Abstract
Purpose Considering the differences between rural and urban spaces, through the theoretical framework developed, the purpose of this paper is to uncover and rationalize the differences between rural and urban new ventures in terms of the environment surrounding the new venture, their general characteristics (e.g. sector, size) and export/economic performance. Design/methodology/approach The theoretical framework is empirically assessed resorting to exploratory statistical analysis based on data collected from a questionnaire survey responded by 408 new ventures headquartered in Portuguese business incubators and science parks. The data collected were treated with the Software Package for the Social Sciences. Findings The results evidence that rural and urban new ventures differ in terms of generic characteristics, namely sector, size and collaborators' human capital. Additionally, they differ concerning export and economic performance as well in relation to the perception of the municipality support. Originality/value The present study innovatively contributes to uncover the role of rural and urban context in entrepreneurship and adds to the scanty empirical literature in the area.

Abstract
Literature has highlighted the challenges of selling experience (vs. search) products online. In addition, the role of celebrity endorsers in purchase intention and attitudes towards brands has been emphasized by scholars. This article argues that celebrities provide cues on products' sensorial characteristics that have been so far disregarded by extant literature. By choosing perfume as a complex experience product, twenty-seven participants from three countries were interviewed in order to find how endorsers could assist e-shoppers to identify fragrant characteristics in the absence of the real scent. The results of the qualitative content analysis reveal that endorsers' personality traits and lifestyle could act as predictor of the type of scent. Scent categorization based on such traits are presented. This article provides valuable contributions to both researchers and practitioners interested in online sales of experience goods. Limitations and avenues for future search are also provided.

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Abstract
The growth in Internet usage has increased the use of electronic services requiring users to register their identity on each service they subscribe to. This has resulted in the prevalence of redundant users data on different services. To protect and regulate access by users to these services identity management systems (IdMs) are put in place. IdMs uses frameworks and standards e.g SAML, OAuth and Shibboleth to manage digital identities of users for identification and authentication process for a service provider. However, current IdMs have not been able to address privacy issues (unauthorised and fine-grained access) that relate to protecting users identity and private data on web services. Many implementations of these frameworks are only concerned with the identification and authentication process of users but not authorisation. They mostly give full control of users digital identities and data to identity and service providers with less or no users participation. This results in a less privacy enhanced solutions that manage users available data in the electronic space. This article proposes a user-centred mandate representation system that empowers resource owners to take full of their digital data; determine and delegate access rights using their mobile phone. Thereby giving users autonomous powers on their resources to grant access to authenticated entities at their will. Our solution is based on the OpenID Connect framework for authorisation service. To evaluate the proposal, we've compared it with some related works and the privacy requirements yardstick outlined in GDPR regulation [1] and [2]. Compared to other systems that use OAuth 2.0 or SAML our solution uses an additional layer of security, where data owner assumes full control over the disclosure of their identity data through an assertion issued from their mobile phones to authorisation server (AS), which in turn issues an access token. This would enable data owners to assert the authenticity of a request, while service providers and requestors also benefit from the correctness and freshness of identity data disclosed to them.

Abstract
Lung cancer is among the deadliest diseases in the world. The detection and characterization of pulmonary nodules are crucial for an accurate diagnosis, which is of vital importance to increase the patients’ survival rates. The segmentation process contributes to the mentioned characterization, but faces several challenges, due to the diversity in nodular shape, size, and texture, as well as the presence of adjacent structures. This paper proposes two methods for pulmonary nodule segmentation in Computed Tomography (CT) scans. First, a conventional approach which applies the Sliding Band Filter (SBF) to estimate the center of the nodule, and consequently the filter’s support points, matching the initial border coordinates. This preliminary segmentation is then refined to include mainly the nodular area, and no other regions (e.g. vessels and pleural wall). The second approach is based on Deep Learning, using the U-Net to achieve the same goal. This work compares both performances, and consequently identifies which one is the most promising tool to promote early lung cancer screening and improve nodule characterization. Both methodologies used 2653 nodules from the LIDC database: the SBF based one achieved a Dice score of 0.663, while the U-Net achieved 0.830, yielding more similar results to the ground truth reference annotated by specialists, and thus being a more reliable approach. © Springer Nature Switzerland AG 2019.