Fast-Evolving Mitochondrial DNA in Ceriantharia: A Reflection of Hexacorallia Paraphyly?

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

Is the evolutionary history of the O-type P element in the saltans and willistoni groups of Drosophila similar to that of the canonical P element?

We studied the occurrence of O-type P elements in at least one species of each subgroup of the saltans group, in order to better understand the phylogenetic relationships among the elements within the saltans group and with those of species belonging to the willistoni group. We found that the O-type subfamily has a patchy distribution within the saltans group (it does not occur in D. neocordata and D. emarginata), low sequence divergence among species of the saltans group as well as in relation to species of the willistoni group, a lower rate of synonymous substitution for coding sequences compared to Adh, and phylogenetic incongruities. These findings suggest that the evolutionary history of the O-type subfamily within the saltans and willistoni groups follows the same model proposed for the canonical subfamily of P elements, i.e., events of horizontal transfer between species of the saltans and willistoni groups.

Spatial electric load forecasting using an evolutionary heuristic

A method for spatial electric load forecasting using elements from evolutionary algorithms is presented. The method uses concepts from knowledge extraction algorithms and linguistic rules' representation to characterize the preferences for land use into a spatial database. The future land use preferences in undeveloped zones in the electrical utility service area are determined using an evolutionary heuristic, which considers a stochastic behavior by crossing over similar rules. The method considers development of new zones and also redevelopment of existing ones. The results are presented in future preference maps. The tests in a real system from a midsized city show a high rate of success when results are compared with information gathered from the utility planning department. The most important features of this method are the need for few data and the simplicity of the algorithm, allowing for future scalability.

Evolutionary heuristic to determine future land use

In the spatial electric load forecasting, the future land use determination is one of the most important tasks, and one of the most difficult, because of the stochastic nature of the city growth. This paper proposes a fast and efficient algorithm to find out the future land use for the vacant land in the utility service area, using ideas from knowledge extraction and evolutionary algorithms. The methodology was implemented into a full simulation software for spatial electric load forecasting, showing a high rate of success when the results are compared to information gathered from specialists. The importance of this methodology lies in the reduced set of data needed to perform the task and the simplicity for implementation, which is a great plus for most of the electric utilities without specialized tools for this planning activity. © 2008 IEEE.

Insights on the HLA-G Evolutionary History Provided by a Nearby Alu Insertion

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)