Abstract
Total white blood cells (WBC) count is an important indication for infection diagnosis, in both human and veterinary medicine. State-of-the-art WBC counts are performed by flow cytometry combined with light scattering or impedance measurements, in the clinical analysis laboratory. These technologies are complex and difficult to be miniaturized into a portable point-of-care (POC) system. Spectroscopy is one of the most powerful technologies for POC miniaturization due to its capacity to analyze low sample quantities, little to no sample preparation, and ‘real-time’ results. WBC is in the proportion of 1:1000 to red blood cells (RBC), and the latter dominate visible-near infrared (Vis-NIR) information due to their large quantities and hemoglobin absorbance. WBC are difficult to be detected by traditional spectral analysis because their information is contained within the interference of hemoglobin bands. Herein, we perform a feasibility study for the direct detection of WBC counts in canine blood by Vis-NIR spectroscopy for veterinary applications, benchmarking current chemometrics techniques with self-learning artificial intelligence—a new advanced method for high-accuracy quantification from spectral information. Results show that total WBC counts can be detected by Vis-NIR spectroscopy to an average detection limit of 7.8 ×109 cells/L, with an R2 of 0.9880 between impedance flow cytometry analysis and spectral quantification. This result opens new possibilities for reagent-less POC technology in infection diagnosis. As WBC counts in dogs range from 5 to 45 ×109 cells/L, the detection limit obtained in this research allows concluding that the combined use of spectroscopy with this SL-AI new algorithm is a step towards the existence of portable and miniaturized Spectral POC hemogram analysis.

Abstract
Waste is one of the biggest problems on Earth today. In the spring of 2020, a team of students enrolled in the European Project Semester at Instituto Superior de Engenharia decided to contribute with the design of an ethically and sustainability-oriented autonomous cleaning robot named MopBot. The project started with the research on similar solutions, ethics, marketing and sustainability to define a concept and create a functional, ethical and sustainability driven design, including the complete control system. Finally, given the undergoing pandemic, the operation of the MopBot was simulated using CoppeliaSim. MopBot is a medium-sized vacuum cleaner, with two vertical brushes, intended to clean autonomously large areas inside buildings such as shopping malls or corridors. It is shipped with a sustainable packaging solution which can be re-purposed as a disposal box for electrical components.

Abstract
Featured Application This work describes the design, modeling, and simulation of a free-rotating wing sail solution for an autonomous environmental land yacht probe. The adopted method involves the application of land sailing principles for the design, the usage of Fusion 360 tool for 3D modeling, and the integration of Gazebo with the Robotic Operating System (ROS) framework for the simulation of the land yacht. Autonomous land yachts can play a major role in the context of environmental monitoring, namely, in open, flat, windy regions, such as iced planes or sandy shorelines. This work addresses the design, modeling, and simulation of a land yacht probe equipped with a rigid free-rotating wing sail and tail flap. The wing was designed with a symmetrical airfoil and dimensions to provide the necessary thrust to displace the vehicle. Specifically, it proposes a novel design and simulation method for free rotating wing sail autonomous land yachts. The simulation relies on the Gazebo simulator together with the Robotic Operating System (ROS) middleware. It uses a modified Gazebo aerodynamics plugin to generate the lift and drag forces and the yawing moment, two newly created plugins, one to act as a wind sensor and the other to set the wing flap angular position, and the 3D model of the land yacht created with Fusion 360. The wing sail aligns automatically to the wind direction and can be set to any given angle of attack, stabilizing after a few seconds. Finally, the obtained polar diagram characterizes the expected sailing performance of the land yacht. The described method can be adopted to evaluate different wing sail configurations, as well as control techniques, for autonomous land yachts.

Abstract
Air pollution kills approximately 7 million people every year and nine out of ten people are exposed to high levels of airborne pollutants. This paper describes the design of a bicycle air probe by a team of multicultural and multidisciplinary students of the European Project Semester, during the spring of 2020. This learning experience started with the analysis of the state-of-the-art, ethics, marketing and sustainability dimensions, and was followed by the design, development and simulation of a proof-of-concept solution. The result is GOairLight - a bicycle probe paired with a mobile app. The probe collects air quality, humidity and temperature data as cyclists ride, while the mobile app shares the collected data with the community, by means of a cloud database, presents relevant air quality information and suggests less polluted routes. Furthermore, it relies on a sustainable energy source - a dynamo powered by the cyclist - and automatic lighting. The latter feature improves cyclist visibility and raises the awareness towards the cyclist, contributing to increased road safety.

Abstract
In the spring of 2020, six undergraduate students from diverse countries and engineering fields decided to design together a solution to monitor the elderly. This project was performed as part of the European Project Semester (EPS) programme at Instituto Superior de Engenharia do Porto (ISEP). The EM-BRACE solution encompasses two interconnected devices (a home station and a bracelet) and mobile/Web twin applications. The bracelet measures and transmits vital user data (pulse, temperature and impacts) to the home station, whereas the latter measures home environment parameters (temperature, humidity and pressure) and sends local and bracelet data to an Internet of Things (IoT) platform. This way, these data become accessible via the mobile/Web application. Thereby, EM-BRACE monitors the health and environment of the elderly and timely notifies caregivers about problems, contributing to the well-being of the elderly and their families. © 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Abstract
The transportation of large loads is still an obstacle to the productivity of some companies. To answer this internal logistics challenge, one solution with high potential is the use of several mobile robots that can execute these tasks cooperatively. This paper addresses the simulation of strategies that allow two omnidirectional robots, a leader and a follower, to coordinate their movement and cooperate in a transportation task (co-transport). This is achieved by implementing a force sensor on the mechanical structure of a support that allows the follower to grab and transport the load on the top of its chassis. Through the measurement of the forces, this robot will be able to react to the movement of the leader, whose function will be to guide the system to its final destination. The system and its cooperation strategies were idealized and then tested in the CoppeliaSim simulator. The results obtained through simulation were the target of an analysis that assessed which strategy best complemented the omnidirectional mobility of the system's constituents and, at the same time, ensured that less forces were exerted on the load during transport.