Fluid intake patterns: an epidemiological study among children and adolescents in Brazil

Background: Energy from liquids is one of the most important factors that could impact on the high prevalence of children and adolescents obesity around the world. There are few data on the liquid consumption in Brazil. The aim of this study is to evaluate the volume and quality of liquids consumed by Brazilian children and adolescents and to determine the proportion of their daily energy intake composed of liquids. Methods: A multicenter study was conducted in five Brazilian cities; the study included 831 participants between 3 and 17 years of age. A four-day dietary record specific to fluids was completed for each individual, and the volume of and Kcal from liquid intake were evaluated. The average number of Kcal in each beverage was determined based on label information, and the daily energy intake data from liquids were compared with the recommendations of the National Health Surveillance Agency (Agencia Nacional de Vigilancia Sanitaria-ANVISA), the Brazilian food regulation authority, according to each subject's age. Results: As the children aged, the volume of carbonated beverages that they consumed increased significantly, and their milk intake decreased significantly. For children between the ages of 3 and 10, milk and dairy products contributed the greatest daily number of Kcal from liquids. Sugar sweetened beverages which included carbonated beverages, nectars and artificial beverages, accounted for 37% and 45% of the total Kcal from liquid intake in the 3-to 6-year-old and 7- to 10-year-old groups, respectively. Among adolescents (participants 11- to 17-years old), most of the energy intake from liquids came from carbonated beverages, which accounted for an average of 207 kcal/day in this group (42% of their total energy intake from liquids). Health professionals should be attentive to the excessive consumption of sugar sweetened beverages in children and adolescents. The movement toward healthier dietary patterns at the individual and population levels may help to improve programs for preventing overweight and obesity in children and adolescents. Conclusion: From childhood to adolescence the daily volume of liquid ingested increased reaching a total of 2.0 liters on average. Of this volume, the daily volume of milk ingested decreased while the carbonated drinks, sweetened, nectars and artificial beverages increased significantly. The proportion of water remained constant in about 1/3 of the total volume. From 3 to 17 years of age the energy intake from carbonated beverages increased by about 20%. The carbonated drinks on average corresponded to a tenth of the daily requirements of energy of adolescents.

A semi-supervised classification technique based on interacting forces

Semi-supervised learning is a classification paradigm in which just a few labeled instances are available for the training process. To overcome this small amount of initial label information, the information provided by the unlabeled instances is also considered. In this paper, we propose a nature-inspired semi-supervised learning technique based on attraction forces. Instances are represented as points in a k-dimensional space, and the movement of data points is modeled as a dynamical system. As the system runs, data items with the same label cooperate with each other, and data items with different labels compete among them to attract unlabeled points by applying a specific force function. In this way, all unlabeled data items can be classified when the system reaches its stable state. Stability analysis for the proposed dynamical system is performed and some heuristics are proposed for parameter setting. Simulation results show that the proposed technique achieves good classification results on artificial data sets and is comparable to well-known semi-supervised techniques using benchmark data sets.

A novel XML document structure comparison framework based-on sub-tree commonalities and label semantics

XML similarity evaluation has become a central issue in the database and information communities, its applications ranging over document clustering, version control, data integration and ranked retrieval. Various algorithms for comparing hierarchically structured data, XML documents in particular, have been proposed in the literature. Most of them make use of techniques for finding the edit distance between tree structures, XML documents being commonly modeled as Ordered Labeled Trees. Yet, a thorough investigation of current approaches led us to identify several similarity aspects, i.e., sub-tree related structural and semantic similarities, which are not sufficiently addressed while comparing XML documents. In this paper, we provide an integrated and fine-grained comparison framework to deal with both structural and semantic similarities in XML documents (detecting the occurrences and repetitions of structurally and semantically similar sub-trees), and to allow the end-user to adjust the comparison process according to her requirements. Our framework consists of four main modules for (i) discovering the structural commonalities between sub-trees, (ii) identifying sub-tree semantic resemblances, (iii) computing tree-based edit operations costs, and (iv) computing tree edit distance. Experimental results demonstrate higher comparison accuracy with respect to alternative methods, while timing experiments reflect the impact of semantic similarity on overall system performance.