Abstract
Assessing the societal contributions of research is not simple, especially for research projects that produce outputs with low technology readiness level. This paper analyses the potential societal impacts of research resulting in technologies with low maturity, but with the potential to be further developed in the long-term. It uses the case of the ESGRIDS (Enhancing Smart Grids for Sustainability) collaborative research project and its outputs aimed at enhancing smart grids for sustainability. Data was collected from the four participant research teams through two sequential questionnaires about technologies' state of development and expected long-term societal effects. Among the main results, we underscore the influence of individual perceptions and organisational contexts over the process of eliciting future developments. The analysis of technologies' status, barriers for market uptake, and potential future developments was translated into a technology roadmap, which outlined the time-dimension for technology maturity evolution and implementation impacts. The technologies developed within the ESGRIDS project can contribute to support consumers' energy decision-making and to encourage them to have a more active role in the electricity market. Those technologies can also create job opportunities associated with the development of new products and services, and contribute to mitigating climate change by promoting the use of renewable energies thus reducing carbon dioxide emissions, in addition to contributing to energy cost reduction by optimizing the use of supply and demand resources. Future research avenues point towards a methodology that can be used for assessing the potential impacts of research projects with low technology readiness outputs.

Abstract
Imaging the spatial distribution of chemical elements at a sample surface is a common application of laserinduced breakdown spectroscopy with vast scientific and technological applications. Yet, typical imaging solutions only explore the creation of two-dimensional maps, which can limit the interpretability of the results and further diagnostics in three-dimensional settings. Within this context, this work explores the combination of spectral imaging techniques and photogrammetry to deploy a versatile solution for the creation of threedimensional spectral imaging models. First, by making use of a numerical algorithm that is able to match features in the spectral image with those of the three-dimensional model, we show how to match the mesh from distinct sensor modalities. Then, we describe a possible visualization workflow, making use of dedicated photogrammetry and visualization software to easily deploy interactive models. Overall, the results demonstrate the versatility of our approach and pave for the development of novel spectral imaging diagnostic strategies that are able to deliver better qualitative analysis and insight in the three-dimensional space.

Abstract

Abstract
Centro de Reabilitacao Profissional de Gaia (CRPG) is a Portuguese public association that promotes the social, educational, occupational, and rehabilitation aspects of people with disabilities. The CRPG project presented in this paper is directly related to the Rehabilitation and reintegration of labor accidents and occupational diseases (RAC/LCA) victims. The solution presented in this paper heavily relied on user research of the institution's procedures and the patients themselves. Their habits, goals, needs, and mental models allowed a better understanding of the heterogeneity of patient's injuries, which usually affected memory, motion, and cognition in different ways and severity. The User Centered-Design methodological approach also encompasses a comparative analysis of mobile applications in Google Play and Apple App Store related to disabilities and features some main features identified by CRPG; interviews with patients and with CRPG stakeholders; personas and contextual scenarios development, requirements, and features definition, workflow, wireflows, lo and high fidelity prototype, formative evaluation with end users. The usability and accessibility test results suggest the viability and efficacy of multiple interaction modalities in improving the accessibility of the application, ensuring a broader reach to the CRPG community with future implications as good practices in the inclusiveness of applications in other contexts.

Abstract
Tension remains between the observed and modeled properties of substellar objects, but objects in binary orbits, with known dynamical masses, can provide a way forward. HD 72946 B is a recently imaged brown dwarf companion to a nearby, solar-type star. We achieve similar to 100 mu as relative astrometry of HD 72946 B in the K band using VLTI/GRAVITY, unprecedented for a benchmark brown dwarf. We fit an ensemble of measurements of the orbit using orbitize! and derive a strong dynamical mass constraint M B = 69.5 +/- 0.5 M Jup assuming a strong prior on the host star mass M A = 0.97 +/- 0.01 M circle dot from an updated stellar analysis. We fit the spectrum of the companion to a grid of self-consistent BT-Settl-CIFIST model atmospheres, and perform atmospheric retrievals using petitRADTRANS. A dynamical mass prior only marginally influences the sampled distribution of effective temperature, but has a large influence on the surface gravity and radius, as expected. The dynamical mass alone does not strongly influence retrieved pressure-temperature or cloud parameters within our current retrieval setup. Independently of the cloud prescription and prior assumptions, we find agreement within +/- 2 sigma between the C/O of the host (0.52 +/- 0.05) and brown dwarf (0.43-0.63), as expected from a molecular cloud collapse formation scenario, but our retrieved metallicities are implausibly high (0.6-0.8) in light of the excellent agreement of the data with the solar-abundance model grid. Future work on our retrieval framework will seek to resolve this tension. Additional study of low surface gravity objects is necessary to assess the influence of a dynamical mass prior on atmospheric analysis.

Abstract
We consider a continuous lifetime model for investor whose lifetime is a random variable. We assume the investor has an access to the social welfare system, the financial market and the life insurance market. The investor aims to find the optimal strategies that maximize the expected utility obtained from consumption, investing in the financial market, buying life insurance, registering in the social welfare system, the size of his estate in the event of premature death and the size of his fortune at time of retirement if he lives that long. We use dynamic programming techniques to derive a second-order nonlinear partial differential equation whose solution is the maximum objective function. We use special case of discounted constant relative risk aversion utilities to find an explicit solutions for the optimal strategies. Finally, we have shown a numerical solution for the problem under consideration and study some properties for the optimal strategies.