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Aim To evaluate low back pain (LBP) incidence and impact throughout pregnancy in terms of women’s well-being and delivery outcomes. Material and methods Cross-sectional prospective study conducted on singleton pregnancies at ≥37th gestational age admitted for delivery. Localization of LBP, intensity and frequency as well as derived functional disability status were assessed with a self-reported questionnaire. Main delivery outcomes including mode of delivery, and maternal or neonatal complications were recorded. Results A total of 229 women participated in the study. LBP prevalence amounted to 55.9%, with the pain already present before pregnancy in 14.0% of the cases. The pain was mostly localized in the lower back (40.6%), symphysis (23.3%), and coccyx (20.5%). Both the frequency and intensity of pain gradually increased significantly during pregnancy, reaching 20 days/month (IQR=10–30) and 6/10 points (IQR=5–8) on a visual analog scale in the 3rd trimester (p Conclusions LBP is a common issue in pregnant women, accounting for increasing morbidity and invalidity, and leading to an increased cesarean section risk during labor.

The managed Fog-to-Cloud (mF2C) Project has been funded by the EU Horizon2020 Programme. It has designed and developed a hierarchical and decentralized management architecture for a fog-to-cloud scenario, which is intended to be secure, robust, scalable and efficient. The resulting solution is based on a software agent to be deployed on all computing elements participating to the mF2C system, from cloud to the IoT devices at the edge. Three different use cases have been developed to validate the mF2C architecture. This article describes the third use case, which has been conceived in a typical smart city context such as the Elmas Airport in Cagliari, Italy. The pilot leverages the use of the mF2C technology to setup hubs in the airport capable of tracking the presence of people and other objects, in order to provide value added services on top for proximity marketing, prediction of path/behaviour of consumers, and taking real time decisions. The app provides assistance to all travellers, but is particularly valuable for elderly or disables people, with potential extensions for emergency situations. It gives chance to travellers to discover all facilities of the airport, aided by a recommender system using machine learning, which can make suggestions according with travellers’ preferences or on similarities to other travellers. The final validation in the real-world scenario has given evidence that the adoption of the fog-to-cloud approach brings relevant benefits in terms of performance and optimization of resource usage, thus demonstrating the efficacy of the mF2C technology.

Security and privacy are a concern in many Internet of Things environments, particularly when anyone can connect their device into it.We demonstrate and discuss the security in an airport environment where users are guided to through security, to their flight, or to shops or other points of interest, which in turn should reduce the stress of the user's stay in the airport. The challenge is not just that any user can connect their phone but also to ensure that personal data is handled correctly - in particular, users must be tracked by the infrastructure in order to guide them. Built on a fog-to-cloud platform developed by the Horizon2020-funded mF2C project, we discuss the steps towards a full implementation in a real airport, and the kind of security assessment that is required to persuade an airport to deploy a pervasive user-facing infrastructure without compromising - and hopefully improving - airport security, fulfilling GDPR compliance.

Airports are confusing environments even at the best of times. Recent advances in IoT have made it possible to develop real-time improved traveler assistance tools for mobile phones, which we describe in this paper. These tools will be particularly valuable for the elderly or disabled travelers, or people with other constraints that require assistance, but will be highly valuable also to the seasoned traveler. The tool covers the essential path through the airport onto the flight, but also allows the traveler to fill their waiting time by discovering the facilities of the airport, aided by a recommender system using machinelearning. At the same time the system provides the airport with anonymized user “heat maps” which can highlight congestion and other aggregated data to highlight situations that require intervention, such as emergencies. Initially targeting Android, the app makes use of the fog-to-cloud platform developed by the Horizon2020-funded mF2C project.

BACKGROUND: As an observational science, epidemiology is regarded by some researchers as inherently flawed and open to false results. In a recent paper, Boffetta et al. [Boffetta P, McLaughlin JK, LaVecchia C, Tarone RE, Lipworth L, Blot WJ. False-positive results in cancer epidemiology: a plea for epistemological modesty. J Natl Cancer Inst 100:988-995 (2008)] argued that “epidemiology is particularly prone to the generation of false-positive results.” They also said “the tendency to emphasize and over-interpret what appear to be new findings is commonplace, perhaps in part because of a belief that the findings provide information that may ultimately improve public health” and that “this tendency to hype new findings increases the likelihood of downplaying inconsistencies within the data or any lack of concordance with other sources of evidence.” The authors supported these serious charges against epidemiology and epidemiologists with few examples. Although we acknowledge that false positives do occur, we view the position of Boffetta and colleagues on false positives as unbalanced and potentially harmful to public health. OBJECTIVE: We aim to provide a more balanced evaluation of epidemiology and its contribution to public health discourse. DISCUSSION: Boffetta and colleagues ignore the fact that false negatives may arise from the very processes that they tout as generating false-positive results. We further disagree with their proposition that false-positive results from a single study will lead to faulty decision making in matters of public health importance. In practice, such public health evaluations are based on all the data available from all relevant disciplines and never to our knowledge on a single study. CONCLUSIONS: The lack of balance by Boffetta and colleagues in their evaluation of die impact of false-positive findings on epidemiology, the charge that “methodological vigilance is often absent” in epidemiologists’ interpretation of their own results, and the false characterization of how epidemiologic findings are used in societal decision making all undermine a major source of information regarding disease risks. We reaffirm the importance of epidemiologic evidence as a critical component of the foundation of public health protection.