Coin migration within the euro area

This paper analyses how many euro coins outflow from Germany and which composition of coins is to be expected in the long run. To this end, a simple mathematical model is formulated and calibrated for €1 coins. The introduction of the euro coins in 2002 presented a unique opportunity to analyse the cross-border migration and the mixing process of coins in different euro-area countries. Based on research by Stoyan and depending on growth assumptions, the annual outflow of German €1 coins is calculated to lie somewhere between 4% and 5%. In the long run, the ratio of German €1 coins in Germany is likely to converge to around 50%. --Euro coins,coin volumes,mixing process

Ranges of control in the transcriptional regulation of Escherichia coli

<p>Abstract</p> <p>Background</p> <p>The positioning of genes in the genome is an important evolutionary degree of freedom for organizing gene regulation. Statistical properties of these distributions have been studied particularly in relation to the transcriptional regulatory network. The systematics of gene-gene distances then become important sources of information on the control, which different biological mechanisms exert on gene expression.</p> <p>Results</p> <p>Here we study a set of categories, which has to our knowledge not been analyzed before. We distinguish between genes that do not participate in the transcriptional regulatory network (i.e. that are according to current knowledge not producing transcription factors and do not possess binding sites for transcription factors in their regulatory region), and genes that via transcription factors either are regulated by or regulate other genes. We find that the two types of genes ("isolated" and "regulatory" genes) show a clear statistical repulsion and have different ranges of correlations. In particular we find that isolated genes have a preference for shorter intergenic distances.</p> <p>Conclusions</p> <p>These findings support previous evidence from gene expression patterns for two distinct logical types of control, namely digital control (i.e. network-based control mediated by dedicated transcription factors) and analog control (i.e. control based on genome structure and mediated by neighborhood on the genome).</p

Cutting a Cake Is Not Always a 'Piece of Cake': A Closer Look at the Foundations of Cake-Cutting Through the Lens of Measure Theory

Cake-cutting is a playful name for the fair division of a heterogeneous, divisible good among agents, a well-studied problem at the intersection of mathematics, economics, and artificial intelligence. The cake-cutting literature is rich and edifying. However, different model assumptions are made in its many papers, in particular regarding the set of allowed pieces of cake that are to be distributed among the agents and regarding the agents' valuation functions by which they measure these pieces. We survey the commonly used definitions in the cake-cutting literature, highlight their strengths and weaknesses, and make some recommendations on what definitions could be most reasonably used when looking through the lens of measure theory

Modeling the Spatial Distribution and Fruiting Pattern of a Key Tree Species in a Neotropical Forest: Methodology and Potential Applications

Damien Caillaud is with UT Austin and Max Planck Institute for Evolutionary Anthropology; Margaret C. Crofoot is with the Smithsonian Tropical Research Institute, Max Planck Institute for Ornithology, and Princeton University; Samuel V. Scarpino is with UT Austin; Patrick A. Jansen is with the Smithsonian Tropical Research Institute, Wageningen University, and University of Groningen; Carol X. Garzon-Lopez is with University of Groningen; Annemarie J. S. Winkelhagen is with Wageningen University; Stephanie A. Bohlman is with Princeton University; Peter D. Walsh is with VaccinApe.Background -- The movement patterns of wild animals depend crucially on the spatial and temporal availability of resources in their habitat. To date, most attempts to model this relationship were forced to rely on simplified assumptions about the spatiotemporal distribution of food resources. Here we demonstrate how advances in statistics permit the combination of sparse ground sampling with remote sensing imagery to generate biological relevant, spatially and temporally explicit distributions of food resources. We illustrate our procedure by creating a detailed simulation model of fruit production patterns for Dipteryx oleifera, a keystone tree species, on Barro Colorado Island (BCI), Panama. Methodology and Principal Findings -- Aerial photographs providing GPS positions for large, canopy trees, the complete census of a 50-ha and 25-ha area, diameter at breast height data from haphazardly sampled trees and long-term phenology data from six trees were used to fit 1) a point process model of tree spatial distribution and 2) a generalized linear mixed-effect model of temporal variation of fruit production. The fitted parameters from these models are then used to create a stochastic simulation model which incorporates spatio-temporal variations of D. oleifera fruit availability on BCI. Conclusions and Significance -- We present a framework that can provide a statistical characterization of the habitat that can be included in agent-based models of animal movements. When environmental heterogeneity cannot be exhaustively mapped, this approach can be a powerful alternative. The results of our model on the spatio-temporal variation in D. oleifera fruit availability will be used to understand behavioral and movement patterns of several species on BCI.The National Center For Ecological Analysis is supported by NSF Grant DEB-0553768, the University of California Santa Barbara and the State of California. The Forest Dynamics Plots were funded by NSF Grants to Stephen Hubbell DEB-0640386, DEB-0425651, DEB-0346488, DEB-0129874, DEB-00753102, DEB-9909347, DEB-9615226, DEB-9615226, DEB-9405933, DEB-9221033, DEB-9100058, DEB-8906869, DEB-8605042, DEB-8206992, DEB-7922197, and by the Center for Tropical Forest Science, the Smithsonian Tropical Forest Research Institute, The John D. and Catherine T. MacArthur Foundation, the Mellon Foundation and the Celera Foundation. DC is supported by NSF grant DEB-0749097 to L.A. Meyers. SS is supported by an NSF Graduate Research Fellowship. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.Biological Sciences, School o