Non-Singularity of the Exact Two-Dimensional String Black Hole

We study the global structure of the exact two-dimensional space-time which emerges from string theory. Previous work has shown that in the semi-classical limit, this is a black hole similar to the Schwarzschild solution. However, we find that in the exact case, a new Euclidean region appears "between" the singularity and black hole interior. However the boundary between the Lorentzian and Euclidean regions is a coordinate singularity, which turns out to be a surface of time reflection symmetry in an extended space-time. Thus strings having fallen through the black hole horizon would eventually emerge through another one into a new asymptotically flat region. The maximally extended space-time consists of an infinite number of universes connected by wormholes. There are no singularities present in this geometry. We also calculate the mass and temperature associated with the space-time.Comment: 9 pages, latex, DAMTP R93/

Applying phylogenomics to understand the emergence of Shiga Toxin producing Escherichia coli O157:H7 strains causing severe human disease in the United Kingdom

Shiga Toxin producing Escherichia coli (STEC) O157:H7 is a recently emerged zoonotic pathogen with considerable morbidity. Since the serotype emerged in the 1980s, research has focussed on unravelling the evolutionary events from the E. coli O55:H7 ancestor to the contemporaneous globally dispersed strains. In this study the genomes of over 1000 isolates from human clinical cases and cattle, spanning the history of STEC O157:H7 in the United Kingdom were sequenced. Phylogenetic analysis reveals the ancestry, key acquisition events and global context of the strains. Dated phylogenies estimate the time to the most recent common ancestor of the current circulating global clone to 175 years ago, followed by rapid diversification. We show the acquisition of specific virulence determinates occurred relatively recently and coincides with its recent detection in the human population. Using clinical outcome data from 493 cases of STEC O157:H7 we assess the relative risk of severe disease including HUS from each of the defined clades in the population and show the dramatic effect Shiga toxin complement has on virulence. We describe two strain replacement events that have occurred in the cattle population in the UK over the last 30 years; one resulting in a highly virulent strain that has accounted for the majority of clinical cases in the UK over the last decade. This work highlights the need to understand the selection pressures maintaining Shiga-toxin encoding bacteriophages in the ruminant reservoir and the study affirms the requirement for close surveillance of this pathogen in both ruminant and human populations

Geographical and climatic limits of needle types of one- and two-needled pinyon pines

Aim The geographical extent and climatic tolerances of one- and two-needled pinyon pines (Pinus subsect. Cembroides) are the focus of questions in taxonomy, palaeoclimatology and modelling of future distributions. The identification of these pines, traditionally classified by one- versus two-needled fascicles, is complicated by populations with both one- and two-needled fascicles on the same tree, and the description of two more recently described one-needled varieties: the fallax-type and californiarum-type. Because previous studies have suggested correlations between needle anatomy and climate, including anatomical plasticity reflecting annual precipitation, we approached this study at the level of the anatomy of individual pine needles rather than species. Location Western North America. Methods We synthesized available and new data from field and herbarium collections of needles to compile maps of their current distributions across western North America. Annual frequencies of needle types were compared with local precipitation histories for some stands. Historical North American climates were modeled on a c. 1-km grid using monthly temperature and precipitation values. A geospatial model (ClimLim), which analyses the effect of climate modulated physiological and ecosystem processes, was used to rank the importance of seasonal climate variables in limiting the distributions of anatomical needle types. Results The pinyon needles were classified into four distinct types based upon the number of needles per fascicle, needle thickness and the number of stomatal rows and resin canals. The individual needles fit well into four categories of needle types, whereas some trees exhibit a mixture of two needle types. Trees from central Arizona containing a mixture of Pinus edulis and fallax-type needles increased their percentage of fallax-type needles following dry years. All four needle types occupy broader geographical regions with distinctive precipitation regimes. Pinus monophylla and californiarum-type needles occur in regions with high winter precipitation. Pinus edulis and fallax-type needles are found in regions with high monsoon precipitation. Areas supporting californiarum-type and fallax-type needle distributions are additionally characterized by a more extreme May–June drought. Main conclusions These pinyon needle types seem to reflect the amount and seasonality of precipitation. The single needle fascicle characterizing the fallax type may be an adaptation to early summer or periodic drought, while the single needle of Pinus monophylla may be an adaptation to summer–autumn drought. Although the needles fit into four distinct categories, the parent trees are sometimes less easily classified, especially near their ancestral Pleistocene ranges in the Mojave and northern Sonoran deserts. The abundance of trees with both one- and two-needled fascicles in the zones between P. monophylla, P. edulis and fallax-type populations suggest that needle fascicle number is an unreliable characteristic for species classification. Disregarding needle fascicle number, the fallax-type needles are nearly identical to P. edulis, supporting Little’s (1968) initial classification of these trees as P. edulis var. fallax, while the californiarum-type needles have a distinctive morphology supporting Bailey’s (1987) classification of this tree as Pinus californiarum

Measurement of the Bottom-Strange Meson Mixing Phase in the Full CDF Data Set

We report a measurement of the bottom-strange meson mixing phase \beta_s using the time evolution of B0_s -> J/\psi (->\mu+\mu-) \phi (-> K+ K-) decays in which the quark-flavor content of the bottom-strange meson is identified at production. This measurement uses the full data set of proton-antiproton collisions at sqrt(s)= 1.96 TeV collected by the Collider Detector experiment at the Fermilab Tevatron, corresponding to 9.6 fb-1 of integrated luminosity. We report confidence regions in the two-dimensional space of \beta_s and the B0_s decay-width difference \Delta\Gamma_s, and measure \beta_s in [-\pi/2, -1.51] U [-0.06, 0.30] U [1.26, \pi/2] at the 68% confidence level, in agreement with the standard model expectation. Assuming the standard model value of \beta_s, we also determine \Delta\Gamma_s = 0.068 +- 0.026 (stat) +- 0.009 (syst) ps-1 and the mean B0_s lifetime, \tau_s = 1.528 +- 0.019 (stat) +- 0.009 (syst) ps, which are consistent and competitive with determinations by other experiments.Comment: 8 pages, 2 figures, Phys. Rev. Lett 109, 171802 (2012

Improving Genetic Prediction by Leveraging Genetic Correlations Among Human Diseases and Traits

Genomic prediction has the potential to contribute to precision medicine. However, to date, the utility of such predictors is limited due to low accuracy for most traits. Here theory and simulation study are used to demonstrate that widespread pleiotropy among phenotypes can be utilised to improve genomic risk prediction. We show how a genetic predictor can be created as a weighted index that combines published genome-wide association study (GWAS) summary statistics across many different traits. We apply this framework to predict risk of schizophrenia and bipolar disorder in the Psychiatric Genomics consortium data, finding substantial heterogeneity in prediction accuracy increases across cohorts. For six additional phenotypes in the UK Biobank data, we find increases in prediction accuracy ranging from 0.7 for height to 47 for type 2 diabetes, when using a multi-trait predictor that combines published summary statistics from multiple traits, as compared to a predictor based only on one trait. © 2018 The Author(s)