Comparison of active and passive forces of the pelvic floor muscles in women with and without stress urinary incontinence

Background: The reduction of the pelvic floor muscles (PFM) strength is a major cause of stress urinary incontinence (SUI). Objective: To compare active and passive forces, and vaginal cavity aperture in continent and stress urinary incontinent women. Method: The study included a total of thirty-two women, sixteen continent women (group 1 - G1) and sixteen women with SUI (group 2 - G2). To evaluate PFM passive and active forces in anteroposterior (sagittal plane) and left-right directions (frontal plane) a stainless steel specular dynamometer was used. Results: The anteroposterior active strength for the continent women (mean +/- standard deviation) (0.3 +/- 0.2 N) was greater compared to the values found in the evaluation of incontinent women (0.1 +/- 0.1 N). The left-right active strength (G1=0.43 +/- 0.1 N; G2=0.40 +/- 0.1 N), the passive force (G1=1.1 +/- 0.2 N; G2=1.1 +/- 0.3 N) and the vaginal cavity aperture (G1=21 +/- 3 mm; G2=24 +/- 4 mm) did not differ between groups 1 and 2. Conclusion: The function evaluation of PFM showed that women with SUI had a lower anteroposterior active strength compared to continent women.

COMPARISON MEASURES OF MAPS GENERATED BY GEOSTATISTICAL METHODS

This study uses several measures derived from the error matrix for comparing two thematic maps generated with the same sample set. The reference map was generated with all the sample elements and the map set as the model was generated without the two points detected as influential by the analysis of local influence diagnostics. The data analyzed refer to the wheat productivity in an agricultural area of 13.55 ha considering a sampling grid of 50 x 50 m comprising 50 georeferenced sample elements. The comparison measures derived from the error matrix indicated that despite some similarity on the maps, they are different. The difference between the estimated production by the reference map and the actual production was of 350 kilograms. The same difference calculated with the mode map was of 50 kilograms, indicating that the study of influential points is of fundamental importance to obtain a more reliable estimative and use of measures obtained from the error matrix is a good option to make comparisons between thematic maps.

Comparison measures of maps generated by geostatistical methods

This study uses several measures derived from the error matrix for comparing two thematic maps generated with the same sample set. The reference map was generated with all the sample elements and the map set as the model was generated without the two points detected as influential by the analysis of local influence diagnostics. The data analyzed refer to the wheat productivity in an agricultural area of 13.55 ha considering a sampling grid of 50 x 50 m comprising 50 georeferenced sample elements. The comparison measures derived from the error matrix indicated that despite some similarity on the maps, they are different. The difference between the estimated production by the reference map and the actual production was of 350 kilograms. The same difference calculated with the mode map was of 50 kilograms, indicating that the study of influential points is of fundamental importance to obtain a more reliable estimative and use of measures obtained from the error matrix is a good option to make comparisons between thematic maps.

Comparison between the complete Bayesian method and empirical Bayesian method for ARCH models using Brazilian financial time series

In this work we compared the estimates of the parameters of ARCH models using a complete Bayesian method and an empirical Bayesian method in which we adopted a non-informative prior distribution and informative prior distribution, respectively. We also considered a reparameterization of those models in order to map the space of the parameters into real space. This procedure permits choosing prior normal distributions for the transformed parameters. The posterior summaries were obtained using Monte Carlo Markov chain methods (MCMC). The methodology was evaluated by considering the Telebras series from the Brazilian financial market. The results show that the two methods are able to adjust ARCH models with different numbers of parameters. The empirical Bayesian method provided a more parsimonious model to the data and better adjustment than the complete Bayesian method.