Vibrational spectroscopic investigations of lead borate and lead aluminoborate glasses

Lead borate (PB) and lead aluminoborate (PBA) glasses in the Systems xPbO · ( 1 0 0 - x)Β₂O₃ (0 ≤ x ≤ 75 mol%) and xPbO · (95 - x)Β₂O₃, 5AI₂O₃ (0 ≤ x ≤ 80 mol%), respectively, have been prepared and investigated by Raman and infrared reflectance spectroscopy to obtain quahtative and quantitative information on the structure of glasses. Using the Martin-Brenig model, structural correlation lengths were determinated from boson peak positions of temperature-reduced Raman spectra and transversal sound velocities. Kramers-Kronig analysis was used to transform the measured infrared reflectance spectra into complex dielectric funcdons. The imaginary part of the complex dielectric funcdon contains the absorption properties of t he material. Α band separadon Computer programme has been used to get more detailed information from the spectra. Far infrared and low-frequency Raman spectra contain information about vibrations of the PbO component within the network

Upgrade of the ultracold neutron source at the pulsed reactor TRIGA Mainz

The performance of the upgraded solid deuterium ultracold neutron source at the pulsed reactor TRIGA Mainz is described. The current configuration stage comprises the installation of a He liquefier to run UCN experiments over long-term periods, the use of stainless steel neutron guides with improved transmission as well as sputter-coated non-magnetic $^{58}$NiMo alloy at the inside walls of the thermal bridge and the converter cup. The UCN yield was measured in a `standard' UCN storage bottle (stainless steel) with a volume of 32 litres outside the biological shield at the experimental area yielding UCN densities of 8.5 /cm$^3$; an increase by a factor of 3.5 compared to the former setup. The measured UCN storage curve is in good agreement with the predictions from a Monte Carlo simulation developed to model the source. The growth and formation of the solid deuterium converter during freeze-out are affected by the ortho/para ratio of the H$_2$ premoderator.Comment: 12 pages, 7 figure

Tumor necrosis factor polymorphisms in psoriatic arthritis : association with the promoter polymorphism TNF-857 independent of the PSORS1 risk allele

Poster presentation Background Single nucleotide polymorphisms (SNPs) of the TNF gene at positions -238 and -308 have earlier been associated with psoriasis vulgaris and psoriatic arthritis (PsA). However, a strong linkage disequilibrium at the chromosomal region 6p21 renders the interpretation of these findings difficult since also other risk factors for psoriasis (PSORS1) than SNPs of the TNF gene have bee mapped to that particular region. Therefore, in this study several SNPs of the TNF gene and of its neighbouring lymphotoxin alpha (LTA) gene were analysed independently and dependently on carrying the PSORS1 risk allele. Methods SNPs in the promoter of the TNF gene (-238G/A, -308G/A, -857C/T, -1031T/C), and one SNP of the LTA gene (+252A/G), of the TNLFRSF1A gene (+36A/G) and of the TNLFRSF1B gene (+676T/G), respectively, were genotyped in 375 psoriasis patients, 375 PsA patients, and 376 controls. The tryptophan–tryptophan–cysteine–cysteine haplotype of the CCHCR1 gene (CCHCR1*WWCC) was used to estimate the genetic impact of the PSORS1 risk allele. Results Whereas an earlier-described association of allele TNF*-238A with psoriasis could be confirmed, our study revealed that this association was completely dependent on concomitant carriage of the PSORS1 risk allele. For PsA, but not psoriasis vulgaris without joint manifestations, strong association with the allele TNF*-857T was detected (OR = 1.956; P value corrected for multiple testing, Pcorr = 0.0025) also in patients negative for the PSORS1 risk allele. Conclusion Our results indicate genetic differences between psoriasis vulgaris patients with and without joint manifestation. While the previously reported association between TNF*-238A and psoriasis seems to primarily reflect linkage disequilibrium with PSORS1, TNF*-857T may represent a risk factor for PsA independent of PSORS1. A potential pathophysiologic relevance of the elucidated genetic association is further suggested by previously reported experimental evidence for a functional impact of the respective TNF polymorphism on TNFalpha expression levels

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