Abstract
The knowledge of hemodynamic behaviour in the abdominal aorta artery bifurcation is of great importance for the early diagnosis of several cardiovascular diseases common in this bifurcation. The work developed focuses on a case study of hemodynamic in the abdominal aorta artery bifurcation, based on a realistic 3D geometric model reconstructed from 2D medical images of a real patient. Hemodynamic quantities based on the wall shear stress (WSS) of the abdominal aorta bifurcation are analysed and is presented an alternative analysis of the well-established stress hemodynamic descriptors to identify specific zones of the artery with a higher probability of developing cardiovascular diseases. The individual analysis of different zones of the artery allowed to obtain information that can remain masked when whole artery is considered as a single zone. The reported results provide a correlation between the analysed stress hemodynamic descriptors and the area of the wall artery. Then, the aim of this work is the identification of regions at the luminal surface subject to atherosusceptible WSS phenotypes. For the patient studied, the analysis presented allowed the identification of the patient's propensity to develop atherosclerosis, according to the hemodynamic descriptors time-averaged WSS (TAWSS), oscillatory shear index (OSI), and relative residence time (RRT). Thus, this work offers a new way of looking to the stress hemodynamic descriptors.

Abstract
Despite its popularity, search engine advertising is a particularly complex and demanding technique. One of the main challenges for Google Ads managers is to adequately monitor performance. Indeed, the literature identifies a plethora of metrics to measure the success of a search engine ads campaign. One research question arises: What are the metrics adopted by small and medium-sized companies to measure the performance of a Google Ads campaign? This chapter includes a mixed-method study with digital marketing professionals experienced in managing Google Ads campaigns for Portuguese SMEs. Interviews helped highlight the main difficulties faced by SEM's Google Ads' managers and to identify the performance measures they mostly control. Then, a survey enabled to analyse the association between performance measures and campaigns' perceived success. The insights produced by this chapter are particularly interesting for researchers, teachers, business managers, and digital marketing professionals, as it presents important clues on measuring the effectiveness of Google Ads campaigns. © 2021, IGI Global.

Abstract

Abstract
The recent pandemic along with the rapid increase in the number of patients that require continuous remote monitoring imposes several challenges to support the high quality of services (QoS) in remote health applications. Remote-health (r-health) systems typically demand intense data collection from different locations within a strict time constraint to support sustainable health services. On the contrary, the end-users with mobile devices have limited batteries that need to run for a long time, while continuously acquiring and transmitting health-related information. Thus, this paper proposes an adaptive deep reinforcement learning (DRL) framework for network selection over heteroge-neous r-health systems to enable continuous remote monitoring for patients with chronic diseases. The proposed framework allows for selecting the optimal network(s) that maximizes the accumulative reward of the patients while considering the patients' state. Moreover, it adopts an adaptive compression scheme at the patient level to further optimize the energy consumption, cost, and latency. Our results depict that the proposed framework outperforms the state-of-the-art techniques in terms of battery lifetime and reward maximization.

Abstract
Digital platforms have, in the past decades, undergone a revolution, evolving from its technical roots so much that nowadays value is mostly generated, not by the technologies that power platforms, but by the ecosystem of applications, developers and users it is able to generate and support. In this paper, we seek to understand the importance industrial platform owners place on the community building and platform growth components of the platform development process by reviewing 50 Horizon 2020 financed projects that stand on the development of platforms. This evidence is leveraged for the case of a validation strategy definition for a platform ecosystem aiming at sharing production capacity. Key findings point to platform developing practices focused on the development of technical components to the detriment of the ecosystem generation element. We also shed light on how different business models and funding schemes impacted the steering of these platforms.

Abstract