Abstract

Abstract
Order picking has driven an increase in the number of logistics researchers. Robotics can help reduce the operational cost of such a process, eliminating the need for a human operator to perform trivial and dangerous tasks such as moving around the warehouse. However, for a mobile robot to perform such tasks, certain problems, such as defining the best path, must be solved. Among the most prominent techniques applied in the calculation of the trajectories of these robotic agents are potential fields and the A* algorithm. However, these techniques have limitations. This study aims to demonstrate a new approach based on the behavior of oceanic relief to map an environment that simulates a logistics warehouse, considering distance, safety, and efficiency in trajectory planning. In this manner, we seek to solve some of the limitations of traditional algorithms. We propose a new mapping technique for mobile robots, followed by a new trajectory planning approach.

Abstract
Natural gas (NG) is commonly used in kitchens, powering stoves, ovens, and other appliances. While it is known for its efficiency and convenience, NG contributes to the release of nitrogen dioxide (NO2) and can have significant implications for human health. In this study, the importance of the use of NG in kitchens on human exposure to NO2 was analyzed. An extensive literature review in the field was conducted, and the NO2 levels were assessed in kitchens with NG cookers in Aveiro and electric cookers in Porto, both in Portugal. Higher levels of NO2 were found in kitchens in Aveiro, where NO2 levels outdoors are lower than in Porto. This pollutant can spread to other rooms, especially when ventilation is lacking, which is particularly concerning during colder seasons and at night. As around 70% of the time is spent at home, this can have a significant impact on human exposure to NO2. Therefore, although Aveiro has low levels of NO2 outdoors, its population may be exposed to much higher levels of this pollutant than the Porto population, a city with air quality issues, but predominantly using electric cookers. This finding emphasizes the need for the stricter regulation of NG use indoors to protect human health and also suggests a shift in human health protection policies from mere monitoring/control of outdoor air quality to a comprehensive assessment of human exposure, including exposure to indoor air quality.

Abstract
Coffee capsules have gained high levels of popularity in the last decades due to their convenience of use, flavour choices, and consistent extraction quality. As governmental bodies are promoting more circular solutions for packaging products, concerns have been raised regarding the environmental impacts of single-use coffee capsules, namely their end-of-life treatment and effective recyclability. This paper presents a novel design based on thin steel sheet material application for new packaging solutions that can support a more circular economy. To validate this new design, a framework was presented for a cross-assessment of Life Cycle Assessment with Circularity Analysis to compare the new tinplate capsule with conventional polypropylene and aluminium capsules. The novel design is more circular (0.97 in the material circularity indicator), in comparison with the polypropylene (0.1) and aluminium (0.80) conventional capsules, due to the ferromagnetic properties that allow for better effectiveness during sorting in urban packaging recycling facilities. As for the environmental assessment, the tinplate has higher environmental impacts than the aluminium and the polypropylene capsules (more 63 % and more 92 %, respectively) due to the high energy intensity processes required to produce this material. These results demonstrate that the novel tinplate capsule should complement the strong results in circularity with further improvements in its environmental performance, namely by the transition of the steel industry to the upcoming generation of decarbonized steel production.

Abstract
After the learning process, certain types of images may not be modeled correctly because they were not well represented in the training set. These failures can then be compensated for by collecting more images from the real-world and incorporating them into the learning process - an expensive process known as active learning. The proposed twist, called active supervision, uses the model itself to change the existing images in the direction where the boundary is less defined and requests feedback from the user on how the new image should be labeled. Experiments in the context of class imbalance show the technique is able to increase model performance in rare classes. Active human supervision helps provide crucial information to the model during training that the training set lacks.

Abstract
Spectral point-of-care technology is reagentless with minimal sampling (<10 mu L) and can be performed in real-time. White blood cells are non-dominant in blood and in spectral information, suffering significant interferences from dominant constituents such as red blood cells, hemoglobin and billirubin. White blood cells of a bigger size can account for 0.5% to 22.5% of blood spectra information. Knowledge expansion was performed using data augmentation through the hybridization of 94 real-world blood samples into 300 synthetic data samples. Synthetic data samples are representative of real-world data, expanding the detailed spectral information through sample hybridization, allowing us to unscramble the spectral white blood cell information from spectra, with correlations of 0.7975 to 0.8397 and a mean absolute error of 32.25% to 34.13%; furthermore, we achieved a diagnostic efficiency between 83% and 100% inside the reference interval (5.5 to 19.5 x 10(9) cell/L), and 85.11% for cases with extreme high white blood cell counts. At the covariance mode level, white blood cells are quantified using orthogonal information on red blood cells, maximizing sensitivity and specificity towards white blood cells, and avoiding the use of non-specific natural correlations present in the dataset; thus, the specifity of white blood cells spectral information is increased. The presented research is a step towards high-specificity, reagentless, miniaturized spectral point-of-care hematology technology for Veterinary Medicine.