Microtensile bond strength of resin cements to caries-affected dentin

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Control design applied to a non-ideal structural system with behavior chaotic

In this paper we study the behavior of a structure vulnerable to excessive vibrations caused by an non-ideal power source. To perform this study, the mathematical model is proposed, derive the equations of motion for a simple plane frame excited by an unbalanced rotating machine with limited power (non-ideal motor). The non-linear and non-ideal dynamics in system is demonstrated with a chaotic behavior. We use a State-Dependent Riccati Equation Control technique for regulate the chaotic behavior, in order to obtain a periodic orbit small and to decrease its amplitude. The simulation results show the identification by State-Dependent Riccati Equation Control is very effective. © 2013 Academic Publications, Ltd.

Transfer of technical know-how in the machine-tool industry in Brazil, part II: the example of Brazil

Includes bibliography

Comparison of Physicochemical Surface Conditioning Methods for Adhesion of bis-GMA Resin Cement to Particulate Filler Composite and Surface Characterization

This study compared the effect of physicochemical surface conditioning methods on the adhesion of bis-GMA-based resin cement to particulate filler composite (PFC) used for indirect dental restorations. PFC blocks (N (block)=54, n (block)=9 per group) were polymerized and randomly subjected to one of the following surface conditioning methods: a) No conditioning (Control-C), b) Hydrofluoric acid (HF)etching for 60s (AE60), c) HF for 90s (AE90), d) HF for 120s (AE120), e) HF for 180s (AE180), and f) air-abrasion with 30 mu m silica-coated alumina particles (AB). The conditioned surfaces were silanized with an MPS silane, and an adhesive resin was applied. Resin composite blocks were bonded to PFC using resin cement and photo-polymerized. PFC-cement-resin composite blocks were cut under coolant water to obtain bar specimens (1mmx0.8mm). Microtensile bond strength test (mu TBS)was performed in a universal testing machine (1mm/min). After debonding, failure modes were classified using stereomicroscopy. Surface characterization was performed on a set of separate specimen surfaces using Scanning Electron Microscopy (SEM), X-Ray Dispersive Spectroscopy (XDS), X-Ray Photoelectron Spectroscopy (XPS), and Fourier Transform-Raman Spectroscopy (FT-RS). Mean mu TBS (MPa) of C (35.6 +/- 4.9) was significantly lower than those of other groups (40.2 +/- 5.6-47.4 +/- 6.1) (p<0.05). The highest mu TBS was obtained in Group AB (47.4 +/- 6.1). Prolonged duration of HF etching increased the results (AE180: 41.9 +/- 7), but was not significantly different than that of AB (p>0.05). Failure types were predominantly cohesive in PFC (34 out of 54) followed by cohesive failure in the cement (16 out of 54). Degree of conversion (DC) of the PFC was 63 +/- 10%. SEM analysis showed increased irregularities on PFC surfaces with the increased etching time. Chemical surface analyses with XPS and FT-RS indicated 11-70% silane on the PFC surfaces that contributed to improved bond strength compared to Group C that presented 5% silane, which seemed to be a threshold. Group AB displayed 83% SiO2 and 17% silane on the surfaces.

Streptococcus Mutans Adhesion to Titanium After Brushing with Fluoride and Fluoride-Free Toothpaste Simulating 10 Years of Use

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Bond Strength of Different Resin Cement and Ceramic Shades Bonded to Dentin

Purpose: To evaluate the microtensile bond strength (MTBS) of ceramic cemented to dentin varying the resin cement and ceramic shades.Materials and Methods: Two VITA VM7 ceramic shades (Base Dentine 0M1 and Base Dentine 5M3) were used. A spectrophotometer was used to determine the percentage translucency of ceramic (thickness: 2.5 mm). For the MTBS test, 80 molar dentin surfaces were etched and an adhesive was applied. Forty blocks (7.2 x 7.2 x 2.5 mm) of each ceramic shade were produced and the ceramic surface was etched (10% hydrofluoric acid) for 60 s, followed by the application of silane and resin cement (A3 yellow and transparent). The blocks were cemented to dentin using either A3 or transparent cement. Specimens were photoactivated for 20 s or 40 s, stored in distilled water (37 degrees C/24 h), and sectioned. Eight experimental groups were obtained (n = 10). Specimens were tested for MTSB using a universal testing machine. Data were statistically analyzed using ANOVA and Tukey's post-hoc tests (alpha <= 0.05).Results: The percentage translucency of 0M1 and 5M3 ceramics were 10.06 (+/- 0.25)% and 1.34 (+/- 0.02)%, respectively. The lowest MTBS was observed for the ceramic shade 5M3. For the 0M1 ceramic, the A3 yellow cement that was photocured for 20 s exhibited the lowest MTBS, while the transparent cement that was photocured for 40 s presented the highest MTBS.Conclusions: For the 2.5-mm-thick 5M3 ceramic restorations, the MTBS of ceramic cemented to dentin significantly increased. The dual-curing cement Variolink II photocured for 40 s is not recommended for cementing the Base Dentine 5M3 feldspathic ceramic to dentin.

Can Heat Treatment Procedures of Pre-hydrolyzed Silane Replace Hydrofluoric Acid in the Adhesion of Resin Cement to Feldspathic Ceramic?

Purpose: To evaluate the influence of heat treatment (HT) procedures of a pre-hydrolyzed silane on bond strength of resin cement to a feldspathic ceramic.Materials and Methods: Ceramic and composite blocks (N = 30) were divided into six groups (n = 5) and subjected to the following conditioning procedures: G1: 9.6% hydrofluoric acid (HF) for 20 s + silane (RelyX Ceramic Primer, 3M ESPE) + resin cement (Panavia F2.0, Kuraray) (control); G2: HF (20 s) + silane + heat treatment in furnace (HTF) (100 degrees C, 2 min) + resin cement; G3: silane + HTF + resin cement; G4-HF (20 s) + silane + heat treatment with hot air (HTA) (50 +/- 5 degrees C for 1 min) + resin cement; G5: silane + HTA + resin cement; G6: silane + resin cement. The microtensile bond strength (MTBS) test was performed using a universal testing machine (1 mm/min). After debonding, the substrate and adherent surfaces were analyzed using a stereomicroscope and SEM to categorize the failure types. The data were statistically evaluated using one-way ANOVA and Tukey's test (5%).Results: The control group (G1) showed no pre-test failures and presented significantly higher mean MTBS (16.01 +/- 1.12 MPa) than did other groups (2.63 +/- 1.05 to 12.55 +/- 1.52 MPa) (p = 0.0001). In the groups where HF was not used, HTF (G3: 12.55 +/- 1.52 MPa) showed significantly higher MTBS than did HTA (G5: 2.63 +/- 1.05 MPa) (p < 0.05). All failure types were mixed, ie, adhesive between the resin cement and ceramic accompanied by cohesive failure in the cement.Conclusion: Heat treatment procedures for the pre-hydrolyzed silane either in a furnace or with the application of hot air cannot replace the use of HF gel for the adhesion of resin cement to feldspathic ceramic. Yet when mean bond strengths and incidence of pre-test failures are considered, furnace heat treatment delivered the second best results after the control group, being considerably better than hot air application.

Effect of Resin Cement Type on the Microtensile Bond Strength to Lithium Disilicate Ceramic and Dentin Using Different Test Assemblies

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Effect of Surface Conditioning Modalities on the Repair Bond Strength of Resin Composite to the Zirconia Core / Veneering Ceramic Complex

Purpose: This study evaluated the effect of different surface conditioning protocols on the repair strength of resin composite to the zirconia core / veneering ceramic complex, simulating the clinical chipping phenomenon.Materials and Methods: Forty disk-shaped zirconia core (Lava Zirconia, 3M ESPE) (diameter: 3 mm) specimens were veneered circumferentially with a feldspathic veneering ceramic (VM7, Vita Zahnfabrik) (thickness: 2 mm) using a split metal mold. They were then embedded in autopolymerizing acrylic with the bonding surfaces exposed. Specimens were randomly assigned to one of the following surface conditioning protocols (n = 10 per group): group 1, veneer: 4% hydrofluoric acid (HF) (Porcelain Etch) + core: aluminum trioxide (50-mu m Al2O3) + core + veneer: silane (ESPE-Sil); group 2: core: Al2O3 (50 mu m) + veneer: HF + core + veneer: silane; group 3: veneer: HF + core: 30 mu m aluminum trioxide particles coated with silica (30 mu m SiO2) + core + veneer: silane; group 4: core: 30 mu m SiO2 + veneer: HF + core + veneer: silane. Core and veneer ceramic were conditioned individually but no attempt was made to avoid cross contamination of conditioning, simulating the clinical intraoral repair situation. Adhesive resin (VisioBond) was applied to both the core and the veneer ceramic, and resin composite (Quadrant Posterior) was bonded onto both substrates using polyethylene molds and photopolymerized. After thermocycling (6000 cycles, 5 degrees C-55 degrees C), the specimens were subjected to shear bond testing using a universal testing machine (1 mm/min). Failure modes were identified using an optical microscope, and scanning electron microscope images were obtained. Bond strength data (MPa) were analyzed statistically using the non-parametric Kruskal-Wallis test followed by the Wilcoxon rank-sum test and the Bonferroni Holm correction (alpha = 0.05).Results: Group 3 demonstrated significantly higher values (MPa) (8.6 +/- 2.7) than those of the other groups (3.2 +/- 3.1, 3.2 +/- 3, and 3.1 +/- 3.5 for groups 1, 2, and 4, respectively) (p < 0.001). All groups showed exclusively adhesive failure between the repair resin and the core zirconia. The incidence of cohesive failure in the ceramic was highest in group 3 (8 out of 10) compared to the other groups (0/10, 2/10, and 2/10, in groups 1, 2, and 4, respectively). SEM images showed that air abrasion on the zirconia core only also impinged on the veneering ceramic where the etching pattern was affected.Conclusion: Etching the veneer ceramic with HF gel and silica coating of the zirconia core followed by silanization of both substrates could be advised for the repair of the zirconia core / veneering ceramic complex.

Influence of Nd:YAG Laser on the Bond Strength of Self-etching and Conventional Adhesive Systems to Dental Hard Tissues

Purpose: The aim of this study was to investigate the influence of Nd:YAG laser on the shear bond strength to enamel and dentin of total and self-etch adhesives when the laser was applied over the adhesives, before they were photopolymerized, in an attempt to create a new bonding layer by dentin-adhesive melting.Material and Methods: One-hundred twenty bovine incisors were ground to obtain flat surfaces. Specimens were divided into two substrate groups (n=60): substrate E (enamel) and substrate D (dentin). Each substrate group was subdivided into four groups (n=15), according to the surface treatment accomplished: X (Xeno III self-etching adhesive, control), XL (Xeno III + laser Nd:YAG irradiation at 140 mJ/10 Hz for 60 seconds + photopolymerization, experimental), S (acid etching + Single Bond conventional adhesive, Control), and SL (acid etching + Single Bond + laser Nd:YAG at 140 mJ/10 Hz for 60 seconds + photopolymerization, experimental). The bonding area was delimited with 3-mm-diameter adhesive tape for the bonding procedures. Cylinders of composite were fabricated on the bonding area using a Teflon matrix. The teeth were stored in water at 37 degrees C/48 h and submitted to shear testing at a crosshead speed of 0.5 mm/min in a universal testing machine. Results were analyzed with three-way analysis of variance (ANOVA; substrate, adhesive, and treatment) and Tukey tests (alpha=0.05). ANOVA revealed significant differences for the substrate, adhesive system, and type of treatment: lased or unlased (p<0.05). The mean shear bond strength values (MPa) for the enamel groups were X=20.2 +/- 5.61, XL=23.6 +/- 4.92, S=20.8 +/- 4.55, SL=22.1 +/- 5.14 and for the dentin groups were X=14.1 +/- 7.51, XL=22.2 +/- 6.45, S=11.2 +/- 5.77, SL=15.9 +/- 3.61. For dentin, Xeno III self-etch adhesive showed significantly higher shear bond strength compared with Single Bond total-etch adhesive; Nd:YAG laser irradiation showed significantly higher shear bond strength compared with control (unlased).Conclusion: Nd:YAG laser application prior to photopolymerization of adhesive systems significantly increased the bond strength to dentin.

A path- and label-cost propagation approach to speedup the training of the optimum-path forest classifier

In general, pattern recognition techniques require a high computational burden for learning the discriminating functions that are responsible to separate samples from distinct classes. As such, there are several studies that make effort to employ machine learning algorithms in the context of big data classification problems. The research on this area ranges from Graphics Processing Units-based implementations to mathematical optimizations, being the main drawback of the former approaches to be dependent on the graphic video card. Here, we propose an architecture-independent optimization approach for the optimum-path forest (OPF) classifier, that is designed using a theoretical formulation that relates the minimum spanning tree with the minimum spanning forest generated by the OPF over the training dataset. The experiments have shown that the approach proposed can be faster than the traditional one in five public datasets, being also as accurate as the original OPF. (C) 2014 Elsevier B. V. All rights reserved.

Multi-scale lacunarity as an alternative to quantify and diagnose the behavior of prostate cancer

Prostate cancer is a serious public health problem accounting for up to 30% of clinical tumors in men. The diagnosis of this disease is made with clinical, laboratorial and radiological exams, which may indicate the need for transrectal biopsy. Prostate biopsies are discerningly evaluated by pathologists in an attempt to determine the most appropriate conduct. This paper presents a set of techniques for identifying and quantifying regions of interest in prostatic images. Analyses were performed using multi-scale lacunarity and distinct classification methods: decision tree, support vector machine and polynomial classifier. The performance evaluation measures were based on area under the receiver operating characteristic curve (AUC). The most appropriate region for distinguishing the different tissues (normal, hyperplastic and neoplasic) was defined: the corresponding lacunarity values and a rule's model were obtained considering combinations commonly explored by specialists in clinical practice. The best discriminative values (AUC) were 0.906, 0.891 and 0.859 between neoplasic versus normal, neoplasic versus hyperplastic and hyperplastic versus normal groups, respectively. The proposed protocol offers the advantage of making the findings comprehensible to pathologists. (C) 2014 Elsevier Ltd. All rights reserved.

Semi-supervised learning with concept drift using particle dynamics applied to network intrusion detection data

Concept drift, which refers to non stationary learning problems over time, has increasing importance in machine learning and data mining. Many concept drift applications require fast response, which means an algorithm must always be (re)trained with the latest available data. But the process of data labeling is usually expensive and/or time consuming when compared to acquisition of unlabeled data, thus usually only a small fraction of the incoming data may be effectively labeled. Semi-supervised learning methods may help in this scenario, as they use both labeled and unlabeled data in the training process. However, most of them are based on assumptions that the data is static. Therefore, semi-supervised learning with concept drifts is still an open challenging task in machine learning. Recently, a particle competition and cooperation approach has been developed to realize graph-based semi-supervised learning from static data. We have extend that approach to handle data streams and concept drift. The result is a passive algorithm which uses a single classifier approach, naturally adapted to concept changes without any explicit drift detection mechanism. It has built-in mechanisms that provide a natural way of learning from new data, gradually "forgetting" older knowledge as older data items are no longer useful for the classification of newer data items. The proposed algorithm is applied to the KDD Cup 1999 Data of network intrusion, showing its effectiveness.