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
Integrate-and-fire (IFN) model of a biological neuron is an amplitude-to-time conversion technique that encodes information in the time-spacing between action potentials (spikes). In principle, this encoding scheme can be used to modulate signals in an impulse radio ultra wide-band (IR-UWB) transmitter, making it suitable for low-power applications, such as in wireless sensor networks (WSN) and biomedical monitoring. This paper then proposes an architecture based on IFN encoding method applied to a UWB transceiver scenario, referred to herein as impulse-radio integrate-and-fire (IRIF) transceiver, followed by a system-level study to attest its effectiveness. The transmitter is composed of an integrate-and-fire modulator, a digital controller and memory block, followed by a UWB pulse generator and filter. At the receiver side, a low-noise amplifier, a squarer, a low-pass filter and a comparator form an energy-detection receiver. A processor reconstructs the original signal at the receiver, and the quality of the synthesized signal is then verified in terms of effective number of bits (ENOB). Finally, a link budget is performed. (C) 2019 Published by Elsevier GmbH.

Abstract
This paper describes the implementation of an end-to-end Internet of Things (IoT) solution, focusing specifically in the multi-protocol sensor node with LoRaWAN and Wi-Fi connectivity options (Pycom's FiPy). A performance assessment will be presented, addressing a comparison between the different protocols (LoRaWAN vs. Wi-Fi) in terms radio coverage, timing issues, among others. Further, it will be investigated the integration onto the sensor node of sensor/actuator circuit blocks for energy metering, supported on Microchip's ATM90E26 single-phase meter. This will provide a practical use case in the field of Industry 4.0, leading to preliminary insights for power quality monitoring. © 2019 IEEE.

Abstract
When the COVID-19 pandemic hits Portugal in early March 2020, medical doctors, engineers and researchers, with the encouragement of the Northern Region Health Administration, teamed up to develop and build, locally and in a short time, a ventilator that might eventually be used in extreme emergency situations in the hospitals of northern Portugal. This letter tells you the story of Pneuma, a low-cost emergency ventilator designed and built under harsh isolation constraints, that gave birth to derivative designs in Brazil and Morocco, has been industrialized with 200 units being produced, and is now looking forward to the certification as a medical device that will possibly support a go-tomarket launch. Open intellectual property (IP), multi disciplinarity teamwork, fast prototyping and product engineering have shortened to a few months an otherwise quite longer idea-to-product route, clearly demonstrating that when scientific and engineering knowledge hold hands great challenges can be successfully faced.

Abstract
The technological market is increasingly evolving as evidenced by the innovative and streamlined manufacturing processes. Printed Circuit Boards (PCB) are widely employed in the electronics fabrication industry, resorting to the Gerber open standard format to transfer the manufacturing data. The Gerber format describes not only metadata related to the manufacturing process but also the PCB image. To be able to map the electronic circuit pattern to be printed, a parser to convert Gerber files into a bitmap image is required. The current literature as well as available Gerber viewers and libraries showed limitations mainly in the Gerber format support, focusing only on a subset of commands. In this work, the development of a recursive descent approach for parsing Gerber files is described, outlining its interpretation and the renderization of 2D bitmap images. All the defined commands in the specification based on Gerber X2 generation were successfully rendered, unlike the tested commercial parsers used in the experiments. Moreover, the obtained results were comparable to those parsers regarding the commands they can execute as well as the ground-truth, emphasizing the accuracy of the proposed approach. Its top-down and recursive architecture allows easy integration with other software regardless of the platform, highlighting its potential inclusion and integration in the production of electronic circuits.

Abstract