Background: The accuracy of fitness of any dental casting is imperative for the success of any prosthodontic treatment. From the time that dental casting was first introduced, efforts have been made to produce more accurate and better fitted castings with minimal marginal discrepancy. The aim of this in vitro study was to evaluate the effects of three different investing and burnout techniques on the vertical marginal discrepancies ofceramometalcopings invested with two types of phosphate- bonded investments. Materials and methods: Sixty wax patterns were fabricated on a standardized prepared brass die representing an upper central incisor by the aid of a custom-made split mold. Three different investing and burnout techniques were applied for an Iraqi investment and a commercial type; Group I:Ring investing with conventional burnout technique (RC);Group II: Ringless investing with conventional burnout technique (RLC);Group III: Ring investing with accelerated burnout technique (RA).Twenty wax patterns of each group were divided into two subgroups according to the type of investment material used (10 for each subgroup) represented as (B) for the BellaStar XL and (W) for the WYMvest investments. Complete castings were finished and seated on the metal die. The accuracy of fit of each coping was determined by measuring the vertical marginal discrepancies between the finish line on the metal die and the margins of each coping at four specific reference points on the labial, mesial, palatal, and distal aspects of the die by the aid of a light microscope supplied with a digital camera.The arithmetic mean of each three records was computed and regarded as the amount of the marginal discrepancy of each coping and was used as a unit for the statistical analysis. Results: Mean marginal accuracy for W(RLC)was found to be the least (13.839+4.5724 um) while the highest mean value related to B(RLC) (29.033+2.102 um). In general, ANOVA test showed significant results among the mean values of the Binvestment subgroups while LSD test showed non-significance between the (RA) and both the (RC) and (RLC) subgroups. On the other hand, significance was present between the (RLC) and (RA)of the Winvestment subgroups while non-significance was located between the (RC) and both the (RLC) and (RA) subgroups. Comparing similar subgroups of the two tested investments, the Student's t-test showed non-significance between the (RC) subgroups while high significance was located between the (RLC) and (RA) subgroups respectively.Concerning the vertical marginal discrepancy of the copings, applying the (RC) technique for both investments caused non-statistical significance between the labial, mesial, palatal, and distal aspects.The (RLC) technique caused high significance between the four aspects, while the (RA) technique caused non-significance between the labial aspect only and the others. Conclusion: The Iraqi investment generally produced less vertical marginal discrepancies (using the three different investing and burn-out techniques) than the commercial investment.In order to achieve a better marginal fit, it seems that ceramometalcopings invested with the commercial investment tested are better be cast using the conventional ring investing and burnout technique.
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This study was done to investigate the impact of different nanoparticles on diesel fuel characteristics, Iraqi diesel fuel was supplied from al-Dura refinery and was treated to enhance performance by improving its characteristics. Two types of nanoparticles were mixed with Iraqi diesel fuel at various weight fractions of 30, 60, 90, and 120 ppm. The diesel engine was tested and run at a constant speed of 1600 rpm to examine and evaluate the engine's performance and determine emissions. In general, ZnO additives' performance analysis showed they are more efficient for diesel fuel engines than CeO. The performance of engine diesel fuel tests showed that the weight fraction of nanoparticles at 90 and 120 ppm give a similar
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Loud noise can be extremely harmful to the auditory system as well as to human health. Noise pollution is primarily caused by traffic noise. The study's goal was to determine how various vehicle types and speeds affected the amount of noise generated by traffic. The two factors were investigated at seven different arterial streets throughout Kirkuk city to measure the noise levels. The measurements were performed during peak hours to compare the result with WHO standards for noise specification. Traffic volume and vehicle speed are shown to be the key elements that determine an increase in noise level.
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Changing oil-wet surfaces toward higher water wettability is of key importance in subsurface engineering applications. This includes petroleum recovery from fractured limestone reservoirs, which are typically mixed or oil-wet, resulting in poor productivity as conventional waterflooding techniques are inefficient. A wettability change toward more water-wet would significantly improve oil displacement efficiency, and thus productivity. Another area where such a wettability shift would be highly beneficial is carbon geo-sequestration, where compressed CO2 is pumped underground for storage. It has recently been identified that more water-wet formations can store more CO2. We thus examined how silica based nanofluids can induce such a wettabil
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Thin films of ZnO nano crystalline doped with different concentrations (0, 6, 9, 12, and 18 )wt. % of copper were deposited on a glass substrate via pulsed laser deposition method (PLD). The properties of ZnO: Cu thin-nanofilms have been studied by absorbing UV-VIS, X-ray diffraction (XRD) and atomic force microscopes (AFM). UV-VIS spectroscopy was used to determine the type and value of the optical energy gap, while X-ray diffraction was used to examine the structure and determine the size of the crystals. Atomic force microscopes were used to study the surface formation of precipitated materials. The UV-VIS spectroscopy was used to determine the type and value of the optical energy gap.
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Diabetic retinopathy is an eye disease in diabetic patients due to damage to the small blood vessels in the retina due to high and low blood sugar levels. Accurate detection and classification of Diabetic Retinopathy is an important task in computer-aided diagnosis, especially when planning for diabetic retinopathy surgery. Therefore, this study aims to design an automated model based on deep learning, which helps ophthalmologists detect and classify diabetic retinopathy severity through fundus images. In this work, a deep convolutional neural network (CNN) with transfer learning and fine tunes has been proposed by using pre-trained networks known as Residual Network-50 (ResNet-50). The overall framework of the proposed
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The government of Iraq states that despite the massive amounts invested in the power generating sector, the country has been plagued by power outages for more than three decades; One of the most common sources of the problem and significant impact on the waste of public funds in contractual processes. The Ministry of Planning issued the sectorial
specialized standard bidding documents (SSBD) of Design, Supply, and Installation of the Electromechanical Works (DSIoEW), which is primarily designed to support the Ministry of Electricity (MoE) by developing economic projects to improve the contractual process that led to raisings Iraqi electricity generation field. The research evaluates the impact of
applying the SSBD-DSIoEW for
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