bluuebunny/crossref_metadata_2025_split huggingface dataset:
Electronic Money Tokens Under the MiCA Regulation
Authors: Madrid Parra Agustín 
Published: January 2025

AbstractThis paper examines the legal regime applicable to electronic money represented by digital tokens, drawing from the general regime for electronic money established by Directive 2009/110/EC of the European Parliament and of the Council of 16 September 2009 on the taking up, pursuit and prudential supervision of the business of electronic money institutions, and the specific regime established by Regulation (EU) 2023/1114 of the European Parliament and of the Council of 31 May 2011 on markets in crypto-assets, and amending Regulations (EU) No. 1093/2010 and (EU) No. 1095/2010 and Directives 2013/36/EU and (EU) 2019/1937 (MiCA Act). Particular attention is paid to the differentiating or specific elements derived from the crypto-asset status of tokens representing electronic money. It is concluded that this type of electronic money, designed as a payment instrument, can also be negotiated and used as an investment instrument. It, therefore, has an ambivalent or hybrid nature as a crypto-asset and an exchange instrument.
Patient- and clinician-based evaluation of large language models for patient education in prostate cancer radiotherapy
Authors: Trapp Christian , Schmidt-Hegemann Nina , Keilholz Michael , Brose Sarah Frederike , Marschner Sebastian N. , Schönecker Stephan , Maier Sebastian H. , Dehelean Diana-Coralia , Rottler Maya , Konnerth Dinah , Belka Claus , Corradini Stefanie , Rogowski Paul 
Published: January 2025

Abstract

Background
This study aims to evaluate the capabilities and limitations of large language models (LLMs) for providing patient education for men undergoing radiotherapy for localized prostate cancer, incorporating assessments from both clinicians and patients.

Methods
Six questions about definitive radiotherapy for prostate cancer were designed based on common patient inquiries. These questions were presented to different LLMs [ChatGPT‑4, ChatGPT-4o (both OpenAI Inc., San Francisco, CA, USA), Gemini (Google LLC, Mountain View, CA, USA), Copilot (Microsoft Corp., Redmond, WA, USA), and Claude (Anthropic PBC, San Francisco, CA, USA)] via the respective web interfaces. Responses were evaluated for readability using the Flesch Reading Ease Index. Five radiation oncologists assessed the responses for relevance, correctness, and completeness using a five-point Likert scale. Additionally, 35 prostate cancer patients evaluated the responses from ChatGPT‑4 for comprehensibility, accuracy, relevance, trustworthiness, and overall informativeness.

Results
The Flesch Reading Ease Index indicated that the responses from all LLMs were relatively difficult to understand. All LLMs provided answers that clinicians found to be generally relevant and correct. The answers from ChatGPT‑4, ChatGPT-4o, and Claude AI were also found to be complete. However, we found significant differences between the performance of different LLMs regarding relevance and completeness. Some answers lacked detail or contained inaccuracies. Patients perceived the information as easy to understand and relevant, with most expressing confidence in the information and a willingness to use ChatGPT‑4 for future medical questions. ChatGPT-4’s responses helped patients feel better informed, despite the initially standardized information provided.

Conclusion
Overall, LLMs show promise as a tool for patient education in prostate cancer radiotherapy. While improvements are needed in terms of accuracy and readability, positive feedback from clinicians and patients suggests that LLMs can enhance patient understanding and engagement. Further research is essential to fully realize the potential of artificial intelligence in patient education.
Automated classification of coronary LEsions fRom coronary computed Tomography angiography scans with an updated deep learning model: ALERT study
Authors: Verpalen Victor A. , Coerkamp Casper F. , Henriques José P. S. , Isgum Ivana , Planken R. Nils 
Published: January 2025

Abstract

Objectives
The use of deep learning models for quantitative measurements on coronary computed tomography angiography (CCTA) may reduce inter-reader variability and increase efficiency in clinical reporting. This study aimed to investigate the diagnostic performance of a recently updated deep learning model (CorEx-2.0) for quantifying coronary stenosis, compared separately with two expert CCTA readers as references.

Methods
This single-center retrospective study included 50 patients that underwent CCTA to rule out obstructive coronary artery disease between 2017-2022. Two expert CCTA readers and CorEx-2.0 independently assessed all 150 vessels using Coronary Artery Disease-Reporting and Data System (CAD-RADS). Inter-reader agreement analysis and diagnostic performance of CorEx-2.0, compared with each expert reader as references, were evaluated using percent agreement, Cohen’s kappa for the binary CAD-RADS classification (CAD-RADS 0-3 versus 4-5) at patient level, and linearly weighted kappa for the 6-group CAD-RADS classification at vessel level.

Results
Overall, 50 patients and 150 vessels were evaluated. Inter-reader agreement using the binary classification at patient level was 91.8% (45/49) with a Cohen’s kappa of 0.80. For the 6-group classification at vessel level, inter-reader agreement was 67.6% (100/148) with a linearly weighted kappa of 0.77. CorEx-2.0 showed 100% sensitivity for detecting CAD-RADS ≥ 4 and kappa values of 0.86 versus both readers using the binary classification at patient level. For the 6-group classification at vessel level, CorEx-2.0 demonstrated weighted kappa values of 0.71 versus reader 1 and 0.73 versus reader 2.

Conclusion
CorEx-2.0 identified all patients with severe stenosis (CAD-RADS ≥ 4) compared with expert readers and approached expert reader performance at vessel level (weighted kappa > 0.70).

Key Points

Question

Can deep learning models improve objectivity in coronary stenosis grading and reporting as coronary CT angiography (CTA) workloads rise?

Findings

The deep learning model (CorEx-2.0) identified all patients with severe stenoses when compared with expert readers and approached expert reader performance at vessel level.

Clinical relevance

CorEx-2.0 is a reliable tool for identifying patients with severe stenoses (≥ 70%), underscoring the potential of using this deep learning model to prioritize coronary CTA reading by flagging patients at risk of severe obstructive coronary artery disease.
Record High Temperatures in the Ocean in 2024
Authors: Cheng Lijing , Abraham John , Trenberth Kevin E. , Reagan James , Zhang Huai-Min , Storto Andrea , Von Schuckmann Karina , Pan Yuying , Zhu Yujing , Mann Michael E. , Zhu Jiang , Wang Fan , Yu Fujiang , Locarnini Ricardo , Fasullo John , Huang Boyin , Graham Garrett , Yin Xungang , Gouretski Viktor , Zheng Fei , Li Yuanlong , Zhang Bin , Wan Liying , Chen Xingrong , Wang Dakui , Feng Licheng , Song Xiangzhou , Liu Yulong , Reseghetti Franco , Simoncelli Simona , Chen Gengxin , Zhang Rongwang , Mishonov Alexey , Tan Zhetao , Wei Wangxu , Yuan Huifeng , Li Guancheng , Ren Qiuping , Cao Lijuan , Lu Yayang , Du Juan , Lyu Kewei , Sulaiman Albertus , Mayer Michael , Wang Huizan , Ma Zhanhong , Bao Senliang , Yan Henqian , Liu Zenghong , Yang Chunxue , Liu Xu , Hausfather Zeke , Szekely Tanguy , Gues Flora 
Published: January 2025

AbstractHeating in the ocean has continued in 2024 in response to increased greenhouse gas concentrations in the atmosphere, despite the transition from an El Niño to neutral conditions. In 2024, both global sea surface temperature (SST) and upper 2000 m ocean heat content (OHC) reached unprecedented highs in the historical record. The 0–2000 m OHC in 2024 exceeded that of 2023 by 16 ± 8 ZJ (1 Zetta Joules = 1021 Joules, with a 95% confidence interval) (IAP/CAS data), which is confirmed by two other data products: 18 ± 7 ZJ (CIGAR-RT reanalysis data) and 40 ± 31 ZJ (Copernicus Marine data, updated to November 2024). The Indian Ocean, tropical Atlantic, Mediterranean Sea, North Atlantic, North Pacific, and Southern Ocean also experienced record-high OHC values in 2024. The global SST continued its record-high values from 2023 into the first half of 2024, and declined slightly in the second half of 2024, resulting in an annual mean of 0.61°C ± 0.02°C (IAP/CAS data) above the 1981–2010 baseline, slightly higher than the 2023 annual-mean value (by 0.07°C ± 0.02°C for IAP/CAS, 0.05°C ± 0.02°C for NOAA/NCEI, and 0.06°C ± 0.11°C for Copernicus Marine). The record-high values of 2024 SST and OHC continue to indicate unabated trends of global heating.
Burnout Syndrome in forensic medicine and its association with vicarious trauma, posttraumatic stress syndrome and occupational stress
Authors: Oprinca-Muja Lilioara-Alexandra , Mohor Cosmin-Ioan , Oprinca George-Călin , Cardoș Roxana , Domnariu Carmen-Daniela , Cristian Adrian-Nicolae , Băcilă Ciprian , Fleacă Sorin-Radu , Cristian Alina , Morar Silviu 
Published: January 2025

AbstractThe burnout phenomenon is a subject of considerable interest due to its impact on both employee well-being and scientific inquiry. Workplace factors, both intrinsic and extrinsic, play a pivotal role in its development, often leading to job dissatisfaction and heightened burnout risk. Chronic stress and burnout induce significant dysregulation in the autonomic nervous system and hormonal pathways, alongside structural brain changes. This paper presents a preliminary review of the literature on burnout syndrome among forensic science workers, focusing on the prevalence of this phenomenon and its triggers. This review aims to consolidate existing research on burnout among forensic medicine workers, highlight significant findings, and encourage further studies. Symptoms range from demoralization to somatic complaints. The Maslach Burnout Inventory (MBI) was the main tool in assessing burnout levels alongside measures of occupational stress, vicarious trauma and posttraumatic stress syndrome. Forensic medicine workers face unique stressors, with notable impacts on burnout levels. These workers experience challenges such as workplace conflicts and exposure to traumatic cases, leading to moderate or high burnout levels, particularly, emotional exhaustion, depersonalization or low personal accomplishment. Despite the prevalence of burnout, many forensic medicine workers lack access to support networks and perceive a disregard for their well-being from supervisors. There is a pressing need for further research to understand the biological mechanisms, susceptibility factors, and discover diagnostic markers of burnout syndrome, with the goal of its recognition as a psychiatric disorder in diagnostic manuals like the Diagnostic and Statistical Manual of Mental Disorders.
The MADS-box protein SHATTERPROOF 2 regulates TAA1 expression in the gynoecium valve margins
Authors: Verma Subodh , Švihlová Lenka , Robert Hélène S. 
Published: January 2025

Abstract

Key message
SHATTERPROOF 2 regulates TAA1 expression for the establishment of the gynoecium valve margins.

Abstract
Gynoecium development and patterning play a crucial role in determining the ultimate structure of the fruit and, thus, seed production. The MADS-box transcription factor SHATTERPROOF 2 (SHP2) contributes to valve margin differentiation and plays a major role in fruit dehiscence and seed dispersal. Despite the acknowledged contribution of auxin to gynoecium development, its precise role in valve margin establishment remains somewhat enigmatic. Our study addresses this gap by uncovering the role of SHP2 as a positive regulator of key auxin biosynthetic genes, TAA1 and YUCCA 4. Genetic and molecular analyses revealed that SHP2 directly regulates the expression of TAA1 in the valve margins of a stage 12 gynoecium with known regulators of flower and ovule development, such as AGAMOUS, SEEDSTICK, and SEPATALA 3. Collectively, our findings define a previously unrecognized function of SHP2 in the regulation of auxin biosynthetic genes during gynoecium development and raise the possibility that the auxin produced under SHP2 regulation may contribute significantly to the valve margin establishment.
Factors affecting pretransplant muscle strength in allogeneic stem cell transplant candidates prior transplantation
Authors: Limbach Matthias , Kuehl Rea , Koeppel Maximilian , Dreger Peter , Luft Thomas , Bohus Martin , Wiskemann Joachim 
Published: January 2025

Abstract

Purpose
Physical performance is crucial for prognosis after allogeneic hematopoietic stem cell transplantation (allo-HCT). Cardiorespiratory fitness has already been shown to have prognostic value, and there is increasing evidence that muscle strength and associated parameters (e.g., sarcopenia) are also of clinical relevance. Therefore, there is a need for the quantification of muscle strength and defining risk factors for reduced performance values.

Methods
Maximal voluntary isokinetic (MVIC) and isometric (MIPT) muscle strength was assessed 2.4 ± 7.1 days prior admission for allo-HCT with a stationary isokinetic testing machine (IsoMed2000). We calculated percentiles for knee extension and hip flexion using healthy reference values. Regression models were used to identify predictors for reduced muscle strength including gender, age, body mass index (BMI), number of previous cardiotoxic therapies, number of previous transplantations, comorbidity index (HCT-CI), hemoglobin level, and physical activity.

Results
Data of 212 patients (male n = 143, female n = 69), with a mean age of 54.49 ± 11.4, revealed considerably deviations from healthy reference values. Patients were located in the following percentiles: MVICKnee 37.5 ± 30.3, MVICHip 39.5 ± 31.3 and MIPTKnee 22.9 ± 26.5; MIPTHip 22.6 ± 27.4. Sub-group analyses showed that patients with younger age and male gender possess the highest deviations. Muscle strength values were significantly (p < 0.05) influenced by age, female gender, lower BMI, and higher HCT-CI.

Conclusion
Muscle strength is considerably reduced immediately prior to allo-HCT. Identified patient characteristics for reduced muscle strength point to the population that should be primarily targeted with exercise respectively resistance training interventions prior to allo-HCT to contribute to a well prepared transplant candidate.

Trial registration
NCT01374399.
Combining UAS-TIR and GEM-2 Techniques for Focused Water Sampling and Isotope Geochemical Analysis at Two Mine Sites in Northern Finland
Authors: Ikonen Juuso , Rauhala Anssi , Tuomela Anne , Postila Heini , Kumpula Timo , Korpelainen Pasi , Pietilä Raija , Valta Riku-Olli , Lerssi Jouni , Panttila Hannu , Korkka-Niemi Kirsti 
Published: January 2025

Abstract
A combination of thermal infrared (TIR) images captured by uncrewed aircraft systems (UASs) and manual geophysical measurements with a GEM-2 device were used to better plan a water sampling campaign at an abandoned Au-Cu mine and an active Ni-Cu-PGE mine in the sub-arctic boreal zone in northern Finland. Anomalies from the TIR images and GEM-2 conductivity values were used to focus the water sampling. The hydrogeochemistry and isotopic compositions of oxygen (δ18O), hydrogen (δ2H), strontium (87Sr/86Sr), and sulfur (δ34S) were analyzed to better understand the flow regime of possible effluent waters at these mine sites. The TIR images were useful in pinpointing sites where groundwater and surface water were potentially interacting. This was confirmed with the oxygen and hydrogen isotopic data. Isotopic values for the two groundwater solutes used here (Sr and S), reflected the local geology and the biogeochemical environment at the mine sites. The electrical conductivity values obtained from the GEM-2 measurements were influenced by the local geochemistry, particularly the presence of conductive sulfide-bearing paraschist rock. The anomalies from the UAS-TIR and GEM-2 data revealed sampling sites well suited for tracking potential effluent waters at the two mine sites.
A reference architecture for the development of GLSP-based web modeling tools
Authors: Metin Haydar , Bork Dominik 
Published: January 2025

AbstractWeb-based modeling tools provide unprecedented opportunities for the realization of modern, powerful, and usable diagram editors running in the cloud. The development of such tools, however, still poses significant challenges for developers. The graphical language server platform (GLSP) aims to reduce some of these challenges by providing the necessary frameworks to efficiently create web modeling tools. However, realizing modeling tools with GLSP remains challenging and not much support for interested tool developers is provided yet. This paper discusses these challenges and lessons learned after working with GLSP and realizing several GLSP-based modeling tools. We present experiences, concepts, and a reusable reference architecture to develop and operate GLSP-based web modeling tools. As a proof of concept, we report on the realization of a GLSP-based UML editor called bigUML. Through bigUML, we show that our procedure and the reference architecture we developed resulted in a scalable and flexible GLSP-based web modeling tool for the UML. The lessons learned, the procedural approach, the reference architecture, and the critical reflection on the challenges and opportunities of using GLSP provide valuable insights to the community and shall ease the decision of whether or not to use GLSP for future tool development projects. With this paper, we publicly release a reference implementation of our architecture.
Targeting BMP-1 enhances anti-tumoral effects of doxorubicin in metastatic mammary cancer: common and distinct features of TGF-β inhibition
Authors: Erin Nuray , Tavşan Esra , Haksever Seren , Yerlikaya Azmi , Riganti Chiara 
Published: January 2025

Abstract
Purpose
Mammary carcinoma is comprised heterogeneous groups of cells with different metastatic potential. 4T1 mammary carcinoma cells metastasized to heart (4THM), liver (4TLM) and brain (4TBM) and demonstrate cancer-stem cell phenotype. Using these cancer cells we found thatTGF-β is the top upstream regulator of metastatic process. In addition, secretion of bone morphogenetic protein 1 (BMP-1), which is crucial for the proteolytic release of TGF-β, was markedly high in metastatic mammary cancer cells compared to non-metastatic cells. Although TGF-β inhibitors are in clinical trials, systemic inhibition of TGF-β may produce heavy side effects. We here hypothesize that inhibition of BMP-1 proteolytic activity inhibits TGF-β activity and induces anti-tumoral effects.

Method and Results
Effects of specific BMP-1 inhibitor on liver and brain metastatic murine mammary cancer cells (4TLM and 4TBM), as well as on human mammary cancer MDA-MB-231 and MCF-7 cells, were examined and compared with the results of TGF-β inhibition. Inhibition of BMP-1 activity markedly suppressed proliferation of cancer cells and enhanced anti-tumoral effects of doxorubicin. Inhibition of BMP-1 activity but not of TGF-β activity decreased colony and spheroid formation. Differential effects of BMP-1 and TGF-β inhibitors on TGF-β secretion was also observed.

Conclusions
These results demonstrated for the first time that the inhibition of BMP-1 activity has therapeutic potential for treatment of metastatic mammary cancer and enhances the anti-tumoral effects of doxorubicin.
Norwegian Mathematics Teacher Educators’ and Research Mathematicians’ Views on Different Aspects of Mathematical Definitions: a Comparative Judgement Study
Authors: Torkildsen Hermund André , Forbregd Tore A. , Reid David A. , Kanwal Shaista 
Published: January 2025

AbstractIn this article we investigate the extent to which characteristics used to describe mathematical definitions in mathematics education research literature reflect what is important to research mathematicians and mathematics teacher educators. We report results from a comparative judgement survey of 57 research mathematicians and 62 mathematics teacher educators. Our results indicate that the two groups are mostly in agreement about the rankings, however, there are some differences. Research mathematicians rank most highly characteristics related to non-ambiguity and non-contradiction, while mathematics teacher educators rank characteristics related to comprehension and referential clarity as highly as characteristics related to non-ambiguity and non-contradiction. Neither group ranked minimality highly, even though this is the characteristic most often listed in the mathematics education research literature. Our study contributes towards a more consistent characterization of mathematical definitions in mathematics education research.
Principles of Service Provision for Young People with Complex Needs: Insights from the Australian Service System
Authors: Malvaso Catia , Klassman Kimberly , Delfabbro Paul , Moulds Lauren 
Published: January 2025

Abstract
The term “complex needs” has been used to describe young people who have a range of multiple and co-occurring problems that can be caused by individual level (e.g., psychosocial needs) and broader social-economic factors (e.g., homelessness, child maltreatment, justice system involvement). Coordinating the multiple services required to support these young people and successfully engaging them in services can be challenging. The purpose of this study was to gain deeper insight into the barriers to, and strategies for, service engagement among young people who require support from multiple services. Interviews and focus groups (N = 12) were conducted with relevant government and non-government stakeholders in an Australian jurisdiction to obtain qualitative insights into barriers and strategies for effective service engagement. Thematic analysis identified 20 principal themes that were differentiated into two overarching categories relating to service engagement: 1) Barriers, and 2) Strategies, and across three levels: 1) Systems; 2) Services; and 3) Individuals. Many of the strategies to facilitate engagement were applicable across all three levels. For example, ‘flexibility’ was identified as a facilitator of service engagement from the individual practitioner level to broader service and system structures. This study highlights barriers that need to be overcome, and strategies that can be employed, to facilitate engagement between services and young people who have complex needs. There is a need to create a service environment that is adaptive to the needs of young people rather than one which requires these young people to adapt to any particular service.
Constrained least squares simplicial-simplicial regression
Authors: Tsagris Michail 
Published: January 2025

Abstract
Simplicial-simplicial regression refers to the regression setting where both the responses and predictor variables lie within the simplex space, i.e. they are compositional. For this setting, constrained least squares, where the regression coefficients themselves lie within the simplex, is proposed. The model is transformation-free but the adoption of a power transformation is straightforward, it can treat more than one compositional datasets as predictors and offers the possibility of weights among the simplicial predictors. Among the model’s advantages are its ability to treat zeros in a natural way and a highly computationally efficient algorithm to estimate its coefficients. Resampling based hypothesis testing procedures are employed regarding inference, such as linear independence, and equality of the regression coefficients to some pre-specified values. The strategy behind the formulation of the new model implemented is related to an existing methodology, that is of the same spirit, showcasing how other similar models can be employed as well. Finally, the performance of the proposed technique and its comparison to the existing methodology takes place using simulation studies and real data examples.