@phdthesis{Swart2017,
  author    = {Swart, Corn{\´e}},
  title     = {Managing protein activity in A. thaliana},
  school      = {Universit{\"a}t Potsdam},
  pages     = {160},
  year      = {2017},
  language  = {en}
}
@phdthesis{Yishai2019,
  author    = {Yishai, Oren},
  title     = {Engineering the reductive glycine pathway in Escherichia coli},
  school      = {Universit{\"a}t Potsdam},
  pages     = {86},
  year      = {2019},
  language  = {en}
}
@phdthesis{RuizRodriguez2019,
  author    = {Ruiz Rodriguez, Janete Lorena},
  title     = {Osmotic pressure effects on collagen mimetic peptides},
  school      = {Universit{\"a}t Potsdam},
  pages     = {139},
  year      = {2019},
  abstract  = {Collagen is the most abundant protein in mammals. In many tissues, collagen molecules assemble to form a hierarchical structure. In the smallest supramolecular unit, named fibril, each molecule is displaced in the axial direction with respect to its neighbors. This staggering creates a periodic gap and overlap regions, where the gap regions exhibit 20\% less density. These fibril-forming collagens play an essential role in the strength of connective tissues. Despite much effort, directed at understanding collagen function and regulation, the influence of the chemical environment on the local structural and mechanical properties remains poorly understood. Recent studies, aimed at elucidating the effect of osmotic pressure, showed that collagen contracts upon water removal. This observation highlights the importance of water for the stabilization and mechanics of the collagen molecule. Using collagen mimetic peptides (CMPs), which fold into triple helical structures reminiscent of natural collagen, the primary goal of this work was to investigate the effect of the osmotic pressure on specific collagen-mimetic sequences. CMPs were used as the model system as they provide sequence control, which is essential for discriminating local from global structural changes and for relating the observed effects to existing knowledge about the full-length collagen molecule. Of specific interest was the structure of individual collagen triple helices as well as their organization into self-assembled higher order structures. These key structural features were monitored with infrared spectroscopy (IR) and synchrotron X-ray scattering, while varying the osmotic pressure. For controlling the osmotic pressure, CMP powder samples were incubated in air of defined relative humidity, ranging from dry conditions to highly "humid". In addition, to obtain more biologically relevant conditions, the CMPs were measured in ultrapure water and in solutions containing small molecule osmolytes. Using the sequences (Pro-Pro-Gly)10, (Pro-Hyp-Gly)10 and (Hyp-Hyp-Gly)10, it was shown that CMPs with different degrees of proline hydroxylation (Hyp = hydroxyproline) exhibit a sequence-specific response to osmotic pressure. IR spectroscopy revealed that osmotic pressure changes affect the strength of the triple helix stabilizing, interchain hydrogen bond and that the extent of this change depends on the degree of hydroxylation. X-ray scattering experiments further showed that changes in osmotic pressure affect both the molecular length as well as the higher order organization of CMPs. Starting from a pseudo-hexagonal packing in the dry state, all three CMPs showed isotropic swelling when increasing the water content to approximately 1.2 water molecules per amino acid, again to different extents depending on the degree of hydroxylation. When increasing the water content further, this pseudo-hexagonal arrangement breaks down. In the fully hydrated state, each CMP is characterized by its own specific and more complex packing geometry. While these changes in the lateral packing arrangement suggest swelling upon hydration, an overall decrease of the molecular length (i.e. contraction) was observed in the axial direction. Also for this structural feature, a strong dependency on the specific amino acid sequence was found. Interestingly, the observed contraction is the opposite of what has been reported for natural collagen. As (Pro-Pro-Gly)n, (Pro-Hyp-Gly)n and (Hyp-Hyp-Gly)n repeat units are found in collagen with a relatively high abundance, this suggests that other collagen sequence fragments need to respond to hydration in the opposite way to obtain a net elongation of the full-length collagen molecule. To test this hypothesis, sequences predicted to be sensitive to osmotic pressure were considered. One such sequence, consisting of two repeat units (Ala-Arg-Gly-Ser-Asp-Gly), was inserted as a guest into a (Pro-Pro-Gly) host. When compared to the canonical CMP sequences investigated earlier, the lateral helix packing follows a similar trend with increasing hydration; however, the host-guest CMP axially elongates with increasing water content. This behavior is more similar to what has been found for natural collagen and suggests that different sequences do determine the molecular length of collagen sequences differently. Interestingly, the canonical sequences are more abundant in the overlap region while the guest sequence is found in the gap region. This allows to speculate that sequences in the gap and overlap regions possess a specifically fine-tuned local response to osmotic pressure changes. Clearly, more experiments with additional sequences are needed to confirm this. In conclusion, the results obtained in this work indicate a highly sequence specific interaction between collagen and water. Osmotic pressure-induced conformational changes mostly originate from local geometries and bonding patterns and affect both the structure of individual triple helices as well as higher order assemblies. One key remaining question is how these conformational changes affect the local mechanical properties of the collagen molecule. As a first step, the stiffness (persistence length) of full-length collagen was determined using atomic force microscopy. In the future, experimental strategies need to be developed that allow for investigating the mechanical properties of specific collagen sequences, e.g. performing single-molecule force spectroscopy of CMPs.},
  language  = {en}
}
@phdthesis{Littmann2024,
  author    = {Littmann, Daniela-Christin},
  title     = {Large eddy simulations of the Arctic boundary layer around the MOSAiC drift track},
  doi       = {10.25932/publishup-62437},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-624374},
  school      = {Universit{\"a}t Potsdam},
  pages     = {xii, 110},
  year      = {2024},
  abstract  = {The icosahedral non-hydrostatic large eddy model (ICON-LEM) was applied around the drift track of the Multidisciplinary Observatory Study of the Arctic (MOSAiC) in 2019 and 2020. The model was set up with horizontal grid-scales between 100m and 800m on areas with radii of 17.5km and 140 km. At its lateral boundaries, the model was driven by analysis data from the German Weather Service (DWD), downscaled by ICON in limited area mode (ICON-LAM) with horizontal grid-scale of 3 km. The aim of this thesis was the investigation of the atmospheric boundary layer near the surface in the central Arctic during polar winter with a high-resolution mesoscale model. The default settings in ICON-LEM prevent the model from representing the exchange processes in the Arctic boundary layer in accordance to the MOSAiC observations. The implemented sea-ice scheme in ICON does not include a snow layer on sea-ice, which causes a too slow response of the sea-ice surface temperature to atmospheric changes. To allow the sea-ice surface to respond faster to changes in the atmosphere, the implemented sea-ice parameterization in ICON was extended with an adapted heat capacity term. The adapted sea-ice parameterization resulted in better agreement with the MOSAiC observations. However, the sea-ice surface temperature in the model is generally lower than observed due to biases in the downwelling long-wave radiation and the lack of complex surface structures, like leads. The large eddy resolving turbulence closure yielded a better representation of the lower boundary layer under strongly stable stratification than the non-eddy-resolving turbulence closure. Furthermore, the integration of leads into the sea-ice surface reduced the overestimation of the sensible heat flux for different weather conditions. The results of this work help to better understand boundary layer processes in the central Arctic during the polar night. High-resolving mesoscale simulations are able to represent temporally and spatially small interactions and help to further develop parameterizations also for the application in regional and global models.},
  language  = {en}
}
@phdthesis{WindirschWoiwode2024,
  author    = {Windirsch-Woiwode, Torben},
  title     = {Permafrost carbon stabilisation by recreating a herbivore-driven ecosystem},
  doi       = {10.25932/publishup-62424},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-624240},
  school      = {Universit{\"a}t Potsdam},
  pages     = {X, 104, A-57},
  year      = {2024},
  abstract  = {With Arctic ground as a huge and temperature-sensitive carbon reservoir, maintaining low ground temperatures and frozen conditions to prevent further carbon emissions that contrib-ute to global climate warming is a key element in humankind's fight to maintain habitable con-ditions on earth. Former studies showed that during the late Pleistocene, Arctic ground condi-tions were generally colder and more stable as the result of an ecosystem dominated by large herbivorous mammals and vast extents of graminoid vegetation - the mammoth steppe. Characterised by high plant productivity (grassland) and low ground insulation due to animal-caused compression and removal of snow, this ecosystem enabled deep permafrost aggrad-ation. Now, with tundra and shrub vegetation common in the terrestrial Arctic, these effects are not in place anymore. However, it appears to be possible to recreate this ecosystem local-ly by artificially increasing animal numbers, and hence keep Arctic ground cold to reduce or-ganic matter decomposition and carbon release into the atmosphere. By measuring thaw depth, total organic carbon and total nitrogen content, stable carbon iso-tope ratio, radiocarbon age, n-alkane and alcohol characteristics and assessing dominant vegetation types along grazing intensity transects in two contrasting Arctic areas, it was found that recreating conditions locally, similar to the mammoth steppe, seems to be possible. For permafrost-affected soil, it was shown that intensive grazing in direct comparison to non-grazed areas reduces active layer depth and leads to higher TOC contents in the active layer soil. For soil only frozen on top in winter, an increase of TOC with grazing intensity could not be found, most likely because of confounding factors such as vertical water and carbon movement, which is not possible with an impermeable layer in permafrost. In both areas, high animal activity led to a vegetation transformation towards species-poor graminoid-dominated landscapes with less shrubs. Lipid biomarker analysis revealed that, even though the available organic material is different between the study areas, in both permafrost-affected and sea-sonally frozen soils the organic material in sites affected by high animal activity was less de-composed than under less intensive grazing pressure. In conclusion, high animal activity af-fects decomposition processes in Arctic soils and the ground thermal regime, visible from reduced active layer depth in permafrost areas. Therefore, grazing management might be utilised to locally stabilise permafrost and reduce Arctic carbon emissions in the future, but is likely not scalable to the entire permafrost region.},
  language  = {en}
}
@phdthesis{Zeppenfeld2021,
  author    = {Zeppenfeld, Stefan},
  title     = {Vom Gast zum Gastwirt?},
  series = {Geschichte der Gegenwart},
  journal   = {Geschichte der Gegenwart},
  number    = {26},
  publisher = {Wallstein-Verlag},
  address   = {G{\"o}ttingen},
  isbn      = {978-3-8353-5022-9},
  pages     = {429},
  year      = {2021},
  abstract  = {Die Arbeitsmigration z{\"a}hlt zu den pr{\"a}genden gesellschaftlichen Wandlungsprozessen der deutschen Nachkriegsgeschichte. 14 Millionen »Gastarbeiter« kamen zwischen 1955 und 1973 in die Bundesrepublik, etwa 3 Millionen von ihnen kehrten nicht in ihre Heimatl{\"a}nder zur{\"u}ck. Vor allem T{\"u}rkeist{\"a}mmige blieben nach dem Anwerbestopp h{\"a}ufiger in Deutschland als die Arbeitskr{\"a}fte aus anderen L{\"a}ndern. Wie keine andere Stadt steht Berlin bis heute f{\"u}r die Einwanderung aus der T{\"u}rkei. Stefan Zeppenfeld untersucht den Wandel der t{\"u}rkischen Arbeitswelten von ihren Anf{\"a}ngen in den 1960er Jahren bis zur Wiedervereinigung. Ausgehend von der »Gastarbeit« im industriellen Großbetrieb sp{\"u}rt er in seiner Studie am Beispiel West-Berlins dem {\"U}bergang in andere Branchen nach. Er zeigt, wie der {\"o}ffentliche Dienst auch f{\"u}r Migrantinnen und Migranten attraktive Aufstiegsm{\"o}glichkeiten er{\"o}ffnete, zeichnet den schwierigen Weg in die gewerbliche Selbstst{\"a}ndigkeit nach und legt illegale Besch{\"a}ftigungsformen als alternative Verdienstm{\"o}glichkeit offen. Damit bettet der Autor die Geschichte der t{\"u}rkischen Arbeitsmigration in die deutsche Zeitgeschichte ein.},
  language  = {de}
}
@phdthesis{Friese2016,
  author    = {Friese, Viviane A.},
  title     = {Solvato-, vapo, mechanochromic and luminescent behavior of Rhodium, Platinum and Gold complexes and their coordination polymers},
  school      = {Universit{\"a}t Potsdam},
  pages     = {100 S.},
  year      = {2016},
  language  = {en}
}
@phdthesis{Brill2022,
  author    = {Brill, Fabio Alexander},
  title     = {Applications of machine learning and open geospatial data in flood risk modelling},
  doi       = {10.25932/publishup-55594},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-555943},
  school      = {Universit{\"a}t Potsdam},
  pages     = {xix, 124},
  year      = {2022},
  abstract  = {Der technologische Fortschritt erlaubt es, zunehmend komplexe Vorhersagemodelle auf Basis immer gr{\"o}ßerer Datens{\"a}tze zu produzieren. F{\"u}r das Risikomanagement von Naturgefahren sind eine Vielzahl von Modellen als Entscheidungsgrundlage notwendig, z.B. in der Auswertung von Beobachtungsdaten, f{\"u}r die Vorhersage von Gefahrenszenarien, oder zur statistischen Absch{\"a}tzung der zu erwartenden Sch{\"a}den. Es stellt sich also die Frage, inwiefern moderne Modellierungsans{\"a}tze wie das maschinelle Lernen oder Data-Mining in diesem Themenbereich sinnvoll eingesetzt werden k{\"o}nnen. Zus{\"a}tzlich ist im Hinblick auf die Datenverf{\"u}gbarkeit und -zug{\"a}nglichkeit ein Trend zur {\"O}ffnung (open data) zu beobachten. Thema dieser Arbeit ist daher, die M{\"o}glichkeiten und Grenzen des maschinellen Lernens und frei verf{\"u}gbarer Geodaten auf dem Gebiet der Hochwasserrisikomodellierung im weiteren Sinne zu untersuchen. Da dieses {\"u}bergeordnete Thema sehr breit ist, werden einzelne relevante Aspekte herausgearbeitet und detailliert betrachtet. Eine prominente Datenquelle im Bereich Hochwasser ist die satellitenbasierte Kartierung von {\"U}berflutungsfl{\"a}chen, die z.B. {\"u}ber den Copernicus Service der Europ{\"a}ischen Union frei zur Verf{\"u}gung gestellt werden. Große Hoffnungen werden in der wissenschaftlichen Literatur in diese Produkte gesetzt, sowohl f{\"u}r die akute Unterst{\"u}tzung der Einsatzkr{\"a}fte im Katastrophenfall, als auch in der Modellierung mittels hydrodynamischer Modelle oder zur Schadensabsch{\"a}tzung. Daher wurde ein Fokus in dieser Arbeit auf die Untersuchung dieser Flutmasken gelegt. Aus der Beobachtung, dass die Qualit{\"a}t dieser Produkte in bewaldeten und urbanen Gebieten unzureichend ist, wurde ein Verfahren zur nachtr{\"a}glichenVerbesserung mittels maschinellem Lernen entwickelt. Das Verfahren basiert auf einem Klassifikationsalgorithmus der nur Trainingsdaten von einer vorherzusagenden Klasse ben{\"o}tigt, im konkreten Fall also Daten von {\"U}berflutungsfl{\"a}chen, nicht jedoch von der negativen Klasse (trockene Gebiete). Die Anwendung f{\"u}r Hurricane Harvey in Houston zeigt großes Potenzial der Methode, abh{\"a}ngig von der Qualit{\"a}t der urspr{\"u}nglichen Flutmaske. Anschließend wird anhand einer prozessbasierten Modellkette untersucht, welchen Einfluss implementierte physikalische Prozessdetails auf das vorhergesagte statistische Risiko haben. Es wird anschaulich gezeigt, was eine Risikostudie basierend auf etablierten Modellen leisten kann. Solche Modellketten sind allerdings bereits f{\"u}r Flusshochwasser sehr komplex, und f{\"u}r zusammengesetzte oder kaskadierende Ereignisse mit Starkregen, Sturzfluten, und weiteren Prozessen, kaum vorhanden. Im vierten Kapitel dieser Arbeit wird daher getestet, ob maschinelles Lernen auf Basis von vollst{\"a}ndigen Schadensdaten einen direkteren Weg zur Schadensmodellierung erm{\"o}glicht, der die explizite Konzeption einer solchen Modellkette umgeht. Dazu wird ein staatlich erhobener Datensatz der gesch{\"a}digten Geb{\"a}ude w{\"a}hrend des schweren El Ni{\~n}o Ereignisses 2017 in Peru verwendet. In diesem Kontext werden auch die M{\"o}glichkeiten des Data-Mining zur Extraktion von Prozessverst{\"a}ndnis ausgelotet. Es kann gezeigt werden, dass diverse frei verf{\"u}gbare Geodaten n{\"u}tzliche Informationen f{\"u}r die Gefahren- und Schadensmodellierung von komplexen Flutereignissen liefern, z.B. satellitenbasierte Regenmessungen, topographische und hydrographische Information, kartierte Siedlungsfl{\"a}chen, sowie Indikatoren aus Spektraldaten. Zudem zeigen sich Erkenntnisse zu den Sch{\"a}digungsprozessen, die im Wesentlichen mit den vorherigen Erwartungen in Einklang stehen. Die maximale Regenintensit{\"a}t wirkt beispielsweise in St{\"a}dten und steilen Schluchten st{\"a}rker sch{\"a}digend, w{\"a}hrend die Niederschlagssumme in tiefliegenden Flussgebieten und bewaldeten Regionen als aussagekr{\"a}ftiger befunden wurde. L{\"a}ndliche Gebiete in Peru weisen in der pr{\"a}sentierten Studie eine h{\"o}here Vulnerabilit{\"a}t als die Stadtgebiete auf. Jedoch werden auch die grunds{\"a}tzlichen Grenzen der Methodik und die Abh{\"a}ngigkeit von spezifischen Datens{\"a}tzen and Algorithmen offenkundig. In der {\"u}bergreifenden Diskussion werden schließlich die verschiedenen Methoden - prozessbasierte Modellierung, pr{\"a}diktives maschinelles Lernen, und Data-Mining - mit Blick auf die Gesamtfragestellungen evaluiert. Im Bereich der Gefahrenbeobachtung scheint eine Fokussierung auf neue Algorithmen sinnvoll. Im Bereich der Gefahrenmodellierung, insbesondere f{\"u}r Flusshochwasser, wird eher die Verbesserung von physikalischen Modellen, oder die Integration von prozessbasierten und statistischen Verfahren angeraten. In der Schadensmodellierung fehlen nach wie vor die großen repr{\"a}sentativen Datens{\"a}tze, die f{\"u}r eine breite Anwendung von maschinellem Lernen Voraussetzung ist. Daher ist die Verbesserung der Datengrundlage im Bereich der Sch{\"a}den derzeit als wichtiger einzustufen als die Auswahl der Algorithmen.},
  language  = {en}
}
@phdthesis{Jongejans2022,
  author    = {Jongejans, Loeka Laura},
  title     = {Organic matter stored in ice-rich permafrost},
  doi       = {10.25932/publishup-56491},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-564911},
  school      = {Universit{\"a}t Potsdam},
  pages     = {xxiii, 178},
  year      = {2022},
  abstract  = {The Arctic is changing rapidly and permafrost is thawing. Especially ice-rich permafrost, such as the late Pleistocene Yedoma, is vulnerable to rapid and deep thaw processes such as surface subsidence after the melting of ground ice. Due to permafrost thaw, the permafrost carbon pool is becoming increasingly accessible to microbes, leading to increased greenhouse gas emissions, which enhances the climate warming. The assessment of the molecular structure and biodegradability of permafrost organic matter (OM) is highly needed. My research revolves around the question "how does permafrost thaw affect its OM storage?" More specifically, I assessed (1) how molecular biomarkers can be applied to characterize permafrost OM, (2) greenhouse gas production rates from thawing permafrost, and (3) the quality of OM of frozen and (previously) thawed sediments. I studied deep (max. 55 m) Yedoma and thawed Yedoma permafrost sediments from Yakutia (Sakha Republic). I analyzed sediment cores taken below thermokarst lakes on the Bykovsky Peninsula (southeast of the Lena Delta) and in the Yukechi Alas (Central Yakutia), and headwall samples from the permafrost cliff Sobo-Sise (Lena Delta) and the retrogressive thaw slump Batagay (Yana Uplands). I measured biomarker concentrations of all sediment samples. Furthermore, I carried out incubation experiments to quantify greenhouse gas production in thawing permafrost. I showed that the biomarker proxies are useful to assess the source of the OM and to distinguish between OM derived from terrestrial higher plants, aquatic plants and microbial activity. In addition, I showed that some proxies help to assess the degree of degradation of permafrost OM, especially when combined with sedimentological data in a multi-proxy approach. The OM of Yedoma is generally better preserved than that of thawed Yedoma sediments. The greenhouse gas production was highest in the permafrost sediments that thawed for the first time, meaning that the frozen Yedoma sediments contained most labile OM. Furthermore, I showed that the methanogenic communities had established in the recently thawed sediments, but not yet in the still-frozen sediments. My research provided the first molecular biomarker distributions and organic carbon turnover data as well as insights in the state and processes in deep frozen and thawed Yedoma sediments. These findings show the relevance of studying OM in deep permafrost sediments.},
  language  = {en}
}
@phdthesis{Metz2023,
  author    = {Metz, Malte},
  title     = {Finite fault earthquake source inversions},
  doi       = {10.25932/publishup-61974},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-619745},
  school      = {Universit{\"a}t Potsdam},
  pages     = {143},
  year      = {2023},
  abstract  = {Earthquake modeling is the key to a profound understanding of a rupture. Its kinematics or dynamics are derived from advanced rupture models that allow, for example, to reconstruct the direction and velocity of the rupture front or the evolving slip distribution behind the rupture front. Such models are often parameterized by a lattice of interacting sub-faults with many degrees of freedom, where, for example, the time history of the slip and rake on each sub-fault are inverted. To avoid overfitting or other numerical instabilities during a finite-fault estimation, most models are stabilized by geometric rather than physical constraints such as smoothing. As a basis for the inversion approach of this study, we build on a new pseudo-dynamic rupture model (PDR) with only a few free parameters and a simple geometry as a physics-based solution of an earthquake rupture. The PDR derives the instantaneous slip from a given stress drop on the fault plane, with boundary conditions on the developing crack surface guaranteed at all times via a boundary element approach. As a side product, the source time function on each point on the rupture plane is not constraint and develops by itself without additional parametrization. The code was made publicly available as part of the Pyrocko and Grond Python packages. The approach was compared with conventional modeling for different earthquakes. For example, for the Mw 7.1 2016 Kumamoto, Japan, earthquake, the effects of geometric changes in the rupture surface on the slip and slip rate distributions could be reproduced by simply projecting stress vectors. For the Mw 7.5 2018 Palu, Indonesia, strike-slip earthquake, we also modelled rupture propagation using the 2D Eikonal equation and assuming a linear relationship between rupture and shear wave velocity. This allowed us to give a deeper and faster propagating rupture front and the resulting upward refraction as a new possible explanation for the apparent supershear observed at the Earth's surface. The thesis investigates three aspects of earthquake inversion using PDR: (1) to test whether implementing a simplified rupture model with few parameters into a probabilistic Bayesian scheme without constraining geometric parameters is feasible, and whether this leads to fast and robust results that can be used for subsequent fast information systems (e.g., ground motion predictions). (2) To investigate whether combining broadband and strong-motion seismic records together with near-field ground deformation data improves the reliability of estimated rupture models in a Bayesian inversion. (3) To investigate whether a complex rupture can be represented by the inversion of multiple PDR sources and for what type of earthquakes this is recommended. I developed the PDR inversion approach and applied the joint data inversions to two seismic sequences in different tectonic settings. Using multiple frequency bands and a multiple source inversion approach, I captured the multi-modal behaviour of the Mw 8.2 2021 South Sandwich subduction earthquake with a large, curved and slow rupturing shallow earthquake bounded by two faster and deeper smaller events. I could cross-validate the results with other methods, i.e., P-wave energy back-projection, a clustering analysis of aftershocks and a simple tsunami forward model. The joint analysis of ground deformation and seismic data within a multiple source inversion also shed light on an earthquake triplet, which occurred in July 2022 in SE Iran. From the inversion and aftershock relocalization, I found indications for a vertical separation between the shallower mainshocks within the sedimentary cover and deeper aftershocks at the sediment-basement interface. The vertical offset could be caused by the ductile response of the evident salt layer to stress perturbations from the mainshocks. The applications highlight the versatility of the simple PDR in probabilistic seismic source inversion capturing features of rather different, complex earthquakes. Limitations, as the evident focus on the major slip patches of the rupture are discussed as well as differences to other finite fault modeling methods.},
  language  = {en}
}