Abstract
This study contributes to identification of psychosocial risk factors in non-teaching staff. The study is exploratory and descriptive. It consists in descriptive statistics of responses to a questionnaire for identification of psychosocial risk factors (translated and adapted from F-PSICO), as well as in content analysis of responses to semi-structured interviews. The results show that the non-teaching staff needs to hide emotions and feelings and also that some of the situations that affect psychologically relate to relationships with co-workers. It is stated that «there is no team spirit» and that these relations are not satisfactory. With the day-to-day workload, these workers are forced to interrupt work and perform various tasks at the same time, dealing with a day-by-day of «breakneck pace», «intense» and «very full» journey. Psychological demands, time autonomy, workload, relationships and social support are psychosocial risk factors that play an important role in the performance of these workers. Finally, some measures to control these risks were recommended. © 2015 Taylor & Francis Group, London.

Abstract
In the nowadays highly unstable manufacturing market, companies are faced, on a daily basis, with important strategic decisions, such as "does the company has the necessary capacity to accept a high volume order?" or "what measures need to be implemented if the product demand increases x% a year?". Decision-makers, i.e. company's managers, rely on their experience and insights supported by classical tools to take such decisions. Classical mathematical solvers or agent-based systems are typical architectural solutions to implement strategic planning tools to support decision-makers on this important task Within the ARUM (Adaptive Production Management) project, a hybrid strategic planning tool was specified and developed, combining the optimization features of classical solvers with the flexibility and agility of agent systems. This paper briefly presents such architecture and focuses on the generation of the "what-if game" mechanism to support the generation of more intelligent and dynamic planning solutions.

Abstract
In the recent trend of data-intensive science, data publication is essential and institutions have to promote it with the researchers. For the past decade, institutional repositories have been widely established for publications, and the motivations for deposit are well established. The situation is quite different for data, as we argue on the basis of a 5-year experience with research data management at the University of Porto. We address research data management from a disciplined yet flexible point of view, focusing on domain-specific metadata models embedded in intuitive tools, to make it easier for researchers to publish their datasets. We use preliminary data from a recent experiment in data publishing to identify motivators and deterrents for data publishing.

Abstract
An extension of the well-known Particle Swarm Optimization (PSO) to multi-robot applications has been recently proposed and denoted as Robotic Darwinian PSO (RDPSO), benefited from the dynamical partitioning of the whole population of robots. Although such strategy allows decreasing the amount of required information exchange among robots, a further analysis on the communication complexity of the RDPSO needs to be carried out so as to evaluate the scalability of the algorithm. Moreover, a further study on the most adequate multi-hop routing protocol should be conducted. Therefore, this paper starts by analyzing the architecture and characteristics of the RDPSO communication system, thus describing the dynamics of the communication data packet structure shared between teammates. Such procedure will be the first step to achieving a more scalable implementation of RDPSO by optimizing the communication procedure between robots. Second, an ad hoc on-demand distance vector reactive routing protocol is extended based on the RDPSO concepts, so as to reduce the communication overhead within swarms of robots. Experimental results with teams of 15 real robots and 60 simulated robots show that the proposed methodology significantly reduces the communication overhead, thus improving the scalability and applicability of the RDPSO algorithm.

Abstract
In this paper, we present the tools of the MediaViz project, a work-in progress platform that aims to provide researchers, academics and professionals from the media field with a set of analytical and exploratory resources to answer high level and complex questions about the online media panorama, in an eficient, visual and interactive way. Our approach consists of aggregating and processing news data from multiple online sources, and provide programatic access to it through an Application Programming Interface (API). The visualization tools leverage the data provided by the API, allowing users to interact, explore and interrogate that information. Through the use of data visualization techniques, we aim to characterize the publication patterns of multiple online news sources by analyzing and comparing distinct dimensions. Dimensions of interest include the frequency and flow of publications and social shares throughout time, and the geographic coverage of online news outlets. We present some of the developed visualization tools and describe how they can offer meaningful insights by providing a bird's-eye view of distinct characteristics of the online mediascape. © 2015 ACM.

Abstract
The smart grid concept defines a new way to architect the power energy system. This evolution is dictated, at large extent, by the need to integrate distributed generation systems,. mainly based on renewable energy sources, consider electrical vehicles and enhance the power system infrastructure in degraded conditions. This change of paradigm implies a modification of the way the networked nodes operate and interconnect, including new control algorithms by introducing decision and action capabilities to controllable devices. This paper introduces an innovative way of modelling each node of the grid based on the holonic paradigm, with the objective of decreasing the number of different control algorithms set up on the grid. A single holon, able to model the behavior of any node (producing, consuming and storing energy), is defined and applied on a low voltage case study.