Abstract
When it was first introduced, the concept of sustainability in the forestry sector had a narrow focus on sustainable wood production. Since then, this concept has evolved and it now considers now the three sustainability dimensions (economic, environmental and social) of the whole forest wood supply chain. The main objective of this study is then to review assessment and optimization studies that consider the forest wood supply chain and at least one of the sustainability dimensions. To accomplish this goal, a total number of 188 papers, published in English-speaking peer-reviewed journals from 1995 to 2017, were reviewed. These papers have been classified according to the sustainability dimensions explored, the stakeholder's involvement, the modeling approaches applied, the supply chain decision levels treated, the uncertainty inclusion, and case study analyzed. Most of the studies reviewed (84.6%) considered only two sustainability dimensions: economic (31.9%), environmental (13.8%), or a combination of both (38.8%). The first study including the three sustainability dimensions was published in 2005. Most of the studies reviewed (64.9%) focus on the bioenergy industry in Europe and North America, due to the growing interest in using biomass to substitute fossil fuels in energy production. The final part of the paper presents the identified specific features of sustainable forest wood supply chains and discusses a future research agenda in the area.

Abstract
In the last decades, the assurance of doctoral education's quality and their respective external quality assurance (QA) systems have been on the agenda of many European countries. Portugal is no exception, with doctoral education being envisaged by the national study programmes' accreditation system. This study aims to discuss both the forms assumed by the QA of doctoral education within the scope of a tightly regulated system, such as the Portuguese one, as well as the effects or impact of such a system in this education level. In trying to explore this impact, particular attention is given to the accreditation results (full accreditation, conditional accreditation and non-accreditation) of the doctoral programmes according to their scientific area and higher education sector (public and private). Overall it is possible to conclude that the Portuguese QA system has been contributing to the reorganisation of doctoral education, both by excluding programmes that do not meet a set of minimum quality criteria and by promoting the enhancement of the remaining programmes, through the enforcement of improvement measures. This reorganisation seems to differently affect doctoral programmes from distinct scientific areas as well as from private and public institutions.

Abstract
Automated Fare Collection (AFC) systems produce a large amount of very detailed data, which analysis may be very useful to authorities and transport planners to define future service delivery strategies. Such analysis can be further improved by relating to other data sources, such as points-of-interest (POI) data. As a result public transport operators are able to identify the city service providers with whom it would be more interesting to establish partnerships and propose joint value propositions benefiting both service providers. The objective of such partnerships is to attract new customers and retain those that already exist by providing combined offers, discounts or loyalty schemes. The potential of such analysis is demonstrated by using data related to the city of Porto, Portugal. This study relies on two different data sources: AFC system data and points-of interest data. Urban mobility data is used to identify mobility patterns of different segments of passengers and points-of-interest data is used to analyse the type of services that are likely to concentrate around public transport stations. The results allowed to identify the potential city services to establish partnerships according to the mobility profiles of passengers and the concentration levels of services around public transport stations. © 2019, ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering.

Abstract
Many public transport mobile ticket solutions have arisen but new technologies can face difficulties when launched for a number of reasons that are directly addressed by usability evaluation - a central process in developing usable, hence useful high quality systems with which humans can interact. This paper presents a usability testing performed in context of use of a recently developed public transport mobile ticketing solution for the Metropolitan Area of Porto, Portugal. The objective was to determine if the application is easy to use and navigate for the average user and to generate valuable suggestions for making the app more user-friendly and tasks such as using public transport services and understanding fares quicker and less complicated. Along with problems detected, a list of recommendations by order of importance for improving usability aspects of the mobile application was provided. This study aims to inform developers about usability practices for making mobile ticketing solutions easier to use and stimulate its wider adoption.

Abstract
Intelligent Transportation Systems are an important enabler for the smart cities paradigm. Currently, such systems generate massive amounts of granular data that can be analyzed to better understand people's dynamics. To address the multivariate nature of spatiotemporal urban mobility data, researchers and practitioners have developed an extensive body of research and interactive visualization tools. Data visualization provides multiple perspectives on data and supports the analytical tasks of domain experts. This article surveys related studies to analyze which topics of urban mobility were addressed and their related phenomena, and to identify the adopted visualization techniques and sensors data types. We highlight research opportunities based on our findings.

Abstract
In public transport, smart card-based ticketing system allows to redesign the UPT network, by providing customized transport services, or incentivize travelers to change specific patterns. However, in open systems, to develop personalized connections the journey destination must be known before the end of the travel. Thus, to obtain that knowledge, in this study three models (Top-K, NB, and J48) were applied using different groups of travelers of an urban public transport network located in a medium-sized European metropolitan area (Porto, Portugal). Typical travelers were selected from the segmentation of transportation card signatures, and groups were defined based on the traveler age or economic conditions. The results show that is possible to predict the journey’s destination based on the past with an accuracy rate that varies, on average, from 20% in the worst scenarios to 65% in the best. © 2019, ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering.