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.

Abstract
Existing architectural locations are often recreated in games using unique “hero” meshes instead of modular assets, which in these cases are commonly perceived as too limited or inaccurate. This applies to real-world locations or, as in this case study, transmedia locations. This study proposes that hero meshes are not always necessary and that modular assets have the potential to recreate even complex architecture. The paper presents a set of development steps for modular assets for game environment art according to a game design lifecycle, and proceeds to demonstrate its potential via a case study. The case study focuses on planning and designing steps; these preliminary results indicate that, when well-designed, modular assets have the potential to recreate complex architectural locations without requiring extensive use of hero meshes. Adopting modular assets instead of hero meshes could potentially reduce the cost and development time of environment art for transmedia games and games featuring real-world architectural locations, as well as increase the reusability of such assets.

Abstract
Background: Trauma is a public health issue with a significant social and economic impact. However, national data on its characterization and the role of nursing in its management is still scarce. Objective: To assess the effectiveness of prehospital nursing interventions in stabilizing trauma victims provided by nurses of Immediate Life Support Ambulances in Portugal. Methodology: Observational, prospective, and descriptive-correlational study. Data were collected by nurses of the Immediate Life Support Ambulances in mainland Portugal, from 01/03/2019 to 30/04/2020, and the Azores, from 01/10/2019 to 30/04/2020. Trauma severity indices were assessed before and after the nursing interventions. Results: This study included 606 cases (79.4% blunt trauma; 40.8% road accidents) reported by 171 nurses. Nurses performed mostly interventions for hemodynamic support (88.9%) and non-pharma-cological pain control (90.6%) of trauma victims. The nursing interventions improved the Revised Trauma Score and the Shock Index (p<0.001). Conclusion: Prehospital nursing interventions improve trauma victims’ clinical status.

Abstract
We make two fits of an ODE system with 5 equations that model immune response by CD4 + T cells with the presence of regulatory T cells (Tregs). We fit the simulations to data regarding gp61 and NP309 epitopes from mice infected with lymphocytic choriomeningitis virus LCMV. We optimized parameters relating to: the T cell maximum growth rate; the T cell capacity; the T cell homeostatic level; and the ending time of the immune activation phase after infection. We quantitatively and qualitatively compare the obtained results with previous fits in the literature using different ODE models and we show that we are able to calibrate the model and obtain good fits describing the data. © 2021, Springer Nature Switzerland AG.

Abstract
Backed by more powerful computational resources and optimized training routines, Deep Learning models have proven unprecedented performance and several benefits to extract information from chest X-ray data. This is one of the most common imaging exams, whose increasing demand is reflected in the aggravated radiologists’ workload. Consequently, healthcare would benefit from computer-aided diagnosis systems to prioritize certain exams and further identify possible pathologies. Pioneering work in chest X-ray analysis has focused on the identification of specific diseases, but to the best of the authors’ knowledge no paper has specifically reviewed relevant work on abnormality detection and multi-label thoracic pathology classification. This paper focuses on those issues, selecting the leading chest X-ray based deep learning strategies for comparison. In addition, the paper discloses the current annotated public chest X-ray databases, covering the common thorax diseases.