Effect of cantilever length and framework alloy on the stress distribution of mandibular-cantilevered implant-supported prostheses

The purpose of this in vitro study was to analyze the stress distribution on components of a mandibular-cantilevered implant-supported prosthesis with frameworks cast in cobalt-chromium (Co-Cr) or palladium-silver (Pd-Ag) alloys, according to the cantilever length. Frameworks were fabricated on (Co-Cr) and (Pd-Ag) alloys and screwed into standard abutments positioned on a master-cast containing five implant replicas. Two linear strain gauges were fixed on the mesial and distal aspects of each abutment to capture deformation. A vertical static load of 100 N was applied to the cantilever arm at the distances of 10, 15, and 20 mm from the center of the distal abutment and the absolute values of specific deformation were recorded. Different patterns of abutment deformation were observed according to the framework alloy. The Co-Cr alloy framework resulted in higher levels of abutment deformation than the silver-palladium alloy framework. Abutment deformation was higher with longer cantilever extensions. Physical properties of the alloys used for framework interfere with abutment deformations patterns. Excessively long cantilever extensions must be avoided. To cite this article:Jacques LB, Moura MS, Suedam V, Souza EAC, Rubo JH. Effect of cantilever length and framework alloy on the stress distribution of mandibular-cantilevered implant-supported prostheses.Clin. Oral Impl. Res. 20, 2009; 737-741.doi: 10.1111/j.1600-0501.2009.01712.x.

Effect of abutment`s height and framework alloy on the load distribution of mandibular cantilevered implant-supported prosthesis

In cantilevered implant-supported complete prosthesis, the abutments` different heights represent different lever arms to which the abutments are subjected resulting in deformation of the components, which in turn transmit the load to the adjacent bone. The purpose of this in vitro study was to quantitatively assess the deformation of abutments of different heights in mandibular cantilevered implant-supported complete prosthesis. A circular steel master cast with five perforations containing implant replicas (O3.75 mm) was used. Two groups were formed according to the types of alloy of the framework (CoCr or PdAg). Three frameworks were made for each group to be tested with 4, 5.5 and 7 mm abutments. A 100 N load was applied at a point 15 mm distal to the center of the terminal implant. Readings of the deformations generated on the mesial and distal aspects of the abutments were obtained with the use of strain gauges. Deformation caused by tension and compression was observed in all specimens with the terminal abutment taking most of the load. An increase in deformation was observed in the terminal abutment as the height was increased. The use of an alloy of higher elastic modulus (CoCr) also caused the abutment deformation to increase. Abutment`s height and framework alloy influence the deformation of abutments of mandibular cantilevered implant-supported prosthesis. To cite this article:Suedam V, Capello SouzaEA, Moura MS, Jacques LB, Rubo JH. Effect of abutment`s height and framework alloy on the load distribution of mandibular cantilevered implant-supported prosthesis. Clin. Oral Impl. Res. 20, 2009; 196-200.doi: 10.1111/j.1600-0501.2008.01609.x.

A zero-augmented gamma mixed model for longitudinal data with many zeros

In many occupational safety interventions, the objective is to reduce the injury incidence as well as the mean claims cost once injury has occurred. The claims cost data within a period typically contain a large proportion of zero observations (no claim). The distribution thus comprises a point mass at 0 mixed with a non-degenerate parametric component. Essentially, the likelihood function can be factorized into two orthogonal components. These two components relate respectively to the effect of covariates on the incidence of claims and the magnitude of claims, given that claims are made. Furthermore, the longitudinal nature of the intervention inherently imposes some correlation among the observations. This paper introduces a zero-augmented gamma random effects model for analysing longitudinal data with many zeros. Adopting the generalized linear mixed model (GLMM) approach reduces the original problem to the fitting of two independent GLMMs. The method is applied to evaluate the effectiveness of a workplace risk assessment teams program, trialled within the cleaning services of a Western Australian public hospital.

Hybrid fuzzy Monte Carlo and logic programming model for distribution network reconfiguration in the presence of outages

This paper presents a methodology for distribution networks reconfiguration in outage presence in order to choose the reconfiguration that presents the lower power losses. The methodology is based on statistical failure and repair data of the distribution power system components and uses fuzzy-probabilistic modelling for system component outage parameters. Fuzzy membership functions of system component outage parameters are obtained by statistical records. A hybrid method of fuzzy set and Monte Carlo simulation based on the fuzzy-probabilistic models allows catching both randomness and fuzziness of component outage parameters. Once obtained the system states by Monte Carlo simulation, a logical programming algorithm is applied to get all possible reconfigurations for every system state. In order to evaluate the line flows and bus voltages and to identify if there is any overloading, and/or voltage violation a distribution power flow has been applied to select the feasible reconfiguration with lower power losses. To illustrate the application of the proposed methodology to a practical case, the paper includes a case study that considers a real distribution network.

Logic programming and fuzzy Monte Carlo for distribution network reconfiguration

This paper present a methodology to choose the distribution networks reconfiguration that presents the lower power losses. The proposed methodology is based on statistical failure and repair data of the distribution power system components and uses fuzzy-probabilistic modeling for system component outage parameters. The proposed hybrid method using fuzzy sets and Monte Carlo simulation based on the fuzzyprobabilistic models allows catching both randomness and fuzziness of component outage parameters. A logic programming algorithm is applied, once obtained the system states by Monte Carlo Simulation, to get all possible reconfigurations for each system state. To evaluate the line flows and bus voltages and to identify if there is any overloading, and/or voltage violation an AC load flow has been applied to select the feasible reconfiguration with lower power losses. To illustrate the application of the proposed methodology, the paper includes a case study that considers a 115 buses distribution network.

Trypanosoma cruzi: cell charge distribution

Differences in cell charge between epimastigote and trypomastigote populations were compared in Y, Cl and Colombiana strains of T. cruzi. Trypomastigote populations were more homogenous in relation to cell charge than epimastigotes. This homogeneity of cell charge was not the result of the selection of trypomastigote sub-populations by the host immunosystem, but may be the result of a surface coat formed by host blood components.

DC Fuzzy Multicriteria Approach to Increase the Probability of Delivering Power in Distribution Networks

This paper proposes a methodology to increase the probability of delivering power to any load point through the identification of new investments. The methodology uses a fuzzy set approach to model the uncertainty of outage parameters, load and generation. A DC fuzzy multicriteria optimization model considering the Pareto front and based on mixed integer non-linear optimization programming is developed in order to identify the adequate investments in distribution networks components which allow increasing the probability of delivering power to all customers in the distribution network at the minimum possible cost for the system operator, while minimizing the non supplied energy cost. To illustrate the application of the proposed methodology, the paper includes a case study which considers an 33 bus distribution network.

Increase of the Delivered Power Probability in Distribution Networks using Pareto DC Programming

A methodology to increase the probability of delivering power to any load point through the identification of new investments in distribution network components is proposed in this paper. The method minimizes the investment cost as well as the cost of energy not supplied in the network. A DC optimization model based on mixed integer non-linear programming is developed considering the Pareto front technique in order to identify the adequate investments in distribution networks components which allow increasing the probability of delivering power for any customer in the distribution system at the minimum possible cost for the system operator, while minimizing the energy not supplied cost. Thus, a multi-objective problem is formulated. To illustrate the application of the proposed methodology, the paper includes a case study which considers a 180 bus distribution network

Multi-criteria optimisation approach to increase the delivered power in radial distribution networks

This study proposes a new methodology to increase the power delivered to any load point in a radial distribution network, through the identification of new investments in order to improve the repair time. This research work is innovative and consists in proposing a full optimisation model based on mixed-integer non-linear programming considering the Pareto front technique. The goal is to achieve a reduction in repair times of the distribution networks components, while minimising the costs of that reduction as well as non-supplied energy costs. The optimisation model considers the distribution network technical constraints, the substation transformer taps, and it is able to choose the capacitor banks size. A case study based on a 33-bus distribution network is presented in order to illustrate in detail the application of the proposed methodology.

Predictive analytical and numerical modeling for orthogonal cutting

In this thesis, a predictive analytical and numerical modeling approach for the orthogonal cutting process is proposed to calculate temperature distributions and subsequently, forces and stress distributions. The models proposed include a constitutive model for the material being cut based on the work of Weber, a model for the shear plane based on Merchants model, a model describing the contribution of friction based on Zorev’s approach, a model for the effect of wear on the tool based on the work of Waldorf, and a thermal model based on the works of Komanduri and Hou, with a fraction heat partition for a non-uniform distribution of the heat in the interfaces, but extended to encompass a set of contributions to the global temperature rise of chip, tool and work piece. The models proposed in this work, try to avoid from experimental based values or expressions, and simplifying assumptions or suppositions, as much as possible. On a thermo-physical point of view, the results were affected not only by the mechanical or cutting parameters chosen, but also by their coupling effects, instead of the simplifying way of modeling which is to contemplate only the direct effect of the variation of a parameter. The implementation of these models was performed using the MATLAB environment. Since it was possible to find in the literature all the parameters for AISI 1045 and AISI O2, these materials were used to run the simulations in order to avoid arbitrary assumption.

Orthogonal models, structure crossing, nesting and inference

We intend to study the algebraic structure of the simple orthogonal models to use them, through binary operations as building blocks in the construction of more complex orthogonal models. We start by presenting some matrix results considering Commutative Jordan Algebras of symmetric matrices, CJAs. Next, we use these results to study the algebraic structure of orthogonal models, obtained by crossing and nesting simpler ones. Then, we study the normal models with OBS, which can also be orthogonal models. We intend to study normal models with OBS (Orthogonal Block Structure), NOBS (Normal Orthogonal Block Structure), obtaining condition for having complete and suffcient statistics, having UMVUE, is unbiased estimators with minimal covariance matrices whatever the variance components. Lastly, see ([Pereira et al. (2014)]), we study the algebraic structure of orthogonal models, mixed models whose variance covariance matrices are all positive semi definite, linear combinations of known orthogonal pairwise orthogonal projection matrices, OPOPM, and whose least square estimators, LSE, of estimable vectors are best linear unbiased estimator, BLUE, whatever the variance components, so they are uniformly BLUE, UBLUE. From the results of the algebraic structure we will get explicit expressions for the LSE of these models.

Effects of forest structure components on the occurence, group size and density of groups of bare-face tamarin (Saguinus bicolor - primates: Callitrichinae) in Central Amazonia

This study analyzed the influence of forest structural components on the occurence, size and density of groups of Bare-face Tamarin (Saguinus bicolor) - the most threatened species in the Amazon - and produced the first map of distribution of groups in large-scale spatial within the area of continuous forest. Population censuses were conducted between November 2002 and July 2003, covering 6400 hectares in the Ducke Reserve, Manaus-AM, Brazil. Groups of S. bicolor were recorded 41 times accordingly distributed in the environments: plateau (20); slopes (12); and lowlands (09). The mean group size was 4.8 indiv./group, and ranged from 2 to 11 individuals. In the sites where the groups were recorded, and in an equivalent number of sites where no tamarins were found located at least 500 m from those where they had been recorded, we placed 50 m x 50 m plots to record the following forest structural components: abundance of trees; abundance of lianas; abundance of fruiting trees and lianas; abundance of snags; abundance of logs; percentage of canopy opening; leaf litter depth; and altitude. Bare-face Tamarin more often uses areas with lower abundance of forest logs, smaller canopy opening and with higher abundance of snags, areas in the forest with smaller canopy opening present higher density of S. bicolor groups. Apparently this species does not use the forest in a random way, and may select areas for its daily activities depending on the micro-environmental heterogeneity produced by the forest structural components.

Exploring the factor structure of neurocognitive measures in older individuals

Here we focus on factor analysis from a best practices point of view, by investigating the factor structure of neuropsychological tests and using the results obtained to illustrate on choosing a reasonable solution. The sample (n=1051 individuals) was randomly divided into two groups: one for exploratory factor analysis (EFA) and principal component analysis (PCA), to investigate the number of factors underlying the neurocognitive variables; the second to test the "best fit" model via confirmatory factor analysis (CFA). For the exploratory step, three extraction (maximum likelihood, principal axis factoring and principal components) and two rotation (orthogonal and oblique) methods were used. The analysis methodology allowed exploring how different cognitive/psychological tests correlated/discriminated between dimensions, indicating that to capture latent structures in similar sample sizes and measures, with approximately normal data distribution, reflective models with oblimin rotation might prove the most adequate.

Defining habitat characteristics influencing the distribution, density and growth of Plaice (Pleuronectes Platessa) and Dab (Limanda Limanda) on west of Ireland nursery grounds

Plaice (Pleuronectes platessa, L.) and dab (Limanda limanda, L.) are among the most abundant flatfishes in the north-eastern Atlantic region and the dominant species in shallow coastal nursery grounds. With increasing pressures on commercial flatfish stocks in combination with changing coastal environments, better knowledge of population dynamics during all life stages is needed to evaluate variability in year-class strength and recruitment to the fishery. The aim of this research was to investigate the complex interplay of biotic and abiotic habitat components influencing the distribution, density and growth of plaice and dab during the vulnerable juvenile life stage and to gain insight in spatial and temporal differences in nursery habitat quality along the west coast of Ireland. Intraspecific variability in plaice diet was observed at different spatial scales and showed a link with condition, recent growth and morphology. This highlights the effect of food availability on habitat quality and the need to consider small scale variation when attempting to link habitat quality to feeding, growth and condition of juvenile flatfish. There was evidence of trophic, spatial and temporal resource partitioning between juvenile plaice and dab allowing the co-existence of morphologically similar species in nursery grounds. In the limited survey years there was no evidence that the carrying capacity of the studied nursery grounds was reached but spatial and interannual variations in fish growth indicated fluctuating environments in terms of food availability, predator densities, sediment features and physico-chemical conditions. Predation was the most important factor affecting habitat quality for juvenile plaice and dab with crab densities negatively correlated to fish condition whereas shrimp densities were negatively associated with densities of small-sized juveniles in spring. A comparison of proxies for fish growth showed the advantage of Fulton’s K for routine use whereas RNA:DNA ratios proved less powerful when short-term environmental fluctuations are lacking. This study illustrated how distinct sets of habitat features can drive spatial variation in density and condition of juvenile flatfish highlighting the value of studying both variables when modeling habitat requirements. The habitat models generated in this study also provide a powerful tool to predict potential climate and anthropogenic impacts on the distribution and condition of juveniles in flatfish nurseries. The need for effective coastal zone management was emphasized to ensure a sustainable use of coastal resources and successful flatfish recruitment to the fishery.

Lectin receptors distribution in the surface membrane of Trypanosoma cruzi blood forms collected from mice submitted to specific treatment

The author investigated the distribution of lectin receptors on Trypanosoma cruzi blood forms collected from mice inoculated with, respectively, the drug-resistant and drug-sensitive strains VL-10 and CL, and treated with the two standard active nitroheterocyclic compounds nifurtimox and benznidazole used for treatment of human Chagas' disease. Blood trypomastigotes purified in Fycoll-Hypaque were incubated with fluorescein-labelled lectins Con A, WGA, EE, WFA, TPA and PNA and then microscopically examined. Neither qualitative or quantitative differences in the fluorescence intensity could be detected between parasites from VL-10 and CL strains submitted or not to treatment. The results suggest that both strains do not differ in their surface membrane carbohydrate moieties. Moreover, the rapid clearance of blood forms the drug-sensitive strain in animals treated with singlo doses of both compounds is not likely to depend on membrane alterations expressed by changes in the carbohydrate components. furthermore, resistance or sensitivity to drugs is not apparently related to carbohydrate distribution on T. cruzi blood forms.