Synthesis of silicon doped SrMO3 (M=Mn, Co): stabilization of the cubic perovskite and enhancement in conductivity

In this paper we report the successful incorporation of silicon into SrMO3 (M=Co, Mn) leading to a structural change from a hexagonal to a cubic perovskite. For M=Co, the cubic phase was observed for low doping levels (3%), and these doped phases showed very high conductivities ( up to ≈350 Scm-1 at room temperature). However, annealing studies at intermediate temperatures (700-800○C), indicated that the cubic phase was metastable with a gradual transformation to a hexagonal cell on annealing. Further work showed that co-doping with Fe resulted in improved stability of the cubic phase; a composition SrCo0.85Fe0.1Si0.05O3-y displayed good stability at intermediate temperatures and a high conductivity (≈150 Scm-1 at room temperature).\ud \ud For M=Mn, the work showed that higher substitution levels were required to form the cubic perovskite (≈15% Si doping), although in these cases the phases were shown to be stable to annealing at intermediate temperatures. Conductivity measurements again showed an enhancement in the conductivity on Si doping, although the conductivities were lower (≈0.3 – 14 Scm-1 in the range 20- 800○C) than the cobalt containing systems. The conductivities of both systems suggest potential for use as cathode materials in solid oxide fuel cells

Integrating basic research with prevention/intervention to reduce risky substance use among college students

Too often basic research on etiological processes that contribute to substance use outcomes is disconnected from efforts to develop prevention and intervention programming. Substance use on college campuses is an area of concern where translational efforts that bring together basic scientists and prevention/intervention practitioners have potential for high impact. We describe an effort at a large, public, urban university in the United States to bring together researchers across the campus with expertise in college behavioral health with university administration and health/wellness practitioners to address college student substance use and mental health. The project “Spit for Science” examines how genetic and environmental influences contribute to behavioral health outcomes across the college years. We argue that findings coming out of basic research can be used to develop more tailored prevention and intervention programming that incorporates both biologically and psychosocially influenced risk factors. Examples of personalized programming suggest this may be a fruitful way to advance the field and reduce risky substance use

Structural matching by discrete relaxation

This paper describes a Bayesian framework for performing relational graph matching by discrete relaxation. Our basic aim is to draw on this framework to provide a comparative evaluation of a number of contrasting approaches to relational matching. Broadly speaking there are two main aspects to this study. Firstly we locus on the issue of how relational inexactness may be quantified. We illustrate that several popular relational distance measures can be recovered as specific limiting cases of the Bayesian consistency measure. The second aspect of our comparison concerns the way in which structural inexactness is controlled. We investigate three different realizations ai the matching process which draw on contrasting control models. The main conclusion of our study is that the active process of graph-editing outperforms the alternatives in terms of its ability to effectively control a large population of contaminating clutter

Teaching assistants and support for literacy and language development

Through an examination of writing done by teaching assistants for an Open University course, this paper examines assistants’ perceptions of their role in children’s learning within the context of the Literacy Hour. There is an analysis of three themes arising from the data i.e. assistants’ practice aimed at increasing children’s participation; assistants’ pedagogic and subject knowledge; and the nature of assistants’ team working with teachers. The data suggests that teaching assistants are very involved in working with the most vulnerable and ‘difficult to teach’ children and that they use a range of intermediary techniques and pedagogic strategies to enable these children to participate in the Literacy Hour. The data lends support to the official view of the role of teaching assistants i.e. that, guided by teachers, they ‘enable the teacher to teach’ and ‘support children’s learning’. However, the data also suggests that teaching assistants teach too, sometimes with a degree of independence. Indeed, the variety (and in some cases sophistication) of ways in which teaching points are developed by them with children appears to signify a clear pedagogic role in terms of extending children’s knowledge of literacy

On the Optimization of Mixture Resolving Signal Processing Structures

Mixture resolving signal processing optimization with optimum linear detection operators and mixture resolving estimator

Learning probability spaces for classification and recognition of patterns with or without supervision

Learning probability spaces for classification and recognition of patterns with or without supervisio

Terrain analysis using radar shape-from-shading

This paper develops a maximum a posteriori (MAP) probability estimation framework for shape-from-shading (SFS) from synthetic aperture radar (SAR) images. The aim is to use this method to reconstruct surface topography from a single radar image of relatively complex terrain. Our MAP framework makes explicit how the recovery of local surface orientation depends on the whereabouts of terrain edge features and the available radar reflectance information. To apply the resulting process to real world radar data, we require probabilistic models for the appearance of terrain features and the relationship between the orientation of surface normals and the radar reflectance. We show that the SAR data can be modeled using a Rayleigh-Bessel distribution and use this distribution to develop a maximum likelihood algorithm for detecting and labeling terrain edge features. Moreover, we show how robust statistics can be used to estimate the characteristic parameters of this distribution. We also develop an empirical model for the SAR reflectance function. Using the reflectance model, we perform Lambertian correction so that a conventional SFS algorithm can be applied to the radar data. The initial surface normal direction is constrained to point in the direction of the nearest ridge or ravine feature. Each surface normal must fall within a conical envelope whose axis is in the direction of the radar illuminant. The extent of the envelope depends on the corrected radar reflectance and the variance of the radar signal statistics. We explore various ways of smoothing the field of surface normals using robust statistics. Finally, we show how to reconstruct the terrain surface from the smoothed field of surface normal vectors. The proposed algorithm is applied to various SAR data sets containing relatively complex terrain structure

DNA Sequence Determinants Controlling Affinity, Stability and Shape of DNA Complexes Bound by the Nucleoid Protein Fis.

The abundant Fis nucleoid protein selectively binds poorly related DNA sequences with high affinities to regulate diverse DNA reactions. Fis binds DNA primarily through DNA backbone contacts and selects target sites by reading conformational properties of DNA sequences, most prominently intrinsic minor groove widths. High-affinity binding requires Fis-stabilized DNA conformational changes that vary depending on DNA sequence. In order to better understand the molecular basis for high affinity site recognition, we analyzed the effects of DNA sequence within and flanking the core Fis binding site on binding affinity and DNA structure. X-ray crystal structures of Fis-DNA complexes containing variable sequences in the noncontacted center of the binding site or variations within the major groove interfaces show that the DNA can adapt to the Fis dimer surface asymmetrically. We show that the presence and position of pyrimidine-purine base steps within the major groove interfaces affect both local DNA bending and minor groove compression to modulate affinities and lifetimes of Fis-DNA complexes. Sequences flanking the core binding site also modulate complex affinities, lifetimes, and the degree of local and global Fis-induced DNA bending. In particular, a G immediately upstream of the 15 bp core sequence inhibits binding and bending, and A-tracts within the flanking base pairs increase both complex lifetimes and global DNA curvatures. Taken together, our observations support a revised DNA motif specifying high-affinity Fis binding and highlight the range of conformations that Fis-bound DNA can adopt. The affinities and DNA conformations of individual Fis-DNA complexes are likely to be tailored to their context-specific biological functions

A matrix representation of graphs and its spectrum as a graph invariant

We use the line digraph construction to associate an orthogonal matrix with each graph. From this orthogonal matrix, we derive two further matrices. The spectrum of each of these three matrices is considered as a graph invariant. For the first two cases, we compute the spectrum explicitly and show that it is determined by the spectrum of the adjacency matrix of the original graph. We then show by computation that the isomorphism classes of many known families of strongly regular graphs (up to 64 vertices) are characterized by the spectrum of this matrix. We conjecture that this is always the case for strongly regular graphs and we show that the conjecture is not valid for general graphs. We verify that the smallest regular graphs which are not distinguished with our method are on 14 vertices.Comment: 14 page