Redrawing the Map of Great Britain from a Network of Human Interactions

Do regional boundaries defined by governments respect the more natural ways that people interact across space? This paper proposes a novel, fine-grained approach to regional delineation, based on analyzing networks of billions of individual human transactions. Given a geographical area and some measure of the strength of links between its inhabitants, we show how to partition the area into smaller, non-overlapping regions while minimizing the disruption to each person's links. We tested our method on the largest non-Internet human network, inferred from a large telecommunications database in Great Britain. Our partitioning algorithm yields geographically cohesive regions that correspond remarkably well with administrative regions, while unveiling unexpected spatial structures that had previously only been hypothesized in the literature. We also quantify the effects of partitioning, showing for instance that the effects of a possible secession of Wales from Great Britain would be twice as disruptive for the human network than that of Scotland.National Science Foundation (U.S.)AT & TAudi AGUnited States. Dept. of Defense (National Defense Science and Engineering Fellowship Program

Detection of Honey Adulteration by Sugar Syrups Using One-dimensional and two-dimensional High-resolution Nuclear Magnetic Resonance

The importance of honey adulteration detection has recently increased owing to the limited production levels in recent years and to the relative high price of honey, therefore this illegal practice has becoming more and more attractive to producers. Hence the need has arisen for more effective analitical methods aiming at detecting honey adulteration. The present research presents an effective method to detect adulteration in honey falsified by intentional addition of different concentrations of commercial sugar syrups, using one-dimensional (1D) and two-dimensional (2D) nuclear magnetic resonance (NMR) coupled with multivariate statistical analysis. Sixty-three authentic and 63 adulterated honey samples were analysed. To prepare adulterated honeys, 7 different sugar syrups normally used for nutrition of bees were used. The best discriminant model was obtained by 1D spectra and the leave-one out cross-validation showed a predictive capacity of 95.2 %. Also 2D NMR have furnished acceptable results (cross-validation correct classification 90.5%), although the 1H-NMR sequence is preferable because it is the simplest and fastest NMR technique