Abstract
Cyber-Physical Systems, as distributed systems of computational elements interacting with the physical world, are highly complex systems. They can, in many instances, be considered safety critical interactive systems, as errors in interaction can have disastrous consequences (consider the case of autonomous vehicles or integrated clinical environments). High assurance is, then, an underlying requirement, also at their user interface. In this position paper we identify five challenges to be solved both in the short and in the long term, regarding the modelling of (1) distributed and (2) heterogeneous interactive systems, (3) the analysis and relation between the different abstraction layers of Cyber-Physical Systems, (4) the modelling of real time/hybrid systems, and (5) the modelling of the dynamic nature of such systems. Solutions for these challenges are not presented, but possible directions are discussed.

Abstract
One of the main strategies for fostering the entrepreneurial mindset in students has been the development of training activities inside and outside classrooms using serious games. The chapter makes a brief description regarding five serious games initiatives that intend to promote and facilitate entrepreneurship education for different educational stages. Furthermore, the authors discuss the key benefits and challenges by the introduction of serious games in the learning process. The authors concluded by identifying that serious games have the potentiality of improving the learning process by providing an immersive experience for students that increases their motivation and potentiates the acquisition of multidisciplinary competencies. However, there are some challenges that should be properly considered and mitigated, namely in terms of assessing learning goals, integration with didactical systems, and support for different styles of learning.

Abstract
With the appearance of innovative virtual reality (VR) technologies, the need to create immersive content arose. Although there are already some non-immersive solutions to address immersive audio-visual content, there are no solutions that allow the creation of immersive multisensory content. This work proposes a novel architecture for a collaborative immersive tool that allows the creation of multisensory VR experiences in real-time, thus promoting the expeditious development, adoption, and use of immersive systems and enabling the building of custom-solutions that can be used in an intuitive manner to support organizations' business initiatives. To validate the presented proposal, two approaches for the authoring tools (Desktop interface and Immersive interface) were subjected to a set of tests and evaluations consisting of a usability study that demonstrated not only the participants' acceptance of the authoring tool but also the importance of using immersive interfaces for the creation of such VR experiences.

Abstract
Serious games are increasingly being used as innovative tool for developing entrepreneurial skills, such as strategic management, leadership, communication, negotiation or decision making. FLIGBY is a serious game that was initially developed with the objective of simulating the business management process and the application of Flow theory in a business context. However, most recently it has been suggested that serious games in general, and FLIGBY in particular, can be used in other contexts, namely in the development of entrepreneurial skills. In this sense, this study tries to verify if the competences developed and evaluated in FLIGBY on the Master Analytics Profiler (MAP) can be used to evaluate the entrepreneurial capacities of the students in the context of the course of entrepreneurship in a higher education institution. The findings indicate that the performance of these students in FLIGBY is very similar to the benchmark with only small oscillations. However, some asymmetries emerged considering the educational and professional experience, such that the students of the management course showed better business-oriented thinking and IT students revealed greater time-management skills. Finally, professional experience has proved to be relevant for making decisions about stress and for the completion of managerial tasks successfully.

Abstract
Soil moisture (SM) at three depths (15, 25, and 30 cm), derived from the optical trapezoidal model (OPTRAM), was used for multiyear, multisite monitoring of agricultural droughts over two agricultural crops (Maize and Soybean) in southern Mozambique. The OPTRAM was implemented using satellite data from Sentinel-2 and was validated against field SM assessed by gravimetric methods and by Watermark Sensors in sandy-soils with very low water holding capacity (0.13 cm(3)/cm(3)). The OPTRAM model estimated the SM at 15 and 25 cm yielding a R-2 >= 0.79 and RMSE <= 0.030 cm(3)/cm(3). The OPTRAM-derived SM was successfully used as input to compute and map the soil water deficit index, an indicator of agricultural drought. The results indicate that OPTRAM can provide useful information to improve water productivity in cropland under the specific conditions of Mozambique agricultural systems and for early warning systems development. (C) 2019 Society of Photo-Optical Instrumentation Engineers (SPIE)

Abstract
This paper proposes a computer assisted diagnostic system for the detection of melanoma in dermoscopy images. Clinical findings have concluded that in case of melanoma, the lesion borders exhibit differential structures such as pigment networks and streaks as opposed to normal skin spots, which have smoother borders. We aim at validating these findings by performing segmentation of the skin lesions followed by an extraction of the peripheral region of the lesion that is subjected to feature extraction and classification for detecting melanoma. For segmentation, we propose a novel active contours based method that takes an initial lesion contour followed by the usage of Kullback-Leibler divergence between the lesion and skin to fit a curve to the lesion boundaries. After segmentation of the lesion, its periphery is extracted to detect melanoma using image features that are based on local binary patterns. For validation of our algorithms, we have used the publicly available PH2 and ISIC dermoscopy datasets. An extensive experimental analysis reveals two important findings: 1) the proposed segmentation method mimics the ground truth data; and 2) the most significant melanoma characteristics in the lesion actually lie on the lesion periphery.