How to move ionized gas: an introduction to the dynamics of HII regions

This review covers the dynamic processes that are important in the evolution and structure of galactic HII regions, concentrating on an elementary presentation of the physical concepts and recent numerical simulations of HII region evolution in a non-uniform medium. The contents are as follows: (1) The equations (Euler equations; Radiative transfer; Rate equations; How to avoid the dynamics; How to avoid the atomic physics). (2) Physical concepts (Static photoionization equilibrium; Ionization front propagation; Structure of a D-type front; Photoablation flows; Other ingredients - Stellar winds, Radiation pressure, Magnetic fields, Instabilities). (3) HII region evolution (Early phases: hypercompact and ultracompact regions; Later phases: compact and extended regions; Clumps and turbulence).Comment: To be published as a chapter in 'Diffuse Matter from Star Forming Regions to Active Galaxies' - A volume Honouring John Dyson. Eds. T. W. Harquist, J. M. Pittard and S. A. E. G. Falle. 25 pages, 7 figures. Some figures degraded to meet size restriction. Full-resolution version available at http://www.ifront.org/wiki/Dyson_Festschrift_Chapte

Strangeness Suppression of q(q)over-bar Creation Observed in Exclusive Reactions

We measured the ratios of electroproduction cross-sections from a proton target for three exclusive meson-baryon final states: $\Lambda K^+$, $p\pi^0$, and $n\pi^+$, with the CLAS detector at Jefferson Lab. Using a simple model of quark hadronization we extract q-qbar creation probabilities for the first time in exclusive two-body production, in which only a single q-qbar pair is created. We observe a sizable suppression of strange quark-antiquark pairs compared to non-strange pairs, similar to that seen in high-energy production.Comment: 5pages, 2figure

Sequential downscaling methods for estimation from aggregate data

Global change processes raise new estimation problems challenging the conventional statistical methods. These methods are based on the ability to obtain observations from unknown true probability distributions, whereas the new problems require recovering information from only partially observable or even unobservable variables. For instance, aggregate data exist at global and national level regarding agricultural production, occurrence of natural disasters, on incomes, etc. without providing any clue as to possibly alarming diversity of conditions at local level. "Downscaling" methods in this case should achieve plausible estimation of local implications emerging from global tendencies by using all available evidences. The aim of this paper is to develop a sequential downcasting method, which can be used in a variety of practical situations. Our main motivation for this was the estimation of spatially distributed crop production, i.e., on a regular grid, consistent with known national-level statistics and in accordance with geographical datasets and agronomic knowledge. We prove convergence of the method to a generalized cross-entropy maximizing solution. We also show that for specific cases this method is reduced to known procedures for estimating transportation flows and doubly stochastic matrices