Abstract
The planning and design of sustainable and smart cities—cities of the future—should properly address the challenges that arise by the every day growth of the urban population. Mobility is an important issue considering social inclusion and the sustainable development of such cities. Thus, future mobility will have an increased importance when having to plan and design the cities of tomorrow. A key component of any future mobility and its metabolism is what is known as Mobility as a Service (MaaS), representing emerging opportunities from any type or mode of transportation in future cities. Through an empirical and explorative research methodology, this chapter presents the main issues and characteristics that any future MaaS should consider. Concluding, some features and trends are presented that should be considered in the development of future MaaS systems, allowing a more convenient provision of sustainable, versatile and attractive mobility services. © 2020, Springer Nature Switzerland AG.

Abstract
In this work, we combined electrochemical techniques with SPR (eSPR) for the label-free detection of cancer biomarker miRNA-145. Detection was performed in a simple two-step assay. In the first step, the gold sensor surface, previously functionalized with a self-assembled monolayer (SAM) of thiolated RNA probes is incubated with the sample containing the target RNA biomarker. In this step, hybridization of RNA fragments with complementary immobilized probes was monitored in real-time by SPR. In the second step, eSPR measurements were performed to improve the sensitivity of the hybridization assay. Potential-induced deposition of a redox probe at the sensor surface resulted in enhanced SPR response promoted by the electrochemical process, thereby allowing the detection of miRNA-145 at femtomolar level (LOD = 0.56 fM), without sample derivatization or post-hybridization treatment for signal amplification. Good linearity was achieved (R-2 = 0.984) over the concentration range from 1.0 fM and 10 nM. Furthermore, the developed eSPR biosensor showed high selectivity towards single-base and two-base mismatch sequences and detection of target miRNA-145 in synthetic human serum was successful achieved.

Abstract
This work reports for the first efforts in establishing the operational conditions necessary for converting a Direct Glucose Fuel Cell (DGFC) into a Molecularly Imprinted Polymer (MIP) based electrochemical autonomous biosensor. Electrochemical studies were performed in a typical three electrodes system besides Anion and Proton Exchange Membrane (AEM and PEM) fuel cells, applying voltammetric and Electrochemical Impedance Spectroscopy (EIS) techniques. Promissory results were obtained for the PEM-DGFC that revealed potential to be converted into a biosensor. Further studies are ongoing by resourcing to MIP technology to convert the PEM-DGFC into an electrochemical sensor for cancer biomarkers.

Abstract
Wiki-based crowdsourced data sources generally lack reliability, as their provenance is not intrinsically marshalled. By using recommendation, one may arguably assess the reliability of wiki-based repositories in order to identify the most interesting articles for a given domain. In this commentary, we explore current trends in scalable modelling and recommendation methods based on side information such as the quality and popularity of wiki articles. The systematic parallelization of such profiling and recommendation algorithms allows the concurrent processing of distributed crowdsourced Wikidata repositories. These algorithms, which perform incremental updating, need further research to improve the performance and generate up-to-date high-quality recommendations. This article builds upon our previous work (Leal et al., 2019) by extending the literature review and identifying important trends and challenges pertaining to crowdsourcing platforms, particularly those of Wikidata provenance.

Abstract
The application of feature engineering in classification problems has been commonly used as a means to increase the classification algorithms performance. There are already many methods for constructing features, based on the combination of attributes but, to the best of our knowledge, none of these methods takes into account a particular characteristic found in many problems: causality. In many observational data sets, causal relationships can be found between the variables, meaning that it is possible to extract those relations from the data and use them to create new features. The main goal of this paper is to propose a framework for the creation of new supposed causal probabilistic features, that encode the inferred causal relationships between the target and the other variables. In this case, an improvement in the performance was achieved when applied to the Random Forest algorithm.

Abstract
In rural destinations like Douro region, tourism activities may be important to territories’ development because they use some of their natural resources and endogenous products, develop another related local economy business, and contributes to population fixation. Technologies can support the promotion and distribution of these destinations, namely digital marketing tools. The present study aims to analyze the influence that some of these tools perceived usefulness, from the tourist point of view, have on a rural destination image. To accomplish this, it was used a sample of 555 tourists visiting Douro destination and data collected were analyzed using structural equation modeling. The results demonstrated that tourist’s trust in tourism digital marketing tools and their attitude toward these tools have an indirect effect on destination image. Moreover, the perceived usefulness of some digital marketing tools utilized to search, plan or purchase Douro destination, as website, booking and mobile devices, has also a positive effect on this destination image. On another hand, the perceived usefulness of a conventional channel, as travel agencies, has a negative effect on this rural destination image. This research provided some interesting insights for practitioners working in tourism destination marketing.