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.

Abstract
The optical analog of the Vernier effect applied to fiber interferometers is a recent tool to enhance the sensitivity and resolution of optical fiber sensors. This effect relies on the overlap between the signals of two interferometers with slightly detuned interference frequencies. The Vernier envelope modulation generated at the output spectrum presents magnified sensing capabilities (i.e., magnified wavelength shift) compared to that of the individual sensing interferometers that constitute the system, leading to a new generation of highly sensitive fiber sensing devices. This review analyses the recent advances and developments of the optical Vernier effect from a fiber sensing point-of-view. Initially, the fundamentals of the effect are introduced, followed by an extensive review on the state-of-the-art, presenting all the different configurations and types of fiber sensing interferometers used to introduce the optical Vernier effect. This paper also includes an overview of the complex case of enhanced Vernier effect and the introduction of harmonics to the effect.

Abstract
Most oncological cases can be detected by imaging techniques, but diagnosis is based on pathological assessment of tissue samples. In recent years, the pathology field has evolved to a digital era where tissue samples are digitised and evaluated on screen. As a result, digital pathology opened up many research opportunities, allowing the development of more advanced image processing techniques, as well as artificial intelligence (AI) methodologies. Nevertheless, despite colorectal cancer (CRC) being the second deadliest cancer type worldwide, with increasing incidence rates, the application of AI for CRC diagnosis, particularly on whole-slide images (WSI), is still a young field. In this review, we analyse some relevant works published on this particular task and highlight the limitations that hinder the application of these works in clinical practice. We also empirically investigate the feasibility of using weakly annotated datasets to support the development of computer-aided diagnosis systems for CRC from WSI. Our study underscores the need for large datasets in this field and the use of an appropriate learning methodology to gain the most benefit from partially annotated datasets. The CRC WSI dataset used in this study, containing 1,133 colorectal biopsy and polypectomy samples, is available upon reasonable request.