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
The calibration of sensors stationed along a cable in marine observatories is a time-consuming and expensive operation that involves taking the mooring out of the water periodically. In this paper, we present a method that allows an underwater vehicle to approach a mooring, in order to take reference measurements along the cable for in-situ sensor calibration. We use the vehicle's Mechanically Scanned Imaging Sonar (MSIS) to identify the cable's reflection within the sonar image. After pre-processing the image to remove noise, enhance contour lines, and perform smoothing, we employ three detection steps: 1) selection of regions of interest that fit the cable's reflection pattern, 2) template matching, and 3) a track-before-detect scheme that utilized the vehicle's motion. The later involves building a lattice of template matching responses for a sequence of sonar images, and using the Viterbi algorithm to find the most probable sequence of cable locations that fits the maximum speed assumed for the surveying vessel. Performance is explored in pool and sea trials, and involves an MSIS onboard an underwater vehicle scanning its surrounding to identify a steel-core cable. The results show a sub-meter accuracy in the multi-reverberant pool environment and in the sea trial. For reproducibility, we share our implementation code.

Abstract
The dark compact object at the centre of the Milky Way is well established to be a supermassive black hole with mass M-center dot similar to 4.3 x 10(6) M-circle dot, but the nature of its environment is still under debate. In this work, we used astrometric and spectroscopic measurements of the motion of the star S2, one of the closest stars to the massive black hole, to determine an upper limit on an extended mass composed of a massive vector field around Sagittarius A*. For a vector with effective mass 10(-19) (less than or similar to) m(s less than or similar to) 10(-18) eV, our Markov chain Monte Carlo analysis shows no evidence for such a cloud, placing an upper bound M-cloud (less than or similar to) 0.1 % M-center dot at 3 sigma confidence level. We show that dynamical friction exerted by the medium on S2 motion plays no role in the analysis performed in this and previous works, and can be neglected thus.

Abstract
Office workers spend a considerable part of their day at the workplace, making it vital to ensure proper indoor environmental quality (IEQ) conditions in office buildings. This work aimed to identify significant factors influencing IEQ and assess the effectiveness of an environmental intervention program, which included the introduction of indoor plants, carbon dioxide (CO2) sensors, ventilation, and printer relocation (source control), in six modern office buildings in improving IEQ. Thirty office spaces in Porto, Portugal, were randomly divided into intervention and control groups. Indoor air quality, thermal comfort, illuminance, and noise were monitored before and after a 14-day intervention implementation. Occupancy, natural ventilation, floor type, and cleaning time significantly influenced IEQ levels. Biophilic interventions appeared to decrease volatile organic compound concentrations by 30%. Installing CO2 sensors and optimizing ventilation strategies in an office that mainly relies on natural ventilation effectively improved air renewal and resulted in a 28% decrease in CO2 levels. The implementation of a source control intervention led to a decrease in ultrafine particle and ozone concentrations by 14% and 85%, respectively. However, an unexpected increase in airborne particle levels was detected. Overall, for a sample of offices that presented acceptable IEQ levels, the intervention program had only minor or inconsistent impacts. Offices with declared IEQ problems are prime candidates for further research to fully understand the potential of environmental interventions.

Abstract
This work focuses on the application of image processing techniques to segment and analyze images of brain sections with the aim of facilitating early diagnosis of brain tumors. The aim is to delineate specific regions of the brain, such as the cranial, intracranial, and encephalic regions, for subsequent geometric analysis. The process involves image pre-processing, conversion to polar coordinates, determination of contour points, Fourier Series approximation, and the use of the Least Square Method to obtain accurate representations of the regions. The proposed approach was tested on Magnetic Resonance Images of three different brains, showing its capability to accurately delineating the targeted regions. The results highlight the potential of signal processing techniques for analyzing brain images and provide insights for further research in this area.

Abstract
Data generated throughout the product development lifecycle is often unused to its full potential, particularly for improving the engineering design process. Although Knowledge-Based Engineering (KBE) approaches are not new, the Digital Twin (DT) concept is giving new momentum to it, fostering the availability of lifecycle data with the potential to be transformed into new design knowledge. This approach creates an opportunity to research howdigital infrastructures and new knowledge-based processes can be articulated to implement more effective KBE approaches. This paper describes how combining a DT-based Digital Platform (DP) with new engineering design processes can improve Knowledge Management (KM) in product design. A case study of a company in the energy sector highlights the challenges and benefits of this approach.