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This dissertation deals with consistent estimates in household surveys. Household surveys are often drawn via cluster sampling, with households sampled at the first stage and persons selected at the second stage. The collected data provide information for estimation at both the person and the household level. However, consistent estimates are desirable in the sense that the estimated household-level totals should coincide with the estimated totals obtained at the person-level. Current practice in statistical offices is to use integrated weighting. In this approach consistent estimates are guaranteed by equal weights for all persons within a household and the household itself. However, due to the forced equality of weights, the individual patterns of persons are lost and the heterogeneity within households is not taken into account. In order to avoid the negative consequences of integrated weighting, we propose alternative weighting methods in the first part of this dissertation that ensure both consistent estimates and individual person weights within a household. The underlying idea is to limit the consistency conditions to variables that emerge in both the personal and household data sets. These common variables are included in the person- and household-level estimator as additional auxiliary variables. This achieves consistency more directly and only for the relevant variables, rather than indirectly by forcing equal weights on all persons within a household. Further decisive advantages of the proposed alternative weighting methods are that original individual rather than the constructed aggregated auxiliaries are utilized and that the variable selection process is more flexible because different auxiliary variables can be incorporated in the person-level estimator than in the household-level estimator.
In the second part of this dissertation, the variances of a person-level GREG estimator and an integrated estimator are compared in order to quantify the effects of the consistency requirements in the integrated weighting approach. One of the challenges is that the estimators to be compared are of different dimensions. The proposed solution is to decompose the variance of the integrated estimator into the variance of a reduced GREG estimator, whose underlying model is of the same dimensions as the person-level GREG estimator, and add a constructed term that captures the effects disregarded by the reduced model. Subsequently, further fields of application for the derived decomposition are proposed such as the variable selection process in the field of econometrics or survey statistics.
In this thesis, we investigate the quantization problem of Gaussian measures on Banach spaces by means of constructive methods. That is, for a random variable X and a natural number N, we are searching for those N elements in the underlying Banach space which give the best approximation to X in the average sense. We particularly focus on centered Gaussians on the space of continuous functions on [0,1] equipped with the supremum-norm, since in that case all known methods failed to achieve the optimal quantization rate for important Gauss-processes. In fact, by means of Spline-approximations and a scheme based on the Best-Approximations in the sense of the Kolmogorov n-width we were able to attain the optimal rate of convergence to zero for these quantization problems. Moreover, we established a new upper bound for the quantization error, which is based on a very simple criterion, the modulus of smoothness of the covariance function. Finally, we explicitly constructed those quantizers numerically.
Soil organic matter (SOM) is an indispensable component of terrestrial ecosystems. Soil organic carbon (SOC) dynamics are influenced by a number of well-known abiotic factors such as clay content, soil pH, or pedogenic oxides. These parameters interact with each other and vary in their influence on SOC depending on local conditions. To investigate the latter, the dependence of SOC accumulation on parameters and parameter combinations was statistically assessed that vary on a local scale depending on parent material, soil texture class, and land use. To this end, topsoils were sampled from arable and grassland sites in south-western Germany in four regions with different soil parent material. Principal component analysis (PCA) revealed a distinct clustering of data according to parent material and soil texture that varied largely between the local sampling regions, while land use explained PCA results only to a small extent. The PCA clusters were differentiated into total clusters that contain the entire dataset or major proportions of it and local clusters representing only a smaller part of the dataset. All clusters were analysed for the relationships between SOC concentrations (SOC %) and mineral-phase parameters in order to assess specific parameter combinations explaining SOC and its labile fractions hot water-extractable C (HWEC) and microbial biomass C (MBC). Analyses were focused on soil parameters that are known as possible predictors for the occurrence and stabilization of SOC (e.g. fine silt plus clay and pedogenic oxides). Regarding the total clusters, we found significant relationships, by bivariate models, between SOC, its labile fractions HWEC and MBC, and the applied predictors. However, partly low explained variances indicated the limited suitability of bivariate models. Hence, mixed-effect models were used to identify specific parameter combinations that significantly explain SOC and its labile fractions of the different clusters. Comparing measured and mixed-effect-model-predicted SOC values revealed acceptable to very good regression coefficients (R2=0.41–0.91) and low to acceptable root mean square error (RMSE = 0.20 %–0.42 %). Thereby, the predictors and predictor combinations clearly differed between models obtained for the whole dataset and the different cluster groups. At a local scale, site-specific combinations of parameters explained the variability of organic carbon notably better, while the application of total models to local clusters resulted in less explained variance and a higher RMSE. Independently of that, the explained variance by marginal fixed effects decreased in the order SOC > HWEC > MBC, showing that labile fractions depend less on soil properties but presumably more on processes such as organic carbon input and turnover in soil.
Many real-life phenomena, such as computer systems, communication networks, manufacturing systems, supermarket checkout lines as well as structural military systems can be represented by means of queueing models. Looking at queueing models, a controller may considerably improve the system's performance by reducing queue lengths, or increasing the throughput, or diminishing the overhead, whereas in the absence of a controller the system behavior may get quite erratic, exhibiting periods of high load and long queues followed by periods, during which the servers remain idle. The theoretical foundations of controlled queueing systems are led in the theory of Markov, semi-Markov and semi-regenerative decision processes. In this thesis, the essential work consists in designing controlled queueing models and investigation of their optimal control properties for the application in the area of the modern telecommunication systems, which should satisfy the growing demands for quality of service (QoS). For two types of optimization criterion (the model without penalties and with set-up costs), a class of controlled queueing systems is defined. The general case of the queue that forms this class is characterized by a Markov Additive Arrival Process and heterogeneous Phase-Type service time distributions. We show that for these queueing systems the structural properties of optimal control policies, e.g. monotonicity properties and threshold structure, are preserved. Moreover, we show that these systems possess specific properties, e.g. the dependence of optimal policies on the arrival and service statistics. In order to practically use controlled stochastic models, it is necessary to obtain a quick and an effective method to find optimal policies. We present the iteration algorithm which can be successfully used to find an optimal solution in case of a large state space.
Many combinatorial optimization problems on finite graphs can be formulated as conic convex programs, e.g. the stable set problem, the maximum clique problem or the maximum cut problem. Especially NP-hard problems can be written as copositive programs. In this case the complexity is moved entirely into the copositivity constraint.
Copositive programming is a quite new topic in optimization. It deals with optimization over the so-called copositive cone, a superset of the positive semidefinite cone, where the quadratic form x^T Ax has to be nonnegative for only the nonnegative vectors x. Its dual cone is the cone of completely positive matrices, which includes all matrices that can be decomposed as a sum of nonnegative symmetric vector-vector-products.
The related optimization problems are linear programs with matrix variables and cone constraints.
However, some optimization problems can be formulated as combinatorial problems on infinite graphs. For example, the kissing number problem can be formulated as a stable set problem on a circle.
In this thesis we will discuss how the theory of copositive optimization can be lifted up to infinite dimension. For some special cases we will give applications in combinatorial optimization.
There is considerable evidence for an association between chronic dysregulation of the hypothalamus-pituitary adrenal (HPA) axis, atrophy of the hippocampus (HC) and cognitive and mood changes in clinical populations and in aging. The present thesis investigated this relationship in young healthy male subjects. Special emphasis was put on measures of HC volume and function derived from structural and functional magnetic resonance imaging (MRI). Higher cortisol levels after awakening were observed in subjects with higher levels of depressive symptomatology. Larger HC volume was associated with higher cortisol levels after awakening and in response to acute stress, whereas cognitive performance was impaired in subjects with larger HC volumes. Hippocampal activation during picture encoding was reduced after stress induction, and positive associations between activation and cognitive performance before stress were not present anymore afterwards. The present findings underscore the importance of structural and functional brain imaging for psychoneuroendocrinological research. The investigation of the association between cortisol levels and hippocampal integrity in young healthy subjects elicited unexpected results and adds to the understanding of HPA dysfunction and HC atrophy in clinical and aged populations.
Introduction:In patients with common variable immunodeficiency (CVID),immunological response is compromised. Knowledge about COVID‐19 in CVIDpatients is sparse. We, here, synthesize current research addressing the level ofthreat COVID‐19posestoCVIDpatientsandthebest‐known treatments.
Method:Review of 14 publications.
Results:The number of CVID patients with moderate to severe (~29%) andcritical infection courses (~10%), and the number of fatal cases (~13%), areincreased compared to the general picture of COVID‐19 infection. However,this might be an overestimate. Systematic cohort‐wide studies are lacking, andasymptomatic or mild cases among CVID patients occur that can easily remainunnoticed. Regular immunoglobulin replacement therapy was administered inalmost all patients, potentially explaining why the numbers of critical and fatalcases were not higher. In addition, the application of convalescent plasma wasdemonstrated to have positive effects.
Conclusions:COVID‐19 poses an elevated threat to CVID patients. However,only systematic studies can provide robust information on the extent of thisthreat. Regular immunoglobulin replacement therapy is beneficial to combatCOVID‐19 in CVID patients, and best treatment after infection includes theuse of convalescent plasma in addition to common medication.
Die räumliche Entwicklung von Städten und Regionen wird durch Trends wie Klimawandel, demographische Veränderungen und Strukturwandel beeinflusst, welche nicht an Verwaltungsgrenzen aufhören, sondern die Entwicklung großflächiger Gebiete bestimmen. Außerdem weisen Grenzräume häufig funktionale und thematische Verflechtungen auf, die über die nationalen Grenzen hinweg bestehen. Damit verbunden sind ein regelmäßiger Austausch und Abhängigkeiten zwischen Grenzräumen und deren Bewohnern. Daher ist die Koordination der grenzüberschreitenden Raumentwicklung entscheidend für eine zukunftsorientierte und nachhaltige räumliche Entwicklung. Aufgrund seiner hohen Bedeutung wird dieses Thema von europäischen Wissenschaftlern in der ersten Ausgabe der Themenhefte Borders in Perspective aus verschiedenen Perspektiven beleuchtet.
The glucocorticoid (GC) cortisol, main mediator of the hypothalamic-pituitary-adrenal axis, has many implications in metabolism, stress response and the immune system. GC function is mediated mainly via the glucocorticoid receptor (GR) which binds as a transcription factor to glucocorticoid response elements (GREs). GCs are strong immunosuppressants and used to treat inflammatory and autoimmune diseases. Long-term usage can lead to several irreversible side effects which make improved understanding indispensable and warrant the adaptation of current drugs. Several large scale gene expression studies have been performed to gain insight into GC signalling. Nevertheless, studies at the proteomic level have not yet been made. The effects of cortisol on monocytes and macrophages were studied in the THP-1 cell line using 2D fluorescence difference gel electrophoresis (2D DIGE) combined with MALDI-TOF mass spectrometry. More than 50 cortisol-modulated proteins were identified which belonged to five functional groups: cytoskeleton, chaperones, immune response, metabolism, and transcription/translation. Multiple GREs were found in the promoters of their corresponding genes (+10 kb/-0.2 kb promoter regions including all alternative promoters available within the Database for Transcription Start Sites (DBTSS)). High quality GREs were observed mainly in cortisol modulated genes, corroborating the proteomics results. Differential regulation of selected immune response related proteins were confirmed by qPCR and immuno-blotting. All immune response related proteins (MX1, IFIT3, SYWC, STAT3, PMSE2, PRS7) which were induced by LPS were suppressed by cortisol and belong mainly to classical interferon target genes. Mx1 has been selected for detailed expression analysis since new isoforms have been identified by proteomics. FKBP51, known to be induced by cortisol, was identified as the strongest differentially expressed protein and contained the highest number of strict GREs. Genomic analysis of five alternative FKBP5 promoter regions suggested GC inducibility of all transcripts. 2D DIGE combined with 2D immunoblotting revealed the existence of several previously unknown FKBP51 isoforms, possibly resulting from these transcripts. Additionally multiple post-translational modifications were found, which could lead to different subcellular localization in monocytes and macrophages as seen by confocal microscopy. Similar results were obtained for the different cellular subsets of human peripheral blood mononuclear cells (PBMCs). FKBP51 was found to be constitutively phosphorylated with up to 8 phosphosites in CD19+ B lymphocytes. Differential Co-immunoprecipitation for cytoplasm and nucleus allowed us to identify new potential interaction partners. Nuclear FKBP51 was found to interact with myosin 9, whereas cytosolic FKBP51 with TRIM21 (synonym: Ro52, Sjögren`s syndrome antigen). The GR has been found to interact with THOC4 and YB1, two proteins implicated in mRNA processing and transcriptional regulation. We also applied proteomics to study rapid non-genomic effects of acute stress in a rat model. The nuclear proteome of the thymus was investigated after 15 min restraint stress and compared to the non-stressed control. Most of the identified proteins were transcriptional regulators found to be enriched in the nucleus probably to assist gene expression in an appropriate manner. The proteomic approach allowed us to further understand the cortisol mediated response in monocytes/macrophages. We identified several new target proteins, but we also found new protein variants and post-translational modifications which need further investigation. Detailed study of FKBP51 and GR indicated a complex regulation network which opened a new field of research. We identified new variants of the anti-viral response protein MX1, displaying differential expression and phosphorylation in the cellular compartments. Further, proteomics allowed us to follow the very early effects of acute stress, which happen prior to gene expression. The nuclear thymocyte proteome of restraint stressed rats revealed an active preparation for subsequent gene expression. Proteomics was successfully applied to study differential protein expression, to identify new protein variants and phosphorylation events as well as to follow translocation. New aspects for future research in the field of cortisol-mediated immune modulation have been added.
Surveys play a major role in studying social and behavioral phenomena that are difficult to
observe. Survey data provide insights into the determinants and consequences of human
behavior and social interactions. Many domains rely on high quality survey data for decision
making and policy implementation including politics, health, business, and the social
sciences. Given a certain research question in a specific context, finding the most appropriate
survey design to ensure data quality and keep fieldwork costs low at the same time is a
difficult task. The aim of examining survey research methodology is to provide the best
evidence to estimate the costs and errors of different survey design options. The goal of this
thesis is to support and optimize the accumulation and sustainable use of evidence in survey
methodology in four steps:
(1) Identifying the gaps in meta-analytic evidence in survey methodology by a systematic
review of the existing evidence along the dimensions of a central framework in the
field
(2) Filling in these gaps with two meta-analyses in the field of survey methodology, one
on response rates in psychological online surveys, the other on panel conditioning
effects for sensitive items
(3) Assessing the robustness and sufficiency of the results of the two meta-analyses
(4) Proposing a publication format for the accumulation and dissemination of metaanalytic
evidence
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.
In order to classify smooth foliated manifolds, which are smooth maifolds equipped with a smooth foliation, we introduce the de Rham cohomologies of smooth foliated manifolds. These cohomologies are build in a similar way as the de Rham cohomologies of smooth manifolds. We develop some tools to compute these cohomologies. For example we proof a Mayer Vietoris theorem for foliated de Rham cohomology and show that these cohomologys are invariant under integrable homotopy. A generalization of a known Künneth formula, which relates the cohomologies of a product foliation with its factors, is discussed. In particular, this envolves a splitting theory of sequences between Frechet spaces and a theory of projective spectrums. We also prove, that the foliated de Rham cohomology is isomorphic to the Cech-de Rham cohomology and the Cech cohomology of leafwise constant functions of an underlying so called good cover.
This dissertation investigates corporate acquisition decisions that represent important corporate development activities for family and non-family firms. The main research objective of this dissertation is to generate insights into the subjective decision-making behavior of corporate decision-makers from family and non-family firms and their weighting of M&A decision-criteria during the early pre-acquisition target screening and selection process. The main methodology chosen for the investigation of M&A decision-making preferences and the weighting of M&A decision criteria is a choice-based conjoint analysis. The overall sample of this dissertation consists of 304 decision-makers from 264 private and public family and non-family firms from mainly Germany and the DACH-region. In the first empirical part of the dissertation, the relative importance of strategic, organizational and financial M&A decision-criteria for corporate acquirers in acquisition target screening is investigated. In addition, the author uses a cluster analysis to explore whether distinct decision-making patterns exist in acquisition target screening. In the second empirical part, the dissertation explores whether there are differences in investment preferences in acquisition target screening between family and non-family firms and within the group of family firms. With regards to the heterogeneity of family firms, the dissertation generated insights into how family-firm specific characteristics like family management, the generational stage of the firm and non-economic goals such as transgenerational control intention influences the weighting of different M&A decision criteria in acquisition target screening. The dissertation contributes to strategic management research, in specific to M&A literature, and to family business research. The results of this dissertation generate insights into the weighting of M&A decision-making criteria and facilitate a better understanding of corporate M&A decisions in family and non-family firms. The findings show that decision-making preferences (hence the weighting of M&A decision criteria) are influenced by characteristics of the individual decision-maker, the firm and the environment in which the firm operates.
Representation Learning techniques play a crucial role in a wide variety of Deep Learning applications. From Language Generation to Link Prediction on Graphs, learned numerical vector representations often build the foundation for numerous downstream tasks.
In Natural Language Processing, word embeddings are contextualized and depend on their current context. This useful property reflects how words can have different meanings based on their neighboring words.
In Knowledge Graph Embedding (KGE) approaches, static vector representations are still the dominant approach. While this is sufficient for applications where the underlying Knowledge Graph (KG) mainly stores static information, it becomes a disadvantage when dynamic entity behavior needs to be modelled.
To address this issue, KGE approaches would need to model dynamic entities by incorporating situational and sequential context into the vector representations of entities. Analogous to contextualised word embeddings, this would allow entity embeddings to change depending on their history and current situational factors.
Therefore, this thesis provides a description of how to transform static KGE approaches to contextualised dynamic approaches and how the specific characteristics of different dynamic scenarios are need to be taken into consideration.
As a starting point, we conduct empirical studies that attempt to integrate sequential and situational context into static KG embeddings and investigate the limitations of the different approaches. In a second step, the identified limitations serve as guidance for developing a framework that enables KG embeddings to become truly dynamic, taking into account both the current situation and the past interactions of an entity. The two main contributions in this step are the introduction of the temporally contextualized Knowledge Graph formalism and the corresponding RETRA framework which realizes the contextualisation of entity embeddings.
Finally, we demonstrate how situational contextualisation can be realized even in static environments, where all object entities are passive at all times.
For this, we introduce a novel task that requires the combination of multiple context modalities and their integration with a KG based view on entity behavior.
Estimation and therefore prediction -- both in traditional statistics and machine learning -- encounters often problems when done on survey data, i.e. on data gathered from a random subset of a finite population. Additional to the stochastic generation of the data in the finite population (based on a superpopulation model), the subsetting represents a second randomization process, and adds further noise to the estimation. The character and impact of the additional noise on the estimation procedure depends on the specific probability law for subsetting, i.e. the survey design. Especially when the design is complex or the population data is not generated by a Gaussian distribution, established methods must be re-thought. Both phenomena can be found in business surveys, and their combined occurrence poses challenges to the estimation.
This work introduces selected topics linked to relevant use cases of business surveys and discusses the role of survey design therein: First, consider micro-econometrics using business surveys. Regression analysis under the peculiarities of non-normal data and complex survey design is discussed. The focus lies on mixed models, which are able to capture unobserved heterogeneity e.g. between economic sectors, when the dependent variable is not conditionally normally distributed. An algorithm for survey-weighted model estimation in this setting is provided and applied to business data.
Second, in official statistics, the classical sampling randomization and estimators for finite population totals are relevant. The variance estimation of estimators for (finite) population totals plays a major role in this framework in order to decide on the reliability of survey data. When the survey design is complex, and the number of variables is large for which an estimated total is required, generalized variance functions are popular for variance estimation. They allow to circumvent cumbersome theoretical design-based variance formulae or computer-intensive resampling. A synthesis of the superpopulation-based motivation and the survey framework is elaborated. To the author's knowledge, such a synthesis is studied for the first time both theoretically and empirically.
Third, the self-organizing map -- an unsupervised machine learning algorithm for data visualization, clustering and even probability estimation -- is introduced. A link to Markov random fields is outlined, which to the author's knowledge has not yet been established, and a density estimator is derived. The latter is evaluated in terms of a Monte-Carlo simulation and then applied to real world business data.
This dissertation looked at both design-based and model-based estimation for rare and clustered populations using the idea of the ACS design. The ACS design (Thompson, 2012, p. 319) starts with an initial sample that is selected by a probability sampling method. If any of the selected units meets a pre-specified condition, its neighboring units are added to the sample and observed. If any of the added units meets the pre-specified condition, its neighboring units are further added to the sample and observed. The procedure continues until there are no more units that meet the pre-specified condition. In this dissertation, the pre-specified condition is the detection of at least one animal in a selected unit. In the design-based estimation, three estimators were proposed under three specific design setting. The first design was stratified strip ACS design that is suitable for aerial or ship surveys. This was a case study in estimating population totals of African elephants. In this case, units/quadrant were observed only once during an aerial survey. The Des Raj estimator (Raj, 1956) was modified to obtain an unbiased estimate of the population total. The design was evaluated using simulated data with different levels of rarity and clusteredness. The design was also evaluated on real data of African elephants that was obtained from an aerial census conducted in parts of Kenya and Tanzania in October (dry season) 2013. In this study, the order in which the samples were observed was maintained. Re-ordering the samples by making use of the Murthy's estimator (Murthy, 1957) can produce more efficient estimates. Hence a possible extension of this study. The computation cost resulting from the n! permutations in the Murthy's estimator however, needs to be put into consideration. The second setting was when there exists an auxiliary variable that is negatively correlated with the study variable. The Murthy's estimator (Murthy, 1964) was modified. Situations when the modified estimator is preferable was given both in theory and simulations using simulated and two real data sets. The study variable for the real data sets was the distribution and counts of oryx and wildbeest. This was obtained from an aerial census that was conducted in parts of Kenya and Tanzania in October (dry season) 2013. Temperature was the auxiliary variable for two study variables. Temperature data was obtained from R package raster. The modified estimator provided more efficient estimates with lower bias compared to the original Murthy's estimator (Murthy, 1964). The modified estimator was also more efficient compared to the modified HH and the modified HT estimators of (Thompson, 2012, p. 319). In this study, one auxiliary variable is considered. A fruitful area for future research would be to incorporate multi-auxiliary information at the estimation phase of an ACS design. This could, in principle, be done by using for instance a multivariate extension of the product estimator (Singh, 1967) or by using the generalized regression estimator (Särndal et al., 1992). The third case under design-based estimation, studied the conjoint use of the stopping rule (Gattone and Di Battista, 2011) and the use of the without replacement of clusters (Dryver and Thompson, 2007). Each of these two methods was proposed to reduce the sampling cost though the use of the stopping rule results in biased estimates. Despite this bias, the new estimator resulted in higher efficiency gain in comparison to the without replacement of cluster design. It was also more efficient compared to the stratified design which is known to reduce final sample size when networks are truncated at stratum boundaries. The above evaluation was based on simulated and real data. The real data was the distribution and counts of hartebeest, elephants and oryx obtained in the same census as above. The bias attributed by the stopping rule has not been evaluated analytically. This may not be direct since the truncated network formed depends on the initial unit sampled (Gattone et al., 2016a). This and the order of the bias however, deserves further investigation as it may help in understanding the effect of the increase in the initial sample size together with the population characteristics on the efficiency of the proposed estimator. Chapter four modeled data that was obtained using the stratified strip ACS (as described in sub-section (3.1)). This was an extension of the model of Rapley and Welsh (2008) by modeling data that was obtained from a different design, the introduction of an auxiliary variable and the use of the without replacement of clusters mechanism. Ideally, model-based estimation does not depend on the design or rather how the sample was obtained. This is however, not the case if the design is informative; such as the ACS design. In this case, the procedure that was used to obtain the sample was incorporated in the model. Both model-based and design-based simulations were conducted using artificial and real data. The study and the auxiliary variable for the real data was the distribution and counts of elephants collected during an aerial census in parts of Kenya and Tanzania in October (dry season) and April (wet season) 2013 respectively. Areas of possible future research include predicting the population total of African elephants in all parks in Kenya. This can be achieved in an economical and reliable way by using the theory of SAE. Chapter five compared the different proposed strategies using the elephant data. Again the study variable was the elephant data from October (dry season) 2013 and the auxiliary variable was the elephant data from April (wet season) 2013. The results show that the choice of particular strategy to use depends on the characteristic of the population under study and the level and the direction of the correlation between the study and the auxiliary variable (if present). One general area of the ACS design that is still behind, is the implementation of the design in the field especially on animal populations. This is partly attributed by the challenges associated with the field implementation, some of which were discussed in section 2.3. Green et al. (2010) however, provides new insights in undertaking the ACS design during an aerial survey such as how the aircraft should turn while surveying neighboring units. A key point throughout the dissertation is the reduction of cost during a survey which can be seen by the reduction in the number of units in the final sample (through the use of stopping rule, use of stratification and truncating networks at stratum boundaries) and ensuring that units are observed only once (by using the without replacement of cluster sampling technique). The cost of surveying an edge unit(s) is assumed to be low in which case the efficiency of the ACS design relative to the non-adaptive design is achieved (Thompson and Collins, 2002). This is however not the case in aerial surveys as the aircraft flies at constant speed and height (Norton-Griffiths, 1978). Hence the cost of surveying an edge unit is the same as the cost of surveying a unit that meets the condition of interest. The without replacement of cluster technique plays a greater role of reducing the cost of sampling in such surveys. Other key points that motivated the sections in the dissertation include gains in efficiency (in all sections) and practicability of the designs in the specific setting. Even though the dissertation focused on animal populations, the methods can as well be implemented in any population that is rare and clustered such as in the study of forestry, plants, pollution, minerals and so on.
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.
Designing a Randomized Trial with an Age Simulation Suit—Representing People with Health Impairments
(2020)
Due to demographic change, there is an increasing demand for professional care services, whereby this demand cannot be met by available caregivers. To enable adequate care by relieving informal and formal care, the independence of people with chronic diseases has to be preserved for as long as possible. Assistance approaches can be used that support promoting physical activity, which is a main predictor of independence. One challenge is to design and test such approaches without affecting the people in focus. In this paper, we propose a design for a randomized trial to enable the use of an age simulation suit to generate reference data of people with health impairments with young and healthy participants. Therefore, we focus on situations of increased physical activity.
Forest inventories provide significant monitoring information on forest health, biodiversity,
resilience against disturbance, as well as its biomass and timber harvesting potential. For this
purpose, modern inventories increasingly exploit the advantages of airborne laser scanning (ALS)
and terrestrial laser scanning (TLS).
Although tree crown detection and delineation using ALS can be seen as a mature discipline, the
identification of individual stems is a rarely addressed task. In particular, the informative value of
the stem attributes—especially the inclination characteristics—is hardly known. In addition, a lack
of tools for the processing and fusion of forest-related data sources can be identified. The given
thesis addresses these research gaps in four peer-reviewed papers, while a focus is set on the
suitability of ALS data for the detection and analysis of tree stems.
In addition to providing a novel post-processing strategy for geo-referencing forest inventory plots,
the thesis could show that ALS-based stem detections are very reliable and their positions are
accurate. In particular, the stems have shown to be suited to study prevailing trunk inclination
angles and orientations, while a species-specific down-slope inclination of the tree stems and a
leeward orientation of conifers could be observed.
Detection of Preferential Water Flow by Electrical Resistivity Tomography and Self-Potential Method
(2021)
This study explores the hydrogeological conditions of a landslide-prone hillslope in the Upper Mosel valley, Luxembourg. The investigation program included the monitoring of piezometer wells, hydrogeological field tests, analysis of drillcore records, and geophysical surveys. Monitoring and field testing in some of the observation wells indicated very pronounced preferential flow. Electrical resistivity tomography (ERT) and self-potential geophysical methods were employed in the study area for exploration of the morphology of preferential flowpaths. Possible signals associated with flowing groundwater in the subsurface were detected; however, they were diffusively spread over a relatively large zone, which did not allow for the determination of an exact morphology of the conduit. Analysis of drillcore records indicated that flowpaths are caused by the dissolution of thin gypsum interlayers in marls. For better understanding of the site’s hydrogeological settings, a 3D hydrogeological model was compiled. By applying different subsurface flow mechanisms, a hydrogeological model with thin, laterally extending flowpaths embedded in a porous media matrix showed the best correspondence with field observations. Simulated groundwater heads in a preferential flow conduit exactly corresponded with the observed heads in the piezometer wells. This study illustrates how hydrogeological monitoring and geophysical surveys in conjunction with the newest hydrogeological models allow for better conceptualization and parametrization of preferential flow.
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.
It has been the overall aim of this research work to assess the potential of hyperspectral remote sensing data for the determination of forest attributes relevant to forest ecosystem simulation modeling and forest inventory purposes. A number of approaches for the determination of structural and chemical attributes from hyperspectral remote sensing have been applied to the collected data sets. Many of the methods to be found in the literature were up to now just applied to broadband multispectral data, applied to vegetation canopies other than forests, reported to work on the leaf level or with modelled data, not validated with ground truth data, or not systematically compared to other methods. Attributes that describe the properties of the forest canopy and that are potentially open to remote sensing were identified, appropriate methods for their retrieval were implemented and field, laboratory and image data (HyMap sensor) were acquired over a number of forest plots. The study on structural attributes compared statistical and physical approaches. In the statistical section, linear predictive models between vegetation indices derived from HyMap data and field measurements of structural forest stand attributes were systematically evaluated. The study demonstrates that for hyperspectral image data, linear regression models can be applied to quantify leaf area index and crown volume with good accuracy. For broadband multispectral data, the accuracy was generally lower. The physically-based approach used the invertible forest reflectance model (INFORM), a combination of well established sub-models FLIM, SAIL and LIBERTY. The model was inverted with HyMap data using a neural network approach. In comparison to the statistical approach, it could be shown that the reflectance model inversion works equally well. In opposition to empirically derived prediction functions that are generally limited to the local conditions at a certain point in time and to a specified sensor type, the calibrated reflectance model can be applied more easily to different optical remote sensing data acquired over central European forests. The study on chemical forest attributes evaluated the information content of HyMap data for the estimation of nitrogen, chlorophyll and water concentration. A number of needle samples of Norway spruce were analysed for their total chlorophyll, nitrogen and water concentrations. The chemical data was linked to needle spectra measured in the laboratory and canopy spectra measured by the HyMap sensor. Wavebands selected in statistical models were often located in spectral regions that are known to be important for chlorophyll detection (red edge, green peak). Predictive models were applied on the HyMap image to compute maps of chlorophyll concentration and nitrogen concentration. Results of map overlay operations revealed coherence between total chlorophyll and zones of stand development stage and between total chlorophyll and zones of soil type. Finally, it can be stated that the hyperspectral remote sensing data generally contains more information relevant to the estimation of the forest attributes compared to multispectral data. Structural forest attributes, except biomass, can be determined with good accuracy from a hyperspectral sensor type like HyMap. Among the chemical attributes, chlorophyll concentration can be determined with good accuracy and nitrogen concentration with moderate accuracy. For future research, additional dimensions have to be taken into account, for instance through exploitation of multi-view angle data. Additionally, existing forest canopy reflectance models should be further improved.
The classic Capital Asset Pricing Model and the portfolio theory suggest that investors hold the market portfolio to diversify idiosyncratic risks. The theory predicts that expected return of assets is positive and that reacts linearly on the overall market. However, in reality, we observe that investors often do not have perfectly diversified portfolios. Empirical studies find that new factors influence the deviation from the theoretical optimal investment. In the first part of this work (Chapter 2) we study such an example, namely the influence of maximum daily returns on subsequent returns. Here we follow ideas of Bali et al. (2011). The goal is to find cross-sectional relations between extremely positive returns and expected average returns. We take account a larger number of markets worldwide. Bali et al. (2011) report with respect to the U.S. market a robust negative relation between MAX (the maximum daily return) and the expected return in the subsequent time. We extent substantially their database to a number of other countries, and also take more recent data into account (until end of 2009). From that we conclude that the relation between MAX and expected returns is not consistent in all countries. Moreover, we test the robustness of the results of Bali et al. (2011) in two time-periods using the same data from CRSP. The results show that the effect of extremely positive returns is not stable over time. Indeed we find a negative cross-sectional relation between the extremely positive returns and the average returns for the first half of the time series, however, we do not find significant effects for the second half. The main results of this chapter serve as a basis for an unpublished working paper Yuan and Rieger (2014b). While in Chapter 2 we have studied factors that prevent optimal diversification, we consider in Chapter 3 and 4 situations where the optimal structure of diversification was previously unknown, namely diversification of options (or structured financial products). Financial derivatives are important additional investment form with respect to diversification. Not only common call and put options, but also structured products enable investors to pursue a multitude of investment strategies to improve the risk-return profile. Since derivatives become more and more important, diversification of portfolios with dimension of derivatives is of particularly practical relevance. We investigate the optimal diversification strategies in connection with underlying stocks for classical rational investors with constant relative risk aversion (CRRA). In particular, we apply Monte Carlo method based on the Black-Scholes model and the Heston model for stochastic volatility to model the stock market processes and the pricing of the derivatives. Afterwards, we compare the benchmark portfolio which consists of derivatives on single assets with derivatives on the index of these assets. First we compute the utility improvement of an investment in the risk-free assets and plain-vanilla options for CRRA investors in various scenarios. Furthermore, we extend our analysis to several kinds of structured products, in particular capital protected notes (CPNs), discount certificates (DCs) and bonus certificates (BCs). We find that the decision of an investor between these two diversification strategies leads to remarkable differences. The difference in the utility improvement is influenced by risk-preferences of investors, stock prices and the properties of the derivatives in the portfolio. The results will be presented in Chapter 3 and are the basis for a yet unpublished working paper Yuan and Rieger (2014a). To check furthermore whether underlyings of structured products influence decisions of investors, we discuss explicitly the utility gain of a stock-based product and an index-based product for an investor whose preferences are described by cumulative prospect theory (CPT) (Chapter 4, compare to Yuan (2014)). The goal is that to investigate the dependence of structured products on their underlying where we put emphasis on the difference between index-products and single-stock-products, in particular with respect to loss-aversion and mental accounting. We consider capital protected notes and discount certificates as examples, and model the stock prices and the index of these stocks via Monte Carlo simulations in the Black-Scholes framework. The results point out that market conditions, particularly the expected returns and volatility of the stocks play a crucial role in determining the preferences of investors for stock-based CPNs and index-based CPNs. A median CPT investor prefers the index-based CPNs if the expected return is higher and the volatility is lower, while he prefers the stock-based CPNs in the other situation. We also show that index-based DCs are robustly more attractive as compared to stock-based DCs for CPT investors.
A big challenge for agriculture in the 21st century is the provision of food safety to fast growing world- population, which not only demands the well utilisation of the available agricultural resources but also to develop new advancements in the mass production of food crops. Wheat is the third largest food crop of the world and Pakistan is the eighth largest wheat producing country globally. Rice is the second most important staple food of Pakistan after wheat, grown in all provinces of the country. Maize is the world- top ranking food crop followed by wheat and rice. The harvested produts have to be stored in different types of storage structures on small or large scale for food as well as seed purpose. In Pakistan, the harvested grains are stored for the whole year till the introduction of fresh produce in order to ensure the regular food supply throughout the year. However, it is this extended storage period making the commodity more vulnerable to insect attacks. Rhyzopertha dominica (Coleoptera: Bostrychidae), Cryptolestes ferrugineus (Coleoptera: Laemophloeidae), Tribolium castaneum (Coleoptera: Tenebrionidae) and Liposcelis spp. (Psocoptera: Liposcelididae) are the major and most damaging insect pests of stored products all around the world. Various management strategies have been adopted for stored grain insect pests mostly relying upon the use of a broad spectrum of insecticides, but the injudicious use of these chemicals raised various environmental and human health related issues, which necessitate the safe use of the prevailing control measures and evaluation of new and alternative control methods. The application of new chemical insecticides, microbial insecticides (particularly entomopathogenic fungi) and the use of inert dusts (diatomaceous earths) is believed amongst the potential alternatives to generally used insecticides in stored grain insect management system. In the current investigations, laboratory bioassays conducted to evaluate the effects of combining Imidacloprid (new chemistry insecticide) with and without Protect-It (diatomaceous earth formulation) against R. dominica, L. paeta, C. ferrugineus and T. castaneum, on three different grain commodities (i.e. wheat, maize and rice) revealed differences in adult mortality levels among grains and insect species tested. Individually, Imidacloprid was more effective as compared with Protect-It alone and the highest numbers of dead adults were recorded in wheat. The insecticidal efficacy of B. bassiana with Protect-It and DEBBM was also assessed against all test insect species under laboratory conditions. The findings of these studies revealed that the more extended exposure period and the higher combined application rate of B. bassiana and DEs provided the highest mortality of the test insect species. The progeny emergence of each insect species was also greatly suppressed where the highest dose rates of the combined treatments were applied. The residual efficacy of all three control measures Imidacloprid, B. bassiana and DEBBM formulation was also evaluated against all test insect species. The bioassays were carried out after grain treatments and monthly for 6 months. The results indicated that the adult mortality of each test insect species was decreased within the six month storage period, and the integarted application of the test grain protectants enhanced the mortality rates than their alone treatments. The maximum mortality was noted in the combined treatment of DEBBM with Imidacloprid. At the end, the effectiveness of B. bassiana, DEBBM and Imidacloprid applied alone as well as in combinations, against all above mentioned test insect species was also evaluated under field conditions in trials conducted in four districts of Punjab, Pakistan. For each district, a significant difference was observed between treatments, while the combined treatments gave better control of test species as compared with them alone. The least number of surviving adults and minimum percentage of grain damage was observed for the DEBBM and Imidacloprid combination, but DEBBM with B. bassiana provided the best long-term protection as compared with the remaining treatments.
Tropospheric ozone (O3) is known to have various detrimental effects on plants, such as visible leaf injury, reduced growth and premature senescence. Flux models offer the determination of the harmful ozone dose entering the plant through the stomata. This dose can then be related to phytotoxic effects mentioned above to obtain dose-response relationships, which are a helpful tool for the formulation of abatement strategies of ozone precursors. rnOzone flux models are dependant on the correct estimation of stomatal conductance (gs). Based on measurements of gs, an ozone flux model for two white clover clones (Trifolium repens L. cv Regal; NC-S (ozone-sensitive) and NC-R (ozone-resistant)) differing in their sensitivity to ozone was developed with the help of artificial neural networks (ANNs). White clover is an important species of various European grassland communities. The clover plants were exposed to ambient air at three sites in the Trier region (West Germany) during five consecutive growing seasons (1997 to 2001). The response parameters visible leaf injury and biomass ratio of NC-S/NC-R clone were regularly assessed. gs-measurements of both clones functioned as output of the ANN-based gs model, while corresponding climate parameters (i.e. temperature, vapour pressure deficit (VPD) and photosynthetic active radiation (PAR)) and various ozone concentration indices were inputs. The development of the model was documented in detail and various model evaluation techniques (e.g. sensitivity analysis) were applied. The resulting gs model was used as a basis for ozone flux calculations, which were related to above mentioned response parameters. rnThe results showed that the ANNs were capable of revealing and learning the complex relationship between gs and key meteorological parameters and ozone concentration indices. The dose-response relationships between ozone fluxes and visible leaf injury were reasonably strong, while those between ozone fluxes and NC-S/NC-R biomass ratio were fairly weak. The results were discussed in detail with respect to the suitability of the chosen experimental methods and model type.
Educational assessment tends to rely on more or less standardized tests, teacher judgments, and observations. Although teachers spend approximately half of their professional conduct in assessment-related activities, most of them enter their professional life unprepared, as classroom assessment is often not part of their educational training. Since teacher judgments matter for the educational development of students, the judgments should be up to a high standard. The present dissertation comprises three studies focusing on accuracy of teacher judgments (Study 1), consequences of (mis-)judgment regarding teacher nomination for gifted programming (Study 2) and teacher recommendations for secondary school tracks (Study 3), and individual student characteristics that impact and potentially bias teacher judgment (Studies 1 through 3). All studies were designed to contribute to a further understanding of classroom assessment skills of teachers. Overall, the results implied that, teacher judgment of cognitive ability was an important constant for teacher nominations and recommendations but lacked accuracy. Furthermore, teacher judgments of various traits and school achievement were substantially related to social background variables, especially the parents" educational background. However, multivariate analysis showed social background variables to impact nomination and recommendation only marginally if at all. All results indicated differentiated but potentially biased teacher judgments to impact their far-reaching referral decisions directly, while the influence of social background on the referral decisions itself seems mediated. Implications regarding further research practices and educational assessment strategies are discussed. The implications on the needs of teachers to be educated on judgment and educational assessment are of particular interest and importance.
My dissertation is concerned with contemporary (Anglo-)Canadian immigrant fiction and proposes an analytic grid with which it may be appreciated and compared more adequately. As a starting-point serves the general observation that the works of many Canadian immigrant writers are characterised by a focus on their respective home cultures as well as on their Canadian host culture. Following the ground-breaking work of Northrop Frye, Margaret Atwood and David Staines, the categories of "there" and "here" are suggested in order to reflect this double encoding of Canadian immigrant literature. However, "here" and "there" are more than spatial configurations in that they represent a concern with issues of multiculturalism and postcolonialism. Both of which are informed by an emphasis on difference and identity, and difference and identity are also what the narratives of M.G. Vassanji, Neil Bissoondath and Rohinton Mistry are preoccupied with. My study sets out to show two things: On the one hand, it attempts to exemplify the complexity and interrelatedness of "there" and "here" in a representative fashion. Hence in their treatments of difference, M.G. Vassanji, Neil Bissoondath and Rohinton Mistry come up with comparable identity constructions "here" and "there" respectively. On the other hand, special attention is paid to the strategies by which Vassanji, Bissoondath and Mistry construct difference and corroborate their respective understandings of identity.
Perennial energy crops (PECs) are increasingly used as feedstock to produce energy in an environmental friendly way. Compared to traditional conversion strategies like thermal use, sophisticated technologies such as biomethanation defined different re-quirements of the feedstock. Whereas the first concept relies on dry, woody mate-rial, biomethanation requires a moist feedstock. Thus, over time, the spectrum of species used as PECs has widened. Moreover, harvest dates were adjusted to pro-vide the feedstock at suitable moisture contents. It is well known that perennial, lignocellulose- based energy crops, compared to annual, sugar- and starch- based ones, offer ecological advantages such as, inter alia, improving biodiversity in landscape, protecting soil against erosion, and protecting groundwater from nutrient inputs. However, one of the main arguments for PEC cultivation was their undemanding nature concerning external inputs. With respect to the broader spectrum of PEC spe-cies and changed harvest dates, the question arises whether the concept of PECs being low- input energy crops is still valid. This also implies the question of suitable grow-ing conditions and sustainable management. The aims of this opinion paper were to classify different PECs according to their life- form strategy, compare nutrient exports when harvested in different maturation stages, and to discuss the results in the context of sustainable PEC cultivation on marginal land. This study revealed that nutrient exports with yield biomass of PECs harvested in green state are in the same range than those of annual energy crops and therewith several times higher than those of PECs harvested in brown state or of woody short rotation coppices. Thus, PECs can-not universally be claimed as low- input energy crops. These results also imply the consequences of cultivation of PECs on marginal land. Finally, the question has to be raised whether the term PECs should prospectively be better specified in written and spoken words.
The German Mittelstand is closely linked to the success of the German economy. Mittelstand firms, thereof numerous Hidden Champions, significantly contribute to Germany’s economic performance, innovation, and export strength. However, the advancing digitalization poses complex challenges for Mittelstand firms. To benefit from the manifold opportunities offered by digital technologies and to defend or even expand existing market positions, Mittelstand firms must transform themselves and their business models. This dissertation uses quantitative methods and contributes to a deeper understanding of the distinct needs and influencing factors of the digital transformation of Mittelstand firms. The results of the empirical analyses of a unique database of 525 mid-sized German manufacturing firms, comprising both firm-related information and survey data, show that organizational capabilities and characteristics significantly influence the digital transformation of Mittelstand firms. The results support the assumption that dynamic capabilities promote the digital transformation of such firms and underline the important role of ownership structure, especially regarding family influence, for the digital transformation of the business model and the pursuit of growth goals with digitalization. In addition to the digital transformation of German Mittelstand firms, this dissertation examines the economic success and regional impact of Hidden Champions and hence, contributes to a better understanding of the Hidden Champion phenomenon. Using quantitative methods, it can be empirically proven that Hidden Champions outperform other mid-sized firms in financial terms and promote regional development. Consequently, the results of this dissertation provide valuable research contributions and offer various practical implications for firm managers and owners as well as policy makers.
This work investigates the industrial applicability of graphics and stream processors in the field of fluid simulations. For this purpose, an explicit Runge-Kutta discontinuous Galerkin method in arbitrarily high order is implemented completely for the hardware architecture of GPUs. The same functionality is simultaneously realized for CPUs and compared to GPUs. Explicit time steppings as well as established implicit methods are under consideration for the CPU. This work aims at the simulation of inviscid, transsonic flows over the ONERA M6 wing. The discontinuities which typically arise in hyperbolic equations are treated with an artificial viscosity approach. It is further investigated how this approach fits into the explicit time stepping and works together with the special architecture of the GPU. Since the treatment of artificial viscosity is close to the simulation of the Navier-Stokes equations, it is reviewed how GPU-accelerated methods could be applied for computing viscous flows. This work is based on a nodal discontinuous Galerkin approach for linear hyperbolic problems. Here, it is extended to non-linear problems, which makes the application of numerical quadrature obligatory. Moreover, the representation of complex geometries is realized using isoparametric mappings. Higher order methods are typically very sensitive with respect to boundaries which are not properly resolved. For this purpose, an approach is presented which fits straight-sided DG meshes to curved geometries which are described by NURBS surfaces. The mesh is modeled as an elastic body and deformed according to the solution of closest point problems in order to minimize the gap to the original spline surface. The sensitivity with respect to geometry representations is reviewed in the end of this work in the context of shape optimization. Here, the aerodynamic drag of the ONERA M6 wing is minimized according to the shape gradient which is implicitly smoothed within the mesh deformation approach. In this context a comparison to the classical Laplace-Beltrami operator is made in a Stokes flow situation.
The forensic application of phonetics relies on individuality in speech. In the forensic domain, individual patterns of verbal and paraverbal behavior are of interest which are readily available, measurable, consistent, and robust to disguise and to telephone transmission. This contribution is written from the perspective of the forensic phonetic practitioner and seeks to establish a more comprehensive concept of disfluency than previous studies have. A taxonomy of possible variables forming part of what can be termed disfluency behavior is outlined. It includes the “classical” fillers, but extends well beyond these, covering, among others, additional types of fillers as well as prolongations, but also the way in which fillers are combined with pauses. In the empirical section, the materials collected for an earlier study are re-examined and subjected to two different statistical procedures in an attempt to approach the issue of individuality. Recordings consist of several minutes of spontaneous speech by eight speakers on three different occasions. Beyond the established set of hesitation markers, additional aspects of disfluency behavior which fulfill the criteria outlined above are included in the analysis. The proportion of various types of disfluency markers is determined. Both statistical approaches suggest that these speakers can be distinguished at a level far above chance using the disfluency data. At the same time, the results show that it is difficult to pin down a single measure which characterizes the disfluency behavior of an individual speaker. The forensic implications of these findings are discussed.
This doctoral dissertation examines two authors of German descent who are representatives for the development of Canadian literature and its regional focus on the prairies: Frederick Philip Grove (1879-1948) and Robert Kroetsch (*1927). Kroetsch, in his essays and talks, has repeatedly referred to Grove as one of his "literary ancestors". Although there exist monographs and numerous articles on both authors, the present study is the first-ever comparative approach. This study's main access is provided by the motif of disguise and masquerade, which plays a central role in the authors' works. Even if critics have looked at the traditional motif (cf. Homer's Odyssey, or many Renaissance plays) in Kroetsch's writing sporadically, and have used it to examine Grove's biography, no approach has attempted a larger contextualization within/among both writers' oeuvres. According to Lloyd Davis, however, the motif can be seen as "representing the cultural dialogism, rather than any particular thesis, of selfhood" (Davis 16). Hence, it helps interrogate a topic that within Canada - the former colony and current multicultural immigrant society - had and has a specific relevance. As an analytical tool, the motif allows for highlighting both the similarities and the differences between the œuvres of Grove and Kroetsch as key-figures of a (post)colonial literature of Western Canada on the one hand, and for general questions pertaining to the characterisation of figures, the definition of narrative positions and even of genres on the other hand. Following the preface, two theoretical chapters outline conceptions of identity and their deducible forms and functions of disguise and masquerade, including a discussion of John Richardson's Wacousta (1832), which is the first Canadian example for the motif's constitutive use. The second major section sketches, in two separate chapters, the poetics and mentalities (Mentalitätsgeschichte) of each writer within the context of their complete works by looking at biographical data as well as the critics' assessments. After immigrating into Manitoba in 1912, Grove soon became the first representative of a literary prairie-realism. Before, he had faked his suicide in 1909 and stripped off his 'original' identity as the German translator (e.g., Wilde, Wells, Flaubert) as well as modestly successful poet and novelist Felix Paul Greve to leave behind debts and a notorious lover and to reinvent himself in the New World. The protean role-plays of 'FPG' - decoded only 23 years after his death - are manifested in his creation of literary characters, in a "collectivity of identities" (Cavell 12) or number of metonymic personae that keep his critics busy to this date. Providing a different story, Kroetsch's family of German background immigrated into Canada in the mid-19th-century. Kroetsch has been thematizing his native province, Alberta, just as much as general national dispositions or questings in the course of his literary career spanning five decades now. His progressive and experimental writing has earned him, for instance, the label of "Mr Canadian Postmodern" by Linda Hutcheon (Canadian Postmodern 183). Particularly important among his specifically postmodern instruments is the principle of archaeology as derived from Foucault and employed as both metaphor and method; further methodological tools are Barthes' theories on reading/writing as an erotic act, Bakhtin's notion of (the) carnival(ization of literature) and a great sensibility for the myths as well as oral traditions of the North American Natives. If the third section analyzes two of FPG's novels to illustrate his transfer, or literal translation, from a German to a Canadian cultural context, the fourth section represents this study's core with three one-to-one comparisons of the two writers' central prose texts. In spite of all affinities between both authors, however, this section already indicates what section five further underlines: Kroetsch clearly transcends Grove's achievements (which ultimately reduce all his characters and texts to nothing but his own will- and wishful projections and identity-configurations); on the level of narrativity, genre and gender, Kroetsch not only goes far beyond parodying Grove, but proves to be an innovator whose mis-en-scène of the motif of disguise provides both more psychological depth and relevance for socio-historical contexts. This comparative study has been informed by research in the Special Archives and Collections at the University of Manitoba (Grove Papers) and at the University of Calgary (Kroetsch Papers), by related talks at Lund, Belfast and Winnipeg as well as by an occasional quotation from an interview I conducted with Robert Kroetsch as early as 1996.
In this study, candidate loci for periodic catatonia (SCZD10, OMIM #605419) on chromosome 15q15 and 22q13.33 have been fine mapped and investigated. Previously, several studies found evidences for a major susceptibility locus on chromosome 15q15 and a further potential locus on 22q13.33 pointing to genetic heterogeneity. Fine mapping was done in our multiplex families through linkage and mutational analysis using genomic markers selected from public databases. Positional candidate genes like SPRED1 and BRD1, and ultra-conserved elements were investigated by direct sequencing in these families. The results narrow down the susceptibility locus on chromosome 15q14-15q15.1 to a region between markers D15S1042 and D15S968, as well as exclusion of SPRED1 and ultra-conserved elements as susceptibility candidates. Fine mapping for two chromosome 23q13.33-linked families showed that the recombination events would place the disease-causing gene to a telomeric ~577 Kb interval and SNP rs138880 investigation revealed an A-allele in the affected person, therefore excludes BRD1 as well as confirmed MLC1 to be the candidate gene for periodic catatonia.
The main purpose of this dissertation is to solve the following question: How will the emergence of the Euro influence the currency composition of the NICs?monetary reserves? Taiwan and Thailand are chosen as our investigation subjects. There are two sorts of motives for central banks' reserve holdings, i.e., intervention-related motives and portfolio-related motives. The need for reserve holdings resulting from intervention-related motives are justified because of the costs resulting from exchange rate instability. On the other hand, we use the Tobin-Markowitz model to justify the need for monetary reserves held for portfolio-related motives. The operational implication of this distinction is the separation of monetary reserves into two tranches corresponding to different objectives. An analysis of a central bank's transaction balance is a money quality analysis. Such an analysis has to do with transaction costs and non-pecuniary rates of return. The facts point out, that the Euro's emergence will not change the fact that the USD will continue to be the major currency of transaction balances of the central banks in Taiwan and Thailand. In order to answer the question about diversification of monetary reserves as idle balance in the two NICs, we carry out an analysis of the portfolio approach, which is based on the basic ideas of the Tobin-Markowitz model. This analysis shows that Taiwan and/or Thailand respectively cannot reduce risk at a given rate of return or increase the rate of return at a given risk by diversifying their monetary reserves as idle balance from the USD to the Euro.
Do Personality Traits, Trust and Fairness Shape the Stock-Investing Decisions of an Individual?
(2023)
This thesis is comprised of three projects, all of which are fundamentally connected to the choices that individuals make about stock investments. Differences in stock market participation (SMP) across countries are large and difficult to explain. The second chapter focuses on differences between Germany (low SMP) and East Asian countries (mostly high SMP). The study hypothesis is that cultural differences regarding social preferences and attitudes towards inequality lead to different attitudes towards stock markets and subsequently to different SMPs. Using a large-scale survey, it is found that these factors can, indeed, explain a substantial amount of the country differences that other known factors (financial literacy, risk preferences, etc.) could not. This suggests that social preferences should be given a more central role in programs that aim to enhance SMP in countries like Germany. The third chapter documented the importance of trust as well as herding for stock ownership decisions. The findings show that trust as a general concept has no significant contribution to stock investment intention. A thorough examination of general trust elements reveals that in group and out-group trust have an impact on individual stock market investment. Higher out group trust directly influences a person's decision to invest in stocks, whereas higher in-group trust increases herding attitudes in stock investment decisions and thus can potentially increase the likelihood of stock investments as well. The last chapter investigates the significance of personality traits in stock investing and home bias in portfolio selection. Findings show that personality traits do indeed have a significant impact on stock investment and portfolio allocation decisions. Despite the fact that the magnitude and significance of characteristics differ between two groups of investors, inexperienced and experienced, conscientiousness and neuroticism play an important role in stock investments and preferences. Moreover, high conscientiousness scores increase stock investment desire and portfolio allocation to risky assets like stocks, discouraging home bias in asset allocation. Regarding neuroticism, a higher-level increases home bias in portfolio selection and decreases willingness to stock investment and portfolio share. Finally, when an investor has no prior experience with portfolio selection, patriotism generates home bias. For experienced investors, having a low neuroticism score and a high conscientiousness and openness score seemed to be a constant factor in deciding to invest in a well-diversified international portfolio
Numerous RCTs demonstrate that cognitive behavioral therapy (CBT) for depression is effective. However, these findings are not necessarily representative of CBT under routine care conditions. Routine care studies are not usually subjected to comparable standardizations, e.g. often therapists may not follow treatment manuals and patients are less homogeneous with regard to their diagnoses and sociodemographic variables. Results on the transferability of findings from clinical trials to routine care are sparse and point in different directions. As RCT samples are selective due to a stringent application of inclusion/exclusion criteria, comparisons between routine care and clinical trials must be based on a consistent analytic strategy. The present work demonstrates the merits of propensity score matching (PSM), which offers solutions to reduce bias by balancing two samples based on a range of pretreatment differences. The objective of this dissertation is the investigation of the transferability of findings from RCTs to routine care settings.
This dissertation develops a rationale of how to use fossil data in solving biogeographical and ecological problems. It is argued that large amounts of fossil data of high quality can be used to document the evolutionary processes (the origin, development, formation and dynamics) of Arealsystems, which can be divided into six stages in North America: the Refugium Stage (before 15,000 years ago: > 15 ka), the Dispersal Stage (from 8,000 to 15,000 years ago: 8.0 - 15 ka), the Developing Stage (from 3,000 to 8,000 years ago: 3.0 - 8.0 ka), the Transitional Stage (from 1,000 to 3,000 years ago: 1 - 3 ka), the Primitive Stage (from 5,00 to 1,000 years ago: 0.5 - 1 ka) and the Human Disturbing Stage (during the last 500 years: < 0.5 ka). The division into these six stages is based on geostatistical analysis of the FAUNMAP database that contains 43,851 fossil records collected from 1860 to 1994 in North America. Fossil data are one of the best materials to test the glacial refugia theory. Glacial refugia represent areas where flora and fauna were preserved during the glacial period, characterized by richness in species and endemic species at present. This means that these (endemic) species should have distributed purely or primarily in these areas during the glacial period. The refugia can therefore be identified by fossil records of that period. If it is not the case, the richness in (endemic) species may not be the result of the glacial refugia. By exploring where mammals lived during the Refugium Stage (> 15 ka), seven refugia in North America can be identified: the California Refugium, the Mexico Refugium, the Florida Refugium, the Appalachia Refugium, the Great Basin Refugium, the Rocky Mountain Refugium and the Great Lake Refugium. The first five refugia coincide well with De Lattin- dispersal centers recognized by biogeographical methods using data on modern distributions. The individuals of a species are not evenly distributed over its Arealsystem. Brown- Hot Spots Model shows that in most cases there is an enormous variation in abundance within an areal of a species: In a census, zero or only a very few individuals occur at most sample locations, but tens or hundreds are found at a few sample sites. Locations where only a few individuals can be sampled in a survey are called "cool spots", and sites where tens or hundreds of individuals can be observed in a survey are called "hot spots". Many areas within the areal are uninhabited, which are called "holes". This model has direct implications for analyzing fossil data: Hot spots have a much higher local population density than cool spots. The chances to discover fossil individuals of a species are much higher in sediments located in a "hot spot" area than in a "cool spot" area. Therefore much higher MNIs (Minimum Number of Individuals) of the species should be found in fossil localities located in the hot spot than in the cool spot area. There are only a few hot spots but many cool spots within an areal of a single hypothetical species, consequently only a few fossil sites can provide with much high MNIs, whereas most other sites can only provide with very low MNIs. This prediction has been proved to be true by analysis of 70 species in FAUMAP containing over 100 fossil records. The temporal and spatial variation in abundance can be reconstructed from the temporospatial distribution of the MNIs of a species over its Arealsystem. Areas with no fossil records from the last thousands of years may be holes, and sites with much higher MNIs may be hot spots, while locations with low MNIs may be cool spots. Although the hot spots of many species can remain unchanged in an area over thousands of years, our study shows that a large shift of hot spots occurred mainly around 1,500-1,000 years ago. There are three directions of movement: from the west side to the east side of the Rockies, from the East of the USA to the east side of the Rockies and from the west side of the Rockies to the Southwest of the USA. The first two directions of shift are called Lewis and Clark- pattern, which can be verified with the observations mad by Lewis and Clark during their expedition in 1805-1806. The historical process of this pattern may well explain the 200-year-old puzzle why big game then abundant on the east side were rare on the west side of the Rocky Mountains noted by modern ecologists and biogeographers. The third direction of shift is called Bayham- pattern. This pattern can be tested by the model of Late Holocene resource intensification first described by Frank E. Bayham. The historical process creating the Bayham pattern will challenge the classic explanation of the Late Holocene resource intensification. An environmental change model has been proposed to account for the shift of hot spots. Implications of glacial refugia and hot spots areas for wildlife management and effective conservation are discussed. Suggestions for paleontologists and zooarchaeologists regarding how to provide more valuable information in their future excavation and research for other disciplines are given.
We will consider discrete dynamical systems (X,T) which consist of a state space X and a linear operator T acting on X. Given a state x in X at time zero, its state at time n is determined by the n-th iteration T^n(x). We are interested in the long-term behaviour of this system, that means we want to know how the sequence (T^n (x))_(n in N) behaves for increasing n and x in X. In the first chapter, we will sum up the relevant definitions and results of linear dynamics. In particular, in topological dynamics the notions of hypercyclic, frequently hypercyclic and mixing operators will be presented. In the setting of measurable dynamics, the most important definitions will be those of weakly and strongly mixing operators. If U is an open set in the (extended) complex plane containing 0, we can define the Taylor shift operator on the space H(U) of functions f holomorphic in U as Tf(z) = (f(z)- f(0))/z if z is not equal to 0 and otherwise Tf(0) = f'(0). In the second chapter, we will start examining the Taylor shift on H(U) endowed with the topology of locally uniform convergence. Depending on the choice of U, we will study whether or not the Taylor shift is weakly or strongly mixing in the Gaussian sense. Next, we will consider Banach spaces of functions holomorphic on the unit disc D. The first section of this chapter will sum up the basic properties of Bergman and Hardy spaces in order to analyse the dynamical behaviour of the Taylor shift on these Banach spaces in the next part. In the third section, we study the space of Cauchy transforms of complex Borel measures on the unit circle first endowed with the quotient norm of the total variation and then with a weak-* topology. While the Taylor shift is not even hypercyclic in the first case, we show that it is mixing for the latter case. In Chapter 4, we will first introduce Bergman spaces A^p(U) for general open sets and provide approximation results which will be needed in the next chapter where we examine the Taylor shift on these spaces on its dynamical properties. In particular, for 1<=p<2 we will find sufficient conditions for the Taylor shift to be weakly mixing or strongly mixing in the Gaussian sense. For p>=2, we consider specific Cauchy transforms in order to determine open sets U such that the Taylor shift is mixing on A^p(U). In both sections, we will illustrate the results with appropriate examples. Finally, we apply our results to universal Taylor series. The results of Chapter 5 about the Taylor shift allow us to consider the behaviour of the partial sums of the Taylor expansion of functions in general Bergman spaces outside its disc of convergence.
The efficacy and effectiveness of psychotherapeutic interventions have been proven time and again. We therefore know that, in general, evidence-based treatments work for the average patient. However, it has also repeatedly been shown that some patients do not profit from or even deteriorate during treatment. Patient-focused psychotherapy research takes these differences between patients into account by focusing on the individual patient. The aim of this research approach is to analyze individual treatment courses in order to evaluate when and under which circumstances a generally effective treatment works for an individual patient. The goal is to identify evidence based clinical decision rules for the adaptation of treatment to prevent treatment failure. Patient-focused research has illustrated how different intake indicators and early change patterns predict the individual course of treatment, but they leave a lot of variance unexplained. The thesis at hand analyzed whether Ecological Momentary Assessment (EMA) strategies could be integrated into patient-focused psychotherapy research in order to improve treatment response prediction models. EMA is an electronically supported diary approach, in which multiple real-time assessments are conducted in participants" everyday lives. We applied EMA over a two-week period before treatment onset in a mixed sample of patients seeking outpatient treatment. The four daily measurements in the patients" everyday environment focused on assessing momentary affect and levels of rumination, perceived self-efficacy, social support and positive or negative life events since the previous assessment. The aim of this thesis project was threefold: First, to test the feasibility of EMA in a routine care outpatient setting. Second, to analyze the interrelation of different psychological processes within patients" everyday lives. Third and last, to test whether individual indicators of psychological processes during everyday life, which were assessed before treatment onset, could be used to improve prediction models of early treatment response. Results from Study I indicate good feasibility of EMA application during the waiting period for outpatient treatment. High average compliance rates over the entire assessment period and low average burdens perceived by the patients support good applicability. Technical challenges and the results of in-depth missing analyses are reported to guide future EMA applications in outpatient settings. Results from Study II shed further light on the rumination-affect link. We replicated results from earlier studies, which identified a negative association between state rumination and affect on a within-person level and additionally showed a) that this finding holds for the majority but not every individual in a diverse patient sample with mixed Axis-I disorders, b) that rumination is linked to negative but also to positive affect and c) that dispositional rumination significantly affects the state rumination-affect association. The results provide exploratory evidence that rumination might be considered a transdiagnostic mechanism of psychological functioning and well-being. Results from Study III finally suggest that the integration of indicators derived from EMA applications before treatment onset can improve prediction models of early treatment response. Positive-negative affect ratios as well as fluctuations in negative affect measured during patients" daily lives allow the prediction of early treatment response. Our results indicate that the combination of commonly applied intake predictors and EMA indicators of individual patients" daily experiences can improve treatment response predictions models. We therefore conclude that EMA can successfully be integrated into patient-focused research approaches in routine care settings to ameliorate or optimize individual care.
Retirement, fertility and sexuality are three key life stage events that are embedded in the framework of population economics in this dissertation. Each topic implies economic relevance. As retirement entry shifts labour supply of experienced workers to zero, this issue is particularly relevant for employers, retirees themselves as well as policymakers who are in charge of the design of the pension system. Giving birth has comprehensive economic relevance for women. Parental leave and subsequent part-time work lead to a direct loss of income. Lower levels of employment, work experience, training and career opportunities result in indirect income losses. Sexuality has decisive influence on the quality of partnerships, subjective well-being and happiness. Well-being and happiness, in turn, are significant key determinants not only in private life but also in the work domain, for example in the area of job performance. Furthermore, partnership quality determines the duration of a partnership. And in general, partnerships enable the pooling of (financial) resources - compared to being single. The contribution of this dissertation emerges from the integration of social and psychological concepts into economic analysis as well as the application of economic theory in non-standard economic research topics. The results of the three chapters show that the multidisciplinary approach yields better prediction of human behaviour than the single disciplines on their own. The results in the first chapter show that both interpersonal conflict with superiors and the individual’s health status play a significant role in retirement decisions. The chapter further contributes to existing literature by showing the moderating role of health within the retirement decision-making: On the one hand, all employees are more likely to retire when they are having conflicts with their superior. On the other hand, among healthy employees, the same conflict raises retirement intentions even more. That means good health is a necessary, but not a sufficient condition for continued working. It may be that conflicts with superiors raise retirement intentions more if the worker is healthy. The key findings of the second chapter reveal significant influence of religion on contraceptive and fertility-related decisions. A large part of research on religion and fertility is originated in evidence from the US. This chapter contrasts evidence from Germany. Additionally, the chapter contributes by integrating miscarriages and abortions, rather than limiting the analysis to births and it gains from rich prospective data on fertility biography of women. The third chapter provides theoretical insights on how to incorporate psychological variables into an economic framework which aims to analyse sexual well-being. According to this theory, personality may play a dual role by shaping a person’s preferences for sex as well as the person’s behaviour in a sexual relationship. Results of econometric analysis reveal detrimental effects of neuroticism on sexual well-being while conscientiousness seems to create a win-win situation for a couple. Extraversions and Openness have ambiguous effects on romantic relationships by enhancing sexual well-being on the one hand but raising commitment problems on the other. Agreeable persons seem to gain sexual satisfaction even if they perform worse in sexual communication.
Broadcast media such as television have spread rapidly worldwide in the last century. They provide viewers with access to new information and also represent a source of entertainment that unconsciously exposes them to different social norms and moral values. Although the potential impact of exposure to television content have been studied intensively in economic research in recent years, studies examining the long-term causal effects of media exposure are still rare. Therefore, Chapters 2 to 4 of this thesis contribute to the better understanding of long-term effects of television exposure.
Chapter 2 empirically investigates whether access to reliable environmental information through television can influence individuals' environmental awareness and pro-environmental behavior. Analyzing exogenous variation in Western television reception in the German Democratic Republic shows that access to objective reporting on environmental pollution can enhance concerns regarding pollution and affect the likelihood of being active in environmental interest groups.
Chapter 3 utilizes the same natural experiment and explores the relationship between exposure to foreign mass media content and xenophobia. In contrast to the state television broadcaster in the German Democratic Republic, West German television regularly confronted its viewers with foreign (non-German) broadcasts. By applying multiple measures for xenophobic attitudes, our findings indicate a persistent mitigating impact of foreign media content on xenophobia.
Chapter 4 deals with another unique feature of West German television. In contrast to East German media, Western television programs regularly exposed their audience to unmarried and childless characters. The results suggest that exposure to different gender stereotypes contained in television programs can affect marriage, divorce, and birth rates. However, our findings indicate that mainly women were affected by the exposure to unmarried and childless characters.
Chapter 5 examines the influence of social media marketing on crowd participation in equity crowdfunding. By analyzing 26,883 investment decisions on three German equity crowdfunding platforms, our results show that startups can influence the success of their equity crowdfunding campaign through social media posts on Facebook and Twitter.
In Chapter 6, we incorporate the concept of habit formation into the theoretical literature on trade unions and contribute to a better understanding of how internal habit preferences influence trade union behavior. The results reveal that such internal reference points lead trade unions to raise wages over time, which in turn reduces employment. Conducting a numerical example illustrates that the wage effects and the decline in employment can be substantial.
This dissertation focuses on e-marketing strategy's effective elements in tourism industry. As case study, research focus is on Airlines, tour operator, chain hotels in Iran and Germany. It aims to show various possibilities to enhance the company- e-marketing strategy and successfully performance e-marketing strategies with recognition effective elements and their important during the strategy designing and implementation process. For the purpose of this research due to the nature of the research, Explanatory -exploratory-applicable; after studying and consulting, Delphi technique has been chosen. In results, we have some effective elements and their important according the Delphi and AHP method. For example between elements "Tourists' Needs, Experience and Expects" with the importance coefficient of %204 is the most remarkable elements and "Customer satisfactions' elements group" with average value 5.54 according the research results have more important than other groups.
A lack of ability to inhibit prepotent responses, or more generally a lack of impulse control, is associated with several disorders such as attention-deficit/hyperactivity disorder and schizophrenia as well as general damage to the prefrontal cortex. A stop-signal task (SST) is a reliable and established measure of response inhibition. However, using the SST as an objective assessment in diagnostic or research-focused settings places significant stress on participants as the task itself requires concentration and cognitive effort and is not particularly engaging. This can lead to decreased motivation to follow task instructions and poor data quality, which can affect assessment efficacy and might increase drop-out rates. Gamification—the application of game-based elements in nongame settings—has shown to improve engaged attention to a cognitive task, thus increasing participant motivation and data quality.
Imagery-based techniques have received increasing interest in psychotherapy research. Whereas their effectiveness has been shown for various psychological disorders, their underlying mechanisms remain unclear. Current research predominantly investigates intrapersonal processes, while interpersonal processes have received no attention to date. The aim of the current dissertation was to fill this lacuna. The three interrelated studies comprising this dissertation were the first to examine the effectiveness of imagery-based techniques in the treatment of test anxiety, relate physiological arousal to emotional processing, and investigate the association between physiological synchrony and multiple process measures.
Study I investigated the feasibility of a newly developed protocol, which integrates imagery-based and cognitive-behavioral components, to treat test anxiety in a sample of 31 students. The results indicated the protocol as acceptable, feasible, and effective in the treatment of test anxiety. Additionally, the imagery-based component was positively associated with therapeutic bond, session evaluation, and emotional experience.
Study II shifted the focus from the effectiveness of imagery-based techniques to client-therapist physiological synchrony as a putative mechanism of change in the same sample. The results suggested that physiological synchrony was greater than chance during both imagery-based and cognitive-behavioral components. Variability of physiological synchrony on the session-level during the imagery-based components and variability on both levels (session and dyad) during the cognitive-behavioral components were demonstrated. Furthermore, physiological synchrony of the imagery-based segments was positively assocatied with therapeutic bond. No association was found for the cognitive-behavioral components.
Study III examined both intrapersonal (i.e., clients’ electrodermal activity) and interpersonal (i.e., client-therapist electrodermal activity synchrony) processes and their associations with emotional processing in a sample of 49 client-therapist-dyads. The results suggested that higher client physiological arousal and a moderate level of physiological synchrony were associated with deeper emotional processing.
Taken together, the results highlight the effectiveness of imagery-based techniques in the treatment of test anxiety. Furthermore, the results of Studies II and III support the idea of physiological synchrony as a mechanism of change in imagery with and without rescripting. The current dissertation takes an important step towards optimizing process research within psychotherapy and contributes to a better understanding of the potency and mechanisms of change of imagery-based techniques. We hope that these studies’ implications will support everyday clinical practice.
Stress and pain are common experiences in human lives. Both, the stress and the pain system have adaptive functions and try to protect the organism in case of harm and danger. However, stress and pain are two of the most challenging problems for the society and the health system. Chronic stress, as often seen in modern societies, has much impact on health and can lead to chronic stress disorders. These disorders also include a number of chronic pain syndromes. However, pain can also be regarded as a stressor itself, especially when we consider how much patients suffer from long-lasting pain and the impact of pain on life quality. In this way, the effects of stress on pain can be fostered. For the generation and manifestation of chronic pain symptoms also learning processes such as classical conditioning play an important role. Processes of classical conditioning can also be influenced by stress. These facts illustrate the complex and various interactions between the pain and the stress systems. Both systems communicate permanently with each other and help to protect the organism and to keep a homeostatic state. They have various ways of communication, for example mechanisms related to endogenous opioids, immune parameters, glucocorticoids and baroreflexes. But an overactivation of the systems, for example caused by ongoing stress, can lead to severe health problems. Therefore, it is of great importance to understand these interactions and their underlying mechanisms. The present work deals with the relationship of stress and pain. A special focus is put on stress related hypocortisolism and pain processing, stress induced hypoalgesia via baroreceptor related mechanisms and stress related cortisol effects on aversive conditioning (as a model of pain learning). This work is a contribution to the wide field of research that tries to understand the complex interactions of stress and pain. To demonstrate the variety, the selected studies highlight different aspects of these interactions. In the first chapter I will give a short introduction on the pain and the stress systems and their ways of interaction. Furthermore, I will give a short summary of the studies presented in Chapter II to V and their background. The results and their meaning for future research will be discussed in the last part of the first chapter. Chronic pain syndromes have been associated with chronic stress and alterations of the HPA axis resulting in chronic hypocortisolism. But if these alterations may play a causal role in the pathophysiology of chronic pain remains unclear. Thus, the study described in Chapter II investigated the effects of pharmacological induced hypocortisolism on pain perception. Both, the stress and the pain system are related to the cardiovascular system. Increase of blood pressure is part of the stress reaction and leads to reduced pain perception. Therefore, it is important for the usage of pain tests to keep in mind potential interferences from activation of the cardiovascular system, especially when pain inhibitory processes are investigated. For this reason we compared two commonly and interchangeably used pain tests with regard to the triggered autonomic reactions. This study is described in chapter III. Chapter IV and V deal with the role of learning processes in pain and related influences of stress. Processes of classical conditioning play an important role for symptom generation and manifestation. In both studies aversive eyeblink conditioning was used as a model for pain learning. In the study described in Chapter IV we compared classical eyeblink conditioning in healthy volunteers to patients suffering from fibromyalgia, a chronic pain disorder. Also, differences of the HPA axis, as part of the stress system, were taken in account. The study of Chapter V investigated effects of the very first stress reaction, particularly rapid non-genomic cortisol effects. Healthy volunteers received an intravenous cortisol administration immediately before the eyeblink conditioning. Rapid effects have only been demonstrated on a cellular level and on animal behavior so far. In general, the studies presented in this work may give an impression of the broad variety of possible interactions between the pain and the stress system. Furthermore, they contribute to our knowledge about theses interactions. However, more research is needed to complete the picture.
In this thesis, global surrogate models for responses of expensive simulations are investigated. Computational fluid dynamics (CFD) have become an indispensable tool in the aircraft industry. But simulations of realistic aircraft configurations remain challenging and computationally expensive despite the sustained advances in computing power. With the demand for numerous simulations to describe the behavior of an output quantity over a design space, the need for surrogate models arises. They are easy to evaluate and approximate quantities of interest of a computer code. Only a few number of evaluations of the simulation are stored for determining the behavior of the response over a whole range of the input parameter domain. The Kriging method is capable of interpolating highly nonlinear, deterministic functions based on scattered datasets. Using correlation functions, distinct sensitivities of the response with respect to the input parameters can be considered automatically. Kriging can be extended to incorporate not only evaluations of the simulation, but also gradient information, which is called gradient-enhanced Kriging. Adaptive sampling strategies can generate more efficient surrogate models. Contrary to traditional one-stage approaches, the surrogate model is built step-by-step. In every stage of an adaptive process, the current surrogate is assessed in order to determine new sample locations, where the response is evaluated and the new samples are added to the existing set of samples. In this way, the sampling strategy learns about the behavior of the response and a problem-specific design is generated. Critical regions of the input parameter space are identified automatically and sampled more densely for reproducing the response's behavior correctly. The number of required expensive simulations is decreased considerably. All these approaches treat the response itself more or less as an unknown output of a black-box. A new approach is motivated by the assumption that for a predefined problem class, the behavior of the response is not arbitrary, but rather related to other instances of the mutual problem class. In CFD, for example, responses of aerodynamic coefficients share structural similarities for different airfoil geometries. The goal is to identify the similarities in a database of responses via principal component analysis and to use them for a generic surrogate model. Characteristic structures of the problem class can be used for increasing the approximation quality in new test cases. Traditional approaches still require a large number of response evaluations, in order to achieve a globally high approximation quality. Validating the generic surrogate model for industrial relevant test cases shows that they generate efficient surrogates, which are more accurate than common interpolations. Thus practical, i.e. affordable surrogates are possible already for moderate sample sizes. So far, interpolation problems were regarded as separate problems. The new approach uses the structural similarities of a mutual problem class innovatively for surrogate modeling. Concepts from response surface methods, variable-fidelity modeling, design of experiments, image registration and statistical shape analysis are connected in an interdisciplinary way. Generic surrogate modeling is not restricted to aerodynamic simulation. It can be applied, whenever expensive simulations can be assigned to a larger problem class, in which structural similarities are expected.
Large scale non-parametric applied shape optimization for computational fluid dynamics is considered. Treating a shape optimization problem as a standard optimal control problem by means of a parameterization, the Lagrangian usually requires knowledge of the partial derivative of the shape parameterization and deformation chain with respect to input parameters. For a variety of reasons, this mesh sensitivity Jacobian is usually quite problematic. For a sufficiently smooth boundary, the Hadamard theorem provides a gradient expression that exists on the surface alone, completely bypassing the mesh sensitivity Jacobian. Building upon this, the gradient computation becomes independent of the number of design parameters and all surface mesh nodes are used as design unknown in this work, effectively allowing a free morphing of shapes during optimization. Contrary to a parameterized shape optimization problem, where a smooth surface is usually created independently of the input parameters by construction, regularity is not preserved automatically in the non-parametric case. As part of this work, the shape Hessian is used in an approximative Newton method, also known as Sobolev method or gradient smoothing, to ensure a certain regularity of the updates, and thus a smooth shape is preserved while at the same time the one-shot optimization method is also accelerated considerably. For PDE constrained shape optimization, the Hessian usually is a pseudo-differential operator. Fourier analysis is used to identify the operator symbol both analytically and discretely. Preconditioning the one-shot optimization by an appropriate Hessian symbol is shown to greatly accelerate the optimization. As the correct discretization of the Hadamard form usually requires evaluating certain surface quantities such as tangential divergence and curvature, special attention is also given to discrete differential geometry on triangulated surfaces for evaluating shape gradients and Hessians. The Hadamard formula and Hessian approximations are applied to a variety of flow situations. In addition to shape optimization of internal and external flows, major focus lies on aerodynamic design such as optimizing two dimensional airfoils and three dimensional wings. Shock waves form when the local speed of sound is reached, and the gradient must be evaluated correctly at discontinuous states. To ensure proper shock resolution, an adaptive multi-level optimization of the Onera M6 wing is conducted using more than 36, 000 shape unknowns on a standard office workstation, demonstrating the applicability of the shape-one-shot method to industry size problems.
Shape optimization is of interest in many fields of application. In particular, shape optimization problems arise frequently in technological processes which are modelled by partial differential equations (PDEs). In a lot of practical circumstances, the shape under investigation is parametrized by a finite number of parameters, which, on the one hand, allows the application of standard optimization approaches, but, on the other hand, unnecessarily limits the space of reachable shapes. Shape calculus presents a way to circumvent this dilemma. However, so far shape optimization based on shape calculus is mainly performed using gradient descent methods. One reason for this is the lack of symmetry of second order shape derivatives or shape Hessians. A major difference between shape optimization and the standard PDE constrained optimization framework is the lack of a linear space structure on shape spaces. If one cannot use a linear space structure, then the next best structure is a Riemannian manifold structure, in which one works with Riemannian shape Hessians. They possess the often sought property of symmetry, characterize well-posedness of optimization problems and define sufficient optimality conditions. In general, shape Hessians are used to accelerate gradient-based shape optimization methods. This thesis deals with shape optimization problems constrained by PDEs and embeds these problems in the framework of optimization on Riemannian manifolds to provide efficient techniques for PDE constrained shape optimization problems on shape spaces. A Lagrange-Newton and a quasi-Newton technique in shape spaces for PDE constrained shape optimization problems are formulated. These techniques are based on the Hadamard-form of shape derivatives, i.e., on the form of integrals over the surface of the shape under investigation. It is often a very tedious, not to say painful, process to derive such surface expressions. Along the way, volume formulations in the form of integrals over the entire domain appear as an intermediate step. This thesis couples volume integral formulations of shape derivatives with optimization strategies on shape spaces in order to establish efficient shape algorithms reducing analytical effort and programming work. In this context, a novel shape space is proposed.
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.
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.
Globalization and the emergence of global value chains have not only changed the way we live, but also the way economists study international economics. These changes are visible in various areas and dimension. This dissertation deals " mostly empirically " with some of these issues related to global value chains. It starts by critically examining the political economy forces determining the occurrence and the extent of trade liberalization conditions in World Bank lending agreements. The focal point is whether these are affected by the World Bank- most influential member countries. Afterwards, the thesis moves on to describe trade of the European Union member countries at each stage of the value chain. The description is based on a new classification of goods into parts, components and final products as well as a newly developed measure describing the average level of development of a countries trading partners. This descriptive exercise is followed by critically examining discrepancies between gross trade and trade in value added with respect to comparative advantage. A gravity model is employed to contrast results when studying the institutional determinants of comparative advantage. Finally, the thesis deals with determinants of regional location choices for foreign direct investment. The analysis is based on a theoretical new economic geography model and employs a newly developed index that accounts for the presence of potentially all suppliers and buyers at all stages of the value chain.
This doctoral thesis includes five studies that deal with the topics work, well-being, and family formation, as well as their interaction. The studies aim to find answers to the following questions: Do workers’ personality traits determine whether they sort into jobs with performance appraisals? Does job insecurity result in lower quality and quantity of sleep? Do public smoking bans affect subjective well-being by changing individuals’ use of leisure time? Can risk preferences help to explain non-traditional family forms? And finally, are differences in out-of-partnership birth rates between East and West Germany driven by cultural characteristics that have evolved in the two separate politico-economic systems? To answer these questions, the following chapters use basic economic subjects such as working conditions, income, and time use, but also employ a range of sociological and psychological concepts such as personality traits and satisfaction measures. Furthermore, all five studies use data from the German Socio-Economic Panel (SOEP), a representative longitudinal panel of private households in Germany, and apply state-of-the-art microeconometric methods. The findings of this doctoral thesis are important for individuals, employers, and policymakers. Workers and employers benefit from knowing the determinants of occupational sorting, as vacancies can be filled more accurately. Moreover, knowing which job-related problems lead to lower well-being and potentially higher sickness absence likely increases efficiency in the workplace. The research on smoking bans and family formation in chapters 4, 5, and 6 is particularly interesting for policymakers. The results on the effects of smoking bans on subjective well-being presented in chapter 4 suggest that the impacts of tobacco control policies could be weighed more carefully. Additionally, understanding why women are willing to take the risks associated with single motherhood can help to improve policies targeting single mothers.
Background
Identifying pain-related response patterns and understanding functional mechanisms of symptom formation and recovery are important for improving treatment.
Objectives
We aimed to replicate pain-related avoidance-endurance response patterns associated with the Fear-Avoidance Model, and its extension, the Avoidance-Endurance Model, and examined their differences in secondary measures of stress, action control (i.e., dispositional action vs. state orientation), coping, and health.
Methods
Latent profile analysis (LPA) was conducted on self-report data from 536 patients with chronic non-specific low back pain at the beginning of an inpatient rehabilitation program. Measures of stress (i.e., pain, life stress) and action control were analyzed as covariates regarding their influence on the formation of different pain response profiles. Measures of coping and health were examined as dependent variables.
Results
Partially in line with our assumptions, we found three pain response profiles of distress-avoidance, eustress-endurance, and low-endurance responses that are depending on the level of perceived stress and action control. Distress-avoidance responders emerged as the most burdened, dysfunctional patient group concerning measures of stress, action control, maladaptive coping, and health. Eustress-endurance responders showed one of the highest levels of action versus state orientation, as well as the highest levels of adaptive coping and physical activity. Low-endurance responders reported lower levels of stress as well as equal levels of action versus state orientation, maladaptive coping, and health compared to eustress-endurance responders; however, equally low levels of adaptive coping and physical activity compared to distress-avoidance responders.
Conclusions
Apart from the partially supported assumptions of the Fear-Avoidance and Avoidance-Endurance Model, perceived stress and dispositional action versus state orientation may play a crucial role in the formation of pain-related avoidance-endurance response patterns that vary in degree of adaptiveness. Results suggest tailoring interventions based on behavioral and functional analysis of pain responses in order to more effectively improve patients quality of life.
ENGLISH ACADEMIC LITERARY DISCOURSE IN SOUTH AFRICA 1958-2004: A REVIEW OF 11 ACADEMIC JOURNALS
(2007)
This study examines the discipline of English studies in South Africa through a review of articles published in 11 academic journals over the period 1958"2004. The aims are to gain a better understanding of the functions of peer-reviewed journals, to reveal the presence of rules governing discursive production, and to uncover the historical shifts in approach and choice of disciplinary objects. The Foucauldian typology of procedures determining discursive production, that is: exclusionary, internal and restrictive procedures, is applied to the discipline of English studies in order to elucidate the existence of such procedures in the discipline. Each journal is reviewed individually and comparatively. Static and chronological statistical analyses are undertaken on the articles in the 11 journals in order to provide empirical evidence to subvert the contention that the discipline is unruly and its choice of objects random. The cumulative results of this analysis are used to describe the major shifts primarily in ranges of disciplinary objects, but also in metadiscursive and thematic debates. Each of the journals is characterised in relation to what the overall analysis reveals about the mainstream developments. The two main findings are that, during the period under review, South African imaginative written artefacts have moved from a marginal position to the centre of focus of the discipline; and that the conception of what constitutes the "literary" has returned to a pre-Practical criticism definition, broadly inclusive of a variety of types of artefact including imaginative writing, such as autobiography, letters, journals and orature.
While women's evolving contribution to entrepreneurship is irrefutable, in almost all nations, gender disparity is an existing reality of entrepreneurship. Social and economic outcomes make women entrepreneurship an important area for scholars and governments. In attempts to find reasons for this gender disparity, academic scholars evaluated various factors and recognised perceptual variables as having outstanding explanatory value in understanding women's entrepreneurship. To advance our knowledge of gender disparity in entrepreneurship, the present study explores the influence of entrepreneurial perceptual variables on women's entrepreneurship and considers the critical role of country-level institutional contexts on the women's entrepreneurial propensity. Therefore, this study examines the impact of perceptual variables in different nations. It also offers connections between entrepreneurial perceptions, women entrepreneurship, and institutional contexts as a critical topic for future studies.
Drawing on the importance of perceptual factors, this dissertation investigates whether and how their perception of entrepreneurial networks influences the individuals' decision to initiate a new venture. Prior scholars considered exposure to entrepreneurial role models as one of the most influential factors on the women's inclination towards entrepreneurship; thus, a systemized analysis makes it possible to identify existing research gaps related to this perception. Hence, to draw a clear picture of the relationship between entrepreneurial role models and entrepreneurship, this dissertation provides a systemized overview of prior studies. Subsequently, Chapter 2 structures the existing literature on entrepreneurial role models and reveals that past literature has focused on the different types of role models, the stage of life at which the exposure to role models occurs, and the context of the exposure. Current discourse argues that the women's lower access to entrepreneurial role models negatively influences their inclination towards entrepreneurship.
Additionally, although the research on women entrepreneurship has proliferated in recent years, little is known about how entrepreneurial perceptual variables form women's propensity towards entrepreneurship in various institutional contexts. The work of Koellinger et al. (2013), hereafter KMS, is one of the most influential papers that investigated the influence of perceptual variables, and it showed that a lower rate of women entrepreneurship is associated with a lower level of their entrepreneurial network, perceived entrepreneurial capability, and opportunity evaluation and with a higher fear of entrepreneurial failure. Thus, this dissertation replicates the work of KMS. Chapter 3 explicitly investigates the influence of the above perceptions on women's entrepreneurial propensity. This research has drawn data from the Global Entrepreneurship Monitor, a cross-national individual-level data set (2001-2006) covering 236,556 individuals across 17 countries. The results of this chapter suggest that gender disparities in entrepreneurial propensity are conditioned by differences in entrepreneurial perceptual variables. Women's lower levels of perceived entrepreneurial capability, entrepreneurial role models and opportunity evaluation and their higher fear of failure lead to lower entrepreneurial propensity.
To extend and generalise the relationship between perceptions and women's entrepreneurial propensity, in Chapter 4, two studies are conducted based on replicated research. Extension 1 generalises the results of KMS by using the same analysis on more recent data. Accordingly, this research implemented the same analysis on 372,069 individuals across the same countries (2011-2016). The recent data show that although gender disparity became significantly weaker, the gender gap is still in men's favour. However, similarly to the replicated study, this research revealed that perceptual factors explain a larger part of the gender disparity. To strengthen prior empirical evidence, in extension 2, utilising a sample of 1,029,863 individuals from 71 countries (2011-2016), the study conducted the same measures and analysis in a more global setting. By including developing countries, gender disparity in entrepreneurial propensity decreased significantly. The study revealed that the relative significance of the influences of perceptions' differs significantly across nations; however, perceptions have a worldwide effect. Moreover, this research found that the ratio of nascent women entrepreneurs in less developed countries to those in more developed nations is 2. More precisely, a higher level of economic development negatively influences the impact of perceptions on women's entrepreneurial propensity.
Whereas prior scholars increasingly underlined the importance of perceptions in explaining a large part of gender disparities in entrepreneurship, most of the prior investigations focused on nascent (early-stage) entrepreneurship, and evidence on the relationship between perceptions and other types of self-employment, such as innovative entrepreneurship, is scant. Innovation is a confirmed key driver of a firm's sustainability, higher competitive capability, and growth. Therefore, Chapter 5 investigates the influence of perceptions on women's innovative entrepreneurship. The chapter points out that entrepreneurial perceptions are the main determinants of the women's decision to offer a new product or service. This chapter also finds that women's innovative entrepreneurship is associated with the country's specific economic setting.
Overall, by underlining the critical role of institutional contexts, this dissertation provides considerable insights into the interaction between perceptions and women entrepreneurship, and its results have implications for policymakers and practitioners, who may find it helpful to consider women entrepreneurship in systemized challenges. Formal and informal barriers affect women's entrepreneurial perceptions and can differ from one country to the other. In this sense, it is crucial to design operational plans to mitigate formal and stereotypical challenges, and thus, more women will be able to start a business, particularly in developing countries in which women significantly comprise a smaller portion of the labour markets. This type of policy could write the "rules of the game" such that these rules enhance the women's propensity towards entrepreneurship.
The search for relevant determinants of knowledge acquisition has a long tradition in educational research, with systematic analyses having started over a century ago. To date, a variety of relevant environmental and learner-related characteristics have been identified, providing a wide body of empirical evidence. However, there are still some gaps in the literature, which are highlighted in the current dissertation. The dissertation includes two meta-analyses summarizing the evidence on the effectiveness of electrical brain stimulation and the effects of prior knowledge on later learning outcomes and one empirical study employing latent profile transition analysis to investigate the changes in conceptual knowledge over time. The results from the three studies demonstrate how learning outcomes can be advanced by input from the environment and that they are highly related to the students" level of prior knowledge. It is concluded that the effects of environmental and learner-related variables impact both the biological and cognitive processes underlying knowledge acquisition. Based on the findings from the three studies, methodological and practical implications are provided, followed by an outline of four recommendations for future research on knowledge acquisition.
Species can show strong variation of local abundance across their ranges. Recent analyses suggested that variation in abundance can be related to environmental suitability, as the highest abundances are often observed in populations living in the most suitable areas. However, there is limited information on the mechanisms through which variation in environmental suitability determines abundance. We analysed populations of the microendemic salamander Hydromantes flavus, and tested several hypotheses on potential relationships linking environmental suitability to population parameters. For multiple populations across the whole species range, we assessed suitability using species distribution models, and measured density, activity level, food intake and body condition index. In high-suitability sites, the density of salamanders was up to 30-times higher than in the least suitable ones. Variation in activity levels and population performance can explain such variation of abundance. In high-suitability sites, salamanders were active close to the surface, and showed a low frequency of empty stomachs. Furthermore, when taking into account seasonal variation, body condition was better in the most suitable sites. Our results show that the strong relationship between environmental suitability and population abundance can be mediated by the variation of parameters strongly linked to individual performance and fitness.
A phenomenon of recent decades is that digital marketplaces on the Internet are establishing themselves for a wide variety of products and services. Recently, it has become possible for private individuals to invest in young and innovative companies (so-called "start-ups"). Via Internet portals, potential investors can examine various start-ups and then directly invest in their chosen start-up. In return, investors receive a share in the firm- profit, while companies can use the raised capital to finance their projects. This new way of financing is called "Equity Crowdfunding" (ECF) or "Crowdinvesting". The aim of this dissertation is to provide empirical findings about the characteristics of ECF. In particular, the question of whether ECF is able to overcome geographic barriers, the interdependence of ECF and capital structure, and the risk of failure for funded start-ups and their chances of receiving follow-up funding by venture capitalists or business angels will be analyzed. The results of the first part of this dissertation show that investors in ECF prefer local companies. In particular, investors who invest larger amounts have a stronger tendency to invest in local start-ups. The second part of the dissertation provides first indications of the interdependencies between capital structure and ECF. The analysis makes clear that the capital structure is not a determinant for undertaking an ECF campaign. The third part of the dissertation analyzes the success of companies financed by ECF in a country comparison. The results show that after a successful ECF campaign German companies have a higher chance of receiving follow-up funding by venture capitalists compared to British companies. The probability of survival, however, is slightly lower for German companies. The results provide relevant implications for theory and practice. The existing literature in the area of entrepreneurial finance will be extended by insights into investor behavior, additions to the capital structure theory and a country comparison in ECF. In addition, implications are provided for various actors in practice.
Entrepreneurial ventures are associated with economic growth, job creation, and innovation. Most entrepreneurial ventures need external funding to succeed. However, they often find it difficult to access traditional forms of financing, such as bank loans. To overcome this hurdle and to provide entrepreneurial ventures with badly-needed external capital, many types of entrepreneurial finance have emerged over the past decades and continue to emerge today. Inspired by these dynamics, this postdoctoral thesis contains five empirical studies that address novel questions regarding established (e.g., venture capital, business angels) and new types of entrepreneurial finance (i.e., initial coin offerings).
This thesis comprises of four research papers on the economics of education and industrial relations, which contribute to the field of empirical economic research. All of the corresponding papers focus on analysing how much time individuals spend on specific activities. The allocation of available time resources is a decision that individuals make throughout their lifetime. In this thesis, we consider individuals at different stages of their lives - students at school, university students, and dependent employees at the workplace.
Part I includes two research studies on student's behaviour in secondary and tertiary education.
Chapter 2 explores whether students who are relatively younger or older within the school year exhibit differential time allocation. Building on previous findings showing that relatively younger students perform worse in school, the study shows that relatively younger students are aware of their poor performance in school and feel more strain as a result. Nevertheless, there are no clear differences to be found in terms of time spent on homework, while relatively younger students spend more time watching television and less time on sports activities. Thus, the results suggest that the lower learning outcomes are not associated with different time allocations between school-related activities and non-school-related activities.
Chapter 3 analyses how individual ability and labour market prospects affect study behaviour. The theoretical modelling predicts that both determinants increase study effort. The empirical investigation is based on cross-sectional data from the National Educational Panel Study (NEPS) and includes thousands of students in Germany. The analyses show that more gifted students exhibit lower subjective effort levels and invest less time in self-study. In contrast, very good labour market prospects lead to more effort exerted by the student, both qualitatively and quantitatively. The potential endogeneity problem is taken into account by using regional unemployment data as an instrumental variable.
Part II includes two labour economic studies on determinants of overtime. Both studies belong to the field of industrial relations, as they focus on union membership on the one hand and the interplay of works councils and collective bargaining coverage on the other.
Chapter 4 shows that union members work less overtime than non-members do. The econometric approach takes the problem of unobserved heterogeneity into account; but provides no evidence that this issue affects the results. Different channels that could lead to this relationship are analysed by examining relevant subgroups separately. For example, this effect of union membership can also be observed in establishments with works councils and for workers who are very likely to be covered by collective bargaining agreements. The study concludes that the observed effect is due to the fact that union membership can protect workers from corresponding increased working time demands by employers.
Chapter 5 builds on previous studies showing a negative effect of works councils on overtime. In addition to co-determination by works councils at the firm level, collective bargaining coverage is an important factor in the German industrial relations system. Corresponding data was not available in the SOEP for quite some time. Therefore, the study uses recent SOEP data, which also contains information on collective bargaining coverage. A cross-sectional analysis is conducted to examine the effects of works councils in establishments with and without collective bargaining coverage. Similar to studies analysing other outcome variables, the results show that the effect of works councils exists only for employees covered by a collective bargaining agreement.
Abstracts book of oral presentations and poster contributions for the mid-term conference of the Interreg IVB NWE project ForeStClim. The international conference took place in Nancy (France) from 20. to 22. September 2010. The topics of the conference sessions were as follows:rnSession 1: Projecting forest sites and stand shiftsrnSession 2: Climate change and water: modelling across spatial and temporal scalesrnSession 3: Addressing climate change in practical silvicultural decision support
Software and interactive systems that adapt their behavior to the user are often referred to as Adaptive Systems. These systems infer the user's goals, knowledge or preferences by observing the user's actions. A synposis of 43 published studies demonstrated that only few of the existing systems are evaluated empirically. Most studies failed to show an advantage of the user model. A new framework is proposed that categorizes existing studies and defines an evaluation procedure which is able to uncover failures and maladaptations in the user model. It consists of four layers: evaluation of input data, evaluation of inference, evaluation of adaptation decision and evaluation of total interaction. Exemplary, the framework has been applied to the HTML-Tutor, an online-course that adapts to the learners' knowledge. Several empirical studies are described that test the accuracy of the user models, and explore the effects of adaptation to knowledge respectively prior knowledge. Generalization issues of the approach are discussed.
Evaluation of an eye tracking setup for studying visual attention in face-to-face conversations
(2021)
Many eye tracking studies use facial stimuli presented on a display to investigate attentional processing of social stimuli. To introduce a more realistic approach that allows interaction between two real people, we evaluated a new eye tracking setup in three independent studies in terms of data quality, short-term reliability and feasibility. Study 1 measured the robustness, precision and accuracy for calibration stimuli compared to a classical display-based setup. Study 2 used the identical measures with an independent study sample to compare the data quality for a photograph of a face (2D) and the face of the real person (3D). Study 3 evaluated data quality over the course of a real face-to-face conversation and examined the gaze behavior on the facial features of the conversation partner. Study 1 provides evidence that quality indices for the scene-based setup were comparable to those of a classical display-based setup. Average accuracy was better than 0.4° visual angle. Study 2 demonstrates that eye tracking quality is sufficient for 3D stimuli and robust against short interruptions without re-calibration. Study 3 confirms the long-term stability of tracking accuracy during a face-to-face interaction and demonstrates typical gaze patterns for facial features. Thus, the eye tracking setup presented here seems feasible for studying gaze behavior in dyadic face-to-face interactions. Eye tracking data obtained with this setup achieves an accuracy that is sufficient for investigating behavior such as eye contact in social interactions in a range of populations including clinical conditions, such as autism spectrum and social phobia.
Natural hazards are diverse and uneven in time and space, therefore, understanding its complexity is key to save human lives and conserve natural ecosystems. Reducing the outputs obtained after each modelling analysis is key to present the results for stakeholders, land managers and policymakers. So, the main goal of this survey was to present a method to synthesize three natural hazards in one multi-hazard map and its evaluation for hazard management and land use planning. To test this methodology, we took as study area the Gorganrood Watershed, located in the Golestan Province (Iran). First, an inventory map of three different types of hazards including flood, landslides, and gullies was prepared using field surveys and different official reports. To generate the susceptibility maps, a total of 17 geo-environmental factors were selected as predictors using the MaxEnt (Maximum Entropy) machine learning technique. The accuracy of the predictive models was evaluated by drawing receiver operating characteristic-ROC curves and calculating the area under the ROC curve-AUCROC. The MaxEnt model not only implemented superbly in the degree of fitting, but also obtained significant results in predictive performance. Variables importance of the three studied types of hazards showed that river density, distance from streams, and elevation were the most important factors for flood, respectively. Lithological units, elevation, and annual mean rainfall were relevant for detecting landslides. On the other hand, annual mean rainfall, elevation, and lithological units were used for gully erosion mapping in this study area. Finally, by combining the flood, landslides, and gully erosion susceptibility maps, an integrated multi-hazard map was created. The results demonstrated that 60% of the area is subjected to hazards, reaching a proportion of landslides up to 21.2% in the whole territory. We conclude that using this type of multi-hazard map may be a useful tool for local administrators to identify areas susceptible to hazards at large scales as we demonstrated in this research.
In politics and economics, and thus in the official statistics, the precise estimation of indicators for small regions or parts of populations, the so-called Small Areas or domains, is discussed intensively. The design-based estimation methods currently used are mainly based on asymptotic properties and are thus reliable for large sample sizes. With small sample sizes, however, this design based considerations often do not apply, which is why special model-based estimation methods have been developed for this case - the Small Area methods. While these may be biased, they often have a smaller mean squared error (MSE) as the unbiased design based estimators. In this work both classic design-based estimation methods and model-based estimation methods are presented and compared. The focus lies on the suitability of the various methods for their use in official statistics. First theory and algorithms suitable for the required statistical models are presented, which are the basis for the subsequent model-based estimators. Sampling designs are then presented apt for Small Area applications. Based on these fundamentals, both design-based estimators and as well model-based estimation methods are developed. Particular consideration is given in this case to the area-level empirical best predictor for binomial variables. Numerical and Monte Carlo estimation methods are proposed and compared for this analytically unsolvable estimator. Furthermore, MSE estimation methods are proposed and compared. A very popular and flexible resampling method that is widely used in the field of Small Area Statistics, is the parametric bootstrap. One major drawback of this method is its high computational intensity. To mitigate this disadvantage, a variance reduction method for parametric bootstrap is proposed. On the basis of theoretical considerations the enormous potential of this proposal is proved. A Monte Carlo simulation study shows the immense variance reduction that can be achieved with this method in realistic scenarios. This can be up to 90%. This actually enables the use of parametric bootstrap in applications in official statistics. Finally, the presented estimation methods in a large Monte Carlo simulation study in a specific application for the Swiss structural survey are examined. Here problems are discussed, which are of high relevance for official statistics. These are in particular: (a) How small can the areas be without leading to inappropriate or to high precision estimates? (b) Are the accuracy specifications for the Small Area estimators reliable enough to use it for publication? (c) Do very small areas infer in the modeling of the variables of interest? Could they cause thus a deterioration of the estimates of larger and therefore more important areas? (d) How can covariates, which are in different levels of aggregation be used in an appropriate way to improve the estimates. The data basis is the Swiss census of 2001. The main results are that in the author- view, the use of small area estimators for the production of estimates for areas with very small sample sizes is advisable in spite of the modeling effort. The MSE estimates provide a useful measure of precision, but do not reach in all Small Areas the level of reliability of the variance estimates for design-based estimators.
Regional climate models are a valuable tool for the study of the climate processes and climate change in polar regions, but the performance of the models has to be evaluated using experimental data. The regional climate model CCLM was used for simulations for the MOSAiC period with a horizontal resolution of 14 km (whole Arctic). CCLM was used in a forecast mode (nested in ERA5) and used a thermodynamic sea ice model. Sea ice concentration was taken from AMSR2 data (C15 run) and from a high-resolution data set (1 km) derived from MODIS data (C15MOD0 run). The model was evaluated using radiosonde data and data of different profiling systems with a focus on the winter period (November–April). The comparison with radiosonde data showed very good agreement for temperature, humidity, and wind. A cold bias was present in the ABL for November and December, which was smaller for the C15MOD0 run. In contrast, there was a warm bias for lower levels in March and April, which was smaller for the C15 run. The effects of different sea ice parameterizations were limited to heights below 300 m. High-resolution lidar and radar wind profiles as well as temperature and integrated water vapor (IWV) data from microwave radiometers were used for the comparison with CCLM for case studies, which included low-level jets. LIDAR wind profiles have many gaps, but represent a valuable data set for model evaluation. Comparisons with IWV and temperature data of microwave radiometers show very good agreement.
Evaluation of desalination techniques for treating the brackish water of Olushandja sub-basin
(2014)
The groundwater of Olushandja sub-basin as part of Cuvelai basin in central-northern Namibia is saline with TDS content varying between 4,000ppm to 90,000ppm. Based on climatic conditions, this region can be classified as a semi-arid to arid region with an annual rainfall during summer time varying between 200mm to 500mm. The mean annual evaporation potential is about 2,800mm, which is much higher than the annual rainfall. The southern block of this sub-basin is of low population density. It has not been covered by the supply networks for electricity and water. Therefore, the inhabitants are forced to use the untreated groundwater from the hand-dug wells for their daily purposes. This groundwater is not safe for human consumption and therefore needs to be desalinated for that purpose. The goal of this thesis has been to select a suitable desalination technology for that region. The technology to be selected is from those which use renewable energy sources, which have capacity of production from 10m3 to 100m3 per day, which are simple and robust against existing harsh environmental conditions and have already been implemented successfully in some place. Based on these criteria, the technologies which emerged from the literature are: multistage flashing (MSF), multi effect distillation (MED), multi effect humidification (MEH), membrane distillation (MD), reverse osmosis (RO) and electro dialysis reversed (ED). Out of these technologies, RO &amp; ED are based on membrane techniques and MSF, MED &amp; MEH use thermal processes whereas MD technology uses a hybrid process of thermal and membrane techniques for desalinating the water. For evaluation of technical performance, environmental sustainability and financial feasibility of the above mentioned desalination techniques, the following criteria have been used: gained output ratio, recovery rate, pretreatment requirements, sensitivity to feed water quality, post treatment, operating temperature, operating pressure, scaling and fouling potential, corrosion susceptibility, brine disposal, prime energy requirement, mechanical and electrical power output, heat energy, running costs and water generation costs. The data regarding the performance standards of the successfully implemented desalination techniques have been obtained from the literature of performance benchmarks. The Utility Value Analysis Tool of the Rafter-Group of Multi-Criteria Analysis (MCA) has been used for measuring the performance score of a technology. To perform the utility analysis, an evaluation matrix has to be constructed through the following procedures: selection of the decision options (or assessment groups), identification of the evaluation criteria, measurement of performance and transformation of the units. Then the criteria under the objective groups are assigned a level of importance for determining their weights.To perform the sensitivity analysis the level of importance of a criterion is changed by giving more weight or rate to the assessment group of interest (or study). Within the assessment group of interests, the best performing desalination technology has been selected according to the outcome of the sensitivity analysis. The important conclusions of this study are the identification of the capabilities of thermal and membrane based small scale desalination technologies and their applicability based on site specific needs. The sensitivity analysis indicates that the MED technology is the most environmental friendly technology that uses minimum energy and produces least concentrated brine for disposal. The ED technology has emerged to be technically suitable, but it is only applicable when source water has less than 12.000 ppm salt content. The MSF process has favorable thermal efficiency and it is insensitive to feed water quality. Its major drawbacks are energy needs and post treatment requirements that affected its net score. The MD and MSF process have scored the lowest for the technical and economic assessment groups and are concluded not to be suitable for Olushandja sub-basin. The MEH process is cheaper and technically more appropriate than the MED in the two assessment groups. Based on the above mentioned evaluations, this study concluded that Olushandja sub-basin needs more data collection on the geological profile, distinctive identification of aquifers and evidence on the interaction between the aquifers. From the best available data obtained, it could not be established with certainty where the highest level of salinity can be found in the profile, or how the geological profile is layered. More data on ground water quality for spatial overview of the trends and pattern of the sub-basin will be useful in drawing better conclusion on the specific desalination technology needed which is suitable for a specified village or living space.
Evaluative conditioning (EC) refers to changes in liking that are due to the pairing of stimuli, and is one of the effects studied in order to understand the processes of attitude formation. Initially, EC had been conceived of as driven by processes that are unique to the formation of attitudes, and that occur independent of whether or not individuals engage in conscious and effortful propositional processes. However, propositional processes have gained considerable popularity as an explanatory concept for the boundary conditions observed in EC studies, with some authors going as far as to suggest that the evidence implies that EC is driven primarily by propositional processes. In this monograph I present research which questions the validity of this claim, and I discuss theoretical challenges and avenues for future EC research.
Due to the transition towards climate neutrality, energy markets are rapidly evolving. New technologies are developed that allow electricity from renewable energy sources to be stored or to be converted into other energy commodities. As a consequence, new players enter the markets and existing players gain more importance. Market equilibrium problems are capable of capturing these changes and therefore enable us to answer contemporary research questions with regard to energy market design and climate policy.
This cumulative dissertation is devoted to the study of different market equilibrium problems that address such emerging aspects in liberalized energy markets. In the first part, we review a well-studied competitive equilibrium model for energy commodity markets and extend this model by sector coupling, by temporal coupling, and by a more detailed representation of physical laws and technical requirements. Moreover, we summarize our main contributions of the last years with respect to analyzing the market equilibria of the resulting equilibrium problems.
For the extension regarding sector coupling, we derive sufficient conditions for ensuring uniqueness of the short-run equilibrium a priori and for verifying uniqueness of the long-run equilibrium a posteriori. Furthermore, we present illustrative examples that each of the derived conditions is indeed necessary to guarantee uniqueness in general.
For the extension regarding temporal coupling, we provide sufficient conditions for ensuring uniqueness of demand and production a priori. These conditions also imply uniqueness of the short-run equilibrium in case of a single storage operator. However, in case of multiple storage operators, examples illustrate that charging and discharging decisions are not unique in general. We conclude the equilibrium analysis with an a posteriori criterion for verifying uniqueness of a given short-run equilibrium. Since the computation of equilibria is much more challenging due to the temporal coupling, we shortly review why a tailored parallel and distributed alternating direction method of multipliers enables to efficiently compute market equilibria.
For the extension regarding physical laws and technical requirements, we show that, in nonconvex settings, existence of an equilibrium is not guaranteed and that the fundamental welfare theorems therefore fail to hold. In addition, we argue that the welfare theorems can be re-established in a market design in which the system operator is committed to a welfare objective. For the case of a profit-maximizing system operator, we propose an algorithm that indicates existence of an equilibrium and that computes an equilibrium in the case of existence. Based on well-known instances from the literature on the gas and electricity sector, we demonstrate the broad applicability of our algorithm. Our computational results suggest that an equilibrium often exists for an application involving nonconvex but continuous stationary gas physics. In turn, integralities introduced due to the switchability of DC lines in DC electricity networks lead to many instances without an equilibrium. Finally, we state sufficient conditions under which the gas application has a unique equilibrium and the line switching application has finitely many.
In the second part, all preprints belonging to this cumulative dissertation are provided. These preprints, as well as two journal articles to which the author of this thesis contributed, are referenced within the extended summary in the first part and contain more details.
Teamwork is ubiquitous in the modern workplace. However, it is still unclear whether various behavioral economic factors de- or increase team performance. Therefore, Chapters 2 to 4 of this thesis aim to shed light on three research questions that address different determinants of team performance.
Chapter 2 investigates the idea of an honest workplace environment as a positive determinant of performance. In a work group, two out of three co-workers can obtain a bonus in a dice game. By misreporting a secret die roll, cheating without exposure is an option in the game. Contrary to claims on the importance of honesty at work, we do not observe a reduction in the third co-worker's performance, who is an uninvolved bystander when cheating takes place.
Chapter 3 analyzes the effect of team size on performance in a workplace environment in which either two or three individuals perform a real-effort task. Our main result shows that the difference in team size is not harmful to task performance on average. In our discussion of potential mechanisms, we provide evidence on ongoing peer effects. It appears that peers are able to alleviate the potential free-rider problem emerging out of working in a larger team.
In Chapter 4, the role of perceived co-worker attractiveness for performance is analyzed. The results show that task performance is lower, the higher the perceived attractiveness of co-workers, but only in opposite-sex constellations.
The following Chapter 5 analyzes the effect of offering an additional payment option in a fundraising context. Chapter 6 focuses on privacy concerns of research participants.
In Chapter 5, we conduct a field experiment in which, participants have the opportunity to donate for the continuation of an art exhibition by either cash or cash and an additional cashless payment option (CPO). The treatment manipulation is completed by framing the act of giving either as a donation or pay-what-you-want contribution. Our results show that donors shy away from using the CPO in all treatment conditions. Despite that, there is no negative effect of the CPO on the frequency of financial support and its magnitude.
In Chapter 6, I conduct an experiment to test whether increased transparency of data processing affects data disclosure and whether the results change if it is indicated that the implementation of the GDPR happened involuntarily. I find that increased transparency raises the number of participants who do not disclose personal data by 21 percent. However, this is not the case in the involuntary-signal treatment, where the share of non-disclosures is relatively high in both conditions.
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.
With the start of the Coronavirus (COVID-19) pandemic, the global education system has a faced immense challenges and disruptions resulting in and the necessity for an immediate redesign of teaching and learning in the school context. Face-to-face classroom instruction had to be replaced by ‘emergency remote teaching’, requiring teacher to adapt their daily routines to a new and unprecedented educational reality. Researchers and policymakers worldwide have agreed that, despite the fact that efforts were made to immediately adapt to emergency remote teaching, disadvantaged and vulnerable students may be especially at risk in emergency remote teaching. Given the differences in schooling organization across countries during the COVID-19 pandemic it can be expected that teachers performed inclusive instructional practices significantly different. Against the unpredictable situation, cross-country research has been urgently required to provide data that could inform education policy. Thus, this study explored teachers’ perceptions of supporting at risk students during the first COVID-19 school closures, as well as examining teachers’ inclusive teaching practices in three countries: Germany, Austria and Portugal. ANOVA results revealed important country differences. In general, it appears that teachers in Germany and Austria reported to have implemented less practices to address vulnerable and at-risk students compared to Portuguese teachers. Implications of the results, as well as further lines of research are outlined.
Extension of an Open GEOBIA Framework for Spatially Explicit Forest Stratification with Sentinel-2
(2022)
Spatially explicit information about forest cover is fundamental for operational forest management and forest monitoring. Although open-satellite-based earth observation data in a spatially high resolution (i.e., Sentinel-2, ≤10 m) can cover some information needs, spatially very high-resolution imagery (i.e., aerial imagery, ≤2 m) is needed to generate maps at a scale suitable for regional and local applications. In this study, we present the development, implementation, and evaluation of a Geographic Object-Based Image Analysis (GEOBIA) framework to stratify forests (needleleaved, broadleaved, non-forest) in Luxembourg. The framework is exclusively based on open data and free and open-source geospatial software. Although aerial imagery is used to derive image objects with a 0.05 ha minimum size, Sentinel-2 scenes of 2020 are the basis for random forest classifications in different single-date and multi-temporal feature setups. These setups are compared with each other and used to evaluate the framework against classifications based on features derived from aerial imagery. The highest overall accuracies (89.3%) have been achieved with classification on a Sentinel-2-based vegetation index time series (n = 8). Similar accuracies have been achieved with classification based on two (88.9%) or three (89.1%) Sentinel-2 scenes in the greening phase of broadleaved forests. A classification based on color infrared aerial imagery and derived texture measures only achieved an accuracy of 74.5%. The integration of the texture measures into the Sentinel-2-based classification did not improve its accuracy. Our results indicate that high resolution image objects can successfully be stratified based on lower spatial resolution Sentinel-2 single-date and multi-temporal features, and that those setups outperform classifications based on aerial imagery only. The conceptual framework of spatially high-resolution image objects enriched with features from lower resolution imagery facilitates the delivery of frequent and reliable updates due to higher spectral and temporal resolution. The framework additionally holds the potential to derive additional information layers (i.e., forest disturbance) as derivatives of the features attached to the image objects, thus providing up-to-date information on the state of observed forests.
Extension of inexact Kleinman-Newton methods to a general monotonicity preserving convergence theory
(2011)
The thesis at hand considers inexact Newton methods in combination with algebraic Riccati equation. A monotone convergence behaviour is proven, which enables a non-local convergence. Above relation is transferred to a general convergence theory for inexact Newton methods securing the monotonicity of the iterates for convex or concave mappings. Several application prove the pratical benefits of the new developed theory.
Variational inequality problems constitute a common basis to investigate the theory and algorithms for many problems in mathematical physics, in economy as well as in natural and technical sciences. They appear in a variety of mathematical applications like convex programming, game theory and economic equilibrium problems, but also in fluid mechanics, physics of solid bodies and others. Many variational inequalities arising from applications are ill-posed. This means, for example, that the solution is not unique, or that small deviations in the data can cause large deviations in the solution. In such a situation, standard solution methods converge very slowly or even fail. In this case, so-called regularization methods are the methods of choice. They have the advantage that an ill-posed original problem is replaced by a sequence of well-posed auxiliary problems, which have better properties (like, e.g., a unique solution and a better conditionality). Moreover, a suitable choice of the regularization term can lead to unconstrained auxiliary problems that are even equivalent to optimization problems. The development and improvement of such methods are a focus of current research, in which we take part with this thesis. We suggest and investigate a logarithmic-quadratic proximal auxiliary problem (LQPAP) method that combines the advantages of the well-known proximal-point algorithm and the so-called auxiliary problem principle. Its exploration and convergence analysis is one of the main results in this work. The LQPAP method continues the recent developments of regularization methods. It includes different techniques presented in literature to improve the numerical stability: The logarithmic-quadratic distance function constitutes an interior point effect which allows to treat the auxiliary problems as unconstrained ones. Furthermore, outer operator approximations are considered. This simplifies the numerical solution of variational inequalities with multi-valued operators since, for example, bundle-techniques can be applied. With respect to the numerical practicability, inexact solutions of the auxiliary problems are allowed using a summable-error criterion that is easy to implement. As a further advantage of the logarithmic-quadratic distance we verify that it is self-concordant (in the sense of Nesterov/Nemirovskii). This motivates to apply the Newton method for the solution of the auxiliary problems. In the numerical part of the thesis the LQPAP method is applied to linearly constrained, differentiable and nondifferentiable convex optimization problems, as well as to nonsymmetric variational inequalities with co-coercive operators. It can often be observed that the sequence of iterates reaches the boundary of the feasible set before being close to an optimal solution. Against this background, we present the strategy of under-relaxation, which robustifies the LQPAP method. Furthermore, we compare the results with an appropriate method based on Bregman distances (BrPAP method). For differentiable, convex optimization problems we describe the implementation of the Newton method to solve the auxiliary problems and carry out different numerical experiments. For example, an adaptive choice of the initial regularization parameter and a combination of an Armijo and a self-concordance step size are evaluated. Test examples for nonsymmetric variational inequalities are hardly available in literature. Therefore, we present a geometric and an analytic approach to generate test examples with known solution(s). To solve the auxiliary problems in the case of nondifferentiable, convex optimization problems we apply the well-known bundle technique. The implementation is described in detail and the involved functions and sequences of parameters are discussed. As far as possible, our analysis is substantiated by new theoretical results. Furthermore, it is explained in detail how the bundle auxiliary problems are solved with a primal-dual interior point method. Such investigations have by now only been published for Bregman distances. The LQPAP bundle method is again applied to several test examples from literature. Thus, this thesis builds a bridge between theoretical and numerical investigations of solution methods for variational inequalities.
Given a compact set K in R^d, the theory of extension operators examines the question, under which conditions on K, the linear and continuous restriction operators r_n:E^n(R^d)→E^n(K),f↦(∂^α f|_K)_{|α|≤n}, n in N_0 and r:E(R^d)→E(K),f↦(∂^α f|_K)_{α in N_0^d}, have a linear and continuous right inverse. This inverse is called extension operator and this problem is known as Whitney's extension problem, named after Hassler Whitney. In this context, E^n(K) respectively E(K) denote spaces of Whitney jets of order n respectively of infinite order. With E^n(R^d) and E(R^d), we denote the spaces of n-times respectively infinitely often continuously partially differentiable functions on R^d. Whitney already solved the question for finite order completely. He showed that it is always possible to construct a linear and continuous right inverse E_n for r_n. This work is concerned with the question of how the existence of a linear and continuous right inverse of r, fulfilling certain continuity estimates, can be characterized by properties of K. On E(K), we introduce a full real scale of generalized Whitney seminorms (|·|_{s,K})_{s≥0}, where |·|_{s,K} coincides with the classical Whitney seminorms for s in N_0. We equip also E(R^d) with a family (|·|_{s,L})_{s≥0} of those seminorms, where L shall be a a compact set with K in L-°. This family of seminorms on E(R^d) suffices to characterize the continuity properties of an extension operator E, since we can without loss of generality assume that E(E(K)) in D^s(L).
In Chapter 2, we introduce basic concepts and summarize the classical results of Whitney and Stein.
In Chapter 3, we modify the classical construction of Whitney's operators E_n and show that |E_n(·)|_{s,L}≤C|·|_{s,K} for s in[n,n+1).
In Chapter 4, we generalize a result of Frerick, Jordá and Wengenroth and show that LMI(1) for K implies the existence of an extension operator E without loss of derivatives, i.e. we have it fulfils |E(·)|_{s,L}≤C|·|_{s,K} for all s≥0. We show that a large class of self similar sets, which includes the Cantor set and the Sierpinski triangle, admits an extensions operator without loss of derivatives.
In Chapter 5 we generalize a result of Frerick, Jordá and Wengenroth and show that WLMI(r) for r≥1 implies the existence of a tame linear extension operator E having a homogeneous loss of derivatives, such that |E(·)|_{s,L}≤C|·|_{(r+ε)s,K} for all s≥0 and all ε>0.
In the last chapter we characterize the existence of an extension operator having an arbitrary loss of derivatives by the existence of measures on K.
Fast and Slow Effects of Cortisol on Several Functions of the Central Nervous System in Humans
(2014)
Cortisol is one of the key substances released during stress to restore homeostasis. Our knowledge of the impact of this glucocorticoid on cognition and behavior in humans is, however, still limited. Two modes of action of cortisol are known, a rapid, nongenomic and a slow, genomic mode. Both mechanisms appear to be involved in mediating the various effects of stress on cognition. Here, three experiments are presented that investigated fast and slow effects of cortisol on several functions of the human brain. The first experiment investigated the interaction between insulin and slow, genomic cortisol effects on resting regional cerebral blood flow (rCBF) in 48 young men. A bilateral, locally distinct increase in rCBF in the insular cortex was observed 37 to 58 minutes after intranasal insulin admission. Cortisol did not influence rCBF, neither alone nor in interaction with insulin. This finding suggests that cortisol does not influence resting cerebral blood flow within a genomic timeframe. The second experiment examined fast cortisol effects on memory retrieval. 40 participants (20 of them female) learned associations between neutral male faces and social descriptions and were tested for recall one week later. Cortisol administered intravenously 8 minutes before retrieval influenced recall performance in an inverted U-shaped dose-response relationship. This study demonstrates a rapid, presumably nongenomic cortisol effect on memory retrieval in humans. The third experiment studied rapid cortisol effects on early multisensory integration. 24 male participants were tested twice in a focused cross-modal choice reaction time paradigm, once after cortisol and once after placebo infusion. Cortisol acutely enhanced the integration of visual targets and startling auditory distractors, when both stimuli appeared in the same sensory hemi-field. The rapidity of effect onset strongly suggests that cortisol changes multisensory integration by a nongenomic mechanism. The work presented in this thesis highlights the essential role of cortisol as a fast acting agent during the stress response. Both the second and the third experiment provide new evidence of nongenomic cortisol effects on human cognition and behavior. Future studies should continue to investigate the impact of rapid cortisol effects on the functioning of the human brain.
This thesis introduces a calibration problem for financial market models based on a Monte Carlo approximation of the option payoff and a discretization of the underlying stochastic differential equation. It is desirable to benefit from fast deterministic optimization methods to solve this problem. To be able to achieve this goal, possible non-differentiabilities are smoothed out with an appropriately chosen twice continuously differentiable polynomial. On the basis of this so derived calibration problem, this work is essentially concerned about two issues. First, the question occurs, if a computed solution of the approximating problem, derived by applying Monte Carlo, discretizing the SDE and preserving differentiability is an approximation of a solution of the true problem. Unfortunately, this does not hold in general but is linked to certain assumptions. It will turn out, that a uniform convergence of the approximated objective function and its gradient to the true objective and gradient can be shown under typical assumptions, for instance the Lipschitz continuity of the SDE coefficients. This uniform convergence then allows to show convergence of the solutions in the sense of a first order critical point. Furthermore, an order of this convergence in relation to the number of simulations, the step size for the SDE discretization and the parameter controlling the smooth approximation of non-differentiabilites will be shown. Additionally the uniqueness of a solution of the stochastic differential equation will be analyzed in detail. Secondly, the Monte Carlo method provides only a very slow convergence. The numerical results in this thesis will show, that the Monte Carlo based calibration indeed is feasible if one is concerned about the calculated solution, but the required calculation time is too long for practical applications. Thus, techniques to speed up the calibration are strongly desired. As already mentioned above, the gradient of the objective is a starting point to improve efficiency. Due to its simplicity, finite differences is a frequently chosen method to calculate the required derivatives. However, finite differences is well known to be very slow and furthermore, it will turn out, that there may also occur severe instabilities during optimization which may lead to the break down of the algorithm before convergence has been reached. In this manner a sensitivity equation is certainly an improvement but suffers unfortunately from the same computational effort as the finite difference method. Thus, an adjoint based gradient calculation will be the method of choice as it combines the exactness of the derivative with a reduced computational effort. Furthermore, several other techniques will be introduced throughout this thesis, that enhance the efficiency of the calibration algorithm. A multi-layer method will be very effective in the case, that the chosen initial value is not already close to the solution. Variance reduction techniques are helpful to increase accuracy of the Monte Carlo estimator and thus allow for fewer simulations. Storing instead of regenerating the random numbers required for the Brownian increments in the SDE will be efficient, as deterministic optimization methods anyway require to employ the identical random sequence in each function evaluation. Finally, Monte Carlo is very well suited for a parallelization, which will be done on several central processing units (CPUs).
This paper provides an overview of five major shifts in urban water supply governance in relation to changing paradigms in the water sector as a whole and in water-related research: i) the municipal hydraulic paradigm in the Global North; ii) its travel to cities in the Global South; iii) the shift from government to governance; iv) the (private) utility model and v) its contestation. The articulation of each shift in the Ghanaian context is described from the creation of the first water supply system during colonial time to the recent contestation against private corporate sector participation. Current challenges are outlined together with new pathways for researching urban water governance. The paper is based on a literature review conducted in 2015 and serves as a background study for further research within the WaterPower project.
As in many other cities of the Global South, in Accra and its Greater Metropolitan Area (GAMA) water provision for drinking, domestic and productive uses is coproduced by multiple provisioning and delivery modalities. This paper contributes to the overall understanding of sociospatial conditions of urban water (in)security in GAMA. By looking at the geography of infrastructure and inequalities in water access, it seeks to identify patterns of uneven access to water. The first part provides an overview of urban water supply in GAMA, focusing on water infrastructure and the perspective of water providers. In the second part, households’ access strategies are discussed by combining both quantitative and qualitative perspectives. The paper brings together literature research and empirical material collected during fieldwork in the Ghanaian capital city.
Fibromyalgia is a disorder of unknown etiology characterized by widespread, chronic musculoskeletal pain of at least three month duration and pressure hyperalgesia at specific tender points on clinical examination. The disorder is accompanied by a multitude of additional symptoms such as fatigue, sleep disturbances, morning stiffness, depression, and anxiety. In terms of biological disturbances, low cortisol concentrations have been repeatedly observed in blood and urine samples of fibromyalgia patients, both under basal and stress-induced conditions. The aim of this dissertation was to investigate the presence of low cortisol concentrations (hypocortisolism) and potential accompanying alterations on sympathetic and immunological levels in female fibromyalgia patients. Beside the expected hypocortisolism, a higher norepinephrine secretion and lower natural killer cell levels were found in the patient group compared to a control group consisting of healthy, age-matched women. In addition, an increased activity of some pro-inflammatory markers was observed thus leading to alterations in the balance of pro-/anti-inflammatory activity. The results underline the relevance of simultaneous investigations of interacting bodily systems for a better understanding of underlying biological mechanisms in stress-related disorders.
With the ongoing trend towards deep learning in the remote sensing community, classical pixel based algorithms are often outperformed by convolution based image segmentation algorithms. This performance was mostly validated spatially, by splitting training and validation pixels for a given year. Though generalizing models temporally is potentially more difficult, it has been a recent trend to transfer models from one year to another, and therefore to validate temporally. The study argues that it is always important to check both, in order to generate models that are useful beyond the scope of the training data. It shows that convolutional neural networks have potential to generalize better than pixel based models, since they do not rely on phenological development alone, but can also consider object geometry and texture. The UNET classifier was able to achieve the highest F1 scores, averaging 0.61 in temporal validation samples, and 0.77 in spatial validation samples. The theoretical potential for overfitting geometry and just memorizing the shape of fields that are maize has been shown to be insignificant in practical applications. In conclusion, kernel based convolutions can offer a large contribution in making agricultural classification models more transferable, both to other regions and to other years.
The availability of data on the feeding habits of species of conservation value may be of great importance to develop analyses for both scientific and management purposes. Stomach flushing is a harmless technique that allowed us to collect extensive data on the feeding habits of six Hydromantes species. Here, we present two datasets originating from a three-year study performed in multiple seasons (spring and autumn) on 19 different populations of cave salamanders. The first dataset contains data of the stomach content of 1,250 salamanders, where 6,010 items were recognized; the second one reports the size of the intact prey items found in the stomachs. These datasets integrate considerably data already available on the diet of the European plethodontid salamanders, being also of potential use for large scale meta-analyses on amphibian diet.
The article deals with the responsibility of the financial sector under criminal law in Germany. This question has been of special interest since the beginning of the financial crisis. The author argues that the transactions of asset-backed securities based on American subprime mortgages fulfill all legal elements of the criminal offence "breach of trust" (Untreue). From the author's point of view, the people's legal loyalty would be severely affected if there were no criminal proceedings against such bankers who purchased those toxic asset-backed securities without sufficient information on their structure and value. Refraining from criminal prosecution even in cases causing high loss would send a dangerous signal towards the investment banking industry.
With two-thirds to three-quarters of all companies, family firms are the most common firm type worldwide and employ around 60 percent of all employees, making them of considerable importance for almost all economies. Despite this high practical relevance, academic research took notice of family firms as intriguing research subjects comparatively late. However, the field of family business research has grown eminently over the past two decades and has established itself as a mature research field with a broad thematic scope. In addition to questions relating to corporate governance, family firm succession and the consideration of entrepreneurial families themselves, researchers mainly focused on the impact of family involvement in firms on their financial performance and firm strategy. This dissertation examines the financial performance and capital structure of family firms in various meta-analytical studies. Meta-analysis is a suitable method for summarizing existing empirical findings of a research field as well as identifying relevant moderators of a relationship of interest.
First, the dissertation examines the question whether family firms show better financial performance than non-family firms. A replication and extension of the study by O’Boyle et al. (2012) based on 1,095 primary studies reveals a slightly better performance of family firms compared to non-family firms. Investigating the moderating impact of methodological choices in primary studies, the results show that outperformance holds mainly for large and publicly listed firms and with regard to accounting-based performance measures. Concerning country culture, family firms show better performance in individualistic countries and countries with a low power distance.
Furthermore, this dissertation investigates the sensitivity of family firm performance with regard to business cycle fluctuations. Family firms show a pro-cyclical performance pattern, i.e. their relative financial performance compared to non-family firms is better in economically good times. This effect is particularly pronounced in Anglo-American countries and emerging markets.
In the next step, a meta-analytic structural equation model (MASEM) is used to examine the market valuation of public family firms. In this model, profitability and firm strategic choices are used as mediators. On the one hand, family firm status itself does not have an impact on firms‘ market value. On the other hand, this study finds a positive indirect effect via higher profitability levels and a negative indirect effect via lower R&D intensity. A split consideration of family ownership and management shows that these two effects are mainly driven by family ownership, while family management results in less diversification and internationalization.
Finally, the dissertation examines the capital structure of public family firms. Univariate meta-analyses indicate on average lower leverage ratios in family firms compared to non-family firms. However, there is significant heterogeneity in mean effect sizes across the 45 countries included in the study. The results of a meta-regression reveal that family firms use leverage strategically to secure their controlling position in the firm. While strong creditor protection leads to lower leverage ratios in family firms, strong shareholder protection has the opposite effect.
Financing of Small and Medium-Sized Enterprises in Europe - Financing Patterns and 'Crowdfunding'
(2015)
Small and medium-sized enterprises (SMEs) play a vital role for the innovativeness, economic growth and competitiveness of Europe. One of the most pressing problems of SMEs is access to finance to ensure their survival and growth. This dissertation uses both quantitative and qualitative exploratory research methods and increases with its holistic approach the transparency in SME financing. The results of a cluster analysis including 12,726 SMEs in 28 European countries reveal that SME financing in Europe is not homogenous but that different financing patterns exist which differ according to the number of financing instruments used and the combinations thereof. Furthermore, the SME financing types can be profiled according to their firm-, product-, industry- and country-specific characteristics. The results of this analysis provide some support for prior findings that smaller, younger and innovative SMEs suffer from a financing gap which cannot be closed with traditional financing instruments. One alternative to close this financing gap is crowdfunding. Even though crowdfunding has shown tremendous growth rates over the past few years, little is known about the determinants of this financing alternative. This dissertation systematically analyses the existing scientific literature on crowdfunding as an alternative in SME financing and reveals existing research gaps. Afterwards, the focus is on the role of investor communication as a way to reduce information asymmetries of the crowd in equity-based crowdfunding. The results of 24 interviews with market participants in equity-based crowdfunding reveal that crowd investors seem to replace personal contacts with alternative ways of communicating, which can be characterized as pseudo-personal (i.e., by using presentation videos, social media and investor relations channels). In addition, it was found that third party endorsements (e.g., other crowd investors, professional investors, customers and platforms) reduce the information asymmetries of crowd investors and hence, increase the likelihood of their investment.
Auf politischer Ebene hat die Finanzierung von Kleinstunternehmen, kleinen und mittleren Unternehmen (KMU) durch die europäische Finanz- und Wirtschaftskrise eine hohe Bedeutung erhalten, da mehr als 99% aller europäischen Unternehmen in Europa dieser Kategorie angehören. Als Reaktion auf die oftmals schwierige Finanzierungssituation von KMU, die maßgeblich zur Gefährdung der Innovationsfähigkeit und der Entwicklung der europäischen Wirtschaft beitragen kann, wurden spezielle staatliche Programme aufgelegt. Trotz des vermehrten Interesses auf politischer und akademischer Ebene bezüglich KMU-Finanzierung, gibt es jedoch auf europäischer Ebene nur wenig empirische Evidenz. Diese Dissertation beschäftigt sich daher in fünf verschiedenen empirischen Studien zu aktuellen Forschungslücken hinsichtlich der Finanzierung von Kleinstunternehmen, kleinen und mittleren Unternehmen in Europa und mit neuen Finanzierungsinstrumenten für innovative Unternehmen oder Start-Ups.
Zunächst wird basierend auf zwei empirischen Untersuchungen (Kapitel 2 und 3) der Status Quo der KMU-Finanzierung in Europa dargelegt. Die Finanzierung von KMU in Europa ist sehr heterogen. Einerseits sind KMU als Gruppe keine homogene Gruppe, da Kleinstunternehmen (< 10 Mitarbeiter), kleine (10–49 Mitarbeiter) und mittlere (50–249 Mitarbeiter) Unternehmen sich nicht nur in ihren Charakteristiken unterscheiden, sondern auch unterschiedliche Finanzierungsmöglichkeiten und -bedürfnisse besitzen. Andererseits existieren Länderunterschiede in der Finanzierung von KMU in Europa. Die Ergebnisse dieser beiden Studien (Kapitel 2 und 3), die auf einer Umfrage der Europäischen Zentralbank und der Europäischen Kommission („SAFE survey“) beruhen, verdeutlichen dies: KMU in Europa verwenden unterschiedliche Finanzierungsmuster und nutzen Finanzierungsmuster komplementär oder substitutiv zueinander. Die verschiedenen Finanzierungsmuster sind wiederum gekennzeichnet durch firmen-, produkt-, und länderspezifische Charakteristika, aber auch durch makroökonomische Variablen (z. B. Inflationsraten).
In Kapitel 3 der Dissertation werden gezielt die Unterschiede zwischen der Finanzierung von Kleinstunternehmen im Vergleich zu kleinen und mittleren Unternehmen untersucht. Während kleine und mittlere Unternehmen eine Vielzahl an verschiedenen Finanzierungsinstrumenten parallel zueinander nutzen (z. B. subventionierte Bankkredite parallel zu Banken-, Überziehungs- und Lieferantenkrediten), greifen Kleinstunternehmen auf wenige Instrumente gleichzeitig zurück (insbesondere kurzfristiges Fremdkapital). Folglich finanzieren sich Kleinstunternehmen entweder intern oder über Überziehungskredite. Die Ergebnisse der Dissertation zeigen somit, dass die Finanzierung der KMU nicht homogen ist. Insbesondere Kleinstunternehmen sollten als eine eigenständige Gruppe innerhalb der KMU mit charakteristischen Finanzierungsmustern behandelt werden.
Innovative Firmen und Start-Ups gelten als wichtiger Motor für die Entwicklung der regionalen Wirtschaft. Auch sie werden in der akademischen Literatur häufig mit Finanzierungsschwierigkeiten in Verbindung gebracht, die das Wachstum und Überleben dieser Unternehmen erschwert. Der zweite Teil der Dissertation beinhaltet daher zwei empirische Studien zu dieser Thematik. Zunächst werden in Kapitel 4 in einer ersten Studie die regionalen und firmenspezifischen Faktoren untersucht, die den Output des geistigen Eigentums erhöhen. Insbesondere regionale Faktoren wurden bisher unzureichend untersucht, welche jedoch speziell für die politischen Entscheidungsträger von besonderer Relevanz sind. Die Ergebnisse dieser Studie zeigen, dass der Erhalt von Venture Capital neben der Firmengröße einen signifikanten Einfluss auf die Höhe des geistigen Eigentums haben. Zwar spielen technische Universitäten keine Rolle bezüglich des Outputs, jedoch zeigt sich ein signifikant positiver Effekt der Studentenrate auf den jeweiligen Output des geistigen Eigentums. Basierend auf diesen Ergebnissen wird in einer zweiten Studie gezielt auf das Finanzierungsinstrument Venture Capital eingegangen und zwischen verschiedenen VC Typen unterschieden: staatliche, unabhängige und Corporate Venture Capital Firmen. Die Ergebnisse zeigen, dass insbesondere Regionen mit einem Angebot an qualifiziertem Humankapital staatliche Venture Capital Investitionen anziehen. Des Weiteren investieren insbesondere Corporate und staatliche Venture Capital Firmen vermehrt in ländliche Regionen.
Als neues Finanzierungsinstrument für besonders innovative Unternehmer hat sich das „Initial Coin Offering (ICO)“ in den letzten Jahren herauskristallisiert, womit sich Kapitel 5 näher beschäftigt. Mithilfe einer Zeitreihenanalyse werden Marktzyklen von ICO Kampagnen, bitcoin und Ether Preisen analysiert. Die Ergebnisse dieser Studie zeigen, dass vergangene ICOs die folgenden ICOs positiv beeinflussen. Zudem haben ICOs einen negativen Einfluss auf die Kryptowährungen Bitcoin und Ether, wohingegen sich der Preis des bitcoin positiv auf den Preis des Ethers auswirkt.
Finding behavioral parameterization for a 1-D water balance model by multi-criteria evaluation
(2019)
Evapotranspiration is often estimated by numerical simulation. However, to produce accurate simulations, these models usually require on-site measurements for parameterization or calibration. We have to make sure that the model realistically reproduces both, the temporal patterns of soil moisture and evapotranspiration. In this study, we combine three sources of information: (i) measurements of sap velocities; (ii) soil moisture; and (iii) expert knowledge on local runoff generation and water balance to define constraints for a “behavioral” forest stand water balance model. Aiming for a behavioral model, we adjusted soil moisture at saturation, bulk resistance parameters and the parameters of the water retention curve (WRC). We found that the shape of the WRC influences substantially the behavior of the simulation model. Here, only one model realization could be referred to as “behavioral”. All other realizations failed for a least one of our evaluation criteria: Not only transpiration and soil moisture are simulated consistently with our observations, but also total water balance and runoff generation processes. The introduction of a multi-criteria evaluation scheme for the detection of unrealistic outputs made it possible to identify a well performing parameter set. Our findings indicate that measurement of different fluxes and state variables instead of just one and expert knowledge concerning runoff generation facilitate the parameterization of a hydrological model.
A basic assumption of standard small area models is that the statistic of interest can be modelled through a linear mixed model with common model parameters for all areas in the study. The model can then be used to stabilize estimation. In some applications, however, there may be different subgroups of areas, with specific relationships between the response variable and auxiliary information. In this case, using a distinct model for each subgroup would be more appropriate than employing one model for all observations. If no suitable natural clustering variable exists, finite mixture regression models may represent a solution that „lets the data decide“ how to partition areas into subgroups. In this framework, a set of two or more different models is specified, and the estimation of subgroup-specific model parameters is performed simultaneously to estimating subgroup identity, or the probability of subgroup identity, for each area. Finite mixture models thus offer a fexible approach to accounting for unobserved heterogeneity. Therefore, in this thesis, finite mixtures of small area models are proposed to account for the existence of latent subgroups of areas in small area estimation. More specifically, it is assumed that the statistic of interest is appropriately modelled by a mixture of K linear mixed models. Both mixtures of standard unit-level and standard area-level models are considered as special cases. The estimation of mixing proportions, area-specific probabilities of subgroup identity and the K sets of model parameters via the EM algorithm for mixtures of mixed models is described. Eventually, a finite mixture small area estimator is formulated as a weighted mean of predictions from model 1 to K, with weights given by the area-specific probabilities of subgroup identity.
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.
The microbial enzyme alkaline phosphatase contributes to the removal of organic phosphorus compounds from wastewaters. To cope with regulatory threshold values for permitted maximum phosphor concentrations in treated wastewaters, a high activity of this enzyme in the biological treatment stage, e.g., the activated sludge process, is required. To investigate the reaction dynamics of this enzyme, to analyze substrate selectivities, and to identify potential inhibitors, the determination of enzyme kinetics is necessary. A method based on the application of the synthetic fluorogenic substrate 4-methylumbelliferyl phosphate is proven for soils, but not for activated sludges. Here, we adapt this procedure to the latter. The adapted method offers the additional benefit to determine inhibition kinetics. In contrast to conventional photometric assays, no particle removal, e.g., of sludge pellets, is required enabling the analysis of the whole sludge suspension as well as of specific sludge fractions. The high sensitivity of fluorescence detection allows the selection of a wide substrate concentration range for sound modeling of kinetic functions.
- Fluorescence array technique for fast and sensitive analysis of high sample numbers
- No need for particle separation – analysis of the whole (diluted) sludge suspension
- Simultaneous determination of standard and inhibition kinetics
Although it has been demonstrated that nociceptive processing can be modulated by heterotopically and concurrently applied noxious stimuli, the nature of brain processes involved in this percept modulation in healthy subjects remains elusive. Using functional magnetic resonance imaging (fMRI) we investigated the effect of noxious counter-stimulation on pain processing. FMRI scans (1.5 T; block-design) were performed in 34 healthy subjects (median age: 23.5 years; range: 20-31 yrs.) during combined and single application (duration: 15 s; ISI=36 s incl. 6 s rating time) of noxious interdigital-web pinching (intensity range: 6-15 N) and contact-heat (45-49 -°C) presented in pseudo-randomized order during two runs separated by approx. 15 min with individually adjusted equi-intense stimuli. In order to control for attention artifacts, subjects were instructed to maintain their focus either on the mechanical or on the thermal pain stimulus. Changes in subjective pain intensity were computed as percent differences (∆%) in pain ratings between single and heterotopic stimulation for both fMRI runs, resulting in two subgroups showing a relative pain increase (subgroup P-IN, N=10) vs. decrease (subgroup P-DE, N=12). Second level and Region of Interest analysis conducted for both subgroups separately revealed that during heterotopic noxious counter-stimulation, subjects with relative pain decrease showed stronger and more widespread brain activations compared to subjects with relative pain increase in pain processing regions as well as a fronto-parietal network. Median-split regression analyses revealed a modulatory effect of prefrontal activation on connectivity between the thalamus and midbrain/pons, supporting the proposed involvement of prefrontal cortex regions in pain modulation. Furthermore, the mid-sagittal size of the total corpus callosum and five of its subareas were measured from the in vivo magnetic resonance imaging (MRI) recordings. A significantly larger relative truncus size (P=.04) was identified in participants reporting a relative decrease of subjective pain intensity during counter-stimulation, when compared to subjects experiencing a relative pain increase. The above subgroup differences observed in functional and structural imaging data are discussed with consideration of potential differences in cognitive and emotional aspects of pain modulation.
This thesis centers on formal tree languages and on their learnability by algorithmic methods in abstractions of several learning settings. After a general introduction, we present a survey of relevant definitions for the formal tree concept as well as special cases (strings) and refinements (multi-dimensional trees) thereof. In Chapter 3 we discuss the theoretical foundations of algorithmic learning in a specific type of setting of particular interest in the area of Grammatical Inference where the task consists in deriving a correct formal description for an unknown target language from various information sources (queries and/or finite samples) in a polynomial number of steps. We develop a parameterized meta-algorithm that incorporates several prominent learning algorithms from the literature in order to highlight the basic routines which regardless of the nature of the information sources have to be run through by all those algorithms alike. In this framework, the intended target descriptions are deterministic finite-state tree automata. We discuss the limited transferability of this approach to another class of descriptions, residual finite-state tree automata, for which we propose several learning algorithms as well. The learnable class by these techniques corresponds to the class of regular tree languages. In Chapter 4we outline a recent range of attempts in Grammatical Inference to extend the learnable language classes beyond regularity and even beyond context-freeness by techniques based on syntactic observations which can be subsumed under the term 'distributional learning', and we describe learning algorithms in several settings for the tree case taking this approach. We conclude with some general reflections on the notion of learning from structural information.
Some of the largest firms in the DACH region (Germany, Austria, Switzerland) are (partially) owned by a foundation and/or a family office, such as Aldi, Bosch, or Rolex. Despite their growing importance, prior research neglected to analyze the impact of these intermediaries on the firms they own. This dissertation closes this research gap by contributing to a deeper understanding of two increasingly used family firm succession vehicles, through four empirical quantitative studies. The first study focuses on the heterogeneity in foundation-owned firms (FOFs) by applying a descriptive analysis to a sample of 169 German FOFs. The results indicate that the family as a central stakeholder in a family foundation fosters governance that promotes performance and growth. The second study examines the firm growth of 204 FOFs compared to matched non-FOFs from the DACH region. The findings suggest that FOFs grow significantly less in terms of sales but not with regard to employees. In addition, it seems that this negative effect is stronger for the upper than for the middle or lower quantiles of the growth distribution. Study three adopts an agency perspective and investigates the acquisition behavior within the group of 164 FOFs. The results reveal that firms with charitable foundations as owners are more likely to undertake acquisitions and acquire targets that are geographically and culturally more distant than firms with a family foundation as owner. At the same time, they favor target companies from the same or related industries. Finally, the fourth study scrutinizes the capital structure of firms owned by single family-offices (SFOs). Drawing on a hand-collected sample of 173 SFO-owned firms in the DACH region, the results show that SFO-owned firms display a higher long-term debt ratio than family-owned firms, indicating that SFO-owned firms follow trade-off theory, similar to private equity-owned firms. Additional analyses show that this effect is stronger for SFOs that sold their original family firm. In conclusion, the outcomes of this dissertation furnish valuable research contributions and offer practical insights for families navigating such intermediaries or succession vehicles in the long term.
Stiftungsunternehmen sind Unternehmen, die sich ganz oder teilweise im Eigentum einer gemeinnützigen oder privaten Stiftung befinden. Die Anzahl an Stiftungsunternehmen in Deutschland ist in den letzten Jahren deutlich gestiegen. Bekannte deutsche Unternehmen wie Aldi, Bosch, Bertelsmann, LIDL oder Würth befinden sich im Eigentum von Stiftungen. Einige von ihnen, wie beispielsweise Fresenius, ZF Friedrichshafen oder Zeiss, sind sogar an der Börse notiert. Die Mehrzahl der Stiftungsunternehmen entsteht dadurch, dass Unternehmensgründer oder Unternehmerfamilien ihr Unternehmen in eine Stiftung einbringen, anstatt es zu vererben oder zu verkaufen.
Die Motive hierfür sind vielfältig und können familiäre Gründe (z. B. Kinderlosigkeit, Vermeidung von Familienstreit), unternehmensbezogene Gründe (z. B. Möglichkeit der langfristigen Planung durch stabile Eigentümerstruktur) und steuerliche Gründe (Vermeidung oder Reduzierung der Erbschaftssteuer) haben oder sind durch die Person des Gründers motiviert (Möglichkeit, das Unternehmen auch nach dem eigenen Tod über die Stiftung noch weiterhin zu prägen). Aufgrund der Tatsache, dass Stiftungsunternehmen zumeist aus Familienunternehmen hervorgehen, wird in der Forschung häufig nicht zwischen Familien- und Stiftungsunternehmen differenziert. Aus diesem Grund werden in dieser Dissertation zu Beginn anhand des Drei-Kreis-Modells für Familienunternehmen die Unterschiede zwischen Stiftungs- und Familienunternehmen dargestellt. Die Ergebnisse zeigen, dass nur eine sehr geringe Anzahl von Stiftungsunternehmen eine große Ähnlichkeit zu klassischen Familienunternehmen aufweist. Die meisten Stiftungsunternehmen unterscheiden sich zum Teil sehr stark von Familienunternehmen. Diese Ergebnisse verdeutlichen, dass Stiftungsunternehmen als separates Forschungsfeld betrachtet werden sollten.
Da innerhalb der Gruppe der Stiftungsunternehmen ebenfalls eine starke Heterogenität herrscht, werden im Anschluss Performanceunterschiede innerhalb der Gruppe der Stiftungsunternehmen untersucht. Hierzu wurden die Daten von 142 deutschen Stiftungsunternehmen für die Jahre 2006-2016 erhoben und mittels einer lineareren Regression ausgewertet. Die Ergebnisse zeigen, dass zwischen den verschiedenen Typen signifikante Unterschiede herrschen. Unternehmen, die von einer gemeinnützigen Stiftung gehalten werden, weisen eine signifikant schlechtere Performance auf, als Unternehmen die eine private Stiftung als Shareholder haben.
Im nächsten Schritt wird die Gruppe der börsennotierten Stiftungsunternehmen untersucht. Mittels einer Ereignisstudie wird getestet, wie sich die Stiftung als Eigentümer eines börsennotierten Unternehmens auf den Shareholder Value auswirkt. Die Ergebnisse zeigen, dass eine Anteilsverringerung einer Stiftung einen positiven Einfluss auf den Shareholder Value hat. Stiftungen werden vom Kapitalmarkt dementsprechend negativ bewertet. Aufgrund der divergierenden Ziele von Stiftung und Unternehmen birgt die Verbindung zwischen Stiftung und Unternehmen potentielle Konflikte und Herausforderungen für die beteiligten Personen. Mittels eines qualitativen explorativen Ansatzes, wird basierend auf Interviews, ein Modell entwickelt, welches die potentiellen Konflikte in Stiftungsunternehmen anhand des Beispiels der Doppelstiftung aufzeigt.
Im letzten Schritt werden Handlungsempfehlungen in Form eines Entwurfs für einen Corporate Governance Kodex erarbeitet, die (potentiellen) Stifterinnen und Stiftern helfen sollen, mögliche Konflikte entweder zu vermeiden oder bereits bestehende Probleme zu lösen.
Die Ergebnisse dieser Dissertation sind relevant für Theorie und Praxis. Aus theoretischer Sicht liegt der Wert dieser Untersuchungen darin, dass Forscher künftig besser zwischen Stiftungs- und Familienunternehmen unterscheiden können. Zudem bringt diese Arbeit den aktuellen Forschungsstand zum Thema Stiftungsunternehmen weiter. Außerdem bietet diese Dissertation insbesondere potentiellen Stiftern einen Überblick über die verschiedenen Ausgestaltungsmöglichkeiten und die Vor- und Nachteile, die diese Konstruktionen mit sich bringen. Die Handlungsempfehlungen ermöglichen es Stiftern, vorab potentielle Gefahren erkennen zu können und diese zu umgehen.
In this thesis, in order to shed light on the biological function of the membrane-bound Glucocorticoid Receptor (mGR), proteomic changes induced by 15 min in vivo acute stress and by short in vitro activation of the mGR were analyzed in T-lymphocytes. The numerous overlaps between the two datasets suggest that the mGR mediates physiologically relevant actions and participates in the early stress response, triggering rapid early priming events that pave the way for the slower genomic GC activities. In addition, a new commercially available method with suitable sensitivity to detect the human mGR is reported and the transcriptional origin of this protein investigated. Our results indicates that specific GR-transcripts, containing exon 1C and 1D, are associated with the expression of this membrane isoform.
Major threats to the Spanish Constitutional Court’s independence and authority have come, first, from political parties and the media and, second, by the Catalonian secession movement. The authority and the legitimacy of the Constitutional Court were tested in the stormy
proceedings on the Statute of Autonomy of Catalonia of 2006 that ended in 2010 and, above all, in the period of 2013–2017, when successive acts directed at the secession of were recurrently Catalonia challenged before the Court and subsequently overturned, and to stop the continued disobedience its rulings the of Court was given extended execution powers for its judgments. These new powers include the temporary replacement of any authority or public official that does not comply with a Court’s ruling and the ordering of a substitutive execution through the central government. The Court declared the new powers to be consistent with the Constitution (with three dissenting votes by four constitutional judges) and it even used them for the first time to enforce its prohibition of the referendum on the independence of Catalonia of 1 October 2017. Nevertheless, the Venice Commission has raised doubts about the opportunity of those powers, which are unusual in European constitutional jurisdiction models. At the end, the Court’s powers were not enough to stop the Catalonian secession process, and on 27 October 2017 the state government implemented the federal coercion clause and suspended Catalonian autonomy until new elections were held.
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
The main focus of this work is to study the computational complexity of generalizations of the synchronization problem for deterministic finite automata (DFA). This problem asks for a given DFA, whether there exists a word w that maps each state of the automaton to one state. We call such a word w a synchronizing word. A synchronizing word brings a system from an unknown configuration into a well defined configuration and thereby resets the system.
We generalize this problem in four different ways.
First, we restrict the set of potential synchronizing words to a fixed regular language associated with the synchronization under regular constraint problem.
The motivation here is to control the structure of a synchronizing word so that, for instance, it first brings the system from an operate mode to a reset mode and then finally again into the operate mode.
The next generalization concerns the order of states in which a synchronizing word transitions the automaton. Here, a DFA A and a partial order R is given as input and the question is whether there exists a word that synchronizes A and for which the induced state order is consistent with R. Thereby, we study different ways for a word to induce an order on the state set.
Then, we change our focus from DFAs to push-down automata and generalize the synchronization problem to push-down automata and in the following work, to visibly push-down automata. Here, a synchronizing word still needs to map each state of the automaton to one state but it further needs to fulfill some constraints on the stack. We study three different types of stack constraints where after reading the synchronizing word, the stacks associated to each run in the automaton must be (1) empty, (2) identical, or (3) can be arbitrary.
We observe that the synchronization problem for general push-down automata is undecidable and study restricted sub-classes of push-down automata where the problem becomes decidable. For visibly push-down automata we even obtain efficient algorithms for some settings.
The second part of this work studies the intersection non-emptiness problem for DFAs. This problem is related to the problem of whether a given DFA A can be synchronized into a state q as we can see the set of words synchronizing A into q as the intersection of languages accepted by automata obtained by copying A with different initial states and q as their final state.
For the intersection non-emptiness problem, we first study the complexity of the, in general PSPACE-complete, problem restricted to subclasses of DFAs associated with the two well known Straubing-Thérien and Cohen-Brzozowski dot-depth hierarchies.
Finally, we study the problem whether a given minimal DFA A can be represented as the intersection of a finite set of smaller DFAs such that the language L(A) accepted by A is equal to the intersection of the languages accepted by the smaller DFAs. There, we focus on the subclass of permutation and commutative permutation DFAs and improve known complexity bounds.
The allergic contact dermatitis (ACD) to small molecular weight compounds is a common inflammatory skin reaction. ACD is restricted to industrialized countries, has an enormous sociomedical and socioeconomic impact. About 2,800 compounds from the six million chemicals known in our environment are believed to have allergic, and to a lesser degree also contact-sensitizing or immunogenic properties causing allergic contact dermatitis. ACD results from T cell responses to harmless, low molecular weight chemicals (haptens) applied to the skin. Haptens are not directly recognized by the cells of the immune system. They need to be presented by subsets of antigen presenting cells to the cells of the immune system. In this regard, epidermal Langerhans cells (LC) and the cells into which they mature (dendritic cells) are believed to play a pivotal role in the sensitization process for ACD. LC are able to bind the haptens, internalize them, and present them to naive T cells and induce thereby the development of effector T cells. They are so-called professional antigen presenting cells. This process is initiated and maintained by the release of several mediators, which are released by various cells after their contact with the haptens. One of the first proteins secreted into the environment is interleukin (IL)-1ß. This cytokine is produced and secreted minutes after an antigen enters the cell. It is commonly believed that the large amounts of this protein and other cytokines such as granulocyte-colony stimulation factor (GM-CSF) and tumor necrosis factor alpha (TNF-ï¡) needed for the initiation and activation of ACD are coming first from other cells residing in the skin, e.g., keratinocytes, monocytes and macrophages. These cytokines provide the danger signals needed for the activation of the Langerhans cell (LC), which then produce via a positive feedback loop various cytokines themselves. In addition, other proteins such as chemokines influence the generation of danger signals, migration, homing of T cells in the local lymph nodes as well as the recruitment of T cells into the skin. Thus, a small molecular compounds or hapten needs to be able to induce danger signals in order to become immunogenic. In this study, we investigated whether para-phenylenediamine (PPD), an arylamine and common contact allergen, is able to induce danger signals and likely provide the signals needed for an initiation of an immune response[162, 163]. PPD is used as an antioxidant, an ingredient of hair dyes, intermediate of dyestuff, and PPD is found in chemicals used for photographic processing. But up to date, it has not been clearly demonstrated if PPD itself is a sensitizing agent. Thus, this study aimed on the potential of PPD to provide the danger signals by studying IL-1β, TNF-ï¡, and monocyte chemoattractant proteins (MCP-1) in human monocytes, peripheral blood mononuclear cells (PBMC) from healthy volunteers, and also in two human monocyte cell lines namely U937, and THP-1. This study found that PPD decreased dose- and time-dependently the expression and release of three relevant mediators involved in the generation of danger signals. Namely, PPD reduced the mRNA and protein levels for IL-1ß, TNF-ï¡, and MCP-1 in primary human monocytes from various donors. These findings were extended and validated by investigations using the cell line U937. The data were highly specific for PPD, and no such results were gained for its known auto oxidation product called Bandrowski- base or for meta-phenylenediamine (MPD), and ortho-phenylenediamine (OPD). Therefore, we can speculate that this effect is likely to be dependent on the para-substitution. Based on these results we conclude that PPD itself is not able to mount a cascade for the induction of danger signals. It should be mentioned that it is still possible that PPD induces danger signals for sensitization by other unknown processes. Therefore, more research is still needed focusing on this subject especially in professional antigen presenting cells in order to solve the still open question whether PPD itself sensitizes naive T cells or if PPD is solely an allergen. Independently we found unexpectedly that PPD as well as other haptens such as 2, 4-Dinitrochlorobenzene, nickelsulfate, as well as some terpenoide increased clearly the expression of CC chemokin receptor 2 (CCR2), the receptor for the chemokine MCP-1. Up to date, the main importance for the CCR2 receptor comes from results demonstrating that CCR2 is critical for the migration of monocytes after encounter with bacterial lipopolysaccharides. Under these circumstances the receptor disappears from the cell surface and is down regulated. An up regulation of CCR2 has not been reported for haptens, and deserves further investigations.