Abstract

Abstract
In the areas of machine-learning/big data, feature selection is normally regarded as a very important problem to be solved, as it directly impacts both data analysis and model creation. The problem of optimizing the selected features of a given dataset is not always trivial, however, throughout the years various ways to counter this optimization problem have been presented. This work presents how feature-selection fits in the larger context of multi-objective problems as well as a review of how both multi-objective evolutionary algorithms and metaheuristics are being used in order to solve feature selection problems.

Abstract
For some years now, master data has become extremely relevant to business success and continuity in an increasingly competitive and global business environment. The banking sector is one example of how the implementation of well-structured and designed master data management policies and initiatives is crucial for reaching positive results. One of the areas in which banks need to ensure extremely fruitful master data management approaches and data governance procedures is when dealing with risk-related data, as it not only ensures accurate and well-supported management and decision-making, but also because banks are required to do so by imposed regulations, such as the BCBS 239. Drawing on a DSR methodology supported research project, where banking and IS-related expertise was continuously merged with existing theoretical knowledge on MDM and BCBS 239 related topics, and a permanent focus on the technical and functional complexity associated with implementing master data management and well-established data governance procedures that ensure regulatory compliance, we propose a novel, six-phase action plan that will allow banks to ensure compliance with BCBS 239 and, consequently, ensure efficient and effective risk data management and reporting.

Abstract
(1) Background: Initiatives aimed at assessing and intervening in health literacy have the potential to promote adherence to self-care behaviours, which is the main focus of intervention by rehabilitation nurses. Thus, the objectives were to analyse the level of health literacy of working-age citizens and identify priority areas for intervention by rehabilitation nurses. (2) Methods: Quantitative, correlational and cross-sectional study, conducted in a multinational company, with the participation of 161 workers. The data were collected between 14 April and 7 May 2021, using a self-completion questionnaire composed of sociodemographic and clinical characterization and the European Health Literacy Survey, following a favourable opinion from the Ethics Committee and the company's management. (3) Results: Overall, low to moderate literacy scores were predominant. Age and education were significantly associated with literacy scores. Workers with higher levels of health literacy had no diagnosed illnesses, took less medication, reported less sadness, fewer memory changes and less muscle and joint pain. (4) Conclusions: The fact that higher levels of health literacy trigger self-care behaviours and, consequently, fewer health problems reinforces the need for rehabilitation nurses to invest in this area.

Abstract
The ongoing outbreak of SARS-CoV-2 has been deeply impacting health systems worldwide. In this context, it is pivotal to measure the efficiency of different nations' response to the pandemic, whose insights can be used by governments and health authorities worldwide to improve their national COVID-19 strategies. Hence, we propose a network Data Envelopment Analysis (DEA) to estimate the efficiencies of fifty-five countries in the current crisis, including the thirty-seven Organisation for Economic Co-operation and Development (OECD) member countries, six OECD prospective members, four OECD key partners, and eight other countries. The network DEA model is designed as a general series structure with five single-division stages - population, contagion, triage, hospitalisation, and intensive care unit admission -, and considers an output maximisation orientation, denoting a social perspective, and an input minimisation orientation, denoting a financial perspective. It includes inputs related to health costs, desirable and undesirable intermediate products related to the use of personal protective equipment and infected population, respectively, and desirable and undesirable outputs regarding COVID-19 recoveries and deaths, respectively. To the best of the authors' knowledge, this is the first study proposing a cross-country efficiency measurement using a network DEA within the context of the COVID-19 crisis. The study concludes that Estonia, Iceland, Latvia, Luxembourg, the Netherlands, and New Zealand are the countries exhibiting higher mean system efficiencies. Their national COVID-19 strategies should be studied, adapted, and used by countries exhibiting worse performances. In addition, the observation of countries with large populations presenting worse mean efficiency scores is statistically significant.

Abstract
In order to promote sound management of research data the European Commission, under the Horizon 2020 framework program, is promoting the adoption of a Data Management Plan (DMP) in research projects. Despite the value of a DMP to make data findable, accessible, interoperable and reusable (FAIR) through time, the development and implementation of DMPs is not yet a common practice in health research. Raising the awareness of researchers in small projects to the benefits of early adoption of a DMP is, therefore, a motivator for others to follow suit. In this paper we describe an approach to engage researchers in the writing of a DMP, in an ongoing project, FrailSurvey, in which researchers are collecting data through a mobile application for self-assessment of fragility. The case study is supported by interviews, a metadata creation session, as well as the validation of recommendations by researchers. With the outline of our process we also outline tools and services that supported the development of the DMP in this small project, particularly since there were no institutional services available to researchers