Abstract
For the past years, the interest in the use of Unmanned Aerial Vehicles (UAVs) has been increasing due to the multiple research topics provided by the field of aerial robotics. Conversely, vehicles are susceptible to failures or malfunctions. Consequently, one main emergent research topic is the detection of a safe landing spot in these emergency scenarios. Therefore, this paper exposes and details the multiple techniques that attempt to solve the problem of landing site detection. This paper aims to present the current literature with several sensors that can be used to solve the aforementioned problem. Finally, the paper presents our proposed approach with some preliminary results in simulation. © CLAWAR Association Ltd.

Abstract
This article was written to study and understand how social networks have changed the way we perceive and create relationships. The exponential increase of social media (SM) has become not only convenient, but also a common habit. It has changed people’s habits and brought a new way of being since the technology era arrived. Although there are several advantages in using these social networks, the uncontrolled use and abuse can be alarming, thus the importance of this research. There are plenty of papers related to the impact of social media on adolescent behaviour and on young people’s academic performance. However, this paper aims to examine the facts and provides a comparison of the effect of social media use between different age sectors: adolescents (between 10 and 17 years old), young adults (18–30), adults (31–45), older adults (46–65) and seniors (+66). In order to explore this issue, an online survey was developed. Using a sample of 358 participants, social media use was analysed by age sectors, focusing on the dependence, habits, the reasons/motivations for people to have these accounts, and how different generations perceive the future of social media. © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2020.

Abstract
The extraction of collagen from fish skins is being proposed as strategy for valorization of marine origin by-products, being a sustainable alternative to mammal collagen. The method commonly uses solutions of organic acids, but new methodologies are arising, aiming to improve process yields and/or the properties of the resulting products. In this work, skins removed from salt brine Atlantic cod (Gadus morhua) were used to extract collagen, using water acidified with CO2, obtaining an extraction yield of 13.8% (w/w). Acidified water extracted collagen (AWC) presented a total content of proline-like amino acids of 151/1000 residues, with a degree of hydroxylation of 38%, and its SDS-PAGE profile is compatible with type I collagen. Moreover, FTIR, CD and XRD results suggest the presence of preserved triple helix, having a denaturation temperature of 32.3 degrees C as determined by micro-DSC. AWC exhibited a typical shear thinning behavior, interesting regarding their further processing, namely in jelly-like formulations. Additionally, the presence of AWC in MRC-5 human fibroblasts culture did not affect cell viability, demonstrating the non-cytotoxic behavior. Overall, the results support the efficiency of the proposed approach for collagen extraction and further enable the design of methodologies to address AWC use in biomedical or cosmetic context.

Abstract
Objectives: To describe baseline clinical characteristics of adult patients with COVID-19. Methods: We conducted a scoping review of the evidence available at LitCovid, until March 23th, 2020, and selected articles that reported the prevalence of socio-demographic characteristics, symptoms and co-morbidities in adults with COVID-19. Results: In total, 1 572 publications were published on LitCovid. We have included 56 articles in our analysis, with 89% conducted in China, and 75% contained inpatients. Three studies were conducted in North America and one in Europe. Participants age ranged from 28 to 70 years, with balanced gender distribution. Proportion of asymptomatic cases were from 2 to 79%. The most common reported symptoms were fever [4-99%], cough [4-92%], dyspnoea/shortness of breath [1-90%], fatigue 4-89%], myalgia [3-65%], and pharyngalgia [2-61%], while regarding co-morbidities we found cardiovascular disease [1-40%], hypertension [0-40%] and cerebrovascular disease [1-40%]. Such heterogeneity impairs the conduction of meta-analysis. Conclusions: The infection by COVID-19 seems to affect people in a very diverse manner and with different characteristics. With the available data it is not possible to clearly identify those at higher risk of being infected with this condition. Furthermore, the evidence from countries other than China is, at the day, too scarce.

Abstract
Online applications now routinely replicate their data at multiple sites around the world. In this paper we present ATLAS, the first state-machine replication protocol tailored for such planet-scale systems. ATLAS does not rely on a distinguished leader, so clients enjoy the same quality of service independently of their geographical locations. Furthermore, clientperceived latency improves as we add sites closer to clients. To achieve this, ATLAS minimizes the size of its quorums using an observation that concurrent data center failures are rare. It also processes a high percentage of accesses in a single round trip, even when these conflict. We experimentally demonstrate that ATLAS consistently outperforms state-of-the-art protocols in planet-scale scenarios. In particular, ATLAS is up to two times faster than Flexible Paxos with identical failure assumptions, and more than doubles the performance of Egalitarian Paxos in the YCSB benchmark.

Abstract
Today’s cloud computing techniques are becoming unsustainable for real time applications as very low latency is required with billions of connected devices. New paradigms are arising; the one that offers an integrated solution for extending cloud resources to the edge of the network and addresses current cloud issues is Fog Computing. Performing Fog Computing brings a set of challenges such as: provisioning edge nodes to perform task volumes downloaded from the Cloud; placing task volumes on edge nodes; resource management on edge nodes; need for a new programming model; programming, resource management, data consistency service discovery challenges; privacy and security and improving the quality of service (QoS) and user experience (QoE). This paper aims at introducing the Fog Computing concept and it presents a literature review on the way it is applied: context-sensitive applications and context-sensitive mobile service platforms. The result of the study is presented as the current research challenges for context aware mobile applications in Fog Computing infrastructure.