bluuebunny/crossref_metadata_2025_split huggingface dataset:
Periodic One-Dimensional Subsurface Channels Induced by Ordered Oxygen Vacancies on CeO2 (110)
Authors: Wang Yong , Li Guanxing , Hu Xiaojuan , Zou Chen , Li Songda , Han Zhong-Kang , Yuan Wentao , Zhang Ze 
Published: February 2025

Abstract

The distribution and interaction of oxygen vacancies (VOs) play a crucial role in determining the properties of metal oxides, particularly ceria, which is widely used in high-temperature industrial applications. However, information about VO behavior at high temperatures is scarce in the literature due to the inherent complexity of VO interactions and the lack of accurate models to describe and predict these interactions under such conditions. Consequently, the existence of long-range ordered Vos remains elusive. Here, we reveal an unexpected periodic one-dimensional subsurface channel induced by ordered VO distributions on CeO2 (110) at high temperatures, using in-situ scanning transmission electron microscopy (STEM), first-principles calculations, and a compressed sensing-assisted cluster expansion model. The strong repulsive interactions between neighboring VOs drive their ordered distribution, which, in turn, facilitates the formation of the periodic one-dimensional subsurface channels by relieving stresses induced by VOs and polarons. The large energy gap between the occupied O 2p band center and the unoccupied Ce 4f band center was identified to underpin these processes and maintain this abnormal subsurface channel. This subsurface channel on CeO2 (110) exhibits sub-nano-level pores and an accumulation of polarons, making it well-suited for the directional transfer of protons, which provides new insights into the high catalytic activity of ceria in hydrogenation reactions. These findings offer not only a deeper understanding of VO interactions and their underlying mechanisms but also a new approach for manipulating VOs for specialized applications.
Testing for treatment effect heterogeneity:
Educational reform, genetic propensities, and family background
Authors: Okbay Aysu , Ahlskog Rafael , Beauchamp Jonathan , Oskarsson Sven , Thom Kevin 
Published: February 2025

Abstract

We study the heterogeneous effects of a Swedish educational reform that increased compulsory schooling from seven to nine years. Following a pre-registered Analysis Plan, we examine how the reform differentially affected 20 outcomes in various domains (education, the labor market, fertility, substance use, and health) for individuals with different genetic propensities towards these outcomes. To estimate the effects of the reform, we leverage the gradual roll-out of the reform with a differences-in-differences estimator that compares municipalities and birth cohorts before and after the reform. Among 105 pre-registered tests of heterogeneous effects as a function of genetic propensities (across outcomes, sexes, and family SES background), we find two significant interactions after correction for multiple hypothesis testing. One of these implies that, among females from high-SES families, the reform had a relatively larger effect on earnings for those with a lower genetic propensity for educational attainment. Our results suggest that sizable heterogeneous effects of educational reforms may not be ubiquitous but do exist, and highlight how careful study designs with preregistration can help uncover them.
Photocatalytic degradation of tetracycline antibiotic using nitrogen-doped reduced graphene oxide supported by titania/platinum nanoparticles
Authors: Moharrami Elham , Keshipour Sajjad 
Published: February 2025

Abstract

Tetracycline, a broad-spectrum antibiotic, is particularly concerning as it is resistant to degradation in water bodies, leading to its persistence in the environment. Herein, the photocatalytic degradation of tetracycline was investigated by a newly developed catalyst of TiO2/Pt nanoparticles, which were immobilized on nitrogen-doped reduced graphene oxide (NRGO). Pt/TiO2@NRGO catalyst was prepared via a convenient pyrolytic route of mixing citric acid/urea/titanium (IV) isopropoxide as the starting materials with the subsequent deposition of Pt nanoparticles by chemical reduction of Pt (IV). Photocatalytic activity of the prepared nanocomposite was evaluated in the decomposition of tetracycline. The obtained results demonstrated the exemplary performance of the prepared heterogeneous catalyst by which the antibiotic removal efficiency was calculated to be ~ 81%. In conclusion, it can be claimed that the outstretched catalyst is able to be employed in the temperature of about 45 oC and neutral pH ranges for efficient degradation of tetracycline.
Associating Attitudes towards AI and Ambiguity: The Distinction of Acceptance and Fear of AI
Authors: Hitsuwari Jimpei , Takano Ryota 
Published: February 2025

Abstract

Since the emergence of ChatGPT, Artificial Intelligence (AI) has become increasingly integrated into society, making it essential to understand how individuals perceive and interact with it. Given AI’s inherent ambiguity and uncertainty, this study examines the relationship between attitudes towards AI and ambiguity. A survey of 554 Japanese participants was conducted using questionnaires, including the Attitude Toward Artificial Intelligence scale (ATAI) scale, which assesses two key dimensions: acceptance and fear, along with the Multidimensional Attitudes Toward Ambiguity Scale. Findings indicate that the Japanese version of the ATAI developed for the first time in this study, demonstrated strong internal consistency, test-retest reliability, and validity. Psychometric properties were supported by AI usage, willingness to use AI, and expected correlations with personality traits, aligning with prior literature. Text-based predictions using natural language processing reinforced this finding, showing significant associations with ATAI scores. This study is the first to examine how attitudes towards AI relate to ambiguity, revealing that Need for complexity and Novelty, and Discomfort with Ambiguity predict AI acceptance and fear. Absolutism positively correlates with both. These results indicate that attitudes towards AI are inherently complex and multidimensional, offering insights for effective and sustainable AI engagement as an ambiguous agent.
Enhancing Egg Grading Precision through AI and Computer Vision-Powered Morphometric Analysis
Authors: Hamadani Henna , Hamadani Ambreen , Boje Pakcha Hannah , Moyon Amelia , Khan A. A. 
Published: February 2025

Abstract

Egg size determination is an important activity in the poultry industry. Traditional methods of size assessment are labour-intensive, error-prone, and time-consuming. Machine learning is proving to be a major game changer in all sectors and this has the potential to upgrade and automate egg grading as well. Considering all this, this research was undertaken to evaluate the potential of AI-driven computer vision approaches for the extraction of egg dimensions from 2D images. The images were annotated and saved as an OBB dataset and were appropriately preprocessed. Yolo11 OBB models were evaluated for their ability to detect eggs and yolo11x-obb model was found to be optimal for this study. The Mean Absolute Errors (MAE) of the two final predictive models for egg size were 0.28 for length and 0.19 for breadth, with Pearson Correlations of 0.81 for length and 0.85 for breadth for Model 1 and MAEs of 0.29 for length and 0.26 for breadth, with Pearson Correlations of 0.88 for length and 0.81 for breadth for Model 2. Science4ImpactStatement: This foundational research concludes that Machine Learning methods can predict egg dimensions with good accuracy and could potentially be used for poultry breeding, automatic egg grading, packaging, processing as well as marketing.
Optimal Cutoff for Neutrophil-to-Lymphocyte Ratio as a Tool for Pre-Chemotherapy Prognosis Stratification of Breast Cancer Patients
Authors: Zandi Armita , Qian Alyssa , Bucciol Regan , Othman Maha 
Published: February 2025

Abstract

Introduction: The neutrophil-to-lymphocyte ratio (NLR) is an established inflammatory marker in cancerpatients. The optimal cut-off as an independent prognostic factor for breast cancer (BC) progression in patients undergoing chemotherapy remains debatable, hindering the effective stratification. This study explored the optimal NLR cut-off by comparing various thresholds and assessing their effectiveness in stratifying BC patients according to prognosis.
Methods: Demographic, clinical, and cancer-specific data on forty-two BC patients were recorded, including complete blood counts before and after two cycles of chemotherapy. Receiver operating characteristic curve assessed discriminatory performance. Diagnostic metrics and Youden’s J index were calculated and McNemar’s test was used to compare baseline NLR cutoffs of 2.5, 3.0, and 3.5. Kaplan-Meier curves assessed the relationship between various NLR cut-offs and other cancer prognostic markers.
Results: The three NLR cutoffs demonstrated distinct diagnostic metrics and Youden’s J index values (p < 0.001), with the 3.0 cutoff providing the most balanced performance. Patients with pre-chemotherapy NLR > 3.0 were predicted to develop advanced stage BC more rapidly compared to those with pre-chemotherapy NLR < 3.0.
Conclusion: We believe that a more stringent NLR cutoff of 3.0 is the most suitable predictor of prognosis in BC patients based on the ranges evaluated in literature.
Evaluating Treatment Options for Symptomatic Uterine Fibroids: A Systematic Review and Meta-analysis of Effectiveness, Recovery, and Long-Term Outcomes (MARIE WP1)
Authors: Bedggood Elena , Jie Sun , Ghosh Snehal , Pathiraja Vindya , Mudalige Tharanga , Rathnayake Nirmala , Cavalini Heitor , Kurmi Om , Eleje George , Phiri Peter , Briggs Paula , Shi Jian qing , Delanerolle Gayathri , Elneil Sohier 
Published: February 2025

Abstract

Background: Uterine fibroids can significantly impair the quality of life of women. While most fibroids remain asymptomatic, 25% of women diagnosed with uterine fibroids require medical intervention.
Methods: A systematic review and meta-analysis protocol was developed and published in PROSPERO (CRD42022346251) to explore surgical treatment outcomes linked to uterine fibroids. Data was gathered using PubMed, Web of Science and ScienceDirect. The pooled data was analysed using the meta-package (version 8.0-1 and version 4.6-0) in R software (version 4.4.2).
Results:
Five studies met the eligibility criteria, and were further analysed to report quality of life, symptom severity and complications linked to surgery. Three studies (n=520) assessed HRQoL via UFS-QoL pre- and post-uterine artery embolisation and myomectomy. The pooled mean difference was -6.99 (95% CI: [-16.49, 2.51]; I²=71.9%; P=0.03), indicating no significant difference in quality of life impact between procedures. However, the pooled mean difference for UFS-QoL symptom severity was 4.85 (95% CI: [0.50, 9.21]; I²=0.0%; P=0.52), suggesting myomectomy significantly reduces symptom severity compared to uterine artery embolisation. Most studies did not report race and ethnicity, and the study sample was not representative of the global female populous.
Conclusion:
Uterine artery embolisation and myomectomy result in comparable improvements in health-related quality of life although myomectomy appears to offer a greater reduction in symptom severity compared to uterine artery embolisation. These findings can assist clinicians and patients make improved shared decisions when selecting the most appropriate treatment for uterine fibroids. Improved research study designs and representation in sample need to be considered when conducting future research.
Tropospheric Assessment of Carbon Monoxide, Nitrogen Dioxiode, and Aerosols in Onitsha, Anambra State, Southeastern Nigeria – a Case Study of 2019–2024
Authors: Okoye Desmond 
Published: February 2025

Abstract

Onitsha faces severe air pollution, exposing residents to harmful levels of carbon monoxide (CO), nitrogen dioxide (NO₂), and aerosols. This study assessed Sentinel-5P satellite data using Google Earth Engine from 2019 to 2024, analyzing pollution trends and statistical differences across the years. CO and NO₂ peaked in February, with CO highest in 2024 (0.0537 mol/m²) and lowest in 2023 (0.0481 mol/m²). NO₂ levels were highest in 2021 and 2022, while aerosols peaked in 2022 and remained high in commercial areas. Statistical analysis confirmed varying significance across years. CO levels were significantly different between 2019 and 2020 (p < 0.05) and highly significantly different between 2022 and 2023 and between 2023 and 2024 (p < 0.01), with no significant differences between 2020 and 2022 (p > 0.05). NO₂ levels were significantly different between 2020 and 2021 (p < 0.05) and between 2022 and 2023 (p < 0.05), while other comparisons showed no significant differences (p > 0.05). Aerosol levels were highly significantly different between 2021 and 2022 (p < 0.01), with no significant differences in the other periods (p > 0.05). Pollution hotspots were found around Onitsha Main Market, Niger Bridge, and Ochanja Market, linked to traffic, industries, and open waste burning. Despite fluctuations, pollutant levels were high, posing health risks. Addressing this requires stricter emission controls, better transportation policies, and continuous air quality monitoring.
Extracellular vesicles deliver functional extrachromosomal DNA in FGFR2-amplified cancer of unknown primary
Authors: Salamon Irene , Gallerani Giulia , Storci Gianluca , Fontana Beatrice , Seravalle Salvatore , Valle Francesco , Brucale Marco , Bortoletto Nicolò , Mariano Marco Pagano , Soru Alessia , Cavazzoni Andrea , Roncarati Roberta , Santi Spartaco , Bonafè Massimiliano , Ferracin Manuela 
Published: February 2025

Abstract

Background The extracellular vesicle (EV) pathway plays a critical role in cell-to-cell communication. Cancer cells release EVs into the extracellular space, where they interact with both cancerous and noncancerous cells, activating signaling pathways and remodeling the tumor microenvironment (TME). In this study, we investigated the functional role of EVs released by FGFR2-amplified cancers of unknown primary (CUPs), which generate extrachromosomal circular DNA (ecDNA) to enhance oncogenic amplification.Methods FGFR2 copy number was quantified using droplet digital PCR (ddPCR) and visualized using fluorescent in situ hybridization (FISH). EVs were isolated via ultracentrifugation, and the circular nature of FGFR2 ecDNA was assessed using Plasmid-Safe ATP-dependent DNase treatment and atomic force microscopy (AFM). Oncogene transfer through EVs was evaluated by administering isolated CUP-derived EVs to recipient NCI-N87 cells or by using a coculture system that facilitated EV transfer to THP-1, HUVEC, and fibroblast cell lines.Results CUP-derived FGFR2-containing ecDNA, which is partially circular, was packaged within EVs and exhibited functional activity upon delivery to TME cells. When cancer (NCI-N87, THP-1) and noncancer (HUVECs, fibroblasts) cells were exposed to CUP-derived EVs—either via direct administration or coculture—they internalized FGFR2 DNA, which was subsequently transcribed, leading to altered cell morphology and increased proliferation, depending on ecDNA type. CUP-derived EVs induced THP-1 polarization toward the M2 macrophage subtype and promoted HUVEC proliferation.Conclusion This mechanism of oncogene transfer can contribute to TME remodeling, potentially explaining the early metastatic potential of CUP.
A CT Operation Agent "Agentographer" built on Multimodal Large Language Model versus Radiographer in Chest CT Lung Cancer Screening
Authors: Yuan Xiaodong , zheng Xueyi , Li Sen , Yi Wanqing , Sun Weirong , Zhang Zhuang , Tian Yuan , Qiao Yuangang , Yang Yujia , Qu Wanwei , You Shan , Wang Chao 
Published: February 2025

Abstract

X-ray Computed Tomography (CT) is widely recognized and globally utilized due to its rapid imaging capability, high spatial resolution, and excellent density resolution. However, the large volume of CT examinations, coupled with complex and repetitive operation procedures, has increased the workload of radiographers and the risk of errors. This is particularly evident in populous countries such as China and India, especially during the prevalence of respiratory infectious diseases or in high-throughout scenarios such as large-scale lung cancer screening. There is an urgent need to enhance the intelligence level of CT examinations to reduce the workload while improving efficiency and quality.
To address this challenge, we propose a CT operation agent named Agentographer, which can autonomously perform CT examinations instead of human technicians. We curated a comprehensive multimodal dataset consisting of radiographer-patient interaction videos with associated Q&A transcripts from four distinct brands and models of CT scanners. After that, the dataset was used to train LLaMA-CT, a model specifically fine-tuned for dynamic scene perception and decision-making during CT examinations.
Then, powered by the LLaMA-CT, Agentographer integrates AI-driven patient interaction, 3D-camera-based isocenter positioning, segmentation-based CT scan location, automated device control, and AI-driven diagnostic and report models into a unified system. In a subsequent clinical trial of 500 subjects undergoing chest CT for lung cancer screening, Agentographer independently completed 476 cases (95.2%), achieving a significant reduction in both effective radiation dose (7%, P<0.001) and CT examination duration (9.3%, P<0.001), facilitating radiologists to issue diagnostic reports 12 hours earlier compared to a control cohort of 510 subjects examined by Radiographers.
Potenziale von Künstlicher Intelligenz für die Hochschullehre – eine Analyse von Strategiepapieren
Authors: Wagner Marlene , Gössl Alexandra , Pishtari Gerti , Ley Tobias 
Published: February 2025

In diesem Beitrag wird untersucht, welche Potenziale Künstliche Intelligenz (KI) für das Lehren und Lernen an Hochschulen bietet und welche Lehr-Lern-Prozesse durch den Einsatz von KI-Systemen sinnvoll unterstützt werden können. Dazu wurden zahlreiche Strategiepapiere zu KI, welche in den letzten Jahren im deutschsprachigen Raum sowie von EU-Institutionen und internationalen Organisationen (z. B. UNESCO, OECD) publiziert wurden, gesammelt und analysiert. Um die Potenziale von KI systematisch zu erfassen und zu bewerten, wurde das Modell der fünf Systemebenen der Lernumwelt Hochschule (Makro-, Exo-, Meso-, Mikro- und Individualebene) herangezogen. Dieses Modell ermöglicht eine strukturierte Betrachtung der verschiedenen Einflussbereiche und Ebenen, auf denen KI in der Hochschullehre wirken kann. Ein besonderer Fokus wurde dabei auf die Mikroebene gelegt, die sich direkt mit den Lehr-Lern-Prozessen befasst. Abschließend werden konkrete Handlungsempfehlungen für Lehrende und Studierende präsentiert, darunter die gezielte Integration von KI-gestützten Tools wie ChatGPT in die Lehre, die Anpassung der Prüfungsformate und Bewertungskriterien, die Förderung von kritischem und strukturiertem Denken sowie die Einhaltung ethischer Richtlinien im Umgang mit KI.
KI meets Lehre – Die Notwendigkeit der curricularen Verankerung von KI-Kompetenzen
Authors: Lambrecht Gabriella-Maria , Lintfert Britta , Martschiske Regine , Wiehenbrauk Daniela 
Published: February 2025

Basierend auf einer im Sommer 2024 durchgeführten Umfrage an der DHBW Heilbronn über die Verbreitung und Verwendung von generativer KI bei Studierenden und Lehrenden wird aufgezeigt, wie Lernprozesse durch die Integration von KI in die Lehre neu gestaltet werden können. Wir zeigen anhand der Befragungsergebnisse, warum eine curriculare Verankerung von KI-Kompetenzen für den Studienerfolg förderlich wäre und welche Rolle Lehrende dabei spielen können. Anhand eines so an der DHBW Heilbronn durchgeführten Praxisbeispiels aus einem betriebswirtschaftlichen Studiengang wird hierbei verdeutlicht, wie mithilfe von Selbstlerneinheiten der Erwerb von KI-Kompetenzen, wie z. B. der reflektierte und kritische Umgang mit KI-Tools, in die eigene Lehre erfolgreich integriert werden kann.
Generative KI im universitären Kontext – Die Perspektive der Studierenden
Authors: Roth Carina , Kolb Annalena , Bredl Klaus , Matthes Eva 
Published: February 2025

Der Beitrag untersucht die Perspektive von Studierenden in Bezug auf generative KI am Beispiel von ChatGPT im universitären Kontext. Dabei geht es unter anderem um deren persönlichen Einsatz, ihre diesbezügliche Einschätzung sowie um Zusammenhänge zwischen Ängstlichkeit, Einstellungen und Einsatzhäufigkeit. Die Datenerhebung mit N = 262 Studierenden (n = 70 weiblich, Alter: M = 22.24) verschiedener Fachrichtungen fand mittels eines theoriegeleiteten Fragebogens statt. Die Ergebnisse zeigen, dass ein großer Teil der Studierenden ChatGPT verwendet, der Wunsch nach universitären Vorgaben und Richtlinien allerdings stark ausgeprägt ist, und dass alle untersuchten Konstrukte miteinander in Zusammenhang stehen. Die Bedeutung der Ergebnisse wird diskutiert, und Implikationen für die Praxis und zukünftige Forschung werden abgeleitet.
ИНТЕРПРЕТАЦИЯ ИМЕНИ АРИСТОТЕЛЬ В АНАЛИТИЧЕСКОЙ ФИЛОСОФИИ
Authors: СПЕШИЛОВА Е.И. 
Published: February 2025

В статье рассматривается проблема референции имён собственных на примере имени Аристотель. Автор анализирует полемику между сторонниками теории дескрипций (дескриптивной теории) и теории прямой референции. Отмечается, что дескриптивная теория сталкивается с некоторыми трудностями, тогда как теория исторического объяснения (как вариант теории прямой референции), предложенная К. Доннеланом, успешно решает указанную проблему.
The article discusses the problem of reference of proper names on the example of name Aris­totle. I analyze the controversy between the theory of descriptions and the theory of direct reference and note that the theory of descriptions faces some difficulties, while the historical explanation theory (as a variant of the theory of direct reference) proposed by K. Donnellan successfully solves the problem.
ПЕРЕВОСПИТАНИЕ ДОЧЕРИ, ЖЕНЫ И МАТЕРИ В ТРАГЕДИИ ЕВРИПИДА "МЕДЕЯ"
Authors: ПИЧУГИНА В.К. 
Published: February 2025

Путем сопоставления отдельных диалогов трагедии Еврипида «Медея» в тексте обозначаются фрагменты, в которых зафиксированы представления драматурга о современной ему педагогической реальности. В «Медее» Еврипидом представлена иерархия добродетелей, которая должна быть принята тем, кто претендует на статус образованного человека. Изменяя мифологический сюжет и высвечивая изменения целым рядом новаторских художественных приемов, Еврипид демонстрирует процесс и результат перевоспитания Медеи-дочери, Медеи-жены и Медеи-матери, которая стремится образумить других и образумиться сама в условиях деления на «своих» и «чужих».
By comparison of separate dialogues in the Medea we isolate passages where Euripides inform us about contemporary educational reality. In his Medea, Euripides presents the hierarchy of virtues, which has to be accepted by any ‘educated’ person. Having changed the mythological plot and highlighted these changes by a number of innovative artistic touches, Euripides shows process and result of re-education of Medea-daughter, Medea-wife and Medea-mother who seeks to make understand others and bring herself to reason, being placed in the circumstances which force her to divide between the «one’s own» and the «others».