Structural change and productivity growth 20 years later: old problems, new opportunities. Summary

Includes bibliography

Fungal communities in the garden chamber soils of leaf-cutting ants

Leaf-cutting ants modify the properties of the soil adjacent to their nests. Here, we examined whether such an ant-altered environment impacts the belowground fungal communities. Fungal diversity and community structure of soil from the fungus garden chambers of Atta sexdens rubropilosa and Atta bisphaerica, two widespread leaf-cutting ants in Brazil, were determined and compared with non-nest soils. Culture-dependent methods revealed similar species richness but different community compositions between both types of soils. Penicillium janthinellum and Trichoderma spirale were the prevalent isolates in fungus chamber soils and non-nest soils, respectively. In contrast to cultivation methods, analyses of clone libraries based on the internal transcribed spacer (ITS) region indicated that richness of operational taxonomic units significantly differed between soils of the fungus chamber and non-nest soils. FastUnifrac analyses based on ITS sequences further revealed a clear distinction in the community structure between both types of soils. Plectania milleri and an uncultured Clavariaceae fungus were prevalent in fungus chamber soils and non-nest soils, respectively. FastUnifrac analyses also revealed that fungal community structures of soil from the garden chambers markedly differed among ant species. Our findings suggest that leaf-cutting ants affect fungal communities in the soil from the fungus chamber in comparison to non-nest soils. © 2013 WILEY-VCH Verlag GmbH & Co.

Automatic microstructural characterization and classification using artificial intelligence techniques on ultrasound signals

Secondary phases such as Laves and carbides are formed during the final solidification stages of nickel based superalloy coatings deposited during the gas tungsten arc welding cold wire process. However, when aged at high temperatures, other phases can precipitate in the microstructure, like the γ″ and δ phases. This work presents a new application and evaluation of artificial intelligent techniques to classify (the background echo and backscattered) ultrasound signals in order to characterize the microstructure of a Ni-based alloy thermally aged at 650 and 950 °C for 10, 100 and 200 h. The background echo and backscattered ultrasound signals were acquired using transducers with frequencies of 4 and 5 MHz. Thus with the use of features extraction techniques, i.e.; detrended fluctuation analysis and the Hurst method, the accuracy and speed in the classification of the secondary phases from ultrasound signals could be studied. The classifiers under study were the recent optimum-path forest (OPF) and the more traditional support vector machines and Bayesian. The experimental results revealed that the OPF classifier was the fastest and most reliable. In addition, the OPF classifier revealed to be a valid and adequate tool for microstructure characterization through ultrasound signals classification due to its speed, sensitivity, accuracy and reliability. © 2013 Elsevier B.V. All rights reserved.

Toxicity of hydramethylnon to the leaf-cutting ant Atta sexdens rubropilosa forel (hymenoptera: Formicidae)

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