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Background: Cryptomarkets, or illegal anonymizing online platforms that facilitate drug trade, have been analyzed in a rapidly growing body of research. Previous research has found that, despite increased risks, cryptomarket sellers are often willing to ship illegal drugs internationally. There is little to no information, however, about the extent to which uncertainty and risk related to geographic constraints shapes buyers' behavior and, in turn, the structure of the global online drug trade network. In this paper, we analyze the structure of a complete cryptomarket trade network with a focus on the role of geographic clustering of buyers and sellers.Methods: We use publicly available crawls of the cryptomarket Abraxas, encompassing market transactions between 463 sellers and 3542 buyers of drugs in 2015. We use descriptive social network analysis and Exponential Random Graph Models (ERGM) to analyze the structure of the trade network.Results: The structure of the online drug trade network is primarily shaped by geographical boundaries. Buyers are more likely to buy from multiple sellers within a single country, and avoid buying from sellers in different countries, which leads to strong geographic clustering. The effect is especially strong between continents and weaker for countries within Europe. A small fraction of buyers (10%) account for more than a half of all drug purchases, while most buyers only buy once.Conclusion: Online drug trade networks might still be heavily shaped by offline (geographic) constraints, despite their ability to provide access for end-users to large international supply. Cryptomarkets might be more "localized" and less international than thought before. We discuss potential explanations for such geographical clustering and implications of the findings. [ABSTRACT FROM AUTHOR]

Prematurely born children are at higher risk for long-term adverse motor and cognitive outcomes. The aim of this paper was to compare quantitative measures derived from electroencephalography (EEG) between extremely (EP) and very prematurely (VP) born children at 9-10 years of age. Fifty-five children born <32 weeks' of gestation underwent EEG at 9-10 years of age and were assessed for motor development and cognitive outcome. Relative frequency power and functional connectivity, as measured by the Phase Lag Index (PLI), were calculated for all frequency bands. Per subject, power spectrum and functional connectivity results were averaged over all channels and pairwise PLI values to explore differences in global frequency power and functional connectivity between EP and VP children. Brain networks were constructed for the upper alpha frequency band using the Minimum Spanning Tree method and were compared between EP and VP children. In addition, the relationships between upper alpha quantitative EEG results and cognitive and motor outcomes were investigated. Relative power and functional connectivity were significantly higher in VP than EP children in the upper alpha frequency band, and VP children had more integrated networks. A strong positive correlation was found between relative upper alpha power and motor outcome whilst controlling for gestational age, age during EEG recording, and gender (ρ = 0.493, p = 0.004). These results suggest that 9-10 years after birth, the effects of the degree of prematurity can be observed in terms of alterations in functional brain activity and that motor deficits are associated with decreases in relative upper alpha power. [ABSTRACT FROM AUTHOR]