The USAID and the teaching of mathematics in Rio Grande do Norte

In the 1960s occurred great changes in the general education and, specially in the mathematical teaching, throughout Brazil. Besides the Law Diretrizes e Bases for Education (law 4024/1961), such changes also was occurred by opposite educational movements. In one side, those ones that valorized the popular education and culture and, for the other side, the international agreements between universities and government organs, like SUDENE and MEC, with United States Agency for International Development (USAID). These agreements purposed the cultural alignment. In this article we will expose some of these agreements and their interference in two courses for teachers' education. These teachers taught mathematics for the elementary school, in Rio Grande do Norte.

Experiencing Manipulative Material for the Teaching and Learning of Mathematics

This paper presents some outcomes from research based on classroom experiences. The main themes are the use of mirrors, kaleidoscopes, dynamic geometry software, and manipulative material considering their possibilities for the teaching and learning of Euclidean and non-Euclidean geometries.

Genomics-based design of defined growth media for the plant pathogen Xylella fastidiosa

Based on the genetic analysis of the phytopathogen Xylella fastidiosa genome, five media with defined composition were developed and the growth abilities of this fastidious prokaryote were evaluated in liquid media and on solid plates. All media had a common salt composition and included the same amounts of glucose and vitamins but differed in their amino acid content. XDM1 medium contained amino acids threonine, serine, glycine, alanine, aspartic acid and glutamic acid, for which complete degradation pathways occur in X fastidiosa; XDM2 included serine and methionine, amino acids for which biosynthetic enzymes are absent, plus asparagine and glutamine, which are abundant in the xylem sap; XDM3 had the same composition as XDM2 but with asparagine replaced by aspartic acid due to the presence of complete degradation pathway for aspartic acid; XDM4 was a minimal medium with glutamine as a sole nitrogen source; XDM5 had the same composition as XDM4, plus methionine. The liquid and solidified XDM2 and XDM3 media were the most effective for the growth of X. fastidiosa. This work opens the opportunity for the in silico design of bacterial defined media once their genome is sequenced. (C) 2002 Federation of European Microbiological Societies. Published by Elsevier B.V. B.V. All rights reserved.

Contribuições da CADES para a Educação (Matemática) Secundária no Brasil: uma Descrição da Produção Bibliográfica (1953-1971)

The so called Campaign for the Improvement and Diffusion of High School (in Portuguese, CADES) took place between 1953 and 1971, in Brazil. During this period, the Campaign published or helped publish dozens of books, in different teaching areas, and several of them were located by the authors of this article. These books guided high school teachers with respect to curriculum planning, legal aspects and methods of teaching. In this article, we contextualize historically this Campaign and also mention its objectives. We briefly describe some of the books found - especially those related to the teaching of mathematics - in order to open perspectives for future approaches and research that can be done based on this written material. Our main aim is to discuss its orientations and to provide ingredients that enable the construction of considerations related to this perspective of training mathematics teachers during a period when there were few colleges and universities to prepare teachers in Brazil.

Neural network based estimation of torque in induction motors for real-time applications

Induction motors are largely used in several industry sectors. The selection of an induction motor has still been inaccurate because in most of the cases the load behavior in its shaft is completely unknown. The proposal of this article is to use artificial neural networks for torque estimation with the purpose of best selecting the induction motors rather than conventional methods, which use classical identification techniques and mechanical load modeling. Since proposed approach estimates the torque behavior from the transient to the steady state, one of its main contributions is the potential to also be implemented in control schemes for real-time applications. Simulation results are also presented to validate the proposed approach.

Time-series-based maximization of distributed wind power generation integration

Energy policies and technological progress in the development of wind turbines have made wind power the fastest growing renewable power source worldwide. The inherent variability of this resource requires special attention when analyzing the impacts of high penetration on the distribution network. A time-series steady-state analysis is proposed that assesses technical issues such as energy export, losses, and short-circuit levels. A multiobjective programming approach based on the nondominated sorting genetic algorithm (NSGA) is applied in order to find configurations that maximize the integration of distributed wind power generation (DWPG) while satisfying voltage and thermal limits. The approach has been applied to a medium voltage distribution network considering hourly demand and wind profiles for part of the U.K. The Pareto optimal solutions obtained highlight the drawbacks of using a single demand and generation scenario, and indicate the importance of appropriate substation voltage settings for maximizing the connection of MPG.

Differential-Evolution-Based Optimization of the Dynamic Response for Parallel Operation of Inverters With No Controller Interconnection

In this paper, the use of differential evolution ( DE), a global search technique inspired by evolutionary theory, to find the parameters that are required to achieve optimum dynamic response of parallel operation of inverters with no interconnection among the controllers is proposed. Basically, in order to reach such a goal, the system is modeled in a certain way that the slopes of P-omega and Q-V curves are the parameters to be tuned. Such parameters, when properly tuned, result in system's eigenvalues located in positions that assure the system's stability and oscillation-free dynamic response with minimum settling time. This paper describes the modeling approach and provides an overview of the motivation for the optimization and a description of the DE technique. Simulation and experimental results are also presented, and they show the viability of the proposed method.

In silico network topology-based prediction of gene essentiality

The identification of genes essential for survival is important for the understanding of the minimal requirements for cellular life and for drug design. As experimental studies with the purpose of building a catalog of essential genes for a given organism are time-consuming and laborious, a computational approach which could predict gene essentiality with high accuracy would be of great value. We present here a novel computational approach, called NTPGE (Network Topology-based Prediction of Gene Essentiality), that relies on the network topology features of a gene to estimate its essentiality. The first step of NTPGE is to construct the integrated molecular network for a given organism comprising protein physical, metabolic and transcriptional regulation interactions. The second step consists in training a decision-tree-based machine-learning algorithm on known essential and non-essential genes of the organism of interest, considering as learning attributes the network topology information for each of these genes. Finally, the decision-tree classifier generated is applied to the set of genes of this organism to estimate essentiality for each gene. We applied the NTPGE approach for discovering the essential genes in Escherichia coli and then assessed its performance. (C) 2007 Elsevier B.V. All rights reserved.

Structuralism and the Applicability of Mathematics

In this paper I argue for the view that structuralism offers the best perspective for an acceptable account of the applicability of mathematics in the empirical sciences. Structuralism, as I understand it, is the view that mathematics is not the science of a particular type of objects, but of structural properties of arbitrary domains of entities, regardless of whether they are actually existing, merely presupposed or only intentionally intended.

A multimedia environment for supporting the teaching of robotics systems

This paper aims at describing an educational system for teaching and learning robotic systems. Multimedia resources were used to construct a virtual laboratory where users are able to use functionalities of a virtual robotic arm, by moving and clicking the mouse without caring about the detailed internal robot operation. Moreover through the multimedia system the user can interact with a real robot arm. The engineering students are the target public of the developed system. With its contents and interactive capabilities, it has been used as a support to the traditional face-to-face classes on the subject of robotics.. In the paper it is first introduced the metaphor of Virtual Laboratory used in the system. Next, it is described the Graphical and Multimedia Environment approach: an interactive graphic user interface with a 3D environment for simulation. Design and implementation issues of the real-time interactive multimedia learning system, which supports the W3C SMIL standard for presenting the real-time multimedia teaching material, are described. Finally, some preliminary conclusions and possible future works from this research are presented.

TEACHING OF MEDICAL MICROBIOLOGY - COMMENTS ON BASIC VERSUS APPLIED ASPECTS RELATED TO PROFESSION

Comments about education and medicine teaching were made. The learning and the curriculum in according with the priorities of the country's health had special emphasis.Students and teachers of Botucatu considered that the improvement of the 2nd year medical microbiological course was good with predominantly basic contents. The students prefer a balanced content or predominantly applied to medicine.Three phases of the teaching of microbiological contents are proposed: 1st - in the basic cycly (2nd year); 2nd - into the course of Clinical Laboratory (3rd or 4th year); 3rd - into the clinical cycle, following a program of integration.

Weather-based prediction of anthracnose severity using artificial neural network models

Data were collected and analysed from seven field sites in Australia, Brazil and Colombia on weather conditions and the severity of anthracnose disease of the tropical pasture legume Stylosanthes scabra caused by Colletotrichum gloeosporioides. Disease severity and weather data were analysed using artificial neural network (ANN) models developed using data from some or all field sites in Australia and/or South America to predict severity at other sites. Three series of models were developed using different weather summaries. of these, ANN models with weather for the day of disease assessment and the previous 24 h period had the highest prediction success, and models trained on data from all sites within one continent correctly predicted disease severity in the other continent on more than 75% of days; the overall prediction error was 21.9% for the Australian and 22.1% for the South American model. of the six cross-continent ANN models trained on pooled data for five sites from two continents to predict severity for the remaining sixth site, the model developed without data from Planaltina in Brazil was the most accurate, with >85% prediction success, and the model without Carimagua in Colombia was the least accurate, with only 54% success. In common with multiple regression models, moisture-related variables such as rain, leaf surface wetness and variables that influence moisture availability such as radiation and wind on the day of disease severity assessment or the day before assessment were the most important weather variables in all ANN models. A set of weights from the ANN models was used to calculate the overall risk of anthracnose for the various sites. Sites with high and low anthracnose risk are present in both continents, and weather conditions at centres of diversity in Brazil and Colombia do not appear to be more conducive than conditions in Australia to serious anthracnose development.