Abstract
Although most Natural Language Processing tasks, such as Text Classification and Natural Language Translation, have experienced a major performance improvement due to recent advances in neural network architectures, Temporal Relation Extraction remains an open challenge. This leaves the door open for new research questions. In this paper, we provide a brief summary of the task and some of the recent efforts that have been made to solve it. In addition, some research opportunities yet to be explored are also discussed.

Abstract

Abstract
Current chemometrics and artificial intelligence methods are unable to deal with complex multi-scale interference of blood constituents in visible shortwave near-infrared spectroscopy point-of-care technologies. The major difficulty is to access the rich information in the spectroscopy signal, unscrambling and interpreting spectral interference to provide analytical quality quantifications. We present a new self-learning artificial intelligence method for spectral processing based on the search of covariance modes with direct correspondence to the BeerLambert law. Dog and cat hemograms were analyzed by impedance flow cytometry and standard laboratory methods (erythrocytes counts, hemoglobin, and hematocrit). Spectral records were performed for the same samples. The methodology was benchmarked against state-of-the-art chemometrics: a multivariate linear model of hemoglobin bands, similarity, partial least squares, local partial least squares, and artificial neural networks. The new method outperforms the state-of-the-art, providing analytical quality quantifications according to desired veterinary pathology guidelines (total errors of 1.69% to 7.14%), whereas chemometric methods cannot. The method finds relevant samples and spectral information that hold the quantitative information for a particular interference mode, in contrast to the current methods that do not hold a relationship with the BeerLambert law. It allows the interpretation of interference bands used in quantification, providing the capacity to determine if the composition of an unknown sample is predictable. This research is especially relevant for improving current optical point-of-care technologies that are affected by spectral interference and moving towards micro-sampling and reagent-less technologies in healthcare and veterinary medicine diagnosis.

Abstract
The consumer's profile and behaviour have undergone drastic changes in recent years, as a result of rapid technological developments associated with the proliferation of the Internet, which have boosted the growth of e-commerce. Retail needed to adopt new strategies to respond to new consumer demands leading to the development of omnichannel. The omnichannel strategy is centred on the consumer and aims to offer him/her a unique, consistent, and quality experience, through any contact point and wherever the consumer wants. However, most Portuguese retailers still opt for a multichannel strategy, where the physical shop and the online shop operate independently from each other. Although there are already some successful cases in Portugal, it can be considered that the use of omnichannel is still at an early stage. More publicity is needed so that retailers are aware of the concept and above all recognise the advantages of this new strategy. Before disclosure it is important to understand why companies work with both online and offline channels and do not opt for an omnichannel strategy. This study aims to analyse Portuguese companies that have not yet adopted an omnichannel strategy, to understand the barriers that make them unwilling to adopt this strategy. To this end, a quantitative research was carried out through the application of surveys to companies in different districts of Portugal to understand their position in relation to omnichannel and the reasons for not moving to this structure. The results obtained made it possible to describe the importance of omnichannel as a commercial and distribution strategy and analyse the reasons why its use by companies in Portugal is still extremely low. The lack of knowledge about the structure and management issues emerged as the biggest barriers.

Abstract
This chapter's first goal is to present the concept of Positive Play as an expression of play focused on social, psychological, and physical well-being and human potential. It presents some of its foundations in the form of eight maxims that emerged from an analysis on various games developed in the industry and in research settings. Afterwards, it demonstrates of how Positive Play can be integrated in different contexts of action, from diagnosis and intervention to contexts focused on prevention and promotion of awareness and knowledge in the scope of mental health, regarding treatment for Anorexia Nervosa, through a series of in-progress case studies in the form of game prototypes.

Abstract
We live in a world where companies are shifting to the industry 4.0 paradigm. One of the pillars of Industry 4.0 is the digitalization of physical assets and manufacturing processes, moving toward the Cyber-Physical Production Systems concept (CPPS). In these systems, every component of the production process - machines, tools, workstations, etc. - is equipped with sensors, possesses information about itself, and can interact with each other, allowing the production of smaller batches at lower prices and increase product customization through adaptative processes. Consequently, companies are evolving their information systems to have more visibility and control over their production systems. This change increases both the production system's agility and its vulnerability to communication and information related disruptions. Hence, companies that adhere to Industry 4.0 enabling technologies must adopt new methodologies and tools to become aware of the new risks that arise by the introduction of new digital platforms, their impacts in the production systems, and how they may react to remain resilient. In this paper, disruption events and adequate mitigation strategies are analysed, modelled, and simulated as part of a methodology designed to measure the impacts of disruptive events on the production system.