability analysis and Log-Log plot of Reservoir Qua

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Publication Date
Wed Nov 13 2019
Journal Name
International Journal Of Research In Pharmaceutical Sciences
Prediction of maternal diabetes and adverse neonatal outcome in normotensive pregnancy using serum uric acid
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Diabetes mellitus, with adverse neonatal events are challenging issues to all obstetricians and pediatricians, where uric acid could play a vital role. We aimed to assess the relationship and prognostic benefits of serum uric acid measured at about 20 weeks’ gestation in normotensive pregnancy, with subsequent maternal diabetes, and neonatal complications. All singleton normotensive pregnant women with normal blood glucose, serum creatinine, and weight before pregnancy, whom attended Medical City Hospital, Department of Obstetrics and Gynecology in Baghdad, were involved and regarded as the case group, on the condition that their serum uric acid measured at 20 weeks’ gestation > 3 mg/dl, but if ≤ 3 mg/dl, they would be regi

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Publication Date
Thu Oct 13 2022
Journal Name
Computation
A Pattern-Recognizer Artificial Neural Network for the Prediction of New Crescent Visibility in Iraq
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Various theories have been proposed since in last century to predict the first sighting of a new crescent moon. None of them uses the concept of machine and deep learning to process, interpret and simulate patterns hidden in databases. Many of these theories use interpolation and extrapolation techniques to identify sighting regions through such data. In this study, a pattern recognizer artificial neural network was trained to distinguish between visibility regions. Essential parameters of crescent moon sighting were collected from moon sight datasets and used to build an intelligent system of pattern recognition to predict the crescent sight conditions. The proposed ANN learned the datasets with an accuracy of more than 72% in comp

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Publication Date
Sat Jun 28 2014
Journal Name
Iraqi Postgraduate Medical Journal
Comparism Between Transvaginal Cervical Length Measurement and Digital Examination in Prediction of Imminent preterm Delivery
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BACKGROUND: Preterm labour is a major cause of perinatal morbidity and mortality, so it is important to predict preterm delivery using the clinical examination of the cervix and uterine contraction frequency. New markers for the prediction of preterm birth have been developed such as transvaginal ultrasound measurement of cervical length as this method is widely available. OBJECTIVE: To determine, whether transvaginal cervical length measurement predicts imminent preterm delivery better than digital cervical length measurement in women presented with preterm labour and intact membranes. PATIENTS AND METHODS: Two hundred women presented with preterm labour between 24 and 36+6 weeks of gestation were included in this study. All women subjecte

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Publication Date
Tue May 01 2018
Journal Name
Journal Of Engineering
Prediction of Municipal Solid Waste Generation Models Using Artificial Neural Network in Baghdad city, Iraq
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The importance of Baghdad city as the capital of Iraq and the center of the attention of delegations because of its long history is essential to preserve its environment. This is achieved through the integrated management of municipal solid waste since this is only possible by knowing the quantities produced by the population on a daily basis. This study focused to predicate the amount of municipal solid waste generated in Karkh and Rusafa separately, in addition to the quantity produced in Baghdad, using IBM SPSS 23 software. Results that showed the average generation rates of domestic solid waste in Rusafa side was higher than that of Al-Karkh side because Rusafa side has higher population density than Al-Karkh side. T

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Publication Date
Thu Dec 29 2016
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
The Effect of Temperature in Vertical Migration Behavior of Three Species Zooplankton
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  The present study included  the impact of the follow-up variation in the temperature of aqueous medium in the vertical migration behavior of different groups of Zooplankton, consisted species Cyclops vernalis, Daphnia magna, Diaptomus dilopatus, that have been grown in controlled in terms of light and pH laboratory conditions, so choosing temperature of respectively 16,20,24,28, and 32 ËšC. The result showed a clear change in the migration behavior of testing planktonic species, it was a negative relationship between temperatures arises and individual of D. magna in the water column.While being appositive relationship with individual of C. vernalis and the same with D. dilopatus. Also, the result revealed a different impact

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