Abstract
The quality of consumer-oriented health information on the Web is usually assessed through the medical certification of websites. These tools are built upon quality indicators but, so far, no standard set of indicators has been defined. The objective of the present study is to explore the popularity of specific document features and their influence on the quality of health web documents, using HON code as ground truth. A set of top-ranked health documents retrieved from a major search engine was characterized in a univariate analysis, and then used in a bivariate analysis to seek features that affect documents' quality. The univariate analysis provides insights into the characteristics of the overall population of the health web documents. The bivariate analysis reveals strong relations between documents' quality and a set of features (namely split content, videos, images, advertisements, English language) that are potential quality indicators. We characterized health web documents and identified specific document features that can be used to assess whether the information in such documents is trustworthy. The main contribution of this work is to provide other features as candidate indicators of quality. Non-health professionals can use these indicators in automatic and manual assessments of health content.

Abstract
As Collaborative Filtering becomes increasingly important in both academia and industry recommendation solutions, it also becomes imperative to study the algorithm selection task in this domain. This problem aims at inding automatic solutions which enable the selection of the best algorithms for a new problem, without performing full-ledged training and validation procedures. Existing work in this area includes several approaches using Metalearning, which relate the characteristics of the problem domain with the performance of the algorithms. This study explores an alternative approach to deal with this problem. Since, in essence, the algorithm selection problem is a recommendation problem, we investigate the use of Collaborative Filtering algorithms to select Collaborative Filtering algorithms. The proposed approach integrates subsampling landmarkers, a data characterization approach commonly used in Metalearning, with a Collaborative Filtering methodology, named CF4CF. The predictive performance obtained by CF4CF using benchmark recommendation datasets was similar or superior to that obtained with Metalearning.

Abstract
The advent of small and low-cost Unmanned Aerial Vehicles (UAVs) is paving the way to use swarms of UAVs to perform missions such as aerial video monitoring and infrastructure inspection. Within a swarm, UAVs communicate by means of a Flying Multi-hop Network (FMN), which due to its dynamics induces frequent changes of network topology and quality of the links. Recently, UAVs have also been used to provide Internet access and enhance the capacity of existing networks in Temporary Events. This brings up additional routing challenges not yet addressed, in order to provide always-on and high capacity paths able to meet the Quality of Service expected by the users. This paper presents RedeFINE, a centralized routing solution for FMNs that selects high-capacity paths between UAVs and avoids communications disruptions, by defining in advance the forwarding tables and the instants they shall be updated in the UAVs; this represents a major step forward with respect to traditional routing protocols. The performance evaluation of RedeFINE shows promising results, especially regarding Throughput and Packet Delivery Ratio, when compared with state of the art routing solutions.

Abstract
Immersion is a state of altered consciousness-not the prim suspension of disbelief, but its joyous capsizing. Since approximately 2012, a new ecosystem of immersive virtual reality technologies and experiments has emerged. In this emerging ecosystem, journalism is still a minor component. Nevertheless, media outlets such as The New York Times, BBC or ABC News have been producing virtual reality news stories. This led to the advent of immersive journalism, not only as a media phenomenon, but also as an academic concept. Drawing on some notions and concepts like the definitions of immersive journalism, immersion and presence, as well as some examples of the relation between journalism practices and visual media, we analyse, reflect and provide a general overview about the main concepts, uses, opportunities and limits of immersive journalism. Thus, the main goal of this article is to provide a theoretical and conceptual gateway that serves as a starting point for immersive journalism future academic and industry endeavours.

Abstract
This paper investigates an ac-dc-ac multilevel power converter. The studied configuration is composed of two single-phase ac-dc-ac three-leg modules and series-connected H-bridges in the shared part of system. Because the proposed converter has shared legs between the input and output, it is employed in applications with same input and output frequency. Uninterrupted power supply and unified power quality conditioner are application examples for this converter. Such multilevel topology has lower dc-link voltage rating, which, consequently, presents low switch blocking voltages when compared to conventional topologies. System model, a space-vector pulsewidth modulation (PWM) strategy to symmetrical and asymmetrical dc-link voltages, and an overall control strategy to adjust the system variables are presented. A power flux analysis shows the operation zone in which the individual dc-link voltage balancing is possible. PWM and control strategies are developed to reduce the semiconductor total losses, harmonic distortion, and switching stress. Two ac-dc-ac multilevel conventional structures are used for comparison. Simulation and experimental results demonstrate the feasibility of the studied converter.

Abstract
A fiber sensor based on a Fabry-Perot cavity is reported for measuring mixtures of water and glycerin. The sensor is fabricated by producing an air bubble near the end face of a multimode fiber section, and reshaping the tip in order to produce a thin silica diaphragm. It is observed that there is dependence between diaphragm dimensions and the structure sensitivity. The sensor with a 20 mu m thick diaphragm presents a sensitivity of 7.81 pm/wt.% regarding the variation of water mass fraction in glycerin. With this sensing head, an experimental resolution of 2.5 wt.% is estimated. By converting the mass fraction into refractive index variations, a maximum sensitivity of 5.49 nm/RIU is obtained. Moreover, given the low-temperature sensitivity (1.6 pm/degrees C), the proposed cavity should be adequate to perform temperature independent measurements. The purity degree of glycerin is one of the most important parameters to be determined in applications such as in pharmaceutical or cosmetic area. The proposed sensor can be an alternative to the previously developed ones.