Zeppelin Universität gemeinnützige GmbH

We investigated how mental contrasting, a self-regulation strategy, affects relationship problem-solving in 105 mixed-gender couples. Couples were assigned to a mental contrasting (juxtaposing the desired future with the main inner obstacle) or indulging (imagining only the desired future) condition. We reassessed problem resolution 2 weeks later. Actor-partner interdependence model analyses revealed that mental contrasting improved problem resolution over this period for problems perceived as important to resolve. Right after the intervention, we also recorded couples’ problem-solving behavior during a Zoom discussion among the partners. Men in the mental contrasting (vs. indulging) condition showed more self-disclosure, especially of feelings, attitudes, and behaviors. Women in the mental contrasting condition were more selective when suggesting solutions. Mental contrasting appears to foster problem-solving by enabling men to engage in self-disclosure, making women selective about solution suggestions, and enabling both women and men to effectively implement solutions, especially for high-importance problems.

Passenger railway transport plays a crucial role in reducing carbon emissions from car use, making its increased adoption essential for meeting climate goals. This study examines the factors influencing the adoption and utilisation of rail transport in Germany, utilising the technology acceptance model (TAM) as a theoretical framework. The adapted model confirms the relevance of TAM in service-oriented contexts, identifying perceived usefulness and perceived ease of use as key drivers of acceptance. A notable finding is the gap between intention and actual behaviour. While many participants expressed a willingness to use rail services, this intention often failed to translate into regular use. This highlights a major challenge in promoting sustainable mobility, as positive attitudes alone are insufficient to shift travel behaviour. The study provides valuable insights for rail service providers seeking to enhance usage and improve public perception. However, limitations must be acknowledged. The sample may not fully reflect the broader population, and a potential selection bias, such as a high proportion of car owners, may affect generalisability. Despite these issues, the study contributes to the literature on TAM in consumer services and underscores the need for further research into the factors influencing the gap between intention and action.

Abstract— This paper introduces an image-based crowd counting method within the Audiovisual Crowd framework, designed to detect and warn against mass crowd stampedes or trampling caused by dangerous overcrowding. The approach utilizes deep convolution neural networks (CNNs) to analyze both visual and audio data, extracting meaningful features to identify anomalies in crowd behavior. The model is trained using CNN architectures and evaluated with Mean Absolute Error (MAE) and Mean Squared Error (MSE) metrics to ensure precise crowd estimation. Experimental results show that while the video-only approach effectively captures spatial information, it is more susceptible to challenges such as low-light and noisy environments. In contrast, the combined audiovisual model achieves enhanced robustness and accuracy, reaching an overall accuracy of 94% in detecting critical crowd anomalies.

Across democratic systems, ideological cleavages increasingly emerge not only between but also within political parties. At the same time, hyperpartisan and digitally networked media ecosystems amplify polarization by fostering ideologically segmented information networks. To explain the interplay between internal party divisions and digital connectivity, we introduce a novel framework termed the “logic of connective faction.” We illustrate this framework via a case from the US, and the sudden circulation of the issue of “Critical Race Theory” (CRT), which became a far-right moniker for regressive education policies. Utilizing an original dataset comprising right-wing and mainstream news sources, newsletters, and social media posts by Republican Members of Congress (n = 1,941,742), we analyze ideological behavior and connectivity patterns, distinguishing Republicans who adopted the “CRT” issue from their co-partisans who did not. We find that the former group represents a distinct faction characterized by greater ideological extremity and deeper integration into right-wing digital networks. Beyond this combination of political behavior and digital connectivity, we highlight various networked media logics, such as platform-based engagement and media attention, which may incentivize such factional behaviors. Finally, we consider implications for political actors and media systems beyond the US.

ABSTRACT Background The role of virtual reality (VR) in education is increasing, which raises questions about VR learning in multi‐user settings. While collaborative VR learning, characterised by shared goals and low division of labour, is well‐researched, cooperative VR learning, which emphasises role differentiation and task interdependence, remains underexplored. This oversight is significant, as cooperation holds unique potential for education and inclusion by accommodating diverse learner abilities and perspectives. Objectives This paper explores diverse multi‐user learning approaches in VR Learning Applications (VRLAs), emphasising cooperation over collaboration. It provides an overview of multi‐user VRLAs, their user engagement types, target groups, subjects, availability, and educational theory integration. Distinguishing between cooperative, collaborative, and social engagement, it also identifies asymmetric cooperation in multi‐user experiences. Methods A systematic literature review was conducted using the PRISMA framework, identifying VRLAs in educational settings which feature multi‐user interactions. The review included 89 studies published since 2013, categorising VRLAs by interaction mode, symmetry, presence of a VR instructor, availability, and presence of didactic justification. Results and Conclusions Collaborative VR remains the dominant mode (44%), but cooperative VRLAs (37%) see growing adoption. Collaborative designs often rely on constructivist educational theory, while cooperative designs tend to leverage role specialisation to mirror real‐world practices, particularly in vocational training and task‐specific scenarios. However, 84% of VRLAs are inaccessible, limiting their broader application. Many studies lack robust didactic justifications, underscoring the need for clearer frameworks.

ABSTRACT Regional organizations have long addressed cross-border challenges like environmental degradation and terrorism. While much of the existing literature analyzes how democratic regional organizations support democracy among members and aspirants, a growing body of research examines how authoritarian counterparts reinforce autocratic rule. This article analyzes five regional organizations in the Middle East and post-Soviet regions—Arab League, Commonwealth of Independent States, Collective Security Treaty Organization, Gulf Cooperation Council, and Shanghai Cooperation Organization—to explore how they are platforms for authoritarian learning. By examining shared responses to the Arab Uprisings, Color Revolutions and Ukraine’s Euromaidan protests, we show how these organizations enable autocrats to exchange strategies, coordinate responses, and learn from one another’s experiences. We argue that such learning plays a key role in helping authoritarian regimes adapt to threats, refine repressive tactics, and ultimately improve their chances of survival. Our framework offers new insight into the transnational dimensions of authoritarian resilience.

<strong class="journal-contentHeaderColor">Abstract.</strong> While modern wind turbine blades utilize pultruded carbon fiber-reinforced polymer (CFRP) planks for structural integrity in spar caps, these materials can sustain damage from operational stresses, leading to potential failures if unaddressed. Traditional down-tower repairs result in significant costs related to dismantling and transportation, especially for offshore installations, emphasizing the need for efficient up-tower repair methods. The research utilizes a finite element model of an 81.6 m rotor blade designed for a 7 MW offshore turbine, subjected to aeroelastic simulations to evaluate load conditions during maintenance. The analysis focuses on a step-wise increased repair zone, assessing susceptibility to buckling, cyclic strains, and permissible wind speeds. Results indicate that while substantial repairs can endanger structural stability, turbulence-induced strain amplitudes are manageable. Recommendations include installing temporary pretensioning and buckling support structures to enhance safety during repairs. Various innovative support designs are proposed for installation from both inside and outside the blade, aimed at improving structural integrity during up-tower repairs.

This meta-analysis examines the antecedents of university entrepreneurial activity (UEA) and the design of university entrepreneurial ecosystem (UEE) elements. An extensive literature search identifies 115 quantitative studies covering UEA measures and antecedents at the university level. From these studies, relevant data is extracted (212,547 observations) and grouped into theory-based clusters. This synthesis of findings allows for the construction of a UEE framework based on these theories. The results vary in relevance and significance as antecedents of UEA and their implications for UEE. The analysis shows that knowledge, organizational R&D, and organizational size have the strongest impact on UEA. Knowledge and organizational R&D belong to the same UEE cluster, whereas organizational size is attributed to another dimension of the UEE.