Abstract
Genealogy studies are growing in popularity, and researchers are increasingly using visualization methods to summarize and communicate their findings. A family tree is a visual representation of family members and their relationships that is commonly used to support the research of a family's history and publish the results. In some cases, an ancestor may occur in more than one place in the lineage of an individual, which is one of the reasons for the occurrence of consanguineous marriages, that is, marriages between blood relative spouses. Current methods for family tree visualization were not designed to analyze and assess the level of consanguinity in the ancestry of individuals. This paper proposes VisAC, an interactive tool to support the visual analysis of consanguinity in individuals' ancestry. The inbreeding coefficient is used as a measure of consanguinity. The coefficient corresponds to an estimate of the probability that two alleles (a variant of a given gene) in the DNA were inherited from the same individual. A visualization design and an interactive tool were developed with genealogists' support. In addition, the feedback collected through a questionnaire about two demo videos and tests with three target users strongly supports the effectiveness of the family tree visual representation and the adequacy of the interactive tool for the exploratory analysis task. Real-world examples are given to illustrate the usefulness of the visualization design, and an example of exploratory analysis is presented to illustrate the use of the interactive tool. In summary, this work formulates the task of visual analysis of consanguinity in ancestors' trees and proposes VisAC, a new visualization tool to support the task.

Abstract
The fast-changing behaviour of people in metropolitan areas is creating several challenges to local authorities in managing the urban space. These changes are strongly related to the evolution of technology and its adoption by companies and citizens. Current regulations need, therefore, to be rapidly updated to respond to the new urban dynamics. However, the gap between local authorities and citizens and the communication difficulties are increasing as urban centres grow, creating obstacles to innovation and hindering the deployment of new mobility solutions. The low levels of participation in public consultation actions decrease the quality of new policies, as well as their acceptance by the community. Not only do cities need to be reinvented, but local authorities also need to rethink how to interact with citizens, competing for attention in a digital world. Although digital tools are easily accessible, they are not available to everyone, and municipalities need to consider both digital and non-digital interactions to ensure that all citizens can participate. In this work, we analyse and compare a set of measures that municipalities have been adopting to increase citizens' engagement, and we develop a methodology to help local authorities increase public participation and improve citizens' commitment towards the city.

Abstract
The transport sector plays a fundamental role in the European Union economy and its efficiency is fundamental to strengthen the region's environmental and economic performance. Unfortunately, the sector still remains heavily dependent on oil resources and is responsible for a large part of the air pollution. The European Union has been promoting various initiatives towards sustainable transport development by setting targets in the sector such as the ones proposed in the 2011 White Paper on transport. Under this context, this study aims at evaluating the environmental performance of the transport sector in 28 European Union countries, from 2015 to 2018, towards the policy agenda established in the strategic documents. The assessment of the transport environmental performance is made through the aggregation of seven sub-indicators into a composite indicator using a Data Envelopment Analysis technique. A variant of the Benefit of the Doubt model is used to determine the weights to aggregate the sub-indicators. The results obtained indicate that the European Union countries have been improving their transport environmental performance in the last two years of the time span under analysis, i.e., 2017 and 2018. Regarding the inefficient countries, results suggest they should improve the transport sustainability mainly by drastically reducing the greenhouse gas emissions from fossil fuel-based propulsion, increasing the share of freight transport using rail and inland waterways and also the share of transport energy from renewable sources.

Abstract
As part of the ongoing climate and energy framework, the European Commission raised recently the 2030 greenhouse gas emission reduction target, moving towards a climate-neutral economy. Transportation represents almost a quarter of Europe’s greenhouse gas emissions, and it is the remaining sector with increasing emissions, above 1990 levels. Considering also the evolving necessity for the reduction of fossil fuels dependency, Europe’s strategy has been designed to support an irreversible shift toward low-emission electric mobility. In this context, the present work assesses the performance of electric mobility in European countries, by using a dynamic analysis in the period 2015–2019, framed in four sustainable dimensions, economy, technology, environment and society. The methodology aggregates several sub-indicators in a composite indicator by using the Data Envelopment Analysis, and evaluates the dynamic change in the sustainable performance through the biennial Malmquist index. Main results indicate that the total productivity change has been improved mainly due to the progression of the frontier that has been observed for all countries from 2018. However, an increasing number of countries have had more difficulties to adopt the best sustainable electric mobility practices, being necessary to design strategies to promote them, mainly in underperforming countries. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Abstract
Global climate changes and the increase in average temperatures are some of the major contemporary problems that have not been considered in the context of external factors to increase accident risk. Studies that include climate information as a safety parameter in machine learning models designed to predict the occurrence of accidents are not usual. This study aims to create a dataset with the most relevant climatic elements, to get better predictions. The results will be applied in future studies to correlate with the accident history in a retail sector company to understand its impact on accident risk. The information was collected from the National Oceanic and Atmospheric Administration (NOAA) climate database and computed by a wrapper method to ensure the selection of the most features. The main goal is to retain all the features in the dataset without causing significant negative impacts on the prediction score. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Abstract
Predicting the performance of a mixture is crucial to designing experiences in product development and formulation research. In this work, an application, MDesign, is proposed to construct models in a mixture design with a practical, educational, and intuitive approach. Developed in MATLAB software, the standalone application aims to contribute to the study of mixtures through the definition of multivariate models of different orders, enabling their statistical analysis to verify the robustness of each of those models. Compared to the obtained results from other applications using data experiments published in the literature, the proposed application presents accurate results and good execution. MDesign can be considered an automatic, robust, and valuable tool to support the mixture design in an industrial context.