Blogpost "Nahtoderfahrungen und ihre Deutungen" - Lebock, Sarah
BloKK-Beitrag für das ZeKK, 04.02.2022

Effect of Surface Hydrophobicity on the Adsorption of a Pilus-Derived Adhesin-like Peptide - Yang, Yu; Huang, Jingyuan; Dornbusch, Daniel; Grundmeier, Guido; Fahmy, Karim; Keller, Adrian; Cheung, David L. (Langmuir)
Keywords: Electrochemistry; Spectroscopy; Surfaces and Interfaces; Condensed Matter Physics; General Materials Science

Time-Dependent DNA Origami Denaturation by Guanidinium Chloride, Guanidinium Sulfate, and Guanidinium Thiocyanate - Hanke, Marcel; Hansen, Niklas; Tomm, Emilia; Grundmeier, Guido; Keller, Adrian (International Journal of Molecular Sciences)
Guanidinium (Gdm) undergoes interactions with both hydrophilic and hydrophobic groups and, thus, is a highly potent denaturant of biomolecular structure. However, our molecular understanding of the interaction of Gdm with proteins and DNA is still rather limited. Here, we investigated the denaturation of DNA origami nanostructures by three Gdm salts, i.e., guanidinium chloride (GdmCl), guanidinium sulfate (Gdm2SO4), and guanidinium thiocyanate (GdmSCN), at different temperatures and in dependence of incubation time. Using DNA origami nanostructures as sensors that translate small molecular transitions into nanostructural changes, the denaturing effects of the Gdm salts were directly visualized by atomic force microscopy. GdmSCN was the most potent DNA denaturant, which caused complete DNA origami denaturation at 50 °C already at a concentration of 2 M. Under such harsh conditions, denaturation occurred within the first 15 min of Gdm exposure, whereas much slower kinetics were observed for the more weakly denaturing salt Gdm2SO4 at 25 °C. Lastly, we observed a novel non-monotonous temperature dependence of DNA origami denaturation in Gdm2SO4 with the fraction of intact nanostructures having an intermediate minimum at about 40 °C. Our results, thus, provide further insights into the highly complex Gdm–DNA interaction and underscore the importance of the counteranion species.
Keywords: Inorganic Chemistry; Organic Chemistry; Physical and Theoretical Chemistry; Computer Science Applications; Spectroscopy; Molecular Biology; General Medicine; Catalysis

Return to play in elite rugby players after severe knee injuries - Robyn, Aneurin D.; Louw, Quinette A.; Baumeister, Jochen (South African Journal of Physiotherapy)
Background: Medical professionals working in an elite sport environment have the challenging task to balance the athlete’s readiness to return to the playing field after severe injury with other stakeholders’ (coaches, sponsors, teammates) opinions and objectives.Objectives: Our study aimed to evaluate differences in the physical profiles of elite rugby players at return to play (RTP) after a severe knee injury, compared with their pre-injury profiles and matched controls.Method: Before the injury, participants performed four performance tests during their preseason screening. These tests were repeated and compared to baseline once a player was declared fit to play.Results: Significant differences (p ≤ 0.05) were found in the injured players’ group who were slower over 10 m speed, in their decision-making time and the total time of the reactive agility tests at RTP, whilst controls were significantly faster over 10 m and 30 m speed tests. The countermovement jump outcomes showed significant improvement in the uninjured participants (p ≤ 0.05).Conclusion: Our study highlights that injured players’ running speeds and decision-making times are slower after injury. The uninjured players have a positive outcome to training and match stimulus by improving their running speed and lower body explosive power during the season.Clinical implications: Our study provides insight into the RTP profile of elite rugby players, and a novel finding was the decision-making time deficit. This highlights the importance of cognitive training during injury rehabilitation as athletes make numerous decisions in a pressured and uncontrolled environment during a match. Speed training development is recommended as the athletes were slower after severe knee injury.
Keywords: Physical Therapy; Sports Therapy and Rehabilitation

Anti-pattern Detection in Process-Driven Decision Support Systems - Kirchhoff, Jonas; Engels, Gregor (Software Business)
Decision makers increasingly rely on decision support systems for optimal decision making. Recently, special attention has been paid to process-driven decision support systems (PD-DSS) in which a process model prescribes the invocation sequence of software-based decision support services and the data exchange between them. Thus, it is possible to quickly combine available decision support services as needed for optimally supporting the decision making process of an individual decision maker. However, process modelers may accidentally create a process model which is technically well-formed and executable, but contains functional and behavioral flaws such as redundant or missing services. These flaws may result in inefficient computations or invalid decision recommendations when the corresponding PD-DSS is utilized by a decision maker. In this paper, we therefore propose an approach to validate functionality and behavior of a process model representing a PD-DSS. Our approach is based on expressing flaws as anti-patterns for which the process model can be automatically checked via graph matching. We prototypically implemented our approach and demonstrate its applicability in the context of decision making for energy network planning.

Psychological readiness of elite rugby players at return to play after severe knee injury - Robyn, A.D.; Louw, Q.A.; Baumeister, Jochen (African Journal for Physical Activity and Health Sciences (AJPHES))
Keywords: General Medicine

Innovative Leichtbau- und Kühlungskonzepte für elektrische Maschinen durch additive Fertigung (ILuKadd3D) - Haase, Michael; Tasche, Frederik; Bieber, Maximilian; Zibart, Alexander

Contrastive Argument Summarization Using Supervised and Unsupervised Machine Learning - Rieskamp, Jonas
Controversial topics like abortion or capital punishment inherently lack of correct answers or the right way to deal with. Thus, in order to find what is true, what is good, or what should be done, the involved parties need to debate. For the purpose of forming an opinion on a controversial topic someone needs to take in a lot of arguments on that topic to gather information which can be a time-consuming process. To increase efficiency, someone can use an argument search engine to quicken the retrieval of relevant arguments. Although the usage of such a service reduces the time to find arguments, there is still a lot of textual data that needs to be read. To this end, computational summarization approaches for arguments can limit the necessary time for information review by generating short snippets capturing the main gist of each argument. Yet, we suggest that approaches that consider one argument at a time show potential for further improvement in terms of efficiency during information review. In fact, arguments on the same topic, like those retrieved by a search engine for a certain query, partially cover the same content, e. g. arguments regarding the death penalty probably use deterrence as a point in favor of it. However, if the same aspect is central in multiple arguments, their snippets reflect this, which leads to redundancy among the snippets. Consequently, someone interested in gathering information on a controversial topic does not necessarily find new information in each snippet he or she reads. We introduce the task of Contrastive Argument Summarization (CAS) which addresses the aforementioned problem regarding existing argument summarization. An approach that addresses CAS aims to produce contrastive snippets for each argument in a set of topic-related arguments. A contrastive snippet should represent the main gist of its argument, it should account for the argumentative nature of the text, and it should be dissimilar to the other topic-related arguments in order to reduce redundancy among the snippets. We propose two approaches addressing CAS, namely an extended version of the LexRank derivation by Alshomary et al. (2020), and an advancement of the work by Bista et al. (2020). Additionally, we develop two automatic measures to assess to which extent the snippets of one set are opposed. For evaluation, we compile a corpus using the args.me search engine Wachsmuth et al. (2017b) to come close to the suggested area of application. Moreover, we conduct a manual annotation study to assess approaches’ effectiveness. We find that the graph-based approach is superior when it comes to contrastiveness (i. e. snippets being dissimilar to topic-related arguments), and that the second approach outperforms the previous one and the unmodified version of Alshomary et al. (2020) when it comes to representativeness (i. e. snippets capturing the main gist of an argument).

Fair, Individually Rational and Cheap Adjustment - Polevoy, Gleb; Dziubiński, Marcin (Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence)
Consider the practical goal of making a desired action profile played, when the planner can only change the payoffs, bound by stringent constraints. Applications include motivating people to choose the closest school, the closest subway station, or to coordinate on a communication protocol or an investment strategy. Employing subsidies and tolls, we adjust the game so that choosing this predefined action profile becomes strictly dominant. Inspired mainly by the work of Monderer and Tennenholtz, where the promised subsidies do not materialise in the not played profiles, we provide a fair and individually rational game adjustment, such that the total outside investments sum up to zero at any profile, thereby facilitating easy and frequent usage of our adjustment without bearing costs, even if some players behave unexpectedly. The resultant action profile itself needs no adjustment. Importantly, we also prove that our adjustment minimises the general transfer among all such adjustments, counting the total subsidising and taxation.
Keywords: adjustment; strictly dominant; fairness; individually rational; transfer; tax; subsidy

Die professionelle pädagogische Beziehung zwischen Referendar*innen und ihren Seminarlehrkräften: Belastungsfaktor oder Ressource? - Kärner, Tobias; Goller, Michael; Bonnes, Caroline; Maué, Elisabeth (Zeitschrift für Erziehungswissenschaft)
Zusammenfassung: Der Beitrag befasst sich mit der professionellen pädagogischen Beziehung zwischen Referendar*innen und ihren Seminarlehrkräften, deren Beitrag für die Beanspruchung der Referendar*innen bisher noch nicht eingängig untersucht wurde. Das Ziel der Studie ist es, anhand einer Querschnittserhebung von 2583 Referendar*innen und ausgebildeten Lehrkräften, kompensatorische sowie verstärkende Effekte der Beziehungsdimensionen Transparenz, Fairness, Vertrauen und Ambivalenz auf die wahrgenommene Beanspruchung im Referendariat zu untersuchen. Die Analyse erfolgt mittels eines latent moderierten Strukturgleichungsansatzes. Die Ergebnisse zeigen, dass Belastungen durch die Kerntätigkeiten im Referendariat sowie Belastungen durch den Umgang mit Kolleg*innen im Lehrer*innenkollegium in signifikant positivem Zusammenhang mit resultierenden Beanspruchungsreaktionen stehen. Je transparenter, fairer und vertrauensvoller und je weniger ambivalent die Beziehung zur Seminarlehrkraft erlebt wird, desto geringer fallen die Beanspruchungsreaktionen aus. Die Ergebnisse werden hinsichtlich ihrer Relevanz für die Beziehungsarbeit im Referendariat als zentralem Ausbildungsbestandteil der zweiten Phase der Lehrer*innenausbildung diskutiert.
Keywords: Education

Cardinality Constrained Scheduling in Online Models - Epstein, Leah; Lassota, Alexandra; Levin, Asaf; Maack, Marten; Rohwedder, Lars (39th International Symposium on Theoretical Aspects of Computer Science, STACS 2022, March 15-18, 2022, Marseille, France (Virtual Conference))

Clear Roads and Dirty Air? Indirect effects of reduced private traffic congestion on emissions from heavy traffic - Hoffmann, Christin; Thommes, Kirsten (Journal of Cleaner Production)
Keywords: Industrial and Manufacturing Engineering; Strategy and Management; General Environmental Science; Renewable Energy; Sustainability and the Environment; Building and Construction

Clear Roads and Dirty Air? Indirect effects of reduced private traffic congestion on emissions from heavy traffic - Hoffmann, Christin; Thommes, Kirsten (Journal of Cleaner Production)
Keywords: Industrial and Manufacturing Engineering; Strategy and Management; General Environmental Science; Renewable Energy; Sustainability and the Environment; Building and Construction

The Moral Debater: A Study on the Computational Generation of Morally Framed Arguments - Alshomary, Milad; El Baff, Roxanne; Gurcke, Timon; Wachsmuth, Henning (Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics)

"Mama Always Had a Way of Explaining Things So I Could Understand": A Dialogue Corpus for Learning How to Explain - Wachsmuth, Henning; Alshomary, Milad (Proceedings of the 29th International Conference on Computational Linguistics)

On the Role of Knowledge in Computational Argumentation - Lauscher, Anne; Wachsmuth, Henning; Gurevych, Iryna; Glavaš, Goran (Transactions of the Association for Computational Linguistics)

Identifying the Human Values behind Arguments - Kiesel, Johannes; Alshomary, Milad; Handke, Nicolas; Cai, Xiaoni; Wachsmuth, Henning; Stein, Benno (Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics)

Domain-specific Language for Condition Monitoring Software Development - Pasic, Faruk; Becker, Matthias (2022 IEEE 27th International Conference on Emerging Technologies and Factory Automation (ETFA))

"Swer siner kunst meister ist, der hat gewalt an siner list". Herborts von Fritzlar Liet von Troye als Fortsetzungstext des Eneasromans Heinrichs von Veldeke am Schnittpunkt von Aneignung und Neukonstitution - Somogyi, Peter (Troja bauen)

No Word Embedding Model Is Perfect: Evaluating the Representation Accuracy for Social Bias in the Media - Spliethöver, Maximilian; Keiff, Maximilian; Wachsmuth, Henning (Proceedings of The 2022 Conference on Empirical Methods in Natural Language Processing (EMNLP 2022))
News articles both shape and reflect public opinion across the political spectrum. Analyzing them for social bias can thus provide valuable insights, such as prevailing stereotypes in society and the media, which are often adopted by NLP models trained on respective data. Recent work has relied on word embedding bias measures, such as WEAT. However, several representation issues of embeddings can harm the measures' accuracy, including low-resource settings and token frequency differences. In this work, we study what kind of embedding algorithm serves best to accurately measure types of social bias known to exist in US online news articles. To cover the whole spectrum of political bias in the US, we collect 500k articles and review psychology literature with respect to expected social bias. We then quantify social bias using WEAT along with embedding algorithms that account for the aforementioned issues. We compare how models trained with the algorithms on news articles represent the expected social bias. Our results suggest that the standard way to quantify bias does not align well with knowledge from psychology. While the proposed algorithms reduce the~gap, they still do not fully match the literature.