Electromagnetic Cascades and Cascade Nucleosynthesis in the Early Universe

We describe a calculation of electromagnetic cascading in radiation and matter in the early universe initiated by the decay of massive particles or by some other process. We have used a combination of Monte Carlo and numerical techniques which enables us to use exact cross sections, where known, for all the relevant processes. In cascades initiated after the epoch of big bang nucleosynthesis $\gamma$-rays in the cascades will photodisintegrate $^4$He, producing $^3$He and deuterium. Using the observed $^3$He and deuterium abundances we are able to place constraints on the cascade energy deposition as a function of cosmic time. In the case of the decay of massive primordial particles, we place limits on the density of massive primordial particles as a function of their mean decay time, and on the expected intensity of decay neutrinos.Comment: compressed and uuencoded postscript. We now include a comparison with previous work of the photon spectrum in the cascade and the limits we calculate for the density of massive particles. The method of calculation of photon spectra at low energies has been improved. Most figures are revised. Our conclusions are substantially unchange

Species Abundance Patterns in Complex Evolutionary Dynamics

An analytic theory of species abundance patterns (SAPs) in biological networks is presented. The theory is based on multispecies replicator dynamics equivalent to the Lotka-Volterra equation, with diverse interspecies interactions. Various SAPs observed in nature are derived from a single parameter. The abundance distribution is formed like a widely observed left-skewed lognormal distribution. As the model has a general form, the result can be applied to similar patterns in other complex biological networks, e.g. gene expression.Comment: 4 pages, 3 figures. Physical Review Letters, in pres

Electron-based crystalline undulator

We discuss the features of a crystalline undulator of the novel type based on the effect of a planar channeling of ultra-relativistic electrons in a periodically bent crystals. It is demonstrated that an electron-based undulator is feasible in the tens of GeV range of the beam energies, which is noticeably higher than the energy interval allowed in a positron-based undulator. Numerical analysis of the main parameters of the undulator as well as the characteristics of the emitted undulator radiation is carried out for 20 and 50 GeV electrons channeling in diamond and silicon crystals along the (111) crystallographic planes.Comment: 16 pages, 8 figures, Latex, IOP styl

Ranking differentially expressed genes from Affymetrix gene expression data: methods with reproducibility, sensitivity, and specificity

<p>Abstract</p> <p>Background</p> <p>To identify differentially expressed genes (DEGs) from microarray data, users of the Affymetrix GeneChip system need to select both a preprocessing algorithm to obtain expression-level measurements and a way of ranking genes to obtain the most plausible candidates. We recently recommended suitable combinations of a preprocessing algorithm and gene ranking method that can be used to identify DEGs with a higher level of sensitivity and specificity. However, in addition to these recommendations, researchers also want to know which combinations enhance reproducibility.</p> <p>Results</p> <p>We compared eight conventional methods for ranking genes: weighted average difference (WAD), average difference (AD), fold change (FC), rank products (RP), moderated <it>t </it>statistic (modT), significance analysis of microarrays (samT), shrinkage <it>t </it>statistic (shrinkT), and intensity-based moderated <it>t </it>statistic (ibmT) with six preprocessing algorithms (PLIER, VSN, FARMS, multi-mgMOS (mmgMOS), MBEI, and GCRMA). A total of 36 real experimental datasets was evaluated on the basis of the area under the receiver operating characteristic curve (AUC) as a measure for both sensitivity and specificity. We found that the RP method performed well for VSN-, FARMS-, MBEI-, and GCRMA-preprocessed data, and the WAD method performed well for mmgMOS-preprocessed data. Our analysis of the MicroArray Quality Control (MAQC) project's datasets showed that the FC-based gene ranking methods (WAD, AD, FC, and RP) had a higher level of reproducibility: The percentages of overlapping genes (POGs) across different sites for the FC-based methods were higher overall than those for the <it>t</it>-statistic-based methods (modT, samT, shrinkT, and ibmT). In particular, POG values for WAD were the highest overall among the FC-based methods irrespective of the choice of preprocessing algorithm.</p> <p>Conclusion</p> <p>Our results demonstrate that to increase sensitivity, specificity, and reproducibility in microarray analyses, we need to select suitable combinations of preprocessing algorithms and gene ranking methods. We recommend the use of FC-based methods, in particular RP or WAD.</p

Study of photo-proton reactions driven by bremsstrahlung radiation of high-intensity laser generated electrons

Photo-nuclear reactions were investigated using a high power table-top laser. The laser system at the University of Jena ( I similar to 3-5 x 10(19) W cm(-2)) produced hard bremsstrahlung photons ( kT similar to 2(9 MeV) via a laser-gas interaction which served to induce ( gamma, p) and ( gamma, n) reactions in Mg, Ti, Zn and Mo isotopes. Several ( gamma, p) decay channels were identified using nuclear activation analysis to determine their integral reaction yields

A robust measure of correlation between two genes on a microarray

<p>Abstract</p> <p>Background</p> <p>The underlying goal of microarray experiments is to identify gene expression patterns across different experimental conditions. Genes that are contained in a particular pathway or that respond similarly to experimental conditions could be co-expressed and show similar patterns of expression on a microarray. Using any of a variety of clustering methods or gene network analyses we can partition genes of interest into groups, clusters, or modules based on measures of similarity. Typically, Pearson correlation is used to measure distance (or similarity) before implementing a clustering algorithm. Pearson correlation is quite susceptible to outliers, however, an unfortunate characteristic when dealing with microarray data (well known to be typically quite noisy.)</p> <p>Results</p> <p>We propose a resistant similarity metric based on Tukey's biweight estimate of multivariate scale and location. The resistant metric is simply the correlation obtained from a resistant covariance matrix of scale. We give results which demonstrate that our correlation metric is much more resistant than the Pearson correlation while being more efficient than other nonparametric measures of correlation (e.g., Spearman correlation.) Additionally, our method gives a systematic gene flagging procedure which is useful when dealing with large amounts of noisy data.</p> <p>Conclusion</p> <p>When dealing with microarray data, which are known to be quite noisy, robust methods should be used. Specifically, robust distances, including the biweight correlation, should be used in clustering and gene network analysis.</p