Within the field of Business Process Management, business rules are commonly used to model company decision logic and govern allowed company behavior. An exemplary business rule in the financial sector could be for example: ”A customer with a mental condition is not creditworthy”. Business rules are usually created and maintained collaboratively and over time. In this setting, modelling errors can occur frequently. A challenging problem in this context is that of inconsistency, i.e., contradictory rules which cannot hold at the same time. For instance, regarding the exemplary rule above, an inconsistency would arise if a (second) modeller entered an additional rule: ”A customer with a mental condition is always creditworthy”, as the two rules cannot hold at the same time. In this thesis, we investigate how to handle such inconsistencies in business rule bases. In particular, we develop methods and techniques for the detection, analysis and resolution of inconsistencies in business rule bases

As a consequence of the world population increase and the resulting water scarcity, water quality is the object of growing attention. In that context, organic anthropogenic molecules — often defined as micropollutants— represent a threat for water resources. Among them, pharmaceuticals are the object of particular concerns due to their permanent discharge, their increasing consumption and their effect-based structures. Pharmaceuticals are mainly introduced in the environment via wastewater treatment plants (WWTPs), along with their metabolites and the on-site formed transformation products (TPs). Once in the aquatic environment, they partition between the different environmental compartments in particular the aqueous phase, suspended particulate matter(SPM) and biota. In the last decades, pharmaceuticals have been widely investigated in the water phase. However, extreme polar pharmaceuticals have rarely been monitored due to the lack of robust analytical methods. Moreover, metabolites and TPs have seldom been included in routine analysis methods although their environmental relevance is proven. Furthermore, pharmaceuticals have been only sporadically investigated in SPM and biota and adequate multi-residue methods are lacking to obtain comprehensive results about their occurrence in these matrices. This thesis endeavors to cover these gaps of knowledge by the development of generic multi-residue methods for pharmaceuticals determination in the water phase, SPM and biota and to evaluate the occurrence and partition of pharmaceuticals into these compartments. For a complete overview, a particular focus was laid on extreme polar pharmaceuticals, pharmaceutical metabolites and TPs. In total, three innovative multi-residue methods were developed, they include analytes covering a broad range of physico-chemical properties. First, a reliable multi-residue method was developed for the analysis of extreme polar pharmaceuticals, metabolites and TPs dissolved in water. The selected analytes covered a significant range of elevated polarity and the method would be easily expendable to further analytes. This versatility could be achieved by the utilization of freeze-drying as sample preparation and zwitterionic hydrophilic interaction liquid chromatography (HILIC) in gradient elution mode. The suitability of HILIC chromatography to simultaneously quantify a large range of micropollutants in aqueous environmental samples was thoroughly studied. Several limitations were pointed out: a very complex and time-consuming method development, a very high sensitivity with regards to modification of the acetonitrile to water ratio in the eluent or the diluent and high positive matrix effects for certain analytes. However, these limitations can be overcome by the utilization of a precise protocol and appropriate labeled internal standards. They are overmatched by the benefits of HILIC which permits the chromatographic separation of extreme polar micropollutants. Investigation of environmental samples showed elevated concentrations of the analytes in the water phase. In particular, gabapentin, metformin, guanylurea and oxypurinol were measured at concentrations in the µg/L range in surface water. Subsequently, a reliable multi-residue method was established for the determination of 57 pharmaceuticals, 47 metabolites and TPs sorbed to SPM down to the low ng/g range. This method was conceived to cover a large range of polarity in particular with the inclusion of extreme polar pharmaceuticals. The extraction procedure was based on pressurized liquid extraction (PLE) followed by a clean-up via solvent exchange and detection via direct injection-reversed-phase LC-MS/MS and freeze-drying HILIC-MS/MS. Pharmaceutical sorption was examined using laboratory experiments. Derived distribution coefficients Kd varied by five orders of magnitude among the analytes and confirmed a high sorption potential for positively charged and nonpolar pharmaceuticals. The occurrence of pharmaceuticals in German rivers SPM was evaluated by the investigation of annual composite SPM samples taken at four sites at the river Rhine and one site at the river Saar between the years 2005 and 2015. It revealed the ubiquitous presence of pharmaceuticals sorbed to SPM in these rivers. In particular, positively charged analytes, even very polar and nonpolar pharmaceuticals showed appreciable concentrations. For many pharmaceuticals, a distinct correlation was observed between the annual quantities consumed in Germany and the concentrations measured in SPM. Studies of composite SPM spatial distribution permitted to get hints about specific industrial discharge by comparing the pollution pattern along the river. For the first time, these results showed the potential of SPM for the monitoring of positively charged and nonpolar pharmaceuticals in surface water. Finally, a reliable and generic multi residue method was developed to investigate 35 pharmaceuticals and 28 metabolites and TPs in fish plasma, fish liver and fish fillet. For this matrix, it was very challenging to develop an adequate clean-up allowing for the sufficient separation of the matrix disturbances from the analytes. In the final method, fish tissue extraction was performed by cell disruption followed by a non-discriminating clean-up based on silica gel solid-phase extraction(SPE) and restrictive access media (RAM) chromatography. Application of the developed method to the measurement of bream and carp tissues from German rivers revealed that even polar micropollutants such as pharmaceuticals are ubiquitously present in fish tissues. In total, 17 analytes were detected for the first time in fish tissues, including 10 metabolites/TPs. The importance of monitoring metabolites and TPs in fish tissues was confirmed with their detection at similar concentrations as their parents. Liver and fillet were shown to be appropriate for the monitoring of pharmaceuticals in fish, whereas plasma is more inconvenient due to very low concentrations and collection difficulties. Elevated concentrations of certain metabolites suggest possible formation of human metabolites in fish. Measured concentrations indicate a low bioaccumulation potential for pharmaceuticals in fish tissues.

Schizophrenia is a chronic mental health disorder, which changes rapidly the life of the persons and their families, who suffer from it. It causes high biological and psychological vulnerability as well as cognitive, emotional and behavioral disorders. Nowadays, evidence-based pharmacotherapy and psychotherapy are available aiming the rehabilitation and recovery of individuals with schizophrenia. A democratic society is obliged to give these people the opportunity to have an access to those treatments. The following three published studies present this dissertation thesis and have a common focus on the implementation of evidence-based psychotherapy in individuals with schizophrenia. The first study evaluates the efficacy of the Integrated Psychological Therapy (IPT) in Greece, one of the most evaluated rehabilitation programs. IPT was compared to Treatment as Usual (TAU) in a randomized controlled trial (RCT) with 48 individuals with schizophrenia. Significant effects favouring IPT were found in working memory, in social perception, in negative symptoms, in general psychopathology and in insight. This study supports evidence for the efficacy of IPT in Greece. The second study evaluates a second hypothesis, when IPT is more and less effective regarding treatment resistant schizophrenia (TRS) and non treatment resistant schizophrenia (NTRS). It is a part of the first paper. Significant effects favouring NTRS were found for verbal memory, for symptoms, for functioning and quality of life. Effect sizes showed superiority of NTRS in comparison to TRS. IPTTRS showed on the other side some significant improvements. This study presents the initial findings of a larger study to be conducted internationally for the first time. The third study is a systematic review, which aims to evaluate the efficacy of Cognitive Behavioral Therapy (CBT), of Meta Cognitive Therapy (MCT), Metacognitive Training (MCTR), Metacognitive Reflection and Insight Therapy (MERIT), of various Rehabilitation Programs and Recovery Programs in individuals with schizophrenia. 41 RCTs and 12 Case Studies were included. The above interventions are efficacious in the improvement of cognitions, symptoms, functional outcome, insight, self-esteem, comorbid disorders and metacognitive capacity. The three studies provide insight regarding the importance of evidence-based psychotherapy in persons with schizophrenia leading to recovery and reintegration into society. Future RCTs with larger samples and long-term follow up, combining evidence-based psychotherapies for individuals with schizophrenia need to be done.

In this thesis we examined the question whether personality traits of early child care workers influence process quality in preschool. Research has shown that in educational settings such as preschool, pedagogical quality affects children’s developmental outcome (e.g. NICHD, 2002; Peisner-Feinberg et al., 1999). A substantial part of pedagogical quality known to be vital in this respect is the interaction between teacher and children (e.g., Tietze, 2008). Results of prior classroom research indicate that the teachers’ personality might be an important factor for good teacher-child-interaction (Mayr, 2011). Thus, personality traits might play a vital role for the interaction in preschool. Therefore, the aims of this thesis were to a) identify pivotal personality traits of child care workers, b) assess ideal levels of the identified personality traits and c) examine the relationship between pivotal personality traits and process quality. On that account, we conducted two requirement analyses and a video study. The results of these studies showed that subject matter experts (parents, child care workers, lecturers) partly agreed as to which personality traits are pivotal for child care workers. Furthermore, the experts showed high consensus with regard to the minimum, ideal and maximum personality trait profiles. Furthermore, child care workers whose profiles lay closer to the experts’ ideal also showed higher process quality. In addition, regression analyses showed that the child care workers’ levels of the Big Two (Communion and Agency) related significantly to their process quality.

Initial goal of the current dissertation was the determination of image-based biomarkers sensitive for neurodegenerative processes in the human brain. One such process is the demyelination of neural cells characteristic for Multiple sclerosis (MS) - the most common neurological disease in young adults for which there is no cure yet. Conventional MRI techniques are very effective in localizing areas of brain tissue damage and are thus a reliable tool for the initial MS diagnosis. However, a mismatch between the clinical fndings and the visualized areas of damage is observed, which renders the use of the standard MRI diffcult for the objective disease monitoring and therapy evaluation. To address this problem, a novel algorithm for the fast mapping of myelin water content using standard multiecho gradient echo acquisitions of the human brain is developed in the current work. The method extents a previously published approach for the simultaneous measurement of brain T1, T∗ 2 and total water content. Employing the multiexponential T∗ 2 decay signal of myelinated tissue, myelin water content is measured based on the quantifcation of two water pools (myelin water and rest) with different relaxation times. Whole brain in vivo myelin water content maps are acquired in 10 healthy controls and one subject with MS. The in vivo results obtained are consistent with previous reports. The acquired quantitative data have a high potential in the context of MS. However, the parameters estimated in a multiparametric acquisition are correlated and constitute therefore an ill-posed, nontrivial data analysis problem. Motivated by this specific problem, a new data clustering approach is developed called Nuclear Potential Clustering, NPC. It is suitable for the explorative analysis of arbitrary dimensional and possibly correlated data without a priori assumptions about its structure. The developed algorithm is based on a concept adapted from nuclear physics. To partition the data, the dynamic behavior of electrically even charged nucleons interacting in a d-dimensional feature space is modeled. An adaptive nuclear potential, comprised of a short-range attractive (Strong interaction) and a long-range repulsive term (Coulomb potential), is assigned to each data point. Thus, nucleons that are densely distributed in space fuse to build nuclei (clusters), whereas single point clusters are repelled (noise). The algorithm is optimized and tested in an extensive study with a series of synthetic datasets as well as the Iris data. The results show that it can robustly identify clusters even when complex configurations and noise are present. Finally, to address the initial goal, quantitative MRI data of 42 patients are analyzed employing NPC. A series of experiments with different sets of image-based features show a consistent grouping tendency: younger patients with low disease grade are recognized as cohesive clusters, while those of higher age and impairment are recognized as outliers. This allows for the definition of a reference region in a feature space associated with phenotypic data. Tracking of the individual's positions therein can disclose patients at risk and be employed for therapy evaluation.