Teaching and learning data structures supported by computers: An experiment using CADILAG tool

This paper aims to present the use of a learning object (CADILAG), developed to facilitate understanding data structure operations by using visual presentations and animations. The CADILAG allows visualizing the behavior of algorithms usually discussed during Computer Science and Information System courses. For each data structure it is possible visualizing its content and its operation dynamically. Its use was evaluated an the results are presented. © 2012 AISTI.

Towards an intelligent graphical interface for linear programming modelling

The increase of computing power of the microcomputers has stimulated the building of direct manipulation interfaces that allow graphical representation of Linear Programming (LP) models. This work discusses the components of such a graphical interface as the basis for a system to assist users in the process of formulating LP problems. In essence, this work proposes a methodology which considers the modelling task as divided into three stages which are specification of the Data Model, the Conceptual Model and the LP Model. The necessity for using Artificial Intelligence techniques in the problem conceptualisation and to help the model formulation task is illustrated.

Persistência da lactação e Influência da estrutura de dados sobre a estimação de parâmetros genéticos para a produção de leite de bovinos da raça Holandesa

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Desenvolvimento de uma plataforma de software para a modelagem digital de terrenos baseada em TIN

Topographical surfaces can be represented with a good degree of accuracy by means of maps. However these are not always the best tools for the understanding of more complex reliefs. In this sense, the greatest contribution of this work is to specify and to implement the architecture of an opensource software system capable of representing TIN (Triangular Irregular Network) based digital terrain models. The system implementation follows the object oriented programming and generic paradigms enabling the integration of various opensource tools such as GDAL, OGR, OpenGL, OpenSceneGraph and Qt. Furthermore, the representation core of the system has the ability to work with multiple topological data structures from which can be extracted, in constant time, all the connectivity relations between the entities vertices, edges and faces existing in a planar triangulation what helps enormously the implementation for real time applications. This is an important capability, for example, in the use of laser survey data (Lidar, ALS, TLS), allowing for the generation of triangular mesh models in the order of millions of points.

Using tree population size structures to assess the impacts of cattle grazing and eucalypts plantations in subtropical South America

To evaluate the effects of distinct management of the matrix in which forest fragments are found upon plant populations thriving in forest remnants in south Brazil, we assessed the conservation status of populations of four woody species (Campomanesia rhombea, Diospyros incontans, Myrciaria cuspidata and Sebastiania commersoniana) through analyses of size structure. Analyzes were carried out at two scales. At a local scale, we consider populations in fragments surrounded by pastures or eucalypts forest plantations, and at a regional scale we also consider larger forest tracts taken as reference areas (Rio Grande do Sul Forest Inventory databank). Population size structures were summarized using the symmetry of height distributions. Small individual size classes prevailed at the local scale in fragments surrounded by eucalypts plantations, whereas in areas exposed to cattle ranching, populations of the same species consistently lack small individuals. At the regional scale, populations in fragments surrounded by pastures presented greater skewness (prevalence of small plants) than populations in reference areas, while populations surrounded by eucalypts plantations presented intermediate skewness. These results reinforce the notion that plantations have a higher conservation value for forest ecosystems than other commercial land uses, like cattle ranching. © 2010 Springer Science+Business Media B.V.

Dispersion of Seeds of Tree Species by the Leaf-Cutting Ant Acromyrmex subterraneus molestans (Hymenoptera: Formicidae) in Vicosa, Minas Gerais State, Brazil

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Vegetative propagation of bauhinia x blakeana, an ornamental sterile tree

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Supercritical fluid extraction from Lippia alba: global yields, kinetic data, and extract chemical composition

In this work, experimental data for the system Lippia alba + CO2 is presented. The major constituents of the L. alba volatile oil are limonene and carvone. Thus, literature data for the systems limonene + CO2 and carvone + CO2, and the Peng-Robinson equation of state (PR-EOS) were used to select the operating temperature and pressure, which maximize the global yield in L. alba extract. Global yields were determined at 80, 100, and 120 bar and 40, 45, and 50 degrees C. L. alba extracts were also obtained by conventional processes (hydrodistillation, low-pressure ethanol extraction and Soxhlet ethanol). The chemical compositions of the extracts were determined by gas and thin layer chromatography (TLC). The secretor structures of L. alba were observed by scanning electron microscopy (SEM) before and after supercritical extraction. The largest yield (similar to 7%, mass of extract/mass of dry solid) of the CO2-extract was obtained at 318 K and 100 bar. The chemical compositions of the CO2-extracts were different from those of the extracts obtained by Soxhlet and low-pressure solvent extraction (LPSE) because of the co-extraction of heavy substances by ethanol. The operating conditions that maximized the carvone and limomene yields were 80 bar and 323 K (80 mass%) and 120 bar and 323 K (17 mass%), respectively. (c) 2004 Elsevier B.V All rights reserved.

An evergreen neotropical savanna tree (Gochnatia polymorpha, Asteraceae) produces different dry- and wet-season leaf types

Gochnatia polymorpha (Less.) Cabrera is a widespread tree species found in different physiognomies of neotropical savanna (cerrado) formations of south-eastern Brazil. The present study describes some leaf anatomical characteristics of this species as a function of the time of leaf flush, during dry or wet seasons. This species presents anatomical plasticity in the cuticle, palisade parenchyma and abaxial epidermis as well as in stomatal size and stomatal and trichome density, which are leaf structures linked with water-status control. Leaf structure changed to suit the particular environmental conditions during dry and wet seasons. The production of different wet-and dry-season leaf types in G. polymorpha could be a response to drought and an adaptation to environmental constraints in the cerrado.

Nested liana-tree network in three distinct neotropical vegetation formations

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Structural Health Monitoring in Smart Structures Through Time Series Analysis

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Experimental Active Vibration Control in Truss Structures Considering Uncertainties in System Parameters

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

High levels of genetic differentiation and selfing in the Brazilian cerrado fruit tree Dipteryx alata Vog. (Fabaceae)

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Spatial Distribution of Seropositive Dogs to Leptospira spp. and Evaluation of Leptospirosis Risk Factors Using a Decision Tree

Background: Leptospirosis is an important zoonotic disease associated with poor areas of urban settings of developing countries and early diagnosis and prompt treatment may prevent disease. Although rodents are reportedly considered the main reservoirs of leptospirosis, dogs may develop the disease, may become asymptomatic carriers and may be used as sentinels for disease epidemiology. The use of Geographical Information Systems (GIS) combined with spatial analysis techniques allows the mapping of the disease and the identification and assessment of health risk factors. Besides the use of GIS and spatial analysis, the technique of data mining, decision tree, can provide a great potential to find a pattern in the behavior of the variables that determine the occurrence of leptospirosis. The objective of the present study was to apply Geographical Information Systems and data prospection (decision tree) to evaluate the risk factors for canine leptospirosis in an area of Curitiba, PR.Materials, Methods & Results: The present study was performed on the Vila Pantanal, a urban poor community in the city of Curitiba. A total of 287 dog blood samples were randomly obtained house-by-house in a two-day sampling on January 2010. In addition, a questionnaire was applied to owners at the time of sampling. Geographical coordinates related to each household of tested dog were obtained using a Global Positioning System (GPS) for mapping the spatial distribution of reagent and non-reagent dogs to leptospirosis. For the decision tree, risk factors included results of microagglutination test (MAT) from the serum of dogs, previous disease on the household, contact with rats or other dogs, dog breed, outdoors access, feeding, trash around house or backyard, open sewer proximity and flooding. A total of 189 samples (about 2/3 of overall samples) were randomly selected for the training file and consequent decision rules. The remained 98 samples were used for the testing file. The seroprevalence showed a pattern of spatial distribution that involved all the Pantanal area, without agglomeration of reagent animals. In relation to data mining, from 189 samples used in decision tree, a total of 165 (87.3%) animal samples were correctly classified, generating a Kappa index of 0.413. A total of 154 out of 159 (96.8%) samples were considered non-reagent and were correctly classified and only 5/159 (3.2%) were wrongly identified. on the other hand, only 11 (36.7%) reagent samples were correctly classified, with 19 (63.3%) samples failing diagnosis.Discussion: The spatial distribution that involved all the Pantanal area showed that all the animals in the area are at risk of contamination by Leptospira spp. Although most samples had been classified correctly by the decision tree, a degree of difficulty of separability related to seropositive animals was observed, with only 36.7% of the samples classified correctly. This can occur due to the fact of seronegative animals number is superior to the number of seropositive ones, taking the differences in the pattern of variable behavior. The data mining helped to evaluate the most important risk factors for leptospirosis in an urban poor community of Curitiba. The variables selected by decision tree reflected the important factors about the existence of the disease (default of sewer, presence of rats and rubbish and dogs with free access to street). The analyses showed the multifactorial character of the epidemiology of canine leptospirosis.