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Der vorliegende Beitrag beschäftigt sich mit den Lehrenden in der betrieblichen Weiterbildung und deren pädagogischem Professionalisierungsbedarf. Beschrieben wird ein von der Feuerwehr- und Rettungsdienstakademie der Branddirektion Frankfurt am Main (FRA) und dem Fachbereich Erziehungswissenschaften der Goethe-Universität entwickeltes Konzept zur Aus- und Weiterbildung pädagogisch tätiger FeuerwehrbeamtInnen, das 2012 erstmals umgesetzt wird. Bislang existierten hierfür weder in Deutschland noch in Österreich einheitliche Vorgaben. Ausgehend von den Bedürfnissen der Feuerwehren und geleitet von theoretischen Positionen der Erwachsenenbildung wird mit dem Konzept nicht zuletzt auch eine lernende Organisation zu verwirklichen versucht. Der Beitrag erläutert Ausgangslage, pädagogische Grundhaltung, Ziele und Ergebnisse der Voruntersuchung und skizziert die konkreten Modulinhalte und den Seminarablauf. Fazit der Autoren: Analog zu der bereits begonnenen Entwicklung in Wirtschaftsunternehmen wird das Niveau der pädagogischen Kenntnisse von lehrendem Personal auch bei den Feuerwehren steigen müssen. (DIPF/Orig.)
Die Fundmeldungen in Band 33 von Botanik und Naturschutz in Hessen stammen von: Dirk Bönsel, Martin de Jong, Wolfgang Ehmke, Peter Emrich, Benjamin Feller, Brunhilde Göbel, Thomas Gregor, Arthur Händler, Sylvain Hodvina, Gerwin Kasperek, Egbert Korte, Ute Lange, Stefan Meyer, Hasko Friedrich Nesemann, Uwe Raabe, Bernd Sauerwein, Marco Schmidt, Christof Nikolaus Schröder, Antje Schwab, Rainer Stoodt und Michael Uebeler.
Bei der zusammenfassenden Analyse unterschiedlicher empirischer Qualifikations- und Forschungsprojekte mit ganz unterschiedlichen Fragestellungen und Erkenntnisinteressen (vgl. Nittel, Schütz, Tippelt 2014; Burkart, Meyer, Stemmer 2016; Meyer 2017; Nittel, Tippelt 2018) zeigt sich sehr deutlich immer wieder ein und dasselbe Phänomen: In den beruflichen Selbstbeschreibungen von pädagogisch Tätigen aus der Elementar- wie der Primarbildung, der Sekundarstufe I und II, der Sozialpädagogik, der Erwachsenenbildung und den Hochschulen nehmen die Begriffe Begleiten und Begleitung eine zentrale Stellung ein. ...
Phylogenetic relationships of the primarily wingless insects are still considered unresolved. Even the most comprehensive phylogenomic studies that addressed this question did not yield congruent results. In order to get a grip on these problems, we here analyzed the sources of incongruence in these phylogenomic studies using an extended transcriptome dataset.Our analyses showed that unevenly distributed missing data can be severely misleading by inflating node support despite the absence of phylogenetic signal. In consequence, only decisive datasets should be used which exclusively comprise data blocks containing all taxa whose relationships are addressed. Additionally, we employed Four-cluster Likelihood-Mapping (FcLM) to measure the degree of congruence among genes of a dataset, as a measure of support alternative to bootstrap. FcLM showed incongruent signal among genes, which in our case is correlated with neither functional class assignment of these genes, nor with model misspecification due to unpartitioned analyses. The herein analyzed dataset is the currently largest dataset covering primarily wingless insects, but failed to elucidate their interordinal phylogenetic relationships. While this is unsatisfying from a phylogenetic perspective, we try to show that the analyses of structure and signal within phylogenomic data can protect us from biased phylogenetic inferences due to analytical artefacts.
Magnetoencephalography (MEG) and Electroencephalography (EEG) provide direct electrophysiological measures at an excellent temporal resolution, but the spatial resolution of source-reconstructed current activity is limited to several millimetres. Here we show, using simulations of MEG signals and Bayesian model comparison, that non-invasive myelin estimates from high-resolution quantitative magnetic resonance imaging (MRI) can enhance MEG/EEG source reconstruction. Our approach assumes that MEG/EEG signals primarily arise from the synchronised activity of pyramidal cells, and since most of the myelin in the cortical sheet originates from these cells, myelin density can predict the strength of cortical sources measured by MEG/EEG. Leveraging recent advances in quantitative MRI, we exploit this structure-function relationship and scale the leadfields of the forward model according to the local myelin density estimates from in vivo quantitative MRI to inform MEG/EEG source reconstruction. Using Bayesian model comparison and dipole localisation errors (DLEs), we demonstrate that adapting local forward fields to reflect increased local myelination at the site of a simulated source explains the simulated data better than models without such leadfield scaling. Our model comparison framework proves sensitive to myelin changes in simulations with exact coregistration and moderate-to-high sensor-level signal-to-noise ratios (≥10 dB) for the multiple sparse priors (MSP) and empirical Bayesian beamformer (EBB) approaches. Furthermore, we sought to infer the microstructure giving rise to specific functional activation patterns by comparing the myelin-informed model which was used to generate the activation with a set of test forward models incorporating different myelination patterns. We found that the direction of myelin changes, however not their magnitude, can be inferred by Bayesian model comparison. Finally, we apply myelin-informed forward models to MEG data from a visuo-motor experiment. We demonstrate improved source reconstruction accuracy using myelin estimates from a quantitative longitudinal relaxation (R1) map and discuss the limitations of our approach.
Highlights
We use quantitative MRI to implement myelin-informed forward models for M/EEG
Local myelin density was modelled by adapting the local leadfields
Myelin-informed forward models can improve source reconstruction accuracy
We can infer the directionality of myelination patterns, but not their strength
We apply our approach to MEG data from a visuo-motor experiment
The genetic make-up of an individual contributes to the susceptibility and response to viral infection. Although environmental, clinical and social factors have a role in the chance of exposure to SARS-CoV-2 and the severity of COVID-191,2, host genetics may also be important. Identifying host-specific genetic factors may reveal biological mechanisms of therapeutic relevance and clarify causal relationships of modifiable environmental risk factors for SARS-CoV-2 infection and outcomes. We formed a global network of researchers to investigate the role of human genetics in SARS-CoV-2 infection and COVID-19 severity. Here we describe the results of three genome-wide association meta-analyses that consist of up to 49,562 patients with COVID-19 from 46 studies across 19 countries. We report 13 genome-wide significant loci that are associated with SARS-CoV-2 infection or severe manifestations of COVID-19. Several of these loci correspond to previously documented associations to lung or autoimmune and inflammatory diseases3,4,5,6,7. They also represent potentially actionable mechanisms in response to infection. Mendelian randomization analyses support a causal role for smoking and body-mass index for severe COVID-19 although not for type II diabetes. The identification of novel host genetic factors associated with COVID-19 was made possible by the community of human genetics researchers coming together to prioritize the sharing of data, results, resources and analytical frameworks. This working model of international collaboration underscores what is possible for future genetic discoveries in emerging pandemics, or indeed for any complex human disease.