Abstract
<p>The current SARS-CoV-2 pandemic has been affecting all sectors worldwide, and efforts have been targeting the enhancement of people’s health and labour conditions of collaborators belonging to healthcare institutions. The recent vaccines emerging against covid-19 are seen as a solution to address the problem that has already killed up to two million people. The preparation of the Pfizer-BioNTech covid-19 vaccine requires a specific manipulation before its administration. A correct homogenization with saline solution is needed and, therefore, a manual process with a predefined protocol should be accomplished. This action can endanger the operators’ ergonomics due to the repetitive movement of the process. This paper proposes a low-cost prototype incorporating an arduino based embedded system actuating a servomotor to perform an autonomous vials’ homogenization allowing to redirect these healthcare workers to other tasks. Moreover, a contactless start order process was implemented to avoid contact with the operator and, consequently, the contamination. The prototype was successfully tested and recognised, and is being applied during the preparation of the covid-19 vaccines at the hospital pharmacy of <em>Centro Hospitalar de Vila Nova de Gaia/Espinho</em>, <em>E.P.E.</em>, Portugal. It can be easily replicated since the source files to assemble it are provided by the authors.</p>

Abstract
Automated guided vehicles (AGV) represent a key element in industries’ intralogistics and the use of AGV fleets bring multiple advantages. Nevertheless, coordinating a fleet of AGV is already a complex task but when exposed to delays in the trajectory and communication faults it can represent a threat, compromising the safety, productivity and efficiency of these systems. Concerning this matter, trajectory planning algorithms allied with supervisory systems have been studied and developed. This article aims to, based on work developed previously, implement and test a Multi AGV Supervisory System on real robots and analyse how the system responds to the dynamic of a real environment, analysing its intervention, what influences it and how the execution time is affected.

Abstract
The development of composites from 1D and 2D nanocarbon building blocks, namely carbon nanotubes and graphene layers, with enhanced properties or novel functionalities is an emerging challenge in material science. Herein, we developed a colloid-based approach using surfactants and polymers to non-covalently functionalize multiwalled carbon nanotubes (MWNTs) and graphene nanoplatelets (GnPs), and to fabricate GnP@MWNT nanocomposites via an electrostatic-driven assembly process in aqueous solution. In the assembly process, two building methods were used and compared (bulk mixing and adapted layer-by-layer assembly), using surfactant and polymer/surfactant combinations as the dispersants for the initial nanomaterials. After their characterization by scanning electron microscopy, Raman spectroscopy and BET analysis, the nanocomposites were evaluated as electrocatalysts for the oxygen reduction reaction (ORR). Results show that the type of the dispersant (namely the presence of polymer) plays a more relevant role than the specific building method in almost all the ORR parameters. Further, the nanocomposites show selectivity toward the 2-electron pathway oxygen reduction for the electrochemical production of hydrogen peroxide. The development and optimization of further nanocomposite electrocatalysts can be pursued using this type of versatile and robust assembly method.

Abstract
The evolution of technology and the increasing connectivity between devices lead to an increased risk of cyberattacks. Good protection systems, such as Intrusion Detection System (IDS) and Intrusion Prevention System (IPS), are essential in trying to prevent, detect and counter most of the attacks. However, the increasing creativity and type of attacks raise the need for more resources and processing power for the protection systems which, in turn, requires horizontal scalability to keep up with the massive companies' network infrastructure and with the complexity of attacks. Technologies like machine learning, show promising results and can be of added value in the detection and prevention of attacks in real-time. But good algorithms and tools are not enough. They require reliable and solid datasets to be able to effectively train the protection systems. The development of a good dataset requires horizontal-scalable, robust, modular and fault-tolerance systems, so that the analyses may be done also in real-time. This paper describes an architecture for horizontal-scaling capture architecture, able to collect packets from multiple sources and prepared for real-time analysis. It depends on multiple modular nodes with specific roles to support different algorithms and tools.

Abstract
The GRAVITY instrument on the ESO VLTI pioneers the field of high-precision near-infrared interferometry by providing astrometry at the 10-100 mu as level. Measurements at this high precision crucially depend on the control of systematic effects. We investigate how aberrations introduced by small optical imperfections along the path from the telescope to the detector affect the astrometry. We develop an analytical model that describes the effect of these aberrations on the measurement of complex visibilities. Our formalism accounts for pupil-plane and focal-plane aberrations, as well as for the interplay between static and turbulent aberrations, and it successfully reproduces calibration measurements of a binary star. The Galactic Center observations with GRAVITY in 2017 and 2018, when both Sgr A* and the star S2 were targeted in a single fiber pointing, are affected by these aberrations at a level lower than 0.5 mas. Removal of these effects brings the measurement in harmony with the dual-beam observations of 2019 and 2020, which are not affected by these aberrations. This also resolves the small systematic discrepancies between the derived distance R-0 to the Galactic Center that were reported previously.

Abstract