Optimized pinhole geometry for small-angle scattering

In order to make the most of the low photon flux in laboratory small-angle X-ray scattering instruments, the experimental geometry has to be chosen carefully, with special stress on the beam-shaping system. The optimum collimation scheme should enable accurate measurements over the desired range of the scattering variable, while yielding the highest flux and the lowest possible instrumental background. In order to identify the best setting, a phase-space optimization of the collimating scheme is carried out in the present work, including constraints on the beam size at the sample position and on the detector surface. The resulting formulae are implemented in a Python script with a graphical user interface, to aid the planning, construction and daily operation of pinhole small-angle scattering cameras

A low variance consistent test of relative dependency

We describe a novel non-parametric statistical hypothesis test of relative dependence between a source variable and two candidate target variables. Such a test enables us to determine whether one source variable is significantly more dependent on a first target variable or a second. Dependence is measured via the Hilbert-Schmidt Independence Criterion (HSIC), resulting in a pair of empirical dependence measures (source-target 1, source-target 2). We test whether the first dependence measure is significantly larger than the second. Modeling the covariance between these HSIC statistics leads to a provably more powerful test than the construction of independent HSIC statistics by sub-sampling. The resulting test is consistent and unbiased, and (being based on U-statistics) has favorable convergence properties. The test can be computed in quadratic time, matching the computational complexity of standard empirical HSIC estimators. The effectiveness of the test is demonstrated on several real-world problems: we identify language groups from a multilingual corpus, and we prove that tumor location is more dependent on gene expression than chromosomal imbalances. Source code is available for download at https://github.com/wbounliphone/reldep.Comment: International Conference on Machine Learning, Jul 2015, Lille, Franc

Measuring Value in Open Access Repositories

Open access institutional repositories were created to promote access to information, encourage scholarly communication, and demonstrate institutional prestige. While these repositories have been widely adopted, the quality of their contents often fails to represent their institution's scholarly output. Moreover, current research uses measurements of quantity, not quality, to assess their value. In response, this article opens new areas of scholarly inquiry by assessing the quality of contents. This is accomplished through a cross-sectional study of repositories at American colleges and universities across the academic spectrum, using citation indexing to identify an institution's articles and authors of highest impact

"Electronic Guide to Wildflowers: Maintaining an Online Database for Natural Areas"

Richard S. Wacha is Professor of Biology in the Department of Biology at Drake University. He can be contacted at [email protected] online guide to wildflowers of the Saylorville Lake Recreation Area, Des Moines River Basin, Polk Co., Iowa, is maintained as a public information project in cooperation with the U.S. Army Corps of Engineers. Each wildflower is represented by a digital image and scientific description. Digitally created diagrams of leaf and flower structure are also included. Issues associated with maintenance of the online guide are discussed. These include: (a) collection of data and online delivery methods, (b) features of a traditional guide compared to those of an electronic guide delivered online, (c) an electronic guide as a database, (d) incorporatig online data in CD-ROM and PDF formats, and (e) publishing online data through the peer review process.Funding was received from a Drake University Faculty Research Grant and from the Department of Biology