Abstract
Our contemporary society necessitates professionals equipped with 21st-century skills. Disciplines within Science, Technology, Engineering, Arts, and Mathematics (known as STEAM) have been particularly effective in fostering these skills. However, when considering students with disabilities, especially those with intellectual or developmental disabilities (IDD), this assertion often falls short. In this context, the RoboSTEAMSEN project emerges as an initiative designed to enhance educational processes by providing teachers of IDD students with the necessary resources to promote STEAM engagement. The project proposes the use of active learning methodologies and robotics to achieve this goal. The primary objective of the project is realized through several strategies: understanding the needs of students with disabilities and adapting the use of robotics and active learning methodologies accordingly; training teachers in the use of these resources; and creating a platform to exchange experiences, resources, lessons learned, tools, case scenarios, etc., while reaching other potential stakeholders such as caregivers and policymakers. The main outcomes of the project are teacher training programs and the development of associated competencies, tools to identify and classify resources for the students, and technological platforms to ensure the sustainability of the project once it concludes.

Abstract
The reliability of Free Space Optical (FSO) communications between a ground station and celestial objects is significantly hampered by the variability in atmospheric conditions. Enhancing the system's capabilities to recover the received signal can significantly increase the robustness and broaden the operational scope of this type of communication. One of the most promising avenues for improvement entails integrating Adaptive Optics systems with the latest Machine Learning techniques. We study different control laws based on a classical integrator, a LQG with a Kalman filter (with a second order autoregressive model) and a Reinforcement Learning approach : we evaluate the performance of the three control laws with the Strehl ratio.

Abstract
Self-adaptive Systems (SaS) are becoming increasingly important for adapting to dynamic environments and for optimizing performance on resource-constrained devices. A practical approach to achieving self-adaptability involves using a Pareto-Front (PF) to store the system's hyper-parameters and the outcomes of hyperparameter combinations. This paper proposes a novel method to approximate a PF, offering a configurable number of solutions that can be adapted to the device's limitations. We conducted extensive experiments across various scenarios, where all PF solutions were replaced, and real world scenarios were performed using actual measurements from a Human Activity Recognition (HAR) system. Our results show that our method consistently outperforms previous methods, mainly when the maximum number of PF solutions is in the order of hundreds. The effectiveness of our method is most apparent in real-case scenarios where it achieves, when executed in a Raspberry Pi 5, up to 87% energy consumption reduction and lower execution times than the second-best algorithm. Additionally, our method ensures a more evenly distributed solution across the PF, preventing the high concentration of solutions.

Abstract
A growing concern with current teaching approaches underscores the need for innovative paradigms and tools in computer programming education, aiming to address disparate user profiles, enhance engagement, and cultivate deeper understanding among learners This article proposes an innovative approach to teaching programming, where students are challenged to write statements for solutions automatically generated. With this approach, rather than simply solving exercises, students are encouraged to develop code analysis and problem formulation skills. For this purpose, a Web application was developed to materialize these ideas, using the OpenAI API to generate exercises and evaluate statements written by the students. The transformation of this application in H5P and its integration in a LMS gamified workflow is explored for wider and more effective adoption.

Abstract
The purpose of this scoping review was to identify and summarize how technology can promote patient participation in the rehabilitation process in hip replacement. We conducted a scoping review following the steps outlined by the Joanna Briggs Institute. The PRISMA Checklist (Preferred Reporting Items for Systematic reviews and Meta-Analyses) was utilized to systematically organize the gathered information. A thorough search of articles was performed on PubMed, Scopus, and CINAHL databases for all publications up to December 2022. Twenty articles were included in this study. Various technologies, such as mobile applications, Web sites, and platforms, offer interactive approaches to facilitate total hip replacement rehabilitation. The analyzed studies were based on the rehabilitation of total hip arthroplasty, which in most of them was developed in mobile applications and Web sites. The studies identified reflect trends in the application of digital health technologies to promote patient engagement in the rehabilitation process and provide risk monitoring and patient education.

Abstract
The Mid-infrared ELT Imager and Spectrograph (METIS) instrument is one of three first-generation science instruments for the Extremely Large Telescope (ELT) in Chile. It has entered the Manufacturing, Assembly, Integration and Testing (MAIT) phase and it is currently scheduled to be installed in 2028. Its Single Conjugate Adaptive Optics (SCAO) system will provide the performance of an extreme adaptive optics system which enables high-contrast imaging (HCI) observations in the thermal/mid-infrared wavelength domain. The METIS Adaptive Optics (AO) control system is responsible for the AO wavefront correction and for supporting AO-related assembly, integration, verification and maintenance activities. It realizes the main AO loop by a Real-Time Computer (RTC) that receives images from a wavefront sensor and commands the corrective optics through the Central Control System (CCS) of the ELT. Several auxiliary functions will run outside of the RTC in the AO Observation Coordination System (AO OCS) that are necessary to maintain the quality of the wavefront correction. For instance, the Differential tip-tilt (DTT) control loop centers the star on the Vortex Phase Mask during HCI observations by adjusting the modulator device via the SCAO Function Control System (FCS) based on sciences images received from the Focal Plane Sensor Gateway (FPS GW). Conceptually, the METIS Adaptive Optics Control System (AOCS) is a distributed software system that is controlled by the METIS Instrument Control System (ICS). This paper describes the current status of the METIS AO control system, driving forces behind the design and the important control loops.