Background: Radiopacity is one of the prerequisites for dental materials, especially for composite restorations. It's essential for easy detection of secondary dental caries as well as observation of the radiographic interface between the materials and tooth structure. The aim of this study to assess the difference in radiopacity of different resin composites using a digital x-ray system. Materials and methods: Ten specimens (6mm diameter and 1mm thickness) of three types of composite resins (Evetric, Estelite Sigma Quick,and G-aenial) were fabricated using Teflon mold. The radiopacity was assessed using dental radiography equipment in combination with a phosphor plate digital system and a grey scale value aluminum step wedge with thickness varying from 1mm to 10mm in steps of 1mm each. The tested materials were radiographed, we used Image J software, on a computer screen to evaluate the degree of radiopacity for each individual material and compare with the aluminum step wedge. Radiopacity was expressed in mm of equivalent aluminum step wedge. Analysis of varience (ANOVA) and Least Significant Difference (LSD) were used to investigate the significance of differences among the tested groups. Results: Statistical analysis showed highly significant difference among the tested groups (p≤0.01). Amongst, G-aenial composite shows the most radiopaque and it is above or equivalent to that of enamel, while Estelite Sigma Quick composite has the lowest radiopacity value and is equivalent to that of dentin. Conclusion: In line with previous studies, and within the limitation of our study, considerable variations in radiopacity values were found among materials depending on the radiopaque elements incorporated into the matrix. All composite materials tested complied with the ISO 4049 standard.
Cadmium sulfide (CdS) nanocrystalline thin films have been prepared by chemical bath deposition (CBD) technique on commercial glass substrates at 70ºC temperature. Cadmium chloride (CdCl2) as a source of cadmium (Cd), thiourea (CS(NH2)2) as a source of sulfur and ammonia solution (NH4OH) were added to maintain the pH value of the solution at 10. The characterization of thin films was carried out through the structural and optical properties by X-ray diffraction (XRD) and UV-VIS spectroscopy. A UV-VIS optical spectroscopy study was carried out to determine the band gap of the nanocrystalline CdS thin film and it showed a blue shift with respect to the bulk value (from 3.9 - 2.4eV). In present w
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Background: Polymethylmethacrylate (PMMA) is the most ‎commonly used mâ€aterial in denture construction. This material is ‎far from ideal in fulfilling the‎ mechanical requirements, like low impact and transverse strength and poor thermal conductivity are present in this material. The purpose of this study was to study the effect of addition a composite which include 1%wt silanized silicone dioxide nano fillers (SiO2) and 1wt% oxygen plasma treated polypropylene fiber (PP) on some properties of heat cured acrylic resin denture base material (PMMA). Materials and methods: One hundâ€red (100) prepared specimens were divided into five groups according to the tests, each group consisted of 20 specimens and t
In this work, spinel ferrites (NiCoFe2O4) were prepared as thin films by dc reactive dual-magnetron co-sputtering technique. Effects of some operation parameters, such as inter-electrode distance, and preparation conditions such as mixing ratio of argon and oxygen in the gas mixture, on the structural and spectroscopic characteristics of the prepared samples were studied. For samples prepared at inter-electrode distance of 5 cm, only one functional group of OH- was observed in the FTIR spectra as all bands belonging to the metal-oxygen vibration were observed. Similarly, the XRD results showed that decreasing the pressure of oxygen in the gas mixture lead to grow more crystal planes in the samples prepare
... Show MoreRationale, aims and objectives: A review of studies published over the last six years gives update about this hot topic. In the middle of COVID-19 pandemic, this study findings can help understand how population may perceive vaccinations. The objectives of this study were to review the literature covering the perceptions about influenza vaccines and to determine factors influencing the acceptance of vaccination using Health Belief Model (HBM). Methods: A comprehensive literature search was performed utilizing PubMed and Google Scholar databases. Three keywords were used: Influenza vaccine, perceptions, and Middle East. Empirical studies that dealt with people/ HCW perceptions of influenza vaccine in the Middle East and writt
... Show MoreThe research discusses the need to find the innovative structures and methodologies for developing Human Capital (HC) in Iraqi Universities. One of the most important of these structures is Communities of Practice (CoPs) which contributes to develop HC by using learning, teaching and training through the conversion speed of knowledge and creativity into practice. This research has been used the comparative approach through employing the methodology of Data Envelopment Analysis (DEA) by using (Excel 2010 - Solver) as a field evidence to prove the role of CoPs in developing HC. In light of the given information, a researcher adopted on an archived preliminary data about (23) colleges at Mosul University as a deliberate sample for t
... Show MoreCodes of red, green, and blue data (RGB) extracted from a lab-fabricated colorimeter device were used to build a proposed classifier with the objective of classifying colors of objects based on defined categories of fundamental colors. Primary, secondary, and tertiary colors namely red, green, orange, yellow, pink, purple, blue, brown, grey, white, and black, were employed in machine learning (ML) by applying an artificial neural network (ANN) algorithm using Python. The classifier, which was based on the ANN algorithm, required a definition of the mentioned eleven colors in the form of RGB codes in order to acquire the capability of classification. The software's capacity to forecast the color of the code that belongs to an object under de
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Codes of red, green, and blue data (RGB) extracted from a lab-fabricated colorimeter device were used to build a proposed classifier with the objective of classifying colors of objects based on defined categories of fundamental colors. Primary, secondary, and tertiary colors namely red, green, orange, yellow, pink, purple, blue, brown, grey, white, and black, were employed in machine learning (ML) by applying an artificial neural network (ANN) algorithm using Python. The classifier, which was based on the ANN algorithm, required a definition of the mentioned eleven colors in the form of RGB codes in order to acquire the capability of classification. The software's capacity to forecast the color of the code that belongs to an ob
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