290 research outputs found
Lattice dynamics and correlated atomic motion from the atomic pair distribution function
The mean-square relative displacements (MSRD) of atomic pair motions in
crystals are studied as a function of pair distance and temperature using the
atomic pair distribution function (PDF). The effects of the lattice vibrations
on the PDF peak widths are modelled using both a multi-parameter Born
von-Karman (BvK) force model and a single-parameter Debye model. These results
are compared to experimentally determined PDFs. We find that the near-neighbor
atomic motions are strongly correlated, and that the extent of this correlation
depends both on the interatomic interactions and crystal structure. These
results suggest that proper account of the lattice vibrational effects on the
PDF peak width is important in extracting information on static disorder in a
disordered system such as an alloy. Good agreement is obtained between the BvK
model calculations of PDF peak widths and the experimentally determined peak
widths. The Debye model successfully explains the average, though not detailed,
natures of the MSRD of atomic pair motion with just one parameter. Also the
temperature dependence of the Debye model largely agrees with the BvK model
predictions. Therefore, the Debye model provides a simple description of the
effects of lattice vibrations on the PDF peak widths.Comment: 9 pages, 11 figure
A Classifier-based approach to identify genetic similarities between diseases
Motivation: Genome-wide association studies are commonly used to identify possible associations between genetic variations and diseases. These studies mainly focus on identifying individual single nucleotide polymorphisms (SNPs) potentially linked with one disease of interest. In this work, we introduce a novel methodology that identifies similarities between diseases using information from a large number of SNPs. We separate the diseases for which we have individual genotype data into one reference disease and several query diseases. We train a classifier that distinguishes between individuals that have the reference disease and a set of control individuals. This classifier is then used to classify the individuals that have the query diseases. We can then rank query diseases according to the average classification of the individuals in each disease set, and identify which of the query diseases are more similar to the reference disease. We repeat these classification and comparison steps so that each disease is used once as reference disease
Peak positions and shapes in neutron pair correlation functions from powders of highly anisotropic crystals
The effect of the powder average on the peak shapes and positions in neutron
pair distribution functions of polycrystalline materials is examined. It is
shown that for highly anisotropic crystals, the powder average leads to shifts
in peak positions and to non-Gaussian peak shapes. The peak shifts can be as
large as several percent of the lattice spacing
European integration assessed in the light of the 'rules vs. standards debate'
The interplay of various legal systems in the European Union (EU) has long triggered a debate on the tension between uniformity and diversity of Member States' (MS) laws. This debate takes place among European legal scholars and is also paralleled by economic scholars, e.g. in the ambit of the 'theory of federalism'. This paper takes an innovative perspective on the discrepancy between 'centralized' and 'decentralized' law-making in the EU by assessing it with the help of the rules versus standards debate. When should the EU legislator grant the national legislator leeway in the formulation of new laws and when should all be fixed ex ante at European level? The literature on the 'optimal shape of legal norms' shall be revisited in the light of law-making in the EU, centrally dealing with the question how much discretion shall be given to the national legislator; and under which circumstances. This paper enhances the established decisive factors for the choice of a rule or a standard in a national setting (complexity, volatility, judges' specialization and frequency of application) by two new crucial factors (switching costs and the benefit of uniformity in terms of information costs) in order to assess law-making policies at EU level
Use of Data-Biased Random Walks on Graphs for the Retrieval of Context-Specific Networks from Genomic Data
Extracting network-based functional relationships within genomic datasets is an important challenge in the computational analysis of large-scale data. Although many methods, both public and commercial, have been developed, the problem of identifying networks of interactions that are most relevant to the given input data still remains an open issue. Here, we have leveraged the method of random walks on graphs as a powerful platform for scoring network components based on simultaneous assessment of the experimental data as well as local network connectivity. Using this method, NetWalk, we can calculate distribution of Edge Flux values associated with each interaction in the network, which reflects the relevance of interactions based on the experimental data. We show that network-based analyses of genomic data are simpler and more accurate using NetWalk than with some of the currently employed methods. We also present NetWalk analysis of microarray gene expression data from MCF7 cells exposed to different doses of doxorubicin, which reveals a switch-like pattern in the p53 regulated network in cell cycle arrest and apoptosis. Our analyses demonstrate the use of NetWalk as a valuable tool in generating high-confidence hypotheses from high-content genomic data
Risk factors predict post-traumatic stress disorder differently in men and women
<p>Abstract</p> <p>Background</p> <p>About twice as many women as men develop post-traumatic stress disorder (PTSD), even though men as a group are exposed to more traumatic events. Exposure to different trauma types does not sufficiently explain why women are more vulnerable.</p> <p>Methods</p> <p>The present work examines the effect of age, previous trauma, negative affectivity (NA), anxiety, depression, persistent dissociation, and social support on PTSD separately in men and women. Subjects were exposed to either a series of explosions in a firework factory near a residential area or to a high school stabbing incident.</p> <p>Results</p> <p>Some gender differences were found in the predictive power of well known risk factors for PTSD. Anxiety predicted PTSD in men, but not in women, whereas the opposite was found for depression. Dissociation was a better predictor for PTSD in women than in men in the explosion sample but not in the stabbing sample. Initially, NA predicted PTSD better in women than men in the explosion sample, but when compared only to other significant risk factors, it significantly predicted PTSD for both men and women in both studies. Previous traumatic events and age did not significantly predict PTSD in either gender.</p> <p>Conclusion</p> <p>Gender differences in the predictive value of social support on PTSD appear to be very complex, and no clear conclusions can be made based on the two studies included in this article.</p
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