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Focus on English Linguistics
(2021)
The Arctic environments constitute rich and dynamic ecosystems, dominated by microorganisms extremely well adapted to survive and function under severe conditions. A range of physiological adaptations allow the microbiota in these habitats to withstand low temperatures, low water and nutrient availability, high levels of UV radiation, etc. In addition, other adaptations of clear competitive nature are directed at not only surviving but thriving in these environments, by disrupting the metabolism of neighboring cells and affecting intermicrobial communication. Since Arctic microbes are bioindicators which amplify climate alterations in the environment, the Arctic region presents the opportunity to study local microbiota and carry out research about interesting, potentially virulent phenotypes that could be dispersed into other habitats around the globe as a consequence of accelerating climate change. In this context, exploration of Arctic habitats as well as descriptions of the microbes inhabiting them are abundant but microbial competitive strategies commonly associated with virulence and pathogens are rarely reported. In this project, environmental samples from the Arctic region were collected and microorganisms (bacteria and fungi) were isolated. The clinical relevance of these microorganisms was assessed by observing the following virulence markers: ability to grow at a range of temperatures, expression of antimicrobial resistance and production of hemolysins. The aim of this project is to determine the frequency and relevance of these characteristics in an effort to understand microbial adaptations in habitats threatened by climate change. The isolates obtained and described here were able to grow at a range of temperatures, in some cases more than 30 °C higher than their original isolation temperature. A considerable number of them consistently expressed compounds capable of lysing sheep and bovine erythrocytes on blood agar at different incubation temperatures. Ethanolic extracts of these bacteria were able to cause rapid and complete lysis of erythrocyte suspensions and might even be hemolytic when assayed on human blood. In silico analyses showed a variety of resistance elements, some of them novel, against natural and synthetic antimicrobial compounds. In vitro experiments against a number of antimicrobial compounds showed resistance phenotypes belonging to wild-type populations and some non-wild type which clearly denote human influence in the acquisition of antimicrobial resistance. The results of this project demonstrate the presence of virulence-associated factors expressed by microorganisms of natural, non-clinical environments. This study contains some of the first reports, to the best of our knowledge, of hemolytic microbes isolated from the Arctic region. In addition, it provides additional information about the presence and expression of intrinsic and acquired antimicrobial resistance in environmental isolates, contributing to the understanding of the evolution of relevant pathogenic species and opportunistic pathogens. Finally, this study highlights some of the potential risks associated with changes in the polar regions (habitat melting and destruction, ecosystem transition and re-colonization) as important indirect consequences of global warming and altered climatic conditions around the planet.
Introduction
(2021)
Food intake is driven by the need for energy but also by the demand for essential nutrients such as protein. Whereas it was well known how diets high in protein mediate satiety, it remained unclear how diets low in protein induce appetite. Therefore, this thesis aims to contribute to the research area of the detection of restricted dietary protein and adaptive responses.
This thesis provides clear evidence that the liver-derived hormone fibroblast growth factor 21 (FGF21) is an endocrine signal of a dietary protein restriction, with the cellular amino acid sensor general control nonderepressible 2 (GCN2) kinase acting as an upstream regulator of FGF21 during protein restriction. In the brain, FGF21 is mediating the protein-restricted metabolic responses, e.g. increased energy expenditure, food intake, insulin sensitivity, and improved glucose homeostasis. Furthermore, endogenous FGF21 induced by dietary protein or methionine restriction is preventing the onset of type 2 diabetes in the New Zealand Obese mouse.
Overall, FGF21 plays an important role in the detection of protein restriction and macronutrient imbalance in rodents and humans, and mediates both the behavioral and metabolic responses to dietary protein restriction. This makes FGF21 a critical physiological signal of dietary protein restriction, highlighting the important but often overlooked impact of dietary protein on metabolism and eating behavior, independent of dietary energy content.
Polymeric semiconductors are strong contenders for replacing traditional inorganic semiconductors in electronic applications requiring low power, low cost and flexibility, such as biosensors, flexible solar cells and electronic displays. Molecular doping has the potential to enable this revolution by improving the conductivity and charge transport properties of this class of materials. Despite decades of research in this field, gaps in our understanding of the nature of dopant–polymer interactions has resulted in limited commercialization of this technology. This work aims at providing a deeper insight into the underlying mechanisms of molecular p-doping of semiconducting polymers in the solution and solid-state, and thereby bring the scientific community closer to realizing the dream of making organic semiconductors commonplace in the electronics industry. The role of 1) dopant size/shape, 2) polymer chain aggregation and 3) charge delocalization on the doping mechanism and efficiency is addressed using optical (UV-Vis-NIR) and electron paramagnetic resonance (EPR) spectroscopies. By conducting a comprehensive study of the nature and concentration of the doping-induced species in solutions of the polymer poly(3-hexylthiophene) (P3HT) with 3 different dopants, we identify the unique optical signatures of the delocalized polaron, localized polaron and charge-transfer complex, and report their extinction coefficient values. Furthermore, with X-ray diffraction, atomic force microscopy and electrical conductivity measurements, we study the impact of processing technique and doping mechanism on the morphology and thereby, charge transport through the doped films.
This work demonstrates that the doping mechanism and type of doping-induced species formed are strongly influenced by the polymer backbone arrangement rather than dopant shape/size. The ability of the polymer chain to aggregate is found to be crucial for efficient charge transfer (ionization) and polaron delocalization. At the same time, our results suggest that the high ionization efficiency of a dopant–polymer system in solution may subsequently hinder efficient charge transport in the solid-state due to the reduction in the fraction of tie chains, which enable charges to move efficiently between aggregated domains in the films. This study demonstrates the complex multifaceted nature of polymer doping while providing important hints for the future design of dopant-host systems and film fabrication techniques.
Noise is ubiquitous in nature and usually results in rich dynamics in stochastic systems such as oscillatory systems, which exist in such various fields as physics, biology and complex networks. The correlation and synchronization of two or many oscillators are widely studied topics in recent years.
In this thesis, we mainly investigate two problems, i.e., the stochastic bursting phenomenon in noisy excitable systems and synchronization in a three-dimensional Kuramoto model with noise. Stochastic bursting here refers to a sequence of coherent spike train, where each spike has random number of followers due to the combined effects of both time delay and noise. Synchronization, as a universal phenomenon in nonlinear dynamical systems, is well illustrated in the Kuramoto model, a prominent model in the description of collective motion.
In the first part of this thesis, an idealized point process, valid if the characteristic timescales in the problem are well separated, is used to describe statistical properties such as the power spectral density and the interspike interval distribution. We show how the main parameters of the point process, the spontaneous excitation rate, and the probability to induce a spike during the delay action can be calculated from the solutions of a stationary and a forced Fokker-Planck equation. We extend it to the delay-coupled case and derive analytically the statistics of the spikes in each neuron, the pairwise correlations between any two neurons, and the spectrum of the total output from the network.
In the second part, we investigate the three-dimensional noisy Kuramoto model, which can be used to describe the synchronization in a swarming model with helical trajectory. In the case without natural frequency, the Kuramoto model can be connected with the Vicsek model, which is widely studied in collective motion and swarming of active matter. We analyze the linear stability of the incoherent state and derive the critical coupling strength above which the incoherent state loses stability. In the limit of no natural frequency, an exact self-consistent equation of the mean field is derived and extended straightforward to any high-dimensional case.
History of Forgetfulness
(2021)
This open access book presents a topical, comprehensive and differentiated analysis of Germany's public administration and reforms. It provides an overview on key elements of German public administration at the federal, Länder and local levels of government as well as on current reform activities of the public sector. It examines the key institutional features of German public administration; the changing relationships between public administration, society and the private sector; the administrative reforms at different levels of the federal system and numerous sectors; and new challenges and modernization approaches like digitalization, Open Government and Better Regulation. Each chapter offers a combination of descriptive information and problem-oriented analysis, presenting key topical issues in Germany which are relevant to an international readership.
Federal Administration
(2021)
The federal administration is significantly small (around 10 percent of all public employees). This speciality of the German administrative system is based on the division of responsibilities: the central (federal) level drafts and adopts most of the laws and public programmes, and the state level (together with the municipal level) implements them. The administration of the federal level comprises the ministries, subordinated agencies for special and selected operational tasks (e.g. the authorisation of drugs, information security and registration of refugees) in distinct administrative sectors (e.g. foreign service, armed forces and federal police). The capacity for preparing and monitoring government bills and statutory instruments is well developed. Moreover, the instruments and tools of coordination are exemplary compared with other countries, although the recent digital turn has been adopted less advanced than elsewhere.
This chapter describes the most prominent public management reform trajectories in German public administration over the past decades since unification. In the 1990s, the New Steering Model emerged as a German variant of the NPM. Since the mid-2000s, local governments in Germany have been subjected to a mandatory reform of their budgeting and accounting system known as the New Municipal Financial Management reforms. Both reforms have led to a substantial change in terms of internal decentralisation, customer orientation, transparency in resource use and the financial situation of administrative bodies. But the emerging reform patterns and their impacts have not replaced the dominance of a strong legalist culture with hierarchical, centralised control. However, in the course of the reforms, a citizen-customer perspective, more participation of citizens and limited application of new management instruments have been accommodated within the persisting bureaucratic system.
Over the last decades, Better Regulation has become a major reform topic at the federal and—in some cases—also at the Länder level. Although the debate about improving regulatory quality and reducing unnecessary burdens created by bureaucracy and red tape date back to the 1960s and 1970s, the introduction by law in 2006 of a new independent institutionalised body for regulatory control at the federal level of government has brought a new quality to the discourse and practice of Better Regulation in Germany. This chapter introduces the basic features of the legislative process at the federal level in Germany, addresses the issue of Better Regulation and outlines the role of the National Regulatory Control Council (Nationaler Normenkontrollrat—NKR) as a ‘watchdog’ for compliance costs, red tape and regulatory impacts.
Although German bureaucracy is typically categorised as Weberian, a clear distinction between politics and administration has never been a defining characteristic of the German political-administrative system. Many close interrelations and interactions between elected politicians and appointed civil servants can be observed at all levels of administration. Higher-ranking civil servants in Germany are used to and generally appreciate the functional politicisation of their jobs, that is their close involvement in all stages of the policy process, from policy formation, goal definition, negotiation within and outside government to the implementation and evaluation of policies. For top positions, therefore, a class of ‘political civil servants’ is a special feature of the German system, and obtaining ‘political craft’ has become an important part of the learning and job experience of higher-ranking civil servants.
German Public Administration
(2021)
The international community of public administration and administrative sciences shows a great interest in the basic features of the German administrative system. The German public administration with its formative decentralisation (called: administrative federalism) is regarded as a prime example of multilevel governance and strong local self-government. Furthermore, over the past decades, the traditional profile of the German administrative system has significantly been reshaped and remoulded through reforms, processes of modernisation and the transformation process in East Germany. Studies on the German administrative system should focus especially on
key institutional features of public administration;
changing relationships between public administration, society and the private sector;
administrative reforms at different levels of the federal system; and
new challenges and modernisation approaches, such as digitalisation, open government and better regulation.
Human resource management (HRM) reform has not been the focus of attention in Germany despite its obvious relevance for effective policy implementation. Although there is a general trend worldwide towards convergence between public and private HRM strategies and practices, management of the workforce in German public administration still remains largely traditional and bureaucratic. This chapter describes and analyses German practices regarding the central functions and elements of HRM such as planning, recruitment, training and leadership. Furthermore, it explores the importance and contribution of public service motivation, performance-related pay and diversity management in the context of German practices. The chapter concludes by highlighting some of the major paradoxes of German public HRM in light of current challenges, such as demographic change, digital transformation and organisational development capabilities.
The chapter analyses recent reforms in the multilevel system of the Länder, specifically territorial, functional and structural reforms, which represent three of the most crucial and closely interconnected reform trajectories at the subnational level. It sheds light on the variety of reform approaches pursued in the different Länder and also highlights some factors that account for these differences. The transfer of state functions to local governments is addressed as well as the restructuring of Länder administrations (e.g. abolishment of the meso level of the Länder administration and of single-purpose state agencies) and the rescaling of territorial boundaries at county and municipal levels, including a brief review of the recently failed (territorial) reforms in Eastern Germany.
The German system of public sector employment (including civil servants and public employees) qualifies as a classical European continental civil service model moulded in traditional forms of a Weberian bureaucracy. Its features include a career-based employment system with entry based on levels of formal qualification. Coordinated by legal frames and centralised collective bargaining, the civil service is, at the same time, decentralised and flexible enough to accommodate regional differences and societal changes. In comparison, the civil service system stands out for its high degrees of professionalism and legal fairness with low levels of corruption or cronyism.
This work develops hybrid methods of imaging spectroscopy for open pit mining and examines their feasibility compared with state-of-the-art. The material distribution within a mine face differs in the small scale and within daily assigned extraction segments. These changes can be relevant to subsequent processing steps but are not always visually identifiable prior to the extraction. Misclassifications that cause false allocations of extracted material need to be minimized in order to reduce energy-intensive material re-handling. The use of imaging spectroscopy aspires to the allocation of relevant deposit-specific materials before extraction, and allows for efficient material handling after extraction. The aim of this work is the parameterization of imaging spectroscopy for pit mining applications and the development and evaluation of a workflow for a mine face, ground- based, spectral characterization. In this work, an application-based sensor adaptation is proposed. The sensor complexity is reduced by down-sampling the spectral resolution of the system based on the samples’ spectral characteristics. This was achieved by the evaluation of existing hyperspectral outcrop analysis approaches based on laboratory sample scans from the iron quadrangle in Minas Gerais, Brazil and by the development of a spectral mine face monitoring workflow which was tested for both an operating and an inactive open pit copper mine in the Republic of Cyprus.
The workflow presented here is applied to three regional data sets: 1) Iron ore samples from Brazil, (laboratory); 2) Samples and hyperspectral mine face imagery from the copper-gold-pyrite mine Apliki, Republic of Cyprus (laboratory and mine face data); and 3) Samples and hyperspectral mine face imagery from the copper-gold-pyrite deposit Three Hills, Republic of Cyprus (laboratory and mine face data). The hyperspectral laboratory dataset of fifteen Brazilian iron ore samples was used to evaluate different analysis methods and different sensor models. Nineteen commonly used methods to analyze and map hyperspectral data were compared regarding the methods’ resulting data products and the accuracy of the mapping and the analysis computation time. Four of the evaluated methods were determined for subsequent analyses to determine the best-performing algorithms: The spectral angle mapper (SAM), a support vector machine algorithm (SVM), the binary feature fitting algorithm (BFF) and the EnMap geological mapper (EnGeoMap). Next, commercially available imaging spectroscopy sensors were evaluated for their usability in open pit mining conditions. Step-wise downsampling of the data - the reduction of the number of bands with an increase of each band’s bandwidth - was performed to investigate the possible simplification and ruggedization of a sensor without a quality fall-off of the mapping results. The impact of the atmosphere visible in the spectrum between 1300–2010nm was reduced by excluding the spectral range from the data for mapping. This tested the feasibility of the method under realistic open pit data conditions. Thirteen datasets based on the different, downsampled sensors were analyzed with the four predetermined methods. The optimum sensor for spectral mine face material distinction was determined as a VNIR-SWIR sensor with 40nm bandwidths in the VNIR and 15nm bandwidths in the SWIR spectral range and excluding the atmospherically impacted bands. The Apliki mine sample dataset was used for the application of the found optimal analyses and sensors. Thirty-six samples were analyzed geochemically and mineralogically. The sample spectra were compiled to two spectral libraries, both distinguishing between seven different geochemical-spectral clusters. The reflectance dataset was downsampled to five different sensors. The five different datasets were mapped with the SAM, BFF and SVM method achieving mapping accuracies of 85-72%, 85-76% and 57-46% respectively. One mine face scan of Apliki was used for the application of the developed workflow. The mapping results were validated against the geochemistry and mineralogy of thirty-six documented field sampling points and a zonation map of the mine face which is based on sixty-six samples and field mapping. The mine face was analyzed with SAM and BFF. The analysis maps were visualized on top of a Structure-from-Motion derived 3D model of the open pit. The mapped geological units and zones correlate well with the expected zonation of the mine face. The third set of hyperspectral imagery from Three Hills was available for applying the fully-developed workflow. Geochemical sample analyses and laboratory spectral data of fifteen different samples from the Three Hills mine, Republic of Cyprus, were used to analyse a downsampled mine face scan of the open pit. Here, areas of low, medium and high ore content were identified.
The developed workflow is successfully applied to the open pit mines Apliki and Three Hills and the spectral maps reflect the prevailing geological conditions. This work leads through the acquisition, preparation and processing of imaging spectroscopy data, the optimum choice of analysis methodology, and the utilization of simplified, robust sensors that meet the requirements of open pit mining conditions. It accentuates the importance of a site-specific and deposit-specific spectral library for the mine face analysis and underlines the need for geological and spectral analysis experts to successfully implement imaging spectroscopy in the field of open pit mining.
In this introductory chapter, the editors describe the main theoretical basis of analysis of this book and the methodological approach. The core of this book consists of 14 country-specific chapters, which allow a European comparison and show the increasing variance in migration policy approaches within and between European countries. The degree of local autonomy, the level of centralisation and the traditional forms of migration policy are factors that especially influence the possibilities for local authorities to formulate their own integration policies.
This chapter focuses on the relationship between public opinion on migration and its media coverage. Different explanatory models, including individual characteristics, cultural factors and the impact of media and politics, have been proposed to explain public attitudes towards migrants. Understanding the local context is important, as the shares of migrants living in each region and city vary considerably. Providing correct statistical information, stressing the diversity of current migration patterns in Europe and taking part in media and public discussions are ways in which to impact public attitudes at the local level.
The chapter begins with a brief historical overview of Germany’s transition in the twentieth and twenty-first century from a transit and emigration country to one of immigration. The next part of this chapter looks at the challenges and problems facing German immigration policy within a multi-level federal system. Finally, the chapter gives an analysis of some of the trends in German migration policy since the refugee crisis in 2015, such as changes in the party system and in the concepts underlying migration policies to better manage, control and limit immigration to Germany.
As expected, the traditions of national-state migration policies continue to play a very important role, path-dependence in this policy field remains high. The distribution of competences in migration policy and the integration of migrants in the nation states continues to be very different. When implementing integration strategies at grassroots level, the respective policies should be tailored to the profile of both the local migrant community and the native population. Besides better migration management in local administration and the interaction of top-down and bottom-up efforts to integrate migrants is of importance.
This book presents an overview of European migration policy and the various institutional arrangements within and between various actors, such as local councils, local media, local economies, and local civil society initiatives. Both the role of local authorities in this policy field and their cooperation with civil society initiatives or networks are under-explored topics for research. In response, this book provides a range of detailed case studies focusing on the six main groups of national and administrative traditions in Europe: Germanic, Scandinavian, Napoleonic, Southeastern European, Central-Eastern European and Anglo-Saxon.
Energy is at the heart of the climate crisis—but also at the heart of any efforts for climate change mitigation. Energy consumption is namely responsible for approximately three quarters of global anthropogenic greenhouse gas (GHG) emissions. Therefore, central to any serious plans to stave off a climate catastrophe is a major transformation of the world's energy system, which would move society away from fossil fuels and towards a net-zero energy future. Considering that fossil fuels are also a major source of air pollutant emissions, the energy transition has important implications for air quality as well, and thus also for human and environmental health. Both Europe and Germany have set the goal of becoming GHG neutral by 2050, and moreover have demonstrated their deep commitment to a comprehensive energy transition. Two of the most significant developments in energy policy over the past decade have been the interest in expansion of shale gas and hydrogen, which accordingly have garnered great interest and debate among public, private and political actors.
In this context, sound scientific information can play an important role by informing stakeholder dialogue and future research investments, and by supporting evidence-based decision-making. This thesis examines anticipated environmental impacts from possible, relevant changes in the European energy system, in order to impart valuable insight and fill critical gaps in knowledge. Specifically, it investigates possible future shale gas development in Germany and the United Kingdom (UK), as well as a hypothetical, complete transition to hydrogen mobility in Germany. Moreover, it assesses the impacts on GHG and air pollutant emissions, and on tropospheric ozone (O3) air quality. The analysis is facilitated by constructing emission scenarios and performing air quality modeling via the Weather Research and Forecasting model coupled with chemistry (WRF-Chem). The work of this thesis is presented in three research papers.
The first paper finds that methane (CH4) leakage rates from upstream shale gas development in Germany and the UK would range between 0.35% and 1.36% in a realistic, business-as-usual case, while they would be significantly lower - between 0.08% and 0.15% - in an optimistic, strict regulation and high compliance case, thus demonstrating the value and potential of measures to substantially reduce emissions. Yet, while the optimistic case is technically feasible, it is unlikely that the practices and technologies assumed would be applied and accomplished on a systematic, regular basis, owing to economics and limited monitoring resources. The realistic CH4 leakage rates estimated in this study are comparable to values reported by studies carried out in the US and elsewhere. In contrast, the optimistic rates are similar to official CH4 leakage data from upstream gas production in Germany and in the UK. Considering that there is a lack of systematic, transparent and independent reports supporting the official values, this study further highlights the need for more research efforts in this direction. Compared with national energy sector emissions, this study suggests that shale gas emissions of volatile organic compounds (VOCs) could be significant, though relatively insignificant for other air pollutants. Similar to CH4, measures could be effective for reducing VOCs emissions.
The second paper shows that VOC and nitrogen oxides (NOx) emissions from a future shale gas industry in Germany and the UK have potentially harmful consequences for European O3 air quality on both the local and regional scale. The results indicate a peak increase in maximum daily 8-hour average O3 (MDA8) ranging from 3.7 µg m-3 to 28.3 µg m-3. Findings suggest that shale gas activities could result in additional exceedances of MDA8 at a substantial percentage of regulatory measurement stations both locally and in neighboring and distant countries, with up to circa one third of stations in the UK and one fifth of stations in Germany experiencing additional exceedances. Moreover, the results reveal that the shale gas impact on the cumulative health-related metric SOMO35 (annual Sum of Ozone Means Over 35 ppb) could be substantial, with a maximum increase of circa 28%. Overall, the findings suggest that shale gas VOC emissions could play a critical role in O3 enhancement, while NOx emissions would contribute to a lesser extent. Thus, the results indicate that stringent regulation of VOC emissions would be important in the event of future European shale gas development to minimize deleterious health outcomes.
The third paper demonstrates that a hypothetical, complete transition of the German vehicle fleet to hydrogen fuel cell technology could contribute substantially to Germany's climate and air quality goals. The results indicate that if the hydrogen were to be produced via renewable-powered water electrolysis (green hydrogen), German carbon dioxide equivalent (CO2eq) emissions would decrease by 179 MtCO2eq annually, though if electrolysis were powered by the current electricity mix, emissions would instead increase by 95 MtCO2eq annually. The findings generally reveal a notable anticipated decrease in German energy emissions of regulated air pollutants. The results suggest that vehicular hydrogen demand is 1000 PJ annually, which would require between 446 TWh and 525 TWh for electrolysis, hydrogen transport and storage. When only the heavy duty vehicle segment (HDVs) is shifted to green hydrogen, the results of this thesis show that vehicular hydrogen demand drops to 371 PJ, while a deep emissions cut is still realized (-57 MtCO2eq), suggesting that HDVs are a low-hanging fruit for contributing to decarbonization of the German road transport sector with hydrogen energy.
Compound values are not universally supported in virtual machine (VM)-based programming systems and languages. However, providing data structures with value characteristics can be beneficial. On one hand, programming systems and languages can adequately represent physical quantities with compound values and avoid inconsistencies, for example, in representation of large numbers. On the other hand, just-in-time (JIT) compilers, which are often found in VMs, can rely on the fact that compound values are immutable, which is an important property in optimizing programs. Considering this, compound values have an optimization potential that can be put to use by implementing them in VMs in a way that is efficient in memory usage and execution time. Yet, optimized compound values in VMs face certain challenges: to maintain consistency, it should not be observable by the program whether compound values are represented in an optimized way by a VM; an optimization should take into account, that the usage of compound values can exhibit certain patterns at run-time; and that necessary value-incompatible properties due to implementation restrictions should be reduced.
We propose a technique to detect and compress common patterns of compound value usage at run-time to improve memory usage and execution speed. Our approach identifies patterns of frequent compound value references and introduces abbreviated forms for them. Thus, it is possible to store multiple inter-referenced compound values in an inlined memory representation, reducing the overhead of metadata and object references. We extend our approach by a notion of limited mutability, using cells that act as barriers for our approach and provide a location for shared, mutable access with the possibility of type specialization. We devise an extension to our approach that allows us to express automatic unboxing of boxed primitive data types in terms of our initial technique. We show that our approach is versatile enough to express another optimization technique that relies on values, such as Booleans, that are unique throughout a programming system. Furthermore, we demonstrate how to re-use learned usage patterns and optimizations across program runs, thus reducing the performance impact of pattern recognition.
We show in a best-case prototype that the implementation of our approach is feasible and can also be applied to general purpose programming systems, namely implementations of the Racket language and Squeak/Smalltalk. In several micro-benchmarks, we found that our approach can effectively reduce memory consumption and improve execution speed.
While a growing body of literature finds positive impacts of Start-Up Subsidies (SUS) on labor market outcomes of participants, little is known about how the design of these programs shapes their effectiveness and hence how to improve policy. As experimental variation in program design is unavailable, we exploit the 2011 reform of the current German SUS program for the unemployed which strengthened case-workers’ discretionary power, increased entry requirements and reduced monetary support. We estimate the impact of the reform on the program’s effectiveness using samples of participants and non-participants from before and after the reform. To control for time-constant unobserved heterogeneity as well as differential selection patterns based on observable characteristics over time, we combine Difference-in-Differences with inverse probability weighting using covariate balancing propensity scores. Holding participants’ observed characteristics as well as macroeconomic conditions constant, the results suggest that the reform was successful in raising employment effects on average. As these findings may be contaminated by changes in selection patterns based on unobserved characteristics, we assess our results using simulation-based sensitivity analyses and find that our estimates are highly robust to changes in unobserved characteristics. Hence, the reform most likely had a positive impact on the effectiveness of the program, suggesting that increasing entry requirements and reducing support in-creased the program’s impacts while reducing the cost per participant.
The large literature that aims to find evidence of climate migration delivers mixed findings. This meta-regression analysis i) summarizes direct links between adverse climatic events and migration, ii) maps patterns of climate migration, and iii) explains the variation in outcomes. Using a set of limited dependent variable models, we meta-analyze thus-far the most comprehensive sample of 3,625 estimates from 116 original studies and produce novel insights on climate migration. We find that extremely high temperatures and drying conditions increase migration. We do not find a significant effect of sudden-onset events. Climate migration is most likely to emerge due to contemporaneous events, to originate in rural areas and to take place in middle-income countries, internally, to cities. The likelihood to become trapped in affected areas is higher for women and in low-income countries, particularly in Africa. We uniquely quantify how pitfalls typical for the broader empirical climate impact literature affect climate migration findings. We also find evidence of different publication biases.
Reciprocal space slicing
(2021)
An experimental technique that allows faster assessment of out-of-plane strain dynamics of thin film heterostructures via x-ray diffraction is presented. In contrast to conventional high-speed reciprocal space-mapping setups, our approach reduces the measurement time drastically due to a fixed measurement geometry with a position-sensitive detector. This means that neither the incident (ω) nor the exit (2θ) diffraction angle is scanned during the strain assessment via x-ray diffraction. Shifts of diffraction peaks on the fixed x-ray area detector originate from an out-of-plane strain within the sample. Quantitative strain assessment requires the determination of a factor relating the observed shift to the change in the reciprocal lattice vector. The factor depends only on the widths of the peak along certain directions in reciprocal space, the diffraction angle of the studied reflection, and the resolution of the instrumental setup. We provide a full theoretical explanation and exemplify the concept with picosecond strain dynamics of a thin layer of NbO2.
Reciprocal space slicing
(2021)
An experimental technique that allows faster assessment of out-of-plane strain dynamics of thin film heterostructures via x-ray diffraction is presented. In contrast to conventional high-speed reciprocal space-mapping setups, our approach reduces the measurement time drastically due to a fixed measurement geometry with a position-sensitive detector. This means that neither the incident (ω) nor the exit (2θ) diffraction angle is scanned during the strain assessment via x-ray diffraction. Shifts of diffraction peaks on the fixed x-ray area detector originate from an out-of-plane strain within the sample. Quantitative strain assessment requires the determination of a factor relating the observed shift to the change in the reciprocal lattice vector. The factor depends only on the widths of the peak along certain directions in reciprocal space, the diffraction angle of the studied reflection, and the resolution of the instrumental setup. We provide a full theoretical explanation and exemplify the concept with picosecond strain dynamics of a thin layer of NbO2.
By regulating the concentration of carbon in our atmosphere, the global carbon cycle drives changes in our planet’s climate and habitability. Earth surface processes play a central, yet insufficiently constrained role in regulating fluxes of carbon between terrestrial reservoirs and the atmosphere. River systems drive global biogeochemical cycles by redistributing significant masses of carbon across the landscape. During fluvial transit, the balance between carbon oxidation and preservation determines whether this mass redistribution is a net atmospheric CO2 source or sink. Existing models for fluvial carbon transport fail to integrate the effects of sediment routing processes, resulting in large uncertainties in fluvial carbon fluxes to the oceans.
In this Ph.D. dissertation, I address this knowledge gap through three studies that focus on the timescale and routing pathways of fluvial mass transfer and show their effect on the composition and fluxes of organic carbon exported by rivers. The hypotheses posed in these three studies were tested in an analog lowland alluvial river system – the Rio Bermejo in Argentina. The Rio Bermejo annually exports more than 100 Mt of sediment and organic matter from the central Andes, and transports this material nearly 1300 km downstream across the lowland basin without influence from tributaries, allowing me to isolate the effects of geomorphic processes on fluvial organic carbon cycling. These studies focus primarily on the geochemical composition of suspended sediment collected from river depth profiles along the length of the Rio Bermejo.
In Chapter 3, I aimed to determine the mean fluvial sediment transit time for the Rio Bermejo and evaluate the geomorphic processes that regulate the rate of downstream sediment transfer. I developed a framework to use meteoric cosmogenic 10Be (10Bem) as a chronometer to track the duration of sediment transit from the mountain front downstream along the ~1300 km channel of the Rio Bermejo. I measured 10Bem concentrations in suspended sediment sampled from depth profiles, and found a 230% increase along the fluvial transit pathway. I applied a simple model for the time-dependent accumulation of 10Bem on the floodplain to estimate a mean sediment transit time of 8.5±2.2 kyr. Furthermore, I show that sediment transit velocity is influenced by lateral migration rate and channel morphodynamics. This approach to measuring sediment transit time is much more precise than other methods previously used and shows promise for future applications.
In Chapter 4, I aimed to quantify the effects of hydrodynamic sorting on the composition and quantity of particulate organic carbon (POC) export transported by lowland rivers. I first used scanning electron miscroscopy (SEM) coupled with nanoscale secondary ion mass spectrometry (NanoSIMS) analyses to show that the Bermejo transports two principal types of POC: 1) mineral-bound organic carbon associated with <4 µm, platy grains, and 2) coarse discrete organic particles. Using n-alkane stable isotope data and particle shape analysis, I showed that these two carbon pools are vertically sorted in the water column, due to differences in particle settling velocity. This vertical sorting may drive modern POC to be transported efficiently from source-to-sink, driving efficient CO2 drawdown. Simultaneously, vertical sorting may drive degraded, mineral-bound POC to be deposited overbank and stored on the floodplain for centuries to millennia, resulting in enhanced POC remineralization. In the Rio Bermejo, selective deposition of coarse material causes the proportion of mineral-bound POC to increase with distance downstream, but the majority of exported POC is composed of discrete organic particles, suggesting that the river is a net carbon sink. In summary, this study shows that selective deposition and hydraulic sorting control the composition and fate of fluvial POC during fluvial transit.
In Chapter 5, I characterized and quantified POC transformation and oxidation during fluvial transit. I analyzed the radiocarbon content and stable carbon isotopic composition of Rio Bermejo suspended sediment and found that POC ages during fluvial transit, but is also degraded and oxidized during transient floodplain storage. Using these data, I developed a conceptual model for fluvial POC cycling that allows the estimation of POC oxidation relative to POC export, and ultimately reveals whether a river is a net source or sink of CO2 to the atmosphere. Through this study, I found that the Rio Bermejo annually exports more POC than is oxidized during transit, largely due to high rates of lateral migration that cause erosion of floodplain vegetation and soil into the river. These results imply that human engineering of rivers could alter the fluvial carbon balance, by reducing lateral POC inputs and increasing the mean sediment transit time.
Together, these three studies quantitatively link geomorphic processes to rates of POC transport and degradation across sub-annual to millennial time scales and nanoscale to 103 km spatial scales, laying the groundwork for a global-scale fluvial organic carbon cycling model.
Investigation of Sirtuin 3 overexpression as a genetic model of fasting in hypothalamic neurons
(2021)
Geomagnetic field modeling using spherical harmonics requires the inversion for hundreds to thousands of parameters. This large-scale problem can always be formulated as an optimization problem, where a global minimum of a certain cost function has to be calculated. A variety of approaches is known in order to solve this inverse problem, e.g. derivative-based methods or least-squares methods and their variants. Each of these methods has its own advantages and disadvantages, which affect for example the applicability to non-differentiable functions or the runtime of the corresponding algorithm.
In this work, we pursue the goal to find an algorithm which is faster than the established methods and which is applicable to non-linear problems. Such non-linear problems occur for example when estimating Euler angles or when the more robust L_1 norm is applied. Therefore, we will investigate the usability of stochastic optimization methods from the CMAES family for modeling the geomagnetic field of Earth's core. On one hand, basics of core field modeling and their parameterization are discussed using some examples from the literature. On the other hand, the theoretical background of the stochastic methods are provided. A specific CMAES algorithm was successfully applied in order to invert data of the Swarm satellite mission and to derive the core field model EvoMag. The EvoMag model agrees well with established models and observatory data from Niemegk. Finally, we present some observed difficulties and discuss the results of our model.
Sephardim and Ashkenazim
(2021)
Sephardic and Ashkenazic Judaism have long been studied separately. Yet, scholars are becoming ever more aware of the need to merge them into a single field of Jewish Studies. This volume opens new perspectives and bridges traditional gaps. The authors are not simply contributing to their respective fields of Sephardic or Ashkenazic Studies. Rather, they all include both Sephardic and Ashkenazic perspectives as they reflect on different aspects of encounters and reconsider traditional narratives. Subjects range from medieval and early modern Sephardic and Ashkenazic constructions of identities, influences, and entanglements in the fields of religious art, halakhah, kabbalah, messianism, and charity to modern Ashkenazic Sephardism and Sephardic admiration for Ashkenazic culture. For reasons of coherency, the contributions all focus on European contexts between the fourteenth and the nineteenth centuries.
Sephardim and Ashkenazim
(2021)
We develop a model of optimal carbon taxation and redistribution taking into account horizontal equity concerns by considering heterogeneous energy efficiencies. By deriving first- and second-best rules for policy instruments including carbon taxes, transfers and energy subsidies, we then investigate analytically how horizontal equity is considered in the social welfare maximizing tax structure. We calibrate the model to German household data and a 30 percent emission reduction goal. Our results show that energy-intensive households should receive more redistributive resources than energy-efficient households if and only if social inequality aversion is sufficiently high. We further find that redistribution of carbon tax revenue via household-specific transfers is the first-best policy. Equal per-capita transfers do not suffer from informational problems, but increase mitigation costs by around 15 percent compared to the first- best for unity inequality aversion. Adding renewable energy subsidies or non-linear energy subsidies, reduces mitigation costs further without relying on observability of households’ energy efficiency.
The aim of the doctoral project was to answer the question of whether the structural word-initial noun capitalization, as it can otherwise only be found in Luxembourgish alongside German, has a function that is advantageous for the reader. The overriding hypothesis was that an advantage is achieved by activating a syntactic category, namely the core of a noun phrase, through the parafoveal perception of the capital letters. This perception from the corner of the eye should make it possible to preprocess the following noun. As a result, sentence processing should be facilitated, which should ultimately be reflected in overall faster reading times and fixation durations.
The structure of the project includes three studies, some of which included different participant groups:
Study 1:
Study design: Semantic priming using garden-path sentences should bring out the functionality of noun capitalization for the reader
Participant groups: German natives reading German
Study 2:
Study design: same design as study 1, but in English
Participant groups:
English natives without any knowledge of German reading English
English natives who regularly read German reading English
German with high proficiency in English reading English
Study 3:
Study design:
Influence of the noun frequency on a potential preprocessing using the boundary paradigm; Study languages: German and English
Participant groups:
German natives reading German
English natives without any knowledge of German reading English
German with high proficiency in English reading English
Brief summary: The noun capitalization clearly has an impact on sentence processing in both German and English. It cannot be confirmed that this has a substantial, decisive advantage.
We investigate how the economic consequences of the pandemic, and of the government-mandated measures to contain its spread, affect the self-employed – particularly women – in Germany. For our analysis, we use representative, real-time survey data in which respondents were asked about their situation during the COVID-19 pandemic. Our findings indicate that among the self-employed, who generally face a higher likelihood of income losses due to COVID-19 than employees, women are 35% more likely to experience income losses than their male counterparts. Conversely, we do not find a comparable gender gap among employees. Our results further suggest that the gender gap among the self-employed is largely explained by the fact that women disproportionately work in industries that are more severely affected by the COVID-19 pandemic. Our analysis of potential mechanisms reveals that women are significantly more likely to be impacted by government-imposed restrictions, i.e. the regulation of opening hours. We conclude that future policy measures intending to mitigate the consequences of such shocks should account for this considerable variation in economic hardship.
In this paper, we study the effect of exogenous global crop price changes on migration from agricultural and non-agricultural households in Sub-Saharan Africa. We show that, similar to the effect of positive local weather shocks, the effect of a locally-relevant global crop price increase on household out-migration depends on the initial household wealth. Higher international producer prices relax the budget constraint of poor agricultural households and facilitate migration. The order of magnitude of a standardized price effect is approx. one third of the standardized effect of a local weather shock. Unlike positive weather shocks, which mostly facilitate internal rural-urban migration, positive income shocks through rising producer prices only increase migration to neighboring African countries, likely due to the simultaneous decrease in real income in nearby urban areas. Finally, we show that while higher producer prices induce conflict, conflict does not play a role for the household decision to send a member as a labor migrant.
Diabetes is a major public health problem with increasing global prevalence. Type 2 diabetes (T2D), which accounts for 90% of all diagnosed cases, is a complex polygenic disease also modulated by epigenetics and lifestyle factors. For the identification of T2D-associated genes, linkage analyses combined with mouse breeding strategies and bioinformatic tools were useful in the past. In a previous study in which a backcross population of the lean and diabetes-prone dilute brown non-agouti (DBA) mouse and the obese and diabetes-susceptible New Zealand obese (NZO) mouse was characterized, a major diabetes quantitative trait locus (QTL) was identified on chromosome 4. The locus was designated non-insulin dependent diabetes from DBA (Nidd/DBA). The aim of this thesis was (i) to perform a detailed phenotypic characterization of the Nidd/DBA mice, (ii) to further narrow the critical region and (iii) to identify the responsible genetic variant(s) of the Nidd/DBA locus. The phenotypic characterization of recombinant congenic mice carrying a 13.6 Mbp Nidd/DBA fragment with 284 genes presented a gradually worsening metabolic phenotype. Nidd/DBA allele carriers exhibited severe hyperglycemia (~19.9 mM) and impaired glucose clearance at 12 weeks of age. Ex vivo perifusion experiments with islets of 13-week-old congenic mice revealed a tendency towards reduced insulin secretion in homozygous DBA mice. In addition, 16-week-old mice showed a severe loss of β-cells and reduced pancreatic insulin content. Pathway analysis of transcriptome data from islets of congenic mice pointed towards a downregulation of cell survival genes. Morphological analysis of pancreatic sections displayed a reduced number of bi-hormonal cells co-expressing glucagon and insulin in homozygous DBA mice, which could indicate a reduced plasticity of endocrine cells in response to hyperglycemic stress. Further generation and phenotyping of recombinant congenic mice enabled the isolation of a 3.3 Mbp fragment that was still able to induce hyperglycemia and contained 61 genes. Bioinformatic analyses including haplotype mapping, sequence and transcriptome analysis were integrated in order to further reduce the number of candidate genes and to identify the presumable causative gene variant. Four putative candidate genes (Ttc39a, Kti12, Osbpl9, Calr4) were defined, which were either differentially expressed or carried a sequence variant. In addition, in silico ChIP-Seq analyses of the 3.3 Mbp region indicated a high number of SNPs located in active regions of binding sites of β-cell transcription factors. This points towards potentially altered cis-regulatory elements that could be responsible for the phenotype conferred by the Nidd/DBA locus. In summary, the Nidd/DBA locus mediates impaired glucose homeostasis and reduced insulin secretion capacity which finally leads to β-cell death. The downregulation of cell survival genes and reduced plasticity of endocrine cells could further contribute to the β-cell loss. The critical region was narrowed down to a 3.3 Mbp fragment containing 61 genes, of which four might be involved in the development of the diabetogenic Nidd/DBA phenotype.
‘Smart’ Janus emulsions
(2021)
Emulsions constitute one of the most prominent and continuously evolving research areas in Colloid Chemistry, which involves the preparation of mixtures or dispersions of immiscible components in a continuous medium. Besides conventional oil-in-water or water-in-oil emulsions, other emulsions of complex droplet morphologies have recently attracted significant research interests. Especially Janus emulsions, in which each droplet is comprised of two distinct sub-regions, have shown versatile potential applications. One of their advantages is the possibility of compartmentalization, which enables to play with two different chemistries in a single droplet. Though microfluidic methods are conventionally used to prepare Janus emulsions, their industrial applications are largely hindered by low throughput and extensive instrumentations. Recently, it has been discovered that simply one-pot moderate/high energy emulsification is also capable of developing Janus morphology, although their preparation and stabilization remain rather substantially challenging. This cumulative doctoral thesis focuses on the preparation and characterization of ‘smart’ Janus emulsions, i.e. Janus emulsions with special stimuli-responsive features. One-step moderate/high energy emulsification of olive and silicone oil in an aqueous medium was carried out. Special consideration was devoted to the interfacial tensions among the components to maintain the criteria of forming characteristic droplet architectures, in addition to avoiding multiple emulsion destabilization phenomena like imminent phase separation or even separated droplet formation. A series of investigations were conducted related to the formation of complexes of charged macromolecules and role of them as stabilizers to achieve stable Janus emulsions for a realistic timeframe (more than 3 months). The correlation between the size of the stabilizer particles and the droplet size of emulsion was established. Furthermore, it was observed that Janus emulsion gels with interesting rheological properties can be fabricated in the presence of suitable polyelectrolyte complexes. Janus emulsions that could be influenced by pH, temperature or magnetic field were successfully produced in presence of characteristic stimuli-responsive stabilizers. Afterwards, the effect of these changes was studied by different characterization techniques. The size and morphology could be tuned easily by changing the pH. The incorporation of iron oxide magnetic nanoparticles (synthesized separately by a co-precipitation method) to one component of the Janus emulsion was carried out so that the movement and orientation of the complex droplets in aqueous media could be controlled by an external magnetic field. Additionally, temperature-triggered instantaneous reversible breakdown of Janus droplets was also accomplished. The responses of the Janus droplets by the stimuli were well-documented and explained. Another goal of the present contribution was to exploit this special morphological feature of emulsions as a template for producing porous materials. This was demonstrated by the preparation of ultralight magnetic responsive aerogels, utilizing Janus emulsion gels. The produced aerogels also showed the capacity to separate toxic dye from water. To the best of our knowledge, this is the first example of investigation towards batch scale production of Janus emulsion with such special stimuli-responsive properties by a simple bulk emulsification method.
In the light of climate change, rising demands for agricultural products and the intensification and specialization of agricultural systems, ensuring an adequate and reliable supply of food is fundamental for food security. Maintaining diversity and redundancy has been postulated as one generic principle to increase the resilience of agricultural production and other ecosystem services. For example, if one crop fails due to climate instability and extreme events, others can compensate the losses. Crop diversity might be particularly important if different crops show asynchronous production trends. Furthermore, spatial heterogeneity has been suggested to increase stability at larger scales as production losses in some areas can be buffered by surpluses in undisturbed ones. Besides systematically investigating the mechanisms underlying stability, identifying transformative pathways that foster them is important.
In my thesis, I aim at answering the following questions: (i) How does yield stability differ between nations, regions and farms, and what is the effect of crop diversity on yield stability in relation to agricultural inputs, climate heterogeneity, climate instability and time at the national, regional or farm level? (ii) Is asynchrony between crops a better predictor of production stability than crop diversity? (iii) What is the effect of asynchrony between and within crops on stability and how is it related to crop diversity and space, respectively? (iv) What is the state of the art and what are knowledge gaps in exploring resilience and its multidimensionality in ecological and social-ecological systems with agent-based models and what are potential ways forward?
In the first chapter, I provide the theoretical background for the subsequent analyses. I stress the need to better understand the resilience of social-ecological systems and particularly the stability of agricultural production. Moreover, I introduce diversity and spatial heterogeneity as two prominently discussed resilience mechanisms and describe approaches to assess resilience.
In the second chapter, I combined agriculture and climate data at three levels of organization and spatial extents to investigate yield stability patterns and their relation to crop diversity, fertilizer, irrigation, climate heterogeneity and instability and time of nations globally, regions in Europe and farms in Germany using statistical analyses. Yield stability decreased from the national to the farm level. Several nations and regions substantially contributed to larger-scale stability. Crop diversity was positively associated with yield stability across all three levels of organization. This effect was typically more profound at smaller scales and in variable climates. In addition to crop diversity, climate heterogeneity was an important stabilizing mechanism especially at larger scales. These results confirm the stabilizing effect of crop diversity and spatial heterogeneity, yet their importance depends on the scale and agricultural management.
Building on the findings of the second chapter, I deepened in the third chapter my research on the effect of crop diversity at the national level. In particular, I tested if asynchrony between crops, i.e. between the temporal production patterns of different crops, better predicts agricultural production stability than crop diversity. The stabilizing effect of asynchrony was multiple times higher than the effect of crop diversity, i.e. asynchrony is one important property that can explain why a higher diversity supports the stability of national food production. Therefore, strategies to stabilize agricultural production through crop diversification also need to account for the asynchrony of the crops considered.
The previous chapters suggest that both asynchrony between crops and spatial heterogeneity are important stabilizing mechanisms. In the fourth chapter, I therefore aimed at better understanding the relative importance of asynchrony between and within crops, i.e. between the temporal production patterns of different crops and between the temporal production patterns of different cultivation areas of the same crop. Better understanding their relative importance is important to inform agricultural management decisions, but so far this has been hardly assessed. To address this, I used crop production data to study the effect of asynchrony between and within crops on the stability of agricultural production in regions in Germany and nations in Europe. Both asynchrony between and within crops consistently stabilized agricultural production. Adding crops increased asynchrony between crops, yet this effect levelled off after eight crops in regions in Germany and after four crops in nations in Europe. Combining already ten farms within a region led to high asynchrony within crops, indicating distinct production patters, while this effect was weaker when combining multiple regions within a nation. The results suggest, that both mechanisms need to be considered in agricultural management strategies that strive for more resilient farming systems.
The analyses in the foregoing chapters focused at different levels of organization, scales and factors potentially influencing agricultural stability. However, these statistical analyses are restricted by data availability and investigate correlative relationships, thus they cannot provide a mechanistic understanding of the actual processes underlying resilience. In this regard, agent-based models (ABM) are a promising tool. Besides their ability to measure different properties and to integrate multiple situations through extensive manipulation in a fully controlled system, they can capture the emergence of system resilience from individual interactions and feedbacks across different levels of organization. In the fifth chapter, I therefore reviewed the state of the art and potential knowledge gaps in exploring resilience and its multidimensionality in ecological and social-ecological systems with ABMs. Next, I derived recommendations for a more effective use of ABMs in resilience research. The review suggests that the potential of ABMs is not utilized in most models as they typically focus on a single dimension of resilience and are mostly limited to one reference state, disturbance type and scale. Moreover, only few studies explicitly test the ability of different mechanisms to support resilience. To solve real-world problems related to the resilience of complex systems, ABMs need to assess multiple stability properties for different situations and under consideration of the mechanisms that are hypothesized to render a system resilient.
In the sixth chapter, I discuss the major conclusions that can be drawn from the previous chapters. Moreover, I showcase the use of simulation models to identify management strategies to enhance asynchrony and thus stability, and the potential of ABMs to identify pathways to implement such strategies.
The results of my thesis confirm the stabilizing effect of crop diversity, yet its importance depends on the scale, agricultural management and climate. Moreover, strategies to stabilize agricultural production through crop diversification also need to account for the asynchrony of the crops considered. As spatial heterogeneity and particularly asynchrony within crops strongly enhances stability, integrated management approaches are needed that simultaneously address multiple resilience mechanisms at different levels of organization, scales and time horizons. For example, the simulation suggests that only increasing the number of crops at both the pixel and landscape level avoids trade-offs between asynchrony between and within crops. If their potential is better exploited, agent-based models have the capacity to systematically assess resilience and to identify comprehensive pathways towards resilient farming systems.
The co-occurrence of warm spells and droughts can lead to detrimental socio-economic and ecological impacts, largely surpassing the impacts of either warm spells or droughts alone. We quantify changes in the number of compound warm spells and droughts from 1979 to 2018 in the Mediterranean Basin using the ERA5 data set. We analyse two types of compound events: 1) warm season compound events, which are extreme in absolute terms in the warm season from May to October and 2) year-round deseasonalised compound events, which are extreme in relative terms respective to the time of the year. The number of compound events increases significantly and especially warm spells are increasing strongly – with an annual growth rates of 3.9 (3.5) % for warm season (deseasonalised) compound events and 4.6 (4.4) % for warm spells –, whereas for droughts the change is more ambiguous depending on the applied definition. Therefore, the rise in the number of compound events is primarily driven by temperature changes and not the lack of precipitation. The months July and August show the highest increases in warm season compound events, whereas the highest increases of deseasonalised compound events occur in spring and early summer. This increase in deseasonalised compound events can potentially have a significant impact on the functioning of Mediterranean ecosystems as this is the peak phase of ecosystem productivity and a vital phenophase.
The co-occurrence of warm spells and droughts can lead to detrimental socio-economic and ecological impacts, largely surpassing the impacts of either warm spells or droughts alone. We quantify changes in the number of compound warm spells and droughts from 1979 to 2018 in the Mediterranean Basin using the ERA5 data set. We analyse two types of compound events: 1) warm season compound events, which are extreme in absolute terms in the warm season from May to October and 2) year-round deseasonalised compound events, which are extreme in relative terms respective to the time of the year. The number of compound events increases significantly and especially warm spells are increasing strongly – with an annual growth rates of 3.9 (3.5) % for warm season (deseasonalised) compound events and 4.6 (4.4) % for warm spells –, whereas for droughts the change is more ambiguous depending on the applied definition. Therefore, the rise in the number of compound events is primarily driven by temperature changes and not the lack of precipitation. The months July and August show the highest increases in warm season compound events, whereas the highest increases of deseasonalised compound events occur in spring and early summer. This increase in deseasonalised compound events can potentially have a significant impact on the functioning of Mediterranean ecosystems as this is the peak phase of ecosystem productivity and a vital phenophase.
Compound weather events may lead to extreme impacts that can affect many aspects of society including agriculture. Identifying the underlying mechanisms that cause extreme impacts, such as crop failure, is of crucial importance to improve their understanding and forecasting. In this study, we investigate whether key meteorological drivers of extreme impacts can be identified using the least absolute shrinkage and selection operator (LASSO) in a model environment, a method that allows for automated variable selection and is able to handle collinearity between variables. As an example of an extreme impact, we investigate crop failure using annual wheat yield as simulated by the Agricultural Production Systems sIMulator (APSIM) crop model driven by 1600 years of daily weather data from a global climate model (EC-Earth) under present-day conditions for the Northern Hemisphere. We then apply LASSO logistic regression to determine which weather conditions during the growing season lead to crop failure. We obtain good model performance in central Europe and the eastern half of the United States, while crop failure years in regions in Asia and the western half of the United States are less accurately predicted. Model performance correlates strongly with annual mean and variability of crop yields; that is, model performance is highest in regions with relatively large annual crop yield mean and variability. Overall, for nearly all grid points, the inclusion of temperature, precipitation and vapour pressure deficit is key to predict crop failure. In addition, meteorological predictors during all seasons are required for a good prediction. These results illustrate the omnipresence of compounding effects of both meteorological drivers and different periods of the growing season for creating crop failure events. Especially vapour pressure deficit and climate extreme indicators such as diurnal temperature range and the number of frost days are selected by the statistical model as relevant predictors for crop failure at most grid points, underlining their overarching relevance. We conclude that the LASSO regression model is a useful tool to automatically detect compound drivers of extreme impacts and could be applied to other weather impacts such as wildfires or floods. As the detected relationships are of purely correlative nature, more detailed analyses are required to establish the causal structure between drivers and impacts.
Compound weather events may lead to extreme impacts that can affect many aspects of society including agriculture. Identifying the underlying mechanisms that cause extreme impacts, such as crop failure, is of crucial importance to improve their understanding and forecasting. In this study, we investigate whether key meteorological drivers of extreme impacts can be identified using the least absolute shrinkage and selection operator (LASSO) in a model environment, a method that allows for automated variable selection and is able to handle collinearity between variables. As an example of an extreme impact, we investigate crop failure using annual wheat yield as simulated by the Agricultural Production Systems sIMulator (APSIM) crop model driven by 1600 years of daily weather data from a global climate model (EC-Earth) under present-day conditions for the Northern Hemisphere. We then apply LASSO logistic regression to determine which weather conditions during the growing season lead to crop failure. We obtain good model performance in central Europe and the eastern half of the United States, while crop failure years in regions in Asia and the western half of the United States are less accurately predicted. Model performance correlates strongly with annual mean and variability of crop yields; that is, model performance is highest in regions with relatively large annual crop yield mean and variability. Overall, for nearly all grid points, the inclusion of temperature, precipitation and vapour pressure deficit is key to predict crop failure. In addition, meteorological predictors during all seasons are required for a good prediction. These results illustrate the omnipresence of compounding effects of both meteorological drivers and different periods of the growing season for creating crop failure events. Especially vapour pressure deficit and climate extreme indicators such as diurnal temperature range and the number of frost days are selected by the statistical model as relevant predictors for crop failure at most grid points, underlining their overarching relevance. We conclude that the LASSO regression model is a useful tool to automatically detect compound drivers of extreme impacts and could be applied to other weather impacts such as wildfires or floods. As the detected relationships are of purely correlative nature, more detailed analyses are required to establish the causal structure between drivers and impacts.
Flooding is a vast problem in many parts of the world, including Europe. It occurs mainly due to extreme weather conditions (e.g. heavy rainfall and snowmelt) and the consequences of flood events can be devastating. Flood risk is mainly defined as a combination of the probability of an event and its potential adverse impacts. Therefore, it covers three major dynamic components: hazard (physical characteristics of a flood event), exposure (people and their physical environment that being exposed to flood), and vulnerability (the elements at risk). Floods are natural phenomena and cannot be fully prevented. However, their risk can be managed and mitigated. For a sound flood risk management and mitigation, a proper risk assessment is needed. First of all, this is attained by a clear understanding of the flood risk dynamics. For instance, human activity may contribute to an increase in flood risk. Anthropogenic climate change causes higher intensity of rainfall and sea level rise and therefore an increase in scale and frequency of the flood events. On the other hand, inappropriate management of risk and structural protection measures may not be very effective for risk reduction. Additionally, due to the growth of number of assets and people within the flood-prone areas, risk increases. To address these issues, the first objective of this thesis is to perform a sensitivity analysis to understand the impacts of changes in each flood risk component on overall risk and further their mutual interactions. A multitude of changes along the risk chain are simulated by regional flood model (RFM) where all processes from atmosphere through catchment and river system to damage mechanisms are taken into consideration. The impacts of changes in risk components are explored by plausible change scenarios for the mesoscale Mulde catchment (sub-basin of the Elbe) in Germany.
A proper risk assessment is ensured by the reasonable representation of the real-world flood event. Traditionally, flood risk is assessed by assuming homogeneous return periods of flood peaks throughout the considered catchment. However, in reality, flood events are spatially heterogeneous and therefore traditional assumption misestimates flood risk especially for large regions. In this thesis, two different studies investigate the importance of spatial dependence in large scale flood risk assessment for different spatial scales. In the first one, the “real” spatial dependence of return period of flood damages is represented by continuous risk modelling approach where spatially coherent patterns of hydrological and meteorological controls (i.e. soil moisture and weather patterns) are included. Further the risk estimations under this modelled dependence assumption are compared with two other assumptions on the spatial dependence of return periods of flood damages: complete dependence (homogeneous return periods) and independence (randomly generated heterogeneous return periods) for the Elbe catchment in Germany. The second study represents the “real” spatial dependence by multivariate dependence models. Similar to the first study, the three different assumptions on the spatial dependence of return periods of flood damages are compared, but at national (United Kingdom and Germany) and continental (Europe) scales. Furthermore, the impacts of the different models, tail dependence, and the structural flood protection level on the flood risk under different spatial dependence assumptions are investigated.
The outcomes of the sensitivity analysis framework suggest that flood risk can vary dramatically as a result of possible change scenarios. The risk components that have not received much attention (e.g. changes in dike systems and in vulnerability) may mask the influence of climate change that is often investigated component.
The results of the spatial dependence research in this thesis further show that the damage under the false assumption of complete dependence is 100 % larger than the damage under the modelled dependence assumption, for the events with return periods greater than approximately 200 years in the Elbe catchment. The complete dependence assumption overestimates the 200-year flood damage, a benchmark indicator for the insurance industry, by 139 %, 188 % and 246 % for the UK, Germany and Europe, respectively. The misestimation of risk under different assumptions can vary from upstream to downstream of the catchment. Besides, tail dependence in the model and flood protection level in the catchments can affect the risk estimation and the differences between different spatial dependence assumptions.
In conclusion, the broader consideration of the risk components, which possibly affect the flood risk in a comprehensive way, and the consideration of the spatial dependence of flood return periods are strongly recommended for a better understanding of flood risk and consequently for a sound flood risk management and mitigation.
As society paves its way towards device miniaturization and precision medicine, micro-scale actuation and guided transport become increasingly prominent research fields, with high potential impact in both technological and clinical contexts. In order to accomplish directed motion of micron-sized objects, as biosensors and drug-releasing microparticles, towards specific target sites, a promising strategy is the use of living cells as smart biochemically-powered carriers, building the so-called bio-hybrid systems. Inspired by leukocytes, native cells of living organisms efficiently migrating to critical targets as tumor tissue, an emerging concept is to exploit the amoeboid crawling motility of such cells as mean of transport for drug delivery applications.
In the research work described in this thesis, I synergistically applied experimental, computational and theoretical modeling approaches to investigate the behaviour and transport mechanism of a novel kind of bio-hybrid system for active transport at the micro-scale, referred to as cellular truck. This system consists of an amoeboid crawling cell, the carrier, attached to a microparticle, the cargo, which may ideally be drug-loaded for specific therapeutic treatments.
For the purposes of experimental investigation, I employed the amoeba Dictyostelium discoideum as crawling cellular carrier, being a renowned model organism for leukocyte migration and, in general, for eukaryotic cell motility. The performed experiments revealed a complex recurrent cell-cargo relative motion, together with an intermittent motility of the cellular truck as a whole. The evidence suggests the presence of cargoes on amoeboid cells to act as mechanical stimulus leading cell polarization, thus promoting cell motility and giving rise to the observed intermittent dynamics of the truck. Particularly, bursts in cytoskeletal polarity along the cell-cargo axis have been
found to occur in time with a rate dependent on cargo geometrical features, as particle diameter. Overall, the collected experimental evidence pointed out a pivotal role of cell-cargo interactions in the emergent cellular truck motion dynamics. Especially, they can determine the transport capabilities of amoeboid cells, as the cargo size significantly impacts the cytoskeletal activity and repolarization dynamics along the cell-cargo axis, the latter responsible for truck displacement and reorientation.
Furthermore, I developed a modeling framework, built upon the experimental evidence on cellular truck behaviour, that connects the relative dynamics and interactions arising at the truck scale with the actual particle transport dynamics. In fact, numerical simulations of the proposed model successfully reproduced the phenomenology of the cell-cargo system, while enabling the prediction of the transport properties of cellular trucks over larger spatial and temporal scales. The theoretical analysis provided a deeper understanding of the role of cell-cargo interaction on mass transport, unveiling in particular how the long-time transport efficiency is governed by the interplay between the persistence time of cell polarity and time scales of the relative dynamics stemming from cell-cargo interaction. Interestingly, the model predicts the existence of an optimal cargo size, enhancing the diffusivity of cellular trucks; this is in line with previous independent experimental data, which appeared rather counterintuitive and had no explanation prior to this study.
In conclusion, my research work shed light on the importance of cargo-carrier interactions in the context of crawling cell-mediated particle transport, and provides a prototypical, multifaceted framework for the analysis and modelling of such complex bio-hybrid systems and their perspective optimization.
Future Outlook and Scenarios
(2021)
Where is local self-government heading in the future? Among trends identified is firstly an intensification of multilevel, intermunicipal, and cross-border governance. In the future even more of cooperation and coordination among different political and administrative levels will be required. Territorial boundaries have become increasingly incongruent with functional public activities. Secondly, the innovative potential of introducing markets as templates for organisational reform has reached its end. Future reforms will most likely try to adapt market reforms to local public contexts, or even reverse the development. Finally, a tightening of state steering and an increased dependence on state funding to uphold local services is expected. Waves of amalgamations might slow down this process but they will not make financial problems disappear completely.
The digital transformation of the local public sector is an important step towards making local service delivery more citizen-centred and user-oriented. The state of digitalisation in public administration in Germany is, however, well behind the far-reaching hopes associated with this modernisation theme. This chapter will explore the question as to what extent digital tools have been introduced in German local governments, more specifically in local one-stop shops (Bürgerämter), which hurdles local actors face when coping with the digital transformation, and which tools impact on citizens and local employees as well as have unintended effects and dysfunctionalities so far. A comprehensive and standardised survey amongst mayors and heads of staff councils in German municipalities as well as citizens and employees’ surveys and case studies will form the empirical basis of this chapter.
Beyond Charter and Index
(2021)
The Chapter examines the concept of local autonomy in modern European states by analysing theoretical approaches. The classical, deductive approach defines local autonomy mostly through legal, economic and financial conditions, especially by formal structures. This proves to be too weak to define the internal strength of local authorities and their real political-administrative power. A more multidimensional definition of autonomy, including indicators as importance, capacity, as well as discretion and democracy at local level is needed. The authors utilise the indicators, used by the Local Autonomy Index (LAI) developed by Ladner et al. and the European Charter of Local Self-Government to find out what is still missing. The contribution redounds to stimulate the scientific debate on local autonomy in Europe. Until the concept of local autonomy will fit for all European states with extremely differentiated local authorities, the research in this field remains a conceptual and heuristic endeavour. Especially, because local government and democracy are until now territory-based, whereas the reality is one of multilevel and cross-border governance.