@article{LatourHusserGiesersetal.2019, author = {Latour, Marlyn and Husser, Tim Oliver and Giesers, Benjamin David and Kamann, S. and G{\"o}ttgens, Fabian and Dreizler, Stefan and Brinchmann, Jan and Bastian, Nate and Wendt, Martin and Weilbacher, Peter Michael and Molinski, N. S.}, title = {A stellar census in globular clusters with MUSE: multiple populations chemistry in NGC 2808 star star star}, series = {Astronomy and astrophysics : an international weekly journal}, volume = {631}, journal = {Astronomy and astrophysics : an international weekly journal}, publisher = {EDP Sciences}, address = {Les Ulis}, issn = {1432-0746}, doi = {10.1051/0004-6361/201936242}, pages = {14}, year = {2019}, abstract = {Context. Galactic globular clusters (GCs) are now known to host multiple populations displaying particular abundance variations. The different populations within a GC can be well distinguished following their position in the pseudo two-colors diagrams, also referred to as "chromosome maps". These maps are constructed using optical and near-UV photometry available from the Hubble Space Telescope (HST) UV survey of GCs. However, the chemical tagging of the various populations in the chromosome maps is hampered by the fact that HST photometry and elemental abundances are both only available for a limited number of stars. Aims. The spectra collected as part of the MUSE survey of globular clusters provide a spectroscopic counterpart to the HST photometric catalogs covering the central regions of GCs. In this paper, we use the MUSE spectra of 1115 red giant branch (RGB) stars in NGC 2808 to characterize the abundance variations seen in the multiple populations of this cluster. Methods. We used the chromosome map of NGC 2808 to divide the RGB stars into their respective populations. We then combined the spectra of all stars belonging to a given population, resulting in one high signal-to-noise ratio spectrum representative of each population. Results. Variations in the spectral lines of O, Na, Mg, and Al are clearly detected among four of the populations. In order to quantify these variations, we measured equivalent width differences and created synthetic populations spectra that were used to determine abundance variations with respect to the primordial population of the cluster. Our results are in good agreement with the values expected from previous studies based on high-resolution spectroscopy. We do not see any significant variations in the spectral lines of Ca, K, and Ba. We also do not detect abundance variations among the stars belonging to the primordial population of NGC 2808. Conclusions. We demonstrate that in spite of their low resolution, the MUSE spectra can be used to investigate abundance variations in the context of multiple populations.}, language = {en} } @book{PohlenzSchubarthSpecketal.2011, author = {Pohlenz, Philipp and Schubarth, Wilfried and Speck, Karsten and Seidel, Andreas and Winter, Martin and Heine, Christoph and Kleinfeld, Merle and Sarrar, Lea and Gemsa, Charlotte and Wendland, Mirko and Schlumm, Katharina and Lehmann, Uta and Kummerow, Udo and Bastian, Laura and Kamm, Caroline and Niproschke, Saskia and Sochadse, Lascha and Kotzur, Katharina and Hebert, Sebastian and Voigt, Frank and Kopp, Andrea}, title = {Nach Bologna: Praktika im Studium - Pflicht oder K{\"u}r?}, editor = {Schubarth, Wilfried and Speck, Karsten and Seidel, Andreas}, publisher = {Universit{\"a}tsverlag Potsdam}, address = {Potsdam}, isbn = {978-3-86956-123-3}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus-51033}, publisher = {Universit{\"a}t Potsdam}, pages = {iii, 339}, year = {2011}, abstract = {Mit dem vorliegenden Band „Nach Bologna: Praktika im Studium - Pflicht oder K{\"u}r? Empirische Analysen und Empfehlungen f{\"u}r die Hochschulpraxis" von Wilfried Schubarth, Karsten Speck und Andreas Seidel wird die Reihe „Potsdamer Beitr{\"a}ge zur Lehrevaluation" unter neuem Titel und ver{\"a}nderter inhaltlicher Schwerpunktsetzung fortgef{\"u}hrt. Die Umbenennung in „Potsdamer Beitr{\"a}ge zur Hochschulforschung" versteht sich als ein Schritt hin zu einer thematischen {\"O}ffnung der Reihe f{\"u}r die verschiedensten Felder der Hochschulforschung. Der vorliegende Band widmet sich einem der zentralen Reformziele von Bologna: der Frage des Praxis- und Berufsbezugs und dabei insbesondere den Praxisphasen im Studium. Mit der Bologna-Reform werden im bildungspolitischen Bereich sehr vielf{\"a}ltige strukturelle und inhaltliche Ziele verfolgt. Das Ziel dieses Bandes besteht deshalb darin, empirische Forschungen zu Praxisbez{\"u}gen und Praxisphasen im Studium vorzustellen, diese in den Kontext aktueller Debatten um Studienqualit{\"a}t und Studienreform zu stellen sowie Folgerungen f{\"u}r die Gestaltung von Praxisphasen abzuleiten. Inhaltliche Schwerpunkte bilden das BMBF-Forschungsprojekt ProPrax und die Praxisphasen im Lehramtsstudium. Die Beitr{\"a}ge dieses Bandes gehen aus einem gleichnamigen Workshop hervor, der am 1. Oktober 2010 in Potsdam stattfand.}, language = {de} } @article{WienholdMacriNouaillesetal.2018, author = {Wienhold, Sandra-Maria and Macri, Mario and Nouailles, Geraldine and Dietert, Kristina and Gurtner, Corinne and Gruber, Achim D. and Heimesaat, Markus M. and Lienau, Jasmin and Schumacher, Fabian and Kleuser, Burkhard and Opitz, Bastian and Suttorp, Norbert and Witzenrath, Martin and M{\"u}ller-Redetzky, Holger C.}, title = {Ventilator-induced lung injury is aggravated by antibiotic mediated microbiota depletion in mice}, series = {Critical Care}, volume = {22}, journal = {Critical Care}, number = {282}, publisher = {BMC}, address = {London}, issn = {1466-609X}, doi = {10.1186/s13054-018-2213-8}, pages = {12}, year = {2018}, abstract = {BackgroundAntibiotic exposure alters the microbiota, which can impact the inflammatory immune responses. Critically ill patients frequently receive antibiotic treatment and are often subjected to mechanical ventilation, which may induce local and systemic inflammatory responses and development of ventilator-induced lung injury (VILI). The aim of this study was to investigate whether disruption of the microbiota by antibiotic therapy prior to mechanical ventilation affects pulmonary inflammatory responses and thereby the development of VILI.MethodsMice underwent 6-8weeks of enteral antibiotic combination treatment until absence of cultivable bacteria in fecal samples was confirmed. Control mice were housed equally throughout this period. VILI was induced 3 days after completing the antibiotic treatment protocol, by high tidal volume (HTV) ventilation (34ml/kg; positive end-expiratory pressure=2 cmH(2)O) for 4h. Differences in lung function, oxygenation index, pulmonary vascular leakage, macroscopic assessment of lung injury, and leukocyte and lymphocyte differentiation were assessed. Control groups of mice ventilated with low tidal volume and non-ventilated mice were analyzed accordingly.ResultsAntibiotic-induced microbiota depletion prior to HTV ventilation led to aggravation of VILI, as shown by increased pulmonary permeability, increased oxygenation index, decreased pulmonary compliance, enhanced macroscopic lung injury, and increased cytokine/chemokine levels in lung homogenates.ConclusionsDepletion of the microbiota by broad-spectrum antibiotics prior to HTV ventilation renders mice more susceptible to developing VILI, which could be clinically relevant for critically ill patients frequently receiving broad-spectrum antibiotics.}, language = {en} } @phdthesis{Bastian2023, author = {Bastian, Martin}, title = {An emergent machine learning approach for seasonal cyclone activity forecasts}, school = {Universit{\"a}t Potsdam}, pages = {135}, year = {2023}, abstract = {Seasonal forecasts are of great interest in many areas. Knowing the amount of precipitation for the upcoming season in regions of water scarcity would facilitate a better water management. If farmers knew the weather conditions of the upcoming summer at sowing time, they could select those cereal species that are best adapted to these conditions. This would allow farmers to improve the harvest and potentially even reduce the amount of pesticides used. However, the undoubted advantages of seasonal forecasts are often opposed by their high degree of uncertainty. The great challenge of generating seasonal forecasts with lead times of several months mainly originates from the chaotic nature of the earth system. In a chaotic system, even tiny differences in the initial conditions can lead to strong deviations in the system's state in the long run. In this dissertation we propose an emergent machine learning approach for seasonal forecasting, called the AnlgModel. The AnlgModel combines the analogue method with myopic feature selection and bootstrapping. To benchmark the abilities of the AnlgModel we apply it to seasonal cyclone activity forecasts in the North Atlantic and Northwest Pacific. The AnlgModel demonstrates competitive hindcast skills with two operational forecasts and even outperforms these for long lead times. In the second chapter we comprehend the forecasting strategy of the Anlg-Model. We thereby analyse the analogue selection process for the 2017 North Atlantic and the 2018 Northwest Pacific seasonal cyclone activity. The analysis shows that those climate indices which are known to influence the seasonal cyclone activity, such as the Ni{\~n}o 3.4 SST, are correctly represented among the selected analogues. Furthermore the selected analogues reflect large-scale climate patterns that were identified by expert reports as being determinative for these particular seasons. In the third chapter we analyse the features that are used by the AnlgModel for its predictions. We therefore inspect the feature relevance (FR). The FR patterns learned by the AnlgModel show a high congruence with the predictor regions used by the operational forecasts. However, the AnlgModel also discovered new features, such as the SST anomaly in the Gulf of Guinea during November. This SST pattern exhibits a remarkably high predictive potential for the upcoming Atlantic hurricane activity. In the final chapter we investigate potential mechanisms, that link two of these regions with high feature relevance to the Atlantic hurricane activity. We mainly focus on ocean surface transport. The ocean surface flow paths are calculated using Lagrangian particle analysis. We demonstrate that the FR patterns in the region of the Canary islands do not correspond with ocean surface transport. It is instead likely that these FR patterns fingerprint a wind transport of latent heat. The second region to be studied is situated in the Gulf of Guinea. Our analysis shows that the FR patterns seen there do fingerprint ocean surface transport. However, our simulations also show that at least one other mechanism is involved in linking the Gulf of Guinea SST anomaly in November to the hurricane activity of the upcoming season. In this work the AnlgModel does not only demonstrate its outstanding forecast skills but also shows its capabilities as research tool for detecting oceanic and atmospheric mechanisms.}, language = {en} }