No abstract

A methodology to predict the stability status of mine rock slopes is proposed. Two techniques of multivariate statistics are used: principal component analysis and discriminant analysis. Firstly, principal component analysis was applied in order to change the original qualitative variables into quantitative ones, as well as to reduce data dimensionality. Then, a boosting procedure was used to optimize the resulting function by the application of discriminant analysis in the principal components. In this research two analyses were performed. In the first analysis two conditions of slope stability were considered: stable and unstable. In the second analysis three conditions of slope stability were considered: stable, overall failure and failure in set of benches. A comprehensive geotechnical database consisting of 18 variables measured in 84 pit-walls all over the world was used to validate the methodology. The discriminant function was validated by two different procedures, internal and external validations.

Agroecus griseus is a serious corn pest in Brazil. Contents of the dorsal abdominal glands (DAGs) in nymphs, and the metathoracic gland (MTG) in adults of this species were characterized and quantified. Compounds found were similar to those of other Pentatomidae species and included aliphatic hydrocarbons, aldehydes, oxo-alkenals, and esters. However, two compounds were found in the MTG that have not been described previously for this family. Mass spectrometry, infrared spectroscopy, and gas chromatographic analysis using coinjection with authentic standards confirmed the identities of the compounds as enantiopure (S)-2-methylbutyl acetate and 3-methyl-2-butenyl acetate. The five nymphal instars showed significantly different ratios of components, mainly between those of the first and later instars. No significant differences were detected in MTG contents between sexes. Gas chromatography (GC) analysis of aeration extracts of males and females showed the presence of a compound released exclusively by males. Gas chromatography - electroantennographic detection (GC-EAD) assays indicated that the male-specific compound is bioactive in females, suggesting the presence of an attractant pheromone. The mass spectrum and infrared data for this compound matched with methyl 2,6,10-trimethyltridecanoate, a sex pheromone component previously detected in the stink bugs, Euschistus heros and E. obscurus. The synthetic standard coeluted with the natural pheromone on two different GC stationary phases, confirming the proposed structure. Y-tube olfactometer assays showed that the synthetic standard was strongly attractive to females, and GC-EAD tests produced responses with antennae from females similar to those of the natural pheromone.

Essa pesquisa apresenta uma análise do perfil dos egressos do Programa de Pós-Graduação em Engenharia Mineral da Universidade Federal de Ouro Preto (PPGEM/UFOP). Para tal, foi realizada uma pesquisa que consistiu no envio de um questionário online para os egressos do PPGEM/UFOP. O questionário foi respondido por 79 egressos do programa. Os resultados indicam que, em sua maioria, os egressos que cursaram o curso de pós-graduação em engenharia mineral obtiveram o título de mestre, moram no estado de Minas Gerais, estudaram em instituição de ensino público durante o ensino médio, realizaram graduação na UFOP e foram bolsistas. Com relação a suas atividades atuais, os egressos são, em sua maioria, servidores públicos e atuam como docentes em instituições públicas de ensino. Além disso, os mesmos consideram que a formação recebida no PPGEM foi excelente e que o aprendizado influenciou positivamente em suas práticas profissionais.

This paper proposes the use of a hybrid method that combines Biased Random Key Genetic Algorithm (BRKGA) with a local search heuristic to separate Brazilian tailing dam data into groups. The goal was identifying dams similar to Fundão and B1 failed dams. The groups were created by solving the clustering problem by BRKGA. The clustering problem consists in separating a set of objects into groups such that members of each group are similar to each other. The data was composed by 427 dams, with the actual 425 dams of Brazilian Register of Tailing Dams and the two Brazilian failed dams from the last years. Computational experiments considering real data available are presented to demonstrate the effi cacy of the proposed method producing feasible solutions. Thus, it is expected that the good results can be applied in the identifi cation of tailings dams with risk potentials, assisting in the identifi cation of these dams.