Feature-based Groundwater Hydrograph Clustering Using Unsupervised Self-Organizing Map-Ensembles

Hydrograph clustering helps to identify dynamic patterns within aquifers systems, an important foundation of characterizing groundwater systems and their influences, which is necessary to effectively manage groundwater resources. We develope an unsupervised modeling approach to characterize and cluster hydrographs on regional scale according to their dynamics. We apply feature-based clustering to improve the exploitation of heterogeneous datasets, explore the usefulness of existing features and propose new features specifically useful to describe groundwater hydrographs. The clustering itself is based on a powerful combination of Self-Organizing Maps with a modified DS2L-Algorithm, which automatically derives the cluster number but also allows to influence the level of detail of the clustering. We further develop a framework that combines these methods with ensemble modeling, internal cluster validation indices, resampling and consensus voting to finally obtain a robust clustering result and remove arbitrariness from the feature selection process. Further we propose a measure to sort hydrographs within clusters, useful for both interpretability and visualization. We test the framework with weekly data from the Upper Rhine Graben System, using more than 1800 hydrographs from a period of 30 years (1986-2016). The results show that our approach is adaptively capable of identifying homogeneous groups of hydrograph dynamics. The resulting clusters show both spatially known and unknown patterns, some of which correspond clearly to external controlling factors, such as intensive groundwater management in the northern part of the test area. This framework is easily transferable to other regions and, by adapting the describing features, also to other time series-clustering applications.

     

A local and global tour on MOMoT

Software and Systems Modeling - Many model transformation scenarios require flexible execution strategies as they should produce models with the highest possible quality. At the same time,...     

Energy Metabolites as Biomarkers in Ischemic and Dilated Cardiomyopathy

With more than 25 million people affected, heart failure (HF) is a global threat. As energy production pathways are known to play a pivotal role in HF, we sought here to identify key metabolic changes in ischemic- and non-ischemic HF by using a multi-OMICS approach. Serum metabolites and mRNAseq and epigenetic DNA methylation profiles were analyzed from blood and left ventricular heart biopsy specimens of the same individuals. In total we collected serum from n = 82 patients with Dilated Cardiomyopathy (DCM) and n = 51 controls in the screening stage. We identified several metabolites involved in glycolysis and citric acid cycle to be elevated up to 5.7-fold in DCM (p = 1.7 × 10⁻⁶). Interestingly, cardiac mRNA and epigenetic changes of genes encoding rate-limiting enzymes of these pathways could also be found and validated in our second stage of metabolite assessment in n = 52 DCM, n = 39 ischemic HF and n = 57 controls. In conclusion, we identified a new set of metabolomic biomarkers for HF. We were able to identify underlying biological cascades that potentially represent suitable intervention targets.     

Structure-Activity Relationships of Benzamides and Isoindolines Designed as SARS-CoV Protease Inhibitors Effective against SARS-CoV-2

Inhibition of coronavirus (CoV)-encoded papain-like cysteine proteases (PL^pro) represents an attractive strategy to treat infections by these important human pathogens. Herein we report on structure-activity relationships (SAR) of the noncovalent active-site directed inhibitor (R)-5-amino-2-methyl-N-(1-(naphthalen-1-yl)ethyl) benzamide ( 2 b ), which is known to bind into the S3 and S4 pockets of the SARS-CoV PL^pro. Moreover, we report the discovery of isoindolines as a new class of potent PL^pro inhibitors. The studies also provide a deeper understanding of the binding modes of this inhibitor class. Importantly, the inhibitors were also confirmed to inhibit SARS-CoV-2 replication in cell culture suggesting that, due to the high structural similarities of the target proteases, inhibitors identified against SARS-CoV PL^pro are valuable starting points for the development of new pan-coronaviral inhibitors.     

Access of the substrate to the active site of yeast oxidosqualene cyclase: an inhibition and site-directed mutagenesis approach

A structural model of Saccharomyces cerevisiae oxidosqualene cyclase (SceOSC) suggests that some residues of the conserved sequence Pro-Ala-Glu-Val-Phe-Gly (residues 524-529) belong to a channel constriction that gives access to the active-site cavity. Starting from the SceOSC C457D mutant, which lacks the cysteine residue next to the catalytic Asp456 residue Cys457 has been replaced but Asp456 is still there, we prepared two further mutants where the wild-type residues Ala525 and Glu526 were individually replaced by cysteine. These mutants, especially E526C, were very sensitive to the thiol-reacting agent dodecyl-maleimide. Moreover, both the specific activity and the thermal stability of E526C were severely reduced. A similar decrease of the enzyme functionality was obtained by replacing Glu526 with alanine, while substitution with the conservative residues aspartate or glutamine did not alter catalytic activity. Molecular modeling of the yeast wild-type OSC and mutants on the template structure of human OSC confirms that the channel constriction is an important aspect of the protein structure and suggests a critical structural role for Glu526.     

Empirische Methodologien und Methoden der angewandten und der empirischen Ethik

Definition of the problem This paper deals with the question of adequate methodologies and methods to conduct empirical research and integrate empirical knowledge in the field of biomedical ethics. Arguments It starts with reflections about the main subject matter of ethics, the human being as a bio-psycho-social creature and its morals, and argues that social sciences are the adequate basic empirical science in the field of ethics in general. The next paragraph considers theory of science perspectives of the relationship of ethics, empirical findings, methodologies and theories and examples of the integration of empirical findings into ethical deliberations. Reasons for the tension between social science and ethics are scrutinized which are different in the yet to be defined field of empirical ethics compared to traditional applied ethics. Conclusion How a bio-psycho-social ethics that incorporates these criteria into its own body of work could look like is finally depicted.     

Business Intelligence Acceptance: The Prominence of Organizational Factors

The specifics of business intelligence systems compared to operational IS motivate the necessity to research the business intelligence systems acceptance determinants separately. The authors followed an exploratory approach in order to conceptualize a business intelligence acceptance model. Their findings show that in the Business Intelligence Systems context, there is a significant emphasis on organizational factors, such as result demonstrability, social influence, and facilitating conditions with sufficient resources that help build an adequate information culture all substantially influencing the effective acceptance of business intelligence systems.     

Dynamic admission control for two customer classes with stochastic demands and strict due dates

We study a dynamic capacity allocation problem with admission control decisions of a company that caters for two demand classes with random arrivals, capacity requirements and strict due dates. We formulate the problem as a Markov decision process (MDP) in order to find the optimal admission control policy that maximises the expected profit of the company. Such a formulation suffers a state-space explosion. Moreover, it involves an additional dimension arising from the multiple possible order sizes that customers can request which further increases the complexity of the problem. To reduce the cardinality of possible policies, and, thus, the computational requirements, we propose a threshold-based policy. We formulate an MDP to generate such a policy. To deal with the curse of dimensionality, we develop threshold-based approximate algorithms based on the state-reduction heuristics with aggregation proposed previously. Our results reveal that for the majority of instances considered the optimal policy has a threshold structure. We then demonstrate the superiority of the proposed threshold-based approximate algorithms over two benchmark policies in terms of the generated profits and the robustness of the solutions to changes in operational conditions. Finally, we show that our proposed policies are also robust to changes in actual demand from its estimation.     

Knowledge and information awareness for initiating transactive memory system processes of computer-supported collaborating ad hoc groups

This paper presents an innovative approach for initiating processes of a transactive memory system in newly formed groups of experts collaborating computer-supported in a complex problem-solving task. Our empirical study compared 15 experimental and 15 control groups, each consisting of triads. In the experimental condition, the triads were provided with a tool for fostering knowledge and information awareness, that is, being informed about the knowledge and the underlying information of the collaboration partners in form of digital concept maps. In the control condition, the groups had no access to this tool. Results confirmed the potential of the tool to initiate processes of a transactive memory system: shared agreement of the knowledge of the other group members’ knowledge proved to influence group performance positively. In addition, previous findings of the tool’s potential to establish knowledge and information awareness and to augment group performance could be replicated. However, the postulated mediating effect of processes of a transactive memory system concerning the impact of knowledge and information awareness on group performance did not reach statistical significance. Aspects for future studies and implications of these findings regarding their practical implementation, for example, in teams of organizations, are discussed.