Abstract
The segmentation of retinal vessels in fundus images has been heavily focused in the past years, given their relevance in the diagnosis of several health conditions. Even though the recent advent of deep learning allowed to foster the performance of computer-based algorithms in this task, further improvement concerning the detection of vessels while suppressing background noise has clinical significance. Moreover, the best performing state-of-the-art methodologies conduct patch-based predictions. This, put together with the preprocessing techniques used in those methodologies, may hinder their use in screening scenarios. Thus, in this paper, we explore a fully convolutional setting that takes raw fundus images and allows to combine patch-based training with global image prediction. Our experiments on the DRIVE, STARE and CHASEDB1 databases show that the proposed methodology achieves state-of-the-art performance in the first and the last, allowing at the same time much faster segmentation of new images.

Abstract
A buildings resilience to seismic activity can be increased by providing ways for the structure to dynamically counteract the effect of the Earth's crust movements. This ability is fundamental in certain regions of the globe, where earthquakes are more frequent, and can be achieved using different strategies. State-of-the-art anti-seismic buildings have, embedded on their structure, mostly passive actuators such as base isolation, Tuned Mass Dampers (TMD) and viscous dampers that can be used to reduce the effect of seismic or even wind induced vibrations. The main disadvantage of this type of building vibration reduction strategies concerns their inability to adapt their properties in accordance to both the excitation signal or structural behaviour. This adaption capability can be promoted by adding to the building active type actuators operating under a closed-loop. However, these systems are substantially larger than passive type solutions and require a considerable amount of energy that may not be available during a severe earthquake due to power grid failure. An intermediate solution between these two extremes is the introduction of semi-active actuators such as magneto-rheological dampers. The inclusion of magneto-rheological actuators is among one of the most promising semi-active techniques. However, the overall performance of this strategy depends on several aspects such as the actuators number and location within the structure and the vibration sensors network. It can be the case where the installation leads to a non-collocated system which presents additional challenges to control. This paper proposes to tackle the problem of controlling the vibration of a non-collocated three-storey building by means of a brain-emotional controller tuned using an evolutionary algorithm. This controller will be used to adjust the stiffness coefficient of a magneto-rheological actuator such that the building's frame oscillation under earthquake excitation, is mitigated. The obtained results suggest that, using this control strategy, it is possible to reduce the building vibration to secure levels.

Abstract
The sense of presence is an important aspect of experiences in Virtual Reality (VR), an emerging technology in education, leading this construct to be increasingly researched in parallel to learning purposes. However, there is not a consensus in the literature on the outcomes of this association. Aiming to outline a panorama in this regard, a systematic literature review was conducted, with a comprehensive analysis of 140 primary studies recovered from five worldwide databases. The analysis shows an overview of 24 years of areas, factors, and methodological approaches that seem to be more inclined to benefit from the sense of presence toward learning purposes. We contribute to the advancement of state of the art by providing an understanding of the relationship among these variables, identifying potential ways to benefit from the sense of presence to further leverage the use of VR for learning purposes.

Abstract
Many of the developments started by social initiatives (bottom-up), others are induced by policies (top-down) or even by both (social and political). Open Design is mainly characterized as a movement generated by and for the community but could also be nourished by private/associative initiatives with the community support, and could be encourage by public entities that perceives Open Design as a flourish method for innovation and leading for a real democratization of the manufacturing. In this paper, three CAD software based on Open Design (rattleCAD, BRL CAD and FreeCAD) are evaluated, according to the number of downloads made in SourceFourge, in order to better understand the usage behavior of these CAD systems. The main findings suggest instability in the short range and stability in the medium and long range, indicating that the communities are active and providing attractive solutions. (C) 2019 The Authors. Published by Elsevier B.V.

Abstract
The literature on gait analysis in Vascular Parkinsonism (VaP), addressing issues such as variability, foot clearance patterns, and the effect of levodopa, is scarce. This study investigates whether spatiotemporal, foot clearance and stride-to-stride variability analysis can discriminate VaP, and responsiveness to levodopa. Fifteen healthy subjects, 15 Idiopathic Parkinson's Disease (IPD) patients and 15 VaP patients, were assessed in two phases: before (Off-state), and one hour after (On-state) the acute administration of a suprathreshold (1.5 times the usual) levodopa dose. Participants were asked to walk a 30-meter continuous course at a self-selected walking speed while wearing foot-worn inertial sensors. For each gait variable, mean, coefficient of variation (CV), and standard deviations SDI and SD2 obtained by Poincare analysis were calculated. General linear models (GLMs) were used to identify group differences. Patients were subject to neuropsychological evaluation (MoCA test) and Brain MRI. VaP patients presented lower mean stride velocity, stride length, lift-off and strike angle, and height of maximum toe (later swing) (p < .05), and higher %gait cycle in double support, with only the latter unresponsive to levodopa. VaP patients also presented higher CV, significantly reduced after levodopa. Yet, all VaP versus IPD differences lost significance when accounting for mean stride length as a covariate. In conclusion, VaP patients presented a unique gait with reduced degrees of foot clearance, probably correlated to vascular lesioning in dopaminergic/non-dopaminergic cortical and subcortical non-dopaminergic networks, still amenable to benefit from levodopa. The dependency of gait and foot clearance and variability deficits from stride length deserves future clarification.

Abstract
In this study, an optical signal recording method for optogenetics stimulation of ChR2 channels expressed in human pulp dental (HPD) cells by using a fiber optic refractive index (RI) sensor based on all fiber Mach-Zehnder interferometer was proposed. All-fiber Mach-Zender interferometric biosensor is composed of a specially fabricated twin-core fiber spliced between two pieces of a single-mode fiber which one of the cores was doped with germanium and the other with phosphorous [1]. The interference pattern in the fiber Mach-Zehnder interferometer is occurred by coupling of the propagation lights of both fiber cores. For coupling the light into both cores, a short length of a coreless fiber optic was used. The length of twin-core fiber was 40 cm. Here, one core of the fiber acts as a reference arm and the other cores as sensing arm. For increasing evanescent wave around the sensing arm of the fiber optic biosensor, a short section of the cladding of the twin-core fiber about 2 cm was etched with HF solution. For this propose, after determining the direction of the cores so that the two cores were in the vertical direction, one side of the twin-core fiber was fixed on Plexiglas substrate by using UV glow and the upper side of the sensor was etched. The thickness of remained clad around the upper core was about 1 micrometer. In the experimental setup as is shown in Fig. 1(a), light from an SLD at 1550 nm after passing an isolator arrived at the sensor and output spectrum was monitored with an optical spectrum analyzer which has 10 pm wavelength resolution. The best RI sensitivity of the sensor in the range of 1.39 to 1.43 was obtained to be 675.74 nm/RIU. For detecting of cell signal by using optogenetic stimulation which ChR2 opsin was expressed on HPD cells, it needs that high concentrations of cells were immobilized to the etched fiber surface by PLL biopolymer. Optogenetic stimulation of ChR2 channel was done using a 470 nm laser diode [2] pulse with a frequency of 15 Hz, a number of pulses 120, duty cycle 50 in 60 seconds, and 300 second rest time. As a result of optogenetic stimulation and activation of light-sensitive ion channels, effective RI around the fiber optic biosensor changes [3]. Obtained results were shown in Fig. 1(b). Changes in the RI lead to a wavelength shift of the sensor spectrum. © 2019 IEEE.