80 research outputs found

    The Energy Density in the Maxwell-Chern-Simons Theory

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    A two-dimensional nonrelativistic fermion system coupled to both electromagnetic gauge fields and Chern-Simons gauge fields is analysed. Polarization tensors relevant in the quantum Hall effect and anyon superconductivity are obtained as simple closed integrals and are evaluated numerically for all momenta and frequencies. The correction to the energy density is evaluated in the random phase approximation (RPA), by summing an infinite series of ring diagrams. It is found that the correction has significant dependence on the particle number density. In the context of anyon superconductivity, the energy density relative to the mean field value is minimized at a hole concentration per lattice plaquette (0.05 \sim 0.06) (p_c a/\hbar)^2 where p_c and a are the momentum cutoff and lattice constant, respectively. At the minimum the correction is about -5 % \sim -25 %, depending on the ratio (2m \omega_c)/(p_c^2) where \omega_c is the frequency cutoff. In the Jain-Fradkin-Lopez picture of the fractional quantum Hall effect the RPA correction to the energy density is very large. It diverges logarithmically as the cutoff is removed, implying that corrections beyond RPA become important at large momentum and frequency.Comment: 19 pages (plain Tex), 12 figures not included, UMN-TH-1246/9

    Defending the genome from the enemy within:mechanisms of retrotransposon suppression in the mouse germline

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    The viability of any species requires that the genome is kept stable as it is transmitted from generation to generation by the germ cells. One of the challenges to transgenerational genome stability is the potential mutagenic activity of transposable genetic elements, particularly retrotransposons. There are many different types of retrotransposon in mammalian genomes, and these target different points in germline development to amplify and integrate into new genomic locations. Germ cells, and their pluripotent developmental precursors, have evolved a variety of genome defence mechanisms that suppress retrotransposon activity and maintain genome stability across the generations. Here, we review recent advances in understanding how retrotransposon activity is suppressed in the mammalian germline, how genes involved in germline genome defence mechanisms are regulated, and the consequences of mutating these genome defence genes for the developing germline

    Microarray-Based Sketches of the HERV Transcriptome Landscape

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    Human endogenous retroviruses (HERVs) are spread throughout the genome and their long terminal repeats (LTRs) constitute a wide collection of putative regulatory sequences. Phylogenetic similarities and the profusion of integration sites, two inherent characteristics of transposable elements, make it difficult to study individual locus expression in a large-scale approach, and historically apart from some placental and testis-regulated elements, it was generally accepted that HERVs are silent due to epigenetic control. Herein, we have introduced a generic method aiming to optimally characterize individual loci associated with 25-mer probes by minimizing cross-hybridization risks. We therefore set up a microarray dedicated to a collection of 5,573 HERVs that can reasonably be assigned to a unique genomic position. We obtained a first view of the HERV transcriptome by using a composite panel of 40 normal and 39 tumor samples. The experiment showed that almost one third of the HERV repertoire is indeed transcribed. The HERV transcriptome follows tropism rules, is sensitive to the state of differentiation and, unexpectedly, seems not to correlate with the age of the HERV families. The probeset definition within the U3 and U5 regions was used to assign a function to some LTRs (i.e. promoter or polyA) and revealed that (i) autonomous active LTRs are broadly subjected to operational determinism (ii) the cellular gene density is substantially higher in the surrounding environment of active LTRs compared to silent LTRs and (iii) the configuration of neighboring cellular genes differs between active and silent LTRs, showing an approximately 8 kb zone upstream of promoter LTRs characterized by a drastic reduction in sense cellular genes. These gathered observations are discussed in terms of virus/host adaptive strategies, and together with the methods and tools developed for this purpose, this work paves the way for further HERV transcriptome projects

    Step by step: reconstruction of terrestrial animal movement paths by dead-reckoning

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    Background: Research on wild animal ecology is increasingly employing GPS telemetry in order to determine animal movement. However, GPS systems record position intermittently, providing no information on latent position or track tortuosity. High frequency GPS have high power requirements, which necessitates large batteries (often effectively precluding their use on small animals) or reduced deployment duration. Dead-reckoning is an alternative approach which has the potential to ‘fill in the gaps’ between less resolute forms of telemetry without incurring the power costs. However, although this method has been used in aquatic environments, no explicit demonstration of terrestrial dead-reckoning has been presented.Results: We perform a simple validation experiment to assess the rate of error accumulation in terrestrial dead-reckoning. In addition, examples of successful implementation of dead-reckoning are given using data from the domestic dog Canus lupus, horse Equus ferus, cow Bos taurus and wild badger Meles meles.Conclusions: This study documents how terrestrial dead-reckoning can be undertaken, describing derivation of heading from tri-axial accelerometer and tri-axial magnetometer data, correction for hard and soft iron distortions on the magnetometer output, and presenting a novel correction procedure to marry dead-reckoned paths to ground-truthed positions. This study is the first explicit demonstration of terrestrial dead-reckoning, which provides a workable method of deriving the paths of animals on a step-by-step scale. The wider implications of this method for the understanding of animal movement ecology are discussed
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