Essential oils from the leaves, stems, flowers and fruits of Melaleuca leucadendra growing in the state of Pernambuco, Brazil, were analyzed using gas chromatography-mass spectrometry (GC-MS). The effects of the oils and their major constituent were evaluated on the agricultural pests Tetranychus urticae and Plutella xylostella in different stages of development. The analysis revealed a M. leucadendra chemotype rich in (E)-nerolidol (81.78 ± 0.90 to 95.78 ± 1.20%). P. xylostella was more susceptible to the oils and major constituent than T. urticae. The fruit oil was 1.5-fold more toxic than the leaf oil to T. urticae eggs. (E)-Nerolidol was 5.5-fold and 4.5-fold more toxic to T. urticae adults than the leaf and fruit oils, respectively. Azamax ® used as the positive control was more efficient than the oils and (E)-nerolidol against T. urticae. However, the oils and (E)-nerolidol were more toxic to P. xylostella than Azamax ® .

Distribution networks have undergone a series of changes, with the insertion of distributed energy resources, such as distributed generation, energy storage systems, and demand response, allowing the consumers to produce energy and have an active role in distribution systems. Thus, it is possible to form microgrids. From the active grid’s point of view, it is necessary to plan the operation considering the distributed resources and the microgrids connected to it, aiming to ensure the maintenance of grid economy and operational safety. So, this paper presents the proposition of a hierarchical model for planning the daily operation of active distribution grids with microgrids. In this case, the entire grid operation is optimized considering the results from the microgrid optimization itself. If none of the technical constraints, for example voltage levels, are reached, the grid is optimized, however, if there are some violations in the constraints feedback is sent to the internal microgrid optimization to be run again. Several scenarios are evaluated to verify the iteration among the controls in a coordinated way allowing the optimization of the operation of microgrids, as well as of the distribution network. A coordinated and hierarchical operation of active distribution networks with microgrids, specifically when they have distributed energy resources allocated and operated in an optimized way, results in a reduction in operating costs, losses, and greater flexibility and security of the whole system.

Didactic platforms, used in real-time digital signal processing courses, are generally dedicated digital signal processors or field-programmable gate arrays. These devices are expensive and difficult to program, preventing their widespread use in signal processing courses. On the other hand, the new technology of digital signal controllers, microcontrollers with floating point and mathematical operations, can reduce the cost of dedicated platforms for real-time digital signal processors, facilitating the development of digital signal processors projects and educational applications, such as teaching adaptive filters. Here, we present a low-cost didactic platform for developing real-time adaptive filters using the digital signal processors hardware based on the ARM Cortex-M7 processor. We present the theoretical aspects of the least mean squares and normalized least mean squares algorithms and an experimental script to help students learn real-time adaptive filters. We also describe the platform structure and the performance measurement, in terms of mean square error, signal-to-noise ratio, and computational efficiency. Finally, we present a brief discussion on the use of this platform in classes and the improvement in the student engagement and attendance.

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