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This work addresses the algorithmic tractability of hard combinatorial problems. Basically, we are considering \NP-hard problems. For those problems we can not find a polynomial time algorithm. Several algorithmic approaches already exist which deal with this dilemma. Among them we find (randomized) approximation algorithms and heuristics. Even though in practice they often work in reasonable time they usually do not return an optimal solution. If we constrain optimality then there are only two methods which suffice for this purpose: exponential time algorithms and parameterized algorithms. In the first approach we seek to design algorithms consuming exponentially many steps who are more clever than some trivial algorithm (who simply enumerates all solution candidates). Typically, the naive enumerative approach yields an algorithm with run time $\Oh^*(2^n)$. So, the general task is to construct algorithms obeying a run time of the form $\Oh^*(c^n)$ where $c<2$. The second approach considers an additional parameter $k$ besides the input size $n$. This parameter should provide more information about the problem and cover a typical characteristic. The standard parameterization is to see $k$ as an upper (lower, resp.) bound on the solution size in case of a minimization (maximization, resp.) problem. Then a parameterized algorithm should solve the problem in time $f(k)\cdot n^\beta$ where $\beta$ is a constant and $f$ is independent of $n$. In principle this method aims to restrict the combinatorial difficulty of the problem to the parameter $k$ (if possible). The basic hypothesis is that $k$ is small with respect to the overall input size. In both fields a frequent standard technique is the design of branching algorithms. These algorithms solve the problem by traversing the solution space in a clever way. They frequently select an entity of the input and create two new subproblems, one where this entity is considered as part of the future solution and another one where it is excluded from it. Then in both cases by fixing this entity possibly other entities will be fixed. If so then the traversed number of possible solution is smaller than the whole solution space. The visited solutions can be arranged like a search tree. To estimate the run time of such algorithms there is need for a method to obtain tight upper bounds on the size of the search trees. In the field of exponential time algorithms a powerful technique called Measure&Conquer has been developed for this purpose. It has been applied successfully to many problems, especially to problems where other algorithmic attacks could not break the trivial run time upper bound. On the other hand in the field of parameterized algorithms Measure&Conquer is almost not known. This piece of work will present examples where this technique can be used in this field. It also will point out what differences have to be made in order to successfully apply the technique. Further, exponential time algorithms for hard problems where Measure&Conquer is applied are presented. Another aspect is that a formalization (and generalization) of the notion of a search tree is given. It is shown that for certain problems such a formalization is extremely useful.
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.
Evapotranspiration (ET) is one of the most important variables in hydrological studies. In the ET process, energy exchange and water transfer are involved. ET consists of transpiration and evaporation. The amount of plants transpiration dominates in ET. Especially in the forest regions, the ratio of transpiration to ET is in general 80-90 %. Meteorological variables, vegetation properties, precipitation and soil moisture are critical influence factors for ET generation. The study area is located in the forest area of Nahe catchment (Rhineland-Palatinate, Germany). The Nahe catchment is highly wooded. About 54.6 % of this area is covered by forest, with deciduous forest and coniferous forest are two primary types. A hydrological model, WaSiM-ETH, was employed for a long-term simulation from 1971-2003 in the Nahe catchment. In WaSiM-ETH, the potential evapotranspiration (ETP) was firstly calculated by the Penman-Monteith equation, and subsequently reduced according to the soil water content to obtain the actual evapotranspiration (ETA). The Penman-Monteith equation has been widely used and recommended for ETP estimation. The difficulties in applying this equation are the high demand of ground-measured meteorological data and the determination of surface resistance. A method combined remote sensing images with ground-measured meteorological data was also used to retrieve the ETA. This method is based on the surface properties such as surface albedo, fractional vegetation cover (FVC) and land surface temperature (LST) to obtain the latent heat flux (LE, corresponding to ETA) through the surface energy balance equation. LST is a critical variable for surface energy components estimation. It was retrieved from the TM/ETM+ thermal infrared (TIR) band. Due to the high-quality and cloudy-free requirements for TM/ETM+ data selection as well as the overlapping cycle of TM/ETM+ sensor is 16 days, images on only five dates are available during 1971-2003 (model ran) " May 15, 2000, July 05, 2001, July 19, August 04 and September 21 in 2003. It is found that the climate conditions of 2000, 2001 and 2003 are wet, medium wet and dry, respectively. Therefore, the remote sensing-retrieved observations are noncontinuous in a limited number over time but contain multiple climate conditions. Aerodynamic resistance and surface resistance are two most important parameters in the Penman-Monteith equation. However, for forest area, the aerodynamic resistance is calculated by a function of wind speed in the model. Since transpiration and evaporation are separately calculated by the Penman-Monteith equation in the model, the surface resistance was divided into canopy surface resistance rsc and soil surface resistance rse. rsc is related to the plants transpiration and rse is related to the bare soil evaporation. The interception evaporation was not taken into account due to its negligible contribution to ET rate under a dry-canopy (no rainfall) condition. Based on the remote sensing-retrieved observations, rsc and rse were calibrated in the WaSiM-ETH model for both forest types: for deciduous forest, rsc = 150 sm−1, rse = 250 sm−1; for coniferous forest, rsc = 300 sm−1, rse = 650 sm−1. We also carried out sensitivity analysis on rsc and rse. The appropriate value ranges of rsc and rse were determined as (annual maximum): for deciduous forest, [100,225] sm−1 for rsc and [50,450] sm−1 for rse; for coniferous forest, [225,375] sm−1 for rsc and [350,1200] sm−1 for rse. Due to the features of the observations that are in a limited number but contain multiple climate conditions, the statistical indices for model performance evaluation are required to be sensitive to extreme values. In this study, boxplots were found to well exhibit the model performance at both spatial and temporal scale. Nush-Sutcliffe efficiency (NSE), RMSE-observations standard deviation ratio (RSR), percent bias (PBIAS), mean bias error (MBE), mean variance of error distribution (S2d), index of agreement (d), root mean square error (RMSE) were found as appropriate statistical indices to provide additional evaluation information to the boxplots. The model performance can be judged as satisfactory if NSE > 0.5, RSR ≤ 0.7, PBIAS < -±12, MBE < -±0.45, S2d < 1.11, d > 0.79, RMSE < 0.97. rsc played a more important role than rse in ETP and ETA estimation by the Penman-Monteith equation, which is attributed to the fact that transpiration dominates in ET. The ETP estimation was found the most correlated to the relative humidity (RH), followed by air temperature (T), relative sunshine duration (SSD) and wind speed (WS). Under wet or medium wet climate conditions, ETA estimation was found the most correlated to T, followed by RH, SSD and WS. Under a water-stress condition, there were very small correlations between ETA and each meteorological variable.
This study focuses on the representation of British South Asian identities in contemporary British audiovisual media. It attempts to answer the question, whether these identities are represented as hybrid, heterogeneous and ambivalent, or whether these contemporary representations follow in the tradition of colonial and postcolonial racialism. Racialised depictions of British South Asians have been the norm not only in the colonial but also in the postcolonial era until the rise of the Black British movement, whose successes have been also acknowledged in the field of representation. However these achievements have to be scrutinized again, especially in the context of the post 9/11 world, rising Islamophobia, and new forms of institutionalized discrimination on the basis of religion. Since the majority of British Muslims are of South Asian origin, this study tries to answer the question whether the marker of religious origin is racial belonging, i.e. skin colour, and old stereotypes associated with the racialised representation are being perpetuated into current depictions through an examination of the varied genre of popular audio visual media texts.
Striving for sustainable development by combating climate change and creating a more social world is one of the most pressing issues of our time. Growing legal requirements and customer expectations require also Mittelstand firms to address sustainability issues such as climate change. This dissertation contributes to a better understanding of sustainability in the Mittelstand context by examining different Mittelstand actors and the three dimensions of sustainability - social, economic, and environmental sustainability - in four quantitative studies. The first two studies focus on the social relevance and economic performance of hidden champions, a niche market leading subgroup of Mittelstand firms. At the regional level, the impact of 1,645 hidden champions located in Germany on various dimensions of regional development is examined. A higher concentration of hidden champions has a positive effect on regional employment, median income, and patents. At the firm level, analyses of a panel dataset of 4,677 German manufacturing firms, including 617 hidden champions, show that the latter have a higher return on assets than other Mittelstand firms. The following two chapters deal with environmental strategies and thus contribute to the exploration of the environmental dimension of sustainability. First, the consideration of climate aspects in investment decisions is compared using survey data from 468 European venture capital and private equity investors. While private equity firms respond to external stakeholders and portfolio performance and pursue an active ownership strategy, venture capital firms are motivated by product differentiation and make impact investments. Finally, based on survey data from 443 medium-sized manufacturing firms in Germany, 54% of which are family-owned, the impact of stakeholder pressures on their decarbonization strategies is analyzed. A distinction is made between symbolic (compensation of CO₂-emissions) and substantive decarbonization strategies (reduction of CO₂-emissions). Stakeholder pressures lead to a proactive pursuit of decarbonization strategies, with internal and external stakeholders varying in their influence on symbolic and substantial decarbonization strategies, and the relationship influenced by family ownership.
There is no longer any doubt about the general effectiveness of psychotherapy. However, up to 40% of patients do not respond to treatment. Despite efforts to develop new treatments, overall effectiveness has not improved. Consequently, practice-oriented research has emerged to make research results more relevant to practitioners. Within this context, patient-focused research (PFR) focuses on the question of whether a particular treatment works for a specific patient. Finally, PFR gave rise to the precision mental health research movement that is trying to tailor treatments to individual patients by making data-driven and algorithm-based predictions. These predictions are intended to support therapists in their clinical decisions, such as the selection of treatment strategies and adaptation of treatment. The present work summarizes three studies that aim to generate different prediction models for treatment personalization that can be applied to practice. The goal of Study I was to develop a model for dropout prediction using data assessed prior to the first session (N = 2543). The usefulness of various machine learning (ML) algorithms and ensembles was assessed. The best model was an ensemble utilizing random forest and nearest neighbor modeling. It significantly outperformed generalized linear modeling, correctly identifying 63.4% of all cases and uncovering seven key predictors. The findings illustrated the potential of ML to enhance dropout predictions, but also highlighted that not all ML algorithms are equally suitable for this purpose. Study II utilized Study I’s findings to enhance the prediction of dropout rates. Data from the initial two sessions and observer ratings of therapist interventions and skills were employed to develop a model using an elastic net (EN) algorithm. The findings demonstrated that the model was significantly more effective at predicting dropout when using observer ratings with a Cohen’s d of up to .65 and more effective than the model in Study I, despite the smaller sample (N = 259). These results indicated that generating models could be improved by employing various data sources, which provide better foundations for model development. Finally, Study III generated a model to predict therapy outcome after a sudden gain (SG) in order to identify crucial predictors of the upward spiral. EN was used to generate the model using data from 794 cases that experienced a SG. A control group of the same size was also used to quantify and relativize the identified predictors by their general influence on therapy outcomes. The results indicated that there are seven key predictors that have varying effect sizes on therapy outcome, with Cohen's d ranging from 1.08 to 12.48. The findings suggested that a directive approach is more likely to lead to better outcomes after an SG, and that alliance ruptures can be effectively compensated for. However, these effects
were reversed in the control group. The results of the three studies are discussed regarding their usefulness to support clinical decision-making and their implications for the implementation of precision mental health.
Evidence points to autonomy as having a place next to affiliation, achievement, and power as one of the basic implicit motives; however, there is still some research that needs to be conducted to support this notion.
The research in this dissertation aimed to address this issue. I have specifically focused on two issues that help solidify the foundation of work that has already been conducted on the implicit autonomy motive, and will also be a foundation for future studies. The first issue is measurement. Implicit motives should be measured using causally valid instruments (McClelland, 1980). The second issue addresses the function of motives. Implicit motives orient, select, and energize behavior (McClelland, 1980). If autonomy is an implicit motive, then we need a valid instrument to measure it and we also need to show that it orients, selects, and energizes behavior.
In the following dissertation, I address these two issues in a series of ten studies. Firstly, I present studies that examine the causal validity of the Operant Motive Test (OMT; Kuhl, 2013) for the implicit affiliation and power motives using established methods. Secondly, I developed and empirically tested pictures to specifically assess the implicit autonomy motive and examined their causal validity. Thereafter, I present two studies that investigated the orienting and energizing effects of the implicit autonomy motive. The results of the studies solidified the foundation of the OMT and how it measures nAutonomy. Furthermore, this dissertation demonstrates that nAutonomy fulfills the criteria for two of the main functions of implicit motives. Taken together, the findings of this dissertation provide further support for autonomy as an implicit motive and a foundation for intriguing future studies.
Behavioural traces from interactions with digital technologies are diverse and abundant. Yet, their capacity for theory-driven research is still to be constituted. In the present cumulative dissertation project, I deliberate the caveats and potentials of digital behavioural trace data in behavioural and social science research. One use case is online radicalisation research. The three studies included, set out to discern the state-of-the-art of methods and constructs employed in radicalization research, at the intersection of traditional methods and digital behavioural trace data. Firstly, I display, based on a systematic literature review of empirical work, the prevalence of digital behavioural trace data across different research strands and discern determinants and outcomes of radicalisation constructs. Secondly, I extract, based on this literature review, hypotheses and constructs and integrate them to a framework from network theory. This graph of hypotheses, in turn, makes the relative importance of theoretical considerations explicit. One implication of visualising the assumptions in the field is to systematise bottlenecks for the analysis of digital behavioural trace data and to provide the grounds for the genesis of new hypotheses. Thirdly, I provide a proof-of-concept for incorporating a theoretical framework from conspiracy theory research (as a specific form of radicalisation) and digital behavioural traces. I argue for marrying theoretical assumptions derived from temporal signals of posting behaviour and semantic meaning from textual content that rests on a framework from evolutionary psychology. In the light of these findings, I conclude by discussing important potential biases at different stages in the research cycle and practical implications.
This work is concerned with the numerical solution of optimization problems that arise in the context of ground water modeling. Both ground water hydraulic and quality management problems are considered. The considered problems are discretized problems of optimal control that are governed by discretized partial differential equations. Aspects of special interest in this work are inaccurate function evaluations and the ensuing numerical treatment within an optimization algorithm. Methods for noisy functions are appropriate for the considered practical application. Also, block preconditioners are constructed and analyzed that exploit the structure of the underlying linear system. Specifically, KKT systems are considered, and the preconditioners are tested for use within Krylov subspace methods. The project was financed by the foundation Stiftung Rheinland-Pfalz für Innovation and carried out in joint work with TGU GmbH, a company of consulting engineers for ground water and water resources.
The Second Language Acquisition of English Non-Finite Complement Clauses – A Usage-Based Perspective
(2022)
One of the most essential hypotheses of usage-based theories and many constructionist approaches to language is that language entails the piecemeal learning of constructions on the basis of general cognitive mechanisms and exposure to the target language in use (Ellis 2002; Tomasello 2003). However, there is still a considerable lack of empirical research on the emergence and mental representation of constructions in second language (L2) acquisition. One crucial question that arises, for instance, is whether L2 learners’ knowledge of a construction corresponds to a native-like mapping of form and meaning and, if so, to what extent this representation is shaped by usage. For instance, it is unclear how learners ‘build’ constructional knowledge, i.e. which pieces of frequency-, form- and meaning-related information become relevant for the entrenchment and schematisation of a L2 construction.
To address these issues, the English catenative verb construction was used as a testbed phenomenon. This idiosyncratic complex construction is comprised of a catenative verb and a non-finite complement clause (see Huddleston & Pullum 2002), which is prototypically a gerund-participial (henceforth referred to as ‘target-ing’ construction) or a to-infinitival complement (‘target-to’ construction):
(1) She refused to do her homework.
(2) Laura kept reading love stories.
(3) *He avoids to listen to loud music.
This construction is particularly interesting because learners often show choices of a complement type different from those of native speakers (e.g. Gries & Wulff 2009; Martinez‐Garcia & Wulff 2012) as illustrated in (3) and is commonly claimed to be difficult to be taught by explicit rules (see e.g. Petrovitz 2001).
By triangulating different types of usage data (corpus and elicited production data) and analysing these by multivariate statistical tests, the effects of different usage-related factors (e.g. frequency, proficiency level of the learner, semantic class of verb, etc.) on the representation and development of the catenative verb construction and its subschemas (i.e. target-to and target-ing construction) were examined. In particular, it was assessed whether they can predict a native-like form-meaning pairing of a catenative verb and non-finite complement.
First, all studies were able to show a robust effect of frequency on the complement choice. Frequency does not only lead to the entrenchment of high-frequency exemplars of the construction but is also found to motivate a taxonomic generalisation across related exemplars and the representation of a more abstract schema. Second, the results indicate that the target-to construction, due to its higher type and token frequency, has a high degree of schematicity and productivity than the target-ing construction for the learners, which allows for analogical comparisons and pattern extension with less entrenched exemplars. This schema is likely to be overgeneralised to (less frequent) target-ing verbs because the learners perceive formal and semantic compatibility between the unknown/infrequent verb and this pattern.
Furthermore, the findings present evidence that less advanced learners (A2-B2) make more coarse-grained generalisations, which are centred around high-frequency and prototypical exemplars/low-scope patterns. In the case of high-proficiency learners (C1-C2), not only does the number of native-like complement choices increase but relational information, such as the semantic subclasses of the verb, form-function contingency and other factors, becomes also relevant for a target-like choice. Thus, the results suggests that with increasing usage experience learners gradually develop a more fine-grained, interconnected representation of the catenative verb construction, which gains more resemblance to the form-meaning mappings of native speakers.
Taken together, these insights highlight the importance for language learning and teaching environments to acknowledge that L2 knowledge is represented in the form of highly interconnected form-meaning pairings, i.e. constructions, that can be found on different levels of abstraction and complexity.