A Quantitative Analysis of Charmonium Suppression in Nuclear Collisions

Data from J/psi and psi' production in p-A collisions are used to determine the cross section for absorption of pre-resonance charmonium in nuclear matter. The J/psi suppression in O-Cu, O-U and S-U collisions is fully reproduced by the corresponding nuclear absorption, while Pb-Pb collisions show an additional suppression increasing with centrality. We study the onset of this change in terms of hadronic comover interactions and conclude that so far no conventional hadronic description can consistently account for all data. Deconfinement, starting at a critical point determined by central S-U collisions, is in accord with the observed suppression pattern.Comment: 37 pages, 12 figures, uses epsfig style, LaTe

Open charm contribution to dilepton spectra produced in nuclear collisions at SPS energies

Measurements of open charm hadro-production from CERN and Fermilab experiments are reviewed, with particular emphasis on the absolute cross sections and on their A and sqrt(s) dependences. Differential pt and xf cross sections calculated with the Pythia event generator are found to be in reasonable agreement with recent data. The calculations are scaled to nucleus-nucleus collisions and the expected lepton pair yield is deduced. The charm contribution to the low mass dilepton continuum observed by the CERES experiment is found to be negligible. In particular, it is shown that the observed low mass dilepton excess in S-Au collisions cannot be explained by charm enhancement.Comment: 19 pages, 12 eps figures included. To be published in Z.Phys.

Charmonium Composition and Nuclear Suppression

We study charmonium production in hadron-nucleus collisions through the intermediate next-to-leading Fock space component $|(\bar{c}c)_8 g>$, formed by a colour octet $\bar{c}c$ pair and a gluon. We estimate the size of this state and show that its interaction with nucleons accounts for the observed charmonium suppression in nuclear interactions.Comment: Plain TeX, 8 pages, 5 figures available upon reques

Temperature dependence of the electron spin g factor in GaAs

The temperature dependence of the electron spin $g$ factor in GaAs is investigated experimentally and theoretically. Experimentally, the $g$ factor was measured using time-resolved Faraday rotation due to Larmor precession of electron spins in the temperature range between 4.5 K and 190 K. The experiment shows an almost linear increase of the $g$ value with the temperature. This result is in good agreement with other measurements based on photoluminescence quantum beats and time-resolved Kerr rotation up to room temperature. The experimental data are described theoretically taking into account a diminishing fundamental energy gap in GaAs due to lattice thermal dilatation and nonparabolicity of the conduction band calculated using a five-level kp model. At higher temperatures electrons populate higher Landau levels and the average $g$ factor is obtained from a summation over many levels. A very good description of the experimental data is obtained indicating that the observed increase of the spin $g$ factor with the temperature is predominantly due to band's nonparabolicity.Comment: 6 pages 4 figure

The Dimensionality of Genomic Information and Its Effect on Genomic Prediction

The genomic relationship matrix (GRM) can be inverted by the algorithm for proven and young (APY) based on recursion on a random subset of animals. While a regular inverse has a cubic cost, the cost of the APY inverse can be close to linear. Theory for the APY assumes that the optimal size of the subset (maximizing accuracy of genomic predictions) is due to a limited dimensionality of the GRM, which is a function of the effective population size (N(e)). The objective of this study was to evaluate these assumptions by simulation. Six populations were simulated with approximate effective population size (N(e)) from 20 to 200. Each population consisted of 10 nonoverlapping generations, with 25,000 animals per generation and phenotypes available for generations 1–9. The last 3 generations were fully genotyped assuming genome length L = 30. The GRM was constructed for each population and analyzed for distribution of eigenvalues. Genomic estimated breeding values (GEBV) were computed by single-step GBLUP, using either a direct or an APY inverse of GRM. The sizes of the subset in APY were set to the number of the largest eigenvalues explaining x% of variation (EIGx, x = 90, 95, 98, 99) in GRM. Accuracies of GEBV for the last generation with the APY inverse peaked at EIG98 and were slightly lower with EIG95, EIG99, or the direct inverse. Most information in the GRM is contained in ∼N(e)L largest eigenvalues, with no information beyond 4N(e)L. Genomic predictions with the APY inverse of the GRM are more accurate than by the regular inverse

Frequentist p-values for large-scale-single step genome-wide association, with an application to birth weight in American Angus cattle.

Background: Single-step genomic best linear unbiased prediction (SSGBLUP) is a comprehensive method for genomic prediction. Point estimates of marker effects from SSGBLUP are often used for genome-wide association studies (GWAS) without a formal framework of hypothesis testing. Our objective was to implement p-values for singlemarker GWAS studies within the single-step GWAS (SSGWAS) framework by deriving computational algorithms and procedures, and by applying these to a large beef cattle population. Methods: P-values were obtained based on the prediction error (co)variances for single nucleotide polymorphisms (SNPs), which were obtained from the prediction error (co)variances of genomic predictions based on the inverse of the coefficient matrix and formulas to estimate SNP effects. Results: Computation of p-values took a negligible time for a dataset with almost 2 million animals in the pedigree and 1424 genotyped sires, and no inflation of statistics was observed. The SNPs that passed the Bonferroni threshold of 10-5.9 were the same as those that explained the highest proportion of additive genetic variance, but even at the same significance levels and effects, some of them explained less genetic variance due to lower allele frequency. Conclusions: The use of a p-value for SSGWAS is a very general and efficient strategy to identify quantitative trait loci (QTL). It can be used for complex datasets such as those used in animal breeding, where only a proportion of the pedigreed animals are genotyped

Deep electronic states in ion-implanted Si

In this paper we present an overview of the deep states present after ion-implantation by various species into n-type silicon, measured by Deep Level Transient Spectroscopy (DLTS) and high resolution Laplace DLTS (LDLTS). Both point and small extended defects are found, prior to any anneal, which can therefore be the precursors to more detrimental defects such as end of range loops. We show that the ion mass is linked to the concentrations of defects that are observed, and the presence of small interstitial clusters directly after ion implantation is established by comparing their behaviour with that of electrically active stacking faults. Finally, future applications of the LDLTS technique to ion-implanted regions in Si-based devices are outlined.</p

Genome-Wide Association Analysis With a 50K Transcribed Gene SNP-Chip Identifies QTL Affecting Muscle Yield in Rainbow Trout

Detection of coding/functional SNPs that change the biological function of a gene may lead to identification of putative causative alleles within QTL regions and discovery of genetic markers with large effects on phenotypes. This study has two-fold objectives, first to develop, and validate a 50K transcribed gene SNP-chip using RNA-Seq data. To achieve this objective, two bioinformatics pipelines, GATK and SAMtools, were used to identify ∼21K transcribed SNPs with allelic imbalances associated with important aquaculture production traits including body weight, muscle yield, muscle fat content, shear force, and whiteness in addition to resistance/susceptibility to bacterial cold-water disease (BCWD). SNPs ere identified from pooled RNA-Seq data collected from ∼620 fish, representing 98 families from growth- and 54 families from BCWD-selected lines with divergent phenotypes. In addition, ∼29K transcribed SNPs without allelic-imbalances were strategically added to build a 50K Affymetrix SNP-chip. SNPs selected included two SNPs per gene from 14K genes and ∼5K non-synonymous SNPs. The SNP-chip was used to genotype 1728 fish. The average SNP calling-rate for samples passing quality control (QC; 1,641 fish) was ≥ 98.5%. The second objective of this study was to test the feasibility of using the new SNP-chip in GWA (Genome-wide association) analysis to identify QTL explaining muscle yield variance. GWA study on 878 fish (representing 197 families from 2 consecutive generations) with muscle yield phenotypes and genotyped for 35K polymorphic markers (passing QC) identified several QTL regions explaining together up to 28.40% of the additive genetic variance for muscle yield in this rainbow trout population. The most significant QTLs were on chromosomes 14 and 16 with 12.71 and 10.49% of the genetic variance, respectively. Many of the annotated genes in the QTL regions were previously reported as important regulators of muscle development and cell signaling. No major QTLs were identified in a previous GWA study using a 57K genomic SNP chip on the same fish population. These results indicate improved detection power of the transcribed gene SNP-chip in the target trait and population, allowing identification of large-effect QTLs for important traits in rainbow trout