bluuebunny/crossref_metadata_2025_split huggingface dataset:
Quinolone Resistance Genes qnr, aac(6′)-Ib-cr, oqxAB, and qepA in Environmental Escherichia coli: Insights into Their Genetic Contexts from Comparative Genomics
Authors: Gomi Ryota , Adachi Fumie 
Published: February 2025

Abstract
Previous studies have reported the occurrence of transferable quinolone resistance determinants in environmental Escherichia coli. However, little is known about their vectors and genetic contexts. To gain insights into these genetic characteristics, we analyzed the complete genomes of 53 environmental E. coli isolates containing one or more transferable quinolone resistance determinants, including 20 sequenced in this study and 33 sourced from RefSeq. The studied genomes carried the following transferable quinolone resistance determinants alone or in combination: aac(6′)-Ib-cr, oqxAB, qepA1, qnrA1, qnrB4, qnrB7, qnrB19, qnrD1, qnrS1, and qnrS2, with qnrS1 being predominant. These resistance genes were detected on plasmids of diverse replicon types; however, aac(6′)-Ib-cr, qnrS1, and qnrS2 were also detected on the chromosome. The genetic contexts surrounding these genes included not only those found in clinical isolates but also novel contexts, such as qnrD1 embedded within a composite transposon-like structure bounded by Tn3-derived inverted-repeat miniature elements (TIMEs). This study provides deep insights into mobile genetic elements associated with transferable quinolone resistance determinants, highlighting the importance of genomic surveillance of antimicrobial-resistant bacteria in the environment.
Enhancing OCR in historical documents with complex layouts through machine learning
Authors: Fleischhacker David , Kern Roman , Göderle Wolfgang 
Published: February 2025

Abstract
This paper explores the challenge of processing and extracting information from large quantities of printed serial sources from the 19th century, which have been largely untapped due to the inadequacies of existing extraction techniques. We focus on the Habsburg Central Europe’s Hof- und Staatsschematismus, a comprehensive record published between 1702 and 1918 that documents the Habsburg civil service’s hierarchy and the evolution of its central administration over two centuries. Our approach sees the significant investment into machine learning-driven layout detection prior to the OCR-process. We generated synthetic data mimicking the Hof- und Staatsschematismus style for initial training of a Faster R-CNN model, followed by fine-tuning the model with a smaller dataset of manually annotated historical documents. Subsequently, we optimised Tesseract-OCR for our document style to enhance the combined structure extraction and OCR process. Our evaluation demonstrates significant improvements in OCR performance metrics (WER and CER), with the combined structure detection and fine-tuned OCR process showing a decrease in error rates of 15.68 percentage points for CER and 19.95 percentage points for WER. These findings underscore the potential of ML techniques in facilitating the extraction and analysis of historical documents.
Functional disability in the Health and Retirement Study: a semi-Markov multi-state analysis
Authors: De Giovanni Domenico , Menzietti Massimiliano , Pirra Marco , Viviano Fabio 
Published: February 2025

Abstract
We propose a direct non-parametric estimation framework for multi-state disability models that does not rely on the Markov assumption. In this context, “direct” denotes a method that does not necessitate the initial estimation of transition intensities. Previous research has demonstrated evidence of non-Markovian properties in disability dynamics, and a number of studies have employed semi-Markov models for Long-Term-Care products. We test the non-Markov assumption on an up-to-date American dataset that includes more than 200,000 records, finding insights on the non-Markovian character of disability. We then focus on transition probabilities, showing the impact of our assumption on these crucial metrics for actuaries. In addition, we investigate the influence of health conditions on all the transitions analyzed.
Molecular analysis confirms Agama picticauda invasion on Western Indian Ocean islands
Authors: Roesch Markus A. , Webster Kathleen C. , Huet Nicolas , Hawlitschek Oliver , Mohamed Youssouf , Sauroy-Toucouère Sohan , Wagner Philipp , Schmitz Andreas 
Published: February 2025

Abstract
The Western Indian Ocean biodiversity hotspot hosts a remarkable array of endemic species, but invasive alien species increasingly threaten its unique ecosystems. Lizards of the West African Agama agama species group are successful colonizers, with recent introductions to Grande Comore (Comoros Archipelago) and Reunion Island. Systematic revisions within the native range of the A. agama species group have left many of the introduced populations without clear identity. We used molecular methods to determine the identities of the Agama species introduced to Grande Comore and Reunion Island, define their respective likely origin, and assess body size characteristics for each island population. We identified Agama picticauda as the species present on both islands with likely origins in two distinct Western African regions. Agamas from Reunion Island had longer and wider heads with greater body weight than Grande Comore individuals. Sexual size dimorphism on both islands was driven by weight, with males being heavier than females. We provide foundations for further research on the ecology and impacts of A. picticauda on Western Indian Ocean islands and to aid in the development of targeted management strategies for controlling this invasive reptile.
Why and When Do Historical Brand Transgressions Matter?
Authors: Pecot Fabien , Lunardo Renaud , Chaney Damien , Eugene Y Chan 
Published: February 2025

Abstract
While many brands face the after-effects of historical transgressions, prior research provides little insight into these issues. Against this backdrop, this research presents five experiments providing convergent evidence for a lingering negative effect of historical brand transgressions (HBTs) on present brand evaluation, an effect that is due to a detrimental effect of HBTs on perceptions of brand warmth. Studies 1 and 2 establish the main effect and mediation. Studies 3–5 examine mitigating effects. Study 3 checks if high institutional pressure can serve as an excuse strategy that buffers the negative effects of a transgression. Studies 4 and 5 test the mitigating effect of different response styles (recognition, apology, and/or compensation). Together, these results contribute to the business ethics and marketing literature by defining the concept of HBT and showing why it harms a current brand’s evaluation and how brands can mitigate its negative effects.
Social media effects on multi-generational diffusion of information technology products
Authors: Li Yinxing , Terui Nobuhiko 
Published: February 2025

Abstract
This paper proposes a multi-generational model that captures the pre- and post-launch effects of social media on product diffusion. Post-launch effects appear in the adoption rate function as covariates, and pre-launch effects are embedded in hierarchical models as diffusion parameters that are connected to successive generations. The model reveals how social media accelerates and decelerates the diffusion of multi-generation products in the pre-launch and post-launch phases. Unlike previous multi-generational diffusion models, this model forecasts sales of new-generation products before launch. We employ the latent topics in social media as social media valence, and the empirical results show that the social media effects accelerate sales in the pre-launch period, and their effects decrease with varying patterns in the post-launch period.
A Framework for Multiphase Pore-Scale Modeling Based on Micro-CT Imaging
Authors: Foroughi Sajjad , Shojaei Mohammad Javad , Lane Nathan , Rashid Bilal , Lakshtanov Dmitry , Ning Yang , Zapata Yuliana , Bijeljic Branko , Blunt Martin J. 
Published: February 2025

Abstract
We demonstrate how to use pore-scale modeling combined with high-resolution imaging to make predictions of multiphase flow properties. Experiments were performed on two sandstone samples that were mixed-wet after contact with crude oil: Bentheimer and a reservoir rock. Flow experiments were combined with high-resolution X-ray imaging from which the pore space, fluid configurations and local contact angles can be measured. We first show that both lattice Boltzmann modeling and a pore network model can predict the fluid occupancy to within experimental and model uncertainty in Bentheimer using the measured contact angles. We then used the greater computational efficiency of the network model to simulate flow in a large network representing the reservoir sample. By calibrating the contact angle to match the observed pore-by-pore arrangement of fluid, the model was able to make predictions of relative permeability and capillary pressure that were within the bounds of experimental and model uncertainty. The results provide a framework for predictive image-based pore-scale modeling, where wet and dry images of rock samples are used to characterize both the pore structure and wettability.
Do direct and courtesy prison stigma hinder support for a startup business? A vignette experiment
Authors: Hickert Audrey , Shi Luzi , Shaw Olivia , Yan Shi 
Published: February 2025

Abstract

Objectives
Test whether support for a small business is lower when started by prisoners or mothers of prisoners compared to local residents or people who identify as LGBTQ.

Methods
We conducted a vignette experiment using a hypothetical social media post for a new business followed by closed- and open-ended questions using a national YouGov sample (N = 1300).

Results
Support for the business is lower when founded by mothers of prisoners than former prisoners (or “local residents”), but lowest when founded by people who identify as LGBTQ. Open-ended responses suggest a lack of awareness of collateral consequences for families of people in prison. Explanations consistent with courtesy stigma were also present.

Conclusions
Given the public’s growing awareness of the benefits of successful reintegration and their willingness to support second chances, more education on the collateral harms of mass incarceration on families could assist with reinvestment in these communities.
Examining Teaching Competencies and Challenges While Integrating Artificial Intelligence in Higher Education
Authors: Ren Xinyue , Wu Min Lun 
Published: February 2025

Abstract
The rapid development of artificial intelligence (AI) technologies has demonstrated their affordances and limitations in revolutionizing pedagogical strategies in higher education. Given the lack of guidelines, policies, and resources to assist instructors in efficiently and ethically integrating AI into teaching and learning practices, this systematic review aimed to investigate AI integration competencies and challenges in higher education from the intelligent Technological Pedagogical Content Knowledge (TPACK) perspective. We first applied the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) to identify 23 studies published between 2019 and 2023 that met the inclusion and exclusion criteria. After conducting open coding and thematic analysis, the research findings showed four AI integration competencies and strategies, including 1) AI literacy and readiness as intelligent technological knowledge, 2) AI-supported innovative pedagogy to supplement instructor social presence and transform the instructor-student relationship, 3) AI as intelligent learning partners to increase student engagement in self-regulated learning and higher-order thinking skills, and 4) AI-driven learning experience design and delivery. AI integration limitations and challenges contained: 1) the short-term novelty effect, 2) digital divides, 3) technical deficiencies, and 4) ethical concerns. Based on the implications for future practices, a diagram was developed to illustrate the systematic considerations to support the sustainability of AI-assisted teaching and learning in higher education.
Investigating normal stress effects on the shear and traction characteristics of performance infill materials used in artificial turf surfaces
Authors: McGowan Harry , Fleming Paul , James David , McMahon Jim , Pak Jae-Hwi , Forrester Steph 
Published: February 2025

Abstract
Styrene butadiene rubber crumb is currently the most widely used performance infill material for artificial turf surfaces globally. Concerns about the impact of microplastics on the environment and human health has led to organic performance infill materials becoming more popular. Research surrounding these new performance infill materials is lacking; one key gap in knowledge is the relationship between normal stress and rotational traction. The purpose of this study was to analyse the relationship between normal stress and rotational traction for three performance infill materials: styrene butadiene rubber, cork and pine. Five normal stresses (10–46 kPa) were analysed during rotational traction testing on three artificial surface systems. Each performance infill material showed a positive, linear relationship between normal stress and mean peak torque, initial stiffness and secondary stiffness. However, the rate at which mean peak torque increased with normal stress varied between infilled systems. Pine infill increased at 1.55 Nm/kPa, cork at 1.51 Nm/kPa and styrene butadiene rubber at 1.16 Nm/kPa. Direct shear testing of each performance infill material was conducted at three normal stresses (25, 50 and 250 kPa) to investigate each performance infill materials relative resistance to shearing. The order of infill materials remained the same for both rotational traction and direct shear testing, with pine consistently producing the highest internal friction angle and styrene butadiene rubber the lowest. The results confirm the need to better understand the performance characteristics of organic infill materials used in artificial turf surfaces to maintain their safety and performance characteristics.
Maximum depositional age of the sedimentary succession in the southwestern margin of the Ulleung Basin from zircon age dating of conventional drilling cores
Authors: Lee Hyun Suk , Son Junghee , Song Gihun , Oh Juhyeon , Kim Yoonsup , Hwang In-Gul , Kim Sehyun , Kwak Wonjun 
Published: February 2025

Abstract
Biostratigraphic research has been conducted over the last four decades in the southwestern Ulleung Basin and has provided a chronostratigraphic framework to understand basin evolution. However, absolute geologic ages for the basin are almost absent owing to the lack of deep-drilled cores. To obtain the absolute age from the zircon, we extensively sampled and measured five deep-drilled conventional cores previously obtained for hydrocarbon exploration from the southwestern shelf of the Ulleung Basin. Maximum Depositional Ages (MDAs) for each cored interval are determined by the youngest age groups of zircons and are calculated to 12.1 ± 0.1 Ma for Gorae I-1, 12.9 ± 0.2 for Gorae I-2, 10.2 ± 0.8 for Gorae V-3, 11.4 ± 0.7 for Gorae V-4, and 16.9 ± 0.3 for Dolgorae V-1. All age groups exhibited relatively narrow errors (avg. ± 0.4 Ma), indicating good accuracy of MDA. The MDAs for the cores were first obtained by Laser Ablation-Multi Collector-Inductively Coupled Plasma Mass Spectrometry (LA-MC-ICPMS), and the youngest zircon grains were subsequently reanalyzed by Sensitive High-Resolution Ion Microprobe (SHRIMP) to prevent age underestimation due to possible Pb loss. The differences in absolute ages of Gorae I-1 and I-2 between LA-MC-ICPMS and SHRIMP methods are below than 0.8 Ma, indicating good verification of MDAs. The four seismic horizons that overlapped with the cored interval were newly established as GR I-2 MDA, GR I-1 MDA, GR V-4 MDA, and GR V-3 MDA (except for Dolgorae V-1 because of the poor quality of the seismic profiles). The newly defined MDA horizons were compared to the biostratigraphic sequence boundaries of (Yi et al., Marine and Petroleum Geology 122, 2020), indicating ages 1 to 3 Ma younger than the biostratigraphic estimates. The four MDA horizons provide a new time framework for sequence stratigraphic interpretation of the Miocene deposits as well as reconstruction of the basin-evolution model in the southwestern shelf of the Ulleung Basin.
Artificial intelligence in orthopedic research assistance: a resident’s perspective
Authors: Perez Rubén Dario Arias , Garcia Ricardo Londoño 
Published: February 2025

Abstract
Artificial intelligence (AI) is transforming orthopedic research by optimizing academic workflows, improving evidence synthesis, and expanding access to advanced data analysis tools. Generative AI models such as ChatGPT and GPT-4, alongside specialized platforms such as Consensus and SciSpace, empower researchers to refine search queries, enhance literature reviews, synthesize documents, and conduct advanced statistical analyses. These technologies enable the interpretation of large datasets, saving time and boosting efficiency. For orthopedic residents, AI is particularly impactful, revolutionizing their education and fostering greater independence in research. This review explores the key applications of AI as a research assistant in orthopedics, as well as its ethical considerations and challenges.
In pursuit of equity in upper secondary education: the curious case of Ghana’s free senior high school policy
Authors: Akuffo Aboabea Gertrude 
Published: February 2025

Abstract
The Free Senior High School policy is Ghana’s attempt at actualising the SDG 4 global consensus on free upper secondary education. Using grounded theory method, this research scrutinises the Free SHS 2018 policy and strategy document, alongside interviews with policymakers, to answer the question: How does the equity provision ensure fairness in upper secondary education, and what equity blind spots exist? Specifically, the study employed a purposive sampling technique, allowing for the deliberate selection of data sources that ensured the collection of focused, meaningful data aligned with the research goals. The findings underscore a disconnect between the policy’s equity intentions and solutions. For example, the policy highlights that, intersectional differences—such as economic, school-based, gender, and regional factors—persist and drive inequitable access. However, these issues are inadequately addressed because the policy applies cookie-cutter-style economic solutions to all inequity concerns. Policymakers from within, and outside from government, hold diverse perspectives on the impact of this disconnect on sub-populations. The former underscores political and technical accountabilities where increasing numbers of enrolment are equated to equity, while the latter underscores differential policy effect sizes on sub-population to mean inequity. Curiously, the policy has improved access despite the equity conundrum, weak economy, lack of private–public initiatives, declining GDP allocation to education, no selective fee waivers, and neglect of secondary education expansion prerequisites. The paper advocates realigning the policy’s equity dimension with its equity goals.
A New Approach for Sleep Stage Identification Combining Hidden Markov Models and EEG Signal Processing
Authors: Pouliou Areti , Papageorgiou Vasileios E. , Petmezas Georgios , Pessoa Diogo , Paiva Rui Pedro , Maglaveras Nicos , Tsaklidis George 
Published: February 2025

Abstract

Purpose
Sleep constitutes a third of human life, underscoring its importance in health-related and psychophysiological research. Monitoring sleep stage evolution is critical for understanding sleep-related issues and diagnosing disorders. This study aims to classify sleep stages using a Hidden Markov Model (HMM) based on spectral statistical measures derived from raw electroencephalography (EEG) signals. It explores effective feature combinations to enhance classification accuracy while maintaining a practical approach requiring minimal inputs.

Methods
We utilized raw EEG signals to extract various statistical features in the frequency domain, identifying combinations that maximize predictive performance. The proposed HMM was employed to classify sleep stages, leveraging these spectral features. Unlike many prior studies that focus solely on machine learning (ML) techniques, our analysis emphasizes feature significance and model interpretability.

Results
Our approach achieved a multiclass classification accuracy of 76.76% using only EEG recordings. This performance demonstrates the utility of spectral statistical features for sleep stage classification, with results comparable to more complex ML methods.

Conclusion
The proposed methodology highlights a practical, accurate and interpretable approach to sleep stage classification using EEG data. Its simplicity and efficiency make it suitable for both offline and online applications, supporting improved diagnosis of sleep disorders and advancing sleep research.
What determines participation in multi-stakeholder partnerships? Assessing sustainability awareness and knowledge
Authors: Enechi Okechukwu , Pattberg Philipp 
Published: February 2025

Abstract
Multi-stakeholder partnerships (MSPs) are widely promoted as essential for achieving the United Nations Sustainable Development Goals (SDGs). However, their implementation is influenced by contextual factors, including stakeholder awareness. Yet while MSPs have been extensively researched as a participatory governance mechanism, there are limited studies examining the impact of sustainability awareness and knowledge on stakeholder participation in MSPs. This study, therefore, examines the impact of sustainability awareness on stakeholder participation in MSPs in Nigeria, focusing on the issue of climate change. Through a survey of 399 MSP participants, we found high overall climate change awareness but varied perceptions of its impact. Though stakeholders were moderately aware of climate policies, awareness of its implementation at the local level was limited. Furthermore, while there was general understanding of SDG interactions, specific linkages among the goals remained unclear. These knowledge gaps could limit local level stakeholder participation and result in misalignment of MSP agenda with local priorities, thereby hindering SDG implementation at the local level. Consequently, the study recommends strengthening MSPs as knowledge-sharing platforms, enhancing sustainability literacy, and fostering MSPs that are local in design with clear link to global sustainability framework. While these recommendations offer a roadmap for enhancing stakeholder participation in MSPs for acceleration of SDGs, it is essential to acknowledge the need for a robust meta-governance framework that would facilitate sustainability awareness and knowledge at the local level for effective local level stakeholder participation in MSPs. This study contributes to the literature on the role of MSPs as central mechanisms for enhancing participation in the SDG process, particularly at the local level in the sub-Saharan African region.
Curbing inappropriate C. difficile treatment in patients receiving concomitant laxatives
Authors: Fields Paige , David Christopher , Choksi Anish , Pettit Natasha N. , Lew Alison K. , Pisano Jennifer , Nguyen Cynthia T. 
Published: February 2025

Abstract
In the setting of universal Clostridioides difficile screening, we implemented an alert that triggered when C. difficile treatment was ordered in patients who recently received laxatives. This resulted in C. difficile treatment avoidance in 37% of patients and was associated with drug cost savings of $143,905 over a 10-month period.