Abstract
Phobias are characterized as the excessive or irrational fear of an object or situation, and specific phobias affect about 10% of the world population. Blood-injection-injury phobia is a specific phobia that has a unique physical response to phobic stimuli, that is, a vasovagal syncope that causes the person to faint. Phobos is a serious game intended for blood phobia treatment that was created to be played in virtual reality with an HTC Vive that has photorealistic graphics to provide a greater immersion. We also developed a console application in C# for electrocardiography sensor connectivity and data acquisition, which gathers a 1 min baseline reading and then has continuous data acquisition during gameplay. Usability tests were conducted with self-reported questionnaires and with a case study population of 10 testers, which gave insight into the previous game experience of the tester for both digital games and virtual reality games, evaluating the discomfort for hardware on both the sensor and the virtual reality headset, as well as the game regarding usability, user experience, level of immersion, and the existence of motion sickness and its source. The results corroborate that the immersion of the game is good, which suggests that it will help with triggering the phobia.

Abstract
Geospatial data acquisition methods like airborne LiDAR allow for obtaining large volumes of data, such as aerial and satellite imagery, which are increasingly being used in archaeology. As in other subjects, the ability to produce raw datasets far exceeds the capacity of domain experts to process and analyze them, but recent developments in image processing, Geographic Information Systems (GIS), Machine Learning (ML) and related technologies enable the transformation of large volumes of data into useful information. However, these technologies are challenging to use and not designed to interact with each other. Hence, tools are needed to efficiently manage, share, document, and reuse archaeological data. This article presents the Odyssey SDI platform, a spatial data infrastructure for annotating, validating, and visualizing data about archaeological sites. This platform is built upon GeoNode, and special-purpose modules were developed for dealing with archaeological information. The main contribution is the integration of remote sensing, GIS features and ML algorithms in a single framework. © 2024 The Author(s).

Abstract
The increasing relevance of remote sensing and artificial intelligence (AI) for archaeological research and cultural heritage management is undeniable. However, there is a critical gap in this field. Many studies conclude with identifying hundreds or even thousands of potential sites, but very few follow through with crucial fieldwork validation to confirm their existence. This research addresses this gap by proposing and implementing a fieldwork validation pipeline. In northern Portugal's Alto Minho region, we employed this pipeline to verify 237 potential burial mounds identified by an AI-powered algorithm. Fieldwork provided valuable information on the optimal conditions for burial mounds and the specific factors that led the algorithm to err. Based on these insights, we implemented two key improvements to the algorithm. First, we incorporated a slope map derived from LiDAR-generated terrain models to eliminate potential burial mound inferences in areas with high slopes. Second, we trained a Vision Transformer model using digital orthophotos of both confirmed burial mounds and previously identified False Positives. This further refines the algorithm's ability to distinguish genuine sites. The improved algorithm was then tested in two areas: the original Alto Minho validation region and the Barbanza region in Spain, where the location of burial mounds was well established through prior field work.

Abstract
The increasing number of IoT deployment scenarios and applications fostered the development of a multitude of specially crafted communication solutions, several proprietary, which are erecting barriers to IoT interoperability, impairing their pervasiveness. To address such problems, several middleware solutions exist to standardize IoT communications, hence promoting and facilitating interoperability. Although being increasingly adopted in most IoT systems, it became clear that there was no one size fits all solution that could address the multiple Quality-of-Service heterogeneous IoT systems may impose. Consequently, we witness new interoperability challenges regarding the usage of diverse middleware. In this work, we address this issue by proposing a novel architecture - the PolyglIoT, that can effectively interconnect diverse middleware solutions while considering the delivery QoS requirements alongside the proposed translation. We analyze the performance and robustness of the solution and show that such Multiprotocol Translator is feasible and can achieve a high performance, thus becoming a fundamental piece to enable future highly heterogeneous IoT systems of systems.

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