Abstract
A growing interest in ocean exploration for scientific and commercial research has been shown, mainly due to the technological developments for maritime and offshore industries. The use of Autonomous surface vehicles (ASV) have a promising role to revolutionize the transportation, monitorization, operation and maintenance areas, allowing to perform distinct task from offshore assets inspection to harbor patrolling. This work presents SENSE, an autonomouS vEssel for multi-domaiN inSpection and maintEnance. It provides an open-source hardware and software architecture that is easy to replicate for both research institutes and industry. This is a multi-purpose vehicle capable of acquiring multi-domain data for inspecting and reconstructing maritime infrastructures. SENSE provides a research platform which can increase the situational awareness capabilities for ASVs. SENSE full configuration provides multimodal sensory data acquired from both domains using a Light Detection And Ranging (LiDAR), a stereoscopic camera, and a multibeam echosounder. In addition, it supplies navigation information obtained from a real-time kinematic satellite navigation system and inertial measurement units. Moreover, the tests performed at the harbor of Marina de Leca, at Porto, Portugal, resulted in a dataset which captures a fully operational harbor. It illustrates several conditions on maritime scenarios, such as undocking and docking examples, crossings with other vehicles and distinct types of moored vessels. The data available represents both domains of the maritime scenario, being the first public dataset acquired for multi-domain observation using a single vehicle. This paper also provides examples of applications for navigation and inspection on multi-domain scenarios, such as odometry estimation, bathymetric surveying and multi-domain mapping.

Abstract
In the last few decades, Portugal has witnessed an extraordinary quantitative and qualitative transformation in housing provision. The pace of housing construction was so extensive that the contemporary real estate market is currently characterized by an excessive supply, vis-a-vis the resident population. In this study, we discuss the impact of the financial process on the housing sector in comparison with tenancy. We consider transaction prices of the housing assignments, either through acquisition or through tenancy. The recent shock resulting from the pandemic situation did not slow down house prices but caused a slight drop in rents. The model used proposes to analyze the fluctuations in prices and rents in the face of external shocks. In the residential market, the estimation is complex due to the many heterogeneous attributes of residential assets. Non-fluctuating variables, such as size, location, and external demand for homes, explain a large part of the variation in price levels included in the model.

Abstract
For space-based Earth Observations and solar system observations, obtaining both high revisit rates (using a constellation of small platforms) and high angular resolution (using large optics and therefore a large platform) is an asset for many applications. Unfortunately, they prevent the occurrence of each other. A deployable satellite concept has been suggested that could grant both assets by producing jointly high revisit rates and high angular resolution of roughly 1 meter on the ground. This concept relies however on the capacity to maintain the phasing of the segments at a sufficient precision (a few tens of nanometers at visible wavelengths), while undergoing strong and dynamic thermal gradients. In the constrained volume environment of a CubeSat, the system must reuse the scientific images to measure the phasing errors. We address in this paper the key issue of focal-plane wave-front sensing for a segmented pupil using a single image with deep learning. We show a first demonstration of measurement on a point source. The neural network is able to identify properly the phase piston-tip-tilt coefficients below the limit of 15nm per petal.

Abstract
This research aims at investigating which web accessibility and usability tools, with the focus on the ones that warrant automation, are available to assess the quality of interfaces for people with disabilities and/or special needs, enabling them to navigate and interact with web and mobile apps. Our search strategy identified 72 scientific articles of the most rated conferences and scientific journals, from which 16 were considered for the systematic literature review (SLR). We found that, despite the existence of various tools either for web or mobile apps, they are not completely effective, covering less than 40% of all the problems encountered. Also, no tool was found capable of adapting the application interfaces according to the type of disabilities that users may present. Therefore, a new tool could be a welcome advancement to provide full accessible and usable experiences.

Abstract
This study presents and applies in vivo lower limb frequency response analysis during standard maximum vertical jump (MVJ) with long and short counter movement (CM) and corresponding muscle stretch shortening cycle (SSC) for comparison without CM and SSC condition. The study makes use of algebraic relation at the frequency domain to obtain the response function from the input and output signals. Single-input/single-output (SI/SO) constant parameter linear system (CPLS) was applied with vertical ground reaction force (GRFz) input and center of gravity (CG) vertical displacement (Delta z) output, obtaining lower limb frequency response function during MVJ impulse phase. Piecewise linearity and limited input-output range of experimentally acquired GRFz and CG Delta z during MVJ impulse phase were assessed to confirm assumptions for CPLS application. Piecewise stationarity of the input and output signal was ensured by acquiring those signals on each MVJ type at similar conditions, guaranteeing experimental repetitions under statistical similar conditions on each CM. Different CM condition on each MVJ type were compared as regards to maximum vertical height, time period of the impulse phase, fundamental harmonic frequencies, convergence of the GRFz input and CG Delta z output Fourier series, their autospectral and cross-spectral density, as well as its input-output coherence, cross-spectrum gain factor, and phase of the frequency response function. Several differences were detected among CM condition, potentially contributing to explain differences on achieved performances at each CM and SSC.

Abstract
This paper presents a new framework for the scheduling of microgrids and distribution feeder reconfiguration (DFR), taking into consideration the uncertainties due to the load demand, market price, and renewable power generation. The model is implemented on the modified IEEE 118-bus test system, including microgrids and smart homes. The problem has been formulated as a two-stage model, which at the first stage, the day-ahead self-scheduling of each microgrid is carried out as a two-objective optimization problem. The two objectives include the minimization of the total operating cost and maximization of the consumer's comfort index. Then, the solution, obtained from the first stage is delivered to the distribution system operator (DSO). Then, at the second stage, the DSO determines the optimal configuration of the system with the aim of minimizing operating costs of the main grid and the penalty of deviating from microgrid scheduling. Note that the penalty is due to the difference in power exchange requested by the microgrids from the power exchange finalized by the DSO. The presented two-stage optimization problem is modeled in a mixed-integer linear programing (MILP) framework with four case studies, and solved in GAMS by using the GURUBI solver. The simulation results show that in the cases the DSO is able to reconfigure the system, the deviation from the optimal scheduling of microgrids would be considerably lower than the cases with fixed system configuration.