Analyzing and Modeling Real-World Phenomena with Complex Networks: A Survey of Applications

The success of new scientific areas can be assessed by their potential for contributing to new theoretical approaches and in applications to real-world problems. Complex networks have fared extremely well in both of these aspects, with their sound theoretical basis developed over the years and with a variety of applications. In this survey, we analyze the applications of complex networks to real-world problems and data, with emphasis in representation, analysis and modeling, after an introduction to the main concepts and models. A diversity of phenomena are surveyed, which may be classified into no less than 22 areas, providing a clear indication of the impact of the field of complex networks.Comment: 103 pages, 3 figures and 7 tables. A working manuscript, suggestions are welcome

Spread of a SARS-CoV-2 variant through Europe in the summer of 2020.

Following its emergence in late 2019, the spread of SARS-CoV-21,2 has been tracked by phylogenetic analysis of viral genome sequences in unprecedented detail3–5. Although the virus spread globally in early 2020 before borders closed, intercontinental travel has since been greatly reduced. However, travel within Europe resumed in the summer of 2020. Here we report on a SARS-CoV-2 variant, 20E (EU1), that was identified in Spain in early summer 2020 and subsequently spread across Europe. We find no evidence that this variant has increased transmissibility, but instead demonstrate how rising incidence in Spain, resumption of travel, and lack of effective screening and containment may explain the variant’s success. Despite travel restrictions, we estimate that 20E (EU1) was introduced hundreds of times to European countries by summertime travellers, which is likely to have undermined local efforts to minimize infection with SARS-CoV-2. Our results illustrate how a variant can rapidly become dominant even in the absence of a substantial transmission advantage in favourable epidemiological settings. Genomic surveillance is critical for understanding how travel can affect transmission of SARS-CoV-2, and thus for informing future containment strategies as travel resumes. © 2021, The Author(s), under exclusive licence to Springer Nature Limited

Mid-rapidity anti-proton to proton ratio from Au+Au collisions at sNN=130 \sqrt{s_{NN}} = 130 GeV

We report results on the ratio of mid-rapidity anti-proton to proton yields in Au+Au collisions at \rts = 130 GeV per nucleon pair as measured by the STAR experiment at RHIC. Within the rapidity and transverse momentum range of $|y|<0.5$ and 0.4 $<p_t<$ 1.0 GeV/$c$, the ratio is essentially independent of either transverse momentum or rapidity, with an average of $0.65\pm 0.01_{\rm (stat.)} \pm 0.07_{\rm (syst.)}$ for minimum bias collisions. Within errors, no strong centrality dependence is observed. The results indicate that at this RHIC energy, although the $p$-\pb pair production becomes important at mid-rapidity, a significant excess of baryons over anti-baryons is still present.Comment: 5 pages, 3 figures, accepted by Phys. Rev. Let

Integrated global assessment of the natural forest carbon potential

Forests are a substantial terrestrial carbon sink, but anthropogenic changes in land use and climate have considerably reduced the scale of this system1. Remote-sensing estimates to quantify carbon losses from global forests2,3,4,5 are characterized by considerable uncertainty and we lack a comprehensive ground-sourced evaluation to benchmark these estimates. Here we combine several ground-sourced6 and satellite-derived approaches2,7,8 to evaluate the scale of the global forest carbon potential outside agricultural and urban lands. Despite regional variation, the predictions demonstrated remarkable consistency at a global scale, with only a 12% difference between the ground-sourced and satellite-derived estimates. At present, global forest carbon storage is markedly under the natural potential, with a total deficit of 226 Gt (model range = 151–363 Gt) in areas with low human footprint. Most (61%, 139 Gt C) of this potential is in areas with existing forests, in which ecosystem protection can allow forests to recover to maturity. The remaining 39% (87 Gt C) of potential lies in regions in which forests have been removed or fragmented. Although forests cannot be a substitute for emissions reductions, our results support the idea2,3,9 that the conservation, restoration and sustainable management of diverse forests offer valuable contributions to meeting global climate and biodiversity targets

Controlling systemic corruption through group size and salary dispersion of public servants

We investigate an agent-based model for the emergence of corruption in public contracts. There are two types of agents: business people and public servants. Both business people and public servants can adopt two strategies: corrupt or honest behavior. Interactions between business people and public servants take place through defined payoff rules. Either type of agent can switch between corrupt or honest strategies by comparing their payoffs after interacting. We measure the level of corruption in the system by the fractions of corrupt and honest agents for asymptotic times. We study the effects of the group size of the interacting agents, the dispersion with respect to the average salary of the public servants, and a parameter representing the institutional control of corruption. We characterize the fractions of honest and corrupt agents as functions of these variables. We construct phase diagrams for the level of corruption in the system in terms of these variables, where three collective states can be distinguished: i) a phase where corruption dominates; ii) a phase where corruption remains in less than 50% of the agents; and iii) a phase where corruption disappears. Our results indicate that a combination of large group sizes of interacting servants and business people and small dispersion of the salaries of public servants, contributes to the decrease of systemic corruption in public contracts

Sources and movements of marine turtles in the Gulf of Venezuela: regional and local assessments

Marine turtles are challenging species to protect because they occur over large geographic scales. Tagging individual turtles at nesting beaches and foraging areas, and the resulting mark-recapture data sets have gradually enabled us to understand marine turtle migratory behaviour and dispersal. Within the Caribbean region, several turtle tagging projects have led to longer-term evaluations and assessments of connectivity. Thus, marine turtle mark-recapture data is important for developing conservation strategies at regional-scale. In this study, we analyse turtle tagging data from the Gulf of Venezuela to determine regional (Caribbean and Atlantic geographic level) and local (within the Gulf of Venezuela) links. To achieve this, we retrieved, compiled, and analysed multiple databases with records of marine turtles that were tagged and then recaptured in the Gulf of Venezuela. Sixty-six tag return records were evaluated, 43 from animals initially tagged outside of the Gulf of Venezuela and then recaptured inside, plus 23 records retrieved from turtles that were tagged and recaptured within the Gulf of Venezuela. We found evidence of connectivity between 12 different locations where initial tagging events occurred, eight from other feeding areas and four from nesting beaches. We described four different movement patterns for 23 turtles tagged and re-captured within the Gulf of Venezuela. Most of the recapture records we obtained occurred after the turtles were known, or presumed, to have been killed by local fishers. Hence, knowing patterns of dispersal and connectivity are crucial to improving local and regional conservation and threat mitigation