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- Hudson, Lawrence N, et al.
(författare)
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The database of the PREDICTS (Projecting Responses of Ecological Diversity In Changing Terrestrial Systems) project
- 2017
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Ingår i: Ecology and Evolution. - : John Wiley & Sons. - 2045-7758. ; 7:1, s. 145-188
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Tidskriftsartikel (refereegranskat)abstract
- The PREDICTS project-Projecting Responses of Ecological Diversity In Changing Terrestrial Systems (www.predicts.org.uk)-has collated from published studies a large, reasonably representative database of comparable samples of biodiversity from multiple sites that differ in the nature or intensity of human impacts relating to land use. We have used this evidence base to develop global and regional statistical models of how local biodiversity responds to these measures. We describe and make freely available this 2016 release of the database, containing more than 3.2 million records sampled at over 26,000 locations and representing over 47,000 species. We outline how the database can help in answering a range of questions in ecology and conservation biology. To our knowledge, this is the largest and most geographically and taxonomically representative database of spatial comparisons of biodiversity that has been collated to date; it will be useful to researchers and international efforts wishing to model and understand the global status of biodiversity.
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- Kehoe, Laura, et al.
(författare)
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Make EU trade with Brazil sustainable
- 2019
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Ingår i: Science. - : American Association for the Advancement of Science (AAAS). - 0036-8075 .- 1095-9203. ; 364:6438, s. 341-
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Tidskriftsartikel (övrigt vetenskapligt/konstnärligt)
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- Calinescu, Radu, et al.
(författare)
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Synthesis and Verification of Self-aware Computing Systems
- 2017
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Ingår i: Self-aware Computing Systems. - Cham : Springer. - 9783319474724 ; , s. 337-373
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Bokkapitel (övrigt vetenskapligt/konstnärligt)abstract
- Self-aware computing systems are envisaged to exploit the knowledge of their own software architecture, hardware infrastructure and environment in order to follow high-level goals through proactively adapting as their environment evolves. This chapter describes two classes of key enabling techniques for self-adaptive systems: automated synthesis and formal verification. The ability to dynamically synthesize component connectors and compositions underpins the proactive adaptation of the architecture of self-aware systems. Deciding when adaptation is needed and selecting valid new architectures or parameters for self-aware systems often requires formal verification. We present the state of the art in the use of the two techniques for the development of self-aware computing systems and summarize the main research challenges associated with their adoption in practice.
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