Abstract
The 2015-2030 agenda framed Sustainable Development as a Universal venture. This decision has a great historic significance as it encompasses building a better future for the whole of humanity, enrolling the millions who have been denied the chance to live a decent, dignified and fulfilling life and to achieve their potential. For the first time, an entire generation will have the chance to succeed in ending poverty while being the last to have a chance of saving the planet. The world will be a better place in 2030 if humanity succeeds in this journey. However, there is hovering skepticism around the feasibility of this accomplishment. The article aims to empirically test the (in)compatibilities among these objectives even for developed economies such as the European Union countries, demonstrating that unless solid bridges are built promoting innovative networks at a transnational level, welfare and prosperity among those ecosystems will be compromised. The results show that the Sustainable Development Goals (SDG) pillars have heterogeneous determinants, which are to some extent incompatible. Moreover, policy makers need to further reinforce multi-country compensations if the environment is to be preserved.

Abstract
Many models have been proposed for the location-allocation problem. In this study, based on sectorization concept, we propose a new single-objective model of this problem, in which, there is a set of customers to be assigned to distribution centres (DCs). In sectorization problems there are two important criteria as compactness and equilibrium, which can be defined as constraints as well as objective functions. In this study, the objective function is defined based on the equilibrium of distances in sectors. The concept of compactness is closely related to the accessibility of customers from DCs. As a new approach, instead of compactness, we define the accessibility of customers from DCs based on the covering radius concept. The interpretation of this definition in real life is explained. As another contribution, in the model, a method is used for the selection of DCs, and a comparison is made with another method from the literature, then the advantages of each are discussed. We generate benchmarks for the problem and we solve it with a solver available in Python’s Pulp library. Implemented codes are presented in brief.

Abstract
About 160 years ago, the concept of entropy was introduced in thermodynamics by Rudolf Clausius. Since then, it has been continually extended, interpreted, and applied by researchers in many scientific fields, such as general physics, information theory, chaos theory, data mining, and mathematical linguistics. This paper presents The Entropy Universe, which aims to review the many variants of entropies applied to time-series. The purpose is to answer research questions such as: How did each entropy emerge? What is the mathematical definition of each variant of entropy? How are entropies related to each other? What are the most applied scientific fields for each entropy? We describe in-depth the relationship between the most applied entropies in time-series for different scientific fields, establishing bases for researchers to properly choose the variant of entropy most suitable for their data. The number of citations over the past sixteen years of each paper proposing a new entropy was also accessed. The Shannon/differential, the Tsallis, the sample, the permutation, and the approximate entropies were the most cited ones. Based on the ten research areas with the most significant number of records obtained in the Web of Science and Scopus, the areas in which the entropies are more applied are computer science, physics, mathematics, and engineering. The universe of entropies is growing each day, either due to the introducing new variants either due to novel applications. Knowing each entropy's strengths and of limitations is essential to ensure the proper improvement of this research field.

Abstract
The ability to operate virtually anywhere and carry payload makes Unmanned Aerial Vehicles (UAVs) perfect platforms to carry communications nodes, including Wi-Fi Access Points (APs) and cellular Base Stations (BSs). This is paving the way to the deployment of flying networks that enable communications to ground users on demand. Still, flying networks impose significant challenges in order to meet the Quality of Experience expectations. State of the art works addressed these challenges, but have been focused on routing and the placement of the UAVs as APs and BSs serving the ground users, overlooking the backhaul network design. The main contribution of this paper is a centralized traffic-aware Gateway UAV Placement (GWP) algorithm for flying networks with controlled topology. GWP takes advantage of the knowledge of the offered traffic and the future topologies of the flying network to enable backhaul communications paths with high enough capacity. The performance achieved using the GWP algorithm is evaluated using ns-3 simulations. The obtained results demonstrate significant gains regarding aggregate throughput and delay.

Abstract
After 12 years of EMOS experience it is time to open the discussion on the future of EMOS. This papers briefly describes the experience from the perspective of the Universities, trying also to describe the needs and role of the NSIs, Banks and other possible actors to join the network, and unlock the future. EMOS should reload (or evolute) to stay current and attractive. Statistical 'thinking' evolved and a major change and challenge for EMOS is to pick up this trend in its cooperation with the universities.

Abstract
This paper presents the development of a hyperbaric system able to collect, transport and maintain deep-sea species in controlled condition from the sea floor up to the surface (HiperSea System). The system is composed by two chambers coupled with a transference set-up. The first chamber is able to reach a maximum of 1km depth collecting both benthic and pelagic deep-sea species. The second chamber is a life support compartment to maintain the specimens alive at the surface, in hyperbaric conditions.