Abstract
Major rivers have traditionally been linked with important human settlements throughout history. The growth of cities over recent river deposits makes necessary the use of multidisciplinary approaches to characterize the evolution of drainage networks in urbanized areas. Since under-consolidated fluvial sediments are especially sensitive to compaction, their spatial distribution, thickness, and mechanical behavior must be studied. Here, we report on subsidence in the city of Seville (Southern Spain) between 2003 and 2010, through the analysis of the results obtained with the Multi-Temporal InSAR (MT-InSAR) technique. In addition, the temporal evolution of the subsidence is correlated with the rainfall, the river water column and the piezometric level. Finally, we characterize the geotechnical parameters of the fluvial sediments and calculate the theoretical settlement in the most representative sectors. Deformation maps clearly indicate that the spatial extent of subsidence is controlled by the distribution of under-consolidated fine-grained fluvial sediments at heights comprised in the range of river level variation. This is clearly evident at the western margin of the river and the surroundings of its tributaries, and differs from rainfall results as consequence of the anthropic regulation of the river. On the other hand, this influence is not detected at the eastern margin due to the shallow presence of coarse-grain consolidated sediments of different terrace levels. The derived results prove valuable for implementing urban planning strategies, and the InSAR technique can therefore be considered as a complementary tool to help unravel the subsidence tendency of cities located over under-consolidated fluvial deposits. Copyright (c) 2017 John Wiley & Sons, Ltd.

Abstract

Abstract
Medical data is particularly interesting as a subject for relational data mining due to the complex interactions which exist between different entities. Furthermore, the ambiguity of medical imaging causes interpretation to be complex and error-prone, and thus particularly amenable to improvement through automated decision support. Probabilistic Inductive Logic Programming (PILP) is a particularly well-suited tool for this task, since it makes it possible to combine the relational nature of this field with the ambiguity inherent in human interpretation of medical imaging. This work presents a PILP setting for breast cancer data, where several clinical and demographic variables were collected retrospectively, and new probabilistic variables and rules reflecting domain knowledge were introduced. A PILP predictive model was built automatically from this data and experiments show that it can not only match the predictions of a team of experts in the area, but also consistently reduce the error rate of malignancy prediction, when compared to other non-relational techniques. © Springer International Publishing AG, part of Springer Nature 2018.

Abstract
With the collapse of communism, some former communist States of Eastern Europe managed to muddle through their way to a market economy and entered the European Union. This brought about the acceleration of Foreign Direct Investment (FDI) among the European economies and accelerated the globalization process. Although there is plenty of research on FDI and trade among countries, the aim of this chapter is to analyze how trade between Portugal and the Czech Republic have evolved over form 2000 until 2015. The chapter seeks to complement previous studies on FDI and trade as Portugal and the Czech Republic are part of the European Union, but have had different historical, cultural, and economic paths. The main conclusion of the chapter is that trade between both countries has grown significantly. The main reason affecting trade between both countries is the economic unrest Portugal has been through since 2008. © 2017 by IGI Global.

Abstract
This paper describes the calibration of an underwater navigation system in enclosed scenarios. The work was performed in the context of the VAMOS project addressing the development of robotic solutions for flooded open pit mine exploration. An algorithm for calibration of extrinsic parameters for DVL and USBL systems is presented. Field experiments were performed with the ROAZ autonomous surface vehicle equipped with the underwater sensors and using precision IMU/GNSS fused data as groundtruth. The tests were performed in Douro River and in the Bejanca open pit mine, one of the VAMOS test sites, both in northern Portugal. The procedure was validated in the operational scenarios and results are presented showing the error correction and navigation quality improvement.

Abstract
Studies relating ageing and countries' economic performance address mostly developed economies. However, extant studies demonstrate that less developed countries (LDC) and emerging economies (EE) are reaching the transition process faster than those from developed regions, which renders the speed of ageing, besides ageing, a critical variable to explore in this context. Comparing system dynamic panel data estimations for 40 LDC, 19 EE and 28 developed countries (DC), between 1990 and 2013, we uncovered that ageing is detrimental to countries' economic growth, with noticeable nuances depending on countries' development level. The current level of ageing significantly and negatively impacts on DC's growth but not on that of LDC or EE. For these latter groups, the most relevant issue is the speed of ageing. The current annual growth of old age dependency ratio significantly diminishes EE's growth prospects whereas the lagged annual growth of the ageing index and the old age dependency ratio significantly curtails LDC's growth. Such results emphasize the need for urgent public policies that might mitigate the imbalance in LDCs' age structure before the speed of ageing leads LDCs to become even much poorer.