bluuebunny/crossref_metadata_2025_split huggingface dataset:
Efficient in vitro germination of the endangered Sinai hawthorn (Crataegus sinaica)
Authors: Aly Hebatallah , Mahmoud Shrouk , El-Bakry Ahmed 
Published: February 2025

Abstract
Sinai hawthorn, Crataegus sinaica, is a rare wild tree species of economic importance with potential for medicinal uses. The in vivo seed germination of this tree species is extremely low. The present study aimed to develop an efficient in vitro seed germination that can contribute to the successful propagation, restoration, and preservation of this critically endangered species. The study examined factors that could enhance seed germination frequency (GP) and dormancy break of mature seeds. This included stratification temperature, cytokinin type and concentration, sinapic acid (SA) concentration, gibberellic acid (GA), and substituting nutrient media with water. Cold-stratified seeds for 4 weeks at 7 °C showed highest GP of 29.3%. GP of 36% was obtained on media containing 0.5 mg/L of each 6-Benzyladenine (BA) and meta-Topolin (mTp). Low concentrations of SA increased GP (50%) in both full and ½ Murashige and Skoog basal media with Gamborg B5 vitamins (MSB5). Sterile ddH2O supplemented with selected combined GA, SA, and mTp treatment showed a higher GP (46%) compared to the control. The study investigated the physiology of seed maturation during late growing season and after stratification and their correlation with germination efficiency. Stratification at 7 °C increased total soluble sugars, decreased abscisic acid (ABA) content, and increased GA. This study presents the first report on seed germination in Sinai hawthorn, highlighting the importance of environmental and physiological treatments for improved efficiency. It also offers a simple, inexpensive, method for in vitro seed germination with high efficiency that may be applied in propagation and restoration.
Public Archives and Data Protection
Authors: Friedewald Michael , Jaillant Lise , Kashumov Alexander , Palla Luisa , Szekely Ivan 
Published: February 2025

Zusammenfassung
Public archives play an important role in our society by identifying, assessing and preserving documentary
material of long-term value, ensuring accountability of government and other organizations. Privacy and
data protection are most important reasons to limit access to these archives. Many documents in public
archives contain sensitive information about individuals, making data protection a primary concern that
limits access to recent archive holdings. This creates a conflict between the need for transparency and
accountability and legal obligations to protect personal data. There are still uncertainties regarding
the practical implementation of the GDPR on the ground. In this article we explore the perspectives of
different interest groups and discuss how an appropriate balance of rights and interests can be realized.
Physics-Informed Neural Networks for Predicting Particle Properties in Plasma Spraying
Authors: Bobzin K. , Heinemann H. , Dokhanchi A. 
Published: February 2025

Abstract
Plasma spraying is a key industrial coating process that exhibits intricate nonlinear interactions among process parameters. This complexity makes accurate predictions of particle properties, which greatly affect process behavior, very challenging. Specifically, particle velocities and temperatures profoundly impact coating quality and process efficiency. Conventional methods often require empirical correlations and extensive parameter tuning due to their limited ability to capture the underlying physics within this intricate system. This study introduces physics-informed neural networks (PINNs) as a solution. By seamlessly integrating known physical laws and constraints directly into the model architecture, PINNs offer the potential to learn the underlying physics of the system. For comparison, artificial neural networks (ANNs) are also developed. Computational fluid dynamics simulations of a plasma generator and plasma jet model provide data to train both ANN and PINN models. The study reveals an improvement in particle velocity prediction through the proposed PINN model, demonstrating its capability to handle complex relationships. However, challenges arise in predicting particle temperature, warranting further investigation. The developed models can aid in optimizing the plasma spraying process by predicting essential particle properties and guiding necessary process adjustments to enhance coating quality.
Persistence in China’s household consumption level: implications for the new growth model
Authors: Claudio-Quiroga Gloria , Gil-Alana Luis Alberiko , Larrarte Andoni Maiza 
Published: February 2025

Abstract
In this paper, we investigate the statistical features of China’s household consumption level by calculating its degree of persistence and testing for the existence of trends in the data. Further, we contrast the results obtained in China with those corresponding to the G7 economies and in the other three countries that make up the fastest developing BRICs group, that is, Brazil, Russia and India. Our results show large degrees of heterogeneity depending on the country and the model used for the analysis though, in general, lower degrees of dependence and thus, more evidence of transitory shocks is observed in China and the rest of BRIC economies than in the G7 countries.
The Biosemiotic Glossary Project: Habit
Authors: Bernardi della Rosa Simone , Zengiaro Nicola 
Published: February 2025

Abstract
In 2014, Morten Tønnessen and the editors of Biosemiotics initiated the “Biosemiotic Glossary Project” with the scope to clarify the terminology used in biosemiotics. This initiative was designed to actively involve the biosemiotic community, fostering dialogue that would contribute to the theoretical evolution of the field. In this paper, we explore how the term “habit” is defined and applied within biosemiotics, and how it relates to general semiotics and philosophy. In biosemiotics, “habit” refers to the regular, recurring behaviors or patterns that emerge from an organism’s interactions with its environment. This concept, deeply rooted in Charles Sanders Peirce’s philosophy, is understood as an adaptive mechanism where repeated actions lead to the stabilization of organisms or systems. Over time, these repeated actions form patterns that guide future behaviors. Peirce extended this concept beyond organisms, suggesting that habits also structure biological and non-biological phenomena by turning random events into predictable regularities. In biosemiotic theory, habits play a central role in semiosis, the process by which living systems generate and interpret meaning, as they regulate interactions and responses in both evolutionary and adaptive contexts. This notion bridges biological development and semiotic processes, offering a deeper understanding of how organisms establish semiotic relationships with their environments. This paper aims to clarify the role of ‘habit’ in biosemiotic discourse and encourage further discussion within the community to refine its use and implications.
Data management as a joint value proposition—A design theory for horizontal data sharing communities
Authors: Lefebvre Hippolyte , Krasikov Pavel , Legner Christine , Flourac Gabin 
Published: February 2025

Abstract
In the data economy, organizations are increasingly engaging in data ecosystems, managing and sharing data as valuable assets to address business and societal challenges. Whereas organizations have traditionally exchanged data vertically along the value chain, we observe a growing trend where they share complementary data assets with others, even at times with their competitors. Despite the rising significance of data ecosystems, research on this emerging form of horizontal data sharing is still scarce. Building on the theory of communities of practice, we study a pioneer data sharing community involving over 40 multinational companies that developed an innovative approach to pool data management efforts. We derive a design theory for horizontal data sharing, structured around eight design principles that align with key dimensions grounded in theory: domain of interest, shared practice, and community. By offering prescriptive design knowledge, our findings make an important contribution to the emerging literature on cross-company data sharing. Our research also provides practitioners with actionable insights on how to establish and operate data sharing communities effectively.
Abnormal Driving Behavior Detection: A Machine and Deep Learning Based Hybrid Model
Authors: Uddin Md. Ashraf , Hossain Nibir , Ahamed Asif , Islam Md Manowarul , Khraisat Ansam , Alazab Ammar , Ahamed Md. Khabir Uddin , Talukder Md. Alamin 
Published: February 2025

Abstract
Car accidents remain a leading cause of unintentional fatalities, with many incidents stemming from driver behaviors that impact vehicle control, such as steering, braking, accelerating, and gear shifting. Activities like searching for items, using mobile devices, or listening to the radio can distract drivers visually, audibly, and physically, posing significant risks to road safety. While various methods have been developed to detect such distractions, their effectiveness often falls short in real-world applications. This paper introduces a novel approach that combines machine learning (ML) and deep learning (DL) techniques to identify both safe and risky driving behaviors. Six ML classifiers were evaluated on real-world data to distinguish between driving behaviors such as aggressive, fatigued, and normal driving, with the Random Forest classifier demonstrating superior performance. Additionally, a specialized deep-learning baseline model was developed using ResNet50 and EfficientNetB6 to classify driving-related images into distinct categories. The hybrid model integrates ML for analyzing tabular data and DL for image recognition, achieving a classification accuracy of 99.3% on the UAH-Drive dataset. Deep learning experiments further revealed that the Base Model outperformed other models, achieving accuracies of 99.32% on the UAH-Drive dataset and 99.87% on the SFD3 dataset. This research presents a robust hybrid ML-DL framework for detecting abnormal driving behaviors, addressing shortcomings of existing techniques in real-world conditions, and offering valuable insights for improving road safety and reducing accidents.
Farmer perceptions of the vulnerabilities of traditional livestock farming systems under global change
Authors: Morales‐Reyes Zebensui , Barbosa Jomar M. , Sánchez‐Zapata José A. , Pérez-Ibarra Irene 
Published: February 2025

Abstract
The continuity of traditional extensive livestock farming is being challenged by rapid socioeconomic and environmental changes, threatening livelihoods and ecosystem services critical to food security and sustainability. We conducted a large-scale assessment involving 255 livestock farmers across six extensive livestock farming systems in Spain to understand their perceptions of vulnerabilities. Using the Coupled Infrastructure Systems framework, we identified 24 different vulnerabilities, mainly caused by external socioeconomic and biophysical disturbances, such as resource costs, low profitability of livestock products, climate variability, and conflicts with wildlife. The main factors explaining these vulnerabilities were primary productivity, farm location, presence of large predators, and climatic conditions. The findings highlight the complex interplay of these factors and provide important insights for the maintenance of extensive livestock farming systems in Europe. This information is crucial for informing policy decisions aimed at supporting these farming systems and ensuring their contribution to food security, sustainability and biodiversity conservation.
Analysis of histological features and recurrence risk assessment of papillary thyroid carcinoma according to presurgery FNAC category
Authors: Wolde Sellasie Sium , Amendola Stefano , Guidobaldi Leo , Piticchio Tommaso , Nardone Isabella , Zaccaria Simona , Tacchi Giovanni , Pedicini Francesco , Uccioli Luigi , Trimboli Pierpaolo 
Published: February 2025

Abstract
Identifying preoperatively cases of more indolent papillary thyroid carcinoma (PTC)could be of high interest. The aim of this study was to verify previously published data on the prognostic value of fine needle aspiration cytology (FNAC)in PTC, also comparing findings from high-volume (HV)and low-volume (LV)institutions. From January 2022 to June 2024, the institutional database of the endocrinological surgery unit of Sant’Eugenio Hospital (Rome, Italy)was retrospectively reviewed to select patients who underwent thyroid surgery for PTC. To evaluate the prognostic value of presurgical FNAC, all histological features and the ATA risk of the study groups were compared. Later, data of patients entirely managed at our institution, considered as an HV institute, were compared with that of cases operated at our institution following FNAC performed LV centres.The 159 PTC nodules included were classified as TIR3B (20.1%),TIR4 (32.7%),and TIR5 (47.2%).The distribution of FNAC report between HV and LV was different (p = 0.01). The presence of lymph node metastasis (p = 0.004), and peri-thyroid tissue invasion (p = 0.02)increased according to the FNAC category. Significant difference among the three FNAC categories was also observed in PTC subtype (p = 0.006)and Hashimoto’s thyroiditis (p = 0.02).In addition, a significant different trend was found in ATA risk assessment, being the risk of recurrence more prevalent according to the FNAC category (p = 0.008). According to the second study aim, the higher prevalence of low-risk cases in TIR3B was confirmed in both HV (p = 0.04) and LV (p = 0.03)subgroups.PTCs with preoperative TIR3B have different histological features and ATA risk assessment with respect to cases with presurgical FNAC of TIR4/5.Particularly, PTC from TIR3B should have a pattern of more indolent cancers. As non-negligible extension, this data is not influenced by the institutional setting with high or low thyroid-FNAC volume.
Pre-clinical Medical Student Generated Formative Questions Can Inform the Topics Covered in Faculty Review Sessions Prior to Summative Assessments
Authors: Karom Jarod , Stanforth Corinne , Banks Laura M. , Hirsch Jason L. , Paul Samuel N. , Bazan Jose A. , Pfeil Sheryl , Pierson Christopher R. 
Published: February 2025

Abstract
Review sessions are challenging for preclinical medical school faculty to prepare due to year-to-year variability of the strengths and weaknesses of different classes. To optimize review session planning, we piloted a novel, co-creation-based workflow within a student-faculty partnership which was well received by faculty in terms of feasibility and utility.
Organizational-performance pay and compensation dispersion
Authors: Bao Jiayi , Wu Andy , Zhang Miaomiao 
Published: February 2025

Abstract
To drive organizational performance, managers design compensation packages to incentivize the collective contribution of individuals across the organization. Different pay components across individuals may prompt individual concerns based on their views of fairness: those with equity concerns believe that compensation should reflect individual contributions and thus support differences in pay (dispersion), while those with equality concerns believe that similar compensation would be fairer, thus supporting uniform pay (compression). We document the performance implications of compensation dispersion under organizational-performance pay; in increasingly prevalent compensation forms such as stock options or pooled bonuses, individual compensation consists of a pre-designated share of rewards contingent on organizational performance. We argue that prevailing equality concerns under organizational-performance pay generate opposing and asymmetric responses to dispersion from individuals with high vs. low shares of the rewards, leading to lower overall organizational performance under unequal, heterogeneous share dispersion (vs. equal, homogeneous share compression). Evidence from a controlled experiment with online workers and a supplementary field study of professional eSports athletes validates our predictions. Manipulation of two boundary conditions in the experiment further supports the proposed mechanism, as the observed effects are more pronounced when equality concerns are stronger: (1) when the payment scheme involves reward sharing (vs. not) and (2) when the rewards are presented in a percentage framing (vs. a point framing) that facilitates a stronger perception of reward-sharing.
Energy-Conserving Hermite Methods for Maxwell’s Equations
Authors: Appelö Daniel , Hagstrom Thomas , Law Yann-Meing 
Published: February 2025

Abstract
Energy-conserving Hermite methods for solving Maxwell’s equations in dielectric and dispersive media are described and analyzed. In three space dimensions, methods of order 2m to

$$2m+2$$

2
m
+
2

require

$$(m+1)^3$$

(
m
+
1
)

3

degrees-of-freedom per node for each field variable and can be explicitly marched in time with steps independent of m. We prove the stability for time steps limited only by domain-of-dependence requirements along with error estimates in a special semi-norm associated with the interpolation process. Numerical experiments are presented which demonstrate that Hermite methods of very high order enable the efficient simulation of the electromagnetic wave propagation over thousands of wavelengths.
Optimisation of Passive Energy Renovation Strategies in Residential Buildings for Life Cycle Global Warming Potential Reduction and Cost-effectiveness
Authors: Arbulu Markel , Oregi Xabat , Etxepare Lauren 
Published: February 2025

Abstract
The European Union (EU) regulations claim an efficient evaluation of the building renovation processes, highlighting the quantification of the life cycle carbon and cost-efficiency, towards the carbon-neutrality targets. The integration of the life cycle thinking (LCT) in the environmental field – by the life cycle assessment (LCA) – and in the economic field – by the life cycle cost (LCC) – are the most promising methodologies for the required evaluation. Based on this, the study aims to optimise passive energy renovation strategies in residential buildings to achieve efficient life cycle carbon reduction and optimal global warming potential (GWP) and cost-efficiency. For this, the research employs the “PARARENOVATE-LCT” tool as a new approach for the parametric enviro-economic evaluation of energy renovation strategies in residential buildings with LCT. As a working methodology, firstly, we define the evaluation scope, case study and life cycle inventory (LCI); secondly, we evaluate each of the 245 scenarios composed by all the combinations of different types of intervention in façade, roof and windows; and thirdly, we conduct the multi-objective optimisation in terms of optimal life cycle GWP reduction and cost-efficiency. The multi-objective optimisation performed by the Pareto method identifies 17 optimal strategies. The results show that the maximum GWP reduction strategies do not coincide with the maximum cost-effectiveness strategies. Therefore, more than half of the GWP can be reduced by some strategy, but with medium cost-effectiveness; however, the strategies with the highest cost-effectiveness reduce around one-third of the climate impact.

Graphical Abstract
The Brussels and California Effects? Circular Economy Policy Influence Across Borders
Authors: Bocken Nancy , Coffay Matthew , Dalhammar Carl 
Published: February 2025

Abstract
The influence of environmental policy has been known to move beyond the country or regional contexts in which they have been implemented. Examples in literature include the “California effect” and the “Brussels effect”, showing how the policies adopted in the EU and California influence other jurisdictions. In this paper we study the following: To what extent are companies operating in the United States influenced by circular economy policies outside their direct context? By interviewing companies operating in the United States, we find that firms are influenced by and actively work to influence circular economy policy, both as it originates from outside the United States (the Brussels effect, referring to policies in Europe) and from within the United States (such as the California effect). Key barriers to circular innovation include the lack of a comprehensive policy framework in the U.S., opposition from competitors, and making the business model work in the U.S. legal context. Strategies to overcome these include: getting legal support for circular business models, developing U.S. regulations, level the playing field for all U.S.-based companies, lobbying for supporting regulation, and collaboration. We find that EV battery recycling is a positive exception where U.S. policy provides clarity for circular innovation. Finally, we find that the characteristics of the ‘typical’ U.S. consumer may call for specific circular business models. We suggest future research to enhance our understanding on how policy might positively drive circular economy innovations in international companies.
Barriers and Opportunities when Transitioning from Linear to Circular Business Models: Evidence from the Construction and Manufacturing Sectors in The Netherlands
Authors: Ho Henry Wai Leong , Haaker Timber , Yishake Maerhaba 
Published: February 2025

Abstract
The shift from linear to circular business models is critical for sustainability in the construction and manufacturing sectors in the Netherlands. However, many companies face significant challenges in making this transition, including financial constraints, cultural resistance, and regulatory hurdles, which hinder the effective implementation of circular practices. This study employs a qualitative approach, conducting ten in-depth interviews with senior managers holding diverse positions and responsibilities from ten medium-sized enterprises. Using the purposive nonprobability sampling technique this research explores the drivers for transitioning, the barriers encountered, and the strategies used to overcome these challenges. The findings reveal that regulatory pressures, internal environmental advocacy, and market demands for sustainable solutions are key drivers of circular business practices. Barriers identified include limited budgets, high marketing costs, organisational resistance to change, and regulatory complexities. Nevertheless, companies identified various opportunities based on the interview result, such as market differentiation, enhanced sustainability, and strategic partnerships. Companies also noted improvements in brand reputation and customer loyalty as direct benefits of embracing circular practices. This research provides valuable insights into the drivers, barriers, and opportunities in adopting circular business models within the construction and manufacturing sectors in the Netherlands. The findings emphasize the importance of stakeholder engagement, continuous education, and the need for financial and policy support to overcome barriers and leverage opportunities for sustainable business growth. Lastly, this research provides recommendations for future studies including expanding the scope to different industries and regions, adopting mixed-methods approaches, and exploring the impact of specific policies and financial mechanisms on circular business model adoption.