Museos, redes sociales y tecnología 2.0

Índice: - Sobre museos, redes sociales y tecnología 2.0 (Alex Ibáñez Etxeberria). - Sitios web y museos: nuevas aplicaciones para el aprendizaje informal (Mikel Asensio, Elena Asenjo y Alex Ibáñez Etxeberria). - From headphones to microphones: mobile social media in the museum as distributed network (Nancy Proctor). - Mobile learning y patrimionio: aprendiendo historia con mi teléfono, mi GPS y mi PDA (Alex Ibáñez Etxeberria, Mikel Asensio y José Miguel Correa). - Digital asset management strategies for multi-platform content delivery (Titus Bicknell). - Redes sociales y museos participativos: la irrupción de las tecnologías 2.0 en la sociedad y su aplicación en los museos a través del caso de Arazi (Juan José Aranburu).

Analytical efficiency evaluation of a network mobility management protocol for Intelligent Transportation Systems

One of the major concerns in an Intelligent Transportation System (ITS) scenario, such as that which may be found on a long-distance train service, is the provision of efficient communication services, satisfying users' expectations, and fulfilling even highly demanding application requirements, such as safety-oriented services. In an ITS scenario, it is common to have a significant amount of onboard devices that comprise a cluster of nodes (a mobile network) that demand connectivity to the outside networks. This demand has to be satisfied without service disruption. Consequently, the mobility of the mobile network has to be managed. Due to the nature of mobile networks, efficient and lightweight protocols are desired in the ITS context to ensure adequate service performance. However, the security is also a key factor in this scenario. Since the management of the mobility is essential for providing communications, the protocol for managing this mobility has to be protected. Furthermore, there are safety-oriented services in this scenario, so user application data should also be protected. Nevertheless, providing security is expensive in terms of efficiency. Based on this considerations, we have developed a solution for managing the network mobility for ITS scenarios: the NeMHIP protocol. This approach provides a secure management of network mobility in an efficient manner. In this article, we present this protocol and the strategy developed to maintain its security and efficiency in satisfactory levels. We also present the developed analytical models to analyze quantitatively the efficiency of the protocol. More specifically, we have developed models for assessing it in terms of signaling cost, which demonstrates that NeMHIP generates up to 73.47% less signaling compared to other relevant approaches. Therefore, the results obtained demonstrate that NeMHIP is the most efficient and secure solution for providing communications in mobile network scenarios such as in an ITS context.

Altruism in the (Social) Network

This paper explores the role of social integration on altruistic behavior. To this aim, we develop a two-stage experimental protocol based on the classic Dictator Game. In the first stage, we ask a group of 77 undergraduate students in Economics to elicit their social network; in the second stage, each of them has to unilaterally decide over the division of a fixed amount of money to be shared with another anonymous member in the group. Our experimental design allows to control for other variables known to be relevant for altruistic behavior: framing and friendship/acquaintance relations. Consistently with previous research, we find that subjects favor their friends and that framing enhances altruistic behavior. Once we control for these effects, social integration (measured by betweenness, a standard centrality measure in network theory) has a positive effect on giving: the larger social isolation within the group, the more likely it is the emergence of selfish behavior. These results suggest that information on the network structure in which subjects are embedded is crucial to account for their behavior.

Influence of Training Set Selection in Artificial Neural Network-Based Propagation Path Loss Predictions

This paper analyzes the use of artificial neural networks (ANNs) for predicting the received power/path loss in both outdoor and indoor links. The approach followed has been a combined use of ANNs and ray-tracing, the latter allowing the identification and parameterization of the so-called dominant path. A complete description of the process for creating and training an ANN-based model is presented with special emphasis on the training process. More specifically, we will be discussing various techniques to arrive at valid predictions focusing on an optimum selection of the training set. A quantitative analysis based on results from two narrowband measurement campaigns, one outdoors and the other indoors, is also presented.

Enhanced Operation of Electricity Distribution Grids Through Smart Metering PLC Network Monitoring, Analysis and Grid Conditioning

Low Voltage (LV) electricity distribution grid operations can be improved through a combination of new smart metering systems' capabilities based on real time Power Line Communications (PLC) and LV grid topology mapping. This paper presents two novel contributions. The first one is a new methodology developed for smart metering PLC network monitoring and analysis. It can be used to obtain relevant information from the grid, thus adding value to existing smart metering deployments and facilitating utility operational activities. A second contribution describes grid conditioning used to obtain LV feeder and phase identification of all connected smart electric meters. Real time availability of such information may help utilities with grid planning, fault location and a more accurate point of supply management.

Valuing Expansions of the Electricity Transmission Network under Uncertainty: The Binodal Case

Transmission investments are currently needed to meet an increasing electricity demand, to address security of supply concerns, and to reach carbon-emissions targets. A key issue when assessing the benefits from an expanded grid concerns the valuation of the uncertain cash flows that result from the expansion. We propose a valuation model that accommodates both physical and economic uncertainties following the Real Options approach. It combines optimization techniques with Monte Carlo simulation. We illustrate the use of our model in a simplified, two-node grid and assess the decision whether to invest or not in a particular upgrade. The generation mix includes coal-and natural gas-fired stations that operate under carbon constraints. The underlying parameters are estimated from observed market data.

NEW METHODOLOGY FOR FEEDER RECONFIGURATION IN DISTRIBUTION NETWORKS WITH DISTRIBUTED ENERGY RESOURCES

This doctoral Thesis defines and develops a new methodology for feeder reconfiguration in distribution networks with Distributed Energy Resources (DER). The proposed methodology is based on metaheuristic Ant Colony Optimization (ACO) algorithms. The methodology is called Item Oriented Ant System (IOAS) and the doctoral Thesis also defines three variations of the original methodology, Item Oriented Ant Colony System (IOACS), Item Oriented Max-min Ant System (IOMMAS) y Item Oriented Max-min Ant Colony System (IOACS). All methodologies pursue a twofold objective, to minimize the power losses and maximize DER penetration in distribution networks. The aim of the variations is to find the algorithm that adapts better to the present optimization problem, solving it most efficiently. The main feature of the methodology lies in the fact that the heuristic information and the exploitation information (pheromone) are attached to the item not to the path. Besides, the doctoral Thesis proposes to use feeder reconfiguration in order to increase the distribution network capacity of accepting a major degree of DER. The proposed methodology and its three variations have been tested and verified in two distribution networks well documented in the existing bibliography. These networks have been modeled and used to test all proposed methodologies for different scenarios with various DER penetration degrees.

Integrated treatment of first episode psychosis with online training (e-learning): study protocol for a randomised controlled trial

Background: The integrated treatment of first episode psychosis has been shown to improve functionality and negative symptoms in previous studies. In this paper, we describe a study of integrated treatment (individual psychoeducation complementary to pharmacotherapy) versus treatment as usual, comparing results at baseline with those at 6-month re-assessment (at the end of the study) for these patients, and online training of professionals to provide this complementary treatment, with the following objectives: 1) to compare the efficacy of individual psychoeducation as add-on treatment versus treatment as usual in improving psychotic and mood symptoms; 2) to compare adherence to medication, functioning, insight, social response, quality of life, and brain-derived neurotrophic factor, between both groups; and 3) to analyse the efficacy of online training of psychotherapists. Methods/design: This is a single-blind randomised clinical trial including patients with first episode psychosis from hospitals across Spain, randomly assigned to either a control group with pharmacotherapy and regular sessions with their psychiatrist (treatment as usual) or an intervention group with integrated care including treatment as usual plus a psychoeducational intervention (14 sessions). Training for professionals involved at each participating centre was provided by the coordinating centre (University Hospital of Alava) through video conferences. Patients are evaluated with an extensive battery of tests assessing clinical and sociodemographic characteristics (Positive and Negative Syndrome Scale, State-Trait Anxiety Inventory, Liebowitz Social Anxiety Scale, Hamilton Rating Scale for Depression, Scale to Assess Unawareness of Mental Disorders, Strauss and Carpenter Prognostic Scale, Global Assessment of Functioning Scale, Morisky Green Adherence Scale, Functioning Assessment Short Test, World Health Organization Quality of Life instrument WHOQOL-BREF (an abbreviated version of the WHOQOL-100), and EuroQoL questionnaire), and brain-derived neurotrophic factor levels are measured in peripheral blood at baseline and at 6 months. The statistical analysis, including bivariate analysis, linear and logistic regression models, will be performed using SPSS. Discussion: This is an innovative study that includes the assessment of an integrated intervention for patients with first episode psychosis provided by professionals who are trained online, potentially making it possible to offer the intervention to more patients.

Landscape Genetics for the Empirical Assessment of Resistance Surfaces: The European Pine Marten (Martes martes) as a Target-Species of a Regional Ecological Network

Coherent ecological networks (EN) composed of core areas linked by ecological corridors are being developed worldwide with the goal of promoting landscape connectivity and biodiversity conservation. However, empirical assessment of the performance of EN designs is critical to evaluate the utility of these networks to mitigate effects of habitat loss and fragmentation. Landscape genetics provides a particularly valuable framework to address the question of functional connectivity by providing a direct means to investigate the effects of landscape structure on gene flow. The goals of this study are (1) to evaluate the landscape features that drive gene flow of an EN target species (European pine marten), and (2) evaluate the optimality of a regional EN design in providing connectivity for this species within the Basque Country (North Spain). Using partial Mantel tests in a reciprocal causal modeling framework we competed 59 alternative models, including isolation by distance and the regional EN. Our analysis indicated that the regional EN was among the most supported resistance models for the pine marten, but was not the best supported model. Gene flow of pine marten in northern Spain is facilitated by natural vegetation, and is resisted by anthropogenic landcover types and roads. Our results suggest that the regional EN design being implemented in the Basque Country will effectively facilitate gene flow of forest dwelling species at regional scale.

Physiological modules for generating discrete and rhythmic movements: action identification by a dynamic recurrent neural network

In this study we employed a dynamic recurrent neural network (DRNN) in a novel fashion to reveal characteristics of control modules underlying the generation of muscle activations when drawing figures with the outstretched arm. We asked healthy human subjects to perform four different figure-eight movements in each of two workspaces (frontal plane and sagittal plane). We then trained a DRNN to predict the movement of the wrist from information in the EMG signals from seven different muscles. We trained different instances of the same network on a single movement direction, on all four movement directions in a single movement plane, or on all eight possible movement patterns and looked at the ability of the DRNN to generalize and predict movements for trials that were not included in the training set. Within a single movement plane, a DRNN trained on one movement direction was not able to predict movements of the hand for trials in the other three directions, but a DRNN trained simultaneously on all four movement directions could generalize across movement directions within the same plane. Similarly, the DRNN was able to reproduce the kinematics of the hand for both movement planes, but only if it was trained on examples performed in each one. As we will discuss, these results indicate that there are important dynamical constraints on the mapping of EMG to hand movement that depend on both the time sequence of the movement and on the anatomical constraints of the musculoskeletal system. In a second step, we injected EMG signals constructed from different synergies derived by the PCA in order to identify the mechanical significance of each of these components. From these results, one can surmise that discrete-rhythmic movements may be constructed from three different fundamental modules, one regulating the co-activation of all muscles over the time span of the movement and two others elliciting patterns of reciprocal activation operating in orthogonal directions.

Strategies for Power Line Communications Smart Metering Network Deployment

Smart Grids are becoming a reality all over the world. Nowadays, the research efforts for the introduction and deployment of these grids are mainly focused on the development of the field of Smart Metering. This emerging application requires the use of technologies to access the significant number of points of supply (PoS) existing in the grid, covering the Low Voltage (LV) segment with the lowest possible costs. Power Line Communications (PLC) have been extensively used in electricity grids for a variety of purposes and, of late, have been the focus of renewed interest. PLC are really well suited for quick and inexpensive pervasive deployments. However, no LV grid is the same in any electricity company (utility), and the particularities of each grid evolution, architecture, circumstances and materials, makes it a challenge to deploy Smart Metering networks with PLC technologies, with the Smart Grid as an ultimate goal. This paper covers the evolution of Smart Metering networks, together with the evolution of PLC technologies until both worlds have converged to project PLC-enabled Smart Metering networks towards Smart Grid. This paper develops guidelines over a set of strategic aspects of PLC Smart Metering network deployment based on the knowledge gathered on real field; and introduces the future challenges of these networks in their evolution towards the Smart Grid.

Efficacy of a cognitive and behavioural psychotherapy applied by primary care psychologists in patients with mixed anxiety-depressive disorder: a research protocol

Background: In contrast with the recommendations of clinical practice guidelines, the most common treatment for anxiety and depressive disorders in primary care is pharmacological. The aim of this study is to assess the efficacy of a cognitive-behavioural psychological intervention, delivered by primary care psychologists in patients with mixed anxiety-depressive disorder compared to usual care. Methods/Design: This is an open-label, multicentre, randomized, and controlled study with two parallel groups. A random sample of 246 patients will be recruited with mild-to-moderate mixed anxiety-depressive disorder, from the target population on the lists of 41 primary care doctors. Patients will be randomly assigned to the intervention group, who will receive standardised cognitive-behavioural therapy delivered by psychologists together with usual care, or to a control group, who will receive usual care alone. The cognitive-behavioural therapy intervention is composed of eight individual 60-minute face-to face sessions conducted in eight consecutive weeks. A follow-up session will be conducted over the telephone, for reinforcement or referral as appropriate, 6 months after the intervention, as required. The primary outcome variable will be the change in scores on the Short Form-36 General Health Survey. We will also measure the change in the frequency and intensity of anxiety symptoms (State-Trait Anxiety Inventory) and depression (Beck Depression Inventory) at baseline, and 3, 6 and 12 months later. Additionally, we will collect information on the use of drugs and health care services. Discussion: The aim of this study is to assess the efficacy of a primary care-based cognitive-behavioural psychological intervention in patients with mixed anxiety-depressive disorder. The international scientific evidence has demonstrated the need for psychologists in primary care. However, given the differences between health policies and health services, it is important to test the effect of these psychological interventions in our geographical setting.

Introducing mobile edge computing capabilities through distributed 5G Cloud Enabled Small Cells

Current trends in broadband mobile networks are addressed towards the placement of different capabilities at the edge of the mobile network in a centralised way. On one hand, the split of the eNB between baseband processing units and remote radio headers makes it possible to process some of the protocols in centralised premises, likely with virtualised resources. On the other hand, mobile edge computing makes use of processing and storage capabilities close to the air interface in order to deploy optimised services with minimum delay. The confluence of both trends is a hot topic in the definition of future 5G networks. The full centralisation of both technologies in cloud data centres imposes stringent requirements to the fronthaul connections in terms of throughput and latency. Therefore, all those cells with limited network access would not be able to offer these types of services. This paper proposes a solution for these cases, based on the placement of processing and storage capabilities close to the remote units, which is especially well suited for the deployment of clusters of small cells. The proposed cloud-enabled small cells include a highly efficient microserver with a limited set of virtualised resources offered to the cluster of small cells. As a result, a light data centre is created and commonly used for deploying centralised eNB and mobile edge computing functionalities. The paper covers the proposed architecture, with special focus on the integration of both aspects, and possible scenarios of application.