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.

Abstract
This study aims to evaluate the implications of the use of maritime pine non-debarked wood chips as an alternative solid fuel in industrial boilers in Portugal, highlighting the energy properties and chemical composition of the produced ash. Several samples are collected from different sources, on which a proximate analysis is carried out in order to determine the volatile matter content, fixed carbon content, ash content and higher heating value (HHV). The chemical composition of the ash samples is determined by the scanning electron microscope (SEM) method. Then, empirical indices were used to assess the utilization of the ash and its tendency to create slagging and fouling deposits in industrial boilers during the combustion process. It was concluded from the obtained results that the use of maritime pine non debarked wood chips can significantly contribute to the formation of slagging and fouling phenomena in industrial boilers. These phenomena will be responsible for a higher number of technical stoppages of the equipment and for an increase in maintenance costs.

Abstract
Recently, crowdsourcing platforms have been used to solve problems in the field of urban planning by involving crowds of citizens in performing tasks. However, the success of this approach is directly related to how work is managed. The goal of the present study is to make a broad characterization of work management in crowdsourcing approaches applied to urban planning through a systematic literature review. More specifically, we aim to investigate aspects related to the quality of work

Abstract
Sentiment analysis is a set of techniques that deal with the verification of sentiment and emotions in written texts. This introductory work aims to explore the combination of scores and polarities of sentiments (positive, neutral and negative) provided by different sentiment analysis tools. The goal is to generate a final score and its respective polarity from the normalization and arithmetic average scores given by those tools that provide a minimum of reliability. The texts analyzed to test our hypotheses were obtained from forum posts from participants in a massive open online course (MOOC) offered by Universidade Aberta de Portugal, and were submitted to four online service APIs offering sentiment analysis: Amazon Comprehend, Google Natural Language, IBM Watson Natural Language Understanding, and Microsoft Text Analytics. The initial results are encouraging, suggesting that the average score is a valid way to increase the accuracy of the predictions from different sentiment analyzers. © Springer Nature Switzerland AG 2019.

Abstract
A robust method is presented for evaluating the diffusion properties of chemicals in ex vivo biological tissues. Using this method that relies only on thickness and collimated transmittance measurements, the diffusion properties of glycerol, fructose, polypropylene glycol and water in muscle tissues were evaluated. Amongst other results, the diffusion coefficient of glycerol in colorectal muscle was estimated with a value of 3.3 x 10(-7) cm(2)/s. Due to the robustness and simplicity of the method, it can be used in other fields of biomedical engineering, namely in organ cryoprotection and food industry.