A Violação da Condição em Kadiwéu

Although kadiwéu presents the same typological facts as the languages analyzed by Baker (1995), this work shows that Baker's polysynthesis parameter , according to which polysynthetic languages are pronominal argument languages, cannot be applied to this language. This paper offers, then, an alternative analysis to the pronominal argument theory for kadiwéu by arguing that nominal phrases are the verbal arguments in this polysynthetic language, like in any other better known language. On this view, one of the main properties of the polysynthetic languages, the so-called Condition C violation (e.g. <>i wants John i to love Mary, <> i broke John i's knife), follows from syntactic movement due to the nature of the Kadiwéu v-system. That is, this paper questions the existence of a polysynthesis parameter and develops Fukui & Speas (1996) insight that the syntax of a given language follows from the functional categories present in this language's lexicon.

Sensitivity and specificity of machine learning classifiers for glaucoma diagnosis using Spectral Domain OCT and standard automated perimetry

PURPOSE: To evaluate the sensitivity and specificity of machine learning classifiers (MLCs) for glaucoma diagnosis using Spectral Domain OCT (SD-OCT) and standard automated perimetry (SAP). METHODS: Observational cross-sectional study. Sixty two glaucoma patients and 48 healthy individuals were included. All patients underwent a complete ophthalmologic examination, achromatic standard automated perimetry (SAP) and retinal nerve fiber layer (RNFL) imaging with SD-OCT (Cirrus HD-OCT; Carl Zeiss Meditec Inc., Dublin, California). Receiver operating characteristic (ROC) curves were obtained for all SD-OCT parameters and global indices of SAP. Subsequently, the following MLCs were tested using parameters from the SD-OCT and SAP: Bagging (BAG), Naive-Bayes (NB), Multilayer Perceptron (MLP), Radial Basis Function (RBF), Random Forest (RAN), Ensemble Selection (ENS), Classification Tree (CTREE), Ada Boost M1(ADA),Support Vector Machine Linear (SVML) and Support Vector Machine Gaussian (SVMG). Areas under the receiver operating characteristic curves (aROC) obtained for isolated SAP and OCT parameters were compared with MLCs using OCT+SAP data. RESULTS: Combining OCT and SAP data, MLCs' aROCs varied from 0.777(CTREE) to 0.946 (RAN).The best OCT+SAP aROC obtained with RAN (0.946) was significantly larger the best single OCT parameter (p<0.05), but was not significantly different from the aROC obtained with the best single SAP parameter (p=0.19). CONCLUSION: Machine learning classifiers trained on OCT and SAP data can successfully discriminate between healthy and glaucomatous eyes. The combination of OCT and SAP measurements improved the diagnostic accuracy compared with OCT data alone.

O esporte paraolímpico no Brasil : abordagem da sociologia do esporte de Pierre Bourdieu

Universidade Estadual de Campinas . Faculdade de Educação Física