High level coordination and decision making of a simulated robotic soccer team

Tese de mestrado integrado. Engenharia Informática e Computação. Faculdade de Engenharia. Universidade do Porto. 201

Sistemas de informação desenvolvidos no âmbito do Programa Aveiro Norte

O propósito deste artigo é o de demonstrar o relevo que os sistemas de informação têm em todo o processo de criação e desenvolvimento de uma nova oferta formativa potenciada pela Universidade de Aveiro no norte do distrito. Inicialmente, e com o intuito de desenvolver ferramentas para a gestão e administração do Programa Aveiro-Norte, criou-se o website do Programa Aveiro-Norte. A sua forte aderência por parte dos vários actores envolvidos na utilização do mesmo sistema, deu origem a novos inputs com vista ao aperfeiçoamento do mesmo, bem como novos sistemas que promovem uma maior interacção com o tecido empresarial da região. Apresentamos, de uma forma sucinta e clara, os vários sistemas em produção e desenvolvimento e como é que interagem no ‘Universo Aveiro-Norte’, dando origem a um portal informativo que promova todas as entidades envolvidas criando um fluxo de informação comum. De salientar, a plataforma Aveiro- Norte, o ABC – Arquivo Bibliográfico para a Produção Científica, o SIEEDV - Sistema de Informação Empresarial Entre o Douro e Vouga e OFEDV – Oferta Formativa de Entre o Douro e Vouga

Didactic Sequence for Teaching Exponential Function

This paper presents a methodological proposal for the teaching of exponential function, resulting from the application of a didactic sequence involving exponential function, where evidence of learning and the consolidation and application of mathematical concepts in problem solving were identified and analyzed. The Didactic Engineering of Michèle Artigue (1988) was used as a research methodology. As theoretical contributions that guided and enabled the development of the research, we chose the use of Mathematical Investigation in the classroom; Didactic Sequence in the conception of Zabala (1999); the Articulated Units of Conceptual Reconstruction proposed by Cabral (2017) and assumptions of Vygotsky\u27s theory. A didactic sequence composed of five UARC\u27s was elaborated to work the exponential function, with a view to minimizing the difficulties naturally imposed by the content to be explained. Microgenetic analysis of verbal interactions between teacher and students was used to analyze the results of the application. The results show that the students participating in the experiment showed evidence of learning, recorded during the process, and began to have a good understanding of the concepts and properties related to the topic, in addition to a good performance in carrying out the activities, facts that corroborate the potential of the didactic sequence proposed herein

Modeling biomass and nutrients in a eucalyptus stand in the cerrado

The prediction of biological processes, which involve growth and plant development, is possible via the adjustment of mathematical models. In forest areas, these models assist in management practices, silviculture, harvesting, and soil fertility. Diameter, basal area, and height are predictors of volume and biomass estimates in forest stands. This study utilized different non-linear models for estimating biomass and nutrient values in the aerial biomass and roots of an unmanaged eucalypt stand in Cerrado dystrophic soil. It was hypothesized that the models would estimate the nutrients of the aboveground biomass and roots after meeting the selection and validation criteria. By statistical analysis of the parameters and subsequent validation, the Schumacher–Hall model was presented to be the best fit for biomass and nutrients. This result confirmed the ability of different variables, including diameter, basal area, and height, to be predicted. Estimating the nutrient values in the aboveground biomass and roots allowed a better understanding of the quality of the vegetal residues that remained in the soil. For dystrophic soils, which occur in the Cerrado, these estimates become even more relevant

The role of ascorbate peroxidase, guaiacol peroxidase, and polysaccharides in cassava (Manihot esculenta Crantz) roots under postharvest physiological deterioration

Abstract This study aimed to investigate the role of ascorbate peroxidase (APX), guaiacol peroxidase (GPX), polysaccharides, and protein contents associated with the early events of postharvest physiological deterioration (PPD) in cassava roots. Increases in APX and GPX activity, as well as total protein contents occurred from 3 to 5 days of storage and were correlated with the delay of PPD. Cassava samples stained with periodic acid-Schiff (PAS) highlighted the presence of starch and cellulose. Degradation of starch granules during PPD was also detected. Slight metachromatic reaction with toluidine blue is indicative of increasing of acidic polysaccharides and may play an important role in PPD delay. Principal component analysis (PCA) classified samples according to their levels of enzymatic activity based on the decision tree model which showed GPX and total protein amounts to be correlated with PPD. The Oriental (ORI) cultivar was more susceptible to PPD.This work was supported by PEC-PG ("Programa de Estudantes Convenio de Pos-Graduacao") coordinated by CAPES ("Coorde nacao de Aperfeicoamento de Pessoal de Nivel Superior"). CNPq has provided a research fellowship to Marcelo Maraschin

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear un derstanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5–7 vast areas of the tropics remain understudied.8–11 In the American tropics, Amazonia stands out as the world’s most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepre sented in biodiversity databases.13–15 To worsen this situation, human-induced modifications16,17 may elim inate pieces of the Amazon’s biodiversity puzzle before we can use them to understand how ecological com munities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple or ganism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region’s vulnerability to environmental change. 15%–18% of the most ne glected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lostinfo:eu-repo/semantics/publishedVersio