Search results for "Machine"
showing 10 items of 2592 documents
Immediate and long-term microshear bond strength of resin-based cements to core build-up materials
2021
Background To evaluate the microshear bond strength (μ-SBS) between resin-based cements and core build-up materials after water storage. Material and methods Cylinders (1x1 mm) of conventional dual-cure resin cement (RelyX ARC, 3M ESPE), universal dual-cure resin cement (RelyX Ultimate, 3M ESPE) or self-adhesive resin cement (RelyX U200, 3M ESPE) were adhered to disks (6x2 mm) made with commercial core build-up materials (Bis-Core, Bisco or LuxaCore Z, DMG) or conventional nanocomposite resin (Filtek Z350 XT, 3M ESPE). The specimens (n=10) were submitted to μ-SBS test using a universal testing machine and fracture pattern analysis at 48 hours or after 9 months of water storage. The data wer…
Bond strength according to the moment of fiber post cutting fixed with self-adhesive cement to the root dentin
2021
Background The fiber posts require a cut in the coronal portion to adjust it to the available clinical space. The cutting of posts cemented may generate tension via bur vibrations of drill on the bonding interface, with the possibility of decreasing the bond strength. Thus, this study aimed to evaluate if the moment of cutting the fiber posts has an effect on its bond strength when fixed with self-adhesive resin cement. Material and methods Thirty-six bovine teeth were randomly divided into three groups after endodontic treatment and post space preparation (n = 12): IAC- the fiber posts were cutting immediately after cementation; ACR - the fiber posts were cutting after coronal reconstructi…
Bond strength evaluation of the veneering-core ceramics bonds.
2009
The purpose of this study was to determine whether the bond of veneering porcelain to a ceramic core in bilayered ceramics was similar to that of the metal ceramic control of well known behaviour. Six groups of nine specimens each were fabricated, whose dimensions were 15 mm long and 8 mm in diameter at the core, and 2 mm long and 8 mm in diameter for the veneer. The groups were GR. 1 (control group): CrNi alloy/d.SIGN (Ivoclar), GR. 2: IPS e.maxPress/IPS e.maxCeram (Ivoclar), GR. 3: IPS e.maxZirCad/ IPS e.maxZirPress (Ivoclar), GR. 4: IPS e.maxZirCad/IPS e.maxCeram (Ivoclar), GR. 5: Lava Frame (3M ESPE)/ Lava Ceram (3M ESPE) and GR. 6: Lava Frame (3M ESPE)/IPS e.maxCeram (Ivoclar). A shear…
Effects of femtosecond laser and other surface treatments on the bond strength of metallic and ceramic orthodontic brackets to zirconia.
2017
Femtosecond laser has been proposed as a method for conditioning zirconia surfaces to boost bond strength. However, metallic or ceramic bracket bonding to femtosecond lasertreated zirconia surfaces has not been tested. This study compared the effects of four conditioning techniques, including femtosecond laser irradiation, on shear bond strength (SBS) of metallic and ceramic brackets to zirconia.Three hundred zirconia plates were divided into five groups: 1) control (C); 2) sandblasting (APA); 3) silica coating and silane (SC); 4) femtosecond laser (FS); 5) sandblasting followed by femtosecond laser (APA+SC). A thermal imaging camera measured temperature changes in the zirconia during irrad…
System-theoretical analysis of the Clare Bishop Area in the cat
1980
The Clare Bishop Area (CBA) is a retinotopically organized cortical area in the cat brain connected to a great variety of visual areas in a very complex wax (Fig. 1). Experimental analysis is difficult because of the following aspects: 1. As the distance from the retina increases, the signal combinations necessary to analyse the system become more and more specific. 2. Feedback loops cannot be opened, so an unequivocal identification of CBA cell properties is impossible. 3. The nonlinear character seems to have a great influence on signal processing. To circumvent these problems, specific signal combinations leading to a separation of input subsystems have been developed (Hoffmann and v. Se…
Computational identification of chemical compounds with potential anti-Chagas activity using a classification tree
2021
Chagas disease is endemic to 21 Latin American countries and is a great public health problem in that region. Current chemotherapy remains unsatisfactory; consequently the need to search for new drugs persists. Here we present a new approach to identify novel compounds with potential anti-chagasic action. A large dataset of 584 compounds, obtained from the Drugs for Neglected Diseases initiative, was selected to develop the computational model. Dragon software was used to calculate the molecular descriptors and WEKA software to obtain the classification tree. The best model shows accuracy greater than 93.4% for the training set; the tree was also validated using a 10-fold cross-validation p…
Effectiveness of local feature selection in ensemble learning for prediction of antimicrobial resistance
2008
In the real world concepts are often not stable but change over time. A typical example of this in the biomedical context is antibiotic resistance, where pathogen sensitivity may change over time as pathogen strains develop resistance to antibiotics that were previously effective. This problem, known as concept drift (CD), complicates the task of learning a robust model. Different ensemble learning (EL) approaches (that instead of learning a single classifier try to learn and maintain a set of classifiers over time) have been shown to perform reasonably well in the presence of concept drift. In this paper we study how much local feature selection (FS) can improve ensemble performance for da…
Drug Activity Characterization Using One-Class Support Vector Machines with Counterexamples
2013
The problem of detecting chemical activity in drugs from its molecular description constitutes a challenging and hard learning task. The corresponding prediction problem can be tackled either as a binary classification problem (active versus inactive compounds) or as a one class problem. The first option leads usually to better prediction results when measured over small and fixed databases while the second could potentially lead to a much better characterization of the active class which could be more important in more realistic settings. In this paper, a comparison of these two options is presented when support vector models are used as predictors.
Microstructure–property relation and machine learning prediction of hole expansion capacity of high-strength steels
2021
Abstract The relationship between microstructure features and mechanical properties plays an important role in the design of materials and improvement of properties. Hole expansion capacity plays a fundamental role in defining the formability of metal sheets. Due to the complexity of the experimental procedure of testing hole expansion capacity, where many influencing factors contribute to the resulting values, the relationship between microstructure features and hole expansion capacity and the complexity of this relation is not yet fully understood. In the present study, an experimental dataset containing the phase constituents of 55 microstructures as well as corresponding properties, su…
A computer program suitable for analysis of choice of categories in biomedical data recognition problems.
1980
The optimum choice of categories in problems of medical data recognition is governed by the choice of categories, the selection of appropriate features, and by the choice of a loss function. Under these circumstances it is often difficult to find out the suitable classification scheme. The computer program described here serves for the design of the optimum recognition procedure. The Bayes rule is used as decision rule. A criterion for the comparison of different choice of categories is given. The program can be performed after estimation of the underlying prior probabilities and the conditional densities obtained from a training set, and before testing the decision rule with real data.