Abstract
Pedestrian behaviour modelling and simulation play a fundamental role in reducing traffic risks and new policies implementation costs. However, representing human behaviour in this dynamic environment is not a trivial task and such models require an accurate representation of pedestrian behaviour. Virtual environments have been gaining notoriety as a behaviour elicitation tool, but it is still necessary to understand the validity of this technique in the context of pedestrian studies, as well as to create guidelines for its use. This work proposes a proper methodology for pedestrian behaviour elicitation using virtual reality environments in conjunction with surveys or questionnaires. The methodology focuses on gathering data about the subject, the context, and the action taken, as well as on analyzing the collected data to finally output a behavioural model. The resulting model can be used as a feedback signal to improve environment conditions for experiment iterations. A concrete implementation was built based on this methodology, serving as an example for future studies. A virtual reality traffic environment and two surveys were used as data sources for pedestrian crossing experiments. The subjects controlled a virtual avatar using an HTC Vive and were asked to traverse the distance between two points in a city. The data collected during the experiment was analyzed and used as input to a machine learning model capable of predicting pedestrian speed, taking into account their actions and perceptions. The proposed methodology allowed for the successful data gathering and its use to predict pedestrian behaviour with fairly acceptable accuracy. © 2019 IEEE.

Abstract
LinkedIn is undoubtedly a market leader when it comes to social networks that are aimed for professional use, demonstrating over time that it is a highly valued instrument used by recruiters, as well as a successful way to complement/replace organic recruitment. One of the areas with the most current demand and specific requirements/skills is Information and Communication Technologies (ICT) and, as in all scientific fields, there is a huge focus on recruiting the best candidate in the shortest time possible. The key goals of this article are to understand the relevance of LinkedIn use by an ICT recruiter taking into account the specific requirements/skills often desired by companies, to perceive if ICT students and workers with an updated LinkedIn profile are contacted by recruiters, and comprehend if it is true to say that recruitment via a social network is faster and does not detract from the quality of the hired candidate, compared with organic recruitment. A survey was performed focusing on students and workers in the ICT field and two semi-structured interviews were conducted in a consulting firm as well as in a software house. The results obtained suggest that LinkedIn is an essential recruitment tool for the ICT companies/consulting firms, but it is important to emphasize that most companies combine organic recruitment with LinkedIn recruitment. In our study, 89% of the respondents with an updated LinkedIn account have already been contacted by recruiters, proving that LinkedIn can certainly increase the probability of being hired. © 2019, Springer Nature Switzerland AG.

Abstract
The optical immersion clearing technique has been successfully applied through the last 30 years in the visible to near infrared spectral range, and has proven to be a promising method to promote the application of optical technologies in clinical practice. To investigate its potential in the ultraviolet range, collimated transmittance spectra from 200 to 1000 nm were measured from colorectal muscle samples under treatment with glycerol-water solutions. The treatments created two new optical windows with transmittance efficiency peaks at 230 and 300 nm, with magnitude increasing with glycerol concentration in the treating solution. Such discovery opens the opportunity to develop clinical procedures to perform diagnosis or treatments in the ultraviolet.

Abstract
The modem societies claim on being safer, more sustainable and with more inclusive mobility policies, towards assuring the world sustainable standards. One of the key future mobility factors is focused on the usage of the soft modes, emphasizing the use of bicycles. This mean of transport needs to be permanently implemented worldwide, supported by policies that can unify user's, planners, public and private companies, academics and politicians. Therefore, it is crucial to understanding the user's motivations to adopt the bicycle as a mean of transport instead of the motorized vehicle solutions. With the aim of understanding the user's characteristics, needs and expectations regarding the use of bicycle, as well as to point out innovative initiatives and the role of bicycles in cities' planning, some European examples were analyzed and described as state-of-the-art practices. Such examples allow us to consider and propose a set of adjustments and future recommendations to strengthen the bicycle option as an effective mass mobility mean.

Abstract
Robotics competitions are increasing in complexity and number challenging the researchers, roboticists and enthusiastic to address the robot applications. One of the well-known competition is the micromouse where the fastest mobile robot to solve a maze is the winner. There are several topics addressed in this competition such as robot prototyping, control, electronics, path planning, optimization, among others. A simulation can be used to speed-up the development and testing algorithms but faces the gap between the reality in the dynamics behaviour. In this paper, an open source realistic simulator tool is presented where the dynamics of the robot, the slippage of the wheels, the friction and the 3D visualization can be found. The complete simulator with the robot model and an example is available that allow the users to test, implement and change all the environment. The presented results validate the proposed simulator. © 2019, Springer Nature Switzerland AG.

Abstract
Developing ground robots for crop monitoring and harvesting in steep slope vineyards is a complex challenge due to two main reasons: harsh condition of the terrain and unstable localization accuracy obtained with Global Navigation Satellite System (GNSS). In this context, a reliable localization system requires an accurate detector for high density of natural/artificial features. In previous works, we presented a novel visual detector for Vineyards Trunks and Masts (ViTruDe) with high levels of detection accuracy. However, its implementation on the most common processing units -central processing units (CPU), using a standard programming language (C/C++), is unable to reach the processing efficiency requirements for real time operation. In this work, we explored parallelization capabilities of processing units, such as graphics processing units (GPU), in order to accelerate the processing time of ViTruDe. This work gives a general perspective on how to parallelize a generic problem in a GPU based solution, while exploring its efficiency when applied to the problem at hands. The ViTruDe detector for GPU was developed considering the constraints of a cost-effective robot to carry-out crop monitoring tasks in steep slope vineyard environments. We compared the proposed ViTruDe implementation on GPU using Compute Unified Compute Unified Device Architecture(CUDA) and CPU, and the achieved solution is over eighty times faster than its CPU counterpart. The training and test data are made public for future research work. This approach is a contribution for an accurate and reliable localization system that is GNSS-free.