Abstract
This article arises from the proposal of a new approach regarding the inclusion of soft-digital skills training in higher education. The study carried out on several curricular units in different higher education courses in Portugal led us to reflect on a different educational model, which combines the development of soft skills in digital environments. Digitalization and the use of technologies since early ages in the educational process are raising interesting questions. This article intends to go deeper on the use of digital technologies, namely through the virtual environments imposed by higher education institutions as a form of study. The main question is how pedagogies and the use of technologies have a meeting point where it is possible to continue humanization in education through the utilization of virtual environments to support the teaching/learning process. The methodology used in this study has its support on questionnaires made to students of higher education in different areas of knowledge, such as medicine, nursing, engineering, management, arts and literature. The main conclusions of this study are the importance of creating and using digital platforms that not only support the study but also contemplate the use of a virtual reality where students can interact with others in the discussion and resolution of real life situations.

Abstract
In this paper, we describe Fourier-based Wave Front Sensors (WFS) as linear integral operators, characterized by their Kernel. In a first part, we derive the dependency of this quantity with respect to the WFS’s optical parameters: pupil geometry, filtering mask, tip/tilt modulation. In a second part we focus the study on the special case of convolutional Kernels. The assumptions required to be in such a regime are described. We then show that these convolutional kernels allow to drastically simplify the WFS’s model by summarizing its behavior in a concise and comprehensive quantity called the WFS’s Impulse Response. We explain in particular how it allows to compute the sensor’s sensitivity with respect to the spatial frequencies. Such an approach therefore provides a fast diagnostic tool to compare and optimize Fourier-based WFSs. In a third part, we develop the impact of the residual phases on the sensor’s impulse response, and show that the convolutional model remains valid. Finally, a section dedicated to the Pyramid WFS concludes this work, and illustrates how the slopes maps are easily handled by the convolutional model.

Abstract
Este artigo apresenta reflexões seminais acerca da utilização de tutores virtuais no sistema de e-learning da Universidade Aberta. O tutor virtual é uma analogia do tutor humano, adota uma interface antropomórfica com características emocionais, comumente denominado de avatar, que integra inteligência artificial e pode constituir uma abordagem interessante, tanto para o professor como para os estudantes, se se perspetivar o futuro dos ambientes típicos de ensino e educação a distância online e em rede e a crescente massificação da individualização do acompanhamento do estudante. Embora atraente de muitas formas, especialmente quando se leva em linha de conta a redução da carga da interação e do apoio que um professor (humano) deve fornecer nesses ambientes, várias questões se colocam visando a plena e efetiva integração de avatares como artefactos de mediação da tutoria virtual. Este artigo fornece um conjunto de perspetivas iniciais sobre este desafio, introduzindo o estado da arte no campo, enquanto apresenta alguns desenvolvimentos recentes e em experimentação na Universidade Aberta pela instanciação de dois avatares – a Maria e o João.;This article presents seminal reflections on the use of virtual tutors in the Aberta University e-learning system. The virtual tutor is an analogy of the human tutor, adopting an anthropomorphic interface with emotional characteristics, commonly called an avatar, which integrates artificial intelligence, and can be an interesting approach for both the teacher and the students, if the future of environments typical of online and networked distance learning and education, and the increasing massification of the individualization of student follow-up. Although attractive in many ways, especially when one takes into account the reduction of the interaction load and the support that a (human) teacher must provide in these environments, several questions are posed for the full and effective integration of avatars as mediation artifacts of virtual tutoring. This article provides a set of initial perspectives on this challenge, introducing the state of the art in the field, while presenting some recent developments and experimentation at the Aberta University by the instantiation of two avatars - Mary and John.

Abstract
Surgical tool detection is attracting increasing attention from the medical image analysis community. The goal generally is not to precisely locate tools in images, but rather to indicate which tools are being used by the surgeon at each instant. The main motivation for annotating tool usage is to design efficient solutions for surgical workflow analysis, with potential applications in report generation, surgical training and even real-time decision support. Most existing tool annotation algorithms focus on laparoscopic surgeries. However, with 19 million interventions per year, the most common surgical procedure in the world is cataract surgery. The CATARACTS challenge was organized in 2017 to evaluate tool annotation algorithms in the specific context of cataract surgery. It relies on more than nine hours of videos, from 50 cataract surgeries, in which the presence of 21 surgical tools was manually annotated by two experts. With 14 participating teams, this challenge can be considered a success. As might be expected, the submitted solutions are based on deep learning. This paper thoroughly evaluates these solutions: in particular, the quality of their annotations are compared to that of human interpretations. Next, lessons learnt from the differential analysis of these solutions are discussed. We expect that they will guide the design of efficient surgery monitoring tools in the near future.

Abstract
Actual integration of high-tech devices brings opportunities for better monitoring, management and control of low voltage networks. In this new paradigm, efficient tools should cope with the great amount of dispersed and considerably distinct data to support smarter decisions in almost real time. Besides the use of tools to enable an optimal network reconfiguration and integration of dispersed and renewable generation, the impact evaluation of integrating storage systems, accurate load forecasting methods must be found even when applied to individual consumers (characterized by the high presence of noise in time series). As this effort becomes providential in the smart grids context, this article compares three different approaches: one based on Kernel Density Estimation, an alternative based on Artificial Neural Networks and a method using Support Vector Machines. The first two methods revealed unequivocal benefits when compared to a Naive method consisting of a simple reproduction of the last available day.

Abstract
This work proposes a multi-criteria decision-making approach to select suppliers in the olive oil sector. Besides several performance criteria required to the supplier, olive oil characteristics such as colour, smell, and density, as well as organoleptic tests are used. Hence, the assessment and selection of suppliers assumes a major importance and needs to be done yearly. The process of finding a set of suppliers to choose from involves two sequential stages, namely identification and elimination. The identification stage consists of finding a set of potential suppliers. Then, in the elimination stage, suppliers that are not able to meet the thresholds associated with some technical indicators are disregarded. Thus, only a small set of very promising suppliers need to be assessed. The assessment was performed by resorting to the Macbeth approach, resulting in a ranking. The results obtained were validated through sensitivity and robustness analyses.