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.

Pfirsichbaum und dunkler Wald. Pflanzliche Konfigurationen zwischen Dynamisierung und Innehalten in 'Partonopier und Meliur' Konrads von Würzburg - Musiol, Marie-Luise; Winst, Silke (Spiritual Vegetation: Vegetal Nature in Religious Contexts Across Medieval and Early Modern Europe (Berliner Mittelalter- und Frühneuzeitforschung, Vol. 26))

Bennewitz, Ingrid/Eming, Jutta/Traulsen, Johannes: Gender Studies – Queer Studies – Intersektionalität. Eine Zwischenbilanz aus mediävistischer Perspektive (Berliner Mittelalter- und Frühneuzeitforschung 25), Göttingen 2019 - Musiol, Marie-Luise (Sexuologie)

Menschlicher Körper, heiliger Körper. Zur Kreuzigung Christi im Donaueschinger Passionsspiel - Musiol, Marie-Luise (Unverfügbar. Kulturen des Heiligen)

Can Tax Rate Changes Accelerate Investment under Entry and Exit Flexibility? – Insights from an Economic Experiment - Fahr, René; Janssen, Elmar A.; Sureth-Sloane, Caren (FinanzArchiv / Public Finance Analysis)
This study investigates the conditions under which tax rate changes accelerate risky investments. While tax rate increases are often expected to harm investment, analytical studies find tax rate increases may foster investment under flexibility.We design a theorybased experimentwith a binomial random walk and entry–exit flexibility.We find accelerated investment upon tax rate increases irrespective of an exit option, but no corresponding response to tax cuts. This asymmetry may be due to tax salience and mechanisms from irreversible choice under uncertainty. Given this evidence of unexpected tax-reform effects, tax policymakers should carefully consider behavioral aspects.
Keywords: Economic ExperimentM; Investment Decisions; Tax Effects; Timing Flexibility; Uncertainty

How Does Trust Affect Concessionary Behavior in Tax Bargaining? - Eberhartinger, Eva; Speitmann, Raffael; Sureth-Sloane, Caren; Wu, Yuchen (FinanzArchiv / Public Finance Analysis)
We study the bargaining behavior between auditor and auditee in a tax setting and scrutinize the effect of interpersonal trust and trust in government on both parties’ concessions. We find evidence that both kinds of trust affect the concessionary behavior, albeit in different ways. While trust in government affects concessionary behavior in line with intuitive predictions, we find that interpersonal trust only affects tax auditors. For high interpersonal trust, the alleviating effect of high trust in government on tax auditors’ concessions is less pronounced. Our findings help tax authorities to shape programs to enhance compliance in an atmosphere of trust.
Keywords: Behavioral Taxation; Concessionary Behavior; Interpersonal Trust; Tax Audit; Trust in Government

Schlieren imaging with fractional Fourier transform to visualise ultrasonic fields - Hetkämper, Tim; Claes, Leander; Henning, Bernd (Sensoren und Messsysteme - Beiträge der 21. ITG/GMA-Fachtagung)

Back to the Roots: Predicting the Source Domain of Metaphors using Contrastive Learning - Sengupta, Meghdut; Alshomary, Milad; Wachsmuth, Henning (Proceedings of the 2022 Workshop on Figurative Language Processing)

Overview of Touché 2022: Argument Retrieval - Bondarenko, Alexander; Fröbe, Maik; Kiesel, Johannes; Syed, Shahbaz; Gurcke, Timon; Beloucif, Meriem; Panchenko, Alexander; Biemann, Chris; Stein, Benno; Wachsmuth, Henning; Potthast, Martin; Hagen, Matthias (Lecture Notes in Computer Science)

Augmented Reality Anwendungen in der betrieblichen Aus‐ und Weiterbildung - Kärner, Tobias; Goller, Michael; Maier, Andreas (Digitalisierung und digitale Medien in der Berufsbildung: Konzepte, Befunde und Herausforderungen)
Der Beitrag widmet sich dem Einsatz von Augmented Reality (AR) in betrieblichen Aus- und Weiterbildungskontexten. Hierbei stehen insbesondere Fragen zu Berufsfeldern und Ausbildungsinhalten, zu verwendeten AR-Spezifikationen, zu Zusammenhängen zwischen AR-Anwendung und leistungs-, wahrnehmungs- und motivationsbezogenen Variablen sowie zur didaktischen Einbettung entsprechender Technologien im Fokus. Auf Basis einer integrierenden Sichtung bestehender Literatur konnten insgesamt 16 Studien sowie zwei bereits vorliegende Literaturreviews in die Analyse eingeschlossen werden. Die Ergebnisse verweisen u. a. auf eine heterogene Lage hinsichtlich forschungsmethodischer Zugänge und didaktischer Referenzkonzepte. Weitgehend förderliche Effekte auf leistungs-, wahrnehmungs- und motivationsbezogene Variablen stimmen insgesamt bezüglich des AR-Einsatzes positiv, machen aber auch die Notwendigkeit einer integrierten Betrachtung technologischer und pädagogisch-instruktionaler Gestaltungsparameter deutlich.
Keywords: Augmented Reality; Ausbildung; Weiterbildung; Lernen mit digitalen Medien; integratives Literaturreview

Kompetenzen des betrieblichen Ausbildungspersonals: Eine literaturbasierte Systematisierung - Bonnes, Caroline; Binkert, Julia; Goller, Michael (Berufsbildung in Wissenschaft und Praxis – BWP)
Startpunkt jeglicher Professionalisierungsbemühungen ist ein Verständnis der für das professionelle Handeln notwendigen Kompetenzen. Dieser Beitrag widmet sich der literaturbasierten Identifikation von Kompetenzen des betrieblichen Ausbildungspersonals und ordnet diese den vier Kompetenzbereichen Fach-, Methoden-, Sozial- und Selbstkompetenz zu. Die Ergebnisse können sowohl als Grundlage für weitere Forschung dienen als auch in der Praxis als Orientierung für die Gestaltung von Qualifizierungsmaßnahmen verwendet werden.

Argument Novelty and Validity Assessment via Multitask and Transfer Learning - Alshomary, Milad; Stahl, Maja (Proceedings of the 9th Workshop on Argument Mining)
An argument is a constellation of premises reasoning towards a certain conclusion. The automatic generation of conclusions is becoming a very prominent task, raising the need for automatic measures to assess the quality of these generated conclusions. The SharedTask at the 9th Workshop on Argument Mining proposes a new task to assess the novelty and validity of a conclusion given a set of premises. In this paper, we present a multitask learning approach that transfers the knowledge learned from the natural language inference task to the tasks at hand. Evaluation results indicate the importance of both knowledge transfer and joint learning, placing our approach in the fifth place with strong results compared to baselines.

Multimodal quantification of degradation pathways during extreme fast charging of lithium-ion batteries - McShane, Eric J.; Paul, Partha P.; Tanim, Tanvir R.; Cao, Chuntian; Steinrück, Hans-Georg; Thampy, Vivek; Trask, Stephen E.; Dunlop, Alison R.; Jansen, Andrew N.; Dufek, Eric J.; Toney, Michael F.; Weker, Johanna Nelson; et al. (Journal of Materials Chemistry A)
Using a unique combination of advanced characterization techniques, we identify specific degradation mechanisms and quantify degradative species formed during fast charge cycling of lithium-ion battery pouch cells.
Keywords: General Materials Science; Renewable Energy; Sustainability and the Environment; General Chemistry

Simultaneous neutron and X-ray tomography for visualization of graphite electrode degradation in fast-charged lithium-ion batteries - Yusuf, Maha; LaManna, Jacob M.; Paul, Partha P.; Agyeman-Budu, David N.; Cao, Chuntian; Dunlop, Alison R.; Jansen, Andrew N.; Polzin, Bryant J.; Trask, Stephen E.; Tanim, Tanvir R.; Dufek, Eric J.; Thampy, Vivek; et al. (Cell Reports Physical Science)
Keywords: General Physics and Astronomy; General Energy; General Engineering; General Materials Science; General Chemistry

HARRIS: Hybrid Ranking and Regression Forests for Algorithm Selection - Fehring, Lukass; Hanselle, Jonas Manuel; Tornede, Alexander (Workshop on Meta-Learning (MetaLearn 2022) @ NeurIPS 2022)
It is well known that different algorithms perform differently well on an instance of an algorithmic problem, motivating algorithm selection (AS): Given an instance of an algorithmic problem, which is the most suitable algorithm to solve it? As such, the AS problem has received considerable attention resulting in various approaches - many of which either solve a regression or ranking problem under the hood. Although both of these formulations yield very natural ways to tackle AS, they have considerable weaknesses. On the one hand, correctly predicting the performance of an algorithm on an instance is a sufficient, but not a necessary condition to produce a correct ranking over algorithms and in particular ranking the best algorithm first. On the other hand, classical ranking approaches often do not account for concrete performance values available in the training data, but only leverage rankings composed from such data. We propose HARRIS- Hybrid rAnking and RegRessIon foreSts - a new algorithm selector leveraging special forests, combining the strengths of both approaches while alleviating their weaknesses. HARRIS' decisions are based on a forest model, whose trees are created based on splits optimized on a hybrid ranking and regression loss function. As our preliminary experimental study on ASLib shows, HARRIS improves over standard algorithm selection approaches on some scenarios showing that combining ranking and regression in trees is indeed promising for AS.

Methoden zum Design digitaler Plattformen, Geschäftsmodelle und Service-Ökosysteme - Robra-Bissantz, Susanne; Lattemann, Christoph; Laue, Ralf; Leonhard-Pfleger, Raphaela; Wagner, Luisa; Gerundt, Oliver; Schlimbach, Ricarda; Baumann, Sabine; Vorbohle, Christian; Gottschalk, Sebastian; Kundisch, Dennis; Engels, Gregor; et al. (HMD Praxis der Wirtschaftsinformatik)

Tackling Crises Together? – An Econometric Analysis of Charitable Crowdfunding During the COVID-19 Pandemic - Althaus, Maike; Poniatowski, Martin; Kundisch, Dennis (Proceedings of the 43rd International Conference on Information Systems (ICIS))

May I have your attention, please? Analyzing the effects of attention screening mechanisms on crowdworking platforms - Laux, Florian; Poniatowski, Martin; Kundisch, Dennis

Online Reviews in B2B Markets: A Qualitative Study on the Underlying Motives - Seutter, Janina

The Structural Power of Reconfigurable Circuits in the Amoebot Model - Padalkin, Andreas; Scheideler, Christian; Warner, Daniel (28th International Conference on DNA Computing and Molecular Programming (DNA 28))

Fault-Tolerant Shape Formation in the Amoebot Model - Kostitsyna, Irina; Scheideler, Christian; Warner, Daniel (28th International Conference on DNA Computing and Molecular Programming (DNA 28))

Online Reviews in B2B Markets: A Qualitative Study of Underlying Motivations - Seutter, Janina (Proceedings of the 30th European Conference on Information Systems (ECIS))

How the Display of the Transaction Count Affects the Purchase Intention - Poniatowski, Martin (Proceedings of the 28th Americas Conference on Information Systems (AMCIS))

Static data-flow analysis for software product lines in C - Schubert, Philipp; Gazzillo, Paul; Patterson, Zach; Braha, Julian; Schiebel, Fabian; Hermann, Ben; Wei, Shiyi; Bodden, Eric (Automated Software Engineering)
Abstract Many critical codebases are written in C, and most of them use preprocessor directives to encode variability, effectively encoding software product lines. These preprocessor directives, however, challenge any static code analysis. SPLlift, a previously presented approach for analyzing software product lines, is limited to Java programs that use a rather simple feature encoding and to analysis problems with a finite and ideally small domain. Other approaches that allow the analysis of real-world C software product lines use special-purpose analyses, preventing the reuse of existing analysis infrastructures and ignoring the progress made by the static analysis community. This work presents VarAlyzer , a novel static analysis approach for software product lines. VarAlyzer first transforms preprocessor constructs to plain C while preserving their variability and semantics. It then solves any given distributive analysis problem on transformed product lines in a variability-aware manner. VarAlyzer ’s analysis results are annotated with feature constraints that encode in which configurations each result holds. Our experiments with 95 compilation units of OpenSSL show that applying VarAlyzer enables one to conduct inter-procedural, flow-, field- and context-sensitive data-flow analyses on entire product lines for the first time, outperforming the product-based approach for highly-configurable systems.
Keywords: inter-procedural static analysis; software product lines; preprocessor; LLVM; C/C++

Overcoming Silos: A Review of Business Model Modeling Languages for Business Ecosystems - Vorbohle, Christian; Kundisch, Dennis (Proceedings of the 30th European Conference on Information Systems (ECIS))

Tackling Crises Together? - An Econometric Analysis of Charitable Crowdfunding During the COVID-19 Pandemic - Althaus, Maike; Poniatowski, Martin; Kundisch, Dennis

Key Properties of Sustainable Business Ecosystem Relationships - Vorbohle, Christian; Kundisch, Dennis

Rollercoaster of Emotions – A Semantic Analysis of Fundraising Campaigns over the Course of the Covid-19 Pandemic - Grieger, Nicole; Seutter, Janina; Kundisch, Dennis (Tagungsband der 17. Internationalen Tagung Wirtschaftsinformatik 2022)

Age of Information Process under Strongly Mixing Communication -- Moment Bound, Mixing Rate and Strong Law - Redder, Adrian; Ramaswamy, Arunselvan; Karl, Holger (Proceedings of the 58th Allerton Conference on Communication, Control, and Computing)
The decentralized nature of multi-agent systems requires continuous data exchange to achieve global objectives. In such scenarios, Age of Information (AoI) has become an important metric of the freshness of exchanged data due to the error-proneness and delays of communication systems. Communication systems usually possess dependencies: the process describing the success or failure of communication is highly correlated when these attempts are ``close'' in some domain (e.g. in time, frequency, space or code as in wireless communication) and is, in general, non-stationary. To study AoI in such scenarios, we consider an abstract event-based AoI process $Δ(n)$, expressing time since the last update: If, at time $n$, a monitoring node receives a status update from a source node (event $A(n-1)$ occurs), then $Δ(n)$ is reset to one; otherwise, $Δ(n)$ grows linearly in time. This AoI process can thus be viewed as a special random walk with resets. The event process $A(n)$ may be nonstationary and we merely assume that its temporal dependencies decay sufficiently, described by $α$-mixing. We calculate moment bounds for the resulting AoI process as a function of the mixing rate of $A(n)$. Furthermore, we prove that the AoI process $Δ(n)$ is itself $α$-mixing from which we conclude a strong law of large numbers for $Δ(n)$. These results are new, since AoI processes have not been studied so far in this general strongly mixing setting. This opens up future work on renewal processes with non-independent interarrival times.

Multi-agent Policy Gradient Algorithms for Cyber-physical Systems with Lossy Communication - Redder, Adrian; Ramaswamy, Arunselvan; Karl, Holger (Proceedings of the 14th International Conference on Agents and Artificial Intelligence)

To Prefer or to Choose? Generating Agency and Power Counterfactuals Jointly for Gender Bias Mitigation - Stahl, Maja; Spliethöver, Maximilian; Wachsmuth, Henning (Proceedings of the Fifth Workshop on Natural Language Processing and Computational Social Science)
Gender bias may emerge from an unequal representation of agency and power, for example, by portraying women frequently as passive and powerless ("She accepted her future'') and men as proactive and powerful ("He chose his future''). When language models learn from respective texts, they may reproduce or even amplify the bias. An effective way to mitigate bias is to generate counterfactual sentences with opposite agency and power to the training. Recent work targeted agency-specific verbs from a lexicon to this end. We argue that this is insufficient, due to the interaction of agency and power and their dependence on context. In this paper, we thus develop a new rewriting model that identifies verbs with the desired agency and power in the context of the given sentence. The verbs' probability is then boosted to encourage the model to rewrite both connotations jointly. According to automatic metrics, our model effectively controls for power while being competitive in agency to the state of the art. In our evaluation, human annotators favored its counterfactuals in terms of both connotations, also deeming its meaning preservation better.

Distributed gradient-based optimization in the presence of dependent aperiodic communication - Redder, Adrian; Ramaswamy, Arunselvan; Karl, Holger (arXiv:2201.11343)
Iterative distributed optimization algorithms involve multiple agents that communicate with each other, over time, in order to minimize/maximize a global objective. In the presence of unreliable communication networks, the Age-of-Information (AoI), which measures the freshness of data received, may be large and hence hinder algorithmic convergence. In this paper, we study the convergence of general distributed gradient-based optimization algorithms in the presence of communication that neither happens periodically nor at stochastically independent points in time. We show that convergence is guaranteed provided the random variables associated with the AoI processes are stochastically dominated by a random variable with finite first moment. This improves on previous requirements of boundedness of more than the first moment. We then introduce stochastically strongly connected (SSC) networks, a new stochastic form of strong connectedness for time-varying networks. We show: If for any $p \ge0$ the processes that describe the success of communication between agents in a SSC network are $α$-mixing with $n^{p-1}α(n)$ summable, then the associated AoI processes are stochastically dominated by a random variable with finite $p$-th moment. In combination with our first contribution, this implies that distributed stochastic gradient descend converges in the presence of AoI, if $α(n)$ is summable.