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Synchrotron radiation-based Fourier transform infrared spectroscopy enables access to vibrational information from mid over far infrared to even terahertz domains. This information may prove critical for the elucidation of fundamental bio-molecular phenomena including folding-mediated innate host defence mechanisms. Antimicrobial peptides (AMPs) represent one of such phenomena. These are major effector molecules of the innate immune system, which favour attack on microbial membranes. AMPs recognise and bind to the membranes whereupon they assemble into pores or channels destabilising the membranes leading to cell death. However, specific molecular interactions responsible for antimicrobial activities have yet to be fully understood. Herein we probe such interactions by assessing molecular specific variations in the near-THz 400-40 cm(-1) range for defined helical AMP templates in reconstituted phospholipid membranes. In particular, we show that a temperature-dependent spectroscopic analysis, supported by 2D correlative tools, provides direct evidence for the membrane-induced and folding-mediated activity of AMPs. The far-FTIR study offers a direct and information-rich probe of membrane-related antimicrobial interactions.
Organic solar cells (OSCs), in recent years, have shown high efficiencies through the development of novel non-fullerene acceptors (NFAs). Fullerene derivatives have been the centerpiece of the accepting materials used throughout organic photovoltaic (OPV) research. However, since 2015 novel NFAs have been a game-changer and have overtaken fullerenes. However, the current understanding of the properties of NFAs for OPV is still relatively limited and critical mechanisms defining the performance of OPVs are still topics of debate.
In this thesis, attention is paid to understanding reduced-Langevin recombination with respect to the device physics properties of fullerene and non-fullerene systems. The work is comprised of four closely linked studies. The first is a detailed exploration of the fill factor (FF) expressed in terms of transport and recombination properties in a comparison of fullerene and non-fullerene acceptors. We investigated the key reason behind the reduced FF in the NFA (ITIC-based) devices which is faster non-geminate recombination relative to the fullerene (PCBM[70]-based) devices. This is then followed by a consideration of a newly synthesized NFA Y-series derivative which exhibits the highest power conversion efficiency for OSC at the time. Such that in the second study, we illustrated the role of disorder on the non-geminate recombination and charge extraction of thick NFA (Y6-based) devices. As a result, we enhanced the FF of thick PM6:Y6 by reducing the disorder which leads to suppressing the non-geminate recombination toward non-Langevin system. In the third work, we revealed the reason behind thickness independence of the short circuit current of PM6:Y6 devices, caused by the extraordinarily long diffusion length of Y6. The fourth study entails a broad comparison of a selection of fullerene and non-fullerene blends with respect to charge generation efficiency and recombination to unveil the importance of efficient charge generation for achieving reduced recombination.
I employed transient measurements such as Time Delayed Collection Field (TDCF), Resistance dependent Photovoltage (RPV), and steady-state techniques such as Bias Assisted Charge Extraction (BACE), Temperature-Dependent Space Charge Limited Current (T-SCLC), Capacitance-Voltage (CV), and Photo-Induce Absorption (PIA), to analyze the OSCs.
The outcomes in this thesis together draw a complex picture of multiple factors that affect reduced-Langevin recombination and thereby the FF and overall performance. This provides a suitable platform for identifying important parameters when designing new blend systems. As a result, we succeeded to improve the overall performance through enhancing the FF of thick NFA device by adjustment of the amount of the solvent additive in the active blend solution. It also highlights potentially critical gaps in the current experimental understanding of fundamental charge interaction and recombination dynamics.
Flares are magnetically driven explosions that occur in the atmospheres of all main sequence stars that possess an outer convection zone. Flaring activity is rooted in the magnetic dynamo that operates deep in the stellar interior, propagates through all layers of the atmosphere from the corona to the photosphere, and emits electromagnetic radiation from radio bands to X-ray. Eventually, this radiation, and associated eruptions of energetic particles, are ejected out into interplanetary space, where they impact planetary atmospheres, and dominate the space weather environments of young star-planet systems.
Thanks to the Kepler and the Transit Exoplanet Survey Satellite (TESS) missions, flare observations have become accessible for millions of stars and star-planet systems. The goal of this thesis is to use these flares as multifaceted messengers to understand stellar magnetism across the main sequence, investigate planetary habitability, and explore how close-in planets can affect the host star.
Using space based observations obtained by the Kepler/K2 mission, I found that flaring activity declines with stellar age, but this decline crucially depends on stellar mass and rotation. I calibrated the age of the stars in my sample using their membership in open clusters from zero age main sequence to solar age. This allowed me to reveal the rapid transition from an active, saturated flaring state to a more quiescent, inactive flaring behavior in early M dwarfs at about 600-800 Myr. This result is an important observational constraint on stellar activity evolution that I was able to de-bias using open clusters as an activity-independent age indicator.
The TESS mission quickly superseded Kepler and K2 as the main source of flares in low mass M dwarfs. Using TESS 2-minute cadence light curves, I developed a new technique for flare localization and discovered, against the commonly held belief, that flares do not occur uniformly across their stellar surface: In fast rotating fully convective stars, giant flares are preferably located at high latitudes. This bears implications for both our understanding of magnetic field emergence in these stars, and the impact on the exoplanet atmospheres: A planet that orbits in the equatorial plane of its host may be spared from the destructive effects of these poleward emitting flares.
AU Mic is an early M dwarf, and the most actively flaring planet host detected to date. Its innermost companion, AU Mic b is one of the most promising targets for a first observation of flaring star-planet interactions. In these interactions, the planet influences the star, as opposed to space weather, where the planet is always on the receiving side. The effect reflects the properties of the magnetosphere shared by planet and star, as well as the so far inaccessible magnetic properties of planets. In the about 50 days of TESS monitoring data of AU Mic, I searched for statistically robust signs of flaring interactions with AU Mic b as flares that occur in surplus of the star's intrinsic activity. I found the strongest yet still marginal signal in recurring excess flaring in phase with the orbital period of AU Mic b. If it reflects true signal, I estimate that extending the observing time by a factor of 2-3 will yield a statistically significant detection. Well within the reach of future TESS observations, this additional data may bring us closer to robustly detecting this effect than we have ever been.
This thesis demonstrates the immense scientific value of space based, long baseline flare monitoring, and the versatility of flares as a carrier of information about the magnetism of star-planet systems. Many discoveries still lay in wait in the vast archives that Kepler and TESS have produced over the years. Flares are intense spotlights into the magnetic structures in star-planet systems that are otherwise far below our resolution limits. The ongoing TESS mission, and soon PLATO, will further open the door to in-depth understanding of small and dynamic scale magnetic fields on low mass stars, and the space weather environment they effect.
Planets that closely orbit magnetically active stars are thought to be able to interact with their magnetic fields in a way that modulates stellar activity. This modulation in phase with the planetary orbit, such as enhanced X-ray activity, chromospheric spots, radio emission, or flares, is considered the clearest sign of magnetic star-planet interaction (SPI). However, the magnitude of this interaction is poorly constrained, and the intermittent nature of the interaction is a challenge for observers. AU Mic is an early M dwarf, and the most actively flaring planet host detected to date. Its innermost companion, AU Mic b, is a promising target for magnetic SPI observations. We used optical light curves of AU Mic obtained by the Transiting Exoplanet Survey Satellite to search for signs of flaring SPI with AU Mic b using a customized Anderson-Darling test. In the about 50 d of observations, the flare distributions with orbital, rotational, and synodic periods were generally consistent with intrinsic stellar flaring. We found the strongest deviation (p = 0.07, n = 71) from intrinsic flaring with the orbital period of AU Mic b, in the high-energy half of our sample (ED > 1 s). If it reflects the true SPI signal from AU Mic b, extending the observing time by a factor of 2-3 will yield a >3 sigma detection. Continued monitoring of AU Mic may therefore reveal flaring SPI with orbital phase, while rotational modulation will smear out due to the star's strong differential rotation.
Stars are uniform spheres, but only to first order. The way in which stellar rotation and magnetism break this symmetry places important observational constraints on stellar magnetic fields, and factors in the assessment of the impact of stellar activity on exoplanet atmospheres. The spatial distribution of flares on the solar surface is well known to be nonuniform, but elusive on other stars. We briefly review the techniques available to recover the loci of stellar flares, and highlight a new method that enables systematic flare localization directly from optical light curves. We provide an estimate of the number of flares we may be able to localize with the Transiting Exoplanet Survey Satellite, and show that it is consistent with the results obtained from the first full sky scan of the mission. We suggest that nonuniform flare latitude distributions need to be taken into account in accurate assessments of exoplanet habitability.
Tidal interaction between an exoplanet and its host star is a possible pathway to transfer angular momentum between the planetary orbit and the stellar spin. In cases where the planetary orbital period is shorter than the stellar rotation period, this may lead to angular momentum being transferred into the star's rotation, possibly counteracting the intrinsic stellar spin-down induced by magnetic braking. Observationally, detecting altered rotational states of single, cool field stars is challenging, as precise ages for such stars are rarely available. Here we present an empirical investigation of the rotation and magnetic activity of a sample of planet-hosting stars that are accompanied by wide stellar companions. Without needing knowledge about the absolute ages of the stars, we test for relative differences in activity and rotation of the planet hosts and their co-eval companions, using X-ray observations to measure the stellar activity levels. Employing three different tidal interaction models, we find that host stars with planets that are expected to tidally interact display elevated activity levels compared to their companion stars. We also find that those activity levels agree with the observed rotational periods for the host stars along the usual rotation-activity relationships, implying that the effect is indeed caused by a tidal interaction and not a purely magnetic interaction that would be expected to affect the stellar activity, but not necessarily the rotation. We conclude that massive, close-in planets have an impact on the stellar rotational evolution, while the smaller, more distant planets do not have a significant influence.
We present observations with the Cosmic Origins Spectrograph onboard the Hubble Space Telescope of seven compact low-mass star-forming galaxies at redshifts, z, in the range 0.3161-0.4276, with various O3Mg2 = [O III] lambda 5007/Mg II lambda 2796+2803 and Mg-2 = Mg II lambda 2796/Mg II lambda 2803 emission-line ratios. We aim to study the dependence of leaking Lyman continuum (LyC) emission on the characteristics of Mg ii emission together with the dependencies on other indirect indicators of escaping ionizing radiation. LyC emission with escape fractions f(esc)(LyC) = 3.1-4.6 per cent is detected in four galaxies, whereas only 1 sigma upper limits of f(esc)(LyC) in the remaining three galaxies were derived. A strong narrow Ly alpha emission line with two peaks separated by V-sep similar to 298-592 km s(-1) was observed in four galaxies with detected LyC emission and very weak Ly alpha emission is observed in galaxies with LyC non-detections. Our new data confirm the tight anticorrelation between f(esc)(LyC) and V-sep found for previous low-redshift galaxy samples. V-sep remains the best indirect indicator of LyC leakage among all considered indicators. It is found that escaping LyC emission is detected predominantly in galaxies with Mg-2 greater than or similar to 1.3. A tendency of an increase of f(esc)(LyC) with increasing of both the O3Mg2 and Mg-2 is possibly present. However, there is substantial scatter in these relations not allowing their use for reliable prediction of f(esc)(LyC).
The oxygen on Ag(111) system has been investigated with Auger electron-photoelectron coincidence spectroscopy (APECS).
The coincidence spectra between O 1s core level photoelectrons and O KLL Auger electrons have been studied together with Ag(3)d/AgM4,5NN coincidences.
We also describe the electron-electron coincidence spectrometer setup, CoESCA, consisting of two angle resolved time-of-flight spectrometers at a synchrotron light source.
Contributions from molecular oxygen and chemisorbed oxygen are assigned using the coincidence data, conclusions are drawn primarily from the O 1s/O KLL data.
The data acquisition and treatment procedure are also outlined.
The chemisorbed oxygen species observed are relevant for the catalytic ethylene oxidation.
The determination of the spin state of iron-bearing compounds at high pressure and temperature is crucial for our understanding of chemical and physical properties of the deep Earth. Studies on the relationship between the coordination of iron and its electronic spin structure in iron-bearing oxides, silicates, carbonates, iron alloys, and other minerals found in the Earth's mantle and core are scarce because of the technical challenges to simultaneously probe the sample at high pressures and temperatures. We used the unique properties of a pulsed and highly brilliant x-ray free electron laser (XFEL) beam at the High Energy Density (HED) instrument of the European XFEL to x-ray heat and probe samples contained in a diamond anvil cell. We heated and probed with the same x-ray pulse train and simultaneously measured x-ray emission and x-ray diffraction of an FeCO3 sample at a pressure of 51 GPa with up to melting temperatures. We collected spin state sensitive Fe K beta(1,3) fluorescence spectra and detected the sample's structural changes via diffraction, observing the inverse volume collapse across the spin transition. During x-ray heating, the carbonate transforms into orthorhombic Fe4C3O12 and iron oxides. Incipient melting was also observed. This approach to collect information about the electronic state and structural changes from samples contained in a diamond anvil cell at melting temperatures and above will considerably improve our understanding of the structure and dynamics of planetary and exoplanetary interiors.
Only a fast and global transformation towards decarbonization and sustainability can keep the Earth in a civilization-friendly state. As hotspots for (green) innovation and experimentation, cities could play an important role in this transition. They are also known to profit from each other's ideas, with policy and technology innovations spreading to other cities. In this way, cities can be conceptualized as nodes in a globe-spanning learning network. The dynamics of this process are important for society's response to climate change and other challenges, but remain poorly understood on a macroscopic level. In this contribution, we develop an approach to identify whether network-based complex contagion effects are a feature of sustainability policy adoption by cities, based on dose-response contagion and surrogate data models. We apply this methodology to an exemplary data set, comprising empirical data on the spreading of a public transport innovation (Bus Rapid Transit Systems) and a global inter-city connection network based on scheduled flight routes. Although our approach is not able to identify detailed mechanisms, our results point towards a contagious spreading process, and cannot be explained by either the network structure or the increase in global adoption rate alone. Further research on the role of a city's abstract "global neighborhood" regarding its policy and innovation decisions is thus both needed and promising, and may connect with research on social tipping processes. The methodology is generic, and can be used to compare the predictive power for innovation spreading of different kinds of inter-city network connections, e.g. via transport links, trade, or co-membership in political networks.
We quantitatively address the conjecture that magnetic helicity must be shed from the Sun by eruptions launching coronal mass ejections in order to limit its accumulation in each hemisphere. By varying the ratio of guide and strapping field and the flux rope twist in a parametric simulation study of flux rope ejection from approximately marginally stable force-free equilibria, different ratios of self- and mutual helicity are set and the onset of the torus or helical kink instability is obtained. The helicity shed is found to vary over a broad range from a minor to a major part of the initial helicity, with self helicity being largely or completely shed and mutual helicity, which makes up the larger part of the initial helicity, being shed only partly. Torus-unstable configurations with subcritical twist and without a guide field shed up to about two-thirds of the initial helicity, while a highly twisted, kink-unstable configuration sheds only about one-quarter. The parametric study also yields stable force-free flux rope equilibria up to a total flux-normalized helicity of 0.25, with a ratio of self- to total helicity of 0.32 and a ratio of flux rope to external poloidal flux of 0.94. These results numerically demonstrate the conjecture of helicity shedding by coronal mass ejections and provide a first account of its parametric dependence. Both self- and mutual helicity are shed significantly; this reduces the total initial helicity by a fraction of ∼0.4--0.65 for typical source region parameters.
Nanostructured silicon and silicon-aluminum compounds are synthesized by a novel synthesis strategy based on spark plasma sintering (SPS) of silicon nanopowder, mesoporous silicon (pSi), and aluminum nanopowder. The interplay of metal-assisted crystallization and inherent porosity is exploited to largely suppress thermal conductivity. Morphology and temperature-dependent thermal conductivity studies allow us to elucidate the impact of porosity and nanostructure on the macroscopic heat transport. Analytic electron microscopy along with quantitative image analysis is applied to characterize the sample morphology in terms of domain size and interpore distance distributions. We demonstrate that nanostructured domains and high porosity can be maintained in densified mesoporous silicon samples. In contrast, strong grain growth is observed for sintered nanopowders under similar sintering conditions. We observe that aluminum agglomerations induce local grain growth, while aluminum diffusion is observed in porous silicon and dispersed nanoparticles. A detailed analysis of the measured thermal conductivity between 300 and 773 K allows us to distinguish the effect of reduced thermal conductivity caused by porosity from the reduction induced by phonon scattering at nanosized domains. With a modified Landauer/Lundstrom approach the relative thermal conductivity and the scattering length are extracted. The relative thermal conductivity confirms the applicability of Kirkpatrick's effective medium theory. The extracted scattering lengths are in excellent agreement with the harmonic mean of log-normal distributed domain sizes and the interpore distances combined by Matthiessen's rule.
Macro-economic assessments of climate impacts lack an analysis of the distribution of daily rainfall, which can resolve both complex societal impact channels and anthropogenically forced changes(1-6). Here, using a global panel of subnational economic output for 1,554 regions worldwide over the past 40 years, we show that economic growth rates are reduced by increases in the number of wet days and in extreme daily rainfall, in addition to responding nonlinearly to the total annual and to the standardized monthly deviations of rainfall. Furthermore, high-income nations and the services and manufacturing sectors are most strongly hindered by both measures of daily rainfall, complementing previous work that emphasized the beneficial effects of additional total annual rainfall in low-income, agriculturally dependent economies(4,7). By assessing the distribution of rainfall at multiple timescales and the effects on different sectors, we uncover channels through which climatic conditions can affect the economy. These results suggest that anthropogenic intensification of daily rainfall extremes(8-10) will have negative global economic consequences that require further assessment by those who wish to evaluate the costs of anthropogenic climate change.
Elementary particle physics is a contemporary topic in science that is slowly being integrated into high-school education. These new implementations are challenging teachers’ professional knowledge worldwide. Therefore, physics education research is faced with two important questions, namely, how can particle physics be integrated in high-school physics curricula and how best to support teachers in enhancing their professional knowledge on particle physics. This doctoral research project set up to provide better guidelines for answering these two questions by conducting three studies on high-school particle physics education.
First, an expert concept mapping study was conducted to elicit experts’ expectations on what high-school students should learn about particle physics. Overall, 13 experts in particle physics, computing, and physics education participated in 9 concept mapping rounds. The broad knowledge base of the experts ensured that the final expert concept map covers all major particle physics aspects. Specifically, the final expert concept map includes 180 concepts and examples, connected with 266 links and crosslinks. Among them are also several links to students’ prior knowledge in topics such as mechanics and thermodynamics. The high interconnectedness of the concepts shows possible opportunities for including particle physics as a context for other curricular topics. As such, the resulting expert concept map is showcased as a well-suited tool for teachers to scaffold their instructional practice.
Second, a review of 27 high-school physics curricula was conducted. The review uncovered which concepts related to particle physics can be identified in most curricula. Each curriculum was reviewed by two reviewers that followed a codebook with 60 concepts related to particle physics. The analysis showed that most curricula mention cosmology, elementary particles, and charges, all of which are considered theoretical particle physics concepts. None of the experimental particle physics concepts appeared in more than half of the reviewed curricula. Additional analysis was done on two curricular subsets, namely curricula with and curricula without an explicit particle physics chapter. Curricula with an explicit particle physics chapter mention several additional explicit particle physics concepts, namely the Standard Model of particle physics, fundamental interactions, antimatter research, and particle accelerators. The latter is an example of experimental particle physics concepts. Additionally, the analysis revealed that, overall, most curricula include Nature of Science and history of physics, albeit both are typically used as context or as a tool for teaching, respectively.
Third, a Delphi study was conducted to investigate stakeholders’ expectations regarding what teachers should learn in particle physics professional development programmes. Over 100 stakeholders from 41 countries represented four stakeholder groups, namely physics education researchers, research scientists, government representatives, and high-school teachers. The study resulted in a ranked list of the 13 most important topics to be included in particle physics professional development programmes. The highest-ranked topics are cosmology, the Standard Model, and real-life applications of particle physics. All stakeholder groups agreed on the overall ranking of the topics. While the highest-ranked topics are again more theoretical, stakeholders also expect teachers to learn about experimental particle physics topics, which are ranked as medium importance topics.
The three studies addressed two research aims of this doctoral project. The first research aim was to explore to what extent particle physics is featured in high-school physics curricula. The comparison of the outcomes of the curricular review and the expert concept map showed that curricula cover significantly less than what experts expect high-school students to learn about particle physics. For example, most curricula do not include concepts that could be classified as experimental particle physics. However, the strong connections between the different concept show that experimental particle physics can be used as context for theoretical particle physics concepts, Nature of Science, and other curricular topics. In doing so, particle physics can be introduced in classrooms even though it is not (yet) explicitly mentioned in the respective curriculum.
The second research aim was to identify which aspects of content knowledge teachers are expected to learn about particle physics. The comparison of the Delphi study results to the outcomes of the curricular review and the expert concept map showed that stakeholders generally expect teachers to enhance their school knowledge as defined by the curricula. Furthermore, teachers are also expected to enhance their deeper school knowledge by learning how to connect concepts from their school knowledge to other concepts in particle physics and beyond. As such, professional development programmes that focus on enhancing teachers’ school knowledge and deeper school knowledge best support teachers in building relevant context in their instruction.
Overall, this doctoral research project reviewed the current state of high-school particle physics education and provided guidelines for future enhancements of the particle physics content in high-school student and teacher education. The outcomes of the project support further implementations of particle physics in high-school education both as explicit content and as context for other curricular topics. Furthermore, the mixed-methods approach and the outcomes of this research project lead to several implications for professional development programmes and science education research, that are discussed in the final chapters of this dissertation.
Effective professional development programs (PDPs) rely on well-defined goals. However, recent studies on PDPs have not explored the goals from a multi-stakeholder perspective. This study identifies the most important learning goals of PDPs at science research institutions as perceived by four groups of stakeholders, namely teachers, education researchers, government representatives, and research scientists. Altogether, over 100 stakeholders from 42 countries involved in PDPs at science research institutions in Europe and North America participated in a three-round Delphi study. In the first round, the stakeholders provided their opinions on what they thought the learning goals of PDPs should be through an open-ended questionnaire. In the second and third rounds, the stakeholders assessed the importance of the learning goals that emerged from the first round by rating and ranking them, respectively. The outcome of the study is a hierarchical list of the ten most important learning goals of PDPs at particle physics laboratories. The stakeholders identified enhancing teachers' knowledge of scientific concepts and models and enhancing their knowledge of the curricula as the most important learning goals. Furthermore, the results show strong agreement between all the stakeholder groups regarding the defined learning goals. Indeed, all groups ranked the learning goals by their perceived importance almost identically. These outcomes could help policymakers establish more specific policies for PDPs. Additionally, they provide PDP practitioners at science research institutions with a solid base for future research and planning endeavors.
In organic solar cells, the resulting device efficiency depends strongly on the local morphology and intermolecular interactions of the blend film. Optical spectroscopy was used to identify the spectral signatures of interacting chromophores in blend films of the donor polymer PM6 with two state-of-the-art nonfullerene acceptors, Y6 and N4, which differ merely in the branching point of the side chain. From temperature-dependent absorption and luminescence spectroscopy in solution, it is inferred that both acceptor materials form two types of aggregates that differ in their interaction energy. Y6 forms an aggregate with a predominant J-type character in solution, while for N4 molecules the interaction is predominantly in a H-like manner in solution and freshly spin-cast film, yet the molecules reorient with respect to each other with time or thermal annealing to adopt a more J-type interaction. The different aggregation behavior of the acceptor materials is also reflected in the blend films and accounts for the different solar cell efficiencies reported with the two blends.
Characterization of binding interactions of SARS-CoV-2 spike protein and DNA-peptide nanostructures
(2022)
Binding interactions of the spike proteins of the severe acute respiratory syndrome corona virus 2 (SARS-CoV-2) to a peptide fragment derived from the human angiotensin converting enzyme 2 (hACE2) receptor are investigated.
The peptide is employed as capture moiety in enzyme linked immunosorbent assays (ELISA) and quantitative binding interaction measurements that are based on fluorescence proximity sensing (switchSENSE).
In both techniques, the peptide is presented on an oligovalent DNA nanostructure, in order to assess the impact of mono- versus trivalent binding modes.
As the analyte, the spike protein and several of its subunits are tested as well as inactivated SARS-CoV-2 and pseudo viruses. While binding of the peptide to the full-length spike protein can be observed, the subunits RBD and S1 do not exhibit binding in the employed concentrations.
Variations of the amino acid sequence of the recombinant full-length spike proteins furthermore influence binding behavior. The peptide was coupled to DNA nanostructures that form a geometric complement to the trimeric structure of the spike protein binding sites.
An increase in binding strength for trimeric peptide presentation compared to single peptide presentation could be generally observed in ELISA and was quantified in switchSENSE measurements. Binding to inactivated wild type viruses could be shown as well as qualitatively different binding behavior of the Alpha and Beta variants compared to the wild type virus strain in pseudo virus models.
A novel idea for an optimal time delay state space reconstruction from uni- and multivariate time series is presented. The entire embedding process is considered as a game, in which each move corresponds to an embedding cycle and is subject to an evaluation through an objective function. This way the embedding procedure can be modeled as a tree, in which each leaf holds a specific value of the objective function. By using a Monte Carlo ansatz, the proposed algorithm populates the tree with many leafs by computing different possible embedding paths and the final embedding is chosen as that particular path, which ends at the leaf with the lowest achieved value of the objective function. The method aims to prevent getting stuck in a local minimum of the objective function and can be used in a modular way, enabling practitioners to choose a statistic for possible delays in each embedding cycle as well as a suitable objective function themselves. The proposed method guarantees the optimization of the chosen objective function over the parameter space of the delay embedding as long as the tree is sampled sufficiently. As a proof of concept, we demonstrate the superiority of the proposed method over the classical time delay embedding methods using a variety of application examples. We compare recurrence plot-based statistics inferred from reconstructions of a Lorenz-96 system and highlight an improved forecast accuracy for map-like model data as well as for palaeoclimate isotope time series. Finally, we utilize state space reconstruction for the detection of causality and its strength between observables of a gas turbine type thermoacoustic combustor.
Weather extremes pose a persistent threat to society on multiple layers. Besides an average of ~37,000 deaths per year, climate-related disasters cause destroyed properties and impaired economic activities, eroding people's livelihoods and prosperity. While global temperature rises – caused by anthropogenic greenhouse gas emissions – the direct impacts of climatic extreme events increase and will further intensify without proper adaptation measures. Additionally, weather extremes do not only have local direct effects. Resulting economic repercussions can propagate either upstream or downstream along trade chains causing indirect effects. One approach to analyze these indirect effects within the complex global supply network is the agent-based model Acclimate. Using and extending this loss-propagation model, I focus in this thesis on three aspects of the relation between weather extremes and economic repercussions.
First, extreme weather events cause direct impacts on local economic performance. I compute daily local direct output loss time series of heat stress, river floods, tropical cyclones, and their consecutive occurrence using (near-future) climate projection ensembles. These regional impacts are estimated based on physical drivers and local productivity distribution. Direct effects of the aforementioned disaster categories are widely heterogeneous concerning regional and temporal distribution. As well, their intensity changes differently under future warming. Focusing on the hurricane-impacted capital, I find that long-term growth losses increase with higher heterogeneity of a shock ensemble.
Second, repercussions are sectorally and regionally distributed via economic ripples within the trading network, causing higher-order effects. I use Acclimate to identify three phases of those economic ripples. Furthermore, I compute indirect impacts and analyze overall regional and global production and consumption changes. Regarding heat stress, global consumer losses double while direct output losses increase by a factor 1.5 between 2000 – 2039. In my research I identify the effect of economic ripple resonance and introduce it to climate impact research. This effect occurs if economic ripples of consecutive disasters overlap, which increases economic responses such as an enhancement of consumption losses. These loss enhancements can even be more amplified with increasing direct output losses, e.g. caused by climate crises.
Transport disruptions can cause economic repercussions as well. For this, I extend the model Acclimate with a geographical transportation route and expand the decision horizon of economic agents. Using this, I show that policy-induced sudden trade restrictions (e.g. a no-deal Brexit) can significantly reduce the longer-term economic prosperity of affected regions. Analyses of transportation disruptions in typhoon seasons indicate that severely affected regions must reduce production as demand falls during a storm. Substituting suppliers may compensate for fluctuations at the beginning of the storm, which fails for prolonged disruptions.
Third, possible coping mechanisms and adaptation strategies arise from direct and indirect economic responses to weather extremes. Analyzing annual trade changes due to typhoon-induced transport disruptions depict that overall exports rise. This trade resilience increases with higher network node diversification. Further, my research shows that a basic insurance scheme may diminish hurricane-induced long-term growth losses due to faster reconstruction in disasters aftermaths. I find that insurance coverage could be an economically reasonable coping scheme towards higher losses caused by the climate crisis. Indirect effects within the global economic network from weather extremes indicate further adaptation possibilities. For one, diversifying linkages reduce the hazard of sharp price increases. Next to this, close economic interconnections with regions that do not share the same extreme weather season can be economically beneficial in the medium run. Furthermore, economic ripple resonance effects should be considered while computing costs. Overall, an increase in local adaptation measures reduces economic ripples within the trade network and possible losses elsewhere. In conclusion, adaptation measures are necessary and potential present, but it seems rather not possible to avoid all direct or indirect losses.
As I show in this thesis, dynamical modeling gives valuable insights into how direct and indirect economic impacts arise from different categories of weather extremes. Further, it highlights the importance of resolving individual extremes and reflecting amplifying effects caused by incomplete recovery or consecutive disasters.