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Left ventricular assist devices (LVADs) have become a valuable treatment for patients with advanced heart failure. Women appear to be disadvantaged in the usage of LVADs and concerning clinical outcomes such as death and adverse events after LVAD implant. Contrary to typical clinical characteristics (e.g., disease severity), device-related factors such as the intended device strategy, bridge to a heart transplantation or destination therapy, are often not considered in research on gender differences. In addition, the relevance of pre-implant psychosocial risk factors, such as substance abuse and limited social support, for LVAD outcomes is currently unclear. Thus, the aim of this dissertation is to explore the role of pre-implant psychosocial risk factors for gender differences in clinical outcomes, accounting for clinical and device-related risk factors.
In the first article, gender differences in pre-implant characteristics of patients registered in The European Registry for Patients with Mechanical Circulatory Support (EUROMACS) were investigated. It was found that women and men differed in multiple pre-implant characteristics depending on device strategy. In the second article, gender differences in major clinical outcomes (i.e., death, heart transplant, device explant due to cardiac recovery, device replacement due to complications) were evaluated for patients in the device strategy destination therapy in the Interagency Registry for Mechanically Assisted Circulation (INTERMACS). Additionally, the association of gender and psychosocial risk factors with the major outcomes were analyzed. Women had similar probabilities to die on LVAD support, and even higher probabilities to experience explant of the device due to cardiac recovery compared with men in the destination therapy subgroup. Pre-implant psychosocial risk factors were not associated with major outcomes. The third article focused on gender differences in 10 adverse events (e.g., device malfunction, bleeding) after LVAD implant in INTERMACS. The association of a psychosocial risk indicator with gender and adverse events after LVAD implantation was evaluated. Women were less likely to have psychosocial risk pre-implant but more likely to experience seven out of 10 adverse events compared with men. Pre-implant psychosocial risk was associated with adverse events, even suggesting a dose response-relationship. These associations appeared to be more pronounced in women.
In conclusion, women appear to have similar survival to men when accounting for device strategy. They have higher probabilities of recovery, but higher probabilities of device replacement and adverse events compared with men. Regarding these adverse events, women may be more susceptible to psychosocial risk factors than men. The results of this dissertation illustrate the importance of gender-sensitive research and suggest considering device strategy when studying gender differences in LVAD recipients. Further research is warranted to elucidate the role of specific psychosocial risk factors that lead to higher probabilities of adverse events, to intervene early and improve patient care in both, women and men
Knowledge acquisition comprises various processes. Each of those has its dedicated research domain. Two examples are the relations between knowledge types and the influences of person-related variables. Furthermore, the transfer of knowledge is another crucial domain in educational research. I investigated these three processes through secondary analyses in this dissertation. Secondary analyses comply with the broadness of each field and yield the possibility of more general interpretations. The dissertation includes three meta-analyses: The first meta-analysis reports findings on the predictive relations between conceptual and procedural knowledge in mathematics in a cross-lagged panel model. The second meta-analysis focuses on the mediating effects of motivational constructs on the relationship between prior knowledge and knowledge after learning. The third meta-analysis deals with the effect of instructional methods in transfer interventions on knowledge transfer in school students. These three studies provide insights into the determinants and processes of knowledge acquisition and transfer. Knowledge types are interrelated; motivation mediates the relation between prior and later knowledge, and interventions influence knowledge transfer. The results are discussed by examining six key insights that build upon the three studies. Additionally, practical implications, as well as methodological and content-related ideas for further research, are provided.
When humans encounter attitude objects (e.g., other people, objects, or constructs), they evaluate them. Often, these evaluations are based on attitudes. Whereas most research focuses on univalent (i.e., only positive or only negative) attitude formation, little research exists on ambivalent (i.e., simultaneously positive and negative) attitude formation. Following a general introduction into ambivalence, I present three original manuscripts investigating ambivalent attitude formation. The first manuscript addresses ambivalent attitude formation from previously univalent attitudes. The results indicate that responding to a univalent attitude object incongruently leads to ambivalence measured via mouse tracking but not ambivalence measured via self-report. The second manuscript addresses whether the same number of positive and negative statements presented block-wise in an impression formation task leads to ambivalence. The third manuscript also used an impression formation task and addresses the question of whether randomly presenting the same number of positive and negative statements leads to ambivalence. Additionally, the effect of block size of the same valent statements is investigated. The results of the last two manuscripts indicate that presenting all statements of one valence and then all statements of the opposite valence leads to ambivalence measured via self-report and mouse tracking. Finally, I discuss implications for attitude theory and research as well as future research directions.
This thesis contains four parts that are all connected by their contributions to the Efficient Market Hypothesis and decision-making literature. Chapter two investigates how national stock market indices reacted to the news of national lockdown restrictions in the period from January to May 2020. The results show that lockdown restrictions led to different reactions in a sample of OECD and BRICS countries: there was a general negative effect resulting from the increase in lockdown restrictions, but the study finds strong evidence for underreaction during the lockdown announcement, followed by some overreaction that is corrected subsequently. This under-/overreaction pattern, however, is observed mostly during the first half of our time series, pointing to learning effects. Relaxation of the lockdown restrictions, on the other hand, had a positive effect on markets only during the second half of our sample, while for the first half of the sample, the effect was negative. The third chapter investigates the gender differences in stock selection preferences on the Taiwan Stock Exchange. By utilizing trading data from the Taiwan Stock Exchange over a span of six years, it becomes possible to analyze trading behavior while minimizing the self-selection bias that is typically present in brokerage data. To study gender differences, this study uses firm-level data. The percentage of male traders in a company is the dependent variable, while the company’s industry and fundamental/technical aspects serve as independent variables. The results show that the percentage of women trading a company rises with a company’s age, market capitalization, a company’s systematic risk, and return. Men trade more frequently and show a preference for dividend-paying stocks and for industries with which they are more familiar. The fourth chapter investigated the relationship between regret and malicious and benign envy. The relationship is analyzed in two different studies. In experiment 1, subjects had to fill out psychological scales that measured regret, the two types of envy, core self-evaluation and the big 5 personality traits. In experiment 2, felt regret is measured in a hypothetical scenario, and the subject’s felt regret was regressed on the other variables mentioned above. The two experiments revealed that there is a positive direct relationship between regret and benign envy. The relationship between regret and malicious envy, on the other hand, is mostly an artifact of core self-evaluation and personality influencing both malicious envy and regret. The relationship can be explained by the common action tendency of self-improvement for regret and benign envy. Chapter five discusses the differences in green finance regulation and implementation between the EU and China. China introduced the Green Silk Road, while the EU adopted the Green Deal and started working with its own green taxonomy. The first difference comes from the definition of green finance, particularly with regard to coal-fired power plants. Especially the responsibility of nation-states’ emissions abroad. China is promoting fossil fuel projects abroad through its Belt and Road Initiative, but the EU’s Green Deal does not permit such actions. Furthermore, there are policies in both the EU and China that create contradictory incentives for economic actors. On the one hand, the EU and China are improving the framework conditions for green financing while, on the other hand, still allowing the promotion of conventional fuels. The role of central banks is also different between the EU and China. China’s central bank is actively working towards aligning the financial sector with green finance. A possible new role of the EU central bank or the priority financing of green sectors through political decision-making is still being debated.
Social entrepreneurship is a successful activity to solve social problems and economic
challenges. Social entrepreneurship uses for-profit industry techniques and tools to build
financially sound businesses that provide nonprofit services. Social entrepreneurial activities
also lead to the achievement of sustainable development goals. However, due to the complex,
hybrid nature of the business, social entrepreneurial activities are typically supported by macrolevel
determinants. To expand our knowledge of how beneficial macro-level determinants can
be, this work examines empirical evidence about the impact of macro-level determinants on
social entrepreneurship. Another aim of this dissertation is to examine the impact at the micro
level, as the growth ambitions of social and commercial entrepreneurs differ. At the beginning,
the introductory section is explained in Chapter 1, which contains the motivation for the
research, the research question, and the structure of the work.
There is an ongoing debate about the origin and definition of social entrepreneurship.
Therefore, the numerous phenomena of social entrepreneurship are examined theoretically in
the previous literature. To determine the common consensus on the topic, Chapter 2 presents
the theoretical foundations and definition of social entrepreneurship. The literature shows that
a variety of determinants at the micro and macro levels are essential for the emergence of social
entrepreneurship as a distinctive business model (Hartog & Hoogendoorn, 2011; Stephan et
al., 2015; Hoogendoorn, 2016). It is impossible to create a society based on a social mission without the support of micro and macro-level-level determinants. This work examines the
determinants and consequences of social entrepreneurship from different methodological
perspectives. The theoretical foundations of the micro- and macro-level determinants
influencing social entrepreneurial activities were discussed in Chapter 3
The purpose of reproducibility in research is to confirm previously published results
(Hubbard et al., 1998; Aguinis & Solarino, 2019). However, due to the lack of data, lack of
transparency of methodology, reluctance to publish, and lack of interest from researchers, there
is a lack of promoting replication of the existing research study (Baker, 2016; Hedges &
Schauer, 2019a). Promoting replication studies has been regularly emphasized in the business
and management literature (Kerr et al., 2016; Camerer et al., 2016). However, studies that
provide replicability of the reported results are considered rare in previous research (Burman
et al., 2010; Ryan & Tipu, 2022). Based on the research of Köhler and Cortina (2019), an
empirical study on this topic is carried out in Chapter 4 of this work.
Given this focus, researchers have published a large body of research on the impact of microand
macro-level determinants on social inclusion, although it is still unclear whether these
studies accurately reflect reality. It is important to provide conceptual underpinnings to the
field through a reassessment of published results (Bettis et al., 2016). The results of their
research make it abundantly clear that the macro determinants support social entrepreneurship.
In keeping with the more narrative approach, which is a crucial concern and requires attention,
Chapter 5 considered the reproducibility of previous results, particularly on the topic of social
entrepreneurship. We replicated the results of Stephan et al. (2015) to establish the trend of
reproducibility and validate the specific conclusions they drew. The literal and constructive
replication in the dissertation inspired us to explore technical replication research on social
entrepreneurship. Chapter 6 evaluates the fundamental characteristics that have proven to be key factors in the
growth of social ventures. The current debate reviews and references literature that has
specifically focused on the development of social entrepreneurship. An empirical analysis of
factors directly related to the ambitious growth of social entrepreneurship is also carried out.
Numerous social entrepreneurial groups have been studied concerning this association. Chapter
6 compares the growth ambitions of social and traditional (commercial) entrepreneurship as
consequences at the micro level. This study examined many characteristics of social and
commercial entrepreneurs' growth ambitions. Scholars have claimed to some extent that the
growth of social entrepreneurship differs from commercial entrepreneurial activities due to
objectivity differences (Lumpkin et al., 2013; Garrido-Skurkowicz et al., 2022). Qualitative
research has been used in studies to support the evidence on related topics, including Gupta et
al (2020) emphasized that research needs to focus on specific concepts of social
entrepreneurship for the field to advance. Therefore, this study provides a quantitative,
analysis-based assessment of facts and data. For this purpose, a data set from the Global
Entrepreneurship Monitor (GEM) 2015 was used, which examined 12,695 entrepreneurs from
38 countries. Furthermore, this work conducted a regression analysis to evaluate the influence
of various social and commercial characteristics of entrepreneurship on economic growth in
developing countries. Chapter 7 briefly explains future directions and practical/theoretical
implications.
Data fusions are becoming increasingly relevant in official statistics. The aim of a data fusion is to combine two or more data sources using statistical methods in order to be able to analyse different characteristics that were not jointly observed in one data source. Record linkage of official data sources using unique identifiers is often not possible due to methodological and legal restrictions. Appropriate data fusion methods are therefore of central importance in order to use the diverse data sources of official statistics more effectively and to be able to jointly analyse different characteristics. However, the literature lacks comprehensive evaluations of which fusion approaches provide promising results for which data constellations. Therefore, the central aim of this thesis is to evaluate a concrete plethora of possible fusion algorithms, which includes classical imputation approaches as well as statistical and machine learning methods, in selected data constellations.
To specify and identify these data contexts, data and imputation-related scenario types of a data fusion are introduced: Explicit scenarios, implicit scenarios and imputation scenarios. From these three scenario types, fusion scenarios that are particularly relevant for official statistics are selected as the basis for the simulations and evaluations. The explicit scenarios are the fulfilment or violation of the Conditional Independence Assumption (CIA) and varying sample sizes of the data to be matched. Both aspects are likely to have a direct, that is, explicit, effect on the performance of different fusion methods. The summed sample size of the data sources to be fused and the scale level of the variable to be imputed are considered as implicit scenarios. Both aspects suggest or exclude the applicability of certain fusion methods due to the nature of the data. The univariate or simultaneous, multivariate imputation solution and the imputation of artificially generated or previously observed values in the case of metric characteristics serve as imputation scenarios.
With regard to the concrete plethora of possible fusion algorithms, three classical imputation approaches are considered: Distance Hot Deck (DHD), the Regression Model (RM) and Predictive Mean Matching (PMM). With Decision Trees (DT) and Random Forest (RF), two prominent tree-based methods from the field of statistical learning are discussed in the context of data fusion. However, such prediction methods aim to predict individual values as accurately as possible, which can clash with the primary objective of data fusion, namely the reproduction of joint distributions. In addition, DT and RF only comprise univariate imputation solutions and, in the case of metric variables, artificially generated values are imputed instead of real observed values. Therefore, Predictive Value Matching (PVM) is introduced as a new, statistical learning-based nearest neighbour method, which could overcome the distributional disadvantages of DT and RF, offers a univariate and multivariate imputation solution and, in addition, imputes real and previously observed values for metric characteristics. All prediction methods can form the basis of the new PVM approach. In this thesis, PVM based on Decision Trees (PVM-DT) and Random Forest (PVM-RF) is considered.
The underlying fusion methods are investigated in comprehensive simulations and evaluations. The evaluation of the various data fusion techniques focusses on the selected fusion scenarios. The basis for this is formed by two concrete and current use cases of data fusion in official statistics, the fusion of EU-SILC and the Household Budget Survey on the one hand and of the Tax Statistics and the Microcensus on the other. Both use cases show significant differences with regard to different fusion scenarios and thus serve the purpose of covering a variety of data constellations. Simulation designs are developed from both use cases, whereby the explicit scenarios in particular are incorporated into the simulations.
The results show that PVM-RF in particular is a promising and universal fusion approach under compliance with the CIA. This is because PVM-RF provides satisfactory results for both categorical and metric variables to be imputed and also offers a univariate and multivariate imputation solution, regardless of the scale level. PMM also represents an adequate fusion method, but only in relation to metric characteristics. The results also imply that the application of statistical learning methods is both an opportunity and a risk. In the case of CIA violation, potential correlation-related exaggeration effects of DT and RF, and in some cases also of RM, can be useful. In contrast, the other methods induce poor results if the CIA is violated. However, if the CIA is fulfilled, there is a risk that the prediction methods RM, DT and RF will overestimate correlations. The size ratios of the studies to be fused in turn have a rather minor influence on the performance of fusion methods. This is an important indication that the larger dataset does not necessarily have to serve as a donor study, as was previously the case.
The results of the simulations and evaluations provide concrete implications as to which data fusion methods should be used and considered under the selected data and imputation constellations. Science in general and official statistics in particular benefit from these implications. This is because they provide important indications for future data fusion projects in order to assess which specific data fusion method could provide adequate results along the data constellations analysed in this thesis. Furthermore, with PVM this thesis offers a promising methodological innovation for future data fusions and for imputation problems in general.
Semantic-Aware Coordinated Multiple Views for the Interactive Analysis of Neural Activity Data
(2024)
Visualizing brain simulation data is in many aspects a challenging task. For one, data used in brain simulations and the resulting datasets is heterogeneous and insight is derived by relating all different kinds of it. Second, the analysis process is rapidly changing while creating hypotheses about the results. Third, the scale of data entities in these heterogeneous datasets is manifold, reaching from single neurons to brain areas interconnecting millions. Fourth, the heterogeneous data consists of a variety of modalities, e.g.: from time series data to connectivity data, from single parameters to a set of parameters spanning parameter spaces with multiple possible and biological meaningful solutions; from geometrical data to hierarchies and textual descriptions, all on mostly different scales. Fifth, visualizing includes finding suitable representations and providing real-time interaction while supporting varying analysis workflows. To this end, this thesis presents a scalable and flexible software architecture for visualizing, integrating and interacting with brain simulations data. The scalability and flexibility is achieved by interconnected services forming in a series of Coordinated Multiple View (CMV) systems. Multiple use cases are presented, introducing views leveraging this architecture, extending its ecosystem and resulting in a Problem Solving Environment (PSE) from which custom-tailored CMV systems can be build. The construction of such CMV system is assisted by semantic reasoning hence the term semantic-aware CMVs.
Physically-based distributed rainfall-runoff models as the standard analysis tools for hydro-logical processes have been used to simulate the water system in detail, which includes spa-tial patterns and temporal dynamics of hydrological variables and processes (Davison et al., 2015; Ek and Holtslag, 2004). In general, catchment models are parameterized with spatial information on soil, vegetation and topography. However, traditional approaches for eval-uation of the hydrological model performance are usually motivated with respect to dis-charge data alone. This may thus cloud model realism and hamper understanding of the catchment behavior. It is necessary to evaluate the model performance with respect to in-ternal hydrological processes within the catchment area as well as other components of wa-ter balance rather than runoff discharge at the catchment outlet only. In particular, a consid-erable amount of dynamics in a catchment occurs in the processes related to interactions of the water, soil and vegetation. Evapotranspiration process, for instance, is one of those key interactive elements, and the parameterization of soil and vegetation in water balance mod-eling strongly influences the simulation of evapotranspiration. Specifically, to parameterize the water flow in unsaturated soil zone, the functional relationships that describe the soil water retention and hydraulic conductivity characteristics are important. To define these functional relationships, Pedo-Transfer Functions (PTFs) are common to use in hydrologi-cal modeling. Opting the appropriate PTFs for the region under investigation is a crucial task in estimating the soil hydraulic parameters, but this choice in a hydrological model is often made arbitrary and without evaluating the spatial and temporal patterns of evapotran-spiration, soil moisture, and distribution and intensity of runoff processes. This may ulti-mately lead to implausible modeling results and possibly to incorrect decisions in regional water management. Therefore, the use of reliable evaluation approaches is continually re-quired to analyze the dynamics of the current interactive hydrological processes and predict the future changes in the water cycle, which eventually contributes to sustainable environ-mental planning and decisions in water management.
Remarkable endeavors have been made in development of modelling tools that provide insights into the current and future of hydrological patterns in different scales and their im-pacts on the water resources and climate changes (Doell et al., 2014; Wood et al., 2011). Although, there is a need to consider a proper balance between parameter identifiability and the model's ability to realistically represent the response of the natural system. Neverthe-less, tackling this issue entails investigation of additional information, which usually has to be elaborately assembled, for instance, by mapping the dominant runoff generation pro-cesses in the intended area, or retrieving the spatial patterns of soil moisture and evapotran-spiration by using remote sensing methods, and evaluation at a scale commensurate with hydrological model (Koch et al., 2022; Zink et al., 2018). The present work therefore aims to give insights into the modeling approaches to simulate water balance and to improve the soil and vegetation parameterization scheme in the hydrological model subject to producing more reliable spatial and temporal patterns of evapotranspiration and runoff processes in the catchment.
An important contribution to the overall body of work is a book chapter included among publications. The book chapter provides a comprehensive overview of the topic and valua-ble insights into the understanding the water balance and its estimation methods.
Moreover, the first paper aimed to evaluate the hydrological model behavior with re-spect to contribution of various sources of information. To do so, a multi-criteria evaluation metric including soft and hard data was used to define constraints on outputs of the 1-D hydrological model WaSiM-ETH. Applying this evaluation metric, we could identify the optimal soil and vegetation parameter sets that resulted in a “behavioral” forest stand water balance model. It was found out that even if simulations of transpiration and soil water con-tent are consistent with measured data, but still the dominant runoff generation processes or total water balance might be wrongly calculated. Therefore, only using an evaluation scheme which looks over different sources of data and embraces an understanding of the local controls of water loss through soil and plant, allowed us to exclude the unrealistic modeling outputs. The results suggested that we may need to question the generally accept-ed soil parameterization procedures that apply default parameter sets.
The second paper attempts to tackle the pointed model evaluation hindrance by getting down to the small-scale catchment (in Bavaria). Here, a methodology was introduced to analyze the sensitivity of the catchment water balance model to the choice of the Pedo-Transfer Functions (PTF). By varying the underlying PTFs in a calibrated and validated model, we could determine the resulting effects on the spatial distribution of soil hydraulic properties, total water balance in catchment outlet, and the spatial and temporal variation of the runoff components. Results revealed that the water distribution in the hydrologic system significantly differs amongst various PTFs. Moreover, the simulations of water balance components showed high sensitivity to the spatial distribution of soil hydraulic properties. Therefore, it was suggested that opting the PTFs in hydrological modeling should be care-fully tested by looking over the spatio-temporal distribution of simulated evapotranspira-tion and runoff generation processes, whether they are reasonably represented.
To fulfill the previous studies’ suggestions, the third paper then aims to focus on evalu-ating the hydrological model through improving the spatial representation of dominant run-off processes. It was implemented in a mesoscale catchment in southwestern Germany us-ing the hydrological model WaSiM-ETH. Dealing with the issues of inadequate spatial ob-servations for rigorous spatial model evaluation, we made use of a reference soil hydrologic map available for the study area to discern the expected dominant runoff processes across a wide range of hydrological conditions. The model was parameterized by applying 11 PTFs and run by multiple synthetic rainfall events. To compare the simulated spatial patterns to the patterns derived by digital soil map, a multiple-component spatial performance metric (SPAEF) was applied. The simulated DRPs showed a large variability with regard to land use, topography, applied rainfall rates, and the different PTFs, which highly influence the rapid runoff generation under wet conditions.
The three published manuscripts proceeded towards the model evaluation viewpoints that ultimately attain the behavioral model outputs. It was performed through obtaining information about internal hydrological processes that lead to certain model behaviors, and also about the function and sensitivity of some of the soil and vegetation parameters that may primarily influence those internal processes in a catchment. Accordingly, using this understanding on model reactions, and by setting multiple evaluation criteria, it was possi-ble to identify which parameterization could lead to behavioral model realization. This work, in fact, will contribute to solving some of the issues (e.g., spatial variability and modeling methods) identified as the 23 unsolved problems in hydrology in the 21st century (Blöschl et al., 2019). The results obtained in the present work encourage the further inves-tigations toward a comprehensive model calibration procedure considering multiple data sources simultaneously. This will enable developing the new perspectives to the current parameter estimation methods, which in essence, focus on reproducing the plausible dy-namics (spatio-temporal) of the other hydrological processes within the watershed.
Allocating scarce resources efficiently is a major task in mechanism design. One of the most fundamental problems in mechanism design theory is the problem of selling a single indivisible item to bidders with private valuations for the item. In this setting, the classic Vickrey auction of~\citet{vickrey1961} describes a simple mechanism to implement a social welfare maximizing allocation.
The Vickrey auction for a single item asks every buyer to report its valuation and allocates the item to the highest bidder for a price of the second highest bid. This auction features some desirable properties, e.g., buyers cannot benefit from misreporting their true value for the item (incentive compatibility) and the auction can be executed in polynomial time.
However, when there is more than one item for sale and buyers' valuations for sets of items are not additive or the set of feasible allocations is constrained, then constructing mechanisms that implement efficient allocations and have polynomial runtime might be very challenging. Consider a single seller selling $n\in \N$ heterogeneous indivisible items to several bidders. The Vickrey-Clarke-Groves auction generalizes the idea of the Vickrey auction to this multi-item setting. Naturally, every bidder has an intrinsic value for every subset of items. As in in the Vickrey auction, bidders report their valuations (Now, for every subset of items!). Then, the auctioneer computes a social welfare maximizing allocation according to the submitted bids and charges buyers the social cost of their winning that is incurred by the rest of the buyers. (This is the analogue to charging the second highest bid to the winning bidder in the single item Vickrey auction.) It turns out that the Vickrey-Clarke-Groves auction is also incentive compatible but it poses some problems: In fact, say for $n=40$, bidders would have to submit $2^{40}-1$ values (one value for each nonempty subset of the ground set) in total. Thus, asking every bidder for its valuation might be impossible due to time complexity issues. Therefore, even though the Vickrey-Clarke-Groves auction implements a social welfare maximizing allocation in this multi-item setting it might be impractical and there is need for alternative approaches to implement social welfare maximizing allocations.
This dissertation represents the results of three independent research papers all of them tackling the problem of implementing efficient allocations in different combinatorial settings.
This cumulative thesis encompass three studies focusing on the Weddell Sea region in the Antarctic. The first study produces and evaluates a high quality data set of wind measurements for this region. The second study produces and evaluates a 15 year regional climate simulation for the Weddell Sea region. And the third study produces and evaluates a climatology of low level jets (LLJs) from the simulation data set. The evaluations were done in the attached three publications and the produced data sets are published online.
In 2015/2016, the RV Polarstern undertook an Antarctic expedition in the Weddell Sea. We operated a Doppler wind lidar on board during that time running different scan patterns. The resulting data was evaluated, corrected, processed and we derived horizontal wind speed and directions for vertical profiles with up to 2 km height. The measurements cover 38 days with a temporal resolution of 10-15 minutes. A comparisons with other radio sounding data showed only minor differences.
The resulting data set was used alongside other measurements to evaluate temperature and wind of simulation data. The simulation data was produced with the regional climate model CCLM for the period of 2002 to 2016 for the Weddell Sea region. Only smaller biases were found except for a strong warm bias during winter near the surface of the Antarctic Plateau. Thus we adapted the model setup and were able to remove the bias in a second simulation.
This new simulation data was then used to derive a climatology of low level jets (LLJs). Statistics of occurrence frequency, height and wind speed of LLJs for the Weddell Sea region are presented along other parameters. Another evaluation with measurements was also performed in the last study.
This study scrutinizes press photographs published during the first 6 weeks of the Russian War in Ukraine, beginning February 24th, 2022. Its objective is to shed light on the emotions evoked in Internet-savvy audiences. This empirical research aims to contribute to the understanding of emotional media effects that shape attitudes and actions of ordinary citizens. Main research questions are: What kind of empathic reactions are observed during the Q-sort study? Which visual patterns are relevant for which emotional evaluations and attributions? The assumption is that the evaluations and attributions of empathy are not random, but follow specific patterns. The empathic reactions are based on visual patterns which, in turn, influence the type of empathic reaction. The identification of specific categories for visual and emotional reaction patterns are arrived at in different methodological processes. Visual pattern categories were developed inductively, using the art history method of iconography-iconology to identify six distinct types of visual motifs in a final sample of 33 war photographs. The overarching categories for empathic reactions—empty empathy, vicarious traumatization and witnessing—were applied deductively, building on E. Ann Kaplan's pivotal distinctions. The main result of this research are three novel categories that combine visual patterns with empathic reaction patterns. The labels for these categories are a direct result of the Q-factorial analysis, interpreted through the lense of iconography-iconology. An exploratory nine-scale forced-choice Q-sort study (Nstimuli = 33) was implemented, followed by self-report interviews with a total of 25 participants [F = 16 (64%), M = 9 (36%), Mage = 26.4 years]. Results from this exploratory research include motivational statements on the meanings of war photography from semi-structured post-sort-interviews. The major result of this study are three types of visual patterns (“factors”) that govern distinct empathic reactions in participants: Factor 1 is “veiled empathy” with highest empathy being attributed to photos showing victims whose corpses or faces were veiled. Additional features of “veiled empathy” are a strong anti-politician bias and a heightened awareness of potential visual manipulation. Factor 2 is “mirrored empathy” with highest empathy attributions to photos displaying human suffering openly. Factor 3 focused on the context. It showed a proclivity for documentary style photography. This pattern ranked photos without clear contextualization lower in empathy than those photos displaying the fully contextualized setting. To the best of our knowledge, no study has tested empathic reactions to war photography empirically. In this respect, the study is novel, but also exploratory. Findings like the three patterns of visual empathy might be helpful for photo selection processes in journalism, for political decision-making, for the promotion of relief efforts, and for coping strategies in civil society to deal with the potentially numbing or traumatizing visual legacy of the War in Ukraine.
Official business surveys form the basis for national and regional business statistics and are thus of great importance for analysing the state and performance of the economy. However, both the heterogeneity of business data and their high dynamics pose a particular challenge to the feasibility of sampling and the quality of the resulting estimates. A widely used sampling frame for creating the design of an official business survey is an extract from an official business register. However, if this frame does not accurately represent the target population, frame errors arise. Amplified by the heterogeneity and dynamics of business populations, these errors can significantly affect the estimation quality and lead to inefficiencies and biases. This dissertation therefore deals with design-based methods for optimising business surveys with respect to different types of frame errors.
First, methods for adjusting the sampling design of business surveys are addressed. These approaches integrate auxiliary information about the expected structures of frame errors into the sampling design. The aim is to increase the number of sampled businesses that are subject to frame errors. The element-specific frame error probability is estimated based on auxiliary information about frame errors observed in previous samples. The approaches discussed consider different types of frame errors and can be incorporated into predefined designs with fixed strata.
As the second main pillar of this work, methods for adjusting weights to correct for frame errors during estimation are developed and investigated. As a result of frame errors, the assumptions under which the original design weights were determined based on the sampling design no longer hold. The developed methods correct the design weights taking into account the errors identified for sampled elements. Case-number-based reweighting approaches, on the one hand, attempt to reconstruct the unknown size of the individual strata in the target population. In the context of weight smoothing methods, on the other hand, design weights are modelled and smoothed as a function of target or auxiliary variables. This serves to avoid inefficiencies in the estimation due to highly scattering weights or weak correlations between weights and target variables. In addition, possibilities of correcting frame errors by calibration weighting are elaborated. Especially when the sampling frame shows over- and/or undercoverage, the inclusion of external auxiliary information can provide a significant improvement of the estimation quality. For those methods whose quality cannot be measured using standard procedures, a procedure for estimating the variance based on a rescaling bootstrap is proposed. This enables an assessment of the estimation quality when using the methods in practice.
In the context of two extensive simulation studies, the methods presented in this dissertation are evaluated and compared with each other. First, in the environment of an experimental simulation, it is assessed which approaches are particularly suitable with regard to different data situations. In a second simulation study, which is based on the structural survey in the services sector, the applicability of the methods in practice is evaluated under realistic conditions.
Wasserbezogene regulierende und versorgende Ökosystemdienstleistungen (ÖSDL) wurden im Hinblick auf das Abflussregime und die Grundwasserneubildung im Biosphärenreservat Pfälzerwald im Südwesten Deutschlands anhand hydrologischer Modellierung unter Verwendung des Soil and Water Assessment Tool (SWAT+) untersucht. Dabei wurde ein holistischer Ansatz verfolgt, wonach den ÖSDL Indikatoren für funktionale und strukturelle ökologische Prozesse zugeordnet werden. Potenzielle Risikofaktoren für die Verschlechterung von wasserbedingten ÖSDL des Waldes, wie Bodenverdichtung durch Befahren mit schweren Maschinen im Zuge von Holzerntearbeiten, Schadflächen mit Verjüngung, entweder durch waldbauliche Bewirtschaftungspraktiken oder durch Windwurf, Schädlinge und Kalamitäten im Zuge des Klimawandels, sowie der Kli-mawandel selbst als wesentlicher Stressor für Waldökosysteme wurden hinsichtlich ihrer Auswirkungen auf hydrologische Prozesse analysiert. Für jeden dieser Einflussfaktoren wurden separate SWAT+-Modellszenarien erstellt und mit dem kalibrierten Basismodell verglichen, das die aktuellen Wassereinzugsgebietsbedingungen basierend auf Felddaten repräsentierte. Die Simulationen bestätigten günstige Bedingungen für die Grundwasserneubildung im Pfälzerwald. Im Zusammenhang mit der hohen Versickerungskapazität der Bodensubstrate der Buntsandsteinverwitterung, sowie dem verzögernden und puffernden Einfluss der Baumkronen auf das Niederschlagswasser, wurde eine signifikante Minderungswirkung auf die Oberflächenabflussbildung und ein ausgeprägtes räumliches und zeitliches Rückhaltepotential im Einzugsgebiet simuliert. Dabei wurde festgestellt, dass erhöhte Niederschlagsmengen, die die Versickerungskapazität der sandigen Böden übersteigen, zu einer kurz geschlossenen Abflussreaktion mit ausgeprägten Oberflächenabflussspitzen führen. Die Simulationen zeigten Wechselwirkungen zwischen Wald und Wasserkreislauf sowie die hydrologische Wirksamkeit des Klimawandels, verschlechterter Bodenfunktionen und altersbezogener Bestandesstrukturen im Zusammenhang mit Unterschieden in der Baumkronenausprägung. Zukunfts-Klimaprojektionen, die mit BIAS-bereinigten REKLIES- und EURO-CORDEX-Regionalklimamodellen (RCM) simuliert wurden, prognostizierten einen höheren Verdunstungsbedarf und eine Verlängerung der Vegetationsperiode bei gleichzeitig häufiger auftretenden Dürreperioden innerhalb der Vegetationszeit, was eine Verkürzung der Periode für die Grundwasserneubildung induzierte, und folglich zu einem prognostizierten Rückgang der Grundwasserneubildungsrate bis zur Mitte des Jahrhunderts führte. Aufgrund der starken Korrelation mit Niederschlagsintensitäten und der Dauer von Niederschlagsereignissen, bei allen Unsicherheiten in ihrer Vorhersage, wurde für die Oberflächenabflussgenese eine Steigerung bis zum Ende des Jahrhunderts prognostiziert.
Für die Simulation der Bodenverdichtung wurden die Trockenrohdichte des Bodens und die SCS Curve Number in SWAT+ gemäß Daten aus Befahrungsversuchen im Gebiet angepasst. Die günstigen Infiltrationsbedingungen und die relativ geringe Anfälligkeit für Bodenverdichtung der grobkörnigen Buntsandsteinverwitterung dominierten die hydrologischen Auswirkungen auf Wassereinzugsgebietsebene, sodass lediglich moderate Verschlechterungen wasserbezogener ÖSDL angezeigt wurden. Die Simulationen zeigten weiterhin einen deutlichen Einfluss der Bodenart auf die hydrologische Reaktion nach Bodenverdichtung auf Rückegassen und stützen damit die Annahme, dass die Anfälligkeit von Böden gegenüber Verdichtung mit dem Anteil an Schluff- und Tonbodenpartikeln zunimmt. Eine erhöhte Oberflächenabflussgenese ergab sich durch das Wegenetz im Gesamtgebiet.
Schadflächen mit Bestandesverjüngung wurden anhand eines artifiziellen Modells innerhalb eines Teileinzugsgebiets unter der Annahme von 3-jährigen Baumsetzlingen in einem Entwicklungszeitraum von 10 Jahren simuliert und hinsichtlich spezifischer Was-serhaushaltskomponenten mit Altbeständen (30 bis 80 Jahre) verglichen. Die Simulation ließ darauf schließen, dass bei fehlender Kronenüberschirmung die hydrologisch verzögernde Wirkung der Bestände beeinträchtigt wird, was die Entstehung von Oberflächenabfluss begünstigt und eine quantitativ geringfügig höhere Tiefensickerung fördert. Hydrologische Unterschiede zwischen dem geschlossenem Kronendach der Altbestände und Jungbeständen mit annähernden Freilandniederschlagsbedingungen wurden durch die dominierenden Faktoren atmosphärischer Verdunstungsanstoß, Niederschlagsmengen und Kronenüberschirmungsgrad bestimmt. Je weniger entwickelt das Kronendach von verjüngten Waldbeständen im Vergleich zu Altbeständen, je höher der atmosphärische Verdunstungsanstoß und je geringer die eingetragenen Niederschlagsmengen, desto größer war der hydrologische Unterschied zwischen den Bestandestypen.
Verbesserungsmaßnahmen für den dezentralen Hochwasserschutz sollten folglich kritische Bereiche für die Abflussbildung im Wald (CSA) berücksichtigen. Die hohe Sensibilität und Anfälligkeit der Wälder gegenüber Verschlechterungen der Ökosystembedingungen legen nahe, dass die Erhaltung des komplexen Gefüges und von intakten Wechselbeziehungen, insbesondere unter der gegebenen Herausforderung des Klimawandels, sorgfältig angepasste Schutzmaßnahmen, Anstrengungen bei der Identifizierung von CSA sowie die Erhaltung und Wiederherstellung der hydrologischen Kontinuität in Waldbeständen erfordern.
Traditional workflow management systems support process participants in fulfilling business tasks through guidance along a predefined workflow model.
Flexibility has gained a lot of attention in recent decades through a shift from mass production to customization. Various approaches to workflow flexibility exist that either require extensive knowledge acquisition and modelling effort or an active intervention during execution and re-modelling of deviating behaviour. The pursuit of flexibility by deviation is to compensate both of these disadvantages through allowing alternative unforeseen execution paths at run time without demanding the process participant to adapt the workflow model. However, the implementation of this approach has been little researched so far.
This work proposes a novel approach to flexibility by deviation. The approach aims at supporting process participants during the execution of a workflow through suggesting work items based on predefined strategies or experiential knowledge even in case of deviations. The developed concepts combine two renowned methods from the field of artificial intelligence - constraint satisfaction problem solving with process-oriented case-based reasoning. This mainly consists of a constraint-based workflow engine in combination with a case-based deviation management. The declarative representation of workflows through constraints allows for implicit flexibility and a simple possibility to restore consistency in case of deviations. Furthermore, the combined model, integrating procedural with declarative structures through a transformation function, increases the capabilities for flexibility. For an adequate handling of deviations the methodology of case-based reasoning fits perfectly, through its approach that similar problems have similar solutions. Thus, previous made experiences are transferred to currently regarded problems, under the assumption that a similar deviation has been handled successfully in the past.
Necessary foundations from the field of workflow management with a focus on flexibility are presented first.
As formal foundation, a constraint-based workflow model was developed that allows for a declarative specification of foremost sequential dependencies of tasks. Procedural and declarative models can be combined in the approach, as a transformation function was specified that converts procedural workflow models to declarative constraints.
One main component of the approach is the constraint-based workflow engine that utilizes this declarative model as input for a constraint solving algorithm. This algorithm computes the worklist, which is proposed to the process participant during workflow execution. With predefined deviation handling strategies that determine how the constraint model is modified in order to restore consistency, the support is continuous even in case of deviations.
The second major component of the proposed approach constitutes the case-based deviation management, which aims at improving the support of process participants on the basis of experiential knowledge. For the retrieve phase, a sophisticated similarity measure was developed that integrates specific characteristics of deviating workflows and combines several sequence similarity measures. Two alternative methods for the reuse phase were developed, a null adaptation and a generative adaptation. The null adaptation simply proposes tasks from the most similar workflow as work items, whereas the generative adaptation modifies the constraint-based workflow model based on the most similar workflow in order to re-enable the constraint-based workflow engine to suggest work items.
The experimental evaluation of the approach consisted of a simulation of several types of process participants in the exemplary domain of deficiency management in construction. The results showed high utility values and a promising potential for an investigation of the transfer on other domains and the applicability in practice, which is part of future work.
Concluding, the contributions are summarized and research perspectives are pointed out.
Energy transport networks are one of the most important infrastructures for the planned energy transition. They form the interface between energy producers and consumers and their features make them good candidates for the tools that mathematical optimization can offer. Nevertheless, the operation of energy networks comes with two major challenges. First, the nonconvexity of the equations that model the physics in the network render the resulting problems extremely hard to solve for large-scale networks. Second, the uncertainty associated to the behavior of the different agents involved, the production of energy, and the consumption of energy make the resulting problems hard to solve if a representative description of uncertainty is to be considered.
In this cumulative dissertation we study adaptive refinement algorithms designed to cope with the nonconvexity and stochasticity of equations arising in energy networks. Adaptive refinement algorithms approximate the original problem by sequentially refining the model of a simpler optimization problem. More specifically, in this thesis, the focus of the adaptive algorithm is on adapting the discretization and description of a set of constraints.
In the first part of this thesis, we propose a generalization of the different adaptive refinement ideas that we study. We sequentially describe model catalogs, error measures, marking strategies, and switching strategies that are used to set up the adaptive refinement algorithm. Afterward, the effect of the adaptive refinement algorithm on two energy network applications is studied. The first application treats the stationary operation of district heating networks. Here, the strength of adaptive refinement algorithms for approximating the ordinary differential equation that describes the transport of energy is highlighted. We introduce the resulting nonlinear problem, consider network expansion, and obtain realistic controls by applying the adaptive refinement algorithm. The second application concerns quantile-constrained optimization problems and highlights the ability of the adaptive refinement algorithm to cope with large scenario sets via clustering. We introduce the resulting mixed-integer linear problem, discuss generic solution techniques, make the link with the generalized framework, and measure the impact of the proposed solution techniques.
The second part of this thesis assembles the papers that inspired the contents of the first part of this thesis. Hence, they describe in detail the topics that are covered and will be referenced throughout the first part.
THE NONLOCAL NEUMANN PROBLEM
(2023)
Instead of presuming only local interaction, we assume nonlocal interactions. By doing so, mass
at a point in space does not only interact with an arbitrarily small neighborhood surrounding it,
but it can also interact with mass somewhere far, far away. Thus, mass jumping from one point to
another is also a possibility we can consider in our models. So, if we consider a region in space, this
region interacts in a local model at most with its closure. While in a nonlocal model this region may
interact with the whole space. Therefore, in the formulation of nonlocal boundary value problems
the enforcement of boundary conditions on the topological boundary may not suffice. Furthermore,
choosing the complement as nonlocal boundary may work for Dirichlet boundary conditions, but
in the case of Neumann boundary conditions this may lead to an overfitted model.
In this thesis, we introduce a nonlocal boundary and study the well-posedness of a nonlocal Neu-
mann problem. We present sufficient assumptions which guarantee the existence of a weak solution.
As in a local model our weak formulation is derived from an integration by parts formula. However,
we also study a different weak formulation where the nonlocal boundary conditions are incorporated
into the nonlocal diffusion-convection operator.
After studying the well-posedness of our nonlocal Neumann problem, we consider some applications
of this problem. For example, we take a look at a system of coupled Neumann problems and analyze
the difference between a local coupled Neumann problems and a nonlocal one. Furthermore, we let
our Neumann problem be the state equation of an optimal control problem which we then study. We
also add a time component to our Neumann problem and analyze this nonlocal parabolic evolution
equation.
As mentioned before, in a local model mass at a point in space only interacts with an arbitrarily
small neighborhood surrounding it. We analyze what happens if we consider a family of nonlocal
models where the interaction shrinks so that, in limit, mass at a point in space only interacts with
an arbitrarily small neighborhood surrounding it.
Survey data can be viewed as incomplete or partially missing from a variety of perspectives and there are different ways of dealing with this kind of data in the prediction and the estimation of economic quantities. In this thesis, we present two selected research contexts in which the prediction or estimation of economic quantities is examined under incomplete survey data.
These contexts are first the investigation of composite estimators in the German Microcensus (Chapters 3 and 4) and second extensions of multivariate Fay-Herriot (MFH) models (Chapters 5 and 6), which are applied to small area problems.
Composite estimators are estimation methods that take into account the sample overlap in rotating panel surveys such as the German Microcensus in order to stabilise the estimation of the statistics of interest (e.g. employment statistics). Due to the partial sample overlaps, information from previous samples is only available for some of the respondents, so the data are partially missing.
MFH models are model-based estimation methods that work with aggregated survey data in order to obtain more precise estimation results for small area problems compared to classical estimation methods. In these models, several variables of interest are modelled simultaneously. The survey estimates of these variables, which are used as input in the MFH models, are often partially missing. If the domains of interest are not explicitly accounted for in a sampling design, the sizes of the samples allocated to them can, by chance, be small. As a result, it can happen that either no estimates can be calculated at all or that the estimated values are not published by statistical offices because their variances are too large.
Coastal erosion describes the displacement of land caused by destructive sea waves,
currents or tides. Due to the global climate change and associated phenomena such as
melting polar ice caps and changing current patterns of the oceans, which result in rising
sea levels or increased current velocities, the need for countermeasures is continuously
increasing. Today, major efforts have been made to mitigate these effects using groins,
breakwaters and various other structures.
This thesis will find a novel approach to address this problem by applying shape optimization
on the obstacles. Due to this reason, results of this thesis always contain the
following three distinct aspects:
The selected wave propagation model, i.e. the modeling of wave propagation towards
the coastline, using various wave formulations, ranging from steady to unsteady descriptions,
described from the Lagrangian or Eulerian viewpoint with all its specialties. More
precisely, in the Eulerian setting is first a steady Helmholtz equation in the form of a
scattering problem investigated and followed subsequently by shallow water equations,
in classical form, equipped with porosity, sediment portability and further subtleties.
Secondly, in a Lagrangian framework the Lagrangian shallow water equations form the
center of interest.
The chosen discretization, i.e. dependent on the nature and peculiarity of the constraining
partial differential equation, we choose between finite elements in conjunction
with a continuous Galerkin and discontinuous Galerkin method for investigations in the
Eulerian description. In addition, the Lagrangian viewpoint offers itself for mesh-free,
particle-based discretizations, where smoothed particle hydrodynamics are used.
The method for shape optimization w.r.t. the obstacle’s shape over an appropriate
cost function, constrained by the solution of the selected wave-propagation model. In
this sense, we rely on a differentiate-then-discretize approach for free-form shape optimization
in the Eulerian set-up, and reverse the order in Lagrangian computations.
Behavioural traces from interactions with digital technologies are diverse and abundant. Yet, their capacity for theory-driven research is still to be constituted. In the present cumulative dissertation project, I deliberate the caveats and potentials of digital behavioural trace data in behavioural and social science research. One use case is online radicalisation research. The three studies included, set out to discern the state-of-the-art of methods and constructs employed in radicalization research, at the intersection of traditional methods and digital behavioural trace data. Firstly, I display, based on a systematic literature review of empirical work, the prevalence of digital behavioural trace data across different research strands and discern determinants and outcomes of radicalisation constructs. Secondly, I extract, based on this literature review, hypotheses and constructs and integrate them to a framework from network theory. This graph of hypotheses, in turn, makes the relative importance of theoretical considerations explicit. One implication of visualising the assumptions in the field is to systematise bottlenecks for the analysis of digital behavioural trace data and to provide the grounds for the genesis of new hypotheses. Thirdly, I provide a proof-of-concept for incorporating a theoretical framework from conspiracy theory research (as a specific form of radicalisation) and digital behavioural traces. I argue for marrying theoretical assumptions derived from temporal signals of posting behaviour and semantic meaning from textual content that rests on a framework from evolutionary psychology. In the light of these findings, I conclude by discussing important potential biases at different stages in the research cycle and practical implications.
No Longer Printing the Legend: The Aporia of Heteronormativity in the American Western (1903-1969)
(2023)
This study critically investigates the U.S.-American Western and its construction of sexuality and gender, revealing that the heteronormative matrix that is upheld and defended in the genre is consistently preceded by the exploration of alternative sexualities and ways to think gender beyond the binary. The endeavor to naturalize heterosexuality seems to be baked in the formula of the U.S.-Western. However, as I show in this study, this endeavor relies on an aporia, because the U.S.-Western can only ever attempt to naturalize gender by constructing it first, hence inevitably and simultaneously construct evidence that supports the opposite: the unnaturalness and contingency of gender and sexuality.
My study relies on the works of Raewyn Connell, Pierre Bourdieu, and Judith Butler, and amalgamates in its methodology established approaches from film and literary studies (i.e., close readings) with a Foucaultian understanding of discourse and discourse analysis, which allows me to relate individual texts to cultural, socio-political and economical contexts that invariably informed the production and reception of any filmic text. In an analysis of 14 U.S.-Westerns (excluding three excursions) that appeared between 1903 and 1969 I give ample and minute narrative and film-aesthetical evidence to reveal the complex and contradictory construction of gender and sexuality in the U.S.-Western, aiming to reveal both the normative power of those categories and its structural instability and inconsistency.
This study proofs that the Western up until 1969 did not find a stable pattern to represent the gender binary. The U.S.-Western is not necessarily always looking to confirm or stabilize governing constructs of (gendered) power. However, it without fail explores and negotiates its legitimacy. Heterosexuality and male hegemony are never natural, self-evident, incontestable, or preordained. Quite conversely: the U.S.-Western repeatedly – and in a surprisingly diverse and versatile way – reveals the illogical constructedness of the heteronormative matrix.
My study therefore offers a fresh perspective on the genre and shows that the critical exploration and negotiation of the legitimacy of heteronormativity as a way to organize society is constitutive for the U.S.-Western. It is the inquiry – not necessarily the affirmation – of the legitimacy of this model that gives the U.S.-Western its ideological currency and significance as an artifact of U.S.-American popular culture.