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Perfectionism is a personality disposition characterized by setting extremely high performance-standards coupled with critical self-evaluations. Often conceived as positive, perfectionism can yield not only beneficial but also deleterious outcomes ranging from anxiety to burnout. In this proposal, we set out to investigate the role of the technology and, particularly, social media in individuals’ strivings for perfection. We lay down theoretical bases for the possibility that social media plays a role in the development of perfectionism. To empirically test the hypothesized relationship, we propose a comprehensive study design based on the experience sampling method. Lastly, we provide an overview of the planned analysis and future steps.
Coming back for more
(2022)
Recent spikes in social networking site (SNS) usage times have launched investigations into reasons for excessive SNS usage. Extending research on social factors (i.e., fear of missing out), this study considers the News Feed setup. More specifically, we suggest that the order of the News Feed (chronological vs. algorithmically assembled posts) affects usage behaviors. Against the background of the variable reward schedule, this study hypothesizes that the different orders exert serendipity differently. Serendipity, termed as unexpected lucky encounters with information, resembles variable rewards. Studies have evidenced a relation between variable rewards and excessive behaviors. Similarly, we hypothesize that order-induced serendipitous encounters affect SNS usage times and explore this link in a two-wave survey with an experimental setup (users using either chronological or algorithmic News Feeds). While theoretically extending explanations for increased SNS usage times by considering the News Feed order, practically the study will offer recommendations for relevant stakeholders.
Visual Social Networking Sites (SNSs) enable users to present themselves favorably to gain likes and the attention of others. Especially, Instagram is known for its focus on beauty, fitness, fashion, and dietary topics. Although a large body of research reports negative weight-related outcomes of SNS usage (e.g., body dissatisfaction, body image concerns), studies examining how SNS usage relates to these outcomes are scarce. Based on the visual normalization theory, we argue that SNS content facilitates normalization of so-called thin- and fit-ideals, thereby leading to biased perceptions of the average body weight in society. Therefore, this study tests whether Instagram use is associated with perceiving that the average person weighs less. Responses of 181 survey participants confirm that Instagram use is negatively related to average weight perception of both women and men. These findings contribute to the growing body of research on how SNS use relates to negative weight-related outcomes.
Stetig steigende Studierendenzahlen und Studierendenerwartungen der „Generation Z“ als „Digital Natives“ stellen Hochschulen bei gleichbleibenden Lehrressourcen vor vielfältige technische, didaktische, organisationale und curriculare Herausforderungen. Aufgrund ihrer Diversität und Heterogenität gibt es keinen einheitlichen Weg der digitalen Transformation im Hochschulsektor. Curricula, Studienstrukturen, Präsenzlehre und digitale Lehr- und Lernangebote müssen auf die jeweiligen Hochschulen, Zielgruppen und Kooperationspartner zugeschnitten werden. Dabei müssen auch neue Zielgruppen erreicht werden, z.B. Berufstätige und Teilzeitstudierende, und die Individualisierung sowie die nationale und internationale Studierendenmobilität gefördert werden. Kompetenzen für die Informationsextraktion aus Lern- und Studienprozessen, (Big) Data Analytics und Visualisierung, Künstliche Intelligenz und Augmented Reality müssen in Hochschulen aufgebaut werden. Von der digitalen Transformation sind alle Bereiche von Hochschulen betroffen, z.B. Präsidien, Fakultäten und gleichgestellte Einrichtungen, Universitätsverwaltungen, Forschungseinrichtungen sowie zentrale und dezentrale (IT-)Dienstleister, die sich mit schnell verändernden Anforderungs- und Rollenprofilen anpassen müssen. Ferner sind rechtliche Rahmenbedingungen zu betrachten, z.B. Datenschutzanforderungen, um die Potenziale von digitalen Lehr- und Lernangeboten und von digitalen Medien in der Lehre zu erschließen. Dieser Track diskutiert theoretische, konzeptionelle, gestaltungsorientierte, empirische und verhaltensorientierte Beiträge.
Enterprise systems have long played an important role in businesses of various sizes. With the increasing complexity of today’s business relationships, specialized application systems are being used more and more. Moreover, emerging technologies such as artificial intelligence are becoming accessible for enterprise systems. This raises the question of the future role of enterprise systems. This minitrack covers novel ideas that contribute to and shape the future role of enterprise systems with five contributions.
The present volume contains a selection of papers presented at the Fifth International Symposium Russian Grammar: System–Usus–Language Variation, from September 22 to 24, 2021, at the University of Potsdam (Germany). The selected essays tackle the issues that arise when Russian Grammar meets new linguistic paradigms (such as corpus linguistics) and new challenges (such as heritage languages). The relevant findings are discussed with a particular focus on an updated version of the 1980 Academy grammar of Russian.
Spectral detection enables multi-color fluorescence fluctuation spectroscopy studies in living cells
(2021)
Fontanes Medien
(2022)
Theodor Fontane war, im durchaus modernen Sinne, ein Medienarbeiter: Als Presse-Agent in London lernte er die innovativste Presselandschaft seiner Zeit kennen; als Redakteur in Berlin leistete er journalistische Kärrnerarbeit; er schrieb Kritiken über das Theater, die bildende Kunst und die Literatur – und auch seine Romane wie seine Reisebücher sind stets Medienprodukte, als Serien in in Zeitungen und Zeitschriften platziert, bevor sie auf dem Buchmarkt erschienen.
Der vorliegende Band dokumentiert die Ergebnisse eines internationalen Kongresses, veranstaltet 2019 vom Theodor-Fontane-Archiv in Potsdam. Die ebenso rasante wie umfassende Medialisierung und Vernetzung der Gesellschaft im Laufe des 19. Jahrhunderts wird dabei als produktive Voraussetzung der schriftstellerischen Tätigkeit Fontanes begriffen. Eingebettet in ein weit verzweigtes Netz der Korrespondenz und der postalischen Textzirkulation, vertraut mit den Routinen und Publika der periodischen Massenpresse, für die er sein Leben lang schrieb, und auf vielfältige Weise geprägt von der visuellen Kultur seiner Zeit wird Theodor Fontane als gleichermaßen journalistisch versierter wie ästhetisch sensibler Grenzgänger erkennbar.
Modern web browsers are digital software platforms, as they allow third-parties to extend functionality by providing extensions. Given the intense competition, differentiation through provided functionality is a key factor for browser platforms. As browsers progress, they constantly release new features. Browsers might thereby enter complementary markets if they add functionality formerly provided by third-party extensions, which is referred to as ‘platform coring’. Previous studies missed the perspective of the involved parties. To address this gap, we conduct interviews with third-party and core developers in the security and privacy domain from Firefox and Chrome. In essence, the study provides three contributions. First, insights into stakeholder-specific issues concerning coring. Second, measures to prevent coring. Third, strategical guidance for developers and owners. Third-parties experienced and core developers acknowledged coring to occur on browser platforms. While developers with extrinsic motivations assess coring negatively, developers with intrinsic motivations perceive coring positively.
Public blockchain
(2020)
Blockchain has the potential to change business transactions to a major extent. Thereby, underlying consensus algorithms are the core mechanism to achieve consistency in distributed infrastructures. Their application aims for transparency and accountability in societal transactions. As a result of missing reviews holistically covering consensus algorithms, we aim to (1) identify prevalent consensus algorithms for public blockchains, and (2) address the resource perspective with a sustainability consideration (whereby we address the three spheres of sustainability). Our systematic literature review identified 33 different consensus algorithms for public blockchains. Our contribution is twofold: first, we provide a systematic summary of consensus algorithms for public blockchains derived from the scientific literature as well as real-world applications and systemize them according to their research focus; second, we assess the sustainability of consensus algorithms using a representative sample and thereby highlight the gaps in literature to address the holistic sustainability of consensus algorithms.
Software platforms allow for the extension of features by third-party contributors. Thereby, platform innovation is an important aspects of platforms attractiveness for users and complementors. While previous research focused the introduction of new features, the aspect of feature removal and discontinued features on software platforms has been disregarded. To explore the phenomenon and motivations for feature removal on software platforms, a review of recent literature is provided. To illustrate the existence of and motivations for feature removal, a case study of the browser platform Mozilla Firefox is presented. The results reveal feature removal to regularly occur on browser platforms for user- and developer-related features. Frequent reasons for feature removal involve unused features, security concerns, and bugs. Related motivations for feature removal are discussed from the platform owner's perspective. Implications for complementors and users are highlighted.
The idea of the continuous improvement process (CIP) helps companies to continuously improve their operation and thereby contributes to their competitiveness. Through digi tization, new potentials emerge to solve known CIP issues. This contribution specifically addresses the individual motivation of employees to contribute to the CIP. Typically, related initiatives lack contributions over time. The use of gamification is a promising way to achieve continuous participation by addressing the individual needs of participants. While the use of extrinsic motivation elements is common in practice, the idea of this approach is to specifically address intrinsic motivations which serve as a long-term motivator. This article contributes to a gam-ification concept for the continuous improvement process. The main results include an adapted CIP, a gamification concept, and a market mechanism. Furthermore, the concept is implemented and demonstrated as a prototype in an online platform.
Increasingly fast development cycles and individualized products pose major challenges for today's smart production systems in times of industry 4.0. The systems must be flexible and continuously adapt to changing conditions while still guaranteeing high throughputs and robustness against external disruptions. Deep rein- forcement learning (RL) algorithms, which already reached impressive success with Google DeepMind's AlphaGo, are increasingly transferred to production systems to meet related requirements. Unlike supervised and unsupervised machine learning techniques, deep RL algorithms learn based on recently collected sensor- and process-data in direct interaction with the environment and are able to perform decisions in real-time. As such, deep RL algorithms seem promising given their potential to provide decision support in complex environments, as production systems, and simultaneously adapt to changing circumstances. While different use-cases for deep RL emerged, a structured overview and integration of findings on their application are missing. To address this gap, this contribution provides a systematic literature review of existing deep RL applications in the field of production planning and control as well as production logistics. From a performance perspective, it became evident that deep RL can beat heuristics significantly in their overall performance and provides superior solutions to various industrial use-cases. Nevertheless, safety and reliability concerns must be overcome before the widespread use of deep RL is possible which presumes more intensive testing of deep RL in real world applications besides the already ongoing intensive simulations.
The paper deals with the increasing growth of embedded systems and their role within structures similar to the Internet (Internet of Things) as those that provide calculating power and are more or less appropriate for analytical tasks. Faced with the example of a cyber-physical manufacturing system, a common objective function is developed with the intention to measure efficient task processing within analytical infrastructures. A first validation is realized on base of an expert panel.
Web Tracking
(2018)
Web tracking seems to become ubiquitous in online business and leads to increased privacy concerns of users. This paper provides an overview over the current state of the art of web-tracking research, aiming to reveal the relevance and methodologies of this research area and creates a foundation for future work. In particular, this study addresses the following research questions: What methods are followed? What results have been achieved so far? What are potential future research areas? For these goals, a structured literature review based upon an established methodological framework is conducted. The identified articles are investigated with respect to the applied research methodologies and the aspects of web tracking they emphasize.
Traditional production systems are enhanced by cyber-physical systems (CPS) and Internet of Things. A kind of next generation systems, those cyber-physical production systems (CPPS) are able to raise the level of autonomy of its production components. To find the optimal degree of autonomy in a given context, a research approach is formulated using a simulation concept. Based on requirements and assumptions, a cyber-physical market is modeled and qualitative hypotheses are formulated, which will be verified with the help of the CPPS of a hybrid simulation environment.
Track and Treat
(2018)
E-Mail tracking mechanisms gather information on individual recipients’ reading behavior. Previous studies show that e-mail newsletters commonly include tracking elements. However, prior work does not examine the degree to which e-mail senders actually employ gathered user information. The paper closes this research gap by means of an experimental study to clarify the use of tracking-based infor- mation. To that end, twelve mail accounts are created, each of which subscribes to a pre-defined set of newsletters from companies based in Germany, the UK, and the USA. Systematically varying e-mail reading patterns across accounts, each account simulates a different type of user with individual read- ing behavior. Assuming senders to track e-mail reading habits, we expect changes in mailer behavior. The analysis confirms the prominence of tracking in that over 92% of the newsletter e-mails contain tracking images. For 13 out of 44 senders an adjustment of communication policy in response to user reading behavior is observed. Observed effects include sending newsletters at different times, adapting advertised products to match the users’ IT environment, increased or decreased mailing frequency, and mobile-specific adjustments. Regarding legal issues, not all companies that adapt the mail-sending behavior state the usage of such mechanisms in their privacy policy.
Many markets are characterized by pricing competition. Typically, competitors are involved that adjust their prices in response to other competitors with different frequencies. We analyze stochastic dynamic pricing models under competition for the sale of durable goods. Given a competitor’s pricing strategy, we show how to derive optimal response strategies that take the anticipated competitor’s price adjustments into account. We study resulting price cycles and the associated expected long-term profits. We show that reaction frequencies have a major impact on a strategy’s performance. In order not to act predictable our model also allows to include randomized reaction times. Additionally, we study to which extent optimal response strategies of active competitors are affected by additional passive competitors that use constant prices. It turns out that optimized feedback strategies effectively avoid a decline in price. They help to gain profits, especially, when aggressive competitor s are involved.
Die optimale Dimensionierung von IT-Hardware stellt Entscheider aufgrund der stetigen Weiterentwicklung zunehmend vor Herausforderungen. Dies gilt im Speziellen auch für Analytics-Infrastrukturen, die zunehmend auch neue Software zur Analyse von Daten einsetzen, welche in den Ressourcenanforderungen stark variieren. Damit eine flexible und gleichzeitig effiziente Gestaltung von Analytics-Infrastrukturen erreicht werden kann, wird ein dynamisch arbeitendes Architekturkonzept vorgeschlagen, das Aufgaben auf Basis einer systemspezifischen Entscheidungsmaxime mit Hilfe einer Eskalationsmatrix verteilt und hierfür Aufgabencharakteristiken sowie verfügbare Hardwareausstattungen entsprechend ihrer Auslastung berücksichtigt.
In times of digitalization, the collection and modeling of business processes is still a challenge for companies. The demand for trustworthy process models that reflect the actual execution steps therefore increases. The respective kinds of processes significantly determine both, business process analysis and the conception of future target processes and they are the starting point for any kind of change initiatives. Existing approaches to model as-is processes, like process mining, are exclusively focused on reconstruction. Therefore, transactional protocols and limited data from a single application system are used. Heterogeneous application landscapes and business processes that are executed across multiple application systems, on the contrary, are one of the main challenges in process mining research. Using RFID technology is hence one approach to close the existing gap between different application systems. This paper focuses on methods for data collection from real world objects via RFID technology and possible combinations with application data (process mining) in order to realize a cross system mining approach.
The digitalization of value networks holds out the prospect of many advantages for the participating compa- nies. Utilizing information platforms, cross-company data exchange enables increased efficiency of collab- oration and offers space for new business models and services. In addition to the technological challenges, the fear of know-how leakage appears to be a significant roadblock that hinders the beneficial realization of new business models in digital ecosystems. This paper provides the necessary building blocks of digital participation and, in particular, classifies the issue of trust creation within it as a significant success factor. Based on these findings, it presents a solution concept that, by linking the identified building blocks, offers the individual actors of the digital value network the opportunity to retain sovereignty over their data and know-how and to use the potential of extensive networking. In particular, the presented concept takes into account the relevant dilemma, that every actor (e. g. the machine users) has to be able to control his commu- nicated data at any time and have sufficient possibilities for intervention that, on the one hand, satisfy the need for protection of his knowledge and, on the other hand, do not excessively diminish the benefits of the system or the business. Taking up this perspective, this paper introduces dedicated data sovereignty and shows a possible implementation concept.
E-Mail Tracking
(2016)
E-mail advertisement, as one instrument in the marketing mix, allows companies to collect fine-grained behavioural data about individual users’ e-mail reading habits realised through sophisticated tracking mechanisms. Such tracking can be harmful for user privacy and security. This problem is especially severe since e-mail tracking techniques gather data without user consent. Striving to increase privacy and security in e-mail communication, the paper makes three contributions. First, a large database of newsletter e-mails is developed. This data facilitates investigating the prevalence of e- mail tracking among 300 global enterprises from Germany, the United Kingdom and the United States. Second, countermeasures are developed for automatically identifying and blocking e-mail tracking mechanisms without impeding the user experience. The approach consists of identifying important tracking descriptors and creating a neural network-based detection model. Last, the effectiveness of the proposed approach is established by means of empirical experimentation. The results suggest a classification accuracy of 99.99%.
Coring on Digital Platforms
(2017)
Today’s mobile devices are part of powerful business ecosystems, which usually involve digital platforms. To better understand the complex phenomenon of coring and related dynamics, this paper presents a case study comparing iMessage as part of Apple’s iOS and WhatsApp. Specifically, it investigates activities regarding platform coring, as the integration of several functionalities provided by third-party applications in the platform core. The paper makes three contributions. First, a systematization of coring activities is developed. Coring modes are differentiated by the amount of coring and application maintenance. Second, the case study revealed that the phenomenon of platform coring is present on digital platforms for mobile devices. Third, the fundamentals of coring are discussed as a first step towards theoretical development. Even though coring constitutes a potential threat for third-party developers regarding their functional differentiation, an idea of what a beneficial partnership incorporating coring activities could look like is developed here.
As Industry 4.0 infrastructures are seen as highly evolutionary environment with volatile, and time-dependent workloads for analytical tasks, particularly the optimal dimensioning of IT hardware is a challenge for decision makers because the digital processing of these tasks can be decoupled from their physical place of origin. Flexible architecture models to allocate tasks efficiently with regard to multi-facet aspects and a predefined set of local systems and external cloud services have been proven in small example scenarios. This paper provides a benchmark of existing task realization strategies, composed of (1) task distribution and (2) task prioritization in a real-world scenario simulation. It identifies heuristics as superior strategies.
The “output-orientation” is omnipresent in teacher education. In order to evaluate teachers' and students' performances, a wide range of different quantitative questionnaires exist worldwide. One important goal of teaching evaluation is to increase the quality of teaching and learning. The author argues, that standard evaluations which are typically made at the end of the semester are problematic due to two reasons. The first one is that some of the questions are too general and don`t offer concrete ideas as to what kind of actions can be taken to make the courses better. The second problem is that the evaluation is mostly made when the course is already over. Because of this criticism, Apelojg invented the Felix-App which offers the possibility to give feedback in real-time by asking for the emotions and needs that occur during different learning situations. The idea is very simple: positive emotions and satisfied needs are helpful for the learning process. Negative emotions and unsatisfied needs have negative effects on the learning process. First descriptive results show, that “managing emotions” during classes can have positive effects on both motivation and emotions.
E-Mail tracking uses personalized links and pictures for gathering information on user behavior, for example, where, when, on what kind of device, and how often an e-mail has been read. This information can be very useful for marketing purposes. On the other hand, privacy and security requirements of customers could be violated by tracking. This paper examines how e-mail tracking works, how it can be detected automatically, and to what extent it is used in German e-commerce. We develop a detection model and software tool in order to collect and analyze more than 600 newsletter e-mails from companies of several different industries. The results show that the usage of e-mail tracking in Germany is prevalent but also varies depending on the industry.
Future ERP Systems
(2021)
This paper presents a research agenda on the current generation of ERP systems which was developed based on a literature review on current problems of ERP systems. The problems are presented following the ERP life cycle. In the next step, the identified problems are mapped on a reference architecture model of ERP systems that is an extension of the three-tier architecture model that is widely used in practice. The research agenda is structured according to the reference architecture model and addresses the problems identified regarding data, infrastructure, adaptation, processes, and user interface layer.
This article provides some insights into the complex relationships between thinking and behavioral patterns, bio graphical aspects and teaching style. The data was analyzed in the Grounded Theory tradition and with the help of ATLAS.ti. The results presented here offer preliminary findings only since the research is still ongoing. The focus is on the ways teachers deal with mistakes. Based on two case examples, it will be shown how the fear of making mistakes can lead to teacher-centered lessons, and thereby limiting pupils' possibilities to learn autonomously.
Many prediction tasks can be done based on users’ trace data. In this paper, we explored convergent thinking as a personality-related attribute and its relation to features gathered in interactive and non-interactive tasks of an online course. This is an under-utilized attribute that could be used for adapting online courses according to the creativity level to enhance the motivation of learners. Therefore, we used the logfile data of a 60 minutes Moodle course with N=128 learners, combined with the Remote Associates Test (RAT). We explored the trace data and found a weak correlation between interactive tasks and the RAT score, which was the highest considering the overall dataset. We trained a Random Forest Regressor to predict convergent thinking based on the trace data and analyzed the feature importance. The result has shown that the interactive tasks have the highest importance in prediction, but the accuracy is very low. We discuss the potential for personalizing online courses and address further steps to improve the applicability.
Expanding modeling notations
(2021)
Creativity is a common aspect of business processes and thus needs a proper representation through process modeling notations. However, creative processes constitute highly flexible process elements, as new and unforeseeable outcome is developed. This presents a challenge for modeling languages. Current methods representing creative-intensive work are rather less able to capture creative specifics which are relevant to successfully run and manage these processes. We outline the concept of creative-intensive processes and present an example from a game design process in order to derive critical process aspects relevant for its modeling. Six aspects are detected, with first and foremost: process flexibility, as well as temporal uncertainty, experience, types of creative problems, phases of the creative process and individual criteria. By first analyzing what aspects of creative work modeling notations already cover, we further discuss which modeling extensions need to be developed to better represent creativity within business processes. We argue that a proper representation of creative work would not just improve the management of those processes, but can further enable process actors to more efficiently run these creative processes and adjust them to better fit to the creative needs.
How games spoil creativity
(2020)
The demand for a creative workforce is every growing and effective measures to improve individual creativity are searched for. This study analyzes the possibility to use games as a prime for a creative mindset. Two short entertainment games, plus a no-game-comparison condition were set up in three versions of an online-study, along with two creativity tasks and scales to assess the individual creative mindset (fixed-vs-growth, creative self-efficacy and affect). Results indicate priming effects of the games, but in the opposite intended direction: gaming diminished the creative test performances. Those playing the games reported more ideas in the open-ended creative problem task, but those answers were of less quality and they solved less closed-problem items compared to those not playing. An impact of further mindset differences could be ruled out.
This paper aims to contribute to exploring the design possibilities of robots for use in human-robot interaction. In an experiment, we investigate the influence of the human's personality and the robot's design, especially its humanization, on its acceptance. We use the Almere model, the Big 5 personality traits, and the anthropomorphic gestalt variants to build the foundation for our investigation. The assumption that an anthropomorphized robot variant would, in principle, be preferred to the standard variant when a natural choice is enforced could not be evidenced in our experiment. This allows for the interpretation that anthropomorphism does not necessarily lead to intentional perception and, consequently, does not guarantee that it can automatically generate acceptance.
In the time of digitalization the demand for organizational change is rising and demands ways to cope with fundamental changes on the organizational as well as individual level. As a basis, learning and forgetting mechanisms need to be understood in order to guide a change process efficiently and successfully. Our research aims to get a better understanding of individual differences and mechanisms in the change context by performing an experiment where individuals learn and later re-learn a complex production process using a simulation setting. The individual’s performance, as well as retentivity and prior knowledge is assessed. Our results show that higher retentivity goes along with better learning and forgetting performances. Prior knowledge did not reveal such relation to the learning and forgetting performances. The influence of age and gender is discussed in detail.
Process analysis usually focuses only on single and selected processes. It is either existent processes that are recorded and analysed or reference processes that are implemented. So far no evident effort has been put into generalising specific process aspects into patterns and comparing those patterns with regard to their efficiency and effectiveness. This article focuses on the combination of dynamic and holistic analytical elements in enterprise architectures. Our goal is to outline an approach to analyse the development of business processes in a cyclical matter and demonstrate this approach based on an existent modelling language. We want to show that organisational learning can derive from the systematic analysis of past and existent processes from which patterns of successful problem solving can be deducted.
e-ASTROGAM is a concept for a breakthrough observatory space mission carrying a gamma-ray telescope dedicated to the study of the non-thermal Universe in the photon energy range from 0.15 MeV to 3 GeV. The lower energy limit can be pushed down to energies as low as 30 keV for gamma-ray burst detection with the calorimeter. The mission is based on an advanced space-proven detector technology, with unprecedented sensitivity, angular and energy resolution, combined with remarkable polarimetric capability. Thanks to its performance in the MeV-GeV domain, substantially improving its predecessors, e-ASTROGAM will open a new window on the non-thermal Universe, making pioneering observations of the most powerful Galactic and extragalactic sources, elucidating the nature of their relativistic outflows and their effects on the surroundings. With a line sensitivity in the MeV energy range one to two orders of magnitude better than previous and current generation instruments, e-ASTROGAM will determine the origin of key isotopes fundamental for the understanding of supernova explosion and the chemical evolution of our Galaxy. The mission will be a major player of the multiwavelength, multimessenger time-domain astronomy of the 2030s, and provide unique data of significant interest to a broad astronomical community, complementary to powerful observatories such as LISA, LIGO, Virgo, KAGRA, the Einstein Telescope and the Cosmic Explorer, IceCube-Gen2 and KM3NeT, SKA, ALMA, JWST, E-ELT, LSST, Athena, and the Cherenkov Telescope Array.
Myriam Yardeni a consacré des travaux à l'histoire de la Réforme, à la pensée politique et à l'historiographie des Huguenots, aux changements d'attitude envers le peuple juif, à l'Église du Désert, mais aussi au Refuge en Allemagne et en particulier en Prusse. Sans pouvoir retracer ici toute cette partie de son itinéraire de recherche, ni même étudier à fond ses contributions majeures à la recherche sur le Refuge en Prusse, ce texte ne veut qu'apporter un témoignage sur la vitalité et la productivité de sa méthode de recherche.