The Science of Sungrazers, Sunskirters, and Other Near-Sun Comets

This review addresses our current understanding of comets that venture close to the Sun, and are hence exposed to much more extreme conditions than comets that are typically studied from Earth. The extreme solar heating and plasma environments that these objects encounter change many aspects of their behaviour, thus yielding valuable information on both the comets themselves that complements other data we have on primitive solar system bodies, as well as on the near-solar environment which they traverse. We propose clear definitions for these comets: We use the term near-Sun comets to encompass all objects that pass sunward of the perihelion distance of planet Mercury (0.307 AU). Sunskirters are defined as objects that pass within 33 solar radii of the Sun’s centre, equal to half of Mercury’s perihelion distance, and the commonly-used phrase sungrazers to be objects that reach perihelion within 3.45 solar radii, i.e. the fluid Roche limit. Finally, comets with orbits that intersect the solar photosphere are termed sundivers. We summarize past studies of these objects, as well as the instruments and facilities used to study them, including space-based platforms that have led to a recent revolution in the quantity and quality of relevant observations. Relevant comet populations are described, including the Kreutz, Marsden, Kracht, and Meyer groups, near-Sun asteroids, and a brief discussion of their origins. The importance of light curves and the clues they provide on cometary composition are emphasized, together with what information has been gleaned about nucleus parameters, including the sizes and masses of objects and their families, and their tensile strengths. The physical processes occurring at these objects are considered in some detail, including the disruption of nuclei, sublimation, and ionisation, and we consider the mass, momentum, and energy loss of comets in the corona and those that venture to lower altitudes. The different components of comae and tails are described, including dust, neutral and ionised gases, their chemical reactions, and their contributions to the near-Sun environment. Comet-solar wind interactions are discussed, including the use of comets as probes of solar wind and coronal conditions in their vicinities. We address the relevance of work on comets near the Sun to similar objects orbiting other stars, and conclude with a discussion of future directions for the field and the planned ground- and space-based facilities that will allow us to address those science topics

Measurement of the WW production cross section in p anti-p collisions at s**(1/2) = 1.96 TeV

We present a measurement of the W boson pair-production cross section in p anti-p collisions at a center-of-mass energy of sqrt{s}=1.96 TeV. The data, collected with the Run II DO detector, correspond to an integrated luminosity of 224-252 pb^-1 depending on the final state (ee, emu or mumu). We observe 25 candidates with a background expectation of 8.1+/-0.6(stat)+/-0.6(syst)+/-0.5(lum) events. The probability for an upward fluctuation of the background to produce the observed signal is 2.3x10^-7, equivalent to 5.2 standard deviations.The measurement yields a cross section of 13.8+4.3/-3.8(stat)+1.2/-0.9(syst)+/-0.9(lum) pb, in agreement with predictions from the standard model.Comment: submitted to PR

Measurement of the Lambda^0_b lifetime in the decay Lambda^0_b -> J/psi Lambda^0 with the D0 Detector

We present measurements of the Lambda^0_b lifetime in the exclusive decay channel Lambda^0_{b}->J/psi Lambda^0, with J/psi to mu+ mu- and Lambda^0 to p pi-, the B^0 lifetime in the decay B^0 -> J/psi K^0_S with J/psi to mu+ mu- and K^0_S to pi+ pi-, and the ratio of these lifetimes. The analysis is based on approximately 250 pb^{-1} of data recorded with the D0 detector in pp(bar) collisions at sqrt{s}=1.96 TeV. The Lambda^0_b lifetime is determined to be tau(Lambda^0_b) = 1.22 +0.22/-0.18 (stat) +/- 0.04 (syst) ps, the B^0 lifetime tau(B^0) = 1.40 +0.11/-0.10 (stat) +/- 0.03 (syst) ps, and the ratio tau(Lambda^0_b)/tau(B^0) = 0.87 +0.17/-0.14 (stat) +/- 0.03 (syst). In contrast with previous measurements using semileptonic decays, this is the first determination of the Lambda^0_b lifetime based on a fully reconstructed decay channel.Comment: 7 pages, 4 figures, Submitted to Physical Review Letters, v2: Added FNAL Pub-numbe

Erratum to Measurement of σ(ppˉ→Z)⋅Br(Z→ττ)\sigma (p \bar p \to Z) \cdot Br(Z \to \tau\tau) at s=\bm{\sqrt{s}=}1.96 TeV, published in Phys. Rev. D {71}, 072004 (2005)

A change in estimated integrated luminosity (from 226 pb$^{-1} to 257 pb$^{-1}$leads to a corrected value for${\sigma (p \bar p \to Z) \cdot}$Br${(Z \to \tau \tau)}$of$209\pm13(stat.)\pm16(syst.)\pm13(lum) pb

TRY plant trait database – enhanced coverage and open access

Plant traits—the morphological, anatomical, physiological, biochemical and phenological characteristics of plants—determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait‐based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits—almost complete coverage for ‘plant growth form’. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait–environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

Large-scale discovery of novel genetic causes of developmental disorders

Despite three decades of successful, predominantly phenotype-driven discovery of the genetic causes of monogenic disorders1, up to half of children with severe developmental disorders of probable genetic origin remain without a genetic diagnosis. Particularly challenging are those disorders rare enough to have eluded recognition as a discrete clinical entity, those with highly variable clinical manifestations, and those that are difficult to distinguish from other, very similar, disorders. Here we demonstrate the power of using an unbiased genotype-driven approach2 to identify subsets of patients with similar disorders. By studying 1,133 children with severe, undiagnosed developmental disorders, and their parents, using a combination of exome sequencing3,4,5,6,7,8,9,10,11 and array-based detection of chromosomal rearrangements, we discovered 12 novel genes associated with developmental disorders. These newly implicated genes increase by 10% (from 28% to 31%) the proportion of children that could be diagnosed. Clustering of missense mutations in six of these newly implicated genes suggests that normal development is being perturbed by an activating or dominant-negative mechanism. Our findings demonstrate the value of adopting a comprehensive strategy, both genome-wide and nationwide, to elucidate the underlying causes of rare genetic disorders