Evaluation of marginal microleakage in Class II cavities: Effect of microhybrid, flowable, and compactable resins

Objective: The goal of the present study was to evaluate the microleakage on the cementum/dentin and enamel surfaces in Class II restorations, using different kinds of resin composite (microhybrid, flowable, and compactable). Method and materials: Forty human caries-free molars were extracted and selected. Eighty Class II standardized cavities were made in the cervical wall at the cementoenamel junction (CEJ) and at the mesial and distal surfaces. The teeth were divided into four groups: G1 - adhesive system + microhybrid resin composite Z100; G2 - adhesive system + compactable resin composite Prodigy Condensable; G3 - adhesive system + flowable resin composite Revolution + Z100 resin composite; G4 - adhesive system + Revolution fluid resin + compactable resin composite Prodigy Condensable. The adhesive system used in this study was Scotchbond Multi-Purpose Plus. The specimens were thermocycled in baths of 5°C and 55°C for 1,000 cycles and immersed in 50% silver nitrate solution. The specimens then were sectioned and evaluated on degree of dye penetration. Results: The results were evaluated using the nonparametric Kruskall-Wallis test, which showed a statistically significant difference between groups G1 and G4, G2 and G4, and G3 and G4. Conclusions: None of the materials was able to eliminate the marginal microleakage at the cervical wall; the application of a low-viscosity resin composite combined with a compactable resin composite significantly decreased the microleakage.

Autogenous bone graft with or without a calcium sulfate barrier in the treatment of class II furcation defects: A histologic and histometric study in dogs

Background: The purpose of this study was to histologically evaluate the healing of surgically created Class II furcation defects treated using an autogenous bone (AB) graft with or without a calcium sulfate (CS) barrier. Methods: The second, third, and fourth mandibular premolars (P2, P3, and P4) of six mongrel dogs were used in this study. Class II furcation defects (5 mm in height × 2 mm in depth) were surgically created and immediately treated. Teeth were randomly divided into three groups: group C (control), in which the defect was filled with blood clot; group AB, in which the defect was filled with AB graft; and group AB/CS, in which the defect was filled with AB graft and covered by a CS barrier. Elaps were repositioned to cover all defects. The animals were euthanized 90 days post-surgery. Mesio-distal serial sections were obtained and stained with either hematoxylin and eosin or Masson's trichrome. Histometric, using image-analysis software, and histologic analyses were performed. Linear and area measurements of periodontal healing were evaluated and calculated as a percentage of the original defect. Percentage data were transformed into arccosine for statistical analysis (analysis of variance; P<0.05). Results: Periodontal regeneration in the three groups was similar. Regeneration of bone and connective tissue in the furcation defects was incomplete in most of the specimens. Statistically significant differences were not found in any of the evaluated parameters among the groups. Conclusion: Periodontal healing was similar using surgical debridement alone, AB graft, or AB graft with a CS barrier in the treatment of Class II furcation defects.

Classification of lumber of Eucalyptus using non-destructive tests

Classification and standardization of the sawn wood is a usual activity, developed by countries that come as great consumers of this material. Brazil does not practice the classification of sawn wood. This work had the main objective of evaluating the sensibility of most common non-destructive tests in the classification of dimension lumber from fast grown Eucalyptus plantation. Wood was obtained from genetic material cultivated at Minas Gerais State, Brazil. 296 beams of structural dimensions (6 cm × 12 cm × 280 cm) from 10 different clones of Eucalyptus were sampled. Beams were non-destructively (stress wave, ultrasound and transverse vibration) and destructively (static bending and compression parallel to grain) tested. Non-destructive results showed sensibility in the classification of structural dimension lumber, being possible to establish wave velocity intervals that attend to the main strength classes reported by Wooden Structures Brazilian Code.

Automatic classification of enzyme family in protein annotation

Most of the tasks in genome annotation can be at least partially automated. Since this annotation is time-consuming, facilitating some parts of the process - thus freeing the specialist to carry out more valuable tasks - has been the motivation of many tools and annotation environments. In particular, annotation of protein function can benefit from knowledge about enzymatic processes. The use of sequence homology alone is not a good approach to derive this knowledge when there are only a few homologues of the sequence to be annotated. The alternative is to use motifs. This paper uses a symbolic machine learning approach to derive rules for the classification of enzymes according to the Enzyme Commission (EC). Our results show that, for the top class, the average global classification error is 3.13%. Our technique also produces a set of rules relating structural to functional information, which is important to understand the protein tridimensional structure and determine its biological function. © 2009 Springer Berlin Heidelberg.

Coupling rate measurement of a novel multi-actuated piezoelectric device using optical interferometry

The class of piezoelectric actuators considered in this paper consists of a multi-flexible structure actuated by two or more piezoceramic devices that must generate different output displacements and forces at different specified points of the domain and in different directions. The devices were modeled by finite element using the software ANSYS and the topology optimization method. The following XY actuators were build to achieve maximum displacement in the X and Y directions with a minimum crosstalk between them. The actuator prototypes are composed of an aluminum structure, manufactured by using a wire Electrical Discharge Machining, which are bonded to rectangular PZT5A piezoceramic blocks by using epoxy resin. Multi-actuator piezoelectric device displacements can be measured by using optical interferometry, since it allows dynamic measurements in the kHz range, which is of the order of the first resonance frequency of these piezomechanisms. A Michelson-type interferometer, with a He-Ne laser source, is used to measure the displacement amplitudes in nanometric range. A new optical phase demodulation technique is applied, based on the properties of the triangular waveform drive voltage applied to the XY piezoelectric nanopositioner. This is a low-phase-modulation-depth-like technique that allows the rapid interferometer auto-calibration. The measurements were performed at 100 Hz frequency, and revealed that the device is linear voltage range utilized in this work. The ratio between the generated and coupled output displacements and the drive voltages is equal to 10.97 nm/V and 1.76 nm/V, respectively, which corresponds to a 16% coupling rate. © 2010 IEEE.

Simultaneous linearization of a class of pairs of involutions with normally hyperbolic composition

In this paper we obtain a result on simultaneous linearization for a class of pairs of involutions whose composition is normally hyperbolic. This extends the corresponding result when the composition of the involutions is a hyperbolic germ of diffeomorphism. Inside the class of pairs with normally hyperbolic composition, we obtain a characterization theorem for the composition to be hyperbolic. In addition, related to the class of interest, we present the classification of pairs of linear involutions via linear conjugacy. © 2012 Elsevier Masson SAS.

Determinação de áreas prioritárias para o restabelecimento da cobertura florestal, apoiada no uso de geotecnologias

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

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.

Pruning methods to MLP neural networks considering proportional apparent error rate for classification problems with unbalanced data

This article deals with classification problems involving unequal probabilities in each class and discusses metrics to systems that use multilayer perceptrons neural networks (MLP) for the task of classifying new patterns. In addition we propose three new pruning methods that were compared to other seven existing methods in the literature for MLP networks. All pruning algorithms presented in this paper have been modified by the authors to do pruning of neurons, in order to produce fully connected MLP networks but being small in its intermediary layer. Experiments were carried out involving the E. coli unbalanced classification problem and ten pruning methods. The proposed methods had obtained good results, actually, better results than another pruning methods previously defined at the MLP neural network area. (C) 2014 Elsevier Ltd. All rights reserved.

A multisensor, multitemporal approach for monitoring herbaceous vegetation growth in the Amazon floodplain

The Amazon River floodplain is an important source of atmospheric CO2 and CH4. Aquatic herbaceous vegetation (macrophytes) have been shown to contribute significantly to floodplain net primary productivity (NPP) and methane emission in the region. Their fast growth rates under both flooded and dry conditions make herbaceous vegetation the most variable element in the Amazon floodplain NPP budget, and the most susceptible to environmental changes. The present study combines multitemporal Radarsat-1 and MODIS images to monitor spatial and temporal changes in herbaceous vegetation cover in the Amazon floodplain. Radarsat-1 images were acquired from Dec/2003 to Oct/2005, and MODIS daily surface reflectance products were acquired for the two cloud-free dates closest to each Radarsat-1 acquisition. An object-based, hierarchical algorithm was developed using the temporal SAR information to discriminate Permanent Open Water (OW), Floodplain (FP) and Upland (UL) classes at Level 1, and then subdivide the FP class into Woody Vegetation (WV) and Possible Macrophytes (PM) at Level 2. At Level 3, optical and SAR information were combined to discriminate actual herbaceous cover at each date. The resulting maps had accuracies ranging from 80% to 90% for Level 1 and 2 classifications, and from 60% to 70% for Level 3 classifications, with kappa values ranging between 0.7 and 0.9 for Levels 1 and 2 and between 0.5 and 0.6 for Level 3. All study sites had noticeable variations in the extent of herbaceous cover throughout the hydrological year, with maximum areas up to four times larger than minimum areas. The proposed classification method was able to capture the spatial pattern of macrophyte growth and development in the studied area, and the multitemporal information was essential for both separating vegetation cover types and assessing monthly variation in herbaceous cover extent.

Automatic classification of prostate stromal tissue in histological images using Haralick descriptors and Local Binary Patterns

In this paper we presente a classification system that uses a combination of texture features from stromal regions: Haralick features and Local Binary Patterns (LBP) in wavelet domain. The system has five steps for classification of the tissues. First, the stromal regions were detected and extracted using segmentation techniques based on thresholding and RGB colour space. Second, the Wavelet decomposition was applied in the extracted regions to obtain the Wavelet coefficients. Third, the Haralick and LBP features were extracted from the coefficients. Fourth, relevant features were selected using the ANOVA statistical method. The classication (fifth step) was performed with Radial Basis Function (RBF) networks. The system was tested in 105 prostate images, which were divided into three groups of 35 images: normal, hyperplastic and cancerous. The system performance was evaluated using the area under the ROC curve and resulted in 0.98 for normal versus cancer, 0.95 for hyperplasia versus cancer and 0.96 for normal versus hyperplasia. Our results suggest that texture features can be used as discriminators for stromal tissues prostate images. Furthermore, the system was effective to classify prostate images, specially the hyperplastic class which is the most difficult type in diagnosis and prognosis.

Classification of intact fresh plums according to sweetness using time-domain nuclear magnetic resonance and chemometrics

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Cone-beam evaluation of pharyngeal airway space in class I, II, and III patients

The purpose of this study is to make a 3-dimensional (3-D) evaluation of the pharyngeal airway space (PAS) in patients with class I, II, and III malocclusion. Sixty patients were evaluated. The patients were divided in 3 groups according to their occlusion classification. The volume and area of PAS were evaluated using the software Dolphin 3-D Imaging in the preoperative period for orthognathic surgery. PAS volume and area were influenced by different patterns of malocclusion. The mean volume and area for class III patients were statistically bigger than for classes I and II patients (P < .001). There was also a significant difference for volume values between class I and II patients, being the bigger volume for the class I patients (P < .05). It was possible to conclude that the class III patients presented a bigger PAS compared with classes I and II patients.