Abstract
Root cause analysis (RCA) is the process through which we find the true cause of a problem. It is a crucial process in manufacturing, as only after finding the root cause and addressing it, it is possible to improve the manufacturing operation. However, this is a very time-consuming process, especially if the amount of data about the manufacturing operation is considerable. With the increase in automation and the advent of Industry 4.0, sensorization of manufacturing environments has expanded, increasing with it the data available. The conjuncture described gives rise to the challenge and the opportunity of automatizing root cause analysis (at least partially), making this process more efficient, using tools from data mining and machine learning to help the analyst find the root cause of a problem. This paper presents an overview of the literature that has been published in the last 17 years on developing automatic root cause analysis (ARCA) solutions in manufacturing. The literature on the topic is disperse and it is currently lacking a connecting thread. As such, this study analyzes how previous studies developed the different elements of an ARCA solution for manufacturing: the types of data used, the methodologies, and the evaluation measures of the methods proposed. The proposed conceptualization establishes the base on which future studies on ARCA can develop results from this analysis, identifying gaps in the literature and future research opportunities.

Abstract
Implementation of information and communication technologies (ICTs) in education is defined as the incorporation of ICTs into teaching and learning activities, both inside and outside the classroom. Despite widely studied, there is still no consensus on how it affects student performance. However, before evaluating this, it is crucial to identify which factors impact students' use of ICT for educational purposes. This understanding can help educational institutions to effectively implement ICT, potentially improving student results. Thus, adapting the conceptual framework proposed by Biagi and Loi (2013) and using the 2018 database of the Program for International Student Assessment (PISA) and a decision tree classification model developed based on CRISP-DM framework, we aim to determine which socio-demographic factors influence students' use of ICT for educational purposes. First, we categorized students according to their use of ICT for educational purposes in two situations: during lessons and outside lessons. Then, we developed a decision tree model to distinguish these categories and find patterns in each group. The model was able to accurately distinguish different levels of ICT adoption and demonstrate that ICT use for entertainment and ICT access at school and at home are among the most influential variables to predict ICT use for educational purposes. Moreover, the model showed that variables related to teaching best practices of Internet utilization at school are not significant predictors of such use. Some results were found to be country-specific, leading to the recommendation that each country adapts the measures to improve ICT use according to its context.

Abstract
A área de conhecimento associada à gestão de ativos potencia a extração de valor de ativos físicos, incorporando uma abordagem integrada que envolve riscos, custos e desempenho. Este trabalho propõe uma nova abordagem para selecionar projetos de investimento em infraestruturas no âmbito da gestão de ativos. A métrica padrão utilizada para a seleção de projetos em ativos múltiplos é o Índice de Valor de Infraestruturas (IVI), que tem sido utilizado para caracterizar ativos do setor de águas em diversos países. Este trabalho desenvolveu dois modelos de programação linear inteira mista. O primeiro modelo de otimização trata de um problema de alocação de orçamento de capital selecionando projetos de investimento com vista à maximização da condição dos ativos. O segundo modelo de otimização trata de um problema de planeamento de orçamento, visando minimizar o capital necessário para manter os ativos nas condições desejadas. A aplicação dos modelos é ilustrada por um estudo de caso de uma empresa que opera no setor da água em Portugal. Os resultados obtidos nos diferentes cenários analisados são discutidos com vista a apoiar o desenho de políticas de gestão de ativos mais eficientes.

Abstract
The Strategic Framework for European Cooperation in Education and Training (ET 2020) aimed to pro-mote the exchange of best practices among the Member States. This paper assesses the performance evo-lution of European countries in terms of the common objectives for the education sector. The framework used to evaluate European education systems is based on constructing a composite indicator adopting a benefit-of-the-doubt approach. The evaluation of performance change over time is done using a Global Malmquist Index. Sigma and beta convergence of EU countries are also explored using non-parametric frontier techniques. The results are analysed for the period 2009-2018 and discussed in light of the goals envisaged and the national policies adopted. The results revealed a trend of improvement in the perfor-mance of education systems in most European countries in the period analysed. Although most European countries moved closer to the European best practice frontier over time, as confirmed by the values of sigma-convergence, a few countries are still lagging considerably below their peers, as revealed by the existence of divergence in beta.(c) 2022 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license ( http://creativecommons.org/licenses/by-nc-nd/4.0/ )

Abstract
Assessing the evolution of the performance of water supply and sanitation services is essential to monitor progress towards the universalization of water services, as specified by the Sustainable Development Goal 6 of Agenda 2030, adopted by United Nations member countries. Brazil, a developing country with a continental size and geographical diversity, will face significant challenges to achieve this goal. The main objective of this paper is to evaluate the evolution of productivity of water supply and sanitation services in Brazilian municipalities in the period 2012-2019. The analysis also explores whether water services' performance is balanced across the country, with a specific analysis of performance at the macroregion level. From a methodological perspective, this research evaluates productivity change over time using a Malmquist Productivity Index estimated with a metafrontier, satisfying the circularity property. It also develops a pseudo Malmquist index that compares productivity levels across macro-regions. The results revealed a productivity loss of approximately 4% at the national level, with an unequal profile across the macro-regions. The Southeast municipalities stand out for exhibiting, on average, higher productivity levels than the South and Northeast municipalities.

Abstract
Decent Work Agenda consists of a comprehensive initiative for promoting safety at work and social protection. Over 20 years since its conceptual release, measuring the progress of its elements is still challenging even after the publication of the decent work indicators guideline by the International Labour Organization in 2012. To close this gap, we use a Directional Distance Function (DDF) to measure the efficiency of safe work environment, and propose a combined measure taking into consideration also the efficacy. To illustrate the application of DDF in a reality-based case, we conducted a longitudinal study in a multinational organization. Data were collected from 21 branches of the company over 4 years (2018-2021). In the period of analysis, 60% of the branches were efficient in average, composing an overall efficiency score of 0.91. Our results also indicated low dispersion between the efficiency scores year on year due to a small-scale interquartile range. Finally, the use of efficiency combined with efficacy resulted in a promising approach for managerial applications. This research presents some contributions. One is the novelty approach of measuring the efficiency of safe work environment using a DDF model in a real-world application. Another is the managerial benefits of identifying benchmarks, as well as revealing potential improvements as a mechanism to reduce decent work deficits. From a modeling perspective, our conclusions suggest caution in considering only efficiency to measure safe work environment due to its relative nature. Thus, further studies are recommended to explore the use of combined measures in the analysis of decent work.