Abstract
With the increasing development of human-AI teaming structures within and across geographies, the time is ripe for a continuous and objective look at the predictors, barriers, and facilitators of human-AI scientific collaboration from a multidisciplinary point of view. This paper aims at contributing to this end by exploiting a set of factors affecting attitudes towards the adoption of human-AI interaction into scientific work settings. In particular, we are interested in identifying the determinants of trust and acceptability when considering the combination of hybrid human-AI approaches for improving research practices. This includes the way as researchers assume human-centered artificial intelligence (AI) and crowdsourcing as valid mechanisms for aiding their tasks. Through the lens of a unified theory of acceptance and use of technology (UTAUT) combined with an extended technology acceptance model (TAM), we pursue insights on the perceived usefulness, potential blockers, and adoption drivers that may be representative of the intention to use hybrid intelligence systems as a way of unveiling unknown patterns from large amounts of data and thus enabling novel scientific discoveries.

Abstract
[No abstract available]

Abstract
A sincronização online de ginástica potencia novas possibilidades para melhorar o bem-estar físico e social das pessoas com restrições de deslocação. A nossa proposta passa pela criação de uma plataforma 3D - Online Gym - que permita que os utilizadores interajam e participem em sessões online de ginástica em grupo através do Microsoft Kinect. No presente artigo, com vista à concretização desta proposta, analisamos três alternativas tecnológicas para a implementação de serviços de deteção de movimentos que possam ser integrados em plataformas gráficas multiutilizador. Nos resultados, expõem-se as características de cada uma e o impacte respetivo para sua utilização na concretização desta proposta ou outras iniciativas similares.

Abstract
Microtasks have become increasingly popular in the digital labor market since they provide easy access to a crowd of people with varying skills and aptitudes to perform remote work tasks that even the most capable algorithmic systems are unable to complete in a timely and efficient fashion. However, despite the latest advancements in crowd-powered and contiguous interfaces, many crowd workers still face some accessibility issues, which ultimately deteriorate the quality of the work produced. To mitigate this problem, we restrict attention to the development of two different web-based mini-games with a focus on cognitive personalization. We have conducted a pilot gamified experience, with six participants with autism, dyslexia, and attention deficit hyperactivity. The results suggest that a web-based mini-game can be incorporated in preliminary microtask-based crowdsourcing execution stages to achieve enhanced cognitive personalization in crowdsourcing settings.

Abstract
This study discusses the intricate relations between generative artificial intelligence (AI) and music composers. Based on a previous rapid review of recent literature, it reinforces a gap and suggests the need to develop human-centered generative AI design strategies prioritizing cultural artistic (and non-artistic) aspects. We posit that AI-based music generation solutions should resonate with the cultural diversity of stakeholders who are impacted by these systems in practice. The paper highlights the significance of metaphorical design as an effective method in human-AI music co-creation by leveraging familiar interfaces and features that are rooted in everyday objects and cognitive models derived from real-world settings. Our insights illustrate possible ways of (re)framing human-AI metaphorical design to shape perceptions and facilitate seamless interactions between humans and intelligent systems in music co-creativity, particularly at the compositional level. At the heart of this research is the alignment of AI-driven music creation systems with user needs, values, and expectations that vary from culture to culture and thus require a continuous and transparent adaptation of the technology in use to accommodate individual preferences and the socio-algorithmic specificities underlying musicians’ activities.

Abstract
This work aims to identify teaching and learning practices in practical classes of Computer Network Technology courses, which promote the use of the Physical Laboratory (PL) as an epistemic tool to improve learning in epistemic terms. Content analysis of Multimodal Narrations (MN) of three classes by two teachers were used. An MN aggregates and organizes the data collected in the PL environment. Based on the results, we infer that the student and the teacher, under certain conditions, use the physical laboratory as an epistemic tool since the physical interactions prove its use and reuse. In addition, this study allows, in the context of work in the physical laboratory of networks, to identify that the orchestrations of mediation patterns adopted by the teacher influence the students' epistemic practices and the use of the laboratory as a tool to produce new knowledge. The following contributions are presented: (1) The quality of the students' epistemic practices is increased if, in the teacher's dynamics of mediation, the control of the students' action is reduced; (2) The orchestration of the teacher's mediation patterns is essential to achieve beneficial results in student learning with the use of artifacts from the physical laboratory of Computer Networks; (3) For the physical laboratory to become an epistemic tool, it is necessary that the mediation standards allow students to develop epistemic practices to a high or very high degree and there is a certain mediation orchestration.