The aim of the present paper is to evaluate the changes of organic matter during the composting process of fresh winery and distillery residues (WDR) by means of classical and chemometric analysis of (13)C cross-polarization magic angle spinning (CPMAS) NMR and Fourier transform infrared (FT-IR) spectra. (13)C NMR spectroscopy displayed a preferential biodegradation of carbohydrates as well as an accumulation of aliphatic chains (cutin- and suberin-like substances). This preferential biodegradation of the organic fractions reduces the landfill emission potential. Although the composition of the input mixture strongly affects the shape of the infrared (IR) spectra, typical bands of components can be selected and used to follow the composting process; that is, changes in the relative absorbances of the band of nitrate (at 1384 cm(-1)) and in the band of carbohydrates (at 1037 cm(-1)) have been observed. In addition, different chemometric tools, such as partial least-squares (PLS), interval PLS (iPLS), backward iPLS (biPLS), and genetic algorithm (GA), have been used to find the most relevant spectral region during the composting process. Chemometric analysis based on the combined and sequential use of iPLS and GA has been revealed as a very powerful tool for the detection in samples of the most relevant spectral region related to the composting process. From the obtained results, it can be concluded that CPMAS (13)C NMR supported by FT-IR could provide information about the evolution and characteristics of the organic matter during the composting process in order to avoid contamination problems after its use as amendment in agriculture or after landfilling.

This paper proposes a pedagogical and technical approach to support the flow of learning activities outside of school and in class. One primary goal is to develop curricula that bring multimedia resources to outdoor settings to enrich the field experience, and to enable students to make connections between what they learn outside and the formal curriculum. A pilot user scenario and the supporting technology for a set of collaborative learning activities involving tasks of preparation, data gathering, data analyzing, visualization and modeling related to a diversity of content areas are described. The background for the mobile infrastructure, including a learning object repository, has been implemented and tested.

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Concept maps are commonly used as knowledge representation mechanisms to classify a given domain in the scope of a constructivist knowledge building process. In this paper we carry out social constructivist learning experiences using concept maps as a collaborative knowledge-sharing tool with applications in the coordination of virtual communities for learning. In our experiment, the community studies an environmental area -theoretically and in-situ, collects data from a variety of experiments and makes a representation of it. Then, they build a common concept map representing their understanding of this area using a set of tools developed ad-hoc and integrated by a metamodel wrapping approach. Finally, they complete it linking their node with the collected information as a way to organize and to navigate through the different pieces of knowledge that they have been accumulating during several fieldtrips.