Abstract
The possibility to preserve perspectives of reality with spontaneous creations allowed by the web tools that now empower common users with content production skills highlights the numerous opportunities for the present and future of cultural identity maintenance. Our research approaches digital storytelling during intergenerational dynamics as a stage for a participatory contribution to the maintenance of cultural identity. With an ethnographic approach and with partnerships with existing senior movements, we seek to (a) understand the storytelling processes during intergenerational dynamics, (b) develop a framework for the participative creation of narratives in the context of intergenerational cultural identity maintenance, (c) support the participatory maintenance of cultural identity through a set of workshops for intergenerational storytelling, (d) understand the challenges and opportunities promoted by digital affinity spaces for the maintenance of cultural identity. Our contribution proposes to develop the understanding of the role that interactive narratives can have in the context of cultural identity maintenance, by developing new usage strategies to enhance cultural mediation through social and ubiquitous storytelling strategies.

Abstract
In the last decade, several HRV based novel methodologies for describing and assessing heart rate dynamics have been proposed in the literature with the aim of risk assessment. Such methodologies attempt to describe the non-linear and complex characteristics of HRV, and hereby the focus is in two of these characteristics, namely long memory and heteroscedasticity with variance clustering. The ARFIMA-GARCH modeling considered here allows the quantification of long range correlations and time-varying volatility. ARFIMA-GARCH HRV analysis is integrated with multimodal brain monitoring in several acute cerebral phenomena such as intracranial hypertension, decompressive craniectomy and brain death. The results indicate that ARFIMA-GARCH modeling appears to reflect changes in Heart Rate Variability (HRV) dynamics related both with the Acute Brain Injury (ABI) and the medical treatments effects. © 2017, Springer International Publishing AG.

Abstract
Propagation of underwater electromagnetic signals for real-time transmission and reception of data gathered during a survey mission between an Autonomous Underwater Vehicle (AUV) and underwater sensor nodes or a docking station, continues to generate a lot of interest worldwide. To this end, underwater antennas will play a significant role in ensuring good data rates and propagation distances for various underwater applications. In this paper, the performance of two dipole antennas with different parasitic elements is assessed through simulation for usage in fresh water and operating in the High Frequency (HF) band. The antennas were designed in FEKO, an electromagnetic simulation software and their performance is assessed in terms of bandwidth, directivity and antenna-to-antenna distance. The results obtained show that these antennas exhibit wide bandwidth, which is important to achieve high data rates. Experimental results of the reflection coefficient of the fabricated antenna measured in fresh water are given that agree well with the simulation results.

Abstract
In the use of ontologies as knowledge information systems (KOS) for purposes of representation, organization and information retrieval, one of the biggest challenges is the ontology development process, which is complex and requires specific technical knowledge of the developers. In the recent years, several methodologies have been developed to support the ontologies building, which have steps well established, but not always well detailed for developers, causing problems in the ontologies development. This paper describes a methodology for the ontologies development, called OntoForInfoScience, which has a differential the detail of the activities of the ontology development cycle, explaining more clearly technical terms, logical and philosophical issues involved in the construction of ontologies. As current practical results of OntoForInfoScience, we presented part of the content of two ontologies developed with such methodology: (i) Hemonto: a biomedical ontology on the human blood components used for hematology and hemotherapy; (ii) Ontolegis: a legal domain ontology that represents the knowledge related to Brazilian legislative information on medical law. It is concluded that the OntoForInfoScience was very useful for the construction of formal ontological representations in both domains modeled and their details allowed to help the developers in logical and philosophical questions of the process of development and in the understanding of technical concepts of ontologies.

Abstract
This paper proposes the use of ontologies to enable information and knowledge exchange, to test different electricity market models and to allow players from different systems to interact in common market environments. Multi-agent based software is particularly well fitted to analyse dynamic and adaptive systems with complex interactions among its constituents, such as the complex and dynamic electricity markets. The main drivers are the markets' restructuring and evolution into regional and continental scales, along with the constant changes brought by the increasing necessity for an adequate integration of renewable energy sources. An ontology to represent the concepts related to the Nord Pool Elspot market is proposed. It is validated through a case study considering the simulation of Elspot market. Results show that heterogeneous agents are able to effectively participate in the simulation by using the proposed ontologies to support their communications with the Nord Pool market operator.

Abstract
This study aims at characterizing the spatial and temporal dynamics of spatio-temporal data sets, characterized by high resolution in the temporal dimension which are becoming the norm rather than the exception in many application areas, namely environmental modelling. In particular, air pollution data, such as NO2 concentration levels, often incorporate also multiple recurring patterns in time imposed by social habits, anthropogenic activities and meteorological conditions. A two-stage modelling approach is proposed which combined with a block bootstrap procedure correctly assesses uncertainty in parameters estimates and produces reliable confidence regions for the space-time phenomenon under study. The methodology provides a model that is satisfactory in terms of goodness of fit, interpretability, parsimony, prediction and forecasting capability and computational costs. The proposed framework is potentially useful for scenario drawing in many areas, including assessment of environmental impact and environmental policies, and in a myriad applications to other research fields.