Effect of Artificial Aging on the Roughness and Microhardness of Sealed Composites

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

Influence of Different Base Thicknesses on Maxillary Complete Denture Processing: Linear and Angular Graphic Analysis on the Movement of Artificial Teeth

Objective: The purpose of this study was to compare the dental movement that occurs during the processing of maxillary complete dentures with 3 different base thicknesses, using 2 investment methods, and microwave polymerization.Methods: A sample of 42 denture models was randomly divided into 6 groups (n = 7), with base thicknesses of 1.25, 2.50, and 3.75 mm and gypsum or silicone flask investment. Points were demarcated on the distal surface of the second molars and on the back of the gypsum cast at the alveolar ridge level to allow linear and angular measurement using AutoCAD software. The data were subjected to analysis of variance with double factor, Tukey test and Fisher (post hoc).Results: Angular analysis of the varying methods and their interactions generated a statistical difference (P = 0.023) when the magnitudes of molar inclination were compared. Tooth movement was greater for thin-based prostheses, 1.25 mm (-0.234), versus thick 3.75 mm (0.2395), with antagonistic behavior. Prosthesis investment with silicone (0.053) showed greater vertical change compared with the gypsum investment (0.032). There was a difference between the point of analysis, demonstrating that the changes were not symmetric.Conclusions: All groups evaluated showed change in the position of artificial teeth after processing. The complete denture with a thin base (1.25 mm) and silicone investment showed the worst results, whereas intermediate thickness (2.50 mm) was demonstrated to be ideal for the denture base.

Alteration of blue pigment in artificial iris in ocular prosthesis: Effect of paint, drying method and artificial aging

The artificial iris is the structure responsible for the dissimulation and aesthetics of ocular prosthesis. The objective of the present study was to evaluate the color stability of artificial iris of microwaveable polymerized ocular prosthesis, as a function of paint type, drying method and accelerated aging. A total of 40 discs of microwaveable polymerized acrylic resin were fabricated, and divided according to the blue paint type ( n = 5): hydrosoluble acrylic, nitrocellulose automotive, hydrosoluble gouache and oil paints. Paints where dried either at natural or at infrared light bulb method. Each specimen was constituted of one disc in colorless acrylic resin and another colored with a basic sclera pigment. Painting was performed in one surface of one of the discs. The specimens were submitted to an artificial aging chamber under ultraviolet light, during 1008 h. A reflective spectrophotometer was used to evaluate color changes. Data were evaluated by 3-way repeated-measures ANOVA and the Tukey HSD test (alpha = 0.05). All paints suffered color alteration. The oil paint presented the highest color resistance to artificial aging regardless of drying method. (C) 2010 British Contact Lens Association. Published by Elsevier Ltd. All rights reserved.

Surface roughness and hardness of a composite resin: influence of finishing and polishing and immersion methods

This study evaluated the finishing and polishing effect on the surface roughness and hardness of the Filtek Supreme XT, in fluoride solutions. Specimens were prepared (n = 140) with half of the samples finished and polished with Super-Snap (R) disks. The experimental groups were divided according to the presence or absence of finishing and polishing and immersion solutions (artificial saliva, sodium fluoride solution at 0.05%-manipulated, Fluordent Reach, Oral B, Fluorgard). The specimens remained immersed in artificial saliva for 24 hours and were then subjected to initial analysis (baseline) of surface roughness and Vickers microhardness. Next, they were immersed in different fluoride solutions for 1 min/day, for 60 days. Afterwards, a new surface roughness and microhardness reading was conducted. The data were submitted to a two-way ANOVA and Tukey's test (5% significance level). For the comparison of mean roughness and hardness at baseline and after 60 days, the paired Student t test was used. The results showed that the surface roughness and microhardness of the Filtek Supreme XT were influenced by the finishing and polishing procedure, independently of the immersion methods.

Influence of surface sealant on the translucency of composite resin: effect of immersion time and immersion media

This study evaluated the effect of surface sealant on the translucency of composite resin immersed in different solutions. The study involved the following materials: Charisma, Fortify and coffee, Coca-Cola®, tea and artificial saliva as solutions. Sixty-four specimens (n = 8) were manufactured and immersed in artificial saliva at 37 ± 1 °C. Samples were immersed in the solutions for three times a day and re-immersed in artificial saliva until the translucency readings. The measurements were carried out at nine times: T1 - 24 hours after specimen preparation, T2 - 24 hours after immersion in the solutions, T3 - 48 hours and T4 to T9 - 7, 14, 21, 30, 60 and 90 days, respectively, after immersion. The translucency values were measured using a JOUAN device. The results were subjected to ANOVA and Tukey's test at 5%. The surface sealant was not able to protect the composite resin against staining, the coffee showed the strongest staining action, followed by tea and regarding immersion time, a significant alteration was noted in the translucency of composite resin after 21 days.

Effects of artificial substratum types and exposure time on macroalgal colonization in a tropical stream

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

Weather-based prediction of anthracnose severity using artificial neural network models

Data were collected and analysed from seven field sites in Australia, Brazil and Colombia on weather conditions and the severity of anthracnose disease of the tropical pasture legume Stylosanthes scabra caused by Colletotrichum gloeosporioides. Disease severity and weather data were analysed using artificial neural network (ANN) models developed using data from some or all field sites in Australia and/or South America to predict severity at other sites. Three series of models were developed using different weather summaries. of these, ANN models with weather for the day of disease assessment and the previous 24 h period had the highest prediction success, and models trained on data from all sites within one continent correctly predicted disease severity in the other continent on more than 75% of days; the overall prediction error was 21.9% for the Australian and 22.1% for the South American model. of the six cross-continent ANN models trained on pooled data for five sites from two continents to predict severity for the remaining sixth site, the model developed without data from Planaltina in Brazil was the most accurate, with >85% prediction success, and the model without Carimagua in Colombia was the least accurate, with only 54% success. In common with multiple regression models, moisture-related variables such as rain, leaf surface wetness and variables that influence moisture availability such as radiation and wind on the day of disease severity assessment or the day before assessment were the most important weather variables in all ANN models. A set of weights from the ANN models was used to calculate the overall risk of anthracnose for the various sites. Sites with high and low anthracnose risk are present in both continents, and weather conditions at centres of diversity in Brazil and Colombia do not appear to be more conducive than conditions in Australia to serious anthracnose development.

Smart structures health monitoring using artificial neural network

This paper presents a non-model based technique to detect and locate structural damage with the use of artificial neural networks. This method utilizes high frequency structural excitation (typically greater than 30 kHz) through a surface-bonded piezoelectric sensor/actuator to detect changes in structural point impedance due to the presence of damage. Two sets of artificial neural networks were developed in order to detect, locate and characterize structural damage by examining changes in the measured impedance curves. A simulation beam model was developed to verify the proposed method. An experiment was successfully performed in detecting damage on a 4-bay structure with bolted-joints, where the bolts were progressively released.

Optimization of Radial Basis Function neural network employed for prediction of surface roughness in hard turning process using Taguchi's orthogonal arrays

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Evaluation of the Possibility of Removing Staining by Repolishing Composite Resins Submitted to Artificial Aging

This in vitro research verified the possibility of eliminating staining caused by coffee and red wine in five composite resins, after being submitted to thermal cycling. Thirty-six specimens were prepared and immersed in water at 37 degrees C for 24 hours. After polishing, specimen color was measured in a spectrophotometer Cintra 10 UV (Visible Spectrometer, GBC, Braeside, VIC, Australia). All specimens were submitted to thermal cycling at temperatures of 5 and 55 degrees C with a dwell time of 1 minute, for 1,000 cycles in a 75% ethanol/water solution. After thermal cycling, the specimens were immersed in water at 37 degrees C until 7 days had elapsed from the time the specimens were prepared. All specimens were then taken to the spectrophotometer for color measurement. The specimens were divided into three groups (N = 12): distilled water (control), coffee, and red wine. For the staining process to occur on only one surface, all the sides, except one, of the surfaces were isolated with white wax. The specimens were immersed in one of the solutions at 37 degrees C for 14 days. The specimens were dried and taken to the spectrophotometer for color measurement. After this, the specimens were submitted to 20 mu m wear three times, and the color was measured after each one of the wear procedures. Calculation of the color difference was made using CIEDE2000 formula. According to the methodology used in this research, it was concluded that the staining caused by coffee and red wine was superficial and one wear of 20 mu m was sufficient to remove the discoloration.

Effect of Surface Treatments on the Bond Strength between Composite Resin and Acrylic Resin Denture Teeth

Purpose: This investigation studied the effects of 3 surface treatments on the shear bond strength of a light-activated composite resin bonded to acrylic resin denture teeth. Materials and Methods: The occlusal surfaces of 30 acrylic resin denture teeth were ground flat with up to 400-grit silicon carbide paper. Three different surface treatments were evaluated: (1) the flat ground surfaces were primed with methyl methacrylate (MMA) monomer for 180 seconds; (2) light-cured adhesive resin was applied and light polymerized according to the manufacturer's instructions; and (3) treatment 1 followed by treatment 2. The composite resin was packed on the prepared surfaces using a split mold. The interface between tooth and composite was loaded at a cross-head speed of 0.5 mm/min until failure. Results: Analysis of variance indicated significant differences between the surface treatments. Results of mean comparisons using Tukey's test showed that significantly higher shear bond strengths were developed by bonding composite resin to the surfaces that were previously treated with MMA and then with the bonding agent when compared to the other treatments. Conclusion: Combined surface treatment of MMA monomer followed by application of light-cured adhesive resin provided the highest shear bond strength between composite resin and acrylic resin denture teeth.

An investigation of electrolytic surface damages and electroplated crhomium effects on fatigue behavior of high strength steel

Fatigue crack initiation occurs at the surface, although sub surface nucleation has also been reported. Localized imperfections like inclusions close to surface and surface small pits can result in crack sources. Coatings are not always beneficial by fatigue point of view too. Mechanical properties of the covering material can change considerably the fatigue behavior of base metal due to residual surface stresses, to micro cracks or to hydrogen embrittlement. This paper is concerned with analysis of electrolytic etch on the fatigue resistance of a 35NCD16 high strength steel in a mechanical condition of (1760 - 1960) MPa, and analysis of electroplated hard chromium effects on the fatigue resistance in a strength condition of 989 MPa. Hardness impression was used as a reference parameter in case of electrolytic etch. In both cases, experimental data showed that fatigue strength of 35NCD16 steel was considerably reduced. Copyright © 2001 Society of Automotive Engineers, Inc.

Bond strength of acrylic teeth to denture base resin after various surface conditioning methods before and after thermocycling

This study aimed to evaluate the durability of adhesion between acrylic teeth and denture base acrylic resin. The base surfaces of 24 acrylic teeth were flatted and submitted to 4 surface treatment methods: SM1 (control): No SM; SM2: application of a methyl methacrylate-based bonding agent (Vitacol); SM3: air abrasion with 30-μm silicone oxide plus silane; SM4: SM3 plus SM2. A heat-polymerized acrylic resin was applied to the teeth. Thereafter, bar specimens were produced for the microtensile test at dry and thermocyled conditions (60 days water storage followed by 12,000 cycles). The results showed that bond strength was significantly affected by the SM (P < .0001) (SM4 = SM2 > SM3 > SM1) and storage regimens (P < .0001) (dry > thermocycled). The methyl methacrylate-based adhesive showed the highest bond strength.

Neural network approach for surface roughness prediction in surface grinding

Several systems are currently tested in order to obtain a feasible and safe method for automation and control of grinding process. This work aims to predict the surface roughness of the parts of SAE 1020 steel ground in a surface grinding machine. Acoustic emission and electrical power signals were acquired by a commercial data acquisition system. The former from a fixed sensor placed near the workpiece and the latter from the electric induction motor that drives the grinding wheel. Both signals were digitally processed through known statistics, which with the depth of cut composed three data sets implemented to the artificial neural networks. The neural network through its mathematical logical system interpreted the signals and successful predicted the workpiece roughness. The results from the neural networks were compared to the roughness values taken from the worpieces, showing high efficiency and applicability on monitoring and controlling the grinding process. Also, a comparison among the three data sets was carried out.

Plant species identification using multi-scale fractal dimension applied to images of adaxial surface epidermis

This paper presents the study of computational methods applied to histological texture analysis in order to identify plant species, a very difficult task due to the great similarity among some species and presence of irregularities in a given species. Experiments were performed considering 300 ×300 texture windows extracted from adaxial surface epidermis from eight species. Different texture methods were evaluated using Linear Discriminant Analysis (LDA). Results showed that methods based on complexity analysis perform a better texture discrimination, so conducting to a more accurate identification of plant species. © 2009 Springer Berlin Heidelberg.