Evaluation of selected recurrence measures in discriminating pre-ictal and inter-ictal periods from epileptic EEG data

7 pages, 4 figures Acknowledgement We are grateful to M. Riedl and G. Ansmann for fruitful discussions and critical comments on earlier versions of the manuscript. This work was supported by the Volkswagen Foundation (Grant Nos. 88461, 88462, 88463, 85390, 85391 and 85392).

Crowdsourcing without a crowd : Reliable online species identification using Bayesian models to minimize crowd size

Acknowledgment This research is supported by an award made by the RCUK Digital Economy program to the University of Aberdeen’s dot.rural Digital Economy Hub (ref. EP/G066051/1).

Stability threshold approach for complex dynamical systems

Acknowledgments This paper was developed within the scope of the IRTG 1740/TRP 2011/50151-0, funded by the DFG/FAPESP, and supported by the Government of the Russian Federation (Agreement No. 14.Z50.31.0033 with the Institute of Applied Physics RAS). The first author thanks Dr Roman Ovsyannikov for valuable discussions regarding estimation of the mistake probability.

Unified underpinning of human mobility in the real world and cyberspace

Acknowledgments This work is supported by National Science Foundation of China (Grant No. 61573064, 61074116 and 11547188), the Youth Scholars Program of Beijing Normal University (grant No. 2014NT38), and the Fundamental Research Funds for the Central Universities Beijing Nova Programme, China. XYY acknowledges the support from the National Natural Science Foundation of China (Grant No. 61304177) and the Fundamental Research Funds of BJTU (Grant No. 2015RC042).

Development of a Digital Tool to Overcome the Challenges of Rural Food SMEs

Peer reviewed

Digital Innovation Through Partnership Between Nature Conservation Organisations and Academia : A Qualitative Impact Assessment

We would like to thank all interviewees for sharing their experiences of working with academics, and the guest editor and three anonymous reviewers for valuable comments on earlier versions of the work. The research in this paper is supported by the RCUK dot.rural Digital economy Research Hub, University of Aberdeen (Grant reference: EP/G066051/1).

Utilising Provenance to Enhance Social Computation

Postprint

Interrogating Capabilities of IoT Devices

This research is supported by the UK Research Councils’ Digital Economy IT as a Utility Network+ (EP/K003569/1) and the dot.rural Digital Economy Hub (EP/G066051/1).

Monitoring compliance with E-contracts and norms

Date of Acceptance: 09/07/2015

Mapping species distributions : A comparison of skilled naturalist and lay citizen science recording

Acknowledgements We are grateful to Elaine O’Mahony, Imogen Pearce, Richard Comont, Anthony McCluskey and other BBCT staff for the many hours of BeeWatch species identification and for all people who submitted sightings to BeeWatch, OPAL, BWARS and the various local recording schemes and societies. We thank the NBN for allowing us to download the bumblebee records without strings attached, and the Essex, Greater London, Cumbria and Sussex based recording centres for providing records upon request. Finally, we are indebted to Tom August and two anonymous reviewers for their valuable critique on an earlier version of this work.

QUAL : A Provenance-Aware Quality Model

The research described here is supported by the award made by the RCUK Digital Economy program to the dot.rural Digital Economy Hub; award reference: EP/G066051/1.

SC-PROV: A Provenance Vocabulary for Social Computation

The research described here is supported by the award made by the RCUK Digital Economy programme to the dot.rural Digital Economy Hub; award reference: EP/G066051/1.

Automated data analysis to rapidly derive and communicate ecological insights from satellite-tag data : A case study of reintroduced red kites

Acknowledgements We thank Andrew Spink (Noldus Information Technology) and the Blogging Birds team members Peter Kindness and Abdul Adeniyi for their valuable contributions to this paper. John Fryxell, Chris Thaxter and Arjun Amar provided valuable comments on an earlier version. The study was part of the Digital Conservation project of dot.rural, the University of Aberdeen’s Digital Economy Research Hub, funded by RCUK (grant reference EP/G066051/1).

The Transport Disruption Ontology

Postprint

Comment on “Effects of Arsenite during Fetal Development on Energy Metabolism and Susceptibility to Diet-Induced Fatty Liver Diseases in Male Mice” and “Mechanisms Underlying Latent Disease Risk Associated with Early-Life Arsenic Exposure: Current Trends and Scientific Gaps”

Peer reviewed