An Ontology of Soil Properties and Processes

Assessing the Underworld (ATU) is a large interdisciplinary UK research project, which addresses challenges in integrated inter-asset maintenance. As assets on the surface of the ground (e.g. roads or pave- ments) and those buried under it (e.g. pipes and cables) are supported by the ground, the properties and processes of soil a ect the performance of these assets to a signi cant degree. In order to make integrated deci- sions, it is necessary to combine the knowledge and expertise in multiple areas, such as roads, soil, buried assets, sensing, etc. This requires an underpinning knowledge model, in the form of an ontology. Within this context, we present a new ontology for describing soil properties (e.g. soil strength) and processes (e.g. soil compaction), as well as how they a ect each other. This ontology can be used to express how the ground a ects and is a ected by assets buried under the ground or on the ground surface. The ontology is written in OWL 2 and openly available from the University of Leeds data repository: http://doi.org/10.5518/54

Environmental Assessment of Soil for Monitoring Volume I: Indicators & Criteria

The ENVASSO Project (Contract 022713) was funded 2006-8, under the European Commission 6th Framework Programme of Research, with the objective of defining and documenting a soil monitoring system appropriate for soil protection at continental level. The ENVASSO Consortium, comprising 37 partners drawn from 25 EU Member States, reviewed soil indicators, identified existing soil inventories and monitoring programmes in the Member States, designed and programmed a database management system to capture, store and supply soil profile data, and drafted procedures and protocols appropriate for inclusion in a European soil monitoring network of sites that are geo-referenced and at which a qualified sampling process is or could be conducted. Volume I, one of six describing the results of the ENVASSO Project, identifies 290 potential indicators relating to 188 key issues for the following nine threats to soil: erosion, organic matter decline, contamination, sealing, compaction, loss of biodiversity, salinisation, landslides and desertification. Sixty candidate indicators that address 27 key issues, covering all these threats, were selected on the basis of their thematic relevance, policy relevance and data availability. Baseline and threshold values are presented and detailed Fact Sheets describe three priority indicators for each soil threat.JRC.DDG.H.7-Land management and natural hazard

MILCS: A mutual information learning classifier system

This paper introduces a new variety of learning classifier system (LCS), called MILCS, which utilizes mutual information as fitness feedback. Unlike most LCSs, MILCS is specifically designed for supervised learning. MILCS's design draws on an analogy to the structural learning approach of cascade correlation networks. We present preliminary results, and contrast them to results from XCS. We discuss the explanatory power of the resulting rule sets, and introduce a new technique for visualizing explanatory power. Final comments include future directions for this research, including investigations in neural networks and other systems. Copyright 2007 ACM

Transcriptome analysis of Thapsia laciniata rouy provides insights into terpenoid biosynthesis and diversity in apiaceae

Thapsia laciniata Rouy (Apiaceae) produces irregular and regular sesquiterpenoids with thapsane and guaiene carbon skeletons, as found in other Apiaceae species. A transcriptomic analysis utilizing Illumina next-generation sequencing enabled the identification of novel genes involved in the biosynthesis of terpenoids in Thapsia. From 66.78 million HQ paired-end reads obtained from T. laciniata roots, 64.58 million were assembled into 76,565 contigs (N50: 1261 bp). Seventeen contigs were annotated as terpene synthases and five of these were predicted to be sesquiterpene synthases. Of the 67 contigs annotated as cytochromes P450, 18 of these are part of the CYP71 clade that primarily performs hydroxylations of specialized metabolites. Three contigs annotated as aldehyde dehydrogenases grouped phylogenetically with the characterized ALDH1 from Artemisia annua and three contigs annotated as alcohol dehydrogenases grouped with the recently described ADH1 from A. annua. ALDH1 and ADH1 were characterized as part of the artemisinin biosynthesis. We have produced a comprehensive EST dataset for T. laciniata roots, which contains a large sample of the T. laciniata transcriptome. These transcriptome data provide the foundation for future research into the molecular basis for terpenoid biosynthesis in Thapsia and on the evolution of terpenoids in Apiaceae.Damian Paul Drew, Bjørn Dueholm, Corinna Weitzel, Ye Zhang, Christoph W. Sensen and Henrik Toft Simonse

A decision support system for ground improvement method selection

Abstract unavailable please refer to PD