Nostalgic representation of reality in television fiction: an empirical study based on the analysis of the Spanish television series Cuéntame cómo pasó

The Spanish transition from dictatorship to democracy is often described as an example of negotiation or agreement between the elites (Sánchez Cuenca and Aguilar, 2009: 433). Journalistic and political elites, aware of their important historical role, agreed a consensus on certain issues (democracy, constitution, amnesty) or characters (King Juan Carlos I), in order to ensure the stability of the democratic process (Zugasti, 2007, 2008). Television, which articulates the discourse of the masses, has been one of the basic means used to illustrate the development. Among the highlights of recent major audiovisual content, Cuéntame cómo pasó (2001-present) -a TV-series designed to explain changes with a nostalgic tone in Spanish society since 1968 until today- stands out. By choosing a random sample of episodes for this research we propose to verify the validity of the representation of the political process which contextualizes the series. By analyzing many elements, such as the opinions of the main characters, their personal, political and geographical situations, we try to show the construction of a focal point that sanctifies the official version. We also stress the pacifying and nostalgic tone, which constructs stereotypes and taboos about the process and which characterizes this series as a symbolic culmination of the democratization undertaken by the elites.

Asymmetric hybrid capacitors based on activated carbon and activated carbon fibre–PANI electrodes

Composites consisting of polyaniline (PANI) coatings inside the microporosity of an activated carbon fibre (ACF) were prepared by electrochemical and chemical methods. Electrochemical characterization of both composites points out that the electrodes with polyaniline show a higher capacitance than the pristine porous carbon electrode. These materials have been used to develop an asymmetric capacitor based on activated carbon (AC) as negative electrode and an ACF–PANI composite as positive electrode in H2SO4 solution as electrolyte. The presence of a thin layer of polyaniline inside the porosity of the activated carbon fibres avoids the oxidation of the carbon material and the oxygen evolution reaction is produced at more positive potentials. This capacitor was tested in a maximum cell voltage of 1.6 V and exhibited high energy densities, calculated for the unpackaged active materials, with values of 20 W h kg−1 and power densities of 2.1 kW kg−1 with excellent cycle lifetime (90% during the first 1000 cycles) and high coulombic efficiency.

A new betweenness centrality measure based on an algorithm for ranking the nodes of a network

We propose and discuss a new centrality index for urban street patterns represented as networks in geographical space. This centrality measure, that we call ranking-betweenness centrality, combines the idea behind the random-walk betweenness centrality measure and the idea of ranking the nodes of a network produced by an adapted PageRank algorithm. We initially use a PageRank algorithm in which we are able to transform some information of the network that we want to analyze into numerical values. Numerical values summarizing the information are associated to each of the nodes by means of a data matrix. After running the adapted PageRank algorithm, a ranking of the nodes is obtained, according to their importance in the network. This classification is the starting point for applying an algorithm based on the random-walk betweenness centrality. A detailed example of a real urban street network is discussed in order to understand the process to evaluate the ranking-betweenness centrality proposed, performing some comparisons with other classical centrality measures.

Partial Product Reduction based on Look-Up Tables

In this paper a new technique for partial product reduction based on the use of look-up tables for efficient processing is presented. We describe how to construct counter devices with pre-calculated data and their subsequent integration into the whole operation. The development of reduction trees organizations for this kind of devices uses the inherent integration benefits of computer memories and offers an alternative implementation to classic operation methods. Therefore, in our experiments we compare our implementation model with CMOS technology model in homogeneous terms.

A Computational Architecture Based on RFID Sensors for Traceability in Smart Cities

Information Technology and Communications (ICT) is presented as the main element in order to achieve more efficient and sustainable city resource management, while making sure that the needs of the citizens to improve their quality of life are satisfied. A key element will be the creation of new systems that allow the acquisition of context information, automatically and transparently, in order to provide it to decision support systems. In this paper, we present a novel distributed system for obtaining, representing and providing the flow and movement of people in densely populated geographical areas. In order to accomplish these tasks, we propose the design of a smart sensor network based on RFID communication technologies, reliability patterns and integration techniques. Contrary to other proposals, this system represents a comprehensive solution that permits the acquisition of user information in a transparent and reliable way in a non-controlled and heterogeneous environment. This knowledge will be useful in moving towards the design of smart cities in which decision support on transport strategies, business evaluation or initiatives in the tourism sector will be supported by real relevant information. As a final result, a case study will be presented which will allow the validation of the proposal.

Errors Associated to Keratoconus Grading using Systems based on Corneal Power

Purpose: To analyze and define the possible errors that may be introduced in keratoconus classification when the keratometric corneal power is used in such classification. Materials and methods: Retrospective study including a total of 44 keratoconus eyes. A comprehensive ophthalmologic examination was performed in all cases, which included a corneal analysis with the Pentacam system (Oculus). Classical keratometric corneal power (Pk), Gaussian corneal power (Pc Gauss), True Net Power (TNP) (Gaussian power neglecting the corneal thickness effect), and an adjusted keratometric corneal power (Pkadj) (keratometric power considering a variable keratometric index) were calculated. All cases included in the study were classified according to five different classification systems: Alió-Shabayek, Amsler-Krumeich, Rabinowitz-McDonnell, collaborative longitudinal evaluation of keratoconus (CLEK), and McMahon. Results: When Pk and Pkadj were compared, differences in the type of grading of keratoconus cases was found in 13.6% of eyes when the Alió-Shabayek or the Amsler-Krumeich systems were used. Likewise, grading differences were observed in 22.7% of eyes with the Rabinowitz-McDonnell and McMahon classification systems and in 31.8% of eyes with the CLEK classification system. All reclassified cases using Pkadj were done in a less severe stage, indicating that the use of Pk may lead to the classification of a cornea as keratoconus, being normal. In general, the results obtained using Pkadj, Pc Gauss or the TNP were equivalent. Differences between Pkadj and Pc Gauss were within ± 0.7D. Conclusion: The use of classical keratometric corneal power may lead to incorrect grading of the severity of keratoconus, with a trend to a more severe grading.

Human Behaviour Recognition based on Trajectory Analysis using Neural Networks

Automated human behaviour analysis has been, and still remains, a challenging problem. It has been dealt from different points of views: from primitive actions to human interaction recognition. This paper is focused on trajectory analysis which allows a simple high level understanding of complex human behaviour. It is proposed a novel representation method of trajectory data, called Activity Description Vector (ADV) based on the number of occurrences of a person is in a specific point of the scenario and the local movements that perform in it. The ADV is calculated for each cell of the scenario in which it is spatially sampled obtaining a cue for different clustering methods. The ADV representation has been tested as the input of several classic classifiers and compared to other approaches using CAVIAR dataset sequences obtaining great accuracy in the recognition of the behaviour of people in a Shopping Centre.