TY - GEN A1 - Gerrits, Ruben T1 - Data of "An experimental study of fungal olivine weathering" N2 - This file contains all the data used for the figures shown in the Dissertation of Ruben Gerrits with the title "An experimental study of fungal olivine weathering". In this study, the weathering-affecting, rock-inhabiting fungus, Knufia petricola A95 and the Fe-bearing olivine (Fe0.2Mg1.8SiO4) were selected to investigate fungi-induced effects on mineral dissolution. The availability of a melanin-deficient mutant (ΔKppks) of K. petricola A95, that produced more extracellular polymeric substances (EPS) than the wild type (WT), enabled comparative studies of the role of melanin and EPS in weathering processes. KW - Olivine KW - Weathering KW - Fungus PY - 2019 U6 - https://doi.org/10.26272/opus4-48770 PB - Bundesanstalt für Materialforschung und -prüfung (BAM) CY - Berlin AN - OPUS4-48770 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - GEN A1 - Kowarik, Stefan A1 - Pithan, L. T1 - kowarik-labs/AI-reflectivity: v0.1 N2 - AI-reflectivity is a code based on artificial neural networks trained with simulated reflectivity data that quickly predicts film parameters from experimental X-ray reflectivity curves. This project has a common root with (ML-reflectivity)[https://github.com/schreiber-lab/ML-reflectivity] and evolved in parallel. Both are linked to the following publication: Fast Fitting of Reflectivity Data of Growing Thin Films Using Neural Networks A. Greco, V. Starostin, C. Karapanagiotis, A. Hinderhofer, A. Gerlach, L. Pithan, S. Liehr, F. Schreiber, S. Kowarik (2019). J. Appl. Cryst. For an online live demonstration using a pre-trained network have a look at github. KW - Artificial neural networks KW - X-ray reflectivity PY - 2019 U6 - https://doi.org/10.5281/zenodo.3477583 PB - Zenodo CY - Geneva AN - OPUS4-51888 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - GEN A1 - Lisec, Jan T1 - CorrectOverloadedPeaks (R package to correct APCI-HR-MS peak data) N2 - Metabolomics, the analysis of potentially all small molecules within a biological system, has become a valuable tool for biomarker identification and the elucidation of biological processes. While metabolites are often present in complex mixtures at extremely different concentrations, the dynamic range of available analytical methods to capture this variance is generally limited. Here, we show that gas chromatography coupled to atmospheric pressure chemical ionization mass spectrometry (GC-APCI-MS), a state of the art analytical technology applied in metabolomics analyses, shows an average linear range (LR) of 2.39 orders of magnitude for a set of 62 metabolites from a representative compound mixture. We further developed a computational tool to extend this dynamic range on average by more than 1 order of magnitude, demonstrated with a dilution series of the compound mixture, using robust and automatic reconstruction of intensity values exceeding the detection limit. The tool is freely available as an R package (CorrectOverloadedPeaks) from CRAN (https://cran.r-project.org/) and can be incorporated in a metabolomics data processing pipeline facilitating large screening assays. KW - Software KW - Metabolomics KW - R package KW - Data processing PY - 2019 UR - https://github.com/cran/CorrectOverloadedPeaks/ PB - GitHub CY - San Francisco, CA, USA AN - OPUS4-57853 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - GEN A1 - Winkelmann, A. A1 - Britton, T. B. A1 - Nolze, Gert T1 - EBSD Kikuchi Pattern Analysis, Silicon 15kV N2 - Supplementary data and images for Si EBSD pattern analysis as presented in: A. Winkelmann, T.B. Britton, G. Nolze "Constraints on the effective electron energy spectrum in backscatter Kikuchi diffraction", Physical Review B (2019). KW - EBSD KW - Electron energy KW - Energy distribution KW - Kikuchi pattern KW - Simulation PY - 2019 U6 - https://doi.org/10.5281/zenodo.2565061 PB - Zenodo CY - Geneva AN - OPUS4-51907 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER -