Abstract
This annual issue embraces articles from three sets of sources: the first covers the topic Virtual Environments and Interaction Design Research at the University of Saint Joseph, Macao SAR, China works selected and guest edited by Carlos Sena Caires and Gerald Estadieu; the second set are three extended articles from the International Conference on Graphics and Interaction (ICGI’2021), selected and guest edited by Daniel Mendes and Nuno Rodrigues; and, finally, two articles from the regular pipeline.

Abstract
Cloud computing and Infrastructure-as-Code (IaC), supported by technologies such as Docker, have shaped how many software systems are built and deployed. Previous research has identified typical issues for some types of IaC specification but not why they come to be, or they have delved into collaboration aspects but not into technical ones. This work aims to characterize the activities around two particular kinds of IaC specification-Dockerfiles and docker-compose.yml files. We seek to know how they can be better supported and therefore study also what approaches and tools practitioners employ. We used an online questionnaire to gather data. The first part of the study reached 68 graduate students from a study program on informatics engineering, and the second one 120 professional software developers. The results show that most of the activities of the process of developing a Dockerfile are perceived as time-consuming, especially when the respondents are beginners with this technology. We also found that solving issues using trial-and-error approaches is very common and that many developers do not use ancillary tools to support the development of Dockerfiles and docker-compose.yml files.

Abstract
We study a variant of the Probabilistic Travelling Salesman Problem arising when retailers crowdsource last-mile deliveries to their own customers, who can refuse or accept in exchange for a reward. A planner must identify which deliveries to offer, knowing that all deliveries need fulfilment, either via crowdsourcing or using the retailer's own vehicle. We formalise the problem and position it in both the literature about crowdsourcing and among routing problems in which not all customers need a visit. We show that to evaluate the objective function of this stochastic problem for even one solution, one needs to solve an exponential number of Travelling Salesman Problems. To address this complexity, we propose Machine Learning and Monte Carlo simulation methods to approximate the objective function, and both a branch-and-bound algorithm and heuristics to reduce the number of evaluations. We show that these approaches work well on small size instances and derive managerial insights on the economic and environmental benefits of crowdsourcing to customers.

Abstract
Cardiac auscultation is the key exam to screen cardiac diseases both in developed and developing countries. A heart sound auscultation procedure can detect the presence of murmurs and point to a diagnosis, thus it is an important first-line assessment and also cost-effective tool. The design automatic recommendation systems based on heart sound auscultation can play an important role in boosting the accuracy and the pervasiveness of screening tools. One such as step, consists in detecting the fundamental heart sound states, a process known as segmentation. A faulty segmentation or a wrong estimation of the heart rate might result in an incapability of heart sound classifiers to detect abnormal waves, such as murmurs. In the process of understanding the impact of a faulty segmentation, several common heart sound segmentation errors are studied in detail, namely those where the heart rate is badly estimated and those where S1/S2 and Systolic/Diastolic states are swapped in comparison with the ground truth state sequence. From the tested algorithms, support vector machine (SVMs) and random forest (RFs) shown to be more sensitive to a wrong estimation of the heart rate (an expected drop of 6% and 8% on the overall performance, respectively) than to a swap in the state sequence of events (an expected drop of 1.9% and 4.6%, respectively).

Abstract
In this paper we describe the implementation of a secure key distribution system based on an ultra-long fiber laser with a bi-directional erbium doped fiber amplifier. The resilience of the system was tested against passive attacks from an eavesdropper, having been observed a similarity in spectrum for both secure configurations of the system.

Abstract
Orion is a NASA spacecraft being developed for human exploration of the Moon and Mars. Crew Dragon is a commercial spacecraft used to transport astronauts to and from the International Space Station (ISS). Both spacecraft are of similar design and both spacecraft perform a water landing following re-entry. This study evaluated the ability of International Institute of Astronautical Sciences (IIAS) Citizen Astronaut Candidates (CAC) to egress a spacecraft mock-up wearing a commercially available intravehicular activity (IVA) spacesuit manufactured by Final Frontier Design (FFD) (Anderson, 2014; Barker and Bellenkes; 1996; Rubio et al., 2004). This suit is similar to those worn by astronauts traveling to the ISS on board Crew Dragon. Mobility assessment revealed that most participants had sufficient ranges of motion to perform egress tasks successfully. In some instances suited participants were unable to perform selected tasks proficiently, but in these instances this often stemmed from difficulty in achieving a stable upright position in the water. Seat ingress and egress evaluation revealed no significant problems with anthropometric accommodation across participants.