The Leptonic Higgs as a Messenger of Dark Matter

We propose that the leptonic cosmic ray signals seen by PAMELA and ATIC result from the annihilation or decay of dark matter particles via states of a leptonic Higgs doublet to $\tau$ leptons, linking cosmic ray signals of dark matter to LHC signals of the Higgs sector. The states of the leptonic Higgs doublet are lighter than about 200 GeV, yielding large $\bar{\tau} \tau$ and $\bar{\tau} \tau \bar{\tau} \tau$ event rates at the LHC. Simple models are given for the dark matter particle and its interactions with the leptonic Higgs, for cosmic ray signals arising from both annihilations and decays in the galactic halo. For the case of annihilations, cosmic photon and neutrino signals are on the verge of discovery.Comment: 34 pages, 9 figures, minor typos corrected, references adde

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

Content and performance of the MiniMUGA genotyping array: A new tool to improve rigor and reproducibility in mouse research

The laboratory mouse is the most widely used animal model for biomedical research, due in part to its well-annotated genome, wealth of genetic resources, and the ability to precisely manipulate its genome. Despite the importance of genetics for mouse research, genetic quality control (QC) is not standardized, in part due to the lack of cost-effective, informative, and robust platforms. Genotyping arrays are standard tools for mouse research and remain an attractive alternative even in the era of high-throughput whole-genome sequencing. Here, we describe the content and performance of a new iteration of the Mouse Universal Genotyping Array (MUGA), MiniMUGA, an array-based genetic QC platform with over 11,000 probes. In addition to robust discrimination between most classical and wild-derived laboratory strains, MiniMUGA was designed to contain features not available in other platforms: (1) chromosomal sex determination, (2) discrimination between substrains from multiple commercial vendors, (3) diagnostic SNPs for popular laboratory strains, (4) detection of constructs used in genetically engineered mice, and (5) an easy-to-interpret report summarizing these results. In-depth annotation of all probes should facilitate custom analyses by individual researchers. To determine the performance of MiniMUGA, we genotyped 6899 samples from a wide variety of genetic backgrounds. The performance of MiniMUGA compares favorably with three previous iterations of the MUGA family of arrays, both in discrimination capabilities and robustness. We have generated publicly available consensus genotypes for 241 inbred strains including classical, wild-derived, and recombinant inbred lines. Here, we also report the detection of a substantial number of XO and XXY individuals across a variety of sample types, new markers that expand the utility of reduced complexity crosses to genetic backgrounds other than C57BL/6, and the robust detection of 17 genetic constructs. We provide preliminary evidence that the array can be used to identify both partial sex chromosome duplication and mosaicism, and that diagnostic SNPs can be used to determine how long inbred mice have been bred independently from the relevant main stock. We conclude that MiniMUGA is a valuable platform for genetic QC, and an important new tool to increase the rigor and reproducibility of mouse research

Low energy electron scattering from molecules on surfaces

SIGLEAvailable from British Library Document Supply Centre- DSC:D062423 / BLDSC - British Library Document Supply CentreGBUnited Kingdo

Erratum: Error correction for diffraction and multiple scattering in free-space microwave measurement of materials (IEEE Transactions on Microwave Theory and Techniques (2006) 54:2 (648-659))

10.1109/TMTT.2006.871948IEEE Transactions on Microwave Theory and Techniques5441631-IETM

Error correction for diffraction and multiple scattering in free-space microwave measurement of materials

10.1109/TMTT.2005.862666IEEE Transactions on Microwave Theory and Techniques542648-659IETM

Impedance matching for the multilayer medium - Toward a design methodology

10.1109/TMTT.2003.808664IEEE Transactions on Microwave Theory and Techniques513908-914IETM

Transient jitter from injection in storage rings

10.1103/PhysRevSTAB.12.091001Physical Review Special Topics - Accelerators and Beams1299100