Abstract
Recently, indoor swimming pool activities have increased to promote health-enhancing physical activities, which require establishing suitable protocols for disinfection and water quality control. Normally, the assessment of the microbial quality of the water in the pools only considers the presence of different bacteria. However, other less frequent but more resistant pathogens, such as free-living amoebas (FLA), are not contemplated in both existing recommendation and research activities. FLA represent a relevant human health risk, not only due to their pathogenicity but also due to the ability to act as vehicles of other pathogens, such as bacteria. Therefore, this work aimed to study the physicochemical characteristics and the occurrence of potentially pathogenic FLA and bacteria in water samples from 20 public indoor swimming facilities in Northern Portugal. Our results showed that some swimming pools presented levels of pH, free chlorine, and conductivity out of the recommended limits. Pathogenic FLA species were detected in two of the facilities under study, where we also report the presence of both, FLA and pathogenic bacteria. Our findings evidence the need to assess the occurrence of FLA and their existence in the same environmental niche as pathogenic bacteria in swimming pool facilities worldwide and to establish recommendations to safeguard the health of the users.

Abstract
Developing safe autonomous robotic applications for outdoor agricultural environments is a research field that still presents many challenges. Simultaneous Localization and Mapping can be crucial to endow the robot to localize itself with accuracy and, consequently, perform tasks such as crop monitoring and harvesting autonomously. In these environments, the robotic localization and mapping systems usually benefit from the high density of visual features. When using filter-based solutions to localize the robot, such an environment usually uses a high number of particles to perform accurately. These two facts can lead to computationally expensive localization algorithms that are intended to perform in real-time. This work proposes a refinement step to a standard high-dimensional filter based localization solution through the novelty of downsampling the filter using an online clustering algorithm and applying a scan-match procedure to each cluster. Thus, this approach allows scan matchers without high computational cost, even in high dimensional filters. Experiments using real data in an agricultural environment show that this approach improves the Particle Filter performance estimating the robot pose. Additionally, results show that this approach can build a precise 3D reconstruction of agricultural environments using visual scans, i.e., 3D scans with RGB information.

Abstract
The maritime industry has been following the paradigm shift toward the automation of typically intelligent procedures, with research regarding autonomous surface vehicles (ASVs) having seen an upward trend in recent years. However, this type of vehicle cannot be employed on a full scale until a few challenges are solved. For example, the docking process of an ASV is still a demanding task that currently requires human intervention. This research work proposes a volumetric convolutional neural network (vCNN) for the detection of docking structures from 3-D data, developed according to a balance between precision and speed. Another contribution of this article is a set of synthetically generated data regarding the context of docking structures. The dataset is composed of LiDAR point clouds, stereo images, GPS, and Inertial Measurement Unit (IMU) information. Several robustness tests carried out with different levels of Gaussian noise demonstrated an average accuracy of 93.34% and a deviation of 5.46% for the worst case. Furthermore, the system was fine-tuned and evaluated in a real commercial harbor, achieving an accuracy of over 96%. The developed classifier is able to detect different types of structures and works faster than other state-of-the-art methods that establish their performance in real environments.

Abstract

Abstract
Rural tourism has become a truly relevant economic activity, with visible impacts (social and economic) to regional and national development and overall sustainability. The sole characteristics of rural destinations make them extremely attractive to tourists that search for experiences away from the massified and more urban areas. Despite this increase in the demand, in order to remain competitive and trigger its development and ensure sustainability, rural destinations need to ensure a twofold approach, first continuously create innovative and engaging tourism experiences, and secondly implement continuously innovative marketing approaches. Hence, to fully understand the state of the art in what concerns the incorporation of innovation by rural tourism marketeers, a systematic literature review focused on that same topic has been performed, the achieved set of 66 articles has been thoroughly analysed, and multiple results of this procedure are presented.

Abstract
Acquired brain injury (ABI) is associated with severe functional consequences at several levels: personal, psychological, social, physical, economic, and systemic. The main objective of the present study is to show the potential of applying virtual reality (VR) in neuropsychological rehabilitation and the consequent psychological and cognitive improvement of the person with ABI. A total of 27 participants of both sexes with moderate or severe ABI participated in an investigation in a clinical trial-type design with pre-test and post-test. Participants in the experimental group (n = 8) underwent a remote holistic neuropsychological intervention program supported by a VR platform: the Virtual Centre for the Rehabilitation of Road Accident Victims (VICERAVI). The experimental group results were compared with a first control group (n = 10) that underwent a conventional holistic neuropsychological intervention face-to-face program; and with a second control group that did not have any neuropsychological intervention (n = 9). We conclude that the VR-based neuropsychological rehabilitation program (NRP) at a distance produces better cognitive results in general cognitive functioning, learning, memory, and executive functioning than the conventional face-to-face NRP. Still, at the psychosocial level, the conventional NRP obtained results similar to those of the VR-based NRP, which did not produce significant improvements. Thus, the study results suggest that the development of VR-based holistic NRPs may benefit the autonomy of people with ABI.