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.

Abstract
The accumulation of dust particles on the solar panels decrease the total amount of solar energy received by the Photovoltaic panel (PV) and, it has also been proven that the increase of temperature reduces the overall efficiency. These effects have been studied by different researchers based on collected data comparison. As both of these parameters have a negative effect on the efficiency of the solar panel, it is essential to keep them clean and at low temperatures. The use of technologies, such as robots, is an effective way of carrying out repetitive tasks at low cost and in a short time. This work consists of developing a robot capable of cleaning and cooling the solar panels, based on images acquired through a camera positioned directly towards the panels, thus maintaining periodic cleaning in order to increase its efficiency. The preliminary results demonstrate the possibility of using this approach for the accomplishment of this task.

Abstract
Nowadays, online route planners for soft modes are provided by several platforms such as Google Maps, OpenStreetMap, Here, or Waze. Itineraries are usually built using Shortest Path Problem algorithms that minimize travel time or distance. In this work, we aim to identify and quantify the main features that influence itineraries’ choice by soft modes users in urban areas, able to support multi-objective routing, using simulated scenarios. We propose a set of 21 indicators, grouped into five dimensions: Safety-Security, Comfort, Air Quality, Accessibility, and TimeDistance. Another contribution of this work is the simulation of scenarios to study soft modes’ multi-objective routing within urban areas. © 2021, AHFE International. All rights reserved.

Abstract
Dynamic Epistemic Logic (DEL) is used in the analysis of a wide class of application scenarios involving multi-agents systems with local perceptions of information and knowledge. In its classical form, the knowledge of epistemic states is represented by sets of propositions. However, the complexity of the current systems, requires other richer structures, than sets of propositions, to represent knowledge on their epistemic states. Algebras, graphs or distributions are examples of useful structures for this end. Based on this observation, we introduced a parametric method to build dynamic epistemic logics on-demand, taking as parameter the specific knowledge representation framework (e.g., propositional, equational or even a modal logic) that better fits the problems in hand. In order to use the built logics in practices, tools support is needed. Based on this, we extended our previous method with a parametric construction of complete proof calculi. The complexity of the model checking and satisfiability problems for the achieved logics are provided. © 2021, IFIP International Federation for Information Processing.

Abstract