Stress distribution in delayed replanted teeth splinted with different orthodontic wires: a three-dimensional finite element analysis

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

Zirconia-based dental crown to support a removable partial denture: a three-dimensional finite element analysis using contact elements and micro-CT data

Veneer fracture is the most common complication in zirconia-based restorations. The aim of this study was to evaluate the mechanical behavior of a zirconia-based crown in a lower canine tooth supporting removable partial denture (RPD) prosthesis, varying the bond quality of the veneer/coping interface. Microtomography (μCT) data of an extracted left lower canine were used to build the finite element model (M) varying the core material (gold core - MAu; zirconia core - MZi) and the quality of the veneer/core interface (complete bonded - MZi; incomplete bonded - MZi-NL). The incomplete bonding condition was only applied for zirconia coping by using contact elements (Target/Contact) with 0.3 frictional coefficients. Stress fields were obtained using Ansys Workbench 10.0. The loading condition (L = 1 N) was vertically applied at the base of the RPD prosthesis metallic support towards the dental apex. Maximum principal (σmax) and von Mises equivalent (σvM) stresses were obtained. The σmax (MPa) for the bonded condition was similar between gold and zirconia cores (MAu, 0.42; MZi, 0.40). The incomplete bonded condition (MZi-NL) raised σmax in the veneer up to 800% (3.23 MPa) in contrast to the bonded condition. The peak of σvM increased up to 270% in the MZi-NL. The incomplete bond condition increasing the stress in the veneer/zirconia interface.

Three-dimensional finite element analysis of anterior single implant-supported prostheses with different bone anchorages

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

Straight and angulated abutments in platform switching: influence of loading on bone stress by three-dimensional finite element analysis

PURPOSE: In view of reports in the literature on the benefits achieved with the use of platform switching, described as the use of an implant with a larger diameter than the abutment diameter, the goal being to prevent the (previously) normal bone loss down to the first thread that occurs around most implants, thus enhancing soft tissue aesthetics and stability and the need for implant inclination due to bone anatomy in some cases, the aim of this study was to evaluate bone stress distribution on peri-implant bone, by using three-dimensional finite element analysis to simulate the influence of implants with different abutment angulations (0 and 15 degrees) in platform switching. METHODS: Four mathematical models of an implant-supported central incisor were created with varying abutment angulations: straight abutment (S1 and S2) and angulated abutment at 15 degrees (A1 and A2), submitted to 2 loading conditions (100 N): S1 and A1-oblique loading (45 degrees) and S2 and A2-axial loading, parallel to the long axis of the implant. Maximum (σmax) and minimum (σmin) principal stress values were obtained for cortical and trabecular bone. RESULTS: Models S1 and A1 showed higher σmax in cortical and trabecular bone when compared with S2 and A2. The highest σmax values (in MPa) in the cortical bone were found in S1 (28.5), followed by A1 (25.7), S2 (11.6), and A2 (5.15). For the trabecular bone, the highest σmax values were found in S1 (7.53), followed by A1 (2.87), S2 (2.85), and A2 (1.47). CONCLUSIONS: Implants with straight abutments generated the highest stress values in bone. In addition, this effect was potentiated when the load was applied obliquely.

Evaluation of comprehensive two-dimensional gas chromatography coupled to rapid scanning quadrupole mass spectrometry for quantitative analysis

Comprehensive two-dimensional gas chromatography (GC x GC) is a powerful technique that provides excellent separation and identification of analytes in highly complex samples with considerable increase in GC peak capacities. However, since second dimension analyses are very fast, detectors with a rapid acquisition rate are required. Over the last years, quite a number of studies have discussed the potential and limitations of the combination GC x GC with a variety of quadrupole mass spectrometers. The present research focuses on the evaluation of qMS effectiveness at a 10,000-amu/s scan speed and 20-Hz scan frequency for the identification (full scan mode acquisition-TIC) and quantification (extracted ion chromatogram) of target pesticide residues in tomato samples. The following MS parameters have been evaluated: number of data points per peak, mass spectrum quality, peak skewing, and sensitivity. The validated proposed GC x GC/qMS method presented satisfactory results in terms of repeatability (coefficient of variation lower than 15%), accuracy (84-117%), and linearity (ranging from 25 to 500 ng/g), while significant enhancement in sensitivity was observed (a factor of around 10) under scan conditions. (C) 2012 Elsevier B.V. All rights reserved.

Three-Dimensional Finite Element Analysis of Stress Distribution on Different Bony Ridges With Different Lengths of Morse Taper Implants and Prosthesis Dimensions

This finite element analysis (FEA) compared stress distribution on different bony ridges rehabilitated with different lengths of morse taper implants, varying dimensions of metal-ceramic crowns to maintain the occlusal alignment. Three-dimensional FE models were designed representing a posterior left side segment of the mandible: group control, 3 implants of 11 mm length; group 1, implants of 13 mm, 11 mm and 5 mm length; group 2, 1 implant of 11 mm and 2 implants of 5 mm length; and group 3, 3 implants of 5 mm length. The abutments heights were 3.5 mm for 13- and 11-mm implants (regular), and 0.8 mm for 5-mm implants (short). Evaluation was performed on Ansys software, oblique loads of 365N for molars and 200N for premolars. There was 50% higher stress on cortical bone for the short implants than regular implants. There was 80% higher stress on trabecular bone for the short implants than regular implants. There was higher stress concentration on the bone region of the short implants neck. However, these implants were capable of dissipating the stress to the bones, given the applied loads, but achieving near the threshold between elastic and plastic deformation to the trabecular bone. Distal implants and/or with biggest occlusal table generated greatest stress regions on the surrounding bone. It was concluded that patients requiring short implants associated with increased proportions implant prostheses need careful evaluation and occlusal adjustment, as a possible overload in these short implants, and even in regular ones, can generate stress beyond the physiological threshold of the surrounding bone, compromising the whole system.

Semi-supervised dimensionality reduction based on partial least squares for visual analysis of high dimensional data

Dimensionality reduction is employed for visual data analysis as a way to obtaining reduced spaces for high dimensional data or to mapping data directly into 2D or 3D spaces. Although techniques have evolved to improve data segregation on reduced or visual spaces, they have limited capabilities for adjusting the results according to user's knowledge. In this paper, we propose a novel approach to handling both dimensionality reduction and visualization of high dimensional data, taking into account user's input. It employs Partial Least Squares (PLS), a statistical tool to perform retrieval of latent spaces focusing on the discriminability of the data. The method employs a training set for building a highly precise model that can then be applied to a much larger data set very effectively. The reduced data set can be exhibited using various existing visualization techniques. The training data is important to code user's knowledge into the loop. However, this work also devises a strategy for calculating PLS reduced spaces when no training data is available. The approach produces increasingly precise visual mappings as the user feeds back his or her knowledge and is capable of working with small and unbalanced training sets.

Stability analysis and area spectrum of three-dimensional Lifshitz black holes

In this work, we probe the stability of a z = 3 three-dimensional Lifshitz black hole by using scalar and spinorial perturbations. We found an analytical expression for the quasinormal frequencies of the scalar probe field, which perfectly agree with the behavior of the quasinormal modes obtained numerically. The results for the numerical analysis of the spinorial perturbations reinforce the conclusion of the scalar analysis, i.e., the model is stable under scalar and spinor perturbations. As an application we found the area spectrum of the Lifshitz black hole, which turns out to be equally spaced.

Two-dimensional numerical approach for the vibration isolation analysis on thin walled wave barriers in poroelastic soils.

[EN]This paper is concerned with the vibration isolation efficiency analysis of total or partially buried thin walled wave barriers in poroelastic soils. A two-dimensional time harmonic model that treats soils and structures in a direct way by combining appropriately the conventional Boundary Element Method (BEM), the Dual BEM (DBEM) and the Finite Element Method es developed to this aim.

Assessing poverty with survey data. Uni-dimensional, multidimensional and resilience poverty analysis in Kenya

Traditionally Poverty has been measured by a unique indicator, income, assuming this was the most relevant dimension of poverty. Sen’s approach has dramatically changed this idea shedding light over the existence of many more dimensions and over the multifaceted nature of poverty; poverty cannot be represented by a unique indicator that only can evaluate a specific aspect of poverty. This thesis tracks an ideal path along with the evolution of the poverty analysis. Starting from the unidimensional analysis based on income and consumptions, this research enter the world of multidimensional analysis. After reviewing the principal approaches, the Foster and Alkire method is critically analyzed and implemented over data from Kenya. A step further is moved in the third part of the thesis, introducing a new approach to multidimensional poverty assessment: the resilience analysis.

Two-dimensional relaxation-diffusion analysis to study water compartmentalization in cells by a single-sided NMR device

In questo lavoro di tesi è presentato un metodo per lo studio della compartimentalizzazione dell’acqua in cellule biologiche, mediante lo studio dell’autodiffusione delle molecole d’acqua tramite uno strumento NMR single-sided. Le misure sono state eseguite nel laboratorio NMR all’interno del DIFA di Bologna. Sono stati misurati i coefficienti di autodiffusione di tre campioni in condizione bulk, ottenendo risultati consistenti con la letteratura. È stato poi analizzato un sistema cellulare modello, Saccharomyces cerevisiae, allo stato solido, ottimizzando le procedure per l’ottenimento di mappe di correlazione 2D, aventi come assi il coefficiente di autodiffusione D e il tempo di rilassamento trasversale T2. In questo sistema l’acqua è confinata e l’autodiffusione è ristretta dalle pareti cellulari, si parla quindi di coefficiente di autodiffusione apparente, Dapp. Mediante le mappe sono state individuate due famiglie di nuclei 1H. Il campione è stato poi analizzato in diluizione in acqua distillata, confermando la separazione del segnale in due distinte famiglie. L’utilizzo di un composto chelato, il CuEDTA, ha permesso di affermare che la famiglia con il Dapp maggiore corrisponde all’acqua esterna alle cellule. L’analisi dei dati ottenuti sulle due famiglie al variare del tempo lasciato alle molecole d’acqua per la diffusione hanno portato alla stima del raggio dei due compartimenti: r=2.3±0.2µm per l’acqua extracellulare, r=0.9±0.1µm per quella intracellulare, che è probabilmente acqua scambiata tra gli organelli e il citoplasma. L’incertezza associata a tali stime tiene conto soltanto dell’errore nel calcolo dei parametri liberi del fit dei dati, è pertanto una sottostima, dovuta alle approssimazioni connesse all’utilizzo di equazioni valide per un sistema poroso costituito da pori sferici connessi non permeabili. Gli ordini di grandezza dei raggi calcolati sono invece consistenti con quelli osservabili dalle immagini ottenute con il microscopio ottico.

Informatics for cross-sample analysis with comprehensive two-dimensional gas chromatography and high-resolution mass spectrometry (GCxGC-HRMS)

This paper describes informatics for cross-sample analysis with comprehensive two-dimensional gas chromatography (GCxGC) and high-resolution mass spectrometry (HRMS). GCxGC-HRMS analysis produces large data sets that are rich with information, but highly complex. The size of the data and volume of information requires automated processing for comprehensive cross-sample analysis, but the complexity poses a challenge for developing robust methods. The approach developed here analyzes GCxGC-HRMS data from multiple samples to extract a feature template that comprehensively captures the pattern of peaks detected in the retention-times plane. Then, for each sample chromatogram, the template is geometrically transformed to align with the detected peak pattern and generate a set of feature measurements for cross-sample analyses such as sample classification and biomarker discovery. The approach avoids the intractable problem of comprehensive peak matching by using a few reliable peaks for alignment and peak-based retention-plane windows to define comprehensive features that can be reliably matched for cross-sample analysis. The informatics are demonstrated with a set of 18 samples from breast-cancer tumors, each from different individuals, six each for Grades 1-3. The features allow classification that matches grading by a cancer pathologist with 78% success in leave-one-out cross-validation experiments. The HRMS signatures of the features of interest can be examined for determining elemental compositions and identifying compounds.

Analysis and Prediction of Transient Opacity Spikes Using Dimensional Modeling

Dimensional modeling, GT-Power in particular, has been used for two related purposes-to quantify and understand the inaccuracies of transient engine flow estimates that cause transient smoke spikes and to improve empirical models of opacity or particulate matter used for engine calibration. It has been proposed by dimensional modeling that exhaust gas recirculation flow rate was significantly underestimated and volumetric efficiency was overestimated by the electronic control module during the turbocharger lag period of an electronically controlled heavy duty diesel engine. Factoring in cylinder-to-cylinder variation, it has been shown that the electronic control module estimated fuel-Oxygen ratio was lower than actual by up to 35% during the turbocharger lag period but within 2% of actual elsewhere, thus hindering fuel-Oxygen ratio limit-based smoke control. The dimensional modeling of transient flow was enabled with a new method of simulating transient data in which the manifold pressures and exhaust gas recirculation system flow resistance, characterized as a function of exhaust gas recirculation valve position at each measured transient data point, were replicated by quasi-static or transient simulation to predict engine flows. Dimensional modeling was also used to transform the engine operating parameter model input space to a more fundamental lower dimensional space so that a nearest neighbor approach could be used to predict smoke emissions. This new approach, intended for engine calibration and control modeling, was termed the "nonparametric reduced dimensionality" approach. It was used to predict federal test procedure cumulative particulate matter within 7% of measured value, based solely on steady-state training data. Very little correlation between the model inputs in the transformed space was observed as compared to the engine operating parameter space. This more uniform, smaller, shrunken model input space might explain how the nonparametric reduced dimensionality approach model could successfully predict federal test procedure emissions when roughly 40% of all transient points were classified as outliers as per the steady-state training data.

Survival Analysis with Large Dimensional Covariates: An Application in Microarray Studies

Use of microarray technology often leads to high-dimensional and low- sample size data settings. Over the past several years, a variety of novel approaches have been proposed for variable selection in this context. However, only a small number of these have been adapted for time-to-event data where censoring is present. Among standard variable selection methods shown both to have good predictive accuracy and to be computationally efficient is the elastic net penalization approach. In this paper, adaptation of the elastic net approach is presented for variable selection both under the Cox proportional hazards model and under an accelerated failure time (AFT) model. Assessment of the two methods is conducted through simulation studies and through analysis of microarray data obtained from a set of patients with diffuse large B-cell lymphoma where time to survival is of interest. The approaches are shown to match or exceed the predictive performance of a Cox-based and an AFT-based variable selection method. The methods are moreover shown to be much more computationally efficient than their respective Cox- and AFT- based counterparts.