Diagnostics of Coronal Magnetic Fields Through the Hanle Effect in UV and IR Lines

The plasma thermodynamics in the solar upper atmosphere, particularly in the corona, are dominated by the magnetic field, which controls the flow and dissipation of energy. The relative lack of knowledge of the coronal vector magnetic field is a major handicap for progress in coronal physics. This makes the development of measurement methods of coronal magnetic fields a high priority in solar physics. The Hanle effect in the UV and IR spectral lines is a largely unexplored diagnostic. We use magnetohydrodynamic (MHD) simulations to study the magnitude of the signal to be expected for typical coronal magnetic fields for selected spectral lines in the UV and IR wavelength ranges, namely the H I Ly-$\alpha$ and the He I 10830 {\AA} lines. We show that the selected lines are useful for reliable diagnosis of coronal magnetic fields. The results show that the combination of polarization measurements of spectral lines with different sensitivities to the Hanle effect may be most appropriate for deducing coronal magnetic properties from future observations.Comment: 15 pages, 5 figures, Frontiers in Astronomy and Space Sciences, 201

A note on leapfrogging vortex rings

In this paper we provide examples, by numerical simulation using the Navier-Stokes equations for axisymmetric laminar flow, of the 'leapfrogging' motion of two, initially identical, vortex rings which share a common axis of symmetry. We show that the number of clear passes that each ring makes through the other increases with Reynolds number, and that as long as the configuration remains stable the two rings ultimately merge to form a single vortex ring

Analysing the behaviour of robot teams through relational sequential pattern mining

This report outlines the use of a relational representation in a Multi-Agent domain to model the behaviour of the whole system. A desired property in this systems is the ability of the team members to work together to achieve a common goal in a cooperative manner. The aim is to define a systematic method to verify the effective collaboration among the members of a team and comparing the different multi-agent behaviours. Using external observations of a Multi-Agent System to analyse, model, recognize agent behaviour could be very useful to direct team actions. In particular, this report focuses on the challenge of autonomous unsupervised sequential learning of the team's behaviour from observations. Our approach allows to learn a symbolic sequence (a relational representation) to translate raw multi-agent, multi-variate observations of a dynamic, complex environment, into a set of sequential behaviours that are characteristic of the team in question, represented by a set of sequences expressed in first-order logic atoms. We propose to use a relational learning algorithm to mine meaningful frequent patterns among the relational sequences to characterise team behaviours. We compared the performance of two teams in the RoboCup four-legged league environment, that have a very different approach to the game. One uses a Case Based Reasoning approach, the other uses a pure reactive behaviour.Comment: 25 page

Farm Facts, Population Update, Report Number 6

What\u27s happening to our farms in South Dakota? Turn to the Census of Agriculture, conducted every 5 years by the United States Bureau of the Census, to find part of the answer. Begun in 1920, this census has grown and changed over the years to provide its present broad coverage of farm facts. From 1978 data* and earlier censuses, here is a summary of the basic characteristics and trends for South Dakota farms and farm operators. SOUTH DAKOTA FARMS The 1978 census counted 39,665 farms in South Dakota. This is 3,160 (7.4%) fewer than shown in the 1974 census.** Table 3.

Preterm infants have deficient monocyte and lymphocyte cytokine responses to Group B Streptococcus

Group B streptococcus GBS) is an important cause of early-and late-onset sepsis in the newborn. Preterm infants have markedly increased susceptibility and worse outcomes, but their immunological responses to GBS are poorly defined. We compared mononuclear cell and whole-blood cytokine responses to heat-killed GBS HKGBS) of preterm infants gestational age [GA], 26 to 33 weeks), term infants, and healthy adults. We investigated the kinetics and cell source of induced cytokines and quantified HKGBS phagocytosis. HKGBS-induced tumor necrosis factor TNF) and interleukin 6 (IL-6) secretion was significantly impaired in preterm infants compared to that in term infants and adults. These cytokines were predominantly monocytic in origin, and production was intrinsically linked to HKGBS phagocytosis. Very preterm infants GA, < 30 weeks) had fewer cytokine-producing monocytes, but nonopsonic phagocytosis ability was comparable to that for term infants and adults. Exogenous complement supplementation increased phagocytosis in all groups, as well as the proportion of preterm monocytes producing IL-6, but for very preterm infants, responses were still deficient. Similar defective preterm monocyte responses were observed in fresh whole cord blood stimulated with live GBS. Lymphocyte-associated cytokines were significantly deficient for both preterm and term infants compared to levels for adults. These findings indicate that a subset of preterm monocytes do not respond to GBS, a defect compounded by generalized weaker lymphocyte responses in newborns. Together these deficient responses may increase the susceptibility of preterm infants to GBS infection

Population Change of Counties and Incorporated Places in South Dakota: 1950-180

This publication is thirteenth in the population update series based on South Dakota\u27s 1980 population. The tables in this report have been assembled to provide a convenient source of population information for the counties and incorporated places of South Dakota. The basic data have been taken from the U.S. Bureau of the Census, 1980 Census of Population � South Dakota PC80-l-A43 and the 1960 Census of Population-South Dakota PC (1) -43A. The figures are final population counts from the various census