Magnetic circular dichroism in X-ray fluorescence of Heusler alloys at threshold excitation

The results of fluorescence measurements of magnetic circular dichroism (MCD) in Mn L_2,L_3 X-ray emission and absorption for Heusler alloys NiMnSb and Co2MnSb are presented. Very intense resonance Mn L_3 emission is found at the Mn 2p_3/2 threshold and is attributed to a peculiarity of the threshold excitation in materials with the half-metallic character of the electronic structure. A theoretical model for the description of resonance scattering of polarized x-rays is suggested.Comment: 3 pages, 2 figures. Discussed at conferences, submitting process in progres

Paying More for the American Dream III: Promoting Responsible Lending to Lower-Income Communities and Communities of Color

This report analyzes 2007 Home Mortgage Disclosure Act data and finds that, in low- and moderate-income communities, depositories with CRA obligations originate a far smaller share of higher-cost loans than lenders not subject to CRA. It also finds that lenders covered by CRA are much less likely to make higher-cost loans in communities of color than lenders not covered by CRA

Reproducibility of graph metrics of human brain structural networks

Recent interest in human brain connectivity has led to the application of graph theoretical analysis to human brain structural networks, in particular white matter connectivity inferred from diffusion imaging and fiber tractography. While these methods have been used to study a variety of patient populations, there has been less examination of the reproducibility of these methods. A number of tractography algorithms exist and many of these are known to be sensitive to user-selected parameters. The methods used to derive a connectivity matrix from fiber tractography output may also influence the resulting graph metrics. Here we examine how these algorithm and parameter choices influence the reproducibility of proposed graph metrics on a publicly available test-retest dataset consisting of 21 healthy adults. The dice coefficient is used to examine topological similarity of constant density subgraphs both within and between subjects. Seven graph metrics are examined here: mean clustering coefficient, characteristic path length, largest connected component size, assortativity, global efficiency, local efficiency, and rich club coefficient. These reproducibility of these network summary measures is examined using the intraclass correlation coefficient (ICC). Graph curves are created by treating the graph metrics as functions of a parameter such as graph density. Functional data analysis techniques are usedto examine differences in graph measures that result from the choice of fiber tracking algorithm. The graph metrics consistently showed good levels of reproducibility as measured with ICC, with the exception of some instability at low graph density levels. The global and local efficiency measures were the most robust to the choice of fiber tracking algorithm

Adaptive query-based sampling of distributed collections

As part of a Distributed Information Retrieval system a de-scription of each remote information resource, archive or repository is usually stored centrally in order to facilitate resource selection. The ac-quisition ofprecise resourcedescriptionsistherefore animportantphase in Distributed Information Retrieval, as the quality of such represen-tations will impact on selection accuracy, and ultimately retrieval per-formance. While Query-Based Sampling is currently used for content discovery of uncooperative resources, the application of this technique is dependent upon heuristic guidelines to determine when a sufficiently accurate representation of each remote resource has been obtained. In this paper we address this shortcoming by using the Predictive Likelihood to provide both an indication of thequality of an acquired resource description estimate, and when a sufficiently good representation of a resource hasbeen obtained during Query-Based Sampling

Camera distortion self-calibration using the plumb-line constraint and minimal Hough entropy

In this paper we present a simple and robust method for self-correction of camera distortion using single images of scenes which contain straight lines. Since the most common distortion can be modelled as radial distortion, we illustrate the method using the Harris radial distortion model, but the method is applicable to any distortion model. The method is based on transforming the edgels of the distorted image to a 1-D angular Hough space, and optimizing the distortion correction parameters which minimize the entropy of the corresponding normalized histogram. Properly corrected imagery will have fewer curved lines, and therefore less spread in Hough space. Since the method does not rely on any image structure beyond the existence of edgels sharing some common orientations and does not use edge fitting, it is applicable to a wide variety of image types. For instance, it can be applied equally well to images of texture with weak but dominant orientations, or images with strong vanishing points. Finally, the method is performed on both synthetic and real data revealing that it is particularly robust to noise.Comment: 9 pages, 5 figures Corrected errors in equation 1

Phase transitions in optimal unsupervised learning

We determine the optimal performance of learning the orientation of the symmetry axis of a set of P = alpha N points that are uniformly distributed in all the directions but one on the N-dimensional sphere. The components along the symmetry breaking direction, of unitary vector B, are sampled from a mixture of two gaussians of variable separation and width. The typical optimal performance is measured through the overlap Ropt=B.J* where J* is the optimal guess of the symmetry breaking direction. Within this general scenario, the learning curves Ropt(alpha) may present first order transitions if the clusters are narrow enough. Close to these transitions, high performance states can be obtained through the minimization of the corresponding optimal potential, although these solutions are metastable, and therefore not learnable, within the usual bayesian scenario.Comment: 9 pages, 8 figures, submitted to PRE, This new version of the paper contains one new section, Bayesian versus optimal solutions, where we explain in detail the results supporting our claim that bayesian learning may not be optimal. Figures 4 of the first submission was difficult to understand. We replaced it by two new figures (Figs. 4 and 5 in this new version) containing more detail

One, four or 100 genera? A new classification of the cone snails

International audienc

Superparamagnetic-like behaviour in RE2WO6 tungstates (where RE = Nd, Sm, Eu, Gd, Dy, Ho and Er)

The magnetization isotherms were used to study the superparamagnetic-like behaviour in polycrystalline (powder) RE2WO6 tungstates (where RE = Nd, Sm, Eu, Gd, Dy, Ho and Er). The magnetization isotherms of the majority tungstates under study revealed both the spontaneous magnetic moments and hysteresis characteristic for the superparamagnetic-like behaviour with blocking temperature TB ¼ 30 K except the Sm2WO6 and Eu2WO6 compounds