1,157 research outputs found
Galactic and Extragalactic Samples of Supernova Remnants: How They Are Identified and What They Tell Us
Supernova remnants (SNRs) arise from the interaction between the ejecta of a
supernova (SN) explosion and the surrounding circumstellar and interstellar
medium. Some SNRs, mostly nearby SNRs, can be studied in great detail. However,
to understand SNRs as a whole, large samples of SNRs must be assembled and
studied. Here, we describe the radio, optical, and X-ray techniques which have
been used to identify and characterize almost 300 Galactic SNRs and more than
1200 extragalactic SNRs. We then discuss which types of SNRs are being found
and which are not. We examine the degree to which the luminosity functions,
surface-brightness distributions and multi-wavelength comparisons of the
samples can be interpreted to determine the class properties of SNRs and
describe efforts to establish the type of SN explosion associated with a SNR.
We conclude that in order to better understand the class properties of SNRs, it
is more important to study (and obtain additional data on) the SNRs in galaxies
with extant samples at multiple wavelength bands than it is to obtain samples
of SNRs in other galaxiesComment: Final 2016 draft of a chapter in "Handbook of Supernovae" edited by
Athem W. Alsabti and Paul Murdin. Final version available at
https://doi.org/10.1007/978-3-319-20794-0_90-
A combinatorial TIR1/AFB–Aux/IAA co-receptor system for differential sensing of auxin
The plant hormone auxin regulates virtually every aspect of plant growth and development. Auxin acts by binding the F-box protein transport inhibitor response 1 (TIR1) and promotes the degradation of the AUXIN/INDOLE-3-ACETIC ACID (Aux/IAA) transcriptional repressors. Here we show that efficient auxin binding requires assembly of an auxin co-receptor complex consisting of TIR1 and an Aux/IAA protein. Heterologous experiments in yeast and quantitative IAA binding assays using purified proteins showed that different combinations of TIR1 and Aux/IAA proteins form co-receptor complexes with a wide range of auxin-binding affinities. Auxin affinity seems to be largely determined by the Aux/IAA. As there are 6 TIR1/AUXIN SIGNALING F-BOX proteins (AFBs) and 29 Aux/IAA proteins in Arabidopsis thaliana, combinatorial interactions may result in many co-receptors with distinct auxin-sensing properties. We also demonstrate that the AFB5–Aux/IAA co-receptor selectively binds the auxinic herbicide picloram. This co-receptor system broadens the effective concentration range of the hormone and may contribute to the complexity of auxin response
Ancestry reported by white adults with cutaneous melanoma and control subjects in central Alabama
BACKGROUND: We sought to evaluate the hypothesis that the high incidence of cutaneous melanoma in white persons in central Alabama is associated with a predominance of Irish and Scots descent. METHODS: Frequencies of country of ancestry reports were tabulated. The reports were also converted to scores that reflect proportional countries of ancestry in individuals. Using the scores, we computed aggregate country of ancestry indices as estimates of group ancestry composition. HLA-DRB1*04 allele frequencies and relationships to countries of ancestry were compared in probands and controls. Results were compared to those of European populations with HLA-DRB1*04 frequencies. RESULTS: Ninety evaluable adult white cutaneous melanoma probands and 324 adult white controls reported countries of ancestry of their grandparents. The respective frequencies of Ireland, and Scotland and "British Isles" reported countries of ancestry were significantly greater in probands than in controls. The respective frequencies of Wales, France, Italy and Poland were significantly greater in controls. 16.7% of melanoma probands and 23.8% of controls reported "Native American" ancestry; the corresponding "Native American" country of ancestry index was not significantly different in probands and controls. The frequency of HLA-DRB1*04 was significantly greater in probands, but was not significantly associated with individual or aggregate countries of ancestry. The frequency of DRB1*04 observed in Alabama was compared to DRB1*04 frequencies reported from England, Wales, Ireland, Orkney Island, France, Germany, and Australia. CONCLUSION: White adults with cutaneous melanoma in central Alabama have a predominance of Irish, Scots, and "British Isles" ancestry and HLA-DRB1*04 that likely contributes to their high incidence of cutaneous melanoma
Study of CP violation in Dalitz-plot analyses of B0 --> K+K-KS, B+ --> K+K-K+, and B+ --> KSKSK+
We perform amplitude analyses of the decays , , and , and measure CP-violating
parameters and partial branching fractions. The results are based on a data
sample of approximately decays, collected with the
BABAR detector at the PEP-II asymmetric-energy factory at the SLAC National
Accelerator Laboratory. For , we find a direct CP asymmetry
in of , which differs
from zero by . For , we measure the
CP-violating phase .
For , we measure an overall direct CP asymmetry of
. We also perform an angular-moment analysis of
the three channels, and determine that the state can be described
well by the sum of the resonances , , and
.Comment: 35 pages, 68 postscript figures. v3 - minor modifications to agree
with published versio
Genome-assisted prediction of a quantitative trait measured in parents and progeny: application to food conversion rate in chickens
Accuracy of prediction of yet-to-be observed phenotypes for food conversion rate (FCR) in broilers was studied in a genome-assisted selection context. Data consisted of FCR measured on the progeny of 394 sires with SNP information. A Bayesian regression model (Bayes A) and a semi-parametric approach (Reproducing kernel Hilbert Spaces regression, RKHS) using all available SNPs (p = 3481) were compared with a standard linear model in which future performance was predicted using pedigree indexes in the absence of genomic data. The RKHS regression was also tested on several sets of pre-selected SNPs (p = 400) using alternative measures of the information gain provided by the SNPs. All analyses were performed using 333 genotyped sires as training set, and predictions were made on 61 birds as testing set, which were sons of sires in the training set. Accuracy of prediction was measured as the Spearman correlation (r¯S) between observed and predicted phenotype, with its confidence interval assessed through a bootstrap approach. A large improvement of genome-assisted prediction (up to an almost 4-fold increase in accuracy) was found relative to pedigree index. Bayes A and RKHS regression were equally accurate (r¯S = 0.27) when all 3481 SNPs were included in the model. However, RKHS with 400 pre-selected informative SNPs was more accurate than Bayes A with all SNPs
A Measurement of Rb using a Double Tagging Method
The fraction of Z to bbbar events in hadronic Z decays has been measured by
the OPAL experiment using the data collected at LEP between 1992 and 1995. The
Z to bbbar decays were tagged using displaced secondary vertices, and high
momentum electrons and muons. Systematic uncertainties were reduced by
measuring the b-tagging efficiency using a double tagging technique. Efficiency
correlations between opposite hemispheres of an event are small, and are well
understood through comparisons between real and simulated data samples. A value
of Rb = 0.2178 +- 0.0011 +- 0.0013 was obtained, where the first error is
statistical and the second systematic. The uncertainty on Rc, the fraction of Z
to ccbar events in hadronic Z decays, is not included in the errors. The
dependence on Rc is Delta(Rb)/Rb = -0.056*Delta(Rc)/Rc where Delta(Rc) is the
deviation of Rc from the value 0.172 predicted by the Standard Model. The
result for Rb agrees with the value of 0.2155 +- 0.0003 predicted by the
Standard Model.Comment: 42 pages, LaTeX, 14 eps figures included, submitted to European
Physical Journal
International Veterinary Epilepsy Task Force consensus proposal: Medical treatment of canine epilepsy in Europe
In Europe, the number of antiepileptic drugs (AEDs) licensed for dogs has grown considerably over the last years. Nevertheless, the same questions remain, which include, 1) when to start treatment, 2) which drug is best used initially, 3) which adjunctive AED can be advised if treatment with the initial drug is unsatisfactory, and 4) when treatment changes should be considered. In this consensus proposal, an overview is given on the aim of AED treatment, when to start long-term treatment in canine epilepsy and which veterinary AEDs are currently in use for dogs. The consensus proposal for drug treatment protocols, 1) is based on current published evidence-based literature, 2) considers the current legal framework of the cascade regulation for the prescription of veterinary drugs in Europe, and 3) reflects the authors’ experience. With this paper it is aimed to provide a consensus for the management of canine idiopathic epilepsy. Furthermore, for the management of structural epilepsy AEDs are inevitable in addition to treating the underlying cause, if possible
Measurement of the B+ and B-0 lifetimes and search for CP(T) violation using reconstructed secondary vertices
The lifetimes of the B+ and B-0 mesons, and their ratio, have been measured in the OPAL experiment using 2.4 million hadronic Z(0) decays recorded at LEP. Z(0) --> b (b) over bar decays were tagged using displaced secondary vertices and high momentum electrons and muons. The lifetimes were then measured using well-reconstructed charged and neutral secondary vertices selected in this tagged data sample. The results aretau(B+) = 1.643 +/- 0.037 +/- 0.025 pstau(Bo) = 1.523 +/- 0.057 +/- 0.053 pstau(B+)/tau(Bo) = 1.079 +/- 0.064 +/- 0.041,where in each case the first error is statistical and the second systematic.A larger data sample of 3.1 million hadronic Z(o) decays has been used to search for CP and CPT violating effects by comparison of inclusive b and (b) over bar hadron decays, No evidence fur such effects is seen. The CP violation parameter Re(epsilon(B)) is measured to be Re(epsilon(B)) = 0.001 +/- 0.014 +/- 0.003and the fractional difference between b and (b) over bar hadron lifetimes is measured to(Delta tau/tau)(b) = tau(b hadron) - tau((b) over bar hadron)/tau(average) = -0.001 +/- 0.012 +/- 0.008
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