Abstract

Abstract
This article analyzes the strategic bilateral bidding behavior in the Spanish electricity wholesale market (OMEL). The collection of data includes information regarding weekly averages of spot prices, the quantity bid in the wholesale market, the quantities purchased in the wholesale market and sold in the open market, and the behavior of conduct parameters for the period from January 2002 to April 2007 for the four largest firms of the Spanish electricity market: Endesa, Iberdrola, Unin Fenosa and Hidrocantabrico. This article employs the New Empirical Industrial Organization approach. The empirical analysis was based on the autoregressive distributed lag approach to cointegration and on the Toda-Yamamoto Granger causality tests to validate the standard version of the theoretical formulation of the standard Cournot model, and its theoretical extension, to encompass the hypothesis of the presence of bid interdependence for electricity quantities sold and bought in the Spanish electricity wholesale market. The results of cointegration and causality analysis reinforce the empirical results of the extended Cournot model with the inclusion of the two main bidding variables that solved the optimization problem of profit maximization for each of the four firms analyzed.

Abstract
Computational media allow the development of very particular relationships with readers. Their nature allows them to register static information but also complex and contingent behaviours that they are capable to operationalise, thus becoming interactive and immersive. These media exist in a dual state between a surface layer and a subface layer. These two are inextricably connected, with the subface often becoming a black box that can only be peered at through surface effusions that both mediate and isolate it. The procedural layer of the subface can be discovered through a process of virtuosic interpretation that allows readers to form a theory of system, breeding empathy with it, and ultimately, transferring some of its processes to their minds. This paper focuses on how virtuosic interpretation is developed, and how from it stems the development of a unique kind of aesthetic experience. It explores how computational media, through anamorphosis and a dialectics of aporia and epiphany, become narrative games. © 2018 Universidade da Beira Interior.All right reserved.

Abstract
In this work, we study reverse complementary genomic word pairs in the human DNA, by comparing both the distance distribution and the frequency of a word to those of its reverse complement. Several measures of dissimilarity between distance distributions are considered, and it is found that the peak dissimilarity works best in this setting. We report the existence of reverse complementary word pairs with very dissimilar distance distributions, as well as word pairs with very similar distance distributions even when both distributions are irregular and contain strong peaks. The association between distribution dissimilarity and frequency discrepancy is also explored, and it is speculated that symmetric pairs combining low and high values of each measure may uncover features of interest. Taken together, our results suggest that some asymmetries in the human genome go far beyond Chargaff's rules. This study uses both the complete human genome and its repeat-masked version.

Abstract
The wireless capsule endoscopy has revolutionized early diagnosis of small bowel diseases. However, a single examination has up to 10 h of video and requires between 30–120 min to read. Computational methods are needed to increase both efficiency and accuracy of the diagnosis. In this paper, an evaluation of deep learning U-Net architecture is presented, to detect and segment red lesions in the small bowel. Its results were compared with those obtained from the literature review. To make the evaluation closer to those used in clinical environments, the U-Net was also evaluated in an annotated sequence by using the Suspected Blood Indicator tool (SBI). Results found that detection and segmentation using U-Net outperformed both the algorithms used in the literature review and the SBI tool. © 2018, Springer International Publishing AG, part of Springer Nature.

Abstract
Wireless Sensor Networks (WSN) are enabler technologies for the implementation of the Internet of Things (IoT) concept. WSNs provide an adequate infrastructure for the last-link communication with smart objects. Nevertheless, the wireless communication medium being inherently unreliable, there is the need to increase its communication reliability. Techniques based on the use of cooperative communication concepts are one of the ways to achieve this target. Within cooperative communication techniques, nodes selected as relays transmit not only their own data, but also cooperate by retransmitting data from other nodes. A fundamental step to improve the communication reliability of WSNs is related to the use of efficient relay selection techniques. This paper proposes a relay selection technique based on multiple criteria to select the smallest number of relay nodes and, at the same time, to ensure an adequate operation of the network. Additionally, two relay updating schemes are also investigated, defining periodic and adaptive updating policies. The simulation results show that both proposed schemes, named Periodic Relay Selection and Adaptive Relay Selection, significantly improve the communication reliability of the network, when compared to other state-of-the-art relay selection schemes.