Abstract
Empty repositions are a major problem for car rental companies that deal with special types of vehicles whose number of units is small. In order to meet reservation requirements concerning time and location, companies are forced to transfer cars between rental stations, bearing significant costs and increasing the environmental impact of their activity due to the fuel consumption and CO2 emission. In this paper, this problem is tackled under a vehicle-reservation assignment framework as a network-flow model in which the profit is maximized. The reservations are allocated considering the initial and future availability of each car, interdependencies between rental groups, and different reservation priorities. To solve this model, a relax-and-fix heuristic procedure is proposed, including a constraint based on local branching that enables and controls modifications between iterations. Using real instances, the value of this approach is established and an improvement of 33% was achieved when compared to the company's current practices.

Abstract
The onset of the global crisis has emphasised the persistence of substantial differences in development and social progress within the euro area. The specific case of countries located in the southern periphery region has come to the centre stage, due to the harsh economic conditions that all these countries have experienced in the recent past. In the aftermath of the American subprime creditbubble, these countries’ high indebtedness raised doubts as to their ability to sustain publicfinances, with the financial crisis developing and gaining momentum due to the fragilities presentedin the economy. To varying degrees of severity, all of these economies have since been forced to introduce strong fiscal tightening pogrammes in order to achieve fiscal consolidation, which have translated into recession and rising unemployment. This book undertakes a comprehensive analysis of the causes of the crisis in southern European countries, showing that the ‘Achilles heel’ of these economies is rooted in the dismal evolution of productivity and in a specialisation pattern excessively based on the so-called ‘traditional’, low and low-medium tech industries, which yield low margins, declining export shares and, ultimately, withering international competitiveness. Such evidence suggests that the southern European periphery industrial growth model has reached itslimits, demanding a multidimensional policy approach capable of overcoming the magnitude and complexity of the present crisis. Without denying the need to adjust public and private balance sheets, it is argued that finding a sustainable path out of the present problems requires addressing the challenges of productivity growth and competitiveness in the long term. © 2014 selection and editorial material, Aurora A.C. Teixeira, Ester G. Silva and Ricardo Paes Mamede; individual chapters, the contributors

Abstract

Abstract
Wearable systems are expected to contribute for improving traditional biopotential signals monitoring devices due to higher freedom and unobtrusiveness provided to the wearer. Textile electrodes present advantages compared with the conventional Ag/AgCl electrodes for the capturing of biopotentials, namely in terms of skin irritation due to the hydrogel and the need of a technician to place the electrodes on the correct positions. Due to the lack of hydrogel, textile electrodes present different electrical contact characteristics. The skin-electrode impedance is an important feature since it affects the captured signal quality. Although a low impedance is desired, a comfortable wearable system should not require the electrodes to be covered by the hydrogel or be moistened. A forearm sleeve provided with textile electrodes was used to study the electrode-skin impedance and the signal-to-noise ratio (SNR) of surface electromyographic (EMG) signals on a long-term use basis. The sleeve can be adjusted for different levels of tightening to control the pressure applied on the electrodes. The obtained results provide valuable information on the pressure that the textile garments of a sleeve or vest should apply on the recording electrodes, in order to assure a good electrical and mechanical contact between the electrodes and the skin and decrease the noise due to motion. It was observed that the electrode-skin impedance measurement alone is not sufficient to establish a relation with the SNR. The extraction of parameters from an electrical equivalent model of the electrode-skin interface allows to determine a relation with the model parameters and the SNR. The evaluation of these parameters during long-term monitoring will allow assessing the quality of biopotential measurements in textile electrodes. © 2014 IEEE.

Abstract
The ability to have an automated real time detection of user interest during a web session is very appealing and can be very useful for a number of web intelligence applications. Low level interaction events associated with user interest manifestations form the basis of user interest models. However such data sets present a number of challenges from a machine learning perspective, including the level of noise in the data and class imbalance (given that the majority of content will not be of interest to a user). In this paper we evaluate a large number of machine learning techniques aimed at learning from class imbalanced data using two data sets collected from a real user study. We use the AUC, recall, precision and model complexity to compare the relative merits of these techniques and conclude that useful models with AUC above 0.8 can be obtained using a mix of sampling and cost based methods. Ensemble models can provide further accuracy but make deployment more complex.

Abstract
The cis-regulatory effects responsible for cancer development have not been as extensively studied as the perturbations of the protein coding genome in tumorigenesis. To better characterize colorectal cancer (CRC) development we conducted an RNA-sequencing experiment of 103 matched tumour and normal colon mucosa samples from Danish CRC patients, 90 of which were germline-genotyped. By investigating allele-specific expression (ASE) we show that the germline genotypes remain important determinants of allelic gene expression in tumours. Using the changes in ASE in matched pairs of samples we discover 71 genes with excess of somatic cis-regulatory effects in CRC, suggesting a cancer driver role. We correlate genotypes and gene expression to identify expression quantitative trait loci (eQTLs) and find 1,693 and 948 eQTLs in normal samples and tumours, respectively. We estimate that 36% of the tumour eQTLs are exclusive to CRC and show that this specificity is partially driven by increased expression of specific transcription factors and changes in methylation patterns. We show that tumour-specific eQTLs are more enriched for low CRC genome-wide association study (GWAS) P values than shared eQTLs, which suggests that some of the GWAS variants are tumour specific regulatory variants. Importantly, tumour-specific eQTL genes also accumulate more somatic mutations when compared to the shared eQTL genes, raising the possibility that they constitute germline-derived cancer regulatory drivers. Collectively the integration of genome and the transcriptome reveals a substantial number of putative somatic and germline cis-regulatory cancer changes that may have a role in tumorigenesis.