Abstract
The interest of using light in clinical practice is increasing strongly and many applications work at various wavelengths from the ultraviolet to the infrared. Due to this great range of applications, the determination of the optical properties of biological tissues in a wide spectral range becomes of interest. The liver is an important organ, since it has a major role in the human body and various pathologies are known to develop within it. For these reasons, this study concerns the estimation of the optical properties of human normal and pathological (metastatic carcinoma) liver tissues between 200 and 1000 nm. The obtained optical properties present the expected wavelength dependencies for both tissues - the refractive index, the absorption and the scattering coefficients decrease with the wavelength and the anisotropy and light penetration depth increase with the wavelength. Although similar behavior was observed for the various properties between the normal and pathological tissues, evidence of smaller blood content in the pathological tissues was found. A possible explanation is that the cancer cells destroy liver's vasculature and internal architecture, providing though a reduction in the blood content. For low wavelengths, it was observed a matching between the scattering and the reduced scattering coefficients, which implies a nearly zero anisotropy in that range. The scattering coefficient decreases from nearly 140 cm(-1) (at 200 nm) to 80 cm(-1) (at 1000 nm) for the normal liver and from nearly 140 cm(-1) (at 200 nm) to 95 cm(-1) (at 1000 nm) for the pathological tissue.

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
We study the time-variable linear polarisation of Sgr A* during a bright near-infrared flare observed with the GRAVITY instrument on July 28, 2018. Motivated by the time evolution of both the observed astrometric and polarimetric signatures, we interpret the data in terms of the polarised emission of a compact region ("hotspot") orbiting a black hole in a fixed, background magnetic field geometry. We calculated a grid of general relativistic ray-tracing models, created mock observations by simulating the instrumental response, and compared predicted polarimetric quantities directly to the measurements. We take into account an improved instrument calibration that now includes the instrument's response as a function of time, and we explore a variety of idealised magnetic field configurations. We find that the linear polarisation angle rotates during the flare, which is consistent with previous results. The hotspot model can explain the observed evolution of the linear polarisation. In order to match the astrometric period of this flare, the near horizon magnetic field is required to have a significant poloidal component, which is associated with strong and dynamically important fields. The observed linear polarisation fraction of similar or equal to 30% is smaller than the one predicted by our model (similar or equal to 50%). The emission is likely beam depolarised, indicating that the flaring emission region resolves the magnetic field structure close to the black hole.

Abstract
The adoption of serious games as a complement to traditional classroom training is still an emerging theme, but it offers relevant potentialities for both students and teachers. This study describes the integration process of serious games in an entrepreneurship course over five years (2014-2018). In the first three years, the ENTRExplorer was adopted, while in the last two years the FLIGBY was used. The experience of using entrepreneurship serious games is analyzed according to multiple perspectives, such as complexity, generation of more entrepreneurial or group working skills, engagement, interactivity, learning outcomes, or even the impact on the intention to establish a new venture. The findings allowed a comparative analysis of the two games, indicating significant differences in some of those dimensions. Nevertheless, the learning outcomes provided by each game were considered relevant by the students, showing that both games can be useful in the process of learning and acquiring entrepreneurship competencies.

Abstract
The many well-established advantages of distributed generation (DG) make their usage in active distribution networks prevalent. However, uncontrolled operation of DG units can negatively interfere with the performance of other equipment, such as tap-changers, in addition to resulting in sub-optimal usage of their potential. Thus, adequate scheduling/control of DG units is critical for operators of the distribution system to avoid those adverse effects. A linearised model of a multi-objective method for coordinating the operation of photovoltaics, battery storage systems, and tap-changers is proposed. Three objective functions are defined for simultaneously enhancing voltage profile, minimising power losses, and reducing peak load power. The formulated multi-objective problem is solved by means of the epsilon-constraint technique. A novel decision-making methodology is offered to find the Pareto optimality and select the preferred solution. To assess to proposed model's performance, it is tested using 33-bus IEEE test system. Consequently, tap-changers suffer lessened stress, the batteries state-of-charge is kept within adequate limits, and the DG units operation is at higher efficiency. The obtained results verify the effectiveness of this approach.

Abstract
Fault-tolerance is a core feature in distributed database systems, particularly the ones deployed in cloud environments. The dependability of these systems often relies in middleware components that abstract the DBMS logic from the replication itself. The highly configurable nature of these systems makes their throughput very dependent on the correct tuning for a given workload. Given the high complexity involved, machine learning techniques are often considered to guide the tuning process and decompose the relations established between tuning variables. This paper presents a machine learning mechanism based on reinforcement learning that attaches to a hybrid replication middleware connected to a DBMS to dynamically live-tune the configuration of the middleware according to the workload being processed. Along with the vision for the system, we present a study conducted over a prototype of the self-tuned replication middleware, showcasing the achieved performance improvements and showing that we were able to achieve an improvement of 370.99% on some of the considered metrics. © IFIP International Federation for Information Processing 2020.