Optimum Power Randomization for the Minimization of Outage Probability

Cataloged from PDF version of article.The optimum power randomization problem is studied to minimize outage probability in flat block-fading Gaussian channels under an average transmit power constraint and in the presence of channel distribution information at the transmitter. When the probability density function of the channel power gain is continuously differentiable with a finite second moment, it is shown that the outage probability curve is a nonincreasing function of the normalized transmit power with at least one inflection point and the total number of inflection points is odd. Based on this result, it is proved that the optimum power transmission strategy involves randomization between at most two power levels. In the case of a single inflection point, the optimum strategy simplifies to on-off signaling for weak transmitters. Through analytical and numerical discussions, it is shown that the proposed framework can be adapted to a wide variety of scenarios including log-normal shadowing, diversity combining over Rayleigh fading channels, Nakagami-m fading, spectrum sharing, and jamming applications. We also show that power randomization does not necessarily improve the outage performance when the finite second moment assumption is violated by the power distribution of the fading. © 2013 IEEE

The Friedreich ataxia GAA repeat expansion mutation induces comparable epigenetic changes in human and transgenic mouse brain and heart tissues

Friedreich ataxia (FRDA) is caused by a homozygous GAA repeat expansion mutation within intron 1 of the FXN gene, leading to reduced expression of frataxin protein. Evidence suggests that the mutation may induce epigenetic changes and heterochromatin formation, thereby impeding gene transcription. In particular, studies using FRDA patient blood and lymphoblastoid cell lines have detected increased DNA methylation of specific CpG sites upstream of the GAA repeat and histone modifications in regions flanking the GAA repeat. In this report we show that such epigenetic changes are also present in FRDA patient brain, cerebellum and heart tissues, the primary affected systems of the disorder. Bisulfite sequence analysis of the FXN flanking GAA regions reveals a shift in the FRDA DNA methylation profile, with upstream CpG sites becoming consistently hypermethylated and downstream CpG sites becoming consistently hypomethylated. We also identify differential DNA methylation at three specific CpG sites within the FXN promoter and one CpG site within exon 1. Furthermore, we show by chromatin immunoprecipitation (ChIP) analysis that there is overall decreased histone H3K9 acetylation together with increased H3K9 methylation of FRDA brain tissue. Further studies of brain, cerebellum and heart tissues from our GAA repeat expansion-containing FRDA YAC transgenic mice reveal comparable epigenetic changes to those detected in FRDA patient tissue. We have thus developed a mouse model that will be a valuable resource for future therapeutic studies targeting epigenetic modifications of the FXN gene to increase frataxin expression

Response Functions to Critical Shocks in Social Sciences: An Empirical and Numerical Study

We show that, provided one focuses on properly selected episodes, one can apply to the social sciences the same observational strategy that has proved successful in natural sciences such as astrophysics or geodynamics. For instance, in order to probe the cohesion of a policy, one can, in different countries, study the reactions to some huge and sudden exogenous shocks, which we call Dirac shocks. This approach naturally leads to the notion of structural (as opposed or complementary to temporal) forecast. Although structural predictions are by far the most common way to test theories in the natural sciences, they have been much less used in the social sciences. The Dirac shock approach opens the way to testing structural predictions in the social sciences. The examples reported here suggest that critical events are able to reveal pre-existing ``cracks'' because they probe the social cohesion which is an indicator and predictor of future evolution of the system, and in some cases foreshadows a bifurcation. We complement our empirical work with numerical simulations of the response function (``damage spreading'') to Dirac shocks in the Sznajd model of consensus build-up. We quantify the slow relaxation of the difference between perturbed and unperturbed systems, the conditions under which the consensus is modified by the shock and the large variability from one realization to another

Possible manifestation of spin fluctuations in the temperature behavior of resistivity in Sm_{1.85}Ce_{0.15}CuO_4 thin films

A pronounced step-like (kink) behavior in the temperature dependence of resistivity $\rho (T)$ is observed in the optimally-doped $Sm_{1.85}Ce_{0.15}CuO_4$ thin films around $T_{sf}=87K$ and attributed to manifestation of strong spin fluctuations induced by $Sm^{3+}$ moments with the energy $\hbar \omega_{sf}=k_BT_{sf}\simeq 7meV$. In addition to fluctuation induced contribution $\rho_{sf}(T)$ due to thermal broadening effects (of the width $\omega_{sf}$), the experimental data are found to be well fitted accounting for residual (zero-temperature) $\rho_{res}$, electron-phonon $\rho _{e-ph}(T)=AT$ and electron-electron $\rho_{e-e}(T)=BT^2$ contributions. The best fits produced $\omega_p=2.1meV$, $\tau_0^{-1}=9.5\times 10^{-14}s^{-1}$, $\lambda =1.2$, and $E_F=0.2eV$ for estimates of the plasmon frequency, the impurity scattering rate, electron-phonon coupling constant, and the Fermi energy, respectively.Comment: 6 pages (REVTEX4), 2 EPS figures; accepted for publication in JETP Letter

GAA repeat expansion mutation mouse models of Friedreich ataxia exhibit oxidative stress leading to progressive neuronal and cardiac pathology

Friedreich ataxia (FRDA) is a neurodegenerative disorder caused by an unstable GAA repeat expansion mutation within intron 1 of the FXN gene. However, the origins of the GAA repeat expansion, its unstable dynamics within different cells and tissues, and its effects on frataxin expression are not yet completely understood. Therefore, we have chosen to generate representative FRDA mouse models by using the human FXN GAA repeat expansion itself as the genetically modified mutation. We have previously reported the establishment of two lines of human FXN YAC transgenic mice that contain unstable GAA repeat expansions within the appropriate genomic context. We now describe the generation of FRDA mouse models by crossbreeding of both lines of human FXN YAC transgenic mice with heterozygous Fxn knockout mice. The resultant FRDA mice that express only human-derived frataxin show comparatively reduced levels of frataxin mRNA and protein expression, decreased aconitase activity, and oxidative stress, leading to progressive neurodegenerative and cardiac pathological phenotypes. Coordination deficits are present, as measured by accelerating rotarod analysis, together with a progressive decrease in locomotor activity and increase in weight. Large vacuoles are detected within neurons of the dorsal root ganglia (DRG), predominantly within the lumbar regions in 6-month-old mice, but spreading to the cervical regions after 1 year of age. Secondary demyelination of large axons is also detected within the lumbar roots of older mice. Lipofuscin deposition is increased in both DRG neurons and cardiomyocytes, and iron deposition is detected in cardiomyocytes after 1 year of age. These mice represent the first GAA repeat expansion-based FRDA mouse models that exhibit progressive FRDA-like pathology and thus will be of use in testing potential therapeutic strategies, particularly GAA repeat-based strategies. (c) 2006 Elsevier Inc. All rights reserved

Googling the brain: discovering hierarchical and asymmetric network structures, with applications in neuroscience

Hierarchical organisation is a common feature of many directed networks arising in nature and technology. For example, a well-defined message-passing framework based on managerial status typically exists in a business organisation. However, in many real-world networks such patterns of hierarchy are unlikely to be quite so transparent. Due to the nature in which empirical data is collated the nodes will often be ordered so as to obscure any underlying structure. In addition, the possibility of even a small number of links violating any overall “chain of command” makes the determination of such structures extremely challenging. Here we address the issue of how to reorder a directed network in order to reveal this type of hierarchy. In doing so we also look at the task of quantifying the level of hierarchy, given a particular node ordering. We look at a variety of approaches. Using ideas from the graph Laplacian literature, we show that a relevant discrete optimization problem leads to a natural hierarchical node ranking. We also show that this ranking arises via a maximum likelihood problem associated with a new range-dependent hierarchical random graph model. This random graph insight allows us to compute a likelihood ratio that quantifies the overall tendency for a given network to be hierarchical. We also develop a generalization of this node ordering algorithm based on the combinatorics of directed walks. In passing, we note that Google’s PageRank algorithm tackles a closely related problem, and may also be motivated from a combinatoric, walk-counting viewpoint. We illustrate the performance of the resulting algorithms on synthetic network data, and on a real-world network from neuroscience where results may be validated biologically