Abstract
Wearable Health Devices (WHDs) are increasingly helping people to better monitor their health status both at an activity/fitness level for self-health tracking and at a medical level providing more data to clinicians with a potential for earlier diagnostic and guidance of treatment. The technology revolution in the miniaturization of electronic devices is enabling to design more reliable and adaptable wearables, contributing for a world-wide change in the health monitoring approach. In this paper we review important aspects in the WHDs area, listing the state-of-the-art of wearable vital signs sensing technologies plus their system architectures and specifications. A focus on vital signs acquired by WHDs is made: first a discussion about the most important vital signs for health assessment using WHDs is presented and then for each vital sign a description is made concerning its origin and effect on heath, monitoring needs, acquisition methods and WHDs and recent scientific developments on the area (electrocardiogram, heart rate, blood pressure, respiration rate, blood oxygen saturation, blood glucose, skin perspiration, capnography, body temperature, motion evaluation, cardiac implantable devices and ambient parameters). A general WHDs system architecture is presented based on the state-of-the-art. After a global review of WHDs, we zoom in into cardiovascular WHDs, analysing commercial devices and their applicability versus quality, extending this subject to smart t-shirts for medical purposes. Furthermore we present a resumed evolution of these devices based on the prototypes developed along the years. Finally we discuss likely market trends and future challenges for the emerging WHDs area.

Abstract
Topology formation in wireless sensor networks is usually done assuming just either the geographical proximity between nodes or the signal strength of communication. In this paper, a heuristic called DbCTF is proposed to guide the formation of cluster-tree networks, which also considers data clustering techniques. The use of DbCTF allows the setup of a data-based topology in the cluster-tree, and also the prioritisation of monitored regions in which relevant events may be occurring. The performance of DbCTF has been compared with a state-of-the-art algorithm, for the specific case of a classical WSN laboratory experiment. The simulation assessment revealed that the cluster-tree formed by DbCTF was able to reduce by more than 20% the average communication delay of message streams conveying critical data, and was also able to increase by more than 35% the average lifetime of the network.

Abstract
The JavaScript ecosystem is evolving dramatically. Nowadays, the language is no longer confined to the boundaries of the browser and is now running in both sides of the Web stack. At the same time, JavaScript it’s starting to play also an important role in desktop and mobile applications development. These facts are leading companies to massively adopt JavaScript in their Web/mobile projects and schools to augment the language spectrum among their courses curricula. Several platforms appeared in recent years aiming to foster the learning of the JavaScript language. Those platforms are mainly characterized with sophisticated UI which allow users to learn JavaScript in a playful and interactive way. Despite its apparent success, these environments are not suitable to be integrated in existent educational platforms. Beyond these interoperability issues, most of these platforms are rigid not allowing teachers to contribute with new exercises, organize the existent exercises in more suitable and modular activities to be deployed in their courses, neither keep track of student’s progress. This paper presents LearnJS as a simple and flexible platform to teach and learn JavaScript. In this platform, instructors can contribute with new exercises and combine them with expositive resources (e.g videos) to define specific course activities. These activities can be gamified with the injection of dynamic attributes to reward the most successful attempts. Finally, instructors can deploy activities in their educational platforms. On the other hand, learners can solve exercises and receive immediate feedback on their solutions through static and dynamic analyzers. Since we are in the early stages of implementation, the paper focus on the presentation of the LearnJS architecture, their main components and their data and integration models. Nevertheless, a prototype of the platform is available in a GitHub repository. © Ricardo Queirós

Abstract

Abstract
This paper results from the research conducted by the first author during the preparation of his MSc Thesis. This research aimed at investigating the impact on the market prices of the Iberian Electricity Market, MIBEL, due to increases of the feed-in generation, as such an increase is expected to occur in the next few years, namely for PV systems. This research was conducted using real market data publicly available in the web site of the Iberian Market Operator for 2016. To estimate this impact, for each trading hour of 2016 we considered new segments at price 0,0 (sic)/MWh to translate the priority given to this type of generation. These segments representing the new feed-in generation were then used together with the selling bids submitted by market agents to build the new aggregated selling curve. The new market price was finally obtained as the intersection of the new selling curve with the original buying curve, that was assumed unchanged. The global result indicates that if the feed-in generation increases by 25% regarding the values of 2016, then the average annual market price decreases by 6,57 % regarding the original value of 39,42 (sic)/MWh.

Abstract
In microcirculation, the cell-free layer (CFL) is a well-known physiological phenomenon that plays an important role in reducing the flow resistance and in balancing nitric oxide (NO) production by endothelial cells and NO scavenging by red blood cells. To better understand this phenomenon, several blood flow studies have been performed in simple geometries at both in vivo and in vitro environments. However, to date little information is available regarding the effects imposed by a complex branching network on the CFL.The present study shows the CFL layer variation at a microchannel network.The images were captured using a high-speed video microscopy system and the thickness of the CFL was measured using both manual and automatic image analysis techniques. Using this methodology, it was possible to visualise the in vitro blood flowing through the network and to identify several flow phenomena that happen in microcirculation. Overall, the results have shown that the concentration of cells and the geometrical configuration of the network have a major impact on the CFL thickness. In particular, the thickness of the CFL decreases as the fluid flows through a microchannel network composed with successive smaller channels. It was also clear that, for the full length of the network, the CFL thickness tends to decrease with the increase of the concentration of cells. The automatic method developed becomes inaccurate for high haematocrit and needs be calibrated by manual methods for Hcts bigger than 10%. The results obtained from this study could help the development and validation of multiscale numerical models able to take into account the CFL for simulating microvascular blood flow.