Abstract
An overwhelming quantity of messages is posted in social networks every minute. To make the utilization of these platforms more productive, it is imperative to filter out information that is irrelevant to the general audience, such as private messages, personal opinions or well-known facts. This work is focused on the automatic classification of public social text according to its potential relevance, from a journalistic point of view, hopefully improving the overall experience of using a social network. Our experiments were based on a set of posts with several criteria, including the journalistic relevance, assessed by human judges. To predict the latter, we rely exclusively on linguistic features, extracted by Natural Language Processing tools, regardless the author of the message and its profile information. In our first approach, different classifiers and feature engineering methods were used to predict relevance directly from the selected features. In a second approach, relevance was predicted indirectly, based on an ensemble of classifiers for other key criteria when defining relevance-controversy, interestingness, meaningfulness, novelty, reliability and scope-also in the dataset. The first approach achieved a F (1)-score of 0.76 and an Area under the ROC curve (AUC) of 0.63. But the best results were achieved by the second approach, with the best learned model achieving a F (1)-score of 0.84 with an AUC of 0.78. This confirmed that journalistic relevance can indeed be predicted by the combination of the selected criteria, and that linguistic features can be exploited to classify the latter.

Abstract

Abstract
One way of contributing to a demonstration that a medical device is acceptably safe is to show that the device satisfies a set of requirements known to mitigate hazards. This paper describes experience using formal techniques to model an IV infusion device and to prove that the modelled device captures a set of requirements. The requirements chosen for the study are based on a draft proposal developed by the US Food and Drug Administration (FDA). A major contributor to device related errors are (user) interaction errors. For this reason the chosen models and requirements focus on user interface related issues.

Abstract
This paper aims at presenting the development of a calibrated building energy simulation model of a school building to study the impact of improving the ventilation system on energy performance. The simulation model was developed with the DesignBudderlEnergyplus software and it was calibrated based on data collected during an energy audit to the school building. Schools need high outdoor airflow rates to remove indoor air contaminants related to occupants and building components, thus requiring mechanical ventilation systems. Due to budget restrictions, school managers decided to schedule the building management system to keep the HVAC systems active only between 6:00 am and 10:00 am. According to the values measured in this school, it was patent that the CO2 concentration was too high in certain periods. Too high peak values undermine the indoor air quality in the remaining occupancy time of the classroom, harming the work conditions for teachers and students. To solve this problem, an extended usage schedule of the mechanical ventilation was simulated (8:00 am to 5:00 pm) according to the required enhancement of indoor air quality, which together with the adoption of the new calculated fresh air flow rates will enhance air quality while avoiding excessive cost, thus increasing energy efficiency. (C) 2017 The Authors. Published by Elsevier Ltd.

Abstract
The original version of this article unfortunately contained an error in the author affiliation. The corresponding author, “Dr. Borislav Nikoli´c” is currently affiliated in “Technische Universität Braunschweig”, but the work of this paper was performed and funded by CISTER/INESC-TEC, ISEP, IPP. Therefore, the corresponding author is linked to both the affiliations. This has been corrected with this erratum.

Abstract
In this work, we present parameter regions for the existence of stable plain solitons of the cubic complex Ginzburg-Landau equation (CGLE) with higher-order terms associated with a fourth-order expansion. Using a perturbation approach around the nonlinear Schrdinger equation soliton and a full numerical analysis that solves an ordinary differential equation for the soliton profiles and using the Evans method in the search for unstable eigenvalues, we have found that the minimum equation allowing these stable solitons is the cubic CGLE plus a term known in optics as Raman-delayed response, which is responsible for the redshift of the spectrum. The other favorable term for the occurrence of stable solitons is a term that represents the increase of nonlinear gain with higher frequencies. At the stability boundary, a bifurcation occurs giving rise to stable oscillatory solitons for higher values of the nonlinear gain. These oscillations can have very high amplitudes, with the pulse energy changing more than two orders of magnitude in a period, and they can even exhibit more complex dynamics such as period-doubling.