VSSI (X)over-bar charts with sampling at fixed times

A standard (X) over bar chart for controlling the process mean takes samples of size no at specified, equally-spaced, fixed-time points. This article proposes a modification of the standard (X) over bar chart that allows one to take additional samples, bigger than no, between these fixed times. The additional samples are taken from the process when there is evidence that the process mean moved from target. Following the notation proposed by Reynolds (1996a) and Costs (1997) we shortly call the proposed (X) over bar chart as VSSIFT (X) over bar chart: where VSSIFT means variable sample size and sampling intervals with fixed times. The (X) over bar chart with the VSSIFT feature is easier to be administered than a standard VSSI (X) over bar chart that is not constrained to sample at the specified fixed times. The performances of the charts in detecting process mean shifts are comparable.

Air-drying of fresh and osmotically pre-treated pineapple slices: Fixed air temperature versus fixed slice temperature drying kinetics

In this investigation, the air drying characteristics of fresh and osmotically pre-treated pineapple slices in a tray dryer were studied under different operating conditions. The air velocity varied from 1.5 to 2.5 m/s and the air temperature from 40 to 70 degreesC. The analytical solution of the second Fick's law for an infinite slab was used to calculate effective diffusion coefficients and their temperature dependence could be well represented by an Arrhenius-type equation. Comparison of the results showed that the diffusion coefficients were lower for the pre-treated fruit. By means of automatic control, it was possible to obtain drying curves under conditions of constant product temperature, which showed to be an alternative to reduce the drying time of pineapple slices.

LH and FSH concentration and follicular development in Nellore heifers submitted to fixed-time artificial insemination protocols with different progesterone concentrations

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

The Geometric Birnbaum-Saunders regression model with cure rate

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Predicting body and carcass characteristics of 2 broiler chicken strains using support vector regression and neural network models

As a new modeling method, support vector regression (SVR) has been regarded as the state-of-the-art technique for regression and approximation. In this study, the SVR models had been introduced and developed to predict body and carcass-related characteristics of 2 strains of broiler chicken. To evaluate the prediction ability of SVR models, we compared their performance with that of neural network (NN) models. Evaluation of the prediction accuracy of models was based on the R-2, MS error, and bias. The variables of interest as model output were BW, empty BW, carcass, breast, drumstick, thigh, and wing weight in 2 strains of Ross and Cobb chickens based on intake dietary nutrients, including ME (kcal/bird per week), CP, TSAA, and Lys, all as grams per bird per week. A data set composed of 64 measurements taken from each strain were used for this analysis, where 44 data lines were used for model training, whereas the remaining 20 lines were used to test the created models. The results of this study revealed that it is possible to satisfactorily estimate the BW and carcass parts of the broiler chickens via their dietary nutrient intake. Through statistical criteria used to evaluate the performance of the SVR and NN models, the overall results demonstrate that the discussed models can be effective for accurate prediction of the body and carcass-related characteristics investigated here. However, the SVR method achieved better accuracy and generalization than the NN method. This indicates that the new data mining technique (SVR model) can be used as an alternative modeling tool for NN models. However, further reevaluation of this algorithm in the future is suggested.

Bayesian outlier analysis in binary regression

We propose alternative approaches to analyze residuals in binary regression models based on random effect components. Our preferred model does not depend upon any tuning parameter, being completely automatic. Although the focus is mainly on accommodation of outliers, the proposed methodology is also able to detect them. Our approach consists of evaluating the posterior distribution of random effects included in the linear predictor. The evaluation of the posterior distributions of interest involves cumbersome integration, which is easily dealt with through stochastic simulation methods. We also discuss different specifications of prior distributions for the random effects. The potential of these strategies is compared in a real data set. The main finding is that the inclusion of extra variability accommodates the outliers, improving the adjustment of the model substantially, besides correctly indicating the possible outliers.

Effects of temporary calf removal and eCG on pregnancy rates to timed-insemination in progesterone-treated postpartum Nellore cows

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

Patients' Expectations of and Satisfaction with Implant-Supported Fixed Partial Dentures and Single Crowns

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

Expression of fibroblast growth factor receptors during development and regression of the bovine corpus luteum

There is evidence that fibroblast growth factors (FGFs) are involved in the regulation of growth and regression of the corpus luteum (CL). However, the expression pattern of most FGF receptors (FGFRs) during CL lifespan is still unknown. The objective of the present study was to determine the pattern of expression of 'B' and 'C' splice variants of FGFRs in the bovine CL. Bovine CL were collected from an abattoir and classed as corpora hemorrhagica (Stage I), developing (Stage II), developed (Stage III) or regressed (Stage IV) CL. Expression of FGFR mRNA was measured by semiquantitative reverse transcription-polymerase chain reaction and FGFR protein was localised by immunohistochemistry. Expression of mRNA encoding the 'B' and 'C' spliced forms of FGFR1 and FGFR2 was readily detectable in the bovine CL and was accompanied by protein localisation. FGFR1C and FGFR2C mRNA expression did not vary throughout CL lifespan, whereas FGFR1B was upregulated in the developed (Stage III) CL. FGFR3B, FGFR3C and FGFR4 expression was inconsistent in the bovine CL. The present data indicate that FGFR1 and FGFR2 splice variants are the main receptors for FGF action in the bovine CL.

Detection of estrogen receptor in formalin-fixed and paraffin-embedded breast carcinoma: correlation with histological patterns.

The authors studied the expression of estrogen receptor (ER) in tissues of breast carcinomas which were previously fixed in formalin and paraffin-embedded. The ER expression was correlated with several histological findings, namely grade of differentiation, tumor necrosis, desmoplasia, lymphocytic infiltration and elastosis. The ER was detected in tissues using the avidin-biotin immunoperoxidase technique associated with the H222 monoclonal antibody from Abbott. All 39 biopsies were of infiltrating ductal carcinoma of breast and 16 of them expressed ER. The statistical analysis showed that the expression of ER was correlated with histological findings of good prognosis as well differentiated carcinomas, no tumor necrosis, absence or mild lymphocytic infiltration around the tumor cells and severe elastosis.

Proliferating cell nuclear antigen (PCNA) in non-Hodgkin's lymphomas: Correlation with working formulation and Kiel classification in formalin-fixed paraffin-embedded material

PCNA is a 36-KD proliferating cell nuclear antigen associated with the cell cycle. The immunocytochemical detection of PCNA represents a useful tool for the study of tumor proliferation activity. This study documents the detection of PCNA, using antibody PC 10 in formalin-fixed, paraffin-embedded tissue, and correlates the proliferative activity of the non-Hodgkin's lymphomas (NHL) with histological grading assessed by the International Working Formulation (WF) and Kiel classification. In 92 cases of NHLs we found a strong correlation between the PCNA index and lymphoma grading. Statistically significant differences were also found between the proliferative index (PI) in low and high grade lymphomas according to the Kiel classification (t = 9.519; p < 0.001) and between low, intermediate and high grade lymphomas according to the WF classification (F = 79.01; p < 0.001). In the Kiel classification the mean of low grade lymphomas was 39.5% and of high grade 75.7%. In the WF the average of low grade lymphomas was 29.7%, intermediate 53.1% and high 75.1%. Although the differences among the groups had been significant, we found variations inside each histological subgroup in both classifications. The intermediate lymphomas were the most heterogeneous group, with PI inside the same histologic subtypes coincident with low and high grade lymphomas. Since PCNA may be used as a marker of cell proliferation in clinical studies to estimate the biological aggressiveness of lymphomas, its determination in intermediate grade NHL could be very useful to evaluate individual cases in this group and determine prognosis and probably the appropriate therapy.