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With the ongoing loss of global biodiversity, long-term recordings of species distribution patterns are increasingly becoming important to investigate the causes and consequences for their change. Therefore, the digitization of scientific literature, both modern and historical, has been attracting growing attention in recent years. To meet this growing demand the Specialised Information Service for Biodiversity Research (BIOfid) was launched in 2017 with the aim of increasing the availability and accessibility of biodiversity information. Closely tied to the research community the interdisciplinary BIOfid team is digitizing data sources of biodiversity related research and provides a modern and professional infrastructure for hosting and sharing them. As a pilot project, German publications on the distribution and ecology of vascular plants, birds, moths and butterflies covering the past 250 years are prioritized. Large parts of the text corpus defined in accordance with the needs of the relevant German research community have already been transferred to a machine-readable format and will be publicly accessible soon. Software tools for text mining, semantic annotation and analysis with respect to the current trends in machine learning are developed to maximize bioscientific data output through user-specific queries that can be created via the BIOfid web portal (https://www.biofid.de/). To boost knowledge discovery, specific ontologies focusing on morphological traits and taxonomy are being prepared and will continuously be extended to keep up with an ever-expanding volume of literature sources.
We have measured the radiative neutron-capture cross section and the total neutron-induced cross section of one of the most important isotopes for the s process, the 25Mg. The measurements have been carried out at the neutron time-of-flight facilities n_TOF at CERN (Switzerland) and GELINA installed at the EC-JRC-IRMM (Belgium). The cross sections as a function of neutron energy have been measured up to approximately 300 keV, covering the energy region of interest to the s process. The data analysis is ongoing and preliminary results show the potential relevance for the s process.
Biodiversity research heavily relies on recent and older literature, and the data contained therein. Despite great effort, large parts of the literature and the data it holds are still not available in appropriate formats needed for efficient compilation and analysis. As a part of the current funding strategy of the German Research Council (Deutsche Forschungsgemeinschaft, DFG), and resulting from an extensive dialogue with the scientific community in Germany, a "Specialised Information Service" (Fachinformationsdienst, FID) for Biodiversity Research will be established with the objective of making further segments of literature about biodiversity available in up-to-date formats. This project, starting 2017, is conducted by the University Library Johann Christian Senckenberg (Frankfurt/Main, Germany) together with the Senckenberg Gesellschaft für Naturforschung and the Text Technology Lab of the Goethe University (Frankfurt/Main).
The new Specialised Information Service for Biodiversity Research (FID Biodiversitätsforschung) comprises four core elements: (A) A text mining approach which encompasses advanced text technologies and a large body of 20th century literature; (B) the digitisation of selected German biodiversity literature; (C) a platform für Open Access journals; and (D) Acquisition of specialised print literature.
Phase transitions in a non-perturbative regime can be studied by ab initio Lattice Field Theory methods. The status and future research directions for LFT investigations of Quantum Chromo-Dynamics under extreme conditions are reviewed, including properties of hadrons and of the hypothesized QCD axion as inferred from QCD topology in different phases. We discuss phase transitions in strong interactions in an extended parameter space, and the possibility of model building for Dark Matter and Electro-Weak Symmetry Breaking. Methodological challenges are addressed as well, including new developments in Artificial Intelligence geared towards the identification of different phases and transitions.