Abstract
The pervasiveness of mobile devices has fostered a multitude of services and applications, but also raised serious privacy concerns. In order to avoid users' tracking and/or users' fingerprinting, smartphones have been tightening the access to unique identifiers. Nevertheless, smartphone applications can still collect diverse data from available sensors and smartphone resources. Using real-world data from a field study we performed, this paper demonstrates the possibility of fingerprinting users from Wi-Fi data in mobile devices and the consequent privacy impact. From the performed analysis, we concluded that a single snapshot of a set of scanned Wi-Fi BSSIDs (MAC addresses) per user is enough to uniquely identify about 99% of the users. In addition, the most frequent Wi-Fi BSSID is sufficient to re-identify more than 90% of the users, a percentage that goes up to 97% of the users with the top-2 scanned BSSIDs. The Wi-Fi SSID (network name) also leads to a re-identification risk of about 83% and 97% with 1 and 2 of the strongest Wi-Fi Access Points (APs), respectively.

Abstract
Integrating physical robots in an educational context often entails acquiring expensive equipment that often operates using proprietary software. Both conditions restrict the students from exploring and fully understanding the internal operation of robots. In response to these limitations, a three-degree-of-freedom robotic manipulator, based on the “EEZYbotARM MK2” open-source design by Carlo Franciscone, is being repurposed and integrated within the SimTwo simulation environment to operate within a hardware-in-the-loop architecture. To accomplish this objective, first, an open-source Arduino-based library was developed aiming at the robot’s online and offline programming akin to industrial robots. The firmware is able to communicate with the SimTwo software in which the digital twin’s robot is living. The dynamic behavior of the robot’s digital twin must be properly parametrized and aligned with the physical robot’s dynamics. This article describes the modeling of the robot joint’s actuator and its closed-loop controller formulation. The obtained results show that the dynamic behavior of the robot joint digital twin closely matches both open and closed-loop, the one of its physical counterpart.

Abstract
This paper presents a novel Nonlinear Model Predictive Controller (NMPC) architecture for trajectory tracking of omnidirectional robots. The key innovation lies in the method of handling constraints on maximum velocity and acceleration outside of the optimization process, significantly reducing computation time. The controller uses a simplified process model to predict the robot’s state evolution, enabling real-time cost function minimization through gradient descent methods. The cost function penalizes position and orientation errors as well as control effort variation. Experimental results compare the performance of the proposed controller with a generic Proportional-Derivative (PD) controller and a NMPC with integrated optimization constraints. The findings reveal that the proposed controller achieves higher precision than the PD controller and similar precision to the NMPC with integrated constraints, but with substantially lower computational effort. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

Abstract
This article describes the construction path of a Responsible Research and Innovation (RRI) tool, starting with a systematic literature review of all responsible innovation tools to extract the essential dimensions and exclude overlapping. Those dimensions were presented in a series of workshops within a Research and Innovation Action European Project where 35 Innovation Actions (IA) were developed. Focusgroup methodology was followed, including the IA's leaders, to generate discussion around the sixteen dimensions and the meanings of the different grades of the Likert scale of an assessment tool to be applied to innovation processes and results.

Abstract
The phase-matching conditions for exciting surface plasmon resonances (SPR) in plasmonic films are typically satisfied via prism, optical fibers or grating-assisted coupling. We recently showed that plasmonic nanospheres can act as local emitters, exciting SPR waves on thin films-termed nanoparticle-induced SPR (NPI-SPR). This structure holds promise for sensing, but the effects of optical fiber geometry and nanoparticle anisotropy on the response were unexplored. This study examines these factors, showing that an etched multimode fiber with a 200 mu m core diameter, taper ratio of 4, and etching angle of 20 degrees optimizes interaction with plasmonic nanoparticles. Tuning the nanoparticle aspect ratio from 1 to 3 shifts the NPI-SPR band from 780 to 1580 nm, with excitation highly dependent on the incident light angle. Notably, for light incident parallel to the film plane, a refractive index sensitivity exceeding 1000 nm/RIU is achieved. This efficient light emission combines the field locality enhancements of plasmonic nanoparticle-on-film structures with the emission efficiency of plasmonic nanoantennas, advancing plasmonic optical fiber chemical and biosensors.

Abstract
We introduce a novel blockchain-based interledger authorisation scheme, a unique solution designed to support delegated authorisation management in cross-domain cloud environments. This innovative approach enables client applications, acting on behalf of a user, to request access to specific resources owned by a different organization. It benefits cross-domain multi-cloud applications, such as large-scale collaboration projects involving multiple cloud service providers. Multi-cloud presents authorisation challenges because of complex access control operations in multiple distinct domains. OAuth2 is the state-of-the-art choice for delegated authorisation. However, it falls short in handling such complex interactions with multiple authorisation servers and resource servers, and this is our motivation. Compared with OAuth2, our approach overcomes the limitations of a centralized model and achieves coordinated distinct delegations among multiple entities without a thirdparty trusted component. authorisation servers are blockchain participants and designated access token issuers, ensuring minimum client data collection and promoting client privacy. Multiple smart contracts are deployed in our multi-ledger blockchain environment to guarantee the provenance of the authorisation operations and facilitate scalable cross-domain authorisation. Our hybrid interledger model combines security techniques such as blockchain-based device authentication, hashed time-lock contracts (HTLCs), and service discovery. The blockchain-based device authentication ensures secure and trusted interactions, HTLCs enable time-bound transactions, and service discovery simplifies finding and connecting to the required cloud services. Our experimental evaluation provides insights into the scalability of our approach, which achieves decentralized authorisation in a multi-cloud environment with acceptable latencies compared with related works and shows stable throughput against concurrent authorisation requests in a multi-ledger system.