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FRANKLIN COUNTY, IOWA'S PROGRAM IN PUBLIC AFFAIRS

Public Economics,

Assimilation of TES data from the Mars Global Surveyor scientifc mapping phase

The Thermal Emission Spectrometer (TES)aboard Mars Global Surveyor has produced data which cover almost two Martian years so far (during its scientific mapping phase). Thermal profiles for the atmosphere below 40 km and total dust opacities can be retrieved from TES nadir spectra and assimilated into a Mars general circulation model (MGCM), by using the assimilation techniques described in detail by Lewis et al. (2002). This paper describes some preliminary results from assimilations of temperature data from the period Ls=141°- 270° corresponding to late northern summer until winter solstice on Mars. Work in progress is devoted to assimilate both temperature and total dust opacity data for the full period for which they are already available

Superconducting film with randomly magnetized dots: A realization of the 2D XY model with random phase shifts

We consider a thin superconducting film with randomly magnetized dots on top of it. The dots produce a disordered pinning potential for vortices in the film. We show that for dots with permanent and random magnetization normal or parallel to the film surface, our system is an experimental realization of the two-dimensional XY model with random phase shifts. The low-temperature superconducting phase, that exists without magnetic dots, survives in the presence of magnetic dots for sufficiently small disorder.Comment: 5 pages, 1 figur

Data assimilation for the Martian atmosphere using MGS Thermal Emission Spectrometer observations

From the introduction: Given the quantity of data expected from current and forthcoming spacecraft missions to Mars, it is now possible to use data assimilation as a means of atmospheric analysis for the first time for a planet other than the Earth. Several groups have described plans to develop assimilation schemes for Mars [Banfield et al., 1995; Houben, 1999; Lewis and Read, 1995; Lewis et al., 1996, 1997; Zhang et al., 2001]. Data assimilation is a technique for the analysis of atmospheric observations which combines currently valid information with prior knowledge from previous observations and dynamical and physical constraints, via the use of a numerical model. Despite the number of new missions, observations of the atmosphere of Mars in the near future are still likely to be sparse when compared to those of the Earth, perhaps comprising one orbiter and a few surface stations at best at any one time. Data assimilation is useful as a means to extract the maximum information from such observations, both by a form of interpolation in space and time using model constraints and by the combination of information from different observations, e.g. temperature profiles and surface pressure measurements which may be irregularly distributed. The procedure can produce a dynamically consistent set of meteorological fields and can be used directly to test and to refine an atmospheric model against observations

Structural change of vortex patterns in anisotropic Bose-Einstein condensates

We study the changes in the spatial distribution of vortices in a rotating Bose-Einstein condensate due to an increasing anisotropy of the trapping potential. Once the rotational symmetry is broken, we find that the vortex system undergoes a rich variety of structural changes, including the formation of zig-zag and linear configurations. These spatial re-arrangements are well signaled by the change in the behavior of the vortex-pattern eigenmodes against the anisotropy parameter. The existence of such structural changes opens up possibilities for the coherent exploitation of effective many-body systems based on vortex patterns.Comment: 5 pages, 4 figure

Hierarchical Models for Independence Structures of Networks

We introduce a new family of network models, called hierarchical network models, that allow us to represent in an explicit manner the stochastic dependence among the dyads (random ties) of the network. In particular, each member of this family can be associated with a graphical model defining conditional independence clauses among the dyads of the network, called the dependency graph. Every network model with dyadic independence assumption can be generalized to construct members of this new family. Using this new framework, we generalize the Erd\"os-R\'enyi and beta-models to create hierarchical Erd\"os-R\'enyi and beta-models. We describe various methods for parameter estimation as well as simulation studies for models with sparse dependency graphs.Comment: 19 pages, 7 figure

Core subjects at the end of primary school : identifying and explaining relative strengths of children with specific language impairment (SLI)

Background In general, children with specific language impairment (SLI) tend to fall behind their typically developing (TD) peers in educational attainment. Less is known about how children with SLI fare in particular areas of the curriculum and what predicts their levels of performance. Aims To compare the distributions of performance of children with SLI in three core school subjects (English, Mathematics and Science); to test the possibility that performance would vary across the core subjects; and to examine the extent to which language impairment predicts performance. Methods & Procedures This study was conducted in England and reports historical data on educational attainments. Teacher assessment and test scores of 176 eleven-year-old children with SLI were examined in the three core subjects and compared with known national norms. Possible predictors of performance were measured, including language ability at ages 7 and 11, educational placement type, and performance IQ. Outcomes & Results Children with SLI, compared with national norms, were found to be at a disadvantage in core school subjects. Nevertheless, some children attained the levels expected of TD peers. Performance was poorest in English; relative strengths were indicated in Science and, to a lesser extent, in Mathematics. Language skills were significant predictors of performance in all three core subjects. PIQ was the strongest predictor for Mathematics. For Science, both early language skills at 7 years and PIQ made significant contributions. Conclusions & Implications Language impacts on the school performance of children with SLI, but differentially across subjects. English for these children is the most challenging of the core subjects, reflecting the high levels of language demand it incurs. Science is an area of relative strength and mathematics appears to be intermediate, arguably because some tasks in these subjects can be performed with less reliance on verbal processing. Many children with SLI do have the potential to reach or exceed educational targets that are set at national levels for TD children