bluuebunny/crossref_metadata_2025_split huggingface dataset:
Aufwind für Agroforstsysteme? Aktuelle Entwicklungen, Chancen und Hemmnisse
im europäischen und deutschen Recht*
Authors: Klimke Marina , Zengerling Cathrin 
Published: February 2025

Zusammenfassung
Agroforstsysteme gelten als eine nachhaltige Landnutzungsoption und sollen vermehrt (wieder) etabliert
werden. Trotz neuer förderrechtlicher Impulse hindert der aktuelle Rechtsrahmen den Ausbau von Agroforstsystemen.
Der Beitrag nimmt die jüngsten Änderungen im Agrarförderrecht zum Anlass für eine detaillierte
Bestandsaufnahme des komplexen Rechtsrahmens für Agroforstsysteme von der europäischen bis zur
Landesebene. Ziel des Beitrags ist es, eine Grundlage für die an den rechtlich und politisch verankerten
Zielen einer nachhaltigen Landnutzung ausgerichtete Weiterentwicklung des Rechtsrahmens zu schaffen.
The link between objective measures and subjective perceptions of extreme weather
Authors: Quoß Franziska 
Published: February 2025

Abstract
One potential driver of support for stricter climate policies is a shift in the political preferences of average citizens as they experience more frequent and severe extreme weather due to the accelerating impacts of climate change. However, research to date on the impact of personal experience of extreme weather on (political) attitudes has yielded mixed results. In this study, I argue that one reason for this inconclusiveness is that what average citizens perceive as “extreme weather” is not yet well understood. Combining individual-level Swiss survey data on subjective perceptions of extreme weather with fine-grained objective weather data, I show that, overall, there is only a very weak link between objective measures and subjective perceptions of extreme weather in Switzerland. This finding demonstrates that what laypeople perceive as extreme weather is not yet fully understood.
Digital Transformation as a Catalyst for Resilience in Stock Price Crisis: Evidence from A ‘New Quality Productivity’ Perspective
Authors: Chen Shunru , Alexiou Constantinos 
Published: February 2025

Abstract
This study explores the impact of digital transformation on stock price crash risk using Chinese A-share listed enterprises from 2011 to 2022. Leveraging the TF-IDF algorithm and deep learning models, it contextualizes digital transformation within China's “new quality productivity” framework, which prioritizes technological innovation over traditional productivity drivers. The findings reveal that digital transformation significantly reduces stock price crash risk, particularly in labor and capital-intensive sectors, by enhancing market transparency and decreasing information asymmetry. Furthermore, the integration of digital transformation with the “new quality productivity” framework amplifies this protective effect, with pronounced benefits for large firms and those covered by analysts or research reports. Conversely, smaller firms or those without such coverage experience a smaller impact. By demonstrating how advanced digital technologies bolster operational agility and investor confidence, this study highlights the critical role of digital transformation in fostering resilience and stabilizing stock prices during crises.
The SARAH trial: more evidence on the role of neurohormonal blockers in prevention of anthracycline-induced cardiotoxicity
Authors: Mecinaj Albulena , Vinje-Jakobsen Victoria , Ngo Doan T. M. , Sverdlov Aaron L. , Myhre Peder L. 
Published: February 2025

Abstract
This mini-review highlights the results of the SARAH trial, which evaluated the efficacy of sacubitril/valsartan in preventing subclinical cardiac dysfunction in patients undergoing anthracycline-based chemotherapy. The trial demonstrated a significant reduction in GLS decline in the treatment group compared to placebo. The findings are discussed in context with other trials investigating neurohormonal blockade for the prevention of cancer therapy-related cardiac dysfunction.
The reel deal? An experimental analysis of perception bias and AI film pitches
Authors: Crosby Paul , McKenzie Jordi 
Published: February 2025

Abstract
Artificial intelligence (AI) is creating significant disruption in many creative industries, including the film industry. With increase in levels of investment in sophisticated AI technologies, film studios can potentially replace, or at least reduce, traditional roles of film professionals. Not surprisingly, such moves have been met with vocal opposition from industry associations and labor unions. In the discourse of such debate, however, limited attention has been given to consumer acceptance of AI in filmmaking. This study provides the first evidence concerning potential perception biases in the context of AI film development, related to film ‘pitches.’ Using a randomized experiment of 500 participants, we find no discernible bias related to AI-generated synopses, inclusive of AI-generated director and casting decisions. Our results suggest that consumers may be accepting of, at least, limited involvement of AI in film development.
A Stitch in Time Saves Nine: Predicting Internet Addiction Levels of Preservice Teachers
Authors: Şan İsmail , Karsak H. Gülhan Orhan , Bonk Curtis J. , Karadeniz Derya 
Published: February 2025

Abstract
The present study aimed to explore the potential moderating effects of extracurricular study habits, internet usage duration, gender and emotion regulation skills on internet addiction of preservice teachers. The sample consisted of 492 preservice teachers (308 female) from 10 different institutions in Turkey, who voluntarily provided data. The findings revealed that emotion regulation skills, particularly reappraisal, interacted with daily internet usage time in predicting internet addiction. High levels of reappraisal emotion regulation were linked to lower levels of internet addiction, regardless of the duration of internet use. Conversely, for individuals with lower reappraisal abilities, a positive correlation emerged between internet usage time and internet addiction. Furthermore, extracurricular study habits significantly contributed to the prediction of internet addiction in a positive way, as evidenced by both regression and correlational analyses. These findings underscore the importance of considering emotion regulation alongside study habits and other physiological factors to better understand and address internet addiction in preservice teachers. The implications of the findings for educational policy and teacher education are discussed.
A new root–soil interface contact model to simulate the overturning behaviour of root system architectures
Authors: Zhu Jun , Leung Anthony Kwan , Knappett Jonathan Adam , Zhang Xingyu , Wang Yu 
Published: February 2025

Abstract
Correctly assessing overturning resistance of tree root systems is vital to designing sustainable and resilient urban forestry. In previous numerical modelling to investigate root anchorage behaviour, none of the root–soil contact models employed was able to capture slipping at the root–soil interface of complex root system architectures efficiently. This study proposed, derived and implemented a novel, computationally efficient, three-dimensional root–soil contact model that can capture interfacial strain-softening shearing behaviour for an arbitrary root system architecture independent from the spatial discretisation of the surrounding soil within a 3D finite-element model. Validation against existing pull-out test and centrifuge data revealed that the model well captured root pull-out and tree overturning behaviours. The validated model was subsequently used to investigate the transfer mechanisms of artificially generated root system architectures when growing with and without the presence of underground walls. Windward root segments that were more closely aligned with the lateral push provided the most contribution to resisting overturning. The presence of underground walls made the root system architecture highly asymmetric, forming a taproot complex that ‘interlocked’ the surrounding soil to provide overturning resistance. The walls also restricted the relative root–soil displacement, reducing the variability in the overturning moment.
From Programming to Prompting: Developing Computational Thinking through Large Language Model-Based Generative Artificial Intelligence
Authors: Hsu Hsiao-Ping 
Published: February 2025

Abstract
The advancement of large language model-based generative artificial intelligence (LLM-based GenAI) has sparked significant interest in its potential to address challenges in computational thinking (CT) education. CT, a critical problem-solving approach in the digital age, encompasses elements such as abstraction, iteration, and generalisation. However, its abstract nature often poses barriers to meaningful teaching and learning. This paper proposes a constructionist prompting framework that leverages LLM-based GenAI to foster CT development through natural language programming and prompt engineering. By engaging learners in crafting and refining prompts, the framework aligns CT elements with five prompting principles, enabling learners to apply and develop CT in contextual and organic ways. A three-phase workshop is proposed to integrate the framework into teacher education, equipping future teachers to support learners in developing CT through interactions with LLM-based GenAI. The paper concludes by exploring the framework’s theoretical, practical, and social implications, advocating for its implementation and validation.
Age-Associated B Cells in Autoimmune Diseases: Pathogenesis and Clinical Implications
Authors: Xie Guangyang , Chen Xiaojing , Gao Yixia , Yang Ming , Zhou Suqing , Lu Liwei , Wu Haijing , Lu Qianjin 
Published: February 2025

Abstract
As a heterogeneous B cell subset, age-associated B cells (ABCs) exhibit distinct transcription profiles, extrafollicular differentiation processes, and multiple functions in autoimmunity. TLR7 and TLR9 signals, along with IFN-γ and IL-21 stimulation, are both essential for ABC differentiation, which is also regulated by chemokine receptors including CXCR3 and CCR2 and integrins including CD11b and CD11c. Given their functions in antigen uptake and presentation, autoantibody and proinflammatory cytokine secretion, and T helper cell activation, ABCs display potential in the prognosis, diagnosis, and therapy for autoimmune diseases, including systemic lupus erythematosus, rheumatoid arthritis, Sjögren’s syndrome, multiple sclerosis, neuromyelitis optica spectrum disorders, and ankylosing spondylitis. Specifically targeting ABCs by inhibiting T-bet and CD11c and activating CD11b and ARA2 represents potential therapeutic strategies for SLE and RA. Although single-cell sequencing technologies have recently revealed the heterogeneous characteristics of ABCs, further investigations to explore and validate ABC-target therapies are still warranted.
Diverging Ethnic Hierarchies? Cultural Distance, Right-Wing Authoritarianism, and Social Distance Perceptions in the Netherlands
Authors: Soiné Hannah , Lancee Bram 
Published: February 2025

Abstract
The existence of hierarchies of ethnic preferences in society is well-documented. However, there is little research about how such ethnic hierarchies can be explained. Improving upon previous studies, we investigated whether individuals’ cultural distance toward ethnic outgroups and their level of right-wing authoritarianism (RWA) contribute to differences in their perception of social distance toward these groups. Our study is based on a survey in the Netherlands (N = 1249) and provides robust evidence for an ethnic hierarchy in the majority group’s perception of social distance toward 36 ethnic groups. However, this hierarchy is not universal. For more right-wing authoritarian individuals, the ethnic hierarchy is particularly steep, meaning they discriminate more between outgroups. By contrast, less right-wing authoritarian individuals differentiate little between outgroups. Furthermore, the relationship between RWA and social distance is moderated by cultural distance. We interpret this finding with symbolic threat theory, according to which greater cultural distance “activates” authoritarian attitudes, which affect the perception of social distance to varying degrees. Our results contribute to understanding the ethnic hierarchy in social distance perceptions by showing that it is determined by characteristics of the perceiving individual (RWA) and of the perceived group (cultural distance) as well as by their interaction.
Laser beam welding of copper under vacuum to extend the process limits
Authors: Schleser Markus , Liebe Philipp , Gerhards Benjamin , Gerhards Benedikt 
Published: February 2025

Abstract
This study explores challenges and innovations in laser beam welding of copper, focusing on infrared lasers, beam shaping and laser welding under vacuum (LaVa). Using a Trumpf TruFiber 2000 P and a Trumpf TruDisc 6000 with BrightLine technology, the research examines copper welding under reduced ambient pressure to improve process stability and seam quality. Single-mode welding shows improved stability with reduced melt ejection and minimal to no porosity. High-speed camera observations show unique behaviour for the analysed parameters, such as a smaller molten pool (2.4 to 4.0 times smaller) and capillary expansion (1.7 to 2.7 times larger) under vacuum conditions. BrightLine technology similarly shows a smaller molten pool (2.0 to 3.3 times smaller) and increased stability. While single-mode welding does not significantly increase penetration depth, multimode welding achieves greater penetration depth (up to 34%) at lower welding velocities (50 mm/s) under vacuum. Comparisons between atmospheric and vacuum welding highlight the benefits of the latter, emphasising uniformity and minimal melt ejection. Process stability correlates with weld quality, demonstrating the benefits of vacuum conditions. The combination of vacuum and established welding techniques extends process boundaries, achieving higher stability and seam quality with both types of lasers. The results indicate that vacuum conditions combined with proven welding approaches enhance copper laser welding. The potential for greater stability and improved weld quality under vacuum, particularly in single-mode welding, enables lower welding velocities down to 8.3 mm/s. Lower velocities, associated with higher energy per unit length, enable greater penetration depths.
Area Variations Under Legendrian Constraint
Authors: Rivière Tristan 
Published: February 2025

Abstract
In any 5-dimensional closed Sasakian manifold, we prove that any minmax operation on the area among Legendrian surfaces is achieved by a continuous conformal Legendrian map from a closed Riemann surface S into

$$N^5$$

N
5

equipped with an integer multiplicity bounded in

$$L^\infty $$

L
∞

. Moreover this map, equipped with this multiplicity, satisfies a weak version of the Hamiltonian Minimal Equation. We conjecture that any solution to this equation is a smooth branched Legendrian immersion away from isolated Schoen–Wolfson conical singularities with non-zero Maslov class.
The determinants of indigenous fruit value-added products packaging preferences among consumers in Bushbuckridge, Mpumalanga, South Africa
Authors: Mthombeni Danisile Leonah , Maluleke Mdungazi Knox 
Published: February 2025

Abstract
Packaging designs and materials have become increasingly important in the food sector because they assist consumers in recognising and understanding the benefits of a particular product. There seems to be scanty research on the suitable packaging materials for value-added products processed from indigenous fruits of Southern Africa. This study analysed the determinants of consumers' preferences regarding indigenous fruit product packaging (plastic containers, bottles, foam containers, and other packaging materials). The study was carried out in the Bushbuckridge Local Municipality, province of Mpumalanga, South Africa, in two malls and two retail complexes, namely: the Bushbuckridge Complex, Acornhoek Mall, Mkhuhlu Plaza, and Thulamahashe Mall. A purposive sampling technique was used to determine the sample size of each shopping mall. Furthermore, a random sampling technique was again used to sample 382 respondents within each shopping mall. A semi-structured questionnaire was used to collect data by interviewing 382 selected respondents. Statistical Package for Social Science (SPSS) version 29.0 was used to analyse data. Further analysis was carried out using descriptive statistics and a multinomial logistic model. The study findings revealed that 96.4% of respondents consumed indigenous fruits, with marula accounting for the most purchased and consumed indigenous fruit at (92.4%), when compared to other indigenous fruits. The multinomial logistic regression model analysis results revealed that market accessibility, colour of the packaging, consumers’ level of education, and shopping centres were significant determinants in the preferred choice of packaging, when comparing bottles and foam containers to plastic packaging. However, there were no significant factors impacting on consumers’ preferences for other packaging materials such as boxes, tins, papers, and cans, compared to plastic packaging. This implies that consumers had insignificant to no preference for other packaging materials used for the indigenous fruit in the study area. It is recommended that the indigenous fruit sellers and processors be informed by the findings of this study when choosing their packaging materials for indigenous fruit products.
Can ChatGPT Be Addictive? A Call to Examine the Shift from Support to Dependence in AI Conversational Large Language Models
Authors: Yankouskaya Ala , Liebherr Magnus , Ali Raian 
Published: February 2025

Abstract
The rapid rise of ChatGPT has introduced a transformative tool that enhances productivity, communication, and task automation across industries. However, concerns are emerging regarding the addictive potential of AI large language models. This paper explores how ChatGPT fosters dependency through key features such as personalised responses, emotional validation, and continuous engagement. By offering instant gratification and adaptive dialogue, ChatGPT may blur the line between AI and human interaction, creating pseudosocial bonds that can replace genuine human relationships. Additionally, its ability to streamline decision-making and boost productivity may lead to over-reliance, reducing users' critical thinking skills and contributing to compulsive usage patterns. These behavioural tendencies align with known features of addiction, such as increased tolerance and conflict with daily life priorities. This viewpoint paper highlights the need for further research into the psychological and social impacts of prolonged interaction with AI tools like ChatGPT.
Probabilistic voting models with varying speeds of Correlation decay
Authors: Toth Gabor 
Published: February 2025

AbstractWe model voting behaviour in the multi-group setting of a two-tier voting system using sequences of de Finetti measures. Our model is defined by using the de Finetti representation of a probability measure (i.e. as a mixture of conditionally independent probability measures) describing voting behaviour. The de Finetti measure describes the interaction between voters and possible outside influences on them. We assume that for each population size there is a (potentially) different de Finetti measure, and as the population grows, the sequence of de Finetti measures converges weakly to the Dirac measure at the origin, representing a tendency toward weakening social cohesion as the population grows large. The resulting model covers a wide variety of behaviours, ranging from independent voting in the limit under fast convergence, a critical convergence speed with its own pattern of behaviour, to a subcritical convergence speed which yields a model in line with empirical evidence of real-world voting data, contrary to previous probabilistic models used in the study of voting. These models can be used, e.g., to study the problem of optimal voting weights in two-tier voting systems.
Potential role of report nudging on diagnosis and treatment of ventilator-associated pneumonia: a quantitative survey
Authors: Claeys Kimberly C. , Kenaa Blaine , Tripathi Ravi K. , Rayner Kristen , Newman Michelle , Leekha Surbhi 
Published: February 2025

Abstract
Diagnosis of ventilator-associated pneumonia (VAP) is challenging and relies heavily on respiratory culture results. The results of this survey underscore the potential for a diagnostic stewardship nudge limiting culture reports to “potential colonization or contamination” in those without clinical findings of VAP to decrease unnecessary antibiotic prescribing.
Invisible data in night-time governance: addressing policy gaps and building a digital rights framework for cities after dark
Authors: Reia Jess 
Published: February 2025

Abstract
As data becomes a key component of urban governance, the night-time economy is still barely visible in datasets or in policies to improve urban life. In the last 20 years, over 50 cities worldwide appointed night mayors and governance mechanisms to tackle conflicts, foster innovation, and help the night-time economy sector grow. However, the intersection of data, digital rights, and 24-hour cities still needs more studies, examples, and policies. Here, the key argument is that the increasing importance of the urban night in academia and local governments claims for much-needed responsible data practices to support and protect nightlife ecosystems. By understanding these ecosystems and addressing data invisibilities, it is possible to develop a robust framework anchored in safeguarding human rights in the digital space and create comprehensive policies to help such ecosystems thrive. Night-time governance matters for the data policy community for three reasons. First, it brings together issues covered in different disciplines by various stakeholders. We need to build bridges between sectors to avoid siloed views of urban data governance. Second, thinking about data in cities also means considering the social, economic, and cultural impact of datafication and artificial intelligence on a 24-hour cycle. Creating a digital rights framework for the night means putting into practice principles of justice, ethics, and responsibility. Third, as Night Studies is an emerging field of research, policy and advocacy, there is an opportunity to help shape how, why, and when data about the night is collected and made available to society.
The REDATAM format and its challenges for data access and information creation in public policy
Authors: Vargas Sepúlveda Mauricio , Barkai Lital 
Published: February 2025

Abstract
The REDATAM (retrieval of data for small areas by microcomputer) statistical package and format, developed by ECLAC, has been a critical tool for disseminating census data across Latin America since the 1990s. However, significant limitations persist, including its proprietary nature, lack of documentation, and restricted flexibility for advanced data analysis. These challenges hinder the transformation of raw census data into actionable information for policymakers, researchers, and advocacy groups. To address these issues, we developed Open REDATAM, an open-source and multiplatform tool that converts REDATAM data into widely supported CSV files and native R and Python data structures. By providing integration with R and Python, Open REDATAM empowers users to work with the tools they already know and perform data analyses without leaving their R or Python window. Our work emphasizes the need for a REDATAM official format specification to further enable informed policy debates that can improve policy processes’ implementation and feedback.