Abstract
Prediction of labor is of extreme importance in obstetric care to allow for preventive measures, assuring that both baby and mother have the best possible care. In this work, the authors studied how important nonlinear parameters (entropy and compression) can be as labor predictors. Linear features retrieved from the SisPorto system for cardiotocogram analysis and nonlinear measures were used to predict labor in a dataset of 1072 antepartum tracings, at between 30 and 35 weeks of gestation. Two groups were defined: Group A-fetuses whose traces date was less than one or two weeks before labor, and Group B-fetuses whose traces date was at least one or two weeks before labor. Results suggest that, compared with linear features such as decelerations and variability indices, compression improves labor prediction both within one (C-Statistics of 0.728) and two weeks (C-Statistics of 0.704). Moreover, the correlation between compression and long-term variability was significantly different in groups A and B, denoting that compression and heart rate variability look at different information associated with whether the fetus is closer to or further from labor onset. Nonlinear measures, compression in particular, may be useful in improving labor prediction as a complement to other fetal heart rate features.

Abstract
The exchange of academic marks between HEIs (Higher Education Institutions) is mandatory in every student mobility programs (i.e. the EU Erasmus Program) but that process remains to present date with insufficient technological support and the absence of a comprehensive reference model that allows the integration of potential technological solutions for the exchange of academic data with existing Academic Information Systems seems to limit greatly the possibility of adopting solutions of this type referred to in the existing literature. This work addresses this issue, conducting an initial bibliographic review aimed at the identification of the fundamental requirements of such an architecture as well as explores some of the technologies that are showing potential for usage in the safe exchange of academic results between partner HEIs, with particular interest in blockchain technology applied in an educational context.

Abstract
The architecture for 5G core includes a Service-Based Architecture for the diverse network functions (NFs), which relies on HTTP/2 for the SBI and TCP as the underlying transport protocol. The specifications of the HTTP family is moving towards more efficient and secure protocols, which are based on UDP to assure enhanced transport but using TLS to secure the communication channel. The next generation of microservices needs to be more secure, performant and easily manageable, where HTTP/3 and containers orchestration platforms (like Kubernetes) can provide significative contributions towards such goals. Different deployment approaches can be followed for services implemented in compliance to the 5G SBA. This paper contributes with the assessment of deployment models for services in 5G networks, where NFs are implemented following traditional architectures (all the functions in a VM) or as serverless architectures (with functions distributed in containers). The performance of microservices in Kubernetes is also evaluated. The evaluation conducted also considers the employment of different versions of HTTPs to empower the service-based interfaces of 5G services. Results demonstrate performance benefits of employing HTTP/3, based on QUIC protocol, in scenarios with networks characterised by losses or delay conditions. Despite such gain, deployment in 5G networks needs to carefully consider aspects related with connection tracking mechanisms to support high volumes of requests.

Abstract
At an estimated annual growth rate of 13.74%, the global health informatics market can reach $123 billion, by 2025, figures that exemplify the development trends of an ever-growing industry. The authors decided to collect data from the general public through an anonymous survey on the subject of health informatics. This survey was developed on Google Forms and later sent to multiple recipients by email and shared on social networks. A total of 165 people, aged 16 to 81 years old, participated in this survey. 98.8% of the respondents consider response time in health a determining factor. 97.6% of the survey participants consider that it is possible to make more accurate and viable clinical diagnoses using health informatics. Furthermore, according to our survey, people do not mind mortgaging their personal data (which is known from the outset for its incalculable value) because they know that, in return, they will benefit from better living conditions. Three experts were also interviewed and according to one of them, one of the biggest challenges in health informatics is “understanding and detecting diseases long before they happen”. This interviewee also stressed the importance of artificial intelligence “in helping people to improve their health through indicators that alert and recommend certain habits and influence the improvement of people’s quality of life”. Finally, the emphasis needs to be on eliminating health costs and facilitating life for people with chronic diseases. © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2020.

Abstract
Ultrasonic sensors offers attractive features at an affordable cost. The main problem faced by the use of these devices is that the data obtained are not so easy to interpret, restricting their efficiency. This paper describes a binaural sensor system that is able to determine the coordinates of an object or a target in a two-dimensional space, focusing on mathematical and signal processing techniques to provide accurate measurements and increase the system reliability. The proposed work consists only of low cost components, which aims to demonstrate that improvement is possible. Experimental tests, performed in different scenarios, reported good accuracy and repeatability of the measurements.

Abstract
The vehicle routing problem with backhauls (VRPB) allows to integrate inbound and outbound routes, which is an efficient strategy to reduce routing costs and also to reduce the environmental and social impacts of transportation. In this paper, we analyze the VRPB literature with a sustainability perspective, which covers environmental and social objectives, collaborative networks and reverse logistics. First, to better understand and analyze the VRPB literature, all related works are characterized according to a common taxonomy provided for routing problems. This taxonomy is extended to differentiate between economic, environmental and social objectives. After identification of all VRPB papers that include sustainability issues, these are analyzed and discussed in more detail. The analysis reveals that research on VRPBs with sustainability concerns is recent and relatively scarce and the most popular aspects investigated are the minimization of fuel consumption andCO2 emissions. Future research lines driven by sustainability concerns are suggested for the VRPB as a promoter of green logistics.