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

Abstract
One of the most important negative consequence in the fusion welding processes is the generation of tensile residual stresses in welded joints. The main goals of this work are to determine the optimal combination of welding parameters to minimize the residual stress level and the influence of each welding parameter in that feature to weld 6082-T6 aluminum alloy plates using the GMAW welding process. To achieve these goals was implemented the Taguchi orthogonal array (L27) to define the design of numerical and experimental tests. All combinations were simulated in the Simufactwelding 6.0 software, from which it was possible to obtain the values of maximum residual stresses. The data treatment was carried out, reaching the combination of levels for each parameter. With ANOVA analysis was found that the parameter with the greatest influence in the residual stress generation was the welding speed, while the parameter with the least influence was the torch angle. Also, to minimize the residual stresses it was observed that the optimal combination of welding parameters is welding current intensity of 202 A, welding speed of 10 mm/s, and 30 degrees of inclination of the angular torch. The two simulations that resulted in the highest and lowest residual stresses were validated experimentally by the hole drilling method to measure the residual stresses.

Abstract
A refractometric sensor was applied to measure in real-time the concentration of Active Pharmaceutical Ingredients (APIs) in crystallization experiments. Paracetamol was used as a model system due to the extensive literature available for this API. The refractometric sensor was fabricated by a simple and inexpensive method that consisted in splicing a short section of a multimode fiber to a single mode fiber. The compact geometry of this sensor, with an external diameter of just $125\ \mu\mathrm{m}$, allowed it to measure the concentration of paracetamol, both in a stirred tank crystallizer operating in batch and in an oscillatory flow crystallizer operating continuously. The proposed technique shows the potential to monitor the concentration of APIs in crystallizers of different sizes and geometries as an alternative to more expensive and complex analysis equipment.