Effects of long-term cyclosporin therapy on gingiva of rats--analysis by stereological and biochemical estimation.

Cyclosporin A (CsA) is used as an immunosuppressive agent and its prominent side effect is the induction of gingival overgrowth, which remains a significant problem. The risk factors appraised include the duration of treatment. However, there are no stereological and biochemical studies exploring the effects of long-term CsA therapy on gingival tissue. The purpose of the present study was to investigate the level of TGF-beta1 in saliva and describe the densities of fibroblasts and collagen fibers in the gingival tissue of rats treated with CsA for long periods. Rats were treated for 60, 120, 180 and 240 days with a daily subcutaneous injection of 10 mg/kg of body weight of CsA. At the end of the experimental periods, saliva was collected for the determination of TGF-beta1 levels. After histological processing, the oral epithelium and the connective tissue area were measured as well as the volume densities of fibroblasts (Vf) and collagen fibers (Vcf). After 60 and 120 days of CsA treatment, there was a significant increase in Vf and Vcf as well as a significant increase in TGF-beta1 levels. After 180 and 240 days, reduction in the gingival overgrowth associated with significant decreases in the level of TGF-beta1, and also decreased Vf and Vcf, were observed. The data presented here suggest that after long-term therapy, a decrease in TGF-beta1 levels occurs, which might contribute to an increase in the proteolytic activity of fibroblasts in the gingiva, favoring the normality of extracellular matrix synthesis.

Identifying multiple interacting bad data in power system state estimation

This paper presents an intelligent search strategy for the conforming bad data errors identification in the generalized power system state estimation, by using the tabu search meta heuristic. The main objective is to detect critical errors involving both analog and topology errors. These errors are represented by conforming errors, whose nature affects measurements that actually do not present bad data and also the conventional bad data identification strategies based on the normalized residual methods. ©2005 IEEE.

Real-time crowd density estimation using images

This paper presents a technique for real-time crowd density estimation based on textures of crowd images. In this technique, the current image from a sequence of input images is classified into a crowd density class. Then, the classification is corrected by a low-pass filter based on the crowd density classification of the last n images of the input sequence. The technique obtained 73.89% of correct classification in a real-time application on a sequence of 9892 crowd images. Distributed processing was used in order to obtain real-time performance. © Springer-Verlag Berlin Heidelberg 2005.

Estimation of variance components and prediction of breeding values in rubber tree breeding using the REML/BLUP procedure

The present paper deals with estimation of variance components, prediction of breeding values and selection in a population of rubber tree [Hevea brasiliensis (Willd. ex Adr. de Juss.) Müell.-Arg.] from Rio Branco, State of Acre, Brazil. The REML/BLUP (restricted maximum likelihood/best linear unbiased prediction) procedure was applied. For this purpose, 37 rubber tree families were obtained and assessed in a randomized complete block design, with three unbalanced replications. The field trial was carried out at the Experimental Station of UNESP, located in Selvíria, State of Mato Grosso do Sul, Brazil. The quantitative traits evaluated were: girth (G), bark thickness (BT), number of latex vessel rings (NR), and plant height (PH). Given the unbalanced condition of the progeny test, the REML/BLUP procedure was used for estimation. The narrow-sense individual heritability estimates were 0.43 for G, 0.18 for BT, 0.01 for NR, and 0.51 for PH. Two selection strategies were adopted: one short-term (ST - selection intensity of 8.85%) and the other long-term (LT - selection intensity of 26.56%). For G, the estimated genetic gains in relation to the population average were 26.80% and 17.94%, respectively, according to the ST and LT strategies. The effective population sizes were 22.35 and 46.03, respectively. The LT and ST strategies maintained 45.80% and 28.24%, respectively, of the original genetic diversity represented in the progeny test. So, it can be inferred that this population has potential for both breeding and ex situ genetic conservation as a supplier of genetic material for advanced rubber tree breeding programs. Copyright by the Brazilian Society of Genetics.

Genetic effects on preweaning weight gain of Nelore-Hereford calves according to different models and estimation methods

Additive and nonadditive genetic effects on preweaning weight gain (PWG) of a commercial crossbred population were estimated using different genetic models and estimation methods. The data set consisted of 103,445 records on purebred and crossbred Nelore-Hereford calves raised under pasture conditions on farms located in south, southeast, and middle west Brazilian regions. In addition to breed additive and dominance effects, the models including different epistasis covariables were tested. Models considering joint additive and environment (latitude) by genetic effects interactions were also applied. In a first step, analyses were carried out under animal models. In a second step, preadjusted records were analyzed using ordinary least squares (OLS) and ridge regression (RR). The results reinforced evidence that breed additive and dominance effects are not sufficient to explain the observed variability in preweaning traits of Bos taurus x Bos indicus calves, and that genotype x environment interaction plays an important role in the evaluation of crossbred calves. Data were ill-conditioned to estimate the effects of genotype x environment interactions. Models including these effects presented multicolinearity problems. In this case, RR seemed to be a powerful tool for obtaining more plausible and stable estimates. Estimated prediction error variances and variance inflation factors were drastically reduced, and many effects that were not significant under ordinary least squares became significant under RR. Predictions of PWG based on RR estimates were more acceptable from a biological perspective. In temperate and subtropical regions, calves with intermediate genetic compositions (close to 1/2 Nelore) exhibited greater predicted PWG. In the tropics, predicted PWG increased linearly as genotype got closer to Nelore. ©2006 American Society of Animal Science. All rights reserved.

Recurrent neural network for induction motor speed estimation in industry applications

Many electronic drivers for the induction motor control are based on sensorless technologies. The proposal of this work Is to present an alternative approach of speed estimation, from transient to steady state, using artificial neural networks. The inputs of the network are the RMS voltage, current and speed estimated of the induction motor feedback to the input with a delay of n samples. Simulation results are also presented to validate the proposed approach. © 2006 IEEE.

A survey of radiographic measurement estimation in assessment of dental implant length.

The aim of this study is to survey radiographic measurement estimation in the assessment of dental implant length according to dentists' confidence. A 19-point questionnaire with closed-ended questions was used by two graduate students to interview 69 dentists during a dental implant meeting. Included were 12 questions related to over- and underestimation in three radiographic modalities: panoramic (P), conventional tomography (T), and computerized tomography (CT). The database was analyzed by Epi-Info 6.04 software and the values from two radiographic modalities, P and T, were compared using a chi2 test. The results showed that 38.24% of the dentists' confidence was in the overestimation of measurements in P, 30.56% in T, and 0% in CT. On the other hand, considering the underestimated measurements, the percentages were 47.06% in P, 33.33% in T, and 1.92% in CT. The frequency of under- and overestimation were statistically significant (chi2 = 6.32; P = .0425) between P and T. CT was the radiographic modality with higher measurement precision according to dentists' confidence. In conclusion, the interviewed dentists felt that CT was the best radiographic modality when considering the measurement estimation precision in preoperative dental implant assessment.

Echocardiographic Doppler estimation of pulmonary artery pressure in critically ill patients with severe hypoxemia

BACKGROUND: In spontaneously breathing cardiac patients, pulmonary artery pressure (PAP) can be accurately estimated from the transthoracic Doppler study of pulmonary artery and tricuspid regurgitation blood flows. In critically ill patients on mechanical ventilation for acute lung injury, the interposition of gas between the probe and the heart renders the transthoracic approach problematic. This study was aimed at determining whether the transesophageal approach could offer an alternative. METHODS: Fifty-one consecutive sedated and ventilated patients with severe hypoxemia (arterial oxygen tension/fraction of inspired oxygen < 300) were prospectively studied. Mean PAP measured from the pulmonary artery catheter was compared with several indices characterizing pulmonary artery blood flow assessed using transesophageal echocardiography: preejection time, acceleration time, ejection duration, preejection time on ejection duration ratio, and acceleration time on ejection duration ratio. In a subgroup of 20 patients, systolic PAP measured from the pulmonary artery catheter immediately before withdrawal was compared with Doppler study of regurgitation tricuspid flow performed immediately after pulmonary artery catheter withdrawal using either the transthoracic or the transesophageal approach. RESULTS: Weak and clinically irrelevant correlations were found between mean PAP and indices of pulmonary artery flow. A statistically significant and clinically relevant correlation was found between systolic PAP and regurgitation tricuspid flow. In 3 patients (14%), pulmonary artery pressure could not be assessed echocardiographically. CONCLUSIONS: In hypoxemic patients on mechanical ventilation, mean PAP cannot be reliably estimated from indices characterizing pulmonary artery blood flow. Systolic PAP can be estimated from regurgitation tricuspid flow using either transthoracic or transesophageal approach. © 2008 American Society of Anesthesiologists, Inc.

Estimation of electrical machine speed using sensorless technology and neural networks

The use of sensorless technologies is an increasing tendency on industrial drivers for electrical machines. The estimation of electrical and mechanical parameters involved with the electrical machine control is used very frequently in order to avoid measurement of all variables related to this process. The cost reduction may also be considered in industrial drivers, besides the increasing robustness of the system, as an advantage of the use of sensorless technologies. This work proposes the use of a recurrent artificial neural network to estimate the speed of induction motor for sensorless control schemes using one single current sensor. Simulation and experimental results are presented to validate the proposed approach. ©2008 IEEE.

Weight vector estimation of circular arrays of antennas using Artificial Neural Networks

This paper presents a model for the control of the radiation pattern of a circular array of antennas, shaping it to address the radiation beam in the direction of the user, in order to reduce the transmitted power and to attenuate interference. The control of the array is based on Artificial Neural Networks (ANN) of the type RBF (Radial Basis Functions), trained from samples generated by the Wiener equation. The obtained results suggest that the objective was reached.

Calibration uncertainty estimation for internal aerodynamic balance

Aerodynamic balances are employed in wind tunnels to estimate the forces and moments acting on the model under test. This paper proposes a methodology for the assessment of uncertainty in the calibration of an internal multi-component aerodynamic balance. In order to obtain a suitable model to provide aerodynamic loads from the balance sensor responses, a calibration is performed prior to the tests by applying known weights to the balance. A multivariate polynomial fitting by the least squares method is used to interpolate the calibration data points. The uncertainties of both the applied loads and the readings of the sensors are considered in the regression. The data reduction includes the estimation of the calibration coefficients, the predicted values of the load components and their corresponding uncertainties, as well as the goodness of fit.

Fault section estimation in automated distribution substations

In this paper, a methodology based on Unconstrained Binary Programming (UBP) model and Genetic Algorithms (GAs) is proposed for estimating fault sections in automated distribution substations. The UBP model, established by using the parsimonious set covering theory, looks for the match between the relays' protective alarms informed by the SCADA system and their expected states. The GA is developed to minimize the UBP model and estimate the fault sections in a swift and reliable manner. The proposed methodology is tested by utilizing a real-life automated distribution substation. Control parameters of the GA are tuned to achieve maximum computational efficiency and reduction of processing time. Results show the potential and efficiency of the methodology for estimating fault section in real-time at Distribution Control Centers. ©2009 IEEE.

The impact of structural reforms on growth in Latin America and the Caribbean: an empirical estimation

Includes bibliography

Structural budget balance: methodology and estimation for the Chilean central government 1987-2001

Includes bibliography

Optimum-Path Forest pruning parameter estimation through Harmony Search

Pattern recognition in large amount of data has been paramount in the last decade, since that is not straightforward to design interactive and real time classification systems. Very recently, the Optimum-Path Forest classifier was proposed to overcome such limitations, together with its training set pruning algorithm, which requires a parameter that has been empirically set up to date. In this paper, we propose a Harmony Search-based algorithm that can find near optimal values for that. The experimental results have showed that our algorithm is able to find proper values for the OPF pruning algorithm parameter. © 2011 IEEE.