CONTEXT TREE SELECTION AND LINGUISTIC RHYTHM RETRIEVAL FROM WRITTEN TEXTS

The starting point of this article is the question "How to retrieve fingerprints of rhythm in written texts?" We address this problem in the case of Brazilian and European Portuguese. These two dialects of Modern Portuguese share the same lexicon and most of the sentences they produce are superficially identical. Yet they are conjectured, on linguistic grounds, to implement different rhythms. We show that this linguistic question can be formulated as a problem of model selection in the class of variable length Markov chains. To carry on this approach, we compare texts from European and Brazilian Portuguese. These texts are previously encoded according to some basic rhythmic features of the sentences which can be automatically retrieved. This is an entirely new approach from the linguistic point of view. Our statistical contribution is the introduction of the smallest maximizer criterion which is a constant free procedure for model selection. As a by-product, this provides a solution for the problem of optimal choice of the penalty constant when using the BIC to select a variable length Markov chain. Besides proving the consistency of the smallest maximizer criterion when the sample size diverges, we also make a simulation study comparing our approach with both the standard BIC selection and the Peres-Shields order estimation. Applied to the linguistic sample constituted for our case study, the smallest maximizer criterion assigns different context-tree models to the two dialects of Portuguese. The features of the selected models are compatible with current conjectures discussed in the linguistic literature.

Structure-semantics interplay in complex networks and its effects on the predictability of similarity in texts

The classification of texts has become a major endeavor with so much electronic material available, for it is an essential task in several applications, including search engines and information retrieval. There are different ways to define similarity for grouping similar texts into clusters, as the concept of similarity may depend on the purpose of the task. For instance, in topic extraction similar texts mean those within the same semantic field, whereas in author recognition stylistic features should be considered. In this study, we introduce ways to classify texts employing concepts of complex networks, which may be able to capture syntactic, semantic and even pragmatic features. The interplay between various metrics of the complex networks is analyzed with three applications, namely identification of machine translation (MT) systems, evaluation of quality of machine translated texts and authorship recognition. We shall show that topological features of the networks representing texts can enhance the ability to identify MT systems in particular cases. For evaluating the quality of MT texts, on the other hand, high correlation was obtained with methods capable of capturing the semantics. This was expected because the golden standards used are themselves based on word co-occurrence. Notwithstanding, the Katz similarity, which involves semantic and structure in the comparison of texts, achieved the highest correlation with the NIST measurement, indicating that in some cases the combination of both approaches can improve the ability to quantify quality in MT. In authorship recognition, again the topological features were relevant in some contexts, though for the books and authors analyzed good results were obtained with semantic features as well. Because hybrid approaches encompassing semantic and topological features have not been extensively used, we believe that the methodology proposed here may be useful to enhance text classification considerably, as it combines well-established strategies. (c) 2012 Elsevier B.V. All rights reserved.

Effect of the classic ketogenic diet on the treatment of refractory epileptic seizures

Objective The ketogenic diet is used as a therapeutic alternative for the treatment of epilepsy in patients with refractory epilepsy. It simulates biochemical changes typical of fasting. The present study verified the nutritional impact of the ketogenic diet on children with refractory epilepsy. Methods Nutritional status data (dietary, biochemical and anthropometric measurements), seizure frequency, and adverse events were collected from the medical records and during outpatient clinic visits of children over a period of 36 months. Results Of the 29 children who initiated the ketogenic diet, 75.8% presented fewer seizures after one month of treatment. After six months, 48.3% of the patients had at least a 90.0% decrease in seizure frequency, and 50.0% of these patients presented total seizure remission. At 12 months, eight patients continued to show positive results, and seven of these children remained on the ketogenic diet for 24 months. There was an improvement of the nutritional status at 24 months, especially in terms of weight, which culminated with the recovery of proper weight-for-height. There were no significant changes in biochemical indices (total cholesterol and components, triglycerides, albumin, total protein, creatinine, glycemia, serum aspartate transaminase and serum alanine transaminase). Serum cholesterol levels increased significantly in the first month, fell in the following six months, and remained within the normal limits thereafter. Conclusion In conclusion, patients on the classic ketogenic diet for at least 24 months gained weight. Moreover, approximately one third of the patients achieved significant reduction in seizure frequency, and some patients achieved total remission.

Identification of literary movements using complex networks to represent texts

The use of statistical methods to analyze large databases of text has been useful in unveiling patterns of human behavior and establishing historical links between cultures and languages. In this study, we identified literary movements by treating books published from 1590 to 1922 as complex networks, whose metrics were analyzed with multivariate techniques to generate six clusters of books. The latter correspond to time periods coinciding with relevant literary movements over the last five centuries. The most important factor contributing to the distinctions between different literary styles was the average shortest path length, in particular the asymmetry of its distribution. Furthermore, over time there has emerged a trend toward larger average shortest path lengths, which is correlated with increased syntactic complexity, and a more uniform use of the words reflected in a smaller power-law coefficient for the distribution of word frequency. Changes in literary style were also found to be driven by opposition to earlier writing styles, as revealed by the analysis performed with geometrical concepts. The approaches adopted here are generic and may be extended to analyze a number of features of languages and cultures.

Comparative study of classic friction among different archwire ligation systems

OBJECTIVE: To describe and compare three alternative methods for controlling classical friction: Self-ligating brackets (SLB), special brackets (SB) and special elastomeric ligatures (SEB). METHODS: The study compared Damon MX, Smart Clip, In-Ovation and Easy Clip self-ligating bracket systems, the special Synergy brackets and Morelli's twin bracket with special 8-shaped elastomeric ligatures. New and used Morelli brackets with new and used elastomeric ligatures were used as control. All brackets had 0.022 x 0.028-in slots. 0.014-in nickel-titanium and stainless steel 0.019 x 0.025-in wires were tied to first premolar steel brackets using each archwire ligation method and pulled by an Instron machine at a speed of 0.5 mm/minute. Prior to the mechanical tests the absence of binding in the device was ruled out. Statistical analysis consisted of the Kruskal-Wallis test and multiple non-parametric analyses at a 1% significance level. RESULTS: When a 0.014-in archwire was employed, all ligation methods exhibited classical friction forces close to zero, except Morelli brackets with new and old elastomeric ligatures, which displayed 64 and 44 centiNewtons, respectively. When a 0.019 x 0.025-in archwire was employed, all ligation methods exhibited values close to zero, except the In-Ovation brackets, which yielded 45 cN, and the Morelli brackets with new and old elastomeric ligatures, which displayed 82 and 49 centiNewtons, respectively. CONCLUSIONS: Damon MX, Easy Clip, Smart Clip, Synergy bracket systems and 8-shaped ligatures proved to be equally effective alternatives for controlling classical friction using 0.014-in nickel-titanium archwires and 0.019 x 0.025-in steel archwires, while the In-Ovation was efficient with 0.014-in archwires but with 0.019 x 0.025-in archwires it exhibited friction that was similar to conventional brackets with used elastomeric ligatures.

Probing the statistical properties of unknown texts: application to the Voynich manuscript

While the use of statistical physics methods to analyze large corpora has been useful to unveil many patterns in texts, no comprehensive investigation has been performed on the interdependence between syntactic and semantic factors. In this study we propose a framework for determining whether a text (e.g., written in an unknown alphabet) is compatible with a natural language and to which language it could belong. The approach is based on three types of statistical measurements, i.e. obtained from first-order statistics of word properties in a text, from the topology of complex networks representing texts, and from intermittency concepts where text is treated as a time series. Comparative experiments were performed with the New Testament in 15 different languages and with distinct books in English and Portuguese in order to quantify the dependency of the different measurements on the language and on the story being told in the book. The metrics found to be informative in distinguishing real texts from their shuffled versions include assortativity, degree and selectivity of words. As an illustration, we analyze an undeciphered medieval manuscript known as the Voynich Manuscript. We show that it is mostly compatible with natural languages and incompatible with random texts. We also obtain candidates for keywords of the Voynich Manuscript which could be helpful in the effort of deciphering it. Because we were able to identify statistical measurements that are more dependent on the syntax than on the semantics, the framework may also serve for text analysis in language-dependent applications.