bluuebunny/crossref_metadata_2025_split huggingface dataset:
A Scalable Method for Validated Data Extraction from Electronic Health Records with Large Language Models
Authors: Stuhlmiller Timothy J. , Rabe AJ , Rapp Jeff , Manasco Penelope , Awawda Alaa , Kouser Hiba , Salamon Hugh , Chuyka Donald , Mahoney William , Wong Kenny K. , Kramer Glenn A. , Shapiro Mark A. 
Published: February 2025

AbstractPurposeExtracting and structuring relevant clinical information from electronic health records (EHRs) remains a challenge due to the heterogeneity of systems, documents, and documentation practices. Large Language Models (LLMs) provide an approach to processing semi-structured and unstructured EHR data, enabling classification, extraction, and standardization.MethodsMedical documents are processed through a structured data pipeline to generate normalized FHIR data. Unstructured data undergoes preprocessing, including optical character recognition, document parsing, text chunking and embedding. Embedding enables search and classification which facilitate document retrieval for extraction. LLMs perform named entity recognition and relation extraction, with outputs mapped to FHIR R4 and OMOP and harmonized with pre-structured data for interoperability. Model performance is evaluated through human validation and automated consistency checks. Iterative refinement, error analysis, and standardized schema selection optimize use for analytics and downstream workflows.ResultsAn LLM-based schema for medication extraction, validated on 34 patients, achieved ∼95% accuracy and F1-score across 7 data fields for 5,789 extracted medications. Deployment across 11,115 patients extracted 2.6 million medication records, increasing total medications by 27% and distinct drug ingredients by 31% over structured data in the EHR. LLM extraction increased oncology medications by 60%, distinct oncology therapies by 64%, and the number of patients with structured oncology medication data by 33%. The LLM enhanced data completeness, improving availability of indication for prescription (61% vs. 31%) and discontinuation reason (17% vs. 0%), outperforming pre-structured data in key clinical variables.ConclusionAn LLM-powered extraction process that employs embeddings, machine learning classification, schema-based extraction, and mapping of extracted information to healthcare data standards, achieves a significant gain in clinically relevant information over pre-structured data available in the EHR.
Compost amendments to potato soils enrich yield-associated members of soil microbiomes across the continental US
Authors: Klasek Scott A. , Crants James E. , Frost Kenneth E. , Schroeder Brenda K. , Rosen Carl J. , Kinkel Linda L. 
Published: February 2025

AbstractPlant health is regulated by complex consortia of soil microbes with growth-promoting and pathogenic functions. In potato production, various soil management practices are undertaken to boost yields and suppress diseases, but connections between these practices, soil microbiomes, and tuber yields have not been characterized across diverse growing regions. To identify growing practices and microbes associated with increased yields, we established four-year field trials across eight US sites from Oregon to Maine that consisted of controls, fumigations, organic amendments, and mustard incorporations. Soil microbiomes consisted of 16S and ITS amplicon sequences from bacteria and microeukaryotes, respectively. While soil treatments influenced microbiomes differently across all field sites, eukaryotes were more sensitive than bacteria to all treatments. Soil treatments impacted proportions of distinct amplicon sequence variants (ASVs), and associations between ASVs and tuber yields varied within genus-level taxonomy and across field sites. Forty-five ASVs were identified as both treatment-impacted and yield-associated within any field site. Models identified three of thirteen compost amendment scenarios and one of thirteen fumigation scenarios that increased tuber yields by increasing proportions of these taxa within soil microbiomes. These ASVs were not influenced by treatment-associated changes in soil nutrients or organic matter, highlighting complex relationships within specific field sites that require further study to achieve the goal of implementing sustainable, microbiome-informed potato production techniques.ImportanceSoil microbes play diverse and interconnected roles in mediating plant health, growth, and disease, but understanding the specifics of how they work and applying them across different agricultural systems remains a challenge. To address this, we amassed a dataset from eight potato field sites across major US growing regions consisting of nearly two thousand soil bacterial and fungal microbiomes paired with soil chemical and tuber yield data. We describe how soil microbiomes are impacted by different soil treatments (compost amendments, chemical fumigation, and mustard incorporation), and identify treatments that boosted yields by up to 23% by increasing proportions of certain bacterial or fungal sequences. Compost amendments affected yield-associated taxa more often than other soil treatments, but these effects varied by rotation length and growing region. Changes to soil chemistry resulting from specific soil treatments did not influence abundances of yield-associated taxa, suggesting that the ways in which they may act to maintain plant vigor are field-specific and complex, calling for further study.
Quantum chromodynamics resolution of the ATOMKI anomaly in
He4
nuclear transitions
Authors: Kubarovsky Valery , West Jennifer Rittenhouse , Brodsky Stanley J. 
Published: February 2025

Observations of anomalous angular correlations in electron-positron pairs produced from excited states of He4, Be8, and C12 nuclei have been suggested as being due to the creation and subsequent decay of a new light particle of mass ∼17MeV. In this work, we investigate the possibility that the source of the observed signals is a set of new excitation channels created by the 12-quark hidden-color Fock state within the He4 nuclear wave function dubbed the “hexadiquark.” We calculate the invariant e+e− mass spectrum for the electromagnetic transition from a new excitation of He4, estimating its differential and total decay width. We find that we can fit the shape of the anomalous signal with the QCD Fock state at excitation energy E*=17.9±1MeV and a Gaussian form factor for the electromagnetic decay. We address the physical issues with the fit parameters using properties of the hexadiquark state, in particular the three weakly repulsive 6C interactions of SU(3)C between diquark pairs. Experimental tests of our model are described in detail. In light of this work, we emphasize the need for independent experimental confirmation or refutation of the ATOMKI results as well as dedicated experiments to search for the proposed new excitations of He4 and other α-cluster nuclei.

Published by the American Physical Society
2025
A deployable agile blockchain as a service (aBaaS) framework for construction projects
Authors: Lu Weisheng , Wu Liupengfei , Yang Zhongze , Peng Ziyu , Chu Louis 
Published: February 2025

PurposeThis study aims to develop an agile blockchain as a service (aBaaS) framework for construction projects, which will support blockchain design, deployment and operation in a flexible, agile and cost-effective manner.Design/methodology/approachThis research adopts a design science research method. The aBaaS framework is then substantiated through two case studies pertinent to construction projects.FindingsIt is found to be highly flexible, achieving high completion rates in customizing the design, deployment and visualization of blockchain systems within given periods. Also, the aBaaS framework is highly agile and cost-effective, capable of responding to changes with low person-day units and labor cost.Research limitations/implicationsLimited sub-service components are built in design management as services (DMSs), deployment as services (DESs) and visualization as services (VISs) of aBaaS framework.Practical implicationsThis research offers a reference for those aiming to realize the potential of blockchain in construction projects.Originality/valueFirstly, it introduces a novel, flexible modular-build DMSs method to help system developers design blockchain systems for projects. Secondly, it improves the blockchain deployment methods by offering plug-and-play DESs for projects. Thirdly, it accelerates the visualization processes for blockchain users in projects by offering them flexible, click-to-go and cost-effective VISs.
Identifying the researchable themes in seventh sustainable development goal: affordable and clean energy
Authors: Murad Muhammad , Othman Shahrina Binti , Kamarudin Muhamad Ali Imran Bin 
Published: February 2025

Purpose
The purpose of this study is to present a bibliometric analysis of affordable and clean energy research, focusing on key themes, collaboration patterns and the field’s intellectual structure.

Design/methodology/approach
Using a sample of 37 articles from Scopus, the authors identified the most frequently used keywords, the most productive countries and organizations and categorized research themes into niche, motor, basic and emerging or declining themes. “Clean Energy,” “Renewable Energy” and “Affordable and Clean Energy” emerged as dominant keywords, highlighting the field’s alignment with global sustainability goals. The USA, China and India were found to be the most productive countries, while institutions like Sri Manakula Vinayagar Engineering College and Nigerian National Petroleum Company played pivotal roles in collaborative networks, reflecting a globalized and interdisciplinary research environment.

Findings
The thematic analysis revealed that motor themes, such as “Climate Change” and “Greenhouse Gases”, are central to the discourse, while topics like “Economic Development” and “Energy Conservation” were identified as niche areas. Basic themes, including “Carbon Dioxide” and “Electricity Industry,” remain foundational yet underdeveloped.

Originality/value
This study provides a structured overview of the affordable and clean energy research landscape, offering insights into current trends and identifying areas for future exploration, with an emphasis on interdisciplinary collaboration and socio-economic impacts.
Empirical forecasting of housing prices in Malaysia using ARIMA
Authors: Olanrewaju AbdulLateef 
Published: February 2025

Purpose
Housing provision is a fundamental driver of national development and economic prosperity. However, housing affordability remains a critical problem worldwide, affecting countries regardless of their level of development, whether developed, developing or underdeveloped. The housing price index (HPI) measures trends in residential property prices and provides valuable insights into market dynamics. This study aims to model and forecast the HPI in Malaysia. Accurate HPI predictions are essential for informing policy decisions, guiding investment strategies and ensuring sustainable housing market development.

Design/methodology/approach
The autoregressive integrated moving average (ARIMA) model was used to analyse historical housing price data for modelling and forecasting housing prices for different types. The accuracy and reliability of the models and forecasts were assessed using key statistical metrics, including variance (s²), log-likelihood, Akaike information criterion, corrected Akaike information criterion and Bayesian information criterion.

Findings
The findings demonstrate that the ARIMA model improves accuracy in capturing seasonal and trend components in the Malaysian housing market, offering actionable insights for strategic decision-making. In addition, this research presents point and annual changes across different housing types that seek to offer a detailed view of price movements. By providing a reliable five-year forecast of the HPI, this study enables more informed decision-making in housing policy, investment strategy and financial planning.

Practical implications
Policymakers can use these insights to stabilise housing markets, whereas investors and developers can anticipate market movements for better capital allocation. Homeowners and prospective buyers will benefit from understanding future price trends, allowing for more strategic decisions regarding property purchases or sales.

Originality/value
The originality of the study lies in its ability to empirically forecast housing prices for various types of housing for the next five years. This provides valuable guidance for housing-related decisions. This research contributes to the growing literature on real estate forecasting in emerging markets and underscores the relevance of advanced time series models in navigating the complexities of dynamic housing markets.
The impact of forced electricity rationing on shopping and media consumption
Authors: Lappeman James , Dlamini Siphiwe , Zulu Ntsatsi , Wahl Kathryn , Cheteni Priviledge 
Published: February 2025

PurposeThis study provides detailed insights into how electricity rationing affects shopping and media consumption in an emerging market context. Given that electricity rationing (also known as load-shedding) is a regular occurrence in many countries, this research brings a unique consumer perspective.Design/methodology/approachThe study employed a qualitative exploratory design to investigate the effect of electricity rationing on shopping and media consumption. A combined convenience and snowball sampling technique was utilised to select 78 households across various locations in South Africa. Through in-depth interviews and thematic analysis, themes were extracted and explained.FindingsThe findings showed that, for higher-income households, media consumption remained relatively consistent or increased during load-shedding periods. Middle-income families showed a mixed pattern of media use in response to load-shedding. Lower-income households were found to bear the brunt of media-consumption constraints caused by electricity shortages. Consumers are increasingly switching to streaming alternatives to adapt to the limitations of load-shedding. The availability of streaming platforms on mobile devices and laptops and limited household battery backups allows viewers to sidestep disruptions caused by outages.Originality/valueWhile electricity outages are the norm in many countries, the impact on shopping and media consumption is significant. To date, no other research has comprehensively explored the impact of these outages on consumer behaviour in emerging markets.
Is university teaching aligned with the sustainable development goals possible? An approach through the virtual training of university professors
Authors: Espejo-Antúnez Luis , Corrales-Serrano Mario , Zamora-Polo Francisco , Cardero-Durán María de los Ángeles 
Published: February 2025

Purpose
This study aims to determine the degree of knowledge acquired by university professors after receiving virtual training on the sustainable development goals (SDGs) and their relationship with the contents of the subjects taught.

Design/methodology/approach
A 40-h virtual course on SGDs and higher education was designed. To evaluate professor knowledge, a questionnaire was administered to professors from different fields of knowledge. The questionnaire consists of 25 questions divided into two sections: Section 1: Q1–Q8 (knowledge and access to information) and Section 2: Q9–Q25 (the relationship of the subjects taught with the 17 SDGs). The virtual classroom was used to do the questionnaire and it lasted 10 min. The internal consistency of the different constructs was analyzed by Cronbach’s alpha, Kaiser–Meyer–Olkim test and Marlett test. Descriptive and inferential analysis were also performed.

Findings
Statistical analysis showed a high reliability for the constructs (smallest Cronbach’s alpha = 0.908). Virtual teaching to teachers significantly improves the results of Section 1 (Q1–Q8) (p < 0.001) and Section 2 (Q9–Q25) (p < 0.001) of the questionnaire. Teachers aged 40–50 years significantly associate the contents of their subjects with SDG1 (Q9, p = 0.02), SDG2 (Q10, p = 0.00) and SDG8 (Q16, p = 0.04) previous course. In addition, the area of origin may influence knowledge about the SDGs. At the end of the course, there were no significant differences between teachers by age, field of knowledge or academic category.

Originality/value
Virtual training on SDGs unifies the knowledge of university faculty, promoting academic curricula aligned to sustain-able training, regardless of age, gender, academic category or field of knowledge.
Multiscale damage analysis of engineering structures from material level to structural level: a systematic review
Authors: Liu Yawen , Sun Bin , Guo Tong , Li Zhaoxia 
Published: February 2025

PurposeDamage of engineering structures is a nonlinear evolutionary process that spans across both material and structural levels, from mesoscale to macroscale. This paper aims to provide a comprehensive review of damage analysis methods at both the material and structural levels.Design/methodology/approachThis study provides an overview of multiscale damage analysis of engineering structures, including its definition and significance. Current status of damage analysis at both material and structural levels is investigated, by reviewing damage models and prediction methods from single-scale to multiscale perspectives. The discussion of prediction methods includes both model-based simulation approaches and data-driven techniques, emphasizing their roles and applications. Finally, summarize the main findings and discuss potential future research directions in this field.FindingsIn the material level, damage research primarily focuses on the degradation of material properties at the macroscale using continuum damage mechanics (CDM). In contrast, at the mesoscale, damage research involves analyzing material behavior in the meso-structural domain, focusing on defects like microcracks and void growth. In structural-level damage analysis, the macroscale is typically divided into component and structural scales. The component scale examines damage progression in individual structural elements, such as beams and columns, often using detailed finite element or mesoscale models. The structural scale evaluates the global behavior of the entire structure, typically using simplified models like beam or shell elements.Originality/valueTo achieve realistic simulations, it is essential to include as many mesoscale details as possible. However, this results in significant computational demands. To balance accuracy and efficiency, multiscale methods are employed. These methods are categorized into hierarchical approaches, where different scales are processed sequentially, and concurrent approaches, where multiple scales are solved simultaneously to capture complex interactions across scales.
Nexus between competition, concentration and bank risk-taking in Indonesian Islamic banking
Authors: Widarjono Agus , Alam Md. Mahmudul , Rafik Abdur , Afandi Akhsyim , Sidiq Sahabudin 
Published: February 2025

Purpose
This study aims to investigate the relationship between competition and bank risk-taking in Indonesian Islamic banking using linear and non-linear approaches.

Design/methodology/approach
The dynamic panel regression using a two-step system generalized method of moments (GMM) is used to investigate the impact of competition on Z-score and financing loss provision (FLP) as proxies of bank stability and financing risk, respectively. This study uses all Indonesian Islamic banks (IB) from 2015–2020 using quarterly data.

Findings
The competition positively affects the Z-score and negatively influences the FLP. Furthermore, higher concentration is positively linked to the Z-score but is negatively related to the FLP. This study also incorporates a quadratic term of the competition to examine the competition-stability nexus. The findings indicate that the squared competition is negative for the Z-score and positive for the FLP. In general, this study confirms the competition-stability view.

Research limitations/implications
Some policy implications can be drawn from this study. Indonesia needs more players, and they are large IB in the form of full-fledged IB. This research uses all IB in Indonesia, but these results reflect conditions in one country with its own business and political environments. Of course, the findings cannot be generalized for all IB worldwide using cross-country data.

Originality/value
To the best of the authors’ knowledge, this is the first study that examines the non-linear relationship between competition and stability using the adjusted Lerner index in IB.
Navigating the black box: board co-option and environmental innovation
Authors: Gull Ammar Ali , Iqbal Umer , Ghafoor Abdul , Ahmed Ammad 
Published: February 2025

PurposeThis study examines the impact of board co-option on environmental innovation and the moderating effect of firms’ industrial context, ESG compensation and environmental policy stringency (EPS) on this relationship. Finally, we examine the implications of the board co-option and eco-innovation nexus on the market value of firms.Design/methodology/approachThis study employs the system generalized method of moments (GMM) estimator on a longitudinal panel dataset of the US-listed firms to test the proposed hypotheses. The system GMM findings are substantiated using the entropy balancing method and difference-in-differences (DiD) estimations to better establish causality while addressing endogeneity concerns.FindingsThe findings provide evidence that board co-option has a negatively significant relationship with environmental innovation. Further analyses imply that the impact of board co-option on environmental innovation is positively significant among firms operating in environmentally sensitive industries, with ESG compensation for executives, and those operating in environments characterized by high environmental policy stringency. Taken together, these results suggest that industrial context, ESG compensation and environmental policy stringency moderate the impact of board co-option on environmental innovation. The results also reveal that more environmentally innovative firms attain greater market valuation when the board is co-opted.Originality/valueThis study is a novel attempt to contribute to the debate on board composition and its impact on corporate environmental innovation. It complements the existing literature on sustainability governance and accounting by providing an understanding of the impact of board co-option on corporate environmental innovation and highlights the role of regulatory pressure, industrial context and executive compensation structure in shaping this relationship. The findings offer valuable insights for academics, senior management and policymakers.