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Higher education system has a critical role to play in educating environmentally aware and participant citizens about global climate change (CC). And, as shown by the 21st Conference of the Parties of the UN Convention on Climate Change – COP 21, held in Paris in December 2015, there is still a path to be followed regarding the role played by universities in the negotiations and in influencing decision-making on a matter of such global importance. The purpose of this first study conducted within Portuguese (Europe), Mexican (Spanish-speaking North America University) and Mozambican (Africa) universities is to investigate higher education system students’ perceptions on CC.

The data were collected through a questionnaire aiming at characterising students from the socio-demography, and from their perceptions, motivations, attitudes and knowledge relating to the topic of CC. Statistical analysis was used to compare and characterise the three national groups under study.

This study did not show significant perception differences among the analysed subsamples, although there was a tendency for Mexican students to express lesser belief that CC was happening, and for Mozambicans to show a greater belief in CC issues and motivation to mitigate its effects which may be related to the specifics contexts. The results show that relevant differences among nationalities mostly concerned the magnitude of choices (e.g. most respondents of each nationality expressed interest in CC issues, but the magnitude of this expression differed according to nationality). The principal component analysis (second and third components) clearly embodied nationality profiles (discussed in the context of different cultures, educational structures and CC impacts).

Further research is warranted to understand the integration of CC into higher education curriculum to improve and target educational efforts to suit students’ needs.

How CC perceptions vary cross-nationally and how research studies that examine the integration of CC into higher education curriculum are areas for which more research is needed.

The results highlight the importance of socio-cultural dimensions of each country in relation to the understanding or perception of CC issues, namely, in what concerns aspects related with gender roles, age, active learning and citizenship. This study’s data evidenced that despite the surveyed students being familiarized with CC phenomena, this knowledge does not translate necessarily into concrete mitigation practices and behaviours.

The development of models that allows the evaluation and prediction of erosion processes is an important tool for the management and planning of coastal systems. Mangrove forests systems are under threat by the impacts of erosion, which is also intensified by human activity (and aggravated in the scenarios of global warming and climate change). The purpose of this paper is to develop a model of geographic information systems (GIS) that can be used for any estuary area, but it can also be used for mangroves.

This paper uses georeferentiation which is defined as a set of parameters that best characterize the mangrove areas: elevation (m); geomorphology; geology; land cover; anthropogenic activities; distance to the coastline (m) and maximum tidal range (m). Three different methods are used to combine the various vulnerability parameters, namely, DRASTIC index, analytical hierarchy process (AHP) and square root of the geometric mean.

The three approaches presented in this work show different types evaluating vulnerability to erosion, highlighting a stronger overvaluation of the areas presented with a high vulnerability, through the use of DRASTIC index when compared with two other approaches. The use of the AHP shows similarity to the square root of the geometric mean model, but the AHP also presents a higher percentage of vulnerable areas classified as having medium to very high vulnerability. On the other hand, the use of square root of the geometric mean led to a higher percentage of areas classified as having low and very low vulnerability.

These three qualitative models, based on a cognitive approach, using the set of parameters defined in this research, are a good tool for the spatial distribution of erosion in different mangroves in the world.

Global warming and climate change scenarios require adaptation and mitigation options supported by science-based strategies and solutions.

The purpose of this paper is to propose a new scheme for obtaining acceptable solutions for problems of continuum topology optimization of structures, regarding the distribution and limitation of discretization errors by considering h-adaptivity.

The new scheme encompasses, simultaneously, the solution of the optimization problem considering a solid isotropic microstructure with penalization (SIMP) and the application of the h-adaptive finite element method. An analysis of discretization errors is carried out using an a posteriori error estimator based on both the recovery and the abrupt variation of material properties. The estimate of new element sizes is computed by a new h-adaptive technique named “Isotropic Error Density Recovery”, which is based on the construction of the strain energy error density function together with the analytical solution of an optimization problem at the element level.

Two-dimensional numerical examples, regarding minimization of the structure compliance and constraint over the material volume, demonstrate the capacity of the methodology in controlling and equidistributing discretization errors, as well as obtaining a great definition of the void–material interface, thanks to the h-adaptivity, when compared with results obtained by other methods based on microstructure.

This paper presents a new technique to design a mesh made with isotropic triangular finite elements. Furthermore, this technique is applied to continuum topology optimization problems using a new iterative scheme to obtain solutions with controlled discretization errors, measured in terms of the energy norm, and a great resolution of the material boundary. Regarding the computational cost in terms of degrees of freedom, the present scheme provides approximations with considerable less error if compared to the optimization process on fixed meshes.

Financial education has become an essential component of the economic balance for families, and much is being discussed about the methods, which raise the levels of financial education of the population. Thus, the overall objective of this study was to evaluate the effect of formal and business education on the level of financial education.

This research is characterized as a quasi-experimental study, with undergraduate students. As a data collection technique, a structured questionnaire was used.

The results confirm the importance of formal and business education, as well as gender, for the financial education of individuals. More specifically, being male and having contact with a greater number of financial disciplines increase the level of financial education of the individual.

This article demonstrated that the trajectory of the knowledge traversed by individuals within the same level of schooling is of paramount importance. The results show that formal and business education can improve the levels of financial education and reinforce the relevance of strategic actions in this area.

A sustainable transportation system should represent a win-win situation: minimizing transport's impact on the environment and reducing natural disasters' effects on transportation. A well-distributed set of rain gauges is crucial for monitoring services in smart cities. However, those services should consider the uncertainties about the registers of rainfall impacts. In this paper, the authors present a case study of optimal rain gauge location based on an actual database of rainfall events with impacts on urban mobility in the city of Sao Paulo (Brazil).

This paper presents a maximal covering location formulation and proposes a robustness analysis considering spatial location perturbations.

In this case study, the robustness of the objective function is above 99.99%. The robustness for the number of covered demand points is 88.93%, and the frequency associated with every candidate is between 11.71% and 69.49%.

Incorporating spatial uncertainties on coverage problems is essential to provide stakeholders more realistic supporting tools and to draw different possible scenarios.