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- Institut für Biochemie und Biologie (49)
- Extern (48)
- Strukturbereich Kognitionswissenschaften (34)
- Hasso-Plattner-Institut für Digital Engineering GmbH (30)
- Institut für Physik und Astronomie (30)
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- Fachgruppe Volkswirtschaftslehre (24)
- Center for Economic Policy Analysis (CEPA) (20)
- Institut für Chemie (17)
- Fachgruppe Betriebswirtschaftslehre (14)
Transitional Justice
(2022)
This publication deals with the topic of transitional justice. In six case studies, the authors link theoretical and practical implications in order to develop some innovative approaches. Their proposals might help to deal more effectively with the transition of societies, legal orders and political systems.
Young academics from various backgrounds provide fresh insights and demonstrate the relevance of the topic. The chapters analyse transitions and conflicts in Sierra Leone, Argentina, Nicaragua, Nepal, and South Sudan as well as Germany’s colonial genocide in Namibia. Thus, the book provides the reader with new insights and contributes to the ongoing debate about transitional justice.
Studies from several countries suggest that COVID-19 vaccination rates are lower among migrants compared to the general population. Urgent calls have been made to improve vaccine outreach to migrants, however, there is limited evidence on effective approaches, especially using social media. We assessed a targeted, low-cost, Facebook campaign disseminating COVID-19 vaccine information among Arabic, Turkish and Russian speakers in Germany (N = 888,994). As part of the campaign, we conducted two randomized, online experiments to assess the impact of the advertisement (1) language and (2) depicted messenger (government authority, religious leader, doctor or family). Key outcomes included reach, click-through rates, conversion rates and cost-effectiveness. Within 29 days, the campaign reached 890 thousand Facebook users. On average, 2.3 individuals accessed the advertised COVID-19 vaccination appointment tool for every euro spent on the campaign. Migrants were 2.4 (Arabic), 1.8 (Russian) and 1.2 (Turkish) times more likely to click on advertisements translated to their native language compared to German-language advertisements. Furthermore, findings showed that government representatives can be more successful in engaging migrants online compared to other messengers, despite common claims of lower trust in government institutions among migrants. This study highlights the potential of tailored, and translated, vaccination campaigns on social media for reaching migrants who may be left out by traditional media campaigns.
A decade ago, it became feasible to store multi-terabyte databases in main memory. These in-memory databases (IMDBs) profit from DRAM's low latency and high throughput as well as from the removal of costly abstractions used in disk-based systems, such as the buffer cache. However, as the DRAM technology approaches physical limits, scaling these databases becomes difficult. Non-volatile memory (NVM) addresses this challenge. This new type of memory is persistent, has more capacity than DRAM (4x), and does not suffer from its density-inhibiting limitations. Yet, as NVM has a higher latency (5-15x) and a lower throughput (0.35x), it cannot fully replace DRAM.
IMDBs thus need to navigate the trade-off between the two memory tiers. We present a solution to this optimization problem. Leveraging information about access frequencies and patterns, our solution utilizes NVM's additional capacity while minimizing the associated access costs. Unlike buffer cache-based implementations, our tiering abstraction does not add any costs when reading data from DRAM. As such, it can act as a drop-in replacement for existing IMDBs. Our contributions are as follows:
(1) As the foundation for our research, we present Hyrise, an open-source, columnar IMDB that we re-engineered and re-wrote from scratch. Hyrise enables realistic end-to-end benchmarks of SQL workloads and offers query performance which is competitive with other research and commercial systems. At the same time, Hyrise is easy to understand and modify as repeatedly demonstrated by its uses in research and teaching.
(2) We present a novel memory management framework for different memory and storage tiers. By encapsulating the allocation and access methods of these tiers, we enable existing data structures to be stored on different tiers with no modifications to their implementation. Besides DRAM and NVM, we also support and evaluate SSDs and have made provisions for upcoming technologies such as disaggregated memory.
(3) To identify the parts of the data that can be moved to (s)lower tiers with little performance impact, we present a tracking method that identifies access skew both in the row and column dimensions and that detects patterns within consecutive accesses. Unlike existing methods that have substantial associated costs, our access counters exhibit no identifiable overhead in standard benchmarks despite their increased accuracy.
(4) Finally, we introduce a tiering algorithm that optimizes the data placement for a given memory budget. In the TPC-H benchmark, this allows us to move 90% of the data to NVM while the throughput is reduced by only 10.8% and the query latency is increased by 11.6%. With this, we outperform approaches that ignore the workload's access skew and access patterns and increase the query latency by 20% or more.
Individually, our contributions provide novel approaches to current challenges in systems engineering and database research. Combining them allows IMDBs to scale past the limits of DRAM while continuing to profit from the benefits of in-memory computing.
Subdividing space through interfaces leads to many space partitions that are relevant to soft matter self-assembly. Prominent examples include cellular media, e.g. soap froths, which are bubbles of air separated by interfaces of soap and water, but also more complex partitions such as bicontinuous minimal surfaces.
Using computer simulations, this thesis analyses soft matter systems in terms of the relationship between the physical forces between the system's constituents and the structure of the resulting interfaces or partitions. The focus is on two systems, copolymeric self-assembly and the so-called Quantizer problem, where the driving force of structure formation, the minimisation of the free-energy, is an interplay of surface area minimisation and stretching contributions, favouring cells of uniform thickness.
In the first part of the thesis we address copolymeric phase formation with sharp interfaces. We analyse a columnar copolymer system "forced" to assemble on a spherical surface, where the perfect solution, the hexagonal tiling, is topologically prohibited. For a system of three-armed copolymers, the resulting structure is described by solutions of the so-called Thomson problem, the search of minimal energy configurations of repelling charges on a sphere. We find three intertwined Thomson problem solutions on a single sphere, occurring at a probability depending on the radius of the substrate.
We then investigate the formation of amorphous and crystalline structures in the Quantizer system, a particulate model with an energy functional without surface tension that favours spherical cells of equal size. We find that quasi-static equilibrium cooling allows the Quantizer system to crystallise into a BCC ground state, whereas quenching and non-equilibrium cooling, i.e. cooling at slower rates then quenching, leads to an approximately hyperuniform, amorphous state. The assumed universality of the latter, i.e. independence of energy minimisation method or initial configuration, is strengthened by our results. We expand the Quantizer system by introducing interface tension, creating a model that we find to mimic polymeric micelle systems: An order-disorder phase transition is observed with a stable Frank-Caspar phase.
The second part considers bicontinuous partitions of space into two network-like domains, and introduces an open-source tool for the identification of structures in electron microscopy images. We expand a method of matching experimentally accessible projections with computed projections of potential structures, introduced by Deng and Mieczkowski (1998). The computed structures are modelled using nodal representations of constant-mean-curvature surfaces. A case study conducted on etioplast cell membranes in chloroplast precursors establishes the double Diamond surface structure to be dominant in these plant cells. We automate the matching process employing deep-learning methods, which manage to identify structures with excellent accuracy.
While estimated numbers of past and future climate migrants are alarming, the growing empirical evidence suggests that the association between adverse climate-related events and migration is not universally positive. This dissertation seeks to advance our understanding of when and how climate migration emerges by analyzing heterogeneous climatic influences on migration in low- and middle-income countries. To this end, it draws on established economic theories of migration, datasets from physical and social sciences, causal inference techniques and approaches from systematic literature review. In three of its five chapters, I estimate causal effects of processes of climate change on inequality and migration in India and Sub-Saharan Africa. By employing interaction terms and by analyzing sub-samples of data, I explore how these relationships differ for various segments of the population. In the remaining two chapters, I present two systematic literature reviews. First, I undertake a comprehensive meta-regression analysis of the econometric climate migration literature to summarize general climate migration patterns and explain the conflicting findings. Second, motivated by the broad range of approaches in the field, I examine the literature from a methodological perspective to provide best practice guidelines for studying climate migration empirically. Overall, the evidence from this dissertation shows that climatic influences on human migration are highly heterogeneous. Whether adverse climate-related impacts materialize in migration depends on the socio-economic characteristics of the individual households, such as wealth, level of education, agricultural dependence or access to adaptation technologies and insurance. For instance, I show that while adverse climatic shocks are generally associated with an increase in migration in rural India, they reduce migration in the agricultural context of Sub-Saharan Africa, where the average wealth levels are much lower so that households largely cannot afford the upfront costs of moving. I find that unlike local climatic shocks which primarily enhance internal migration to cities and hence accelerate urbanization, shocks transmitted via agricultural producer prices increase migration to neighboring countries, likely due to the simultaneous decrease in real income in nearby urban areas. These findings advance our current understanding by showing when and how economic agents respond to climatic events, thus providing explicit contexts and mechanisms of climate change effects on migration in the future. The resulting collection of findings can guide policy interventions to avoid or mitigate any present and future welfare losses from climate change-related migration choices.
During his trip to New Spain in 1803, Alexander von Humboldt visited large tracts of New Spanish territory, which includes modern Mexico and part of the United States. This trip provided the data for his geographical Atlas of the region, as well as information about the ancient Mexican cultures that he would later include in the general Atlas and in other major works, such as Vues des Cordillères. Likewise, Humboldt’s Political Essay on the Kingdom of New Spain displayed a comprehensive physical, natural, economic, and social description of Mexico in the colonial period, which will also be analysed. With these works, Humboldt presented a new geographical and cultural image of New Spain to the European audiences. In addition to this, his work made important contributions to cartographic knowledge.
Writing travel, writing life
(2022)
The book compares the texts of three Swiss authors: Ella Maillart, Annemarie Schwarzenbach and Nicolas Bouvier. The focus is on their trip from Genève to Kabul that Ella Maillart and Annemarie Schwarzenbach made together in 1939/1940 and Nicolas Bouvier 1953/1954 with the artist Thierry Vernet. The comparison shows the strong connection between the journey and life and between ars vivendi and travel literature.
This book also gives an overview of and organises the numerous terms, genres, and categories that already exist to describe various travel texts and proposes the new term travelling narration. The travelling narration looks at the text from a narratological perspective that distinguishes the author, narrator, and protagonist within the narration.
In the examination, ten motifs could be found to characterise the travelling narration: Culture, Crossing Borders, Freedom, Time and Space, the Aesthetics of Landscapes, Writing and Reading, the Self and/as the Other, Home, Religion and Spirituality as well as the Journey. The importance of each individual motif does not only apply in the 1930s or 1950s but also transmits important findings for living together today and in the future.
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.
Due to the major role of greenhouse gas emissions in global climate change, the development of non-fossil energy technologies is essential. Deep geothermal energy represents such an alternative, which offers promising properties such as a high base load capability and a large untapped potential. The present work addresses barite precipitation within geothermal systems and the associated reduction in rock permeability, which is a major obstacle to maintaining high efficiency. In this context, hydro-geochemical models are essential to quantify and predict the effects of precipitation on the efficiency of a system.
The objective of the present work is to quantify the induced injectivity loss using numerical and analytical reactive transport simulations. For the calculations, the fractured-porous reservoirs of the German geothermal regions North German Basin (NGB) and Upper Rhine Graben (URG) are considered.
Similar depth-dependent precipitation potentials could be determined for both investigated regions (2.8-20.2 g/m3 fluid). However, the reservoir simulations indicate that the injectivity loss due to barite deposition in the NGB is significant (1.8%-6.4% per year) and the longevity of the system is affected as a result; this is especially true for deeper reservoirs (3000 m). In contrast, simulations of URG sites indicate a minor role of barite (< 0.1%-1.2% injectivity loss per year). The key differences between the investigated regions are reservoir thicknesses and the presence of fractures in the rock, as well as the ionic strength of the fluids. The URG generally has fractured-porous reservoirs with much higher thicknesses, resulting in a greater distribution of precipitates in the subsurface. Furthermore, ionic strengths are higher in the NGB, which accelerates barite precipitation, causing it to occur more concentrated around the wellbore. The more concentrated the precipitates occur around the wellbore, the higher the injectivity loss.
In this work, a workflow was developed within which numerical and analytical models can be used to estimate and quantify the risk of barite precipitation within the reservoir of geothermal systems. A key element is a newly developed analytical scaling score that provides a reliable estimate of induced injectivity loss. The key advantage of the presented approach compared to fully coupled reservoir simulations is its simplicity, which makes it more accessible to plant operators and decision makers. Thus, in particular, the scaling score can find wide application within geothermal energy, e.g., in the search for potential plant sites and the estimation of long-term efficiency.
Climate change is one of the greatest challenges to humanity in this century, and most noticeable consequences are expected to be impacts on the water cycle – in particular the distribution and availability of water, which is fundamental for all life on Earth. In this context, it is essential to better understand where and when water is available and what processes influence variations in water storages. While estimates of the overall terrestrial water storage (TWS) variations are available from the GRACE satellites, these represent the vertically integrated signal over all water stored in ice, snow, soil moisture, groundwater and surface water bodies. Therefore, complementary observational data and hydrological models are still required to determine the partitioning of the measured signal among different water storages and to understand the underlying processes. However, the application of large-scale observational data is limited by their specific uncertainties and the incapacity to measure certain water fluxes and storages. Hydrological models, on the other hand, vary widely in their structure and process-representation, and rarely incorporate additional observational data to minimize uncertainties that arise from their simplified representation of the complex hydrologic cycle.
In this context, this thesis aims to contribute to improving the understanding of global water storage variability by combining simple hydrological models with a variety of complementary Earth observation-based data. To this end, a model-data integration approach is developed, in which the parameters of a parsimonious hydrological model are calibrated against several observational constraints, inducing GRACE TWS, simultaneously, while taking into account each data’s specific strengths and uncertainties. This approach is used to investigate 3 specific aspects that are relevant for modelling and understanding the composition of large-scale TWS variations.
The first study focusses on Northern latitudes, where snow and cold-region processes define the hydrological cycle. While the study confirms previous findings that seasonal dynamics of TWS are dominated by the cyclic accumulation and melt of snow, it reveals that inter-annual TWS variations on the contrary, are determined by variations in liquid water storages. Additionally, it is found to be important to consider the impact of compensatory effects of spatially heterogeneous hydrological variables when aggregating the contribution of different storage components over large areas. Hence, the determinants of TWS variations are scale-dependent and underlying driving mechanism cannot be simply transferred between spatial and temporal scales. These findings are supported by the second study for the global land areas beyond the Northern latitudes as well.
This second study further identifies the considerable impact of how vegetation is represented in hydrological models on the partitioning of TWS variations. Using spatio-temporal varying fields of Earth observation-based data to parameterize vegetation activity not only significantly improves model performance, but also reduces parameter equifinality and process uncertainties. Moreover, the representation of vegetation drastically changes the contribution of different water storages to overall TWS variability, emphasizing the key role of vegetation for water allocation, especially between sub-surface and delayed water storages. However, the study also identifies parameter equifinality regarding the decay of sub-surface and delayed water storages by either evapotranspiration or runoff, and thus emphasizes the need for further constraints hereof.
The third study focuses on the role of river water storage, in particular whether it is necessary to include computationally expensive river routing for model calibration and validation against the integrated GRACE TWS. The results suggest that river routing is not required for model calibration in such a global model-data integration approach, due to the larger influence other observational constraints, and the determinability of certain model parameters and associated processes are identified as issues of greater relevance. In contrast to model calibration, considering river water storage derived from routing schemes can already significantly improve modelled TWS compared to GRACE observations, and thus should be considered for model evaluation against GRACE data.
Beyond these specific findings that contribute to improved understanding and modelling of large-scale TWS variations, this thesis demonstrates the potential of combining simple modeling approaches with diverse Earth observational data to improve model simulations, overcome inconsistencies of different observational data sets, and identify areas that require further research. These findings encourage future efforts to take advantage of the increasing number of diverse global observational data.
Sustainable urban growth
(2022)
This dissertation explores the determinants for sustainable and socially optimalgrowth in a city. Two general equilibrium models establish the base for this evaluation, each adding its puzzle piece to the urban sustainability discourse and examining the role of non-market-based and market-based policies for balanced growth and welfare improvements in different theory settings. Sustainable urban growth either calls for policy actions or a green energy transition. Further, R&D market failures can pose severe challenges to the sustainability of urban growth and the social optimality of decentralized allocation decisions. Still, a careful (holistic) combination of policy instruments can achieve sustainable growth and even be first best.
The motivation for this work was the question of reliability and robustness of seismic tomography. The problem is that many earth models exist which can describe the underlying ground motion records equally well. Most algorithms for reconstructing earth models provide a solution, but rarely quantify their variability. If there is no way to verify the imaged structures, an interpretation is hardly reliable. The initial idea was to explore the space of equivalent earth models using Bayesian inference. However, it quickly became apparent that the rigorous quantification of tomographic uncertainties could not be accomplished within the scope of a dissertation.
In order to maintain the fundamental concept of statistical inference, less complex problems from the geosciences are treated instead. This dissertation aims to anchor Bayesian inference more deeply in the geosciences and to transfer knowledge from applied mathematics. The underlying idea is to use well-known methods and techniques from statistics to quantify the uncertainties of inverse problems in the geosciences. This work is divided into three parts:
Part I introduces the necessary mathematics and should be understood as a kind of toolbox. With a physical application in mind, this section provides a compact summary of all methods and techniques used. The introduction of Bayesian inference makes the beginning. Then, as a special case, the focus is on regression with Gaussian processes under linear transformations. The chapters on the derivation of covariance functions and the approximation of non-linearities are discussed in more detail.
Part II presents two proof of concept studies in the field of seismology. The aim is to present the conceptual application of the introduced methods and techniques with moderate complexity. The example about traveltime tomography applies the approximation of non-linear relationships. The derivation of a covariance function using the wave equation is shown in the example of a damped vibrating string. With these two synthetic applications, a consistent concept for the quantification of modeling uncertainties has been developed.
Part III presents the reconstruction of the Earth's archeomagnetic field. This application uses the whole toolbox presented in Part I and is correspondingly complex. The modeling of the past 1000 years is based on real data and reliably quantifies the spatial modeling uncertainties. The statistical model presented is widely used and is under active development.
The three applications mentioned are intentionally kept flexible to allow transferability to similar problems. The entire work focuses on the non-uniqueness of inverse problems in the geosciences. It is intended to be of relevance to those interested in the concepts of Bayesian inference.
Plate tectonics describes the movement of rigid plates at the surface of the Earth as well as their complex deformation at three types of plate boundaries: 1) divergent boundaries such as rift zones and mid-ocean ridges, 2) strike-slip boundaries where plates grind past each other, such as the San Andreas Fault, and 3) convergent boundaries that form large mountain ranges like the Andes. The generally narrow deformation zones that bound the plates exhibit complex strain patterns that evolve through time. During this evolution, plate boundary deformation is driven by tectonic forces arising from Earth’s deep interior and from within the lithosphere, but also by surface processes, which erode topographic highs and deposit the resulting sediment into regions of low elevation. Through the combination of these factors, the surface of the Earth evolves in a highly dynamic way with several feedback mechanisms. At divergent boundaries, for example, tensional stresses thin the lithosphere, forcing uplift and subsequent erosion of rift flanks, which creates a sediment source. Meanwhile, the rift center subsides and becomes a topographic low where sediments accumulate. This mass transfer from foot- to hanging wall plays an important role during rifting, as it prolongs the activity of individual normal faults. When rifting continues, continents are eventually split apart, exhuming Earth’s mantle and creating new oceanic crust. Because of the complex interplay between deep tectonic forces that shape plate boundaries and mass redistribution at the Earth’s surface, it is vital to understand feedbacks between the two domains and how they shape our planet.
In this study I aim to provide insight on two primary questions: 1) How do divergent and strike-slip plate boundaries evolve? 2) How is this evolution, on a large temporal scale and a smaller structural scale, affected by the alteration of the surface through erosion and deposition? This is done in three chapters that examine the evolution of divergent and strike-slip plate boundaries using numerical models. Chapter 2 takes a detailed look at the evolution of rift systems using two-dimensional models. Specifically, I extract faults from a range of rift models and correlate them through time to examine how fault networks evolve in space and time. By implementing a two-way coupling between the geodynamic code ASPECT and landscape evolution code FastScape, I investigate how the fault network and rift evolution are influenced by the system’s erosional efficiency, which represents many factors like lithology or climate. In Chapter 3, I examine rift evolution from a three-dimensional perspective. In this chapter I study linkage modes for offset rifts to determine when fast-rotating plate-boundary structures known as continental microplates form. Chapter 4 uses the two-way numerical coupling between tectonics and landscape evolution to investigate how a strike-slip boundary responds to large sediment loads, and whether this is sufficient to form an entirely new type of flexural strike-slip basin.
This study explores the identity of the Bene Israel caste from India and its assimilation into Israeli society. The large immigration from India to Israel started in the early 1950s and continued until the early 1970s. Initially, these immigrants struggled hard as they faced many problems such as the language barrier, cultural differences, a new climate, geographical isolation, and racial discrimination. This analysis focuses on the three major aspects of the integration process involving the Bene Israel: economic, socio-cultural and political. The study covers the period from the early fifties to the present.
I will focus on the origin of the Bene Israel, which has evolved after their immigration to Israel; from a Hindu–Muslim lifestyle and customs they integrated into the Jewish life of Israel. Despite its ethnographic nature, this study has theological implications as it is an encounter between Jewish monotheism and Indian polytheism.
All the western scholars who researched the Bene Israel community felt impelled to rely on information received by community members themselves. No written historical evidence recorded Bene Israel culture and origin. Only during the nineteenth century onwards, after the intrusion of western Jewish missionaries, were Jewish books translated into Marathi . Missionary activities among the Bene Israel served as a catalyst for the Bene Israel themselves to investigate their historical past . Haeem Samuel Kehimkar (1830-1908), a Bene Israel teacher, wrote notes on the history of the Bene Israel in India in Marathi in 1897. Brenda Ness wrote in her dissertation:
The results [of the missionary activities] are several works about the community in English and Marathi by Bene-Israel authors which have appeared during the last century. These are, for the most part, not documented; they consist of much theorizing on accepted tradition and tend to be apologetic in nature.
There can be no philosophical explanation or rational justification for an entire community to leave their motherland India, and enter into a process of annihilation of its own free will. I see this as a social and cultural suicide. In craving for a better future in Israel, the Indian Bene Israel community pays an enormously heavy price as a people that are today discarded by the East and disowned by the West: because they chose to become something that they never were and never could be. As it is written, “know where you came from, and where you are going.” A community with an ancient history from a spiritual culture has completely lost its identity and self-esteem.
In concluding this dissertation, I realize the dilemma with which I have confronted the members of the Bene Israel community which I have reviewed after strenuous and constant self-examination. I chose to evolve the diversifications of the younger generations urges towards acceptance, and wish to clarify my intricate analysis of this controversial community. The complexity of living in a Jewish State, where citizens cannot fulfill their basic desires, like matrimony, forced an entire community to conceal their true identity and perjure themselves to blend in, for the sake of national integration. Although scholars accepted their new claims, the skepticism of the rabbinate authorities prevails, and they refuse to marry them to this day, suspecting they are an Indian caste.
In the present thesis I investigate the lattice dynamics of thin film hetero structures of magnetically ordered materials upon femtosecond laser excitation as a probing and manipulation scheme for the spin system. The quantitative assessment of laser induced thermal dynamics as well as generated picosecond acoustic pulses and their respective impact on the magnetization dynamics of thin films is a challenging endeavor. All the more, the development and implementation of effective experimental tools and comprehensive models are paramount to propel future academic and technological progress.
In all experiments in the scope of this cumulative dissertation, I examine the crystal lattice of nanoscale thin films upon the excitation with femtosecond laser pulses. The relative change of the lattice constant due to thermal expansion or picosecond strain pulses is directly monitored by an ultrafast X-ray diffraction (UXRD) setup with a femtosecond laser-driven plasma X-ray source (PXS). Phonons and spins alike exert stress on the lattice, which responds according to the elastic properties of the material, rendering the lattice a versatile sensor for all sorts of ultrafast interactions. On the one hand, I investigate materials with strong magneto-elastic properties; The highly magnetostrictive rare-earth compound TbFe2, elemental Dysprosium or the technological relevant Invar material FePt. On the other hand I conduct a comprehensive study on the lattice dynamics of Bi1Y2Fe5O12 (Bi:YIG), which exhibits high-frequency coherent spin dynamics upon femtosecond laser excitation according to the literature. Higher order standing spinwaves (SSWs) are triggered by coherent and incoherent motion of atoms, in other words phonons, which I quantified with UXRD. We are able to unite the experimental observations of the lattice and magnetization dynamics qualitatively and quantitatively. This is done with a combination of multi-temperature, elastic, magneto-elastic, anisotropy and micro-magnetic modeling.
The collective data from UXRD, to probe the lattice, and time-resolved magneto-optical Kerr effect (tr-MOKE) measurements, to monitor the magnetization, were previously collected at different experimental setups. To improve the precision of the quantitative assessment of lattice and magnetization dynamics alike, our group implemented a combination of UXRD and tr-MOKE in a singular experimental setup, which is to my knowledge, the first of its kind. I helped with the conception and commissioning of this novel experimental station, which allows the simultaneous observation of lattice and magnetization dynamics on an ultrafast timescale under identical excitation conditions. Furthermore, I developed a new X-ray diffraction measurement routine which significantly reduces the measurement time of UXRD experiments by up to an order of magnitude. It is called reciprocal space slicing (RSS) and utilizes an area detector to monitor the angular motion of X-ray diffraction peaks, which is associated with lattice constant changes, without a time-consuming scan of the diffraction angles with the goniometer. RSS is particularly useful for ultrafast diffraction experiments, since measurement time at large scale facilities like synchrotrons and free electron lasers is a scarce and expensive resource. However, RSS is not limited to ultrafast experiments and can even be extended to other diffraction techniques with neutrons or electrons.
In this thesis, I present my contributions to the field of ultrafast molecular spectroscopy. Using the molecule 2-thiouracil as an example, I use ultrashort x-ray pulses from free- electron lasers to study the relaxation dynamics of gas-phase molecular samples. Taking advantage of the x-ray typical element- and site-selectivity, I investigate the charge flow and geometrical changes in the excited states of 2-thiouracil.
In order to understand the photoinduced dynamics of molecules, knowledge about the ground-state structure and the relaxation after photoexcitation is crucial. Therefore, a part of this thesis covers the electronic ground-state spectroscopy of mainly 2-thiouracil to provide the basis for the time-resolved experiments. Many of the previously published studies that focused on the gas-phase time-resolved dynamics of thionated uracils after UV excitation relied on information from solution phase spectroscopy to determine the excitation energies. This is not an optimal strategy as solvents alter the absorption spec- trum and, hence, there is no guarantee that liquid-phase spectra resemble the gas-phase spectra. Therefore, I measured the UV-absorption spectra of all three thionated uracils to provide a gas-phase reference and, in combination with calculations, we determined the excited states involved in the transitions.
In contrast to the UV absorption, the literature on the x-ray spectroscopy of thionated uracil is sparse. Thus, we measured static photoelectron, Auger-Meitner and x-ray absorption spectra on the sulfur L edge before or parallel to the time-resolved experiments we performed at FLASH (DESY, Hamburg). In addition, (so far unpublished) measurements were performed at the synchrotron SOLEIL (France) which have been included in this thesis and show the spin-orbit splitting of the S 2p photoline and its satellite which was not observed at the free-electron laser.
The relaxation of 2-thiouracil has been studied extensively in recent years with ultrafast visible and ultraviolet methods showing the ultrafast nature of the molecular process after photoexcitation. Ultrafast spectroscopy probing the core-level electrons provides a complementary approach to common optical ultrafast techniques. The method inherits its local sensitivity from the strongly localised core electrons. The core energies and core-valence transitions are strongly affected by local valence charge and geometry changes, and past studies have utilised this sensitivity to investigate the molecular process reflected by the ultrafast dynamics. We have built an apparatus that provides the requirements to perform time-resolved x-ray spectroscopy on molecules in the gas phase. With the apparatus, we performed UV-pump x-ray-probe electron spectroscopy on the S 2p edge of 2-thiouracil using the free-electron laser FLASH2. While the UV triggers the relaxation dynamics, the x-ray probes the single sulfur atom inside the molecule. I implemented photoline self-referencing for the photoelectron spectral analysis. This minimises the spectral jitter of the FEL, which is due to the underlying self-amplified spontaneous emission (SASE) process. With this approach, we were not only able to study dynamical changes in the binding energy of the electrons but also to detect an oscillatory behaviour in the shift of the observed photoline, which we associate with non-adiabatic dynamics involving several electronic states. Moreover, we were able to link the UV-induced shift in binding energy to the local charge flow at the sulfur which is directly connected to the electronic state. Furthermore, the analysis of the Auger-Meitner electrons shows that energy shifts observed at early stages of the photoinduced relaxation are related to the geometry change in the molecule. More specifically, the observed increase in kinetic energy of the Auger-Meitner electrons correlates with a previously predicted C=S bond stretch.
One aspect of achieving a more sustainable chemical industry is the minimization of the usage of solvents and chemicals. Thus, optimization and development of chemical processes for large-scale production is favourably performed in small batches. The critical step in this approach is upscaling the batches from the small reaction systems to the large reactors mandatory for cost efficient production in an industrial environment. Scaling up the bulk volume always goes along with increasing the surface where the reaction medium is in contact with the confining vessel. Since volume scales proportional with the cubic dimension while the surface scales quadratic, their ratio is size-dependent. The influence of reaction vessel walls can change the reaction performance. A number of phenomena occurring at the surface-liquid interface can affect reaction rates and yields, resulting in possible difficulties in predicting and extrapolating from small size production scale to large industrial processes. The application of levitated droplets as a containerless reaction vessels provides a promising possibility to avoid the above-mentioned issues.
In the presented work, an efficient coupling of acoustically levitated droplets to an ion mobility (IM) spectrometer, operating at ambient conditions, was designed for real-time monitoring of chemical reactions. The design of the system comprises noncontact sampling and ionization of the droplet realised by laser desorption/ionization at 2,94 µm. The scope of the work includes fundamental studies covering understanding of laser irradiation of droplets enclosed in an acoustical field. Understanding of this phenomenon is crucial to comprehending the effects of temporal and spatial resolution of the generated ion plume that influence the resolution of the system.
The set-up includes an acoustic trap, laser irradiation and ion manipulation electrostatic lenses operating at high voltage at ambient pressure. The complexity of the design needs to fully be considered for an effective ion transfer at the interface region between the levitated droplet and IM spectrometer. For sampling and ionization, two distinct laser pulse lengths were evaluated, ns and µs. Irradiation via µs laser pulses provides several advantages: i) the droplet volume is not extensively impinged, as in case of ns laser pulses, allowing the sampling of only the small volume of the droplet; ii) the lower fluence results in less pronounced oscillations of the droplet confined in the acoustic field. The droplet will not be dissipated out of the acoustic field leading to loss of the sample; iii) the mild laser irradiation results in better spatial and temporal ion plume confinement, leading to better resolution of the detected ion packets. Finally, this knowledge allows the application of ion optics necessary to induce ion flow between the droplet suspended in the acoustic field and the IM spectrometer. The ion optics, composed of 2 electrostatic lenses placed in the near vicinity of the droplet, allow effective focusing of the ion plume and its redirection directly to the IM spectrometer entrance. This novel coupling has proved to be successful for detection of some simple molecules ionizable at the 2.94 µm wavelength. To further demonstrate the applicability of the system, a proof-of-principle reaction was selected, fulfilling the requirements of the system, and was subjected to comprehensive investigation of its performance. Herein, the reaction between N-Boc cysteine methyl ester and allyl alcohol has been performed in a batch reactor and on-line monitored via 1H NMR to establish reaction propagation. With the additional assessment, it was confirmed that the thiol-ene coupling can be performed within first 20 minutes of the irradiation with a reaction yield above 50%, proving that the reaction can be applied as a study case to assess the possibilities of the developed system.
Digital transformation (DT) has not only been a major challenge in recent years, it is also supposed to continue to enormously impact our society and economy in the forthcoming decade. On the one hand, digital technologies have emerged, diffusing and determining our private and professional lives. On the other hand, digital platforms have leveraged the potentials of digital technologies to provide new business models. These dynamics have a massive effect on individuals, companies, and entire ecosystems. Digital technologies and platforms have changed the way persons consume or interact with each other. Moreover, they offer companies new opportunities to conduct their business in terms of value creation (e.g., business processes), value proposition (e.g., business models), or customer interaction (e.g., communication channels), i.e., the three dimensions of DT. However, they also can become a threat for a company's competitiveness or even survival. Eventually, the emergence, diffusion, and employment of digital technologies and platforms bear the potential to transform entire markets and ecosystems.
Against this background, IS research has explored and theorized the phenomena in the context of DT in the past decade, but not to its full extent. This is not surprising, given the complexity and pervasiveness of DT, which still requires far more research to further understand DT with its interdependencies in its entirety and in greater detail, particularly through the IS perspective at the confluence of technology, economy, and society. Consequently, the IS research discipline has determined and emphasized several relevant research gaps for exploring and understanding DT, including empirical data, theories as well as knowledge of the dynamic and transformative capabilities of digital technologies and platforms for both organizations and entire industries.
Hence, this thesis aims to address these research gaps on the IS research agenda and consists of two streams. The first stream of this thesis includes four papers that investigate the impact of digital technologies on organizations. In particular, these papers study the effects of new technologies on firms (paper II.1) and their innovative capabilities (II.2), the nature and characteristics of data-driven business models (II.3), and current developments in research and practice regarding on-demand healthcare (II.4). Consequently, the papers provide novel insights on the dynamic capabilities of digital technologies along the three dimensions of DT. Furthermore, they offer companies some opportunities to systematically explore, employ, and evaluate digital technologies to modify or redesign their organizations or business models.
The second stream comprises three papers that explore and theorize the impact of digital platforms on traditional companies, markets, and the economy and society at large. At this, paper III.1 examines the implications for the business of traditional insurance companies through the emergence and diffusion of multi-sided platforms, particularly in terms of value creation, value proposition, and customer interaction. Paper III.2 approaches the platform impact more holistically and investigates how the ongoing digital transformation and "platformization" in healthcare lastingly transform value creation in the healthcare market. Paper III.3 moves on from the level of single businesses or markets to the regulatory problems that result from the platform economy for economy and society, and proposes appropriate regulatory approaches for addressing these problems. Hence, these papers bring new insights on the table about the transformative capabilities of digital platforms for incumbent companies in particular and entire ecosystems in general.
Altogether, this thesis contributes to the understanding of the impact of DT on organizations and markets through the conduction of multiple-case study analyses that are systematically reflected with the current state of the art in research. On this empirical basis, the thesis also provides conceptual models, taxonomies, and frameworks that help describing, explaining, or predicting the impact of digital technologies and digital platforms on companies, markets and the economy or society at large from an interdisciplinary viewpoint.
Accurately solving classification problems nowadays is likely to be the most relevant machine learning task. Binary classification separating two classes only is algorithmically simpler but has fewer potential applications as many real-world problems are multi-class. On the reverse, separating only a subset of classes simplifies the classification task. Even though existing multi-class machine learning algorithms are very flexible regarding the number of classes, they assume that the target set Y is fixed and cannot be restricted once the training is finished. On the other hand, existing state-of-the-art production environments are becoming increasingly interconnected with the advance of Industry 4.0 and related technologies such that additional information can simplify the respective classification problems. In light of this, the main aim of this thesis is to introduce dynamic classification that generalizes multi-class classification such that the target class set can be restricted arbitrarily to a non-empty class subset M of Y at any time between two consecutive predictions.
This task is solved by a combination of two algorithmic approaches. First, classifier calibration, which transforms predictions into posterior probability estimates that are intended to be well calibrated. The analysis provided focuses on monotonic calibration and in particular corrects wrong statements that appeared in the literature. It also reveals that bin-based evaluation metrics, which became popular in recent years, are unjustified and should not be used at all. Next, the validity of Platt scaling, which is the most relevant parametric calibration approach, is analyzed in depth. In particular, its optimality for classifier predictions distributed according to four different families of probability distributions as well its equivalence with Beta calibration up to a sigmoidal preprocessing are proven. For non-monotonic calibration, extended variants on kernel density estimation and the ensemble method EKDE are introduced. Finally, the calibration techniques are evaluated using a simulation study with complete information as well as on a selection of 46 real-world data sets.
Building on this, classifier calibration is applied as part of decomposition-based classification that aims to reduce multi-class problems to simpler (usually binary) prediction tasks. For the involved fusing step performed at prediction time, a new approach based on evidence theory is presented that uses classifier calibration to model mass functions. This allows the analysis of decomposition-based classification against a strictly formal background and to prove closed-form equations for the overall combinations. Furthermore, the same formalism leads to a consistent integration of dynamic class information, yielding a theoretically justified and computationally tractable dynamic classification model. The insights gained from this modeling are combined with pairwise coupling, which is one of the most relevant reduction-based classification approaches, such that all individual predictions are combined with a weight. This not only generalizes existing works on pairwise coupling but also enables the integration of dynamic class information.
Lastly, a thorough empirical study is performed that compares all newly introduced approaches to existing state-of-the-art techniques. For this, evaluation metrics for dynamic classification are introduced that depend on corresponding sampling strategies. Thereafter, these are applied during a three-part evaluation. First, support vector machines and random forests are applied on 26 data sets from the UCI Machine Learning Repository. Second, two state-of-the-art deep neural networks are evaluated on five benchmark data sets from a relatively recent reference work. Here, computationally feasible strategies to apply the presented algorithms in combination with large-scale models are particularly relevant because a naive application is computationally intractable. Finally, reference data from a real-world process allowing the inclusion of dynamic class information are collected and evaluated. The results show that in combination with support vector machines and random forests, pairwise coupling approaches yield the best results, while in combination with deep neural networks, differences between the different approaches are mostly small to negligible. Most importantly, all results empirically confirm that dynamic classification succeeds in improving the respective prediction accuracies. Therefore, it is crucial to pass dynamic class information in respective applications, which requires an appropriate digital infrastructure.
Enhanced geothermal systems (EGS) are considered a cornerstone of future sustainable energy production. In such systems, high-pressure fluid injections break the rock to provide pathways for water to circulate in and heat up. This approach inherently induces small seismic events that, in rare cases, are felt or can even cause damage. Controlling and reducing the seismic impact of EGS is crucial for a broader public acceptance. To evaluate the applicability of hydraulic fracturing (HF) in EGS and to improve the understanding of fracturing processes and the hydromechanical relation to induced seismicity, six in-situ, meter-scale HF experiments with different injection schemes were performed under controlled conditions in crystalline rock in a depth of 410 m at the Äspö Hard Rock Laboratory (Sweden).
I developed a semi-automated, full-waveform-based detection, classification, and location workflow to extract and characterize the acoustic emission (AE) activity from the continuous recordings of 11 piezoelectric AE sensors. Based on the resulting catalog of 20,000 AEs, with rupture sizes of cm to dm, I mapped and characterized the fracture growth in great detail. The injection using a novel cyclic injection scheme (HF3) had a lower seismic impact than the conventional injections. HF3 induced fewer AEs with a reduced maximum magnitude and significantly larger b-values, implying a decreased number of large events relative to the number of small ones. Furthermore, HF3 showed an increased fracture complexity with multiple fractures or a fracture network. In contrast, the conventional injections developed single, planar fracture zones (Publication 1).
An independent, complementary approach based on a comparison of modeled and observed tilt exploits transient long-period signals recorded at the horizontal components of two broad-band seismometers a few tens of meters apart from the injections. It validated the efficient creation of hydraulic fractures and verified the AE-based fracture geometries. The innovative joint analysis of AEs and tilt signals revealed different phases of the fracturing process, including the (re-)opening, growth, and aftergrowth of fractures, and provided evidence for the reactivation of a preexisting fault in one of the experiments (Publication 2). A newly developed network-based waveform-similarity analysis applied to the massive AE activity supports the latter finding.
To validate whether the reduction of the seismic impact as observed for the cyclic injection schemes during the Äspö mine-scale experiments is transferable to other scales, I additionally calculated energy budgets for injection experiments from previously conducted laboratory tests and from a field application. Across all three scales, the cyclic injections reduce the seismic impact, as depicted by smaller maximum magnitudes, larger b-values, and decreased injection efficiencies (Publication 3).
The echo chamber model describes the development of groups in heterogeneous social networks. By heterogeneous social network we mean a set of individuals, each of whom represents exactly one opinion. The existing relationships between individuals can then be represented by a graph. The echo chamber model is a time-discrete model which, like a board game, is played in rounds. In each round, an existing relationship is randomly and uniformly selected from the network and the two connected individuals interact. If the opinions of the individuals involved are sufficiently similar, they continue to move closer together in their opinions, whereas in the case of opinions that are too far apart, they break off their relationship and one of the individuals seeks a new relationship. In this paper we examine the building blocks of this model. We start from the observation that changes in the structure of relationships in the network can be described by a system of interacting particles in a more abstract space.
These reflections lead to the definition of a new abstract graph that encompasses all possible relational configurations of the social network. This provides us with the geometric understanding necessary to analyse the dynamic components of the echo chamber model in Part III. As a first step, in Part 7, we leave aside the opinions of the inidividuals and assume that the position of the edges changes with each move as described above, in order to obtain a basic understanding of the underlying dynamics. Using Markov chain theory, we find upper bounds on the speed of convergence of an associated Markov chain to its unique stationary distribution and show that there are mutually identifiable networks that are not apparent in the dynamics under analysis, in the sense that the stationary distribution of the associated Markov chain gives equal weight to these networks.
In the reversible cases, we focus in particular on the explicit form of the stationary distribution as well as on the lower bounds of the Cheeger constant to describe the convergence speed.
The final result of Section 8, based on absorbing Markov chains, shows that in a reduced version of the echo chamber model, a hierarchical structure of the number of conflicting relations can be identified.
We can use this structure to determine an upper bound on the expected absorption time, using a quasi-stationary distribution. This hierarchy of structure also provides a bridge to classical theories of pure death processes. We conclude by showing how future research can exploit this link and by discussing the importance of the results as building blocks for a full theoretical understanding of the echo chamber model. Finally, Part IV presents a published paper on the birth-death process with partial catastrophe. The paper is based on the explicit calculation of the first moment of a catastrophe. This first part is entirely based on an analytical approach to second degree recurrences with linear coefficients. The convergence to 0 of the resulting sequence as well as the speed of convergence are proved. On the other hand, the determination of the upper bounds of the expected value of the population size as well as its variance and the difference between the determined upper bound and the actual value of the expected value. For these results we use almost exclusively the theory of ordinary nonlinear differential equations.
The increasing introduction of non-native plant species may pose a threat to local biodiversity. However, the basis of successful plant invasion is not conclusively understood, especially since these plant species can adapt to the new range within a short period of time despite impoverished genetic diversity of the starting populations. In this context, DNA methylation is considered promising to explain successful adaptation mechanisms in the new habitat. DNA methylation is a heritable variation in gene expression without changing the underlying genetic information. Thus, DNA methylation is considered a so-called epigenetic mechanism, but has been studied in mainly clonally reproducing plant species or genetic model plants. An understanding of this epigenetic mechanism in the context of non-native, predominantly sexually reproducing plant species might help to expand knowledge in biodiversity research on the interaction between plants and their habitats and, based on this, may enable more precise measures in conservation biology.
For my studies, I combined chemical DNA demethylation of field-collected seed material from predominantly sexually reproducing species and rearing offsping under common climatic conditions to examine DNA methylation in an ecological-evolutionary context. The contrast of chemically treated (demethylated) plants, whose variation in DNA methylation was artificially reduced, and untreated control plants of the same species allowed me to study the impact of this mechanism on adaptive trait differentiation and local adaptation. With this experimental background, I conducted three studies examining the effect of DNA methylation in non-native species along a climatic gradient and also between climatically divergent regions.
The first study focused on adaptive trait differentiation in two invasive perennial goldenrod species, Solidago canadensis sensu latu and S. gigantea AITON, along a climate gradient of more than 1000 km in length in Central Europe. I found population differences in flowering timing, plant height, and biomass in the temporally longer-established S. canadensis, but only in the number of regrowing shoots for S. gigantea. While S. canadensis did not show any population structure, I was able to identify three genetic groups along this climatic gradient in S. gigantea. Surprisingly, demethylated plants of both species showed no change in the majority of traits studied. In the subsequent second study, I focused on the longer-established goldenrod species S. canadensis and used molecular analyses to infer spatial epigenetic and genetic population differences in the same specimens from the previous study. I found weak genetic but no epigenetic spatial variation between populations. Additionally, I was able to identify one genetic marker and one epigenetic marker putatively susceptible to selection. However, the results of this study reconfirmed that the epigenetic mechanism of DNA methylation appears to be hardly involved in adaptive processes within the new range in S. canadensis.
Finally, I conducted a third study in which I reciprocally transplanted short-lived plant species between two climatically divergent regions in Germany to investigate local adaptation at the plant family level. For this purpose, I used four plant families (Amaranthaceae, Asteraceae, Plantaginaceae, Solanaceae) and here I additionally compared between non-native and native plant species. Seeds were transplanted to regions with a distance of more than 600 kilometers and had either a temperate-oceanic or a temperate-continental climate. In this study, some species were found to be maladapted to their own local conditions, both in non-native and native plant species alike. In demethylated individuals of the plant species studied, DNA methylation had inconsistent but species-specific effects on survival and biomass production. The results of this study highlight that DNA methylation did not make a substantial contribution to local adaptation in the non-native as well as native species studied.
In summary, my work showed that DNA methylation plays a negligible role in both adaptive trait variation along climatic gradients and local adaptation in non-native plant species that either exhibit a high degree of genetic variation or rely mainly on sexual reproduction with low clonal propagation. I was able to show that the adaptive success of these non-native plant species can hardly be explained by DNA methylation, but could be a possible consequence of multiple introductions, dispersal corridors and meta-population dynamics. Similarly, my results illustrate that the use of plant species that do not predominantly reproduce clonally and are not model plants is essential to characterize the effect size of epigenetic mechanisms in an ecological-evolutionary context.
Objective
To improve consumer decision making, the results of risk assessments on food, feed, consumer products or chemicals need to be communicated not only to experts but also to non-expert audiences. The present study draws on evidence from literature reviews and focus groups with diverse stakeholders to identify content to integrate into an existing risk assessment communication (Risk Profile).
Methods
A combination of rapid literature reviews and focus groups with experts (risk assessors (n = 15), risk managers (n = 8)), and non-experts (general public (n = 18)) were used to identify content and strategies for including information about risk assessment results in the “Risk Profile” from the German Federal Institute for Risk Assessment. Feedback from initial focus groups was used to develop communication prototypes that informed subsequent feedback rounds in an iterative process. A final prototype was validated in usability tests with experts.
Results
Focus group feedback and suggestions from risk assessors were largely in line with findings from the literature. Risk managers and lay persons offered similar suggestions on how to improve the existing communication of risk assessment results (e.g., including more explanatory detail, reporting probabilities for individual health impairments, and specifying risks for subgroups in additional sections). Risk managers found information about quality of evidence important to communicate, whereas people from the general public found this information less relevant. Participants from lower educational backgrounds had difficulties understanding the purpose of risk assessments. User tests found that the final prototype was appropriate and feasible to implement by risk assessors.
Conclusion
An iterative and evidence-based process was used to develop content to improve the communication of risk assessments to the general public while being feasible to use by risk assessors. Remaining challenges include how to communicate dose-response relationships and standardise quality of evidence ratings across disciplines.
Successful communication is often explored by people throughout their life courses. To effectively transfer one’s own information to others, people employ various linguistic tools, such as word order information, prosodic cues, and lexical choices. The exploration of these linguistic cues is known as the study of information structure (IS). Moreover, an important issue in the language acquisition of children is the investigation of how they acquire IS. This thesis seeks to improve our understanding of how children acquire different tools (i.e., prosodical cues, syntactical cues, and the focus particle only) of focus marking in a cross linguistic perspective.
In the first study, following Szendrői and her colleagues (2017)- the sentence-picture verification task- was performed to investigate whether three- to five-year-old Mandarin-speaking children as well as Mandarin-speaking adults could apply prosodic information to recognize focus in sentences. More, in the second study, not only Mandarin-speaking adults and Mandarin-speaking children but also German-speaking adults and German-speaking children were included to confirm the assumption that children could have adult-like performance in understanding sentence focus by identifying language specific cues in their mother tongue from early onwards. In this study, the same paradigm- the sentence-picture verification task- as in the first study was employed together with the eye-tracking method. Finally, in the last study, an issue of whether five-year-old Mandarin-speaking children could understand the pre-subject only sentence was carried out and again whether prosodic information would help them to better understand this kind of sentences.
The overall results seem to suggest that Mandarin-speaking children from early onwards could make use of the specific linguistic cues in their ambient language. That is, in Mandarin, a Topic-prominent and tone language, the word order information plays a more important rule than the prosodic information and even three-year-old Mandarin-speaking children could follow the word order information. More, although it seems that German-speaking children could follow the prosodic information, they did not have the adult-like performance in the object-accented condition. A feasible reason for this result is that there are more possibilities of marking focus in German, such as flexible word order, prosodic information, focus particles, and thus it would take longer time for German-speaking children to manage these linguistic tools. Another important empirical finding regarding the syntactically-marked focus in German is that it seems that the cleft construction is not a valid focus construction and this result corroborates with the previous observations (Dufter, 2009). Further, eye-tracking method did help to uncover how the parser direct their attention for recognizing focus. In the final study, it is showed that with explicit verbal context Mandarin-speaking children could understand the pre-subject only sentence and the study brought a better understanding of the acquisition of the focus particle- only with the Mandarin-speaking children.
Different lake systems might reflect different climate elements of climate changes, while the responses of lake systems are also divers, and are not completely understood so far. Therefore, a comparison of lakes in different climate zones, during the high-amplitude and abrupt climate fluctuations of the Last Glacial to Holocene transition provides an exceptional opportunity to investigate distinct natural lake system responses to different abrupt climate changes. The aim of this doctoral thesis was to reconstruct climatic and environmental fluctuations down to (sub-) annual resolution from two different lake systems during the Last Glacial-Interglacial transition (~17 and 11 ka). Lake Gościąż, situated in the temperate central Poland, developed in the Allerød after recession of the Last Glacial ice sheets. The Dead Sea is located in the Levant (eastern Mediterranean) within a steep gradient from sub-humid to hyper-arid climate, and formed in the mid-Miocene. Despite their differences in sedimentation processes, both lakes form annual laminations (varves), which are crucial for studies of abrupt climate fluctuations. This doctoral thesis was carried out within the DFG project PALEX-II (Paleohydrology and Extreme Floods from the Dead Sea ICDP Core) that investigates extreme hydro-meteorological events in the ICDP core in relation to climate changes, and ICLEA (Virtual Institute of Integrated Climate and Landscape Evolution Analyses) that intends to better the understanding of climate dynamics and landscape evolutions in north-central Europe since the Last Glacial. Further, it contributes to the Helmholtz Climate Initiative REKLIM (Regional Climate Change and Humans) Research Theme 3 “Extreme events across temporal and spatial scales” that investigates extreme events using climate data, paleo-records and model-based simulations. The three main aims were to (1) establish robust chronologies of the lakes, (2) investigate how major and abrupt climate changes affect the lake systems, and (3) to compare the responses of the two varved lakes to these hemispheric-scale climate changes.
Robust chronologies are a prerequisite for high-resolved climate and environmental reconstructions, as well as for archive comparisons. Thus, addressing the first aim, the novel chronology of Lake Gościąż was established by microscopic varve counting and Bayesian age-depth modelling in Bacon for a non-varved section, and was corroborated by independent age constrains from 137Cs activity concentration measurements, AMS radiocarbon dating and pollen analysis. The varve chronology reaches from the late Allerød until AD 2015, revealing more Holocene varves than a previous study of Lake Gościąż suggested. Varve formation throughout the complete Younger Dryas (YD) even allowed the identification of annually- to decadal-resolved leads and lags in proxy responses at the YD transitions.
The lateglacial chronology of the Dead Sea (DS) was thus far mainly based on radiocarbon and U/Th-dating. In the unique ICDP core from the deep lake centre, continuous search for cryptotephra has been carried out in lateglacial sediments between two prominent gypsum deposits – the Upper and Additional Gypsum Units (UGU and AGU, respectively). Two cryptotephras were identified with glass analyses that correlate with tephra deposits from the Süphan and Nemrut volcanoes indicating that the AGU is ~1000 years younger than previously assumed, shifting it into the YD, and the underlying varved interval into the Bølling/Allerød, contradicting previous assumptions.
Using microfacies analyses, stable isotopes and temperature reconstructions, the second aim was achieved at Lake Gościąż. The YD lake system was dynamic, characterized by higher aquatic bioproductivity, more re-suspended material and less anoxia than during the Allerød and Early Holocene, mainly influenced by stronger water circulation and catchment erosion due to stronger westerly winds and less lake sheltering. Cooling at the YD onset was ~100 years longer than the final warming, while environmental proxies lagged the onset of cooling by ~90 years, but occurred contemporaneously during the termination of the YD. Chironomid-based temperature reconstructions support recent studies indicating mild YD summer temperatures. Such a comparison of annually-resolved proxy responses to both abrupt YD transitions is rare, because most European lake archives do not preserve varves during the YD.
To accomplish the second aim at the DS, microfacies analyses were performed between the UGU (~17 ka) and Holocene onset (~11 ka) in shallow- (Masada) and deep-water (ICDP core) environments. This time interval is marked by a huge but fluctuating lake level drop and therefore the complete transition into the Holocene is only recorded in the deep-basin ICDP core. In this thesis, this transition was investigated for the first time continuously and in detail. The final two pronounced lake level drops recorded by deposition of the UGU and AGU, were interrupted by one millennium of relative depositional stability and a positive water budget as recorded by aragonite varve deposition interrupted by only a few event layers. Further, intercalation of aragonite varves between the gypsum beds of the UGU and AGU shows that these generally dry intervals were also marked by decadal- to centennial-long rises in lake level. While continuous aragonite varves indicate decadal-long stable phases, the occurrence of thicker and more frequent event layers suggests general more instability during the gypsum units. These results suggest a pattern of complex and variable hydroclimate at different time scales during the Lateglacial at the DS.
The third aim was accomplished based on the individual studies above that jointly provide an integrated picture of different lake responses to different climate elements of hemispheric-scale abrupt climate changes during the Last Glacial-Interglacial transition. In general, climatically-driven facies changes are more dramatic in the DS than at Lake Gościąż. Further, Lake Gościąż is characterized by continuous varve formation nearly throughout the complete profile, whereas the DS record is widely characterized by extreme event layers, hampering the establishment of a continuous varve chronology. The lateglacial sedimentation in Lake Gościąż is mainly influenced by westerly winds and minor by changes in catchment vegetation, whereas the DS is primarily influenced by changes in winter precipitation, which are caused by temperature variations in the Mediterranean. Interestingly, sedimentation in both archives is more stable during the Bølling/Allerød and more dynamic during the YD, even when sedimentation processes are different.
In summary, this doctoral thesis presents seasonally-resolved records from two lake archives during the Lateglacial (ca 17-11 ka) to investigate the impact of abrupt climate changes in different lake systems. New age constrains from the identification of volcanic glass shards in the lateglacial sediments of the DS allowed the first lithology-based interpretation of the YD in the DS record and its comparison to Lake Gościąż. This highlights the importance of the construction of a robust chronology, and provides a first step for synchronization of the DS with other eastern Mediterranean archives. Further, climate reconstructions from the lake sediments showed variability on different time scales in the different archives, i.e. decadal- to millennial fluctuations in the lateglacial DS, and even annual variations and sub-decadal leads and lags in proxy responses during the rapid YD transitions in Lake Gościąż. This showed the importance of a comparison of different lake archives to better understand the regional and local impacts of hemispheric-scale climate variability. An unprecedented example is demonstrated here of how different lake systems show different lake responses and also react to different climate elements of abrupt climate changes. This further highlights the importance of the understanding of the respective lake system for climate reconstructions.
The heterogeneity of today's state-of-the-art computer architectures is confronting application developers with an immense degree of complexity which results from two major challenges. First, developers need to acquire profound knowledge about the programming models or the interaction models associated with each type of heterogeneous system resource to make efficient use thereof. Second, developers must take into account that heterogeneous system resources always need to exchange data with each other in order to work on a problem together. However, this data exchange is always associated with a certain amount of overhead, which is why the amounts of data exchanged should be kept as low as possible.
This thesis proposes three programming abstractions to lessen the burdens imposed by these major challenges with the goal of making heterogeneous system resources accessible to a wider range of application developers. The lib842 compression library provides the first method for accessing the compression and decompression facilities of the NX-842 on-chip compression accelerator available in IBM Power CPUs from user space applications running on Linux. Addressing application development of scale-out GPU workloads, the CloudCL framework makes the resources of GPU clusters more accessible by hiding many aspects of distributed computing while enabling application developers to focus on the aspects of the data parallel programming model associated with GPUs. Furthermore, CloudCL is augmented with transparent data compression facilities based on the lib842 library in order to improve the efficiency of data transfers among cluster nodes. The improved data transfer efficiency provided by the integration of transparent data compression yields performance improvements ranging between 1.11x and 2.07x across four data-intensive scale-out GPU workloads. To investigate the impact of programming abstractions for data placement in NUMA systems, a comprehensive evaluation of the PGASUS framework for NUMA-aware C++ application development is conducted. On a wide range of test systems, the evaluation demonstrates that PGASUS does not only improve the developer experience across all workloads, but that it is also capable of outperforming NUMA-agnostic implementations with average performance improvements of 1.56x.
Based on these programming abstractions, this thesis demonstrates that by providing a sufficient degree of abstraction, the accessibility of heterogeneous system resources can be improved for application developers without occluding performance-critical properties of the underlying hardware.
Hunting Down Animal Verbs
(2022)
Language change is an essential feature of human language, and it is therefore one of the focal areas of the scientific study of language. Language change is always tacitly at work in all languages of the world and at all levels of a given language, be it phonology, morphology, syntax, semantics, etc. It has been suggested that it is precisely the capacity to constantly change and adjust that allows language to keep serving the communicative goals of its users, from ancient to modern times (Fauconnier & Turner, 2003, p. 179).
This thesis investigates an especially salient pattern of lexicogrammatical change, namely word-formation of verbs from animal nouns by zero-derivation, in the process of which such nouns as, for example, dog, horse, or beaver change their usage and meaning to produce animal verbs: to dog ‘to follow someone persistently and with a malicious intent’, to horse about/around ‘to make fun of, to ‘rag’, to ridicule someone’ and to beaver away ‘to work at working with great enthusiasm’ respectively. In the previous literature this pattern of language change has been termed verbal zoosemy (e.g. Kiełtyka, 2016), i.e. metaphorical construal of human actions by means of linguistic material from the domain of animals.
The approach taken in this study is not to simply report on the objective changes in the morphology, syntactic distribution and meaning of such linguistic units before and after conversion, but to uncover the complexity of cognitive mechanisms which allow the speakers of English to reclassify such well-established nominal units as animal noun into verbs. It is assumed that the grammatical change in these lexical units is predicated on and triggered by preceding semantic change. Thus, the study is set in the framework of Cognitive Historical Semantics and employs the Conceptual Metaphor and Metonymy Theory (CMMT) to untangle the intricacies of the semantic change making the grammatical change of animal nouns into verbs possible and acceptable in the minds of English speakers.
To this end, this study employed the Oxford English Dictionary Online (OED Online) to compile a glossary of 96 denominal animal verbal forms tied to 209 verbal senses (most verbs in the dataset displayed polysemy). The data collected from the OED Online included not only the senses of the verbs, but also the date of the earliest recorded use of the verbal form with the given sense (regarded in the study as the date of conversion), the earliest usage examples for individual senses and morphologically or semantically related linguistic units from the lexical field of the respective parent noun which were amenable to explaining the observed instances of semantic change. Each instance of zoosemisation, i.e. of the creation of a separate metaphorical verbal sense, was then carefully analysed on the basis of the data collected and classified with the help of the CMMT. In the final stage, a comprehensive and systematic classification of the senses of animal verbs in accordance with the cognitive mechanisms of their creation (metaphor, metonymy, or a combination thereof) was produced together with a timeline of the first appearance of individual metaphorical senses of animal verbs recorded in the OED.
The results show that animal verbs are produced through the interaction of conceptual metaphor and metonymy. Specifically, it was established that two major patterns of metaphor-metonymy interaction underpinning the process of verbal zoosemisation are metaphor from metonymy and metonymy from metaphor. In the former pattern, either an already existing metonymic animal verb is expanded to include the target domain PEOPLE, or the animal noun itself acts as a metonymic vehicle to a certain element of the idealised cognitive model of the given animal, which is metaphorically projected onto people. In the latter mechanism, a metaphorical projection of an animal term initially enters the lexicon in the form of a metaphorical animal noun referring to a human entity, and later in the course of language development it comes to metonymically stand for the action, which the given entity either performs or is involved in. Secondarily, it was observed that individual animal nouns can undergo multiple rounds of zoosemic conversion over time depending on the semantic frame in which the given linguistic unit undergoes denominal conversion, and that results in the polysemy of most animal verbs.
Botulinum neurotoxin (BoNT) is used for the treatment of a number of ailments. The activity of the toxin that is isolated from bacterial cultures is frequently tested in the mouse lethality assay. Apart from the ethical concerns inherent to this assay, species-specific differences in the affinity for different BoNT serotypes give rise to activity results that differ from the activity in humans. Thus, BoNT/B is more active in mice than in humans. The current study shows that the stimulus-dependent release of a luciferase from a differentiated human neuroblastoma–based reporter cell line (SIMA-hPOMC1-26-Gluc) was inhibited by clostridial and recombinant BoNT/A to the same extent, whereas both clostridial and recombinant BoNT/B inhibited the release to a lesser extent and only at much higher concentrations, reflecting the low activity of BoNT/B in humans. By contrast, the genetically modified BoNT/B-MY, which has increased affinity for human synaptotagmin, and the BoNT/B protein receptor inhibited luciferase release effectively and with an EC50 comparable to recombinant BoNT/A. This was due to an enhanced uptake into the reporter cells of BoNT/B-MY in comparison to the recombinant wild-type toxin. Thus, the SIMA-hPOMC1-26-Gluc cell assay is a versatile tool to determine the activity of different BoNT serotypes providing human-relevant dose-response data.
A task-based parallel elliptic solver for numerical relativity with discontinuous Galerkin methods
(2022)
Elliptic partial differential equations are ubiquitous in physics. In numerical relativity---the study of computational solutions to the Einstein field equations of general relativity---elliptic equations govern the initial data that seed every simulation of merging black holes and neutron stars. In the quest to produce detailed numerical simulations of these most cataclysmic astrophysical events in our Universe, numerical relativists resort to the vast computing power offered by current and future supercomputers. To leverage these computational resources, numerical codes for the time evolution of general-relativistic initial value problems are being developed with a renewed focus on parallelization and computational efficiency. Their capability to solve elliptic problems for accurate initial data must keep pace with the increasing detail of the simulations, but elliptic problems are traditionally hard to parallelize effectively.
In this thesis, I develop new numerical methods to solve elliptic partial differential equations on computing clusters, with a focus on initial data for orbiting black holes and neutron stars. I develop a discontinuous Galerkin scheme for a wide range of elliptic equations, and a stack of task-based parallel algorithms for their iterative solution. The resulting multigrid-Schwarz preconditioned Newton-Krylov elliptic solver proves capable of parallelizing over 200 million degrees of freedom to at least a few thousand cores, and already solves initial data for a black hole binary about ten times faster than the numerical relativity code SpEC. I also demonstrate the applicability of the new elliptic solver across physical disciplines, simulating the thermal noise in thin mirror coatings of interferometric gravitational-wave detectors to unprecedented accuracy. The elliptic solver is implemented in the new open-source SpECTRE numerical relativity code, and set up to support simulations of astrophysical scenarios for the emerging era of gravitational-wave and multimessenger astronomy.
We present the first systematic literature review on stress and burnout in K−12 teachers during the COVID-19 pandemic. Based on a systematic literature search, we identified 17 studies that included 9,874 K−12 teachers from around the world. These studies showed some indication that burnout did increase during the COVID-19 pandemic. There were, however, almost no differences in the levels of stress and burnout experienced by K−12 teachers compared to individuals employed in other occupational fields. School principals' leadership styles emerged as an organizational characteristic that is highly relevant for K−12 teachers' levels of stress and burnout. Individual teacher characteristics associated with burnout were K−12 teachers' personality, self-efficacy in online teaching, and perceived vulnerability to COVID-19. In order to reduce stress, there was an indication that stress-management training in combination with training in technology use for teaching may be superior to stress-management training alone. Future research needs to adopt more longitudinal designs and examine the interplay between individual and organizational characteristics in the development of teacher stress and burnout during the COVID-19 pandemic and beyond.
The Role of the Precuneus in Human Spatial Updating in a Real Environment Setting—A cTBS Study
(2022)
As we move through an environment, we update positions of our body relative to other objects, even when some objects temporarily or permanently leave our field of view—this ability is termed egocentric spatial updating and plays an important role in everyday life. Still, our knowledge about its representation in the brain is still scarce, with previous studies using virtual movements in virtual environments or patients with brain lesions suggesting that the precuneus might play an important role. However, whether this assumption is also true when healthy humans move in real environments where full body-based cues are available in addition to the visual cues typically used in many VR studies is unclear. Therefore, in this study we investigated the role of the precuneus in egocentric spatial updating in a real environment setting in 20 healthy young participants who underwent two conditions in a cross-over design: (a) stimulation, achieved through applying continuous theta-burst stimulation (cTBS) to inhibit the precuneus and (b) sham condition (activated coil turned upside down). In both conditions, participants had to walk back with blindfolded eyes to objects they had previously memorized while walking with open eyes. Simplified trials (without spatial updating) were used as control condition, to make sure the participants were not affected by factors such as walking blindfolded, vestibular or working memory deficits. A significant interaction was found, with participants performing better in the sham condition compared to real stimulation, showing smaller errors both in distance and angle. The results of our study reveal evidence of an important role of the precuneus in a real-environment egocentric spatial updating; studies on larger samples are necessary to confirm and further investigate this finding.
The geomagnetic main field is vital for live on Earth, as it shields our habitat against the solar wind and cosmic rays. It is generated by the geodynamo in the Earth’s outer core and has a rich dynamic on various timescales. Global models of the field are used to study the interaction of the field and incoming charged particles, but also to infer core dynamics and to feed numerical simulations of the geodynamo. Modern satellite missions, such as the SWARM or the CHAMP mission, support high resolution reconstructions of the global field. From the 19 th century on, a global network of magnetic observatories has been established. It is growing ever since and global models can be constructed from the data it provides. Geomagnetic field models that extend further back in time rely on indirect observations of the field, i.e. thermoremanent records such as burnt clay or volcanic rocks and sediment records from lakes and seas. These indirect records come with (partially very large) uncertainties, introduced by the complex measurement methods and the dating procedure.
Focusing on thermoremanent records only, the aim of this thesis is the development of a new modeling strategy for the global geomagnetic field during the Holocene, which takes the uncertainties into account and produces realistic estimates of the reliability of the model. This aim is approached by first considering snapshot models, in order to address the irregular spatial distribution of the records and the non-linear relation of the indirect observations to the field itself. In a Bayesian setting, a modeling algorithm based on Gaussian process regression is developed and applied to binned data. The modeling algorithm is then extended to the temporal domain and expanded to incorporate dating uncertainties. Finally, the algorithm is sequentialized to deal with numerical challenges arising from the size of the Holocene dataset.
The central result of this thesis, including all of the aspects mentioned, is a new global geomagnetic field model. It covers the whole Holocene, back until 12000 BCE, and we call it ArchKalmag14k. When considering the uncertainties that are produced together with the model, it is evident that before 6000 BCE the thermoremanent database is not sufficient to support global models. For times more recent, ArchKalmag14k can be used to analyze features of the field under consideration of posterior uncertainties. The algorithm for generating ArchKalmag14k can be applied to different datasets and is provided to the community as an open source python package.
Text collections, such as corpora of books, research articles, news, or business documents are an important resource for knowledge discovery. Exploring large document collections by hand is a cumbersome but necessary task to gain new insights and find relevant information. Our digitised society allows us to utilise algorithms to support the information seeking process, for example with the help of retrieval or recommender systems. However, these systems only provide selective views of the data and require some prior knowledge to issue meaningful queries and asses a system’s response. The advancements of machine learning allow us to reduce this gap and better assist the information seeking process. For example, instead of sighting countless business documents by hand, journalists and investigator scan employ natural language processing techniques, such as named entity recognition. Al-though this greatly improves the capabilities of a data exploration platform, the wealth of information is still overwhelming. An overview of the entirety of a dataset in the form of a two-dimensional map-like visualisation may help to circumvent this issue. Such overviews enable novel interaction paradigms for users, which are similar to the exploration of digital geographical maps. In particular, they can provide valuable context by indicating how apiece of information fits into the bigger picture.This thesis proposes algorithms that appropriately pre-process heterogeneous documents and compute the layout for datasets of all kinds. Traditionally, given high-dimensional semantic representations of the data, so-called dimensionality reduction algorithms are usedto compute a layout of the data on a two-dimensional canvas. In this thesis, we focus on text corpora and go beyond only projecting the inherent semantic structure itself. Therefore,we propose three dimensionality reduction approaches that incorporate additional information into the layout process: (1) a multi-objective dimensionality reduction algorithm to jointly visualise semantic information with inherent network information derived from the underlying data; (2) a comparison of initialisation strategies for different dimensionality reduction algorithms to generate a series of layouts for corpora that grow and evolve overtime; (3) and an algorithm that updates existing layouts by incorporating user feedback provided by pointwise drag-and-drop edits. This thesis also contains system prototypes to demonstrate the proposed technologies, including pre-processing and layout of the data and presentation in interactive user interfaces.
It is estimated that data scientists spend up to 80% of the time exploring, cleaning, and transforming their data. A major reason for that expenditure is the lack of knowledge about the used data, which are often from different sources and have heterogeneous structures. As a means to describe various properties of data, metadata can help data scientists understand and prepare their data, saving time for innovative and valuable data analytics. However, metadata do not always exist: some data file formats are not capable of storing them; metadata were deleted for privacy concerns; legacy data may have been produced by systems that were not designed to store and handle meta- data. As data are being produced at an unprecedentedly fast pace and stored in diverse formats, manually creating metadata is not only impractical but also error-prone, demanding automatic approaches for metadata detection.
In this thesis, we are focused on detecting metadata in CSV files – a type of plain-text file that, similar to spreadsheets, may contain different types of content at arbitrary positions. We propose a taxonomy of metadata in CSV files and specifically address the discovery of three different metadata: line and cell type, aggregations, and primary keys and foreign keys.
Data are organized in an ad-hoc manner in CSV files, and do not follow a fixed structure, which is assumed by common data processing tools. Detecting the structure of such files is a prerequisite of extracting information from them, which can be addressed by detecting the semantic type, such as header, data, derived, or footnote, of each line or each cell. We propose the supervised- learning approach Strudel to detect the type of lines and cells. CSV files may also include aggregations. An aggregation represents the arithmetic relationship between a numeric cell and a set of other numeric cells. Our proposed AggreCol algorithm is capable of detecting aggregations of five arithmetic functions in CSV files. Note that stylistic features, such as font style and cell background color, do not exist in CSV files. Our proposed algorithms address the respective problems by using only content, contextual, and computational features.
Storing a relational table is also a common usage of CSV files. Primary keys and foreign keys are important metadata for relational databases, which are usually not present for database instances dumped as plain-text files. We propose the HoPF algorithm to holistically detect both constraints in relational databases. Our approach is capable of distinguishing true primary and foreign keys from a great amount of spurious unique column combinations and inclusion dependencies, which can be detected by state-of-the-art data profiling algorithms.
Biological invasions may result from multiple introductions, which might compensate for reduced gene pools caused by bottleneck events, but could also dilute adaptive processes. A previous common-garden experiment showed heritable latitudinal clines in fitness-related traits in the invasive goldenrod Solidago canadensis in Central Europe. These latitudinal clines remained stable even in plants chemically treated with zebularine to reduce epigenetic variation. However, despite the heritability of traits investigated, genetic isolation-by-distance was non-significant. Utilizing the same specimens, we applied a molecular analysis of (epi)genetic differentiation with standard and methylation-sensitive (MSAP) AFLPs. We tested whether this variation was spatially structured among populations and whether zebularine had altered epigenetic variation. Additionally, we used genome scans to mine for putative outlier loci susceptible to selection processes in the invaded range. Despite the absence of isolation-by-distance, we found spatial genetic neighborhoods among populations and two AFLP clusters differentiating northern and southern Solidago populations. Genetic and epigenetic diversity were significantly correlated, but not linked to phenotypic variation. Hence, no spatial epigenetic patterns were detected along the latitudinal gradient sampled. Applying genome-scan approaches (BAYESCAN, BAYESCENV, RDA, and LFMM), we found 51 genetic and epigenetic loci putatively responding to selection. One of these genetic loci was significantly more frequent in populations at the northern range. Also, one epigenetic locus was more frequent in populations in the southern range, but this pattern was lost under zebularine treatment. Our results point to some genetic, but not epigenetic adaptation processes along a large-scale latitudinal gradient of S. canadensis in its invasive range.
“Broadcast your gender.”
(2022)
Social media platforms provide a large array of behavioral data relevant to social scientific research. However, key information such as sociodemographic characteristics of agents are often missing. This paper aims to compare four methods of classifying social attributes from text. Specifically, we are interested in estimating the gender of German social media creators. By using the example of a random sample of 200 YouTube channels, we compare several classification methods, namely (1) a survey among university staff, (2) a name dictionary method with the World Gender Name Dictionary as a reference list, (3) an algorithmic approach using the website gender-api.com, and (4) a Multinomial Naïve Bayes (MNB) machine learning technique. These different methods identify gender attributes based on YouTube channel names and descriptions in German but are adaptable to other languages. Our contribution will evaluate the share of identifiable channels, accuracy and meaningfulness of classification, as well as limits and benefits of each approach. We aim to address methodological challenges connected to classifying gender attributes for YouTube channels as well as related to reinforcing stereotypes and ethical implications.
Intelligence, as well as working memory and attention, affect the acquisition of mathematical competencies. This paper aimed to examine the influence of working memory and attention when taking different mathematical skills into account as a function of children’s intellectual ability. Overall, intelligence, working memory, attention and numerical skills were assessed twice in 1868 German pre-school children (t1, t2) and again at 2nd grade (t3). We defined three intellectual ability groups based on the results of intellectual assessment at t1 and t2. Group comparisons revealed significant differences between the three intellectual ability groups. Over time, children with low intellectual ability showed the lowest achievement in domain-general and numerical and mathematical skills compared to children of average intellectual ability. The highest achievement on the aforementioned variables was found for children of high intellectual ability. Additionally, path modelling revealed that, depending on the intellectual ability, different models of varying complexity could be generated. These models differed with regard to the relevance of the predictors (t2) and the future mathematical skills (t3). Causes and conclusions of these findings are discussed.
In order to improve a recently established cell-based assay to assess the potency of botulinum neurotoxin, neuroblastoma-derived SiMa cells and induced pluripotent stem-cells (iPSC) were modified to incorporate the coding sequence of a reporter luciferase into a genetic safe harbor utilizing CRISPR/Cas9. A novel method, the double-control quantitative copy number PCR (dc-qcnPCR), was developed to detect off-target integrations of donor DNA. The donor DNA insertion success rate and targeted insertion success rate were analyzed in clones of each cell type. The dc-qcnPCR reliably quantified the copy number in both cell lines. The probability of incorrect donor DNA integration was significantly increased in SiMa cells in comparison to the iPSCs. This can possibly be explained by the lower bundled relative gene expression of a number of double-strand repair genes (BRCA1, DNA2, EXO1, MCPH1, MRE11, and RAD51) in SiMa clones than in iPSC clones. The dc-qcnPCR offers an efficient and cost-effective method to detect off-target CRISPR/Cas9-induced donor DNA integrations.
Background: As the number of cardiac diseases continuously increases within the last years in modern society, so does cardiac treatment, especially cardiac catheterization. The procedure of a cardiac catheterization is challenging for both patients and practitioners. Several potential stressors of psychological or physical nature can occur during the procedure. The objective of the study is to develop and implement a stress management intervention for both practitioners and patients that aims to reduce the psychological and physical strain of a cardiac catheterization.
Methods: The clinical study (DRKS00026624) includes two randomized controlled intervention trials with parallel groups, for patients with elective cardiac catheterization and practitioners at the catheterization lab, in two clinic sites of the Ernst-von-Bergmann clinic network in Brandenburg, Germany. Both groups received different interventions for stress management. The intervention for patients comprises a psychoeducational video with different stress management technics and additional a standardized medical information about the cardiac catheterization examination. The control condition includes the in hospitals practiced medical patient education before the examination (usual care). Primary and secondary outcomes are measured by physiological parameters and validated questionnaires, the day before (M1) and after (M2) the cardiac catheterization and at a postal follow-up 6 months later (M3). It is expected that people with standardized information and psychoeducation show reduced complications during cardiac catheterization procedures, better pre- and post-operative wellbeing, regeneration, mood and lower stress levels over time. The intervention for practitioners includes a Mindfulness-based stress reduction program (MBSR) over 8 weeks supervised by an experienced MBSR practitioner directly at the clinic site and an operative guideline. It is expected that practitioners with intervention show improved perceived and chronic stress, occupational health, physical and mental function, higher effort-reward balance, regeneration and quality of life. Primary and secondary outcomes are measured by physiological parameters (heart rate variability, saliva cortisol) and validated questionnaires and will be assessed before (M1) and after (M2) the MBSR intervention and at a postal follow-up 6 months later (M3). Physiological biomarkers in practitioners will be assessed before (M1) and after intervention (M2) on two work days and a two days off. Intervention effects in both groups (practitioners and patients) will be evaluated separately using multivariate variance analysis.
Discussion: This study evaluates the effectiveness of two stress management intervention programs for patients and practitioners within cardiac catheter laboratory. Study will disclose strains during a cardiac catheterization affecting both patients and practitioners. For practitioners it may contribute to improved working conditions and occupational safety, preservation of earning capacity, avoidance of participation restrictions and loss of performance. In both groups less anxiety, stress and complications before and during the procedures can be expected. The study may add knowledge how to eliminate stressful exposures and to contribute to more (psychological) security, less output losses and exhaustion during work. The evolved stress management guidelines, training manuals and the standardized patient education should be transferred into clinical routines
Cutting-edge hyperscanning methods led to a paradigm shift in social neuroscience. It allowed researchers to measure dynamic mutual alignment of neural processes between two or more individuals in naturalistic contexts. The ever-growing interest in hyperscanning research calls for the development of transparent and validated data analysis methods to further advance the field. We have developed and tested a dual electroencephalography (EEG) analysis pipeline, namely DEEP. Following the preprocessing of the data, DEEP allows users to calculate Phase Locking Values (PLVs) and cross-frequency PLVs as indices of inter-brain phase alignment of dyads as well as time-frequency responses and EEG power for each participant. The pipeline also includes scripts to control for spurious correlations. Our goal is to contribute to open and reproducible science practices by making DEEP publicly available together with an example mother-infant EEG hyperscanning dataset.
Biofilms are complex living materials that form as bacteria get embedded in a matrix of self-produced protein and polysaccharide fibres. The formation of a network of extracellular biopolymer fibres contributes to the cohesion of the biofilm by promoting cell-cell attachment and by mediating biofilm-substrate interactions. This sessile mode of bacteria growth has been well studied by microbiologists to prevent the detrimental effects of biofilms in medical and industrial settings. Indeed, biofilms are associated with increased antibiotic resistance in bacterial infections, and they can also cause clogging of pipelines or promote bio-corrosion. However, biofilms also gained interest from biophysics due to their ability to form complex morphological patterns during growth. Recently, the emerging field of engineered living materials investigates biofilm mechanical properties at multiple length scales and leverages the tools of synthetic biology to tune the functions of their constitutive biopolymers.
This doctoral thesis aims at clarifying how the morphogenesis of Escherichia coli (E. coli) biofilms is influenced by their growth dynamics and mechanical properties. To address this question, I used methods from cell mechanics and materials science. I first studied how biological activity in biofilms gives rise to non-uniform growth patterns. In a second study, I investigated how E. coli biofilm morphogenesis and its mechanical properties adapt to an environmental stimulus, namely the water content of their substrate. Finally, I estimated how the mechanical properties of E. coli biofilms are altered when the bacteria express different extracellular biopolymers.
On nutritive hydrogels, micron-sized E. coli cells can build centimetre-large biofilms. During this process, bacterial proliferation and matrix production introduce mechanical stresses in the biofilm, which release through the formation of macroscopic wrinkles and delaminated buckles. To relate these biological and mechanical phenomena, I used time-lapse fluorescence imaging to track cell and matrix surface densities through the early and late stages of E. coli biofilm growth. Colocalization of high cell and matrix densities at the periphery precede the onset of mechanical instabilities at this annular region. Early growth is detected at this outer annulus, which was analysed by adding fluorescent microspheres to the bacterial inoculum. But only when high rates of matrix production are present in the biofilm centre, does overall biofilm spreading initiate along the solid-air interface. By tracking larger fluorescent particles for a long time, I could distinguish several kinematic stages of E. coli biofilm expansion and observed a transition from non-linear to linear velocity profiles, which precedes the emergence of wrinkles at the biofilm periphery. Decomposing particle velocities to their radial and circumferential components revealed a last kinematic stage, where biofilm movement is mostly directed towards the radial delaminated buckles, which verticalize. The resulting compressive strains computed in these regions were observed to substantially deform the underlying agar substrates. The co-localization of higher cell and matrix densities towards an annular region and the succession of several kinematic stages are thus expected to promote the emergence of mechanical instabilities at the biofilm periphery. These experimental findings are predicted to advance future modelling approaches of biofilm morphogenesis.
E. coli biofilm morphogenesis is further anticipated to depend on external stimuli from the environment. To clarify how the water could be used to tune biofilm material properties, we quantified E. coli biofilm growth, wrinkling dynamics and rigidity as a function of the water content of the nutritive substrates. Time-lapse microscopy and computational image analysis revealed that substrates with high water content promote biofilm spreading kinetics, while substrates with low water content promote biofilm wrinkling. The wrinkles observed on biofilm cross-sections appeared more bent on substrates with high water content, while they tended to be more vertical on substrates with low water content. Both wet and dry biomass, accumulated over 4 days of culture, were larger in biofilms cultured on substrates with high water content, despite extra porosity within the matrix layer. Finally, the micro-indentation analysis revealed that substrates with low water content supported the formation of stiffer biofilms. This study shows that E. coli biofilms respond to the water content of their substrate, which might be used for tuning their material properties in view of further applications.
Biofilm material properties further depend on the composition and structure of the matrix of extracellular proteins and polysaccharides. In particular, E. coli biofilms were suggested to present tissue-like elasticity due to a dense fibre network consisting of amyloid curli and phosphoethanolamine-modified cellulose. To understand the contribution of these components to the emergent mechanical properties of E. coli biofilms, we performed micro-indentation on biofilms grown from bacteria of several strains. Besides showing higher dry masses, larger spreading diameters and slightly reduced water contents, biofilms expressing both main matrix components also presented high rigidities in the range of several hundred kPa, similar to biofilms containing only curli fibres. In contrast, a lack of amyloid curli fibres provides much higher adhesive energies and more viscoelastic fluid-like material behaviour. Therefore, the combination of amyloid curli and phosphoethanolamine-modified cellulose fibres implies the formation of a composite material whereby the amyloid curli fibres provide rigidity to E. coli biofilms, whereas the phosphoethanolamine-modified cellulose rather acts as a glue. These findings motivate further studies involving purified versions of these protein and polysaccharide components to better understand how their interactions benefit biofilm functions.
All three studies depict different aspects of biofilm morphogenesis, which are interrelated. The first work reveals the correlation between non-uniform biological activities and the emergence of mechanical instabilities in the biofilm. The second work acknowledges the adaptive nature of E. coli biofilm morphogenesis and its mechanical properties to an environmental stimulus, namely water. Finally, the last study reveals the complementary role of the individual matrix components in the formation of a stable biofilm material, which not only forms complex morphologies but also functions as a protective shield for the bacteria it contains. Our experimental findings on E. coli biofilm morphogenesis and their mechanical properties can have further implications for fundamental and applied biofilm research fields.
Plants can be primed to survive the exposure to a severe heat stress (HS) by prior exposure to a mild HS. The information about the priming stimulus is maintained by the plant for several days. This maintenance of acquired thermotolerance, or HS memory, is genetically separable from the acquisition of thermotolerance itself and several specific regulatory factors have been identified in recent years.
On the molecular level, HS memory correlates with two types of transcriptional memory, type I and type II, that characterize a partially overlapping subset of HS-inducible genes. Type I transcriptional memory or sustained induction refers to the sustained transcriptional induction above non-stressed expression levels of a gene for a prolonged time period after the end of the stress exposure. Type II transcriptional memory refers to an altered transcriptional response of a gene after repeated exposure to a stress of similar duration and intensity. In particular, enhanced re-induction refers to a transcriptional pattern in which a gene is induced to a significantly higher degree after the second stress exposure than after the first.
This thesis describes the functional characterization of a novel positive transcriptional regulator of type I transcriptional memory, the heat shock transcription factor HSFA3, and compares it to HSFA2, a known positive regulator of type I and type II transcriptional memory. It investigates type I transcriptional memory and its dependence on HSFA2 and HSFA3 for the first time on a genome-wide level, and gives insight on the formation of heteromeric HSF complexes in response to HS. This thesis confirms the tight correlation between transcriptional memory and H3K4 hyper-methylation, reported here in a case study that aimed to reduce H3K4 hyper-methylation of the type II transcriptional memory gene APX2 by CRISPR/dCas9-mediated epigenome editing. Finally, this thesis gives insight into the requirements for a heat shock transcription factor to function as a positive regulator of transcriptional memory, both in terms of its expression profile and protein abundance after HS and the contribution of individual functional domains.
In summary, this thesis contributes to a more detailed understanding of the molecular processes underlying transcriptional memory and therefore HS memory, in Arabidopsis thaliana.
Cosmic rays (CRs) are a ubiquitous and an important component of astrophysical environments such as the interstellar medium (ISM) and intracluster medium (ICM). Their plasma physical interactions with electromagnetic fields strongly influence their transport properties. Effective models which incorporate the microphysics of CR transport are needed to study the effects of CRs on their surrounding macrophysical media. Developing such models is challenging because of the conceptional, length-scale, and time-scale separation between the microscales of plasma physics and the macroscales of the environment. Hydrodynamical theories of CR transport achieve this by capturing the evolution of CR population in terms of statistical moments. In the well-established one-moment hydrodynamical model for CR transport, the dynamics of the entire CR population are described by a single statistical quantity such as the commonly used CR energy density. In this work, I develop a new hydrodynamical two-moment theory for CR transport that expands the well-established hydrodynamical model by including the CR energy flux as a second independent hydrodynamical quantity. I detail how this model accounts for the interaction between CRs and gyroresonant Alfvén waves. The small-scale magnetic fields associated with these Alfvén waves scatter CRs which fundamentally alters CR transport along large-scale magnetic field lines. This leads to the effects of CR streaming and diffusion which are both captured within the presented hydrodynamical theory. I use an Eddington-like approximation to close the hydrodynamical equations and investigate the accuracy of this closure-relation by comparing it to high-order approximations of CR transport. In addition, I develop a finite-volume scheme for the new hydrodynamical model and adapt it to the moving-mesh code Arepo. This scheme is applied using a simulation of a CR-driven galactic wind. I investigate how CRs launch the wind and perform a statistical analysis of CR transport properties inside the simulated circumgalactic medium (CGM). I show that the new hydrodynamical model can be used to explain the morphological appearance of a particular type of radio filamentary structures found inside the central molecular zone (CMZ). I argue that these harp-like features are synchrotron-radiating CRs which are injected into braided magnetic field lines by a point-like source such as a stellar wind of a massive star or a pulsar. Lastly, I present the finite-volume code Blinc that uses adaptive mesh refinement (AMR) techniques to perform simulations of radiation and magnetohydrodynamics (MHD). The mesh of Blinc is block-structured and represented in computer memory using a graph-based approach. I describe the implementation of the mesh graph and how a diffusion process is employed to achieve load balancing in parallel computing environments. Various test problems are used to verify the accuracy and robustness of the employed numerical algorithms.
Background
Ankle sprain is the most common injury in basketball. Chronic ankle instability develops from an acute ankle sprain may cause negative effects on quality of life, ankle functionality or on increasing risk for recurrent ankle sprains and post-traumatic osteoarthritis. To facilitate a preventative strategy of chronic ankle instability (CAI) in the basketball population, gathering epidemiological data is essential. However, the epidemiological data of CAI in basketball is limited. Therefore, this study aims to investigate the prevalence of CAI in basketball athletes and to determine whether gender, competitive level, and basketball playing position influence this prevalence.
Methods
In a cross-sectional study, in total 391 Taiwanese basketball athletes from universities and sports clubs participated. Besides non-standardized questions about demographics and their history of ankle sprains, participants further filled out the standard Cumberland Ankle Instability Tool applied to determine the presence of ankle instability. Questionnaires from 255 collegiate and 133 semi-professional basketball athletes (male = 243, female = 145, 22.3 ± 3.8 years, 23.3 ± 2.2 kg/m2) were analyzed. Differences in prevalence between gender, competitive level and playing position were determined using the Chi-square test.
Results
In the surveyed cohort, 26% had unilateral CAI while 50% of them had bilateral CAI. Women had a higher prevalence than men in the whole surveyed cohort (X2(1) = 0.515, p = 0.003). This gender disparity also showed from sub-analyses, that the collegiate female athletes had a higher prevalence than collegiate men athletes (X2(1) = 0.203, p = 0.001). Prevalence showed no difference between competitive levels (p > 0.05) and among playing positions (p > 0.05).
Conclusions
CAI is highly prevalent in the basketball population. Gender affects the prevalence of CAI. Regardless of the competitive level and playing position the prevalence of CAI is similar. The characteristic of basketball contributes to the high prevalence. Prevention of CAI should be a focus in basketball. When applying the CAI prevention measures, gender should be taken into consideration.
Background
Benefit finding, defined as perceiving positive life changes resulting from adversity and negative life stressors, gains growing attention in the context of chronic illness. The study aimed at examining the psychometric properties of the Benefit Finding Scale for Children (BFSC) in a sample of German youth facing chronic conditions.
Methods
A sample of adolescents with various chronic conditions (N = 304; 12 – 21years) completed the 10-item BFSC along with measures of intra- and interpersonal resources, coping strategies, and health-related quality of life (hrQoL). The total sample was randomly divided into two subsamples for conducting exploratory and confirmatory factor analyses (EFA/CFA).
Results
EFA revealed that the BFSC scores had a one-dimensional factor structure. CFA verified the one-dimensional factor structure with an acceptable fit. The BFSC exhibited acceptable internal consistency (α = 0.87 – 0.88) and construct validity. In line with our hypotheses, benefit finding was positively correlated with optimism, self-esteem, self-efficacy, sense of coherence, and support seeking. There were no correlations with avoidance, wishful thinking, emotional reaction, and hrQoL. Sex differences in benefit finding were not consistent across subsamples. Benefit finding was also positively associated with age, disease severity, and social status.
Conclusions
The BFSC is a psychometrically sound instrument to assess benefit finding in adolescents with chronic illness and may facilitate further research on positive adaptation processes in adolescents, irrespective of their specific diagnosis.
Li and B in ascending magmas: an experimental study on their mobility and isotopic fractionation
(2022)
This research study focuses on the behaviour of Li and B during magmatic ascent, and decompression-driven degassing related to volcanic systems. The main objective of this dissertation is to determine whether it is possible to use the diffusion properties of the two trace elements as a tool to trace magmatic ascent rate. With this objective, diffusion-couple and decompression experiments have been performed in order to study Li and B mobility in intra-melt conditions first, and then in an evolving system during decompression-driven degassing.
Synthetic glasses were prepared with rhyolitic composition and an initial water content of 4.2 wt%, and all the experiments were performed using an internally heated pressure vessel, in order to ensure a precise control on the experimental parameters such as temperature and pressure.
Diffusion-couple experiments were performed with a fix pressure 300 MPa. The temperature was varied in the range of 700-1250 °C with durations between 0 seconds and 24 hours. The diffusion-couple results show that Li diffusivity is very fast and starts already at very low temperature. Significant isotopic fractionation occurs due to the faster mobility of 6Li compared to 7Li. Boron diffusion is also accelerated by the presence of water, but the results of the isotopic ratios are unclear, and further investigation would be necessary to well constrain the isotopic fractionation process of boron in hydrous silicate melts. The isotopic ratios results show that boron isotopic fractionation might be affected by the speciation of boron in the silicate melt structure, as 10B and 11B tend to have tetrahedral and trigonal coordination, respectively.
Several decompression experiments were performed at 900 °C and 1000 °C, with pressures going from 300 MPa to 71-77 MPa and durations of 30 minutes, two, five and ten hours, in order to trigger water exsolution and the formation of vesicles in the sample. Textural observations and the calculation of the bubble number density confirmed that the bubble size and distribution after decompression is directly proportional to the decompression rate.
The overall SIMS results of Li and B show that the two trace elements tend to progressively decrease their concentration with decreasing decompression rates. This is explained because for longer decompression times, the diffusion of Li and B into the bubbles has more time to progress and the melt continuously loses volatiles as the bubbles expand their volumes.
For fast decompression, Li and B results show a concentration increase with a δ7Li and δ11B decrease close to the bubble interface, related to the sudden formation of the gas bubble, and the occurrence of a diffusion process in the opposite direction, from the bubble meniscus to the unaltered melt. When the bubble growth becomes dominant and Li and B start to exsolve into the gas phase, the silicate melt close to the bubble gets depleted in Li and B, because of a stronger diffusion of the trace elements into the bubble.
Our data are being applied to different models, aiming to combine the dynamics of bubble nucleation and growth with the evolution of trace elements concentration and isotopic ratios. Here, first considerations on these models will be presented, giving concluding remarks on this research study. All in all, the final remarks constitute a good starting point for further investigations. These results are a promising base to continue to study this process, and Li and B can indeed show clear dependences on decompression-related magma ascent rates in volcanic systems.
As of late, epidemiological studies have highlighted a strong association of dairy intake with lower disease risk, and similarly with an increased amount of odd-chain fatty acids (OCFA). While the OCFA also demonstrate inverse associations with disease incidence, the direct dietary sources and mode of action of the OCFA remain poorly understood.
The overall aim of this thesis was to determine the impact of two main fractions of dairy, milk fat and milk protein, on OCFA levels and their influence on health outcomes under high-fat (HF) diet conditions. Both fractions represent viable sources of OCFA, as milk fats contain a significant amount of OCFA and milk proteins are high in branched chain amino acids (BCAA), namely valine (Val) and isoleucine (Ile), which can produce propionyl-CoA (Pr-CoA), a precursor for endogenous OCFA synthesis, while leucine (Leu) does not. Additionally, this project sought to clarify the specific metabolic effects of the OCFA heptadecanoic acid (C17:0).
Both short-term and long-term feeding studies were performed using male C57BL/6JRj mice fed HF diets supplemented with milk fat or C17:0, as well as milk protein or individual BCAA (Val; Leu) to determine their influences on OCFA and metabolic health. Short-term feeding revealed that both milk fractions induce OCFA in vivo, and the increases elicited by milk protein could be, in part, explained by Val intake. In vitro studies using primary hepatocytes further showed an induction of OCFA after Val treatment via de novo lipogenesis and increased α-oxidation. In the long-term studies, both milk fat and milk protein increased hepatic and circulating OCFA levels; however, only milk protein elicited protective effects on adiposity and hepatic fat accumulation—likely mediated by the anti-obesogenic effects of an increased Leu intake. In contrast, Val feeding did not increase OCFA levels nor improve obesity, but rather resulted in glucotoxicity-induced insulin resistance in skeletal muscle mediated by its metabolite 3-hydroxyisobutyrate (3-HIB). Finally, while OCFA levels correlated with improved health outcomes, C17:0 produced negligible effects in preventing HF-diet induced health impairments.
The results presented herein demonstrate that the beneficial health outcomes associated with dairy intake are likely mediated through the effects of milk protein, while OCFA levels are likely a mere association and do not play a significant causal role in metabolic health under HF conditions. Furthermore, the highly divergent metabolic effects of the two BCAA, Leu and Val, unraveled herein highlight the importance of protein quality.
Large quantities of the antibiotic florfenicol are used in animal farming and aquaculture, contaminating the ecosystem with antibiotic residues and promoting antimicrobial resistance, ultimately leading to untreatable multidrug-resistant pathogens. Florfenicol-resistant bacteria often activate export mechanisms that result in resistance to various structurally unrelated antibiotics. We devised novel strategies for the enzymatic inactivation of florfenicol in different media, such as saltwater or milk. Using a combinatorial approach and selection, we optimized a hydrolase (EstDL136) for florfenicol cleavage. Reaction kinetics were followed by time-resolved NMR spectroscopy. Importantly, the hydrolase remained active in different media, such as saltwater or cow milk. Various environmentally-friendly application strategies for florfenicol inactivation were developed using the optimized hydrolase. As a potential filter device for cost-effective treatment of waste milk or aquacultural wastewater, the hydrolase was immobilized on Ni-NTA agarose or silica as carrier materials. In two further application examples, the hydrolase was used as cell extract or encapsulated with a semi-permeable membrane. This facilitated, for example, florfenicol inactivation in whole milk, which can help to treat waste milk from medicated cows, to be fed to calves without the risk of inducing antibiotic resistance. Enzymatic inactivation of antibiotics, in general, enables therapeutic intervention without promoting antibiotic resistance.
The intake of high-fat diets (HFDs) containing large amounts of saturated long-chain fatty acids leads to obesity, oxidative stress, inflammation, and insulin resistance. The trace element selenium, as a crucial part of antioxidative selenoproteins, can protect against the development of diet-induced insulin resistance in white adipose tissue (WAT) by increasing glutathione peroxidase 3 (GPx3) and insulin receptor (IR) expression. Whether selenite (Se) can attenuate insulin resistance in established lipotoxic and obese conditions is unclear. We confirm that GPX3 mRNA expression in adipose tissue correlates with BMI in humans. Cultivating 3T3-L1 pre-adipocytes in palmitate-containing medium followed by Se treatment attenuates insulin resistance with enhanced GPx3 and IR expression and adipocyte differentiation. However, feeding obese mice a selenium-enriched high-fat diet (SRHFD) only resulted in a modest increase in overall selenoprotein gene expression in WAT in mice with unaltered body weight development, glucose tolerance, and insulin resistance. While Se supplementation improved adipocyte morphology, it did not alter WAT insulin sensitivity. However, mice fed a SRHFD exhibited increased insulin content in the pancreas. Overall, while selenite protects against palmitate-induced insulin resistance in vitro, obesity impedes the effect of selenite on insulin action and adipose tissue metabolism in vivo.
Background and Objectives: Low back pain is a worldwide health problem. An early diagnosis is required to develop personalized treatment strategies. The Risk Stratification Index (RSI) was developed to serve the purpose. The aim of this pilot study is to cross-culturally translate the RSI to a French version (RSI-F) and evaluate the test-retest reliability of RSI-F using a French active population. Materials and Methods: The RSI was translated from German to French (RSI-F) based on the guidelines of cross-cultural adaptation of self-report measures. A total of 42 French recreational athletes (age 18–63 years) with non-specific low back pain were recruited and filled in the RSI-F twice. The test-retest reliability was examined using intraclass correlation coefficient (ICC1,2) and Pearson correlation coefficient. Results: Finally, 33 questionnaires were analyzed (14 males and 19 females, age 31 ± 10 years, 9.5 ± 3.2 h/week of training). The test-retest of RSI-F CPI and DISS were excellent (CPI: ICC1,2 = 0.989, p < 0.001; r = 0.989, p < 0.001; DISS: ICC1,2 = 0.991, p < 0.001; r = 0.991, p < 0.001), as well as Korff pain intensity (ICC1,2 = 0.995, p < 0.001; r = 0.995, p < 0.001) and disability (ICC1,2 = 0.998, p < 0.001; r = 0.998, p < 0.001). Conclusion: The RSI-F is linguistically accurate and reliable for use by a French-speaking active population with non-specific low back pain. The RSI-F is considered a tool to examine the evolution of psychosocial factors and therefore the risk of chronicity and the prognostic of pain. Further evaluations, such as internal, external validity, and responsiveness should be evaluated in a larger population.