Who has a repeat abortion? Identifying women at risk of repeated terminations of pregnancy : analysis of routinely collected health care data

Peer reviewed

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).

Basement structure of the Hontomín CO2 storage site (Spain) determined by integration of microgravity and 3D seismic data

We dedicate this paper to the memory of Prof. Andres Perez Estaún, who was a great and committed scientist, wonderful colleague and even better friend. The datasets in this work have been funded by Fundación Ciudad de la Energía (Spanish Government, www.ciuden.es) and by the European Union through the “European Energy Programme 15 for Recovery” and the Compostilla OXYCFB300 project. Dr. Juan Alcalde is currently funded by NERC grant NE/M007251/1. Simon Campbell and Samuel Cheyney are acknowledged for thoughtful comments on gravity inversion

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).

A trait-based approach for predicting species responses to environmental change from sparse data : how well might terrestrial mammals track climate change?

Funded by COST (European Cooperation in Science and Technology) CEH projects. Grant Numbers: NEC05264, NEC05100 Natural Environment Research Council UK. Grant Number: NE/J008001/1 © 2016 The Authors. Global Change Biology Published by John Wiley & Sons Ltd. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

TravelBot: Journey Disruption Alerts Utilising Social Media and Linked Data

Postprint

Use of phosphorous mapping and sea-level change data in assessing coastal activity zones and establishing site chronology : A case study from the Icelandic multi-period site of Vatnsfjörður

This paper forms part of Lukasz Mikolajczyk's PhD dissertation, which is supervised by Karen Milek

Is routine hospital episode data sufficient for identifying individuals with chronic kidney disease? : A comparison study with laboratory data

© The Author(s) 2014. Acknowledgements We thank the Information Services Division, Scotland, who provided the SMR01 data, and NHS Grampian, who provided the biochemistry data. We also thank the University of Aberdeen’s Data Management Team. Funding This work was supported by the Chief Scientists Office for Scotland (grant no. CZH/4/656).

Joint interpretation of magnetotelluric, seismic, and well-log data in Hontomín (Spain)

Acknowledgements. This work is dedicated to the memory of Andrés Pérez-Estaún, brilliant scientist, colleague, and friend. The authors sincerely thank Ian Ferguson and an anonymous reviewer for their useful comments on the manuscript. Xènia Ogaya is currently supported in the Dublin Institute for Advanced Studies by a Science Foundation Ireland grant IRECCSEM (SFI grant 12/IP/1313). Juan Alcalde is funded by NERC grant NE/M007251/1, on interpretational uncertainty. Juanjo Ledo, Pilar Queralt and Alex Marcuello thank Ministerio de Economía y Competitividad and EU Feder Funds through grant CGL2014- 54118-C2-1-R. Funding for this Project has been partially provided by the Spanish Ministry of Industry, Tourism and Trade, through the CIUDEN-CSIC-Inst. Jaume Almera agreement (ALM-09-027: Characterization, Development and Validation of Seismic Techniques applied to CO2 Geological Storage Sites), the CIUDEN-Fundació Bosch i Gimpera agreement (ALM-09-009 Development and Adaptation of Electromagnetic techniques: Characterisation of Storage Sites) and the project PIERCO2 (Progress In Electromagnetic Research for CO2 geological reservoirs CGL2009-07604). The CIUDEN project is co-financed by the European Union through the Technological Development Plant of Compostilla OXYCFB300 Project (European Energy Programme for Recovery).

Vertical crustal motion along the Mediterranean and Black Sea coast derived from ocean altimetry and tide gauge data

Tide gauge (TG) data along the northern Mediterranean and Black Sea coasts are compared to the sea-surface height (SSH) anomaly obtained from ocean altimetry (TOPEX/Poseidon and ERS-1/2) for a period of nine years (1993–2001). The TG measures the SSH relative to the ground whereas the altimetry does so with respect to the geocentric reference frame; therefore their difference would be in principle a vertical ground motion of the TG sites, though there are different error sources for this estimate as is discussed in the paper. In this study we estimate such vertical ground motion, for each TG site, from the slope of the SSH time series of the (non-seasonal) difference between the TG record and the altimetry measurement at a point closest to the TG. Where possible, these estimates are further compared with those derived from nearby continuous Global Positioning System (GPS) data series. These results on vertical ground motion along the Mediterranean and Black Sea coasts provide useful source data for studying, contrasting, and constraining tectonic models of the region. For example, in the eastern coast of the Adriatic Sea and in the western coast of Greece, a general subsidence is observed which may be related to the Adriatic lithosphere subducting beneath the Eurasian plate along the Dinarides fault.

Adsorption of pure fluids in activated carbon with a modified lattice gas model

In this article we study the effects of adsorbed phase compression, lattice structure, and pore size distribution on the analysis of adsorption in microporous activated carbon. The lattice gas approach of Ono-Kondo is modified to account for the above effects. Data of nitrogen adsorption at 77 K onto a number of activated carbon samples are analyzed to investigate the pore filling pressure versus pore width, the packing effect, and the compression of the adsorbed phase. It is found that the PSDs obtained from this analysis are comparable to those obtained by the DFT method. The discrete nature of the PSDs derived from the modified lattice gas theory is due to the inherent assumption of discrete layers of molecules. Nevertheless, it does provide interesting information on the evolution of micropores during the activation process.

Neural networks for time-varying data

This paper reviews some basic issues and methods involved in using neural networks to respond in a desired fashion to a temporally-varying environment. Some popular network models and training methods are introduced. A speech recognition example is then used to illustrate the central difficulty of temporal data processing: learning to notice and remember relevant contextual information. Feedforward network methods are applicable to cases where this problem is not severe. The application of these methods are explained and applications are discussed in the areas of pure mathematics, chemical and physical systems, and economic systems. A more powerful but less practical algorithm for temporal problems, the moving targets algorithm, is sketched and discussed. For completeness, a few remarks are made on reinforcement learning.

Seeking Relationships in Big Data: A Bayesian Perspective

The real purpose of collecting big data is to identify causality in the hope that this will facilitate credible predictivity . But the search for causality can trap one into infinite regress, and thus one takes refuge in seeking associations between variables in data sets. Regrettably, the mere knowledge of associations does not enable predictivity. Associations need to be embedded within the framework of probability calculus to make coherent predictions. This is so because associations are a feature of probability models, and hence they do not exist outside the framework of a model. Measures of association, like correlation, regression, and mutual information merely refute a preconceived model. Estimated measures of associations do not lead to a probability model; a model is the product of pure thought. This paper discusses these and other fundamentals that are germane to seeking associations in particular, and machine learning in general. ACM Computing Classification System (1998): H.1.2, H.2.4., G.3.

Mean current and temperature data from the Gulf of Cádiz

During "Meteor" cruise 23 in spring 1971 intensive investigations of the Mediterranean outflow in the Gulf of Cidiz were carried out. In order to give a budget of the inflow and outflow numerous CTD-stations were taken. The observations also included six moored current meter arrays deployed in the known outflow channels. The considerations given here are based mainly on three hydrographic sections, current meter records averaged over one month, and geological observations from the bed forms beneath the Mediterranean undercurrent. The results show that the outflow essentially is determined by the bathymetry of the area. At least four separate outflow channels could be confirmed. The volumentric transport rates of three of them were calculated. These channels are the northerly near shelf branch (0.40 * 10**6 m**3 * sec**-1), the main branch (1.39 * 10**6 m**3 * sec**-1) in southwesterly direction, and an intermediate branch (0.24 * 10**6 m**3 * sec**-1) found between both. In a static box model the progressive mixing of 0.95 * 10**6 m**3 * sec**-1 pure Mediterranean Water with 1.97 * 10**6 m**3 * sec**-1 North Atlantic Central Water is demonstrated.