Background: Prophylaxis methods are used to mechanically remove plaque and stain from tooth surfaces; such methods give rise to loss of superficial structure and roughen the surface of composites as a result of their abrasive action. This study was done to assess the effect of three polishing systems on surface texture of new anterior composites after storage in artificial saliva. Materials and methods: A total of 40 Giomer and Tetric®N-Ceram composite discs of 12 mm internal diameter and 3mm height were prepared using a specially designed cylindrical mold and were stored in artificial saliva for one month and then samples were divided into four groups according to surface treatment: Group A (control group):10 specimens received no surface polish and were subdivided into A1 (Giomer) and A2 (Tetric®N-Ceram). Group B: 10 specimens received polishing with Air polishing devise (APD) and were subdivided into B1 (Giomer) and B2 (Tetric®N-Ceram). Group C: 10 specimens received polishing with pumice and brush and were subdivided into C1 (Giomer) and C2 (Tetric®N-Ceram). Group D: 10 specimens were polished with pumice and rubber cup and were subdivided into D1 (Giomer) and D2 (Tetric®N-Ceram). Testing was done by means of profilometer and statistically analyzed using analysis of variance test (ANOVA), LSD and student t-test. Also samples were photographed by special orthoplane camera using light polarizing microscope. Results: The results showed a highly statistical significant difference in surface roughness among Giomer subgroups P<0.05. Also there was a highly significant difference P<0.05 when comparing Tetric subgroups according to type of surface treatment. Furthermore there was non-significant difference P>0.05 between groups according to the type of restorative material used. Conclusion: The use of prophylactic surface treatment significantly increased Giomer and Tetric ceram surface roughness and the use of rotating brush has shown the roughest surface among all other types of prophylactic protocols also Giomer had shown more surface roughness than Tetric ceram although the difference was not significant.
An application of neural network technique was introduced in modeling the point efficiency of sieve tray, based on a
data bank of around 33l data points collected from the open literature.Two models proposed,using back-propagation
algorithm, the first model network consists: volumetric liquid flow rate (QL), F foctor for gas (FS), liquid density (pL),
gas density (pg), liquid viscosity (pL), gas viscosity (pg), hole diameter (dH), weir height (hw), pressure (P) and surface
tension between liquid phase and gas phase (o). In the second network, there are six parameters as dimensionless
group: Flowfactor (F), Reynolds number for liquid (ReL), Reynolds number for gas through hole (Reg), ratio of weir
height to hole diqmeter
Objectives: This study aimed to evaluate and compare the effect of plasma treatment versus conventional treatment on the micro shear bond strength (μSBS), surface roughness, and wettability of three different CAD/CAM materials. Materials and methods: Sixty cylindrical specimens (5 mm diameter ×3 mm height) were prepared from three different CAD/CAM materials: Group A: Zirconia, Group B: Lithium disilicate, and Group C: Resin nano-ceramic. Each group was subdivided into two subgroups according to surface treatment used: Subgroup I: Conventional treatment, zirconia was sandblasted with Al2O3, while lithium disilicate and resin nano-ceramic were etched with hydrofluoric acid. Subgroup II: Plasma treatment, the surface of each material was tr
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This study aims to demonstrate the role of artificial intelligence and metaverse techniques, mainly logistical Regression, in reducing earnings management in Iraqi private banks. Synthetic intelligence approaches have shown the capability to detect irregularities in financial statements and mitigate the practice of earnings management. In contrast, many privately owned banks in Iraq historically relied on manual processes involving pen and paper for recording and posting financial information in their accounting records. However, the banking sector in Iraq has undergone technological advancements, leading to the Automation of most banking operations. Conventional audit techniques have become outdated due to factors such as the accuracy of d
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Objectives: The study aims at:
1- Measuring the level of lead in workers’ saliva and blood in the factory.
2- Studying the correlation between the saliva lead level and the infection that caused by microorganisms, isolation and
identification.
3-Studying the influence of high blood lead level on the total white blood cells.
Methodology: This study has been conducted for the period from March 15th, 2010 to May, 20th
, 2010. A total of (60)
saliva and blood samples were collected from workers in batteries industry factory in Baghdad and another (20) samples
were collected as a control group. Lead level had been measured in blood and saliva samples, then microorganisms were
isolated the from the saliva samples.
In this research Artificial Neural Network (ANN) technique was applied to study the filtration process in water treatment. Eight models have been developed and tested using data from a pilot filtration plant, working under different process design criteria; influent turbidity, bed depth, grain size, filtration rate and running time (length of the filtration run), recording effluent turbidity and head losses. The ANN models were constructed for the prediction of different performance criteria in the filtration process: effluent turbidity, head losses and running time. The results indicate that it is quite possible to use artificial neural networks in predicting effluent turbidity, head losses and running time in the filtration process, wi
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Cutting forces are important factors for determining machine serviceability and product quality. Factors such as speed feed, depth of cut and tool noise radius affect on surface roughness and cutting forces in turning operation. The artificial neural network model was used to predict cutting forces with related to inputs including cutting speed (m/min), feed rate (mm/rev), depth of cut (mm) and work piece hardness (Map). The outputs of the ANN model are the machined cutting force parameters, the neural network showed that all (outputs) of all components of the processing force cutting force FT (N), feed force FA (N) and radial force FR (N) perfect accordance with the experimental data. Twenty-five samp
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In the literature, several correlations have been proposed for hold-up prediction in rotating disk contactor. However,
these correlations fail to predict hold-up over wide range of conditions. Based on a databank of around 611
measurements collected from the open literature, a correlation for hold up was derived using Artificial Neiral Network
(ANN) modeling. The dispersed phase hold up was found to be a function of six parameters: N, vc , vd , Dr , c d m / m ,
s . Statistical analysis showed that the proposed correlation has an Average Absolute Relative Error (AARE) of 6.52%
and Standard Deviation (SD) 9.21%. A comparison with selected correlations in the literature showed that the
developed ANN correlation noticeably