Abstract
Imbalanced learning is one of the most relevant problems in machine learning. However, it faces two crucial challenges. First, the amount of methods proposed to deal with such problem has grown immensely, making the validation of a large set of methods impractical. Second, it requires specialised knowledge, hindering its use by those without such level of experience. In this paper, we propose the Automated Imbalanced Classification method, ATOMIC. Such a method is the first automated machine learning approach for imbalanced classification tasks. It provides a ranking of solutions most likely to ensure an optimal approximation to a new domain, drastically reducing associated computational complexity and energy consumption. We carry this out by anticipating the loss of a large set of predictive solutions in new imbalanced learning tasks. We compare the predictive performance of ATOMIC against state-of-the-art methods using 101 imbalanced data sets. Results demonstrate that the proposed method provides a relevant approach to imbalanced learning while reducing learning and testing efforts of candidate solutions by approximately 95%.

Abstract
The design and synthesis of artificial receptors based on molecular imprinting (MI) technology for the development of a new MIP-based biosensor for detection of the stress biomarker a-amylase in human saliva in point-of-care (PoC) applications is described in this work. The portable electrochemical devices for monitoring a-amylase consists of cost-effective and disposable gold screen-printed electrodes (AuSPEs). To build the electrochemical device, the template biomolecule was firstly immobilized directly over the working area of the gold chip previously activated with a self-assembled monolayer (SAM) of cysteamine (CA). Then, pyrrole (Py) monomer was selected as building block of a polymeric network prepared by CV electropolymerization. After the electropolymerization process, the enzyme was removed from the polymer film in order to build the specific recognition sites for the target enzyme. The MIP biosensor showed a very wide linear concentration range (between 3.0 × 10-4 to 0.60 mg mL-1 in buffer solution and between 3.0 × 10-4 to 3.0 × 10-2 mg mL-1 in human saliva) and low detection levels were achieved (LOD < 3.0 × 10-4 mg mL-1) using square wave voltammetry (SWV) as the electroanalytical technique.

Abstract
The need to implement a new development dynamic in rural regions has been one of the concerns of the rural tourism sector, which is currently starting its digital transformation process and the adoption of digital technologies and tools. In the light of literature, one of the tools with the greatest promotion potential is digital marketing, since it allows reaching new and larger target audiences more efficiently and effectively. Realizing the lack of a conceptual and functional vision capable of guiding the planning and execution of digital marketing initiatives in the context of rural tourism, this article proposes a conceptual model focused on characterizing the potential impact that digital marketing initiatives can generate, namely in terms of the development of a positive image of the rural tourism destination and of the influence on the tourists' decision to visit.

Abstract
Micro and Small Enterprises have emerged as an important alternative for the generation of jobs and income, mainly in countries that present serious market failures for the creation of productive jobs. However, the lack of commercial and managerial skills, inadequate access to markets, as well as the absence of an entrepreneurial culture has led to a high level of failure in these ventures. Additionally, the current competitive scenario has been increasingly based on innovation, responsible for the destruction of traditional competitive barriers, requiring a new approach on the part of Micro and Small Enterprises to be able to remain in the market sustainably. Accordingly, this research aims to determine the influence that business management has on the degree of innovation of Brazilian Micro and Small Enterprises through Structural Equation Modeling. As a theoretical contribution, the present investigation may point to statistical evidence that may support a causal inference between business management, understood in the present investigation as a decision process on strategic and operational aspects of a business, and the innovation capacity of companies. Furthermore, this research can provide important practical contributions by highlighting the relevance that business management has for Micro and Small Enterprises, also pointing to the need for Micro and Small Enterprises to adopt systematic business management practices that raise their potential concerning the development of innovations and the maintenance of a sustainable competitive position.

Abstract
Due to the pervasiveness of Interconnected devices, large amounts of heterogeneous data types are being continuously collected. Regardless of the benefits that come from sharing data, exposing sensitive and private information arises serious privacy concerns. To prevent unwanted disclosures and, hence, to protect users' privacy, several privacy-preserving mechanisms have been proposed. However, the data heterogeneity and the inherent correlations among the different data types have been disregarded when developing such mechanisms. Our goal is to develop privacy-preserving mechanisms that are suitable for data heterogeneity and data correlation. These aspects will also be considered to develop mechanisms to achieve private learning. © 2021 Owner/Author.

Abstract
Air pollution kills approximately 7 million people every year and nine out of ten people are exposed to high levels of airborne pollutants. This paper describes the design of a bicycle air probe by a team of multicultural and multidisciplinary students of the European Project Semester, during the spring of 2020. This learning experience started with the analysis of the state-of-the-art, ethics, marketing and sustainability dimensions, and was followed by the design, development and simulation of a proof-of-concept solution. The result is GOairLight - a bicycle probe paired with a mobile app. The probe collects air quality, humidity and temperature data as cyclists ride, while the mobile app shares the collected data with the community, by means of a cloud database, presents relevant air quality information and suggests less polluted routes. Furthermore, it relies on a sustainable energy source - a dynamo powered by the cyclist - and automatic lighting. The latter feature improves cyclist visibility and raises the awareness towards the cyclist, contributing to increased road safety.