Abstract
Ideally, to carry out screening for eye diseases, it is expected to use specialized medical equipment to capture retinal fundus images. However, since this kind of equipment is generally expensive and has low portability, and with the development of technology and the emergence of smartphones, new portable and cheaper screening options have emerged, one of them being the D-Eye device. When compared to specialized equipment, this equipment and other similar devices associated with a smartphone present lower quality and less field-of-view in the retinal video captured, yet with sufficient quality to perform a medical pre-screening. Individuals can be referred for specialized screening to obtain a medical diagnosis if necessary. Two methods were proposed to extract the relevant regions from these lower-quality videos (the retinal zone). The first one is based on classical image processing approaches such as thresholds and Hough Circle transform. The other performs the extraction of the retinal location by applying a neural network, which is one of the methods reported in the literature with good performance for object detection, the YOLO v4, which was demonstrated to be the preferred method to apply. A mosaicing technique was implemented from the relevant retina regions to obtain a more informative single image with a higher field of view. It was divided into two stages: the GLAMpoints neural network was applied to extract relevant points in the first stage. Some homography transformations are carried out to have in the same referential the overlap of common regions of the images. In the second stage, a smoothing process was performed in the transition between images.

Abstract
The Switched Reluctance Generator (SRG) has been widely studied for Wind Energy Conversion Systems (WECS). However, a major drawback of the SRG system adopting the conventional control is the slow response of the DC link voltage controller. In this paper, a Proportional Resonant (PR) control strategy is proposed to control the output voltage of the SRG system to improve the fast response. The SRG model has a high non-linearity, which makes the design of controllers a difficult task. For this reason, the important practical engineering aspect of this work is the role played by the SRG model linearization in testing the sensitivity of the PR controller performance to specific parameter changes. The characteristics of steady-state behaviors of the SRG-based WECS under different control approaches are simulated and compared. The controller is implemented on a digital signal processor (TMS320F28379D). The experimental results are carried out using a 250 W 8/6 SRG prototype to assess the performance of the proposed control compared with the traditional Proportional Integral (PI) control strategy. The experimental results show that the PR control enhances the steady-state performance of the SR power generation system in WECS. Compared to PI control, the rise and settling times are reduced by 45% and 43%, respectively, without an overshoot.

Abstract
Higher Education Institutions use social media as a marketing channel to attract and engage users so that the institution is promoted and thus a wide range of benefits can be achieved. These institutions are evaluated globally on various success parameters, being published in rankings. In this paper, we analyze the publishing strategies and compare the results with their overall ranking positions. The results show that there is a tendency to find a particular strategy in the top ranked universities. We also found cases where the strategies are less prominent and do not match the ranking positions.

Abstract
Underwater autonomous manipulation is the capability of a mobile robot to perform intervention tasks that require physical contact with unstructured environments without continuous human supervision. Being difficult to assess the behaviour of existing motion planner algorithms, this research proposes a new planner evaluation metric to identify well-behaved planners for specialized tasks of inspection and monitoring of man-made underwater structures. This metric is named NEMU and combines three different performance indicators: effectiveness, safety and adaptability. NEMU deals with the randomization of sampling-based motion planners. Moreover, this article presents a benchmark of multiple planners applied to a 6 DoF manipulator operating underwater. Results conducted in real scenarios show that different planners are better suited for different tasks. Experiments demonstrate that the NEMU metric can be used to distinguish the performance of planners for particular movement conditions. Moreover, it identifies the most promising planner for collision-free motion planning, being a valuable contribution for the inspection of maritime structures, as well as for the manipulation procedures of autonomous underwater vehicles during close range operations.

Abstract

Abstract
<p>Volcanic gases and particulate matter (PM) can be hazardous for population not only during an eruptive event, but also during the post-eruption phase, even at significant distances from the volcanic edifice. Volcanic plume dispersion can be affected by diverse factors, such as the weather conditions (<em>e.g</em>., wind speed and direction, rainfall) and/or the topography. Several studies have showed that gas concentrations and PM impacts on the quotidian life during a volcanic crisis can be significant, highlighting the importance of setting up permanent monitoring systems.</p><p>Instruments with carbon dioxide (CO<sub>2</sub>), sulphur dioxide (SO<sub>2</sub>)<sub></sub>and particulate matter (PM<sub>2.5</sub> and PM<sub>10</sub>) low-cost sensors were developed in order to easily and continuously monitor any volcanic area, and the 2021 Cumbre Vieja eruption was chosen as test site to deploy and validate the instrumentation. A network of nine instruments was set up around the volcanic eruption site, covering both the north and south areas of the lava flows, at distances varying between 1.6 and 7 km from the volcano craters. Five instruments were designed to work autonomously in the field, powered by batteries, and the electrical network powered the other four sensors. All nine instruments broadcasted the recorded data via LoRa communication.</p><p>The network settled after the 9<sup>th</sup> December 2021, closer to the ending of the eruptive period, recorded maximum CO<sub>2</sub> concentrations of 1585 ppm at station named “Perm-2”, located at about 4.8 km distance from the volcanic craters, on the 21<sup>st</sup> December 2021. Regarding particulate matter, even if the 24 hour-mean standards set by the World Health Organization (WHO) for the PM<sub>2.5</sub> and PM<sub>10</sub> (25 mg/m<sup>3</sup> and 50 mg/m<sup>3</sup>, respectively) were not exceeded during the monitored period, maximum concentrations were also recorded for these two parameters (470 and 874 mg/m<sup>3</sup>) at “Perm-2” in the 21<sup>st</sup> December. For the same period, the station located closer to the volcano craters measured maximum SO<sub>2</sub> concentrations of 1.11 ppm. Maximum PM values were recorded also at other two monitoring sites in the same day, suggesting spatial and temporal correlation between the different parameters. In this particular case, and considering that maximum concentrations were registered during the night in the exclusion zone, one can reject the potential association of the measured values with suspended ashes resulting from sweeping and cleaning activities. For other periods, particularly after the ending of the eruption, this association must be considered. The highest concentrations of particles post-eruption were measured in the 31<sup>st</sup> December 2021 and 3<sup>rd</sup> January 2022.</p><p>The installed instruments seem to be adequate for an easier and faster deploy during a volcanic crises, allowing recognizing the presence of hazardous gas and particulate matter concentrations, crucial to reduce potential health effects on the population, even after the end of the eruptive phase.</p>