Abstract
Reinforcement Learning techniques allow learning complex behaviors to deal with a variety of situations in a matter of hours. This complexity is even more prominent in multi-agent continuous 3D environments. This paper compares how the actions taken by two agents independently trained via a self-play approach differ from the ones taken when they are controlled by the same policy. It also explores the emergence of competitive or collaborative behaviors in a natural game setting. By implementing a 3D simulated version of the Dance Dance Revolution, the acquisition of more specific abilities like equilibrium, balance, and dexterity was tested. The approach achieved very good results learning a predefined sequence of buttons (7 arrows correctly pressed in 20M timesteps), revealing a similar learning behavior to human beings (improving with training and performing better in this kind of sequence than in random ones). The self-play approach also produced some interesting effects by developing cooperative behaviors in theoretically competitive scenarios.

Abstract
Models-at different levels of abstraction and pertaining to different engineering views-are central in the design of railway networks, in particular signalling systems. The design of such systems must follow numerous strict rules, which may vary from project to project and require information from different views. This renders manual verification of railway networks costly and error-prone. This paper presents EVEREST, a tool for automating the verification of railway network models that preserves the loosely coupled nature of the design process. To achieve this goal, EVEREST first combines two different views of a railway network model-the topology provided in signalling diagrams containing the functional infrastructure, and the precise coordinates of the elements provided in technical drawings (CAD)-in a unified model stored in the railML standard format. This railML model is then verified against a set of user-defined infrastructure rules, written in a custom modal logic that simplifies the specification of spatial constraints in the network. The violated rules can be visualized both in the signalling diagrams and technical drawings, where the element(s) responsible for the violation are highlighted. EVEREST is integrated in a long-term effort of EFACEC to implement industry-strong tools to automate and formally verify the design of railway solutions. © 2022 ACM.

Abstract
Purpose This study contributes to the understanding of how cultural organizations are using digital technologies to redesign their business models and enable sustainable and impactful audiovisual digital archives. Design/methodology/approach An inductive multiple case research design was used. Five cases of audiovisual digital archives of independent films were selected. Data collected was based on desk research, onsite visits, interviews with top managers responsible for the digitalization of some of the archives and experimentation with the services provided. Data was collected and analyzed based on a theoretical framework defined from the literature for business models of cultural organizations. Findings The archives analyzed faced the challenge of aligning the commercial viability with a mission of making content available to increase cultural knowledge. A sustainable business model may be achieved by using different revenue models, while guaranteeing to offer a value proposition carefully aligned with stakeholders' expectations. Moreover, an impactful business model, i.e. a business model that enhances the creation of cultural value for customers and reaches wider audiences, requires careful audience management and the use of data analysis about audience behavior to adjust the offering. Finally, the business model must consider the resources, activities and infrastructure that ensure critical capabilities for the business and must be designed to ensure financial resilience of the organization. Originality/value This study contributes with a holistic analysis of business models for the digital transformation of cultural organizations, detailing alternative configurations for the most relevant components of a digital business model for audiovisual archives.

Abstract
The European rabbit (Oryctolagus cuniculus) was the first animal model used to understand human diseases like rabies and syphilis. Nowadays, the rabbit is still used to study several human infectious diseases like syphilis, HIV and papillomavirus. However, due to several mainly practical reasons, it has been replaced as an animal model by mice (Mus musculus). The rabbit and mouse share a recent common ancestor and are classified in the superorder Glires which arose at approximately 82 million years ago (mya). These species diverged from the Primates' ancestor at around 92 million years ago and, as such, one expects the rabbit-human and mouse-human genetic distances to be very similar. To evaluate this hypothesis, we developed a set of tools for automatic data extraction, sequence alignment and similarity study, and a web application for visualization of the resulting data. We aligned and calculated the genetic distances for 2793 innate immune system genes from human, rabbit and mouse using sequences available in the NCBI database. The obtained results show that the rabbit-human genetic distance is lower than the mouse-human genetic distance for 88% of these genes. Furthermore, when we considered only genes with a difference in genetic distance higher than 0.05, this figure increase to 93%. These results can be explained by the increase of the mutation rates in the mouse lineage suggested by some authors and clearly show that, at least looking to the genetic distance to human genes, the European rabbit is a better model to study innate immune system genes than the mouse.

Abstract

Abstract