Abstract
Data is everywhere and in everything we do. Most of the time, usable information is hidden in raw data and because of that, there is an increasing demand for people capable of working creatively with it. To fully understand how we can assist data science workers to become more productive in their jobs, we first need to understand who they are, how they work, what are the skills they hold and lack, and which tools they need. In this paper, we present the results of the analysis of several interviews conducted with data scientists. Our research allowed us to conclude that the heterogeneity between these professionals is still understudied, which makes the development of methodologies and tools more challenging and error prone. The results of this research are particularly useful for both the scientific community and industry to propose adequate solutions for these professionals.

Abstract
In this study machine learning methods were applied to RGB data obtained by an unmanned aerial vehicle (UAV) to assess this effectiveness in vineyard classification. The very high-resolution UAV-based imagery was subjected to a photogrammetric processing allowing the generation of different outcomes: orthophoto mosaic, crop surface model and five vegetation indices. The orthophoto mosaic was used in an object-based image analysis approach to group pixels with similar values into objects. Three machine learning techniques-support vector machine (SVM), random forest (RF) and artificial neural network (ANN)-were applied to classify the data into four classes: grapevine, shadow, soil and other vegetation. The data were divided with 22% (n=240, 60 per class) for training purposes and 78% (n = 850) for testing purposes. The mean value of the objects from each feature were used to create a dataset for prediction. The results demonstrated that both RF and ANN models showed a good performance, yet the RF classifier achieved better results.

Abstract
Entrepreneurship can be perceived as an individual's ability to identify opportunities, and to develop solutions that create innovative solutions for society. It can be a business, a project or even a movement that generates real change and impact on people's daily lives. What defines an entrepreneur is his/her behavior and attitudes and not personality traits or any other innate characteristics. It is not possible to predict which individuals have an entrepreneurial profile, but we can work on developing the skills that are necessary to become an entrepreneur. Therefore, this view assumes that entrepreneurial skills can be developed through education and life experiences. The teaching of entrepreneurship is a theme that has generated considerable interest in higher education institutions. Several programs have been proposed. Currently, it is necessary to evaluate their effectiveness, considering multiple perspectives. Only through the evaluation of the performance of these courses we can ensure that students are properly prepared for the challenges they will encounter in the labor market, whether through the launch of a start-up or in the management of a company or project. This study uses the EntreComp framework to assess the development of entrepreneurial skills and to identify the factors that influence their performance. This study offers both theoretical and practical contributions. In the conceptual component, a framework that has a multidisciplinary view of the entrepreneurial skills has been developed. On a practical level, it can be applied within a course of entrepreneurship, which will enable its replication to various educational institutions.

Abstract
Composites are finding increased use in structural high demanding and high added value applications in advanced industries. A wide diversity exists in terms of matrix type, which can be either polymeric or metallic and type of reinforcements (ceramic, polymeric or metallic). Several technologies have been used to produce these composites; among them, additive manufacturing (AM) is currently being applied. In structural applications, the presence of defects due to fabrication is of major concern, since it affects the performance of a component with negative impact, which can affect, ultimately, human lives. Thus, the detection of defects is highly important, not only surface defects but also barely visible defects. This chapter describes the main types of defects expected in composites produced by AM. The fundamentals of different non-destructive testing (NDT) techniques are briefly discussed, as well as the state of the art of numerical simulation for several NDT techniques. A multiparametric and customized inspection system was developed based on the combination of innovative techniques in modelling and testing. Experimental validation with eddy currents, ultrasounds, X-ray and thermography is presented and analysed, as well as integration of distinctive techniques and 3D scanning characterization. © 2020, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG.

Abstract
Nowadays wearable devices are very popular. The reason for that is the sudden reduction in pricing and the increase in functionalities. Healthcare services have been greatly benefiting from the emergence of these devices since they can collect vital signs and help healthcare professionals to easily monitor patients. Medical wellness, prevention, diagnosis, treatment and monitoring services are the main focus of Healthcare applications. Some companies have already invested in this market and we present some of them and their strategies. Furthermore, we also conducted a group interview with Altice Labs in order to better understand the critical points and challenges they encountered while developing and maintaining their service. With the purpose of comprehending users’ receptiveness to mHealth systems (mobile health systems which users wear - wearables) and their opinion about sharing data, we also created a questionnaire (which had 114 valid responses). Based on the research done we propose a different approach. In our product and service concept solution, which we share herein, we consider people of all ages to be targets for the product/service and, beyond that, we consider the use of machine learning techniques to extract knowledge from the information gathered. Finally, we discuss the advantages and drawbacks of this kind of system, showing our critical point of view. © 2020, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG.

Abstract
Purpose The purpose of this paper is to identify the antecedents and consequences of social media fashion influencer's (SMFI) diffusion of fashion information. This study proposes and examines following research questions: What motivates SMFI to share fashion information? In what way shared fashion information impact SMFI? Design/methodology/approach This study uses semi-structured interviews with SMFI to learn about their relationships with followers. It then conducts a survey of 510 SMFI in Portugal. The data are analyzed by structural equation modeling. Findings The results indicate that intrinsic motivation can develop a SMFIs' fashion leadership, while the SMFIs' perceived usability of fashion blogs does not. The authors also find a self-serving bias among SMFI. Research limitations/implications SMFIs' fashion leadership is associated with the intrinsic motivations of sharing and helping other consumers make fashion decisions, which indicates that marketers can improve their results through using opinion SMFI to assist fashion consumers in purchasing decisions. Further studies should explore the processes adopted by fashion consumers to evaluate SMFI. Originality/value This study helps to understand the antecedents and consequences of fashion diffusion by SMFIs. In particular, the research helps the marketers to understand how the bonds between SMFIs and followers are nurtured.