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Chinese CSP for the world?
(2022)
For three consecutive five-year plans since 2006, China has worked on building up an internationally competitive CSP industry and value chain. One big milestone in commercializing proprietary Chinese CSP technology was the 2016 demonstration program of 20 commercial-scale projects. China sought to increase and demonstrate capacities for domestic CSP technology development and deployment. At the end of the 13th five-year period, we take stock of the demonstrated progress of the Chinese CSP industry towards delivering internationally competitive CSP projects. We find that in January 2021, eight commercial-scale projects, in total 500 MW, have been completed and three others were under construction in China. In addition, Chinese EPC’s have participated in three international CSP projects, although proprietary Chinese CSP designs have not been applied outside China. The largest progress has been made in molten-salt tower technology, with several projects by different companies completed and operating successfully: here, the aims were met, and Chinese companies are now at the global forefront of this segment. Further efforts for large-scale demonstration are needed, however, for other CSP technologies, including parabolic trough - with additional demonstration hindered by a lack of further deployment policies. In the near future, Chinese companies seek to employ the demonstrated capabilities in the tower segment abroad and are developing projects using Chinese technology, financing, and components in several overseas markets. If successful, this will likely lead to increasing competition and further cost reductions for the global CSP sector.
Digitization and demographic change are enormous challenges for companies. Learning factories as innovative learning places can help prepare older employees for the digital change but must be designed and configured based on their specific learning requirements. To date, however, there are no particular recommendations to ensure effective age-appropriate training of bluecollar workers in learning factories. Therefore, based on a literature review, design characteristics and attributes of learning factories and learning requirements of older employees are presented. Furthermore, didactical recommendations for realizing age-appropriate learning designs in learning factories and a conceptualized scenario are outlined by synthesizing the findings.
Throughout the years 2020 and 2021, schools were temporarily closed to slow the spread of SarsCoV-2. For some periods, children were locked out of sports in schools (physical education lessons, school sports working groups) and organized sports in sports clubs which often resulted in physical inactivity. Did these restrictions affect children’s physical fitness? The EMOTIKON project (www.uni-potsdam.de/emotikon) annually assesses the physical fitness (cardiorespiratory endurance [6-minute-run test], coordination [star-run test], speed [20-m sprint test], lower [standing long jump test] and upper [ball push test] limbs muscle power, and balance [one-legged stance test]) of all third graders in the Federal State of Brandenburg, Germany. Participation is mandatory for all public primary schools. In the falls from 2016 to 2021, 83,476 keyage children (i.e., school enrollment according to the legal key date, between eight and nine years in third grade) from 512 schools were assessed with the EMOTIKON test battery. We tested the Covid pandemic effect on a composite score of the four highly correlated physical fitness tests assessing cardiorespiratory endurance, coordination, speed and powerLOW and on another composite score of the three running tests (cardiorespiratory endurance, coordination, speed), as well as separately on all six physical fitness components. Secular trends for each of the physical fitness components and differences between schools and children were taken into account in linear mixed models. We found a negative Covid pandemic effect on the two composite physical fitness scores, as well as on cardiorespiratory endurance, coordination, and speed. We found a positive Covid pandemic effect on powerLOW. Coordination was associated with the largest negative Covid pandemic effect, also passing the threshold of smallest meaningful change (SMC, i.e., 0.2 Cohen’s d) when accumulated across two years. Given the educational context, Covid pandemic effects were also compared relative to the expected age-related development of the physical fitness components between eight and nine years. The Covid pandemic-related developmental costs/gains ranged from three to seven months relative to a longitudinal age effect, and from five to 17 months relative to a cross-sectional age effect. We propose that a longitudinal assessment yields a more reliable estimate of the developmental (age-related) gain than a cross-sectional one. Therefore, we consider the smaller Covid pandemic-related developmental costs/gains to be more credible. Interestingly, on the school level, „fitter” schools (relatively higher Grand Mean) exhibited larger negative Covid pandemic effects than schools with a lower physical fitness score. Negative Covid pandemic effects for the three run tasks were also found by Bähr et al. (2022), who tested the physical fitness of 16,496 Thuringian third-graders from 292 schools with the same six physical fitness tests used in EMOTIKON. Our results may be used to prioritize health-related interventions.
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.
The metaverse is envisioned as a virtual shared space facilitated by emerging technologies such as virtual reality (VR), augmented reality (AR), the Internet of Things (IoT), 5G, artificial intelligence (AI), big data, spatial computing, and digital twins (Allam et al., 2022; Dwivedi et al., 2022; Ravenscraft, 2022; Wiles, 2022). While still a nascent concept, the metaverse has the potential to “transform the physical world, as well as transport or extend physical activities to a virtual world” (Wiles, 2022). Big data technologies will also be essential in managing the enormous amounts of data created in the metaverse (Sun et al., 2022). Metaverse technologies can offer the public sector a host of benefits, such as simplified information exchange, stronger communication with citizens, better access to public services, or benefiting from a new virtual economy. Implementations are underway in several cities around the world (Geraghty et al., 2022). In this paper, we analyze metaverse opportunities for the public sector and explore their application in the context of Germany’s Federal Employment Agency. Based on an analysis of academic literature and practical examples, we create a capability map for potential metaverse business capabilities for different areas of the public sector (broadly defined). These include education (virtual training and simulation, digital campuses that offer not just online instruction but a holistic university campus experience, etc.), tourism (virtual travel to remote locations and museums, virtual festival participation, etc.), health (employee training – as for emergency situations, virtual simulations for patient treatment – for example, for depression or anxiety, etc.), military (virtual training to experience operational scenarios without being exposed to a real-world threats, practice strategic decision-making, or gain technical knowledge for operating and repairing equipment, etc.), administrative services (document processing, virtual consultations for citizens, etc.), judiciary (AI decision-making aids, virtual proceedings, etc.), public safety (virtual training for procedural issues, special operations, or unusual situations, etc.), emergency management (training for natural disasters, etc.), and city planning (visualization of future development projects and interactive feedback, traffic management, attraction gamification, etc.), among others. We further identify several metaverse application areas for Germany's Federal Employment Agency. These applications can help it realize the goals of the German government for digital transformation that enables faster, more effective, and innovative government services. They include training of employees, training of customers, and career coaching for customers. These applications can be implemented using interactive learning games with AI agents, virtual representations of the organizational spaces, and avatars interacting with each other in these spaces. Metaverse applications will both use big data (to design the virtual environments) and generate big data (from virtual interactions). Issues related to data availability, quality, storage, processing (and related computing power requirements), interoperability, sharing, privacy and security will need to be addressed in these emerging metaverse applications (Sun et al., 2022). Special attention is needed to understand the potential for power inequities (wealth inequity, algorithmic bias, digital exclusion) due to technologies such as VR (Egliston & Carter, 2021), harmful surveillance practices (Bibri & Allam, 2022), and undesirable user behavior or negative psychological impacts (Dwivedi et al., 2022). The results of this exploratory study can inform public sector organizations of emerging metaverse opportunities and enable them to develop plans for action as more of the metaverse technologies become a reality. While the metaverse body of research is still small and research agendas are only now starting to emerge (Dwivedi et al., 2022), this study offers a building block for future development and analysis of metaverse applications.
Disinformation campaigns spread rapidly through social media and can cause serious harm, especially in crisis situations, ranging from confusion about how to act to a loss of trust in government institutions. Therefore, the prevention of digital disinformation campaigns represents an important research topic. However, previous research in the field of information systems focused on the technical possibilities to detect and combat disinformation, while ethical and legal perspectives have been neglected so far. In this article, we synthesize previous information systems literature on disinformation prevention measures and discuss these measures from an ethical and legal perspective. We conclude by proposing questions for future research on the prevention of disinformation campaigns from an IS, ethical, and legal perspective. In doing so, we contribute to a balanced discussion on the prevention of digital disinformation campaigns that equally considers technical, ethical, and legal issues, and encourage increased interdisciplinary collaboration in future research.
DPP-4 inhibition with linagliptin delays the progression of diabetic nephropathy in db/db mice
(2012)
Like versus dislike
(2012)
As Facebook's Like-button has become ubiquitous, it is the purpose of this research to investigate (1) whether Likes serve as a signal of a product's or service's quality and (2) how the introduction of a Dislike-button would alter perceptions. Following a qualitative study, we conducted an experiment in which 653 participants were presented with website screenshots featuring varying levels of Likes and Dislikes. The results indicate that the theoretical framing of Likes as a Signal is valid and that people do perceive the quality of products and services as superior when they are associated with more Likes. Signaling also explains the counter-intuitive finding that Dislikes can have a positive effect on people's quality perceptions. Results are discussed with respect to theory and practical implications.
Nanogradient polymer brushes
(2012)
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.
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.
Many prediction tasks can be done based on users’ trace data. This paper explores divergent and convergent thinking as person-related attributes and predicts them based on features gathered in an online course. We use the logfile data of a short Moodle course, combined with an image test (IMT), the Alternate Uses Task (AUT), the Remote Associates Test (RAT), and creative self-efficacy (CSE). Our results show that originality and elaboration metrics can be predicted with an accuracy of ~.7 in cross-validation, whereby predicting fluency and RAT scores perform worst. CSE items can be predicted with an accuracy of ~.45. The best performing model is a Random Forest Tree, where the features were reduced using a Linear Discriminant Analysis in advance. The promising results can help to adjust online courses to the learners’ needs based on their creative performances.
Digital Platforms (DPs) has established themself in recent years as a central concept of the Information Technology Science. Due to the great diversity of digital platform concepts, clear definitions are still required. Furthermore, DPs are subject to dynamic changes from internal and external factors, which pose challenges for digital platform operators, developers and customers. Which current digital platform research directions should be taken to address these challenges remains open so far. The following paper aims to contribute to this by outlining a systematic literature review (SLR) on digital platform concepts in the context of the Industrial Internet of Things (IIoT) for manufacturing companies and provides a basis for (1) a selection of definitions of current digital platform and ecosystem concepts and (2) a selection of current digital platform research directions. These directions are diverted into (a) occurrence of digital platforms, (b) emergence of digital platforms, (c) evaluation of digital platforms, (d) development of digital platforms, and (e) selection of digital platforms.
Openness indicators for the evaluation of digital platforms between the launch and maturity phase
(2024)
In recent years, the evaluation of digital platforms has become an important focus in the field of information systems science. The identification of influential indicators that drive changes in digital platforms, specifically those related to openness, is still an unresolved issue. This paper addresses the challenge of identifying measurable indicators and characterizing the transition from launch to maturity in digital platforms. It proposes a systematic analytical approach to identify relevant openness indicators for evaluation purposes. The main contributions of this study are the following (1) the development of a comprehensive procedure for analyzing indicators, (2) the categorization of indicators as evaluation metrics within a multidimensional grid-box model, (3) the selection and evaluation of relevant indicators, (4) the identification and assessment of digital platform architectures during the launch-to-maturity transition, and (5) the evaluation of the applicability of the conceptualization and design process for digital platform evaluation.
Developing a new paradigm
(2020)
Internet users commonly agree that it is important for them to protect their personal data. However, the same users readily disclose their data when requested by an online service. The dichotomy between privacy attitude and actual behaviour is commonly referred to as the “privacy paradox”. Over twenty years of research were not able to provide one comprehensive explanation for the paradox and seems even further from providing actual means to overcome the paradox. We argue that the privacy paradox is not just an instantiation of the attitude-behaviour gap. Instead, we introduce a new paradigm explaining the paradox as the result of attitude-intention and intentionbehaviour gaps. Historically, motivational goal-setting psychologists addressed the issue of intentionbehaviour gaps in terms of the Rubicon Model of Action Phases and argued that commitment and volitional strength are an essential mechanism that fuel intentions and translate them into action. Thus, in this study we address the privacy paradox from a motivational psychological perspective by developing two interventions on Facebook and assess whether the 287 participants of our online experiment actually change their privacy behaviour. The results demonstrate the presence of an intentionbehaviour gap and the efficacy of our interventions in reducing the privacy paradox.
Association between skeletal robustness and physical activity in schoolchildren - First results
(2011)
An increasing number of clinicians (i.e., nurses and physicians) suffer from mental health-related issues like depression and burnout. These, in turn, stress communication, collaboration, and decision- making—areas in which Conversational Agents (CAs) have shown to be useful. Thus, in this work, we followed a mixed-method approach and systematically analysed the literature on factors affecting the well-being of clinicians and CAs’ potential to improve said well-being by relieving support in communication, collaboration, and decision-making in hospitals. In this respect, we are guided by Brigham et al. (2018)’s model of factors influencing well-being. Based on an initial number of 840 articles, we further analysed 52 papers in more detail and identified the influences of CAs’ fields of application on external and individual factors affecting clinicians’ well-being. As our second method, we will conduct interviews with clinicians and experts on CAs to verify and extend these influencing factors.
Fluvial systems are one of the major features shaping a landscape. They adjust to the prevailing tectonic and climatic setting and therefore are very sensitive markers of changes in these systems. If their response to tectonic and climatic forcing is quantified and if the climatic signal is excluded, it is possible to derive a local deformation history. Here, we investigate fluvial terraces and erosional surfaces in the southern Chilean forearc to assess a long-term geomorphic and hence tectonic evolution. Remote sensing and field studies of the Nahuelbuta Range show that the long-term deformation of the Chilean forearc is manifested by breaks in topography, sequences of differentially uplifted marine, alluvial and strath terraces as well as tectonically modified river courses and drainage basins. We used SRTM-90-data as basic elevation information for extracting and delineating drainage networks. We calculated hypsometric curves as an indicator for basin uplift, stream-length gradient indices to identify stream segments with anomalous slopes, and longitudinal river profiles as well as DS-plots to identify knickpoints and other anomalies. In addition, we investigated topography with elevation-slope graphs, profiles, and DEMs to reveal erosional surfaces. During the first field trip we already measured palaeoflow directions, performed pebble counting and sampled the fluvial terraces in order to apply cosmogenic nuclide dating (<sup>10Be, <sup>26Al) as well as provenance analyses. Our preliminary analysis of the Coastal Cordillera indicates a clear segmentation between the northern and southern parts of the Nahuelbuta Range. The Lanalhue Fault, a NW-SE striking fault zone oblique to the plate boundary, defines the segment boundary. Furthermore, we find a complex drainage re-organisation including a drainage reversal and wind gap on the divide between the Tirúa and Pellahuén basins east of the town Tirúa. The coastal basins lost most of their Andean sediment supply areas that existed in Tertiary and in part during early Pleistocene time. Between the Bío-Bío and Imperial rivers no Andean river is recently capable to traverse the Coastal Cordillera, suggesting ongoing Quaternary uplift of the entire range. From the spatial distribution of geomorphic surfaces in this region two uplift signals may be derived: (1) a long-term differential uplift process, active since the Miocene and possibly caused by underplating of subducted trench sediments, (2) a younger, local uplift affecting only the northern part of the Nahuelbuta Range that may be caused by the interaction of the forearc with the subduction of the Mocha Fracture Zone at the latitude of the Arauco peninsula. Our approach thus provides results in our attempt to decipher the characteristics of forearc development of active convergent margins using long-term geomorphic indicators. Furthermore, it is expected that our ongoing assessment will constrain repeatedly active zones of deformation. <hr> Interdisziplinäres Zentrum für Musterdynamik und Angewandte Fernerkundung Workshop vom 9. - 10. Februar 2006
In Time and the Other Johannes Fabian analysed how modern conceptions of time were “not only secularized and naturalized but also thoroughly spatialized.” According to Fabian, this was particularly visible in modern anthropology which “promoted a scheme in terms of which not only past cultures but all living societies were irrevocably placed on a temporal slope, a stream of Time – some upstream, others downstream.”3 Anthropologists attributed otherness to a distant past which was traditionally associated with cultural retardation, i.e. a lower degree of development, progress, and civilization. Cultural difference was expressed in terms of temporal distance while temporal distance was attributed to spatial remoteness. The result was a phenomenon that Fabian coined “the denial of coevalness” which pointed towards “a persistent and systematic tendency to place the referent(s) of anthropology in a Time other than the present of the producer of anthropological discourse.
In honour of Seymour Papert
(2018)
Forth is nice and flexible but to a philosopher and teacher educator Logo is the more impressing language. Both are relatives of Lisp, but Forth has a reverse Polish notation where as Logo has an infix notation. Logo allows top down programming, Forth only bottom up. Logo enables recursive programming, Forth does not. Logo includes turtle graphics, Forth has nothing comparable. So what to do if you can't get Logo and have no information about its inner architecture? This should be a case of "empirical modelling": How can you model observable results of the behaviour of Logo in terms of Forth? The main steps to solve this problem are shown in the first part of the paper.
The second part of the paper discusses the problem of modelling and shows that the modelling of making and the modelling of recognition have the same mathematical structure. So "empirical modelling" can also serve for modelling desired behaviour of technical systems.
The last part of the paper will show that the heuristic potential of a problem which should be modeled is more important than the programming language. The Picasso construal shows, in a very simple way, how children of different ages can model emotional relations in human behaviour with a simple Logo system.
Background:
Like most countries, Germany is currently recruiting international nurses due to staff shortages. While these are mostly academic, the academisation of nursing in Germany has only just begun. This allows for a broader look at the participation of migrant nurses: How do care teams deal with the fact that immigrant colleagues are theoretically more highly qualified than long-established colleagues?
Methods:
Case studies were conducted in four inpatient care teams of two hospitals in 2022. Qualitative data include 26 observation protocols, 4 group discussions and 17 guided interviews. These were analysed using the documentary method and validated intersubjectively.
Results:
Due to current academisation efforts in Germany and the immigration of academised nursing staff from abroad, the areas of activity and responsibility of nursing in Germany are under negotiating pressure. This concerns basic care for example, which in Germany is provided by skilled workers, but in other countries is mostly provided by assistants or relatives. The question of who should provide basic care, whether all nurses or only nursing assistants, documents the struggle between an established and a new understanding of care. In this context, the knowledge and skills of migrant and academicised care workers become a crucial aspect in the struggle for a new professional identity for care in Germany.
Conclusions:
The specific situation in Germany makes it possible to show the potential for change that international care migration can constitute for destination countries. The far-reaching process of change of German nursing is given a further dimension not only by its academization, but by the immigration of international and academically trained nursing staff, where inclusive or exclusive effects can already be observed.
Key messages: The increasing proportion of migrant nurses accelerates the current discussion on nursing in Germany. Conflict areas show up in everyday work of care teams and must be addressed there.
Enhancing economic efficiency in modular production systems through deep reinforcement learning
(2024)
In times of increasingly complex production processes and volatile customer demands, the production adaptability is crucial for a company's profitability and competitiveness. The ability to cope with rapidly changing customer requirements and unexpected internal and external events guarantees robust and efficient production processes, requiring a dedicated control concept at the shop floor level. Yet in today's practice, conventional control approaches remain in use, which may not keep up with the dynamic behaviour due to their scenario-specific and rigid properties. To address this challenge, deep learning methods were increasingly deployed due to their optimization and scalability properties. However, these approaches were often tested in specific operational applications and focused on technical performance indicators such as order tardiness or total throughput. In this paper, we propose a deep reinforcement learning based production control to optimize combined techno-financial performance measures. Based on pre-defined manufacturing modules that are supplied and operated by multiple agents, positive effects were observed in terms of increased revenue and reduced penalties due to lower throughput times and fewer delayed products. The combined modular and multi-staged approach as well as the distributed decision-making further leverage scalability and transferability to other scenarios.
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.
CpG-oligonucleotides modulate sphingosine-1-phosphate metabolism in normal human keratinocytes
(2012)
This first volume of the DIGAREC Series holds the proceedings of the conference “The Philosophy of Computer Games”, held at the University of Potsdam from May 8-10, 2008. The contributions of the conference address three fields of computer game research that are philosophically relevant and, likewise, to which philosophical reflection is crucial. These are: ethics and politics, the action-space of games, and the magic circle. All three topics are interlinked and constitute the paradigmatic object of computer games: Whereas the first describes computer games on the outside, looking at the cultural effects of games as well as on moral practices acted out with them, the second describes computer games on the inside, i.e. how they are constituted as a medium. The latter finally discusses the way in which a border between these two realms, games and non-games, persists or is already transgressed in respect to a general performativity.
The game itself?
(2020)
In this paper, we reassess the notion and current state of ludohermeneutics in game studies, and propose a more solid foundation for how to conduct hermeneutic game analysis. We argue that there can be no ludo-hermeneutics as such, and that every game interpretation rests in a particular game ontology, whether implicit or explicit. The quality of this ontology, then, determines a vital aspect of the quality of the analysis.
The game itself?
(2020)
In this paper, we reassess the notion and current state of ludohermeneutics in game studies, and propose a more solid foundation for how to conduct hermeneutic game analysis. We argue that there can be no ludo-hermeneutics as such, and that every game interpretation rests in a particular game ontology, whether implicit or explicit. The quality of this ontology, then, determines a vital aspect of the quality of the analysis.
Proceedings of TripleA 10
(2024)
The TripleA workshop series was founded in 2014 by linguists from Potsdam and Tübingen with the aim of providing a platform for researchers that conduct theoretically-informed linguistic fieldwork on meaning. Its focus is particularly on languages that are under-represented in the current research landscape, including but not limited to languages of Africa, Asia, and Australia, hence TripleA.
For its 10th anniversary, TripleA returned to the University of Potsdam on the 7-9th of June 2023.
The programme included 21 talks dealing with no less than 22 different languages, including three invited talks given by Sihwei Chen (Academia Sinica), Jérémy Pasquereau (Laboratoire de Linguistique de Nantes, CNRS) and Agata Renans (Ruhr-Universität Bochum). Nine of these (invited or peer-reviewed) talks are featured in this volume.
Breaking down barriers
(2024)
Many researchers hesitate to provide full access to their datasets due to a lack of knowledge about research data management (RDM) tools and perceived fears, such as losing the value of one's own data. Existing tools and approaches often do not take into account these fears and missing knowledge. In this study, we examined how conversational agents (CAs) can provide a natural way of guidance through RDM processes and nudge researchers towards more data sharing. This work offers an online experiment in which researchers interacted with a CA on a self-developed RDM platform and a survey on participants’ data sharing behavior. Our findings indicate that the presence of a guiding and enlightening CA on an RDM platform has a constructive influence on both the intention to share data and the actual behavior of data sharing. Notably, individual factors do not appear to impede or hinder this effect.
Social media constitute an important arena for public debates and steady interchange of issues relevant to society. To boost their reputation, commercial organizations also engage in political, social, or environmental debates on social media. To engage in this type of digital activism, organizations increasingly utilize the social media profiles of executive employees and other brand ambassadors. However, the relationship between brand ambassadors’ digital activism and corporate reputation is only vaguely understood. The results of a qualitative inquiry suggest that digital activism via brand ambassadors can be risky (e.g., creating additional surface for firestorms, financial loss) and rewarding (e.g., emitting authenticity, employing ‘megaphones’ for industry change) at the same time. The paper informs both scholarship and practitioners about strategic trade-offs that need to be considered when employing brand ambassadors for digital activism.