7 resultados para Event Log Comparison

em Biblioteca Digital da Produção Intelectual da Universidade de São Paulo (BDPI/USP)


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Objectives: (1) To compare the anatomopathological variables and recurrence rates in patients with early-stage adenocarcinoma (AC) and squamous cell carcinoma (SCC) of the uterine cervix; (2) to identify the independent risk factors for recurrence. Study design: This historical cohort study assessed 238 patients with carcinoma of the uterine cervix (113 and IIA), who underwent radical hysterectomy with pelvic lymph node dissection between 1980 and 1999. Comparison of category variables between the two histological types was carried out using the Pearson`s X-2 test or Fisher exact test. Disease-free survival rates for AC and SCC were calculated using the Kaplan-Meier method and the curves were compared using the log-rank test. The Cox proportional hazards model was used to identify the independent risk factors for recurrence. Results: There were 35 cases of AC (14.7%) and 203 of SCC (85.3%). AC presented lower histological grade than did SCC (grade 1: 68.6% versus 9.4%; p < 0.001), lower rate of lymphovascular space involvement (25.7% versus 53.7%; p = 0.002), lower rate of invasion into the middle or deep thirds of the uterine cervix (40.0% versus 80.8%; p < 0.001) and lower rate of lymph node metastasis (2.9% versus 16.3%; p = 0.036). Although the recurrence rate was lower for AC than for SCC (11.4% versus 15.8%), this difference was not statistically significant (p = 0.509). Multivariate analysis identified three independent risk factors for recurrence: presence of metastases in the pelvic lymph nodes, invasion of the deep third of the uterine cervix and absence of or slight inflammatory reaction in the cervix. When these variables were adjusted for the histological type and radiotherapy status, they remained in the model as independent risk factors. Conclusion: The AC group showed less aggressive histological behavior than did the SCC group, but no difference in the disease-free survival rates was noted. (C) 2006 Elsevier Ireland Ltd. All rights reserved.

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Sampling protocols for detecting Salmonella on poultry differ among various countries. In the United States, the U.S. Department of Agriculture Food Safety and Inspection Service dictates that whole broiler carcasses should be rinsed with 400 ml of 1% buffered peptone water, whereas in the European Union 25-g samples composed of neck skin from three carcasses are evaluated. The purpose of this study was to evaluate a whole carcass rinse (WCR) and a neck skin excision (NS) procedure for Salmonella and Escherichia coli isolation from the same broiler carcass. Carcasses were obtained from three broiler processing plants. The skin around the neck area was aseptically removed and bagged separately from the carcass, and microbiological analysis was performed. The corresponding carcass was bagged and a WCR sample was evaluated. No significant difference (alpha <= 0.05) in Salmonella prevalence was found between the samples processed by the two methods, but both procedures produced many false-negative Salmonella results. Prechill, 37% (66 carcasses), 28% (50 carcasses), and 51% (91 carcasses) of the 180 carcasses examined were positive for Salmonella by WCR, NS, and both procedures combined, respectively. Postchill, 3% (5 carcasses), 7% (12 carcasses), and 10% (17 carcasses) of the 177 carcasses examined were positive for Salmonella by the WCR, NS, and combination of both procedures, respectively. Prechill, E. coli plus coliform counts were 3.0 and 2.6 log CFU/ml by the WCR and NS methods, respectively. Postchill. E. coli plus coliform counts were 1.7 and 1.4 log CFU/ml by the WCR and NS methods, respectively.

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In interval-censored survival data, the event of interest is not observed exactly but is only known to occur within some time interval. Such data appear very frequently. In this paper, we are concerned only with parametric forms, and so a location-scale regression model based on the exponentiated Weibull distribution is proposed for modeling interval-censored data. We show that the proposed log-exponentiated Weibull regression model for interval-censored data represents a parametric family of models that include other regression models that are broadly used in lifetime data analysis. Assuming the use of interval-censored data, we employ a frequentist analysis, a jackknife estimator, a parametric bootstrap and a Bayesian analysis for the parameters of the proposed model. We derive the appropriate matrices for assessing local influences on the parameter estimates under different perturbation schemes and present some ways to assess global influences. Furthermore, for different parameter settings, sample sizes and censoring percentages, various simulations are performed; in addition, the empirical distribution of some modified residuals are displayed and compared with the standard normal distribution. These studies suggest that the residual analysis usually performed in normal linear regression models can be straightforwardly extended to a modified deviance residual in log-exponentiated Weibull regression models for interval-censored data. (C) 2009 Elsevier B.V. All rights reserved.

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In this paper, the generalized log-gamma regression model is modified to allow the possibility that long-term survivors may be present in the data. This modification leads to a generalized log-gamma regression model with a cure rate, encompassing, as special cases, the log-exponential, log-Weibull and log-normal regression models with a cure rate typically used to model such data. The models attempt to simultaneously estimate the effects of explanatory variables on the timing acceleration/deceleration of a given event and the surviving fraction, that is, the proportion of the population for which the event never occurs. The normal curvatures of local influence are derived under some usual perturbation schemes and two martingale-type residuals are proposed to assess departures from the generalized log-gamma error assumption as well as to detect outlying observations. Finally, a data set from the medical area is analyzed.

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Oxygen isotope records of stalagmites from China and Oman reveal a weak summer monsoon event, with a double-plunging structure, that started 8.21 +/- 0.02 kyr B. P. An identical but antiphased pattern is also evident in two stalagmite records from eastern Brazil, indicating that the South American Summer Monsoon was intensified during the 8.2 kyr B. P. event. These records demonstrate that the event was of global extent and synchronous within dating errors of <50 years. In comparison with recent model simulations, it is plausible that the 8.2 kyr B. P. event can be tied in changes of the Atlantic Meridional Overturning Circulation triggered by a glacial lake draining event. This, in turn, affected North Atlantic climate and latitudinal position of the Intertropical Convergence Zone, resulting in the observed low-latitude monsoonal precipitation patterns.

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The main objective of this paper is to study a logarithm extension of the bimodal skew normal model introduced by Elal-Olivero et al. [1]. The model can then be seen as an alternative to the log-normal model typically used for fitting positive data. We study some basic properties such as the distribution function and moments, and discuss maximum likelihood for parameter estimation. We report results of an application to a real data set related to nickel concentration in soil samples. Model fitting comparison with several alternative models indicates that the model proposed presents the best fit and so it can be quite useful in real applications for chemical data on substance concentration. Copyright (C) 2011 John Wiley & Sons, Ltd.

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In this paper we show the results of a comparison simulation study for three classification techniques: Multinomial Logistic Regression (MLR), No Metric Discriminant Analysis (NDA) and Linear Discriminant Analysis (LDA). The measure used to compare the performance of the three techniques was the Error Classification Rate (ECR). We found that MLR and LDA techniques have similar performance and that they are better than DNA when the population multivariate distribution is Normal or Logit-Normal. For the case of log-normal and Sinh(-1)-normal multivariate distributions we found that MLR had the better performance.