Does Adhesive Thickness Affect Resin-dentin Bond Strength After Thermal/Load Cycling?

This study evaluated the influence of adhesive layer thickness (ADL) on the resin-dentin bond strength of two adhesive systems (AS) after ther-mal and mechanical loading (TML). A flat superficial dentin surface was exposed with 600-grit SiC paper on 40 molars. After primer application, the adhesive layer of Scotchbond Multipurpose (SBMP) or Clearfil SE Bond (CSEB) was applied in one or two layers to a delimited area (52 mm(2)) and resin blocks (Filtek 2250) were built incrementally: Half of the sample was stored in distilled water (37 C, 24 hours) and submitted to thermal (1,000; 5 degrees-55 degrees C) and mechanical cycles (500,000; 10kgf) [TML]. The other half was stored in distilled water (72 hours). The teeth were then sectioned to obtain sticks (0.8 mm(2)) to be tested under tensile mode (1.0 mm/minute). The fracture mode was analyzed at 400x. The BS from all sticks from the same tooth was averaged for statistical purposes. The data was analyzed by three-way ANOVA. The x(2) test was used (p<0.05) to compare the frequency of pre-testing failure specimens. Higher BS values were observed for SBMP regardless of the ADL. The TML reduced the BS values irrespective of the adhesive employed and the ADL. A higher frequency of pre-testing failure specimens was observed for the cycled groups. A thicker adhesive layer, acting as an intermediate flexible layer, did not min-imize the damage caused by thermal/mechanical load cycling for a three-step etch-and-rinse and two-step self-etch system.

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.

Clinical feasibility of mandibular implant overdenture retainers submitted to immediate load

Clinical feasibility of mandibular implant overdenture retainers submitted to immediate load Introduction: Millions of people around the world do not have access to the benefits of osseointegration. Treatments involving oral rehabilitation with overdentures have been widely used by specialists in the oral medicine field. This is an alternative therapy for retention and stability achievement in total prosthesis with conventional treatment, and two implants are enough to establish a satisfactory overdenture. Objective: The objectives of the study were to evaluate 16 patients of both sexes, with an average age of 47.4 +/- 4 years, using electromyographic analysis of masseter and temporal muscles and analyse the increase of incisive and molar maximal bite force with their existing complete dentures and following mandibular implant overdenture therapy to assess the benefits of this treatment. Materials and methods: For these tests, the Myosystem-BR1 electromyograph and the IDDK Kratos dynamometer were used. Statistical analysis was performed using the repeated measures test (SPSS 17.0). Results: A decrease in electromyographic activity during the rest, lateral and protrusion movements and increase of the maximal incisive and molar bite force after 15 months with a mandibular implant overdenture was observed. Conclusion: All the patients in this study reported a considerable improvement in the masticatory function and prostheses stability following treatment. It is possible to propose that the use of mandibular implants overdenture should become the selected treatment for totally edentulous patients to facilitate oral function and quality of life.

An adaptive neural-wavelet model for short term load forecasting

This paper proposed a novel model for short term load forecast in the competitive electricity market. The prior electricity demand data are treated as time series. The forecast model is based on wavelet multi-resolution decomposition by autocorrelation shell representation and neural networks (multilayer perceptrons, or MLPs) modeling of wavelet coefficients. To minimize the influence of noisy low level coefficients, we applied the practical Bayesian method Automatic Relevance Determination (ARD) model to choose the size of MLPs, which are then trained to provide forecasts. The individual wavelet domain forecasts are recombined to form the accurate overall forecast. The proposed method is tested using Queensland electricity demand data from the Australian National Electricity Market. (C) 2001 Elsevier Science B.V. All rights reserved.

Asymptomatic primary Epstein-Barr virus infection occurs in the absence of blood T-cell repertoire perturbations despite high levels of systemic viral load

Primary infection with the human herpesvirus, Epstein-Barr virus (EBV), may result in subclinical seroconversion or may appear as infectious mononucleosis (IM), a lymphoproliferative disease of variable severity. Why primary infection manifests differently between patients is unknown, and, given the difficulties in identifying donors undergoing silent seroconversion, little information has been reported. However, a longstanding assumption has been held that IM represents an exaggerated form of the virologic and immunologic events of asymptomatic infection. T-cell receptor (TCR) repertoires of a unique cohort of subclinically infected patients undergoing silent infection were studied, and the results highlight a fundamental difference between the 2 forms of infection. In contrast to the massive T-cell expansions mobilized during the acute symptomatic phase of IM, asymptomatic donors largely maintain homeostatic T-cell control and peripheral blood repertoire diversity. This disparity cannot simply be linked to severity or spread of the infection because high levels of EBV DNA were found in the blood from both types of acute infection. The results suggest that large expansions of T cells within the blood during IM may not always be associated with the control of primary EBV infection and that they may represent an overreaction that exacerbates disease. (C) 2001 by The American Society of Hematology.

A portable load cell for in-situ ore impact breakage testing

This paper discusses the design and characterisation of a short, and hence portable impact load cell for in-situ quantification of ore breakage properties under impact loading conditions. Much literature has been published in the past two decades about impact load cells for ore breakage testing. It has been conclusively shown that such machines yield significant quantitative energy-fragmentation information about industrial ores. However, documented load cells are all laboratory systems that are not adapted for in-situ testing due to their dimensions and operating requirements. The authors report on a new portable impact load cell designed specifically for in-situ testing. The load cell is 1.5 m in height and weighs 30 kg. Its physical and operating characteristics are detailed in the paper. This includes physical dimensions, calibration and signal deconvolution. Emphasis is placed on the deconvolution issue, which is significant for such a short load cell. Finally, it is conclusively shown that the short load cell is quantitatively as accurate as its larger laboratory analogues. (C) 2062 Elsevier Science B.V. All rights reserved.

Simulation of the load-unload response ratio and critical sensitivity in the lattice solid model

The Load-Unload Response Ratio (LURR) method is an intermediate-term earthquake prediction approach that has shown considerable promise. It involves calculating the ratio of a specified energy release measure during loading and unloading where loading and unloading periods are determined from the earth tide induced perturbations in the Coulomb Failure Stress on optimally oriented faults. In the lead-up to large earthquakes, high LURR values are frequently observed a few months or years prior to the event. These signals may have a similar origin to the observed accelerating seismic moment release (AMR) prior to many large earthquakes or may be due to critical sensitivity of the crust when a large earthquake is imminent. As a first step towards studying the underlying physical mechanism for the LURR observations, numerical studies are conducted using the particle based lattice solid model (LSM) to determine whether LURR observations can be reproduced. The model is initialized as a heterogeneous 2-D block made up of random-sized particles bonded by elastic-brittle links. The system is subjected to uniaxial compression from rigid driving plates on the upper and lower edges of the model. Experiments are conducted using both strain and stress control to load the plates. A sinusoidal stress perturbation is added to the gradual compressional loading to simulate loading and unloading cycles and LURR is calculated. The results reproduce signals similar to those observed in earthquake prediction practice with a high LURR value followed by a sudden drop prior to macroscopic failure of the sample. The results suggest that LURR provides a good predictor for catastrophic failure in elastic-brittle systems and motivate further research to study the underlying physical mechanisms and statistical properties of high LURR values. The results provide encouragement for earthquake prediction research and the use of advanced simulation models to probe the physics of earthquakes.

Load-unload response ratio and accelerating moment/energy release critical region scaling and earthquake prediction

The main idea of the Load-Unload Response Ratio (LURR) is that when a system is stable, its response to loading corresponds to its response to unloading, whereas when the system is approaching an unstable state, the response to loading and unloading becomes quite different. High LURR values and observations of Accelerating Moment/Energy Release (AMR/AER) prior to large earthquakes have led different research groups to suggest intermediate-term earthquake prediction is possible and imply that the LURR and AMR/AER observations may have a similar physical origin. To study this possibility, we conducted a retrospective examination of several Australian and Chinese earthquakes with magnitudes ranging from 5.0 to 7.9, including Australia's deadly Newcastle earthquake and the devastating Tangshan earthquake. Both LURR values and best-fit power-law time-to-failure functions were computed using data within a range of distances from the epicenter. Like the best-fit power-law fits in AMR/AER, the LURR value was optimal using data within a certain epicentral distance implying a critical region for LURR. Furthermore, LURR critical region size scales with mainshock magnitude and is similar to the AMR/AER critical region size. These results suggest a common physical origin for both the AMR/AER and LURR observations. Further research may provide clues that yield an understanding of this mechanism and help lead to a solid foundation for intermediate-term earthquake prediction.

A reduced load approximation accounting for link interactions in a loss network

This paper is concerned with evaluating the performance of loss networks. Accurate determination of loss network performance can assist in the design and dimen- sioning of telecommunications networks. However, exact determination can be difficult and generally cannot be done in reasonable time. For these reasons there is much interest in developing fast and accurate approximations. We develop a reduced load approximation that improves on the famous Erlang fixed point approximation (EFPA) in a variety of circumstances. We illustrate our results with reference to a range of networks for which the EFPA may be expected to perform badly.

Definition of MV Load Diagrams via Weighted Evidence Accumulation Clustering using Subsampling

A definition of medium voltage (MV) load diagrams was made, based on the data base knowledge discovery process. Clustering techniques were used as support for the agents of the electric power retail markets to obtain specific knowledge of their customers’ consumption habits. Each customer class resulting from the clustering operation is represented by its load diagram. The Two-step clustering algorithm and the WEACS approach based on evidence accumulation (EAC) were applied to an electricity consumption data from a utility client’s database in order to form the customer’s classes and to find a set of representative consumption patterns. The WEACS approach is a clustering ensemble combination approach that uses subsampling and that weights differently the partitions in the co-association matrix. As a complementary step to the WEACS approach, all the final data partitions produced by the different variations of the method are combined and the Ward Link algorithm is used to obtain the final data partition. Experiment results showed that WEACS approach led to better accuracy than many other clustering approaches. In this paper the WEACS approach separates better the customer’s population than Two-step clustering algorithm.

Determination of electricity consumers’ load profiles via weighted evidence accumulation clustering using subsampling

With the electricity market liberalization, the distribution and retail companies are looking for better market strategies based on adequate information upon the consumption patterns of its electricity consumers. A fair insight on the consumers’ behavior will permit the definition of specific contract aspects based on the different consumption patterns. In order to form the different consumers’ classes, and find a set of representative consumption patterns we use electricity consumption data from a utility client’s database and two approaches: Two-step clustering algorithm and the WEACS approach based on evidence accumulation (EAC) for combining partitions in a clustering ensemble. While EAC uses a voting mechanism to produce a co-association matrix based on the pairwise associations obtained from N partitions and where each partition has equal weight in the combination process, the WEACS approach uses subsampling and weights differently the partitions. As a complementary step to the WEACS approach, we combine the partitions obtained in the WEACS approach with the ALL clustering ensemble construction method and we use the Ward Link algorithm to obtain the final data partition. The characterization of the obtained consumers’ clusters was performed using the C5.0 classification algorithm. Experiment results showed that the WEACS approach leads to better results than many other clustering approaches.

Typical load profiles in the smart grid context – a clustering methods comparison

The present research paper presents five different clustering methods to identify typical load profiles of medium voltage (MV) electricity consumers. These methods are intended to be used in a smart grid environment to extract useful knowledge about customer’s behaviour. The obtained knowledge can be used to support a decision tool, not only for utilities but also for consumers. Load profiles can be used by the utilities to identify the aspects that cause system load peaks and enable the development of specific contracts with their customers. The framework presented throughout the paper consists in several steps, namely the pre-processing data phase, clustering algorithms application and the evaluation of the quality of the partition, which is supported by cluster validity indices. The process ends with the analysis of the discovered knowledge. To validate the proposed framework, a case study with a real database of 208 MV consumers is used.

Knowledge extraction from medium voltage load diagrams to support the definition of electrical tariffs

With the electricity market liberalization, distribution and retail companies are looking for better market strategies based on adequate information upon the consumption patterns of its electricity customers. In this environment all consumers are free to choose their electricity supplier. A fair insight on the customer´s behaviour will permit the definition of specific contract aspects based on the different consumption patterns. In this paper Data Mining (DM) techniques are applied to electricity consumption data from a utility client’s database. To form the different customer´s classes, and find a set of representative consumption patterns, we have used the Two-Step algorithm which is a hierarchical clustering algorithm. Each consumer class will be represented by its load profile resulting from the clustering operation. Next, to characterize each consumer class a classification model will be constructed with the C5.0 classification algorithm.

Fuzzy Monte Carlo mathematical model for load curtailment minimization in transmission power systems

This paper presents a methodology which is based on statistical failure and repair data of the transmission power system components and uses fuzzyprobabilistic modeling for system component outage parameters. Using statistical records allows developing the fuzzy membership functions of system component outage parameters. The proposed 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. A network contingency analysis to identify any overloading or voltage violation in the network is performed once obtained the system states by Monte Carlo simulation. This is followed by a remedial action algorithm, based on optimal power flow, to reschedule generations and alleviate constraint violations and, at the same time, to avoid any load curtailment, if possible, or, otherwise, to minimize the total load curtailment, for the states identified by the contingency analysis. In order to illustrate the application of the proposed methodology to a practical case, the paper will include a case study for the Reliability Test System (RTS) 1996 IEEE 24 BUS.

Contextual intelligent load management with ANN adaptive learning module

With the current increase of energy resources prices and environmental concerns intelligent load management systems are gaining more and more importance. This paper concerns a SCADA House Intelligent Management (SHIM) system that includes an optimization module using deterministic and genetic algorithm approaches. SHIM undertakes contextual load management based on the characterization of each situation. SHIM considers available generation resources, load demand, supplier/market electricity price, and consumers’ constraints and preferences. The paper focus on the recently developed learning module which is based on artificial neural networks (ANN). The learning module allows the adjustment of users’ profiles along SHIM lifetime. A case study considering a system with fourteen discrete and four variable loads managed by a SHIM system during five consecutive similar weekends is presented.