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,...     

Influence of BaO on Pd/Al2O3-based catalysts in C2H4 and CO oxidation as well as in NO reduction

In this study, Pd/Al₂O₃ and Pd/BaO/Al₂O₃ metallic monoliths were used to investigate the effect of BaO in C₂H₄ and CO oxidation as well as in NO reduction. A FT-IR gas analyser was used to study the activity of the catalysts. Several activity experiments carried out with dissimilar feedstreams revealed that BaO enhances CO and C₂H₄ oxidation as well as NO reduction reactions in rich conditions. This effect is due to BaO, which causes a decrease in the ethene poisoning of palladium. In lean conditions BaO is present in the form of Ba(OH)₂ which reacts with oxidised NO releasing water. Therefore, NO was stored during the lean reaction.     

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.     

Airwriting: a wearable handwriting recognition system

We present a wearable input system which enables interaction through 3D handwriting recognition. Users can write text in the air as if they were using an imaginary blackboard. The handwriting gestures are captured wirelessly by motion sensors applying accelerometers and gyroscopes which are attached to the back of the hand. We propose a two-stage approach for spotting and recognition of handwriting gestures. The spotting stage uses a support vector machine to identify those data segments which contain handwriting. The recognition stage uses hidden Markov models (HMMs) to generate a text representation from the motion sensor data. Individual characters are modeled by HMMs and concatenated to word models. Our system can continuously recognize arbitrary sentences, based on a freely definable vocabulary. A statistical language model is used to enhance recognition performance and to restrict the search space. We show that continuous gesture recognition with inertial sensors is feasible for gesture vocabularies that are several orders of magnitude larger than traditional vocabularies for known systems. In a first experiment, we evaluate the spotting algorithm on a realistic data set including everyday activities. In a second experiment, we report the results from a nine-user experiment on handwritten sentence recognition. Finally, we evaluate the end-to-end system on a small but realistic data set.     

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.     

Error training: Replication and the function of exploratory behavior

A study of 30 psychology students replicated and extended the findings of Frese et al. (1991) on the superiority of error training, a procedure in which trainees are exposed to many errors. The hypothesis was that error training would lead to exploration and this would increase performance. The error training group performed better than the group that received training in which they were not allowed to make any errors. Students in both the error training and the error avoidant groups performed better if they explored. Exploration was done in contrast to the instruction in the error avoidant group. The data suggest that it is necessary to look into the question of whether errors instigate exploration.     

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.