Aim:The aim of this study was to compare the neutralizing effect of antioxidant agents on the microleakage of dental restorations in nonvital teeth after bleaching with carbamide peroxide. Also assessed was the correlation of the microleakage data between an electrochemical and a staining technique.

This article presents a novel neural network (NN) based on NCP function for solving nonconvex nonlinear optimization (NCNO) problem subject to nonlinear inequality constraints. We first apply the p-power convexification of the Lagrangian function in the NCNO problem. The proposed NN is a gradient model which is constructed by an NCP function and an unconstrained minimization problem. The main feature of this NN is that its equilibrium point coincides with the optimal solution of the original problem. Under a proper assumption and utilizing a suitable Lyapunov function, it is shown that the proposed NN is Lyapunov stable and convergent to an exact optimal solution of the original problem. Finally, simulation results on two numerical examples and two practical examples are given to show the effectiveness and applicability of the proposed NN.

AimThe aim of the present study was to determine the shear bond strength of self-adhesive resin cements to enamel and dentin with and without surface treatments, and compare them with conventional resin cement as the control group.MethodsIn this experimental study, buccal and lingual surface of the thirty sound human premolars were polished in order to obtain a flat surface of enamel (E) in buccal, and dentin (D) in lingual. Sixty feldspathic ceramic blocks (2×3×3 mm) were prepared and randomly divided into six groups (n=10). Each block was cemented to the prepared surface (30 enamel and 30 dentin surface) according to different protocol: E1 and D1; RelyX ARC as control group, E2, D2; RelyX Unicem, E3, D3; acid etching +RelyX Unicem. The specimens were termocycled and subjected to shear forces by a universal testing machine at a cross head speed of 0.5 mm/min. The mode of fracture were evaluated by stereomicroscope. Data were analyzed with descriptive statistical methods using SPSS version 15. One-way ANOVA, and post hoc Tukey tests were used to compare bond strengths between the groups with different adhesives at α=0.05.ResultsStatistical analysis showed no significant differences within the enamel subgroups, but there were significant differences within the dentinal subgroups, and statistically significant differences were found between the groups D1and D3 (p=0.02). Comparison between similar enamel and dentinal subgroups showed that there was a significant difference just between the subgroups E3 and D3 (p=0.01).ConclusionElective etching of enamel did not lead to significant increase in the shear bond strength of RelyX Unicem in comparison to RelyX ARC. On the other hand, elective etching of dentin reduces the bond strength of RelyX Unicem with the dentin.

Background:The aim of this retrospective study was to assess the survival rate and causes of failure of quartz fiber posts used to restore endodontically treated teeth.Materials and Methods:Thirty-eight patients with endodontically treated premolar and anterior teeth that were then restored with a coronoradicular quartz fiber post and extensive composite resin restorations were selected for participation in the study. The age of the restorations ranged from 1 to 6 years. Survival probabilities of the restorations as well as causes of failures were analyzed using the Kaplan-Meier analysis and the Logistic regression (α = 0.05).Results:The overall cumulative survival rate (48.8%) was determined, while the survival probabilities after 1, 2, 4, 5, and 6 years of service were 88.37%, 60.95%, 45.71%, 32.65%, and 0%, respectively.Conclusions:The survival probability of endodontically treated teeth restored with a quartz fiber post and composite restorations is associated with the dental arch.

Introduction: The purpose of this study was to compare the effect of the bioactive glass, the glass ionomer, and the Erbium YAG laser as liners on the remineralization of the affected dentin. Methods: The present study was conducted on 64 healthy extracted human molars divided into 4 groups, 1 control group and 3 experimental groups. After artificially inducing dentinal caries lesions, each of the experimental groups was applied to the cavity floor and then restored with a composite. The samples were stored after thermocycling in an incubator for two months. Finally, the hardness of the cavity floor was measured at 3 depths of 20, 50 and 100 μm by the Vickers microhardness tester. The dentin conditions underneath the liners were also evaluated with FESEM. Statistical analysis was performed by two-way ANOVA and the post-hoc Games-Howell test (P<0.05). Results: Among the groups, the lowest microhardness value was in the control group (P<0.05) except at a depth of 100 μm; therefore, there was no significant difference between the control group and the bioactive glass (P>0.05). The laser group had the highest microhardness value, which was significantly different from the control group (P<0.05). There was a significant difference between the laser and bioactive glass (P<0.05), except at a depth of 20 μm. The laser and glass ionomer had only a significant difference at a depth of 100 μm (P<0.05). The microhardness value induced by glass ionomer was higher than bioactive glass, which in no depth was significant (P>0.05). Partial dentinal tubule occlusion was observed with FESEM in each of the experimental groups as compared to the control group. Conclusion: The microhardness values were higher in all groups than in the control group. The laser might be more successful in remineralization than the other ones.

This paper presents a recurrent neural network for solving nonconvex nonlinear optimization problems subject to nonlinear inequality constraints. First, the p‐power transformation is exploited for local convexification of the Lagrangian function in nonconvex nonlinear optimization problem. Next, the proposed neural network is constructed based on the Karush–Kuhn–Tucker (KKT) optimality conditions and the projection function. An important property of this neural network is that its equilibrium point corresponds to the optimal solution of the original problem. By utilizing an appropriate Lyapunov function, it is shown that the proposed neural network is stable in the sense of Lyapunov and convergent to the global optimal solution of the original problem. Also, the sensitivity of the convergence is analysed by changing the scaling factors. Compared with other existing neural networks for such problem, the proposed neural network has more advantages such as high accuracy of the obtained solutions, fast convergence, and low complexity. Finally, simulation results are provided to show the benefits of the proposed model, which compare to or outperform existing models.

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