bluuebunny/crossref_metadata_2025_split huggingface dataset:
Characterization of a nosocomial outbreak caused by VIM-1Klebsiella michiganensisusing Fourier-Transform Infrared (FT-IR) Spectroscopy
Authors: Rodriguez-Temporal David , Sánchez-Cueto María , Buenestado-Serrano Sergio , Blázquez-Sánchez Mario , Cercenado Emilia , Gutiérrez-Pareja Mark , Molero-Salinas Andrea , López-Camacho Elena , Muñoz Patricia , García de Viedma Darío , Pérez-Lago Laura , Rodríguez-Sánchez Belén 
Published: July 2024

ABSTRACTHealthcare-associated infections (HAIs) are a significant concern worldwide due to their impact on patient safety and healthcare costs.Klebsiellaspp., particularlyKlebsiella pneumoniaeandKlebsiella oxytoca, are frequently implicated in HAIs and often exhibit multidrug resistance mechanisms, posing challenges for infection control. In this study, we evaluated Fourier-transform Infrared (FT-IR) spectroscopy as a rapid method for characterizing a nosocomial outbreak caused by VIM-1-producingK. oxytoca.A total of 47 isolates, including outbreak strains and controls, were collected from Hospital Universitario Gregorio Marañón, Spain and the University Hospital Basel, Switzerland. FT-IR spectroscopy was employed for bacterial typing, offering rapid and accurate results compared to conventional methods like pulsed-field gel electrophoresis (PFGE) and correlating with whole-genome sequencing (WGS) results. The FT-IR spectra analysis revealed distinct clusters corresponding to outbreak strains, suggesting a common origin.Subsequent WGS analysis identifiedKlebsiella michiganensisas the causative agent of the outbreak, challenging the initial assumption based on FT-IR results. However, both FT-IR and WGS methods showed high concordance, with an Adjusted Rand index (AR) of 0.882 and an Adjusted Wallace coefficient (AW) of 0.937, indicating the reliability of FT-IR in outbreak characterization.Furthermore, FT-IR spectra visualization highlighted discriminatory features between outbreak and non-outbreak isolates, facilitating rapid screening in case and outbreak is suspected.In conclusion, FT-IR spectroscopy offers a rapid and cost-effective alternative to traditional typing methods, enabling timely intervention and effective management of nosocomial outbreaks. Its integration with WGS enhances the accuracy of outbreak investigations, demonstrating its utility in clinical microbiology and infection control practices.
Small Extracellular Vesicles from Human Bone Marrow Mesenchymal Stromal Cells enhance migration and regulate gene expression of reparative mechanisms in human dermal fibroblasts
Authors: Lei Rui , Borges da Silva Tamiris , Cui Zhanfeng , Ye Hua 
Published: July 2024

AbstractStudies have showed that mesenchymal stromal cells (MSCs) could secrete a variety of bioactive particles, including small extracellular vesicles (sEVs), a type of membrane bound vesicle produced by cells, that might be a key intermediate to the beneficial paracrine effects of MSC therapy. In this study, we harvested the conditioned medium (CM) from both human bone marrow mesenchymal stromal cells (hBM-MSCs) and normal human dermal fibroblasts (NHDFs), fractionated CM of each into the sEV fraction and non-small extracellular vesicle (NsEV) fraction and compared their functions on NHDF-based migration and proliferation assays, as crucial processes in wound healing, coupled with transcriptomic analysis through mRNA sequencing to assess the regulation on gene expression of the recipient NHDFs by secretome exposure. Our findings show that both sEV and NsEV as well as CM from hBM-MSCs showed an overall promotive effect on migration behaviour of NHDFs, but MSC-sEV seems to be more potent for NHDF migration among different MSC secretome fractions and is also superior in effect to the corresponding sEVs produced by the recipient NHDFs (HDF-sEV). Gene ontology analysis revealed enrichment of pathways related to migration, corroboratingin vitroresults; changes in genes within the regulation of proliferation pathway were also significant. Our study provides referential significance for the choice of cellular secretome fractions to be used in wound healing studies and trials. The secretome fractionation and functional comparison strategy using cell-based model and comparative transcriptomics analysis would be a useful tool for comprehensive functional evaluation of cellular secretome.
DdmDE eliminates plasmid invasion by DNA-guided DNA targeting
Authors: Yang Xiao-Yuan , Shen Zhangfei , Wang Chen , Nakanishi Kotaro , Fu Tian-Min 
Published: July 2024

AbstractHorizontal gene transfer is a key driver of bacterial evolution, but it also presents severe risks to bacteria by introducing invasive mobile genetic elements. To counter these threats, bacteria have developed various defense systems, including prokaryotic Argonautes (pAgo) and theDNADefenseModule DdmDE system. Through biochemical analysis, structural determination, andin vivoplasmid clearance assays, we elucidate the assembly and activation mechanisms of DdmDE, which eliminates small, multicopy plasmids. We demonstrate that DdmE, a pAgo-like protein, acts as a catalytically inactive, DNA-guided, DNA-targeting defense module. In the presence of guide DNA, DdmE targets plasmids and recruits a dimeric DdmD, which contains nuclease and helicase domains. Upon binding to DNA substrates, DdmD transitions from an autoinhibited dimer to an active monomer, which then translocates along and cleaves the plasmids. Together, our findings reveal the intricate mechanisms underlying DdmDE-mediated plasmid clearance, offering fundamental insights into bacterial defense systems against plasmid invasions.
Fine-tuning large language models for effective nutrition support in residential aged care: a domain expertise approach
Authors: Alkhalaf Mohammad , Shen Jun , Chang Hui-Chen (Rita) , Deng Chao , Yu Ping 
Published: July 2024

AbstractPurposeMalnutrition is a serious health concern, particularly among the older people living in residential aged care facilities. An automated and efficient method is required to identify the individuals afflicted with malnutrition in this setting. The recent advancements in transformer-based large language models (LLMs) equipped with sophisticated context-aware embeddings, such as RoBERTa, have significantly improved machine learning performance, particularly in predictive modelling. Enhancing the embeddings of these models on domain-specific corpora, such as clinical notes, is essential for elevating their performance in clinical tasks. Therefore, our study introduces a novel approach that trains a foundational RoBERTa model on nursing progress notes to develop a RAC domain-specific LLM. The model is further fine-tuned on nursing progress notes to enhance malnutrition identification and prediction in residential aged care setting.MethodsWe develop our domain-specific model by training the RoBERTa LLM on 500,000 nursing progress notes from residential aged care electronic health records (EHRs). The model’s embeddings were used for two downstream tasks: malnutrition note identification and malnutrition prediction. Its performance was compared against baseline RoBERTa and BioClinicalBERT. Furthermore, we truncated long sequence text to fit into RoBERTa’s 512-token sequence length limitation, enabling our model to handle sequences up to1536 tokens.ResultsUtilizing 5-fold cross-validation for both tasks, our RAC domain-specific LLM demonstrated significantly better performance over other models. In malnutrition note identification, it achieved a slightly higher F1-score of 0.966 compared to other LLMs. In prediction, it achieved significantly higher F1-score of 0.655. We enhanced our model’s predictive capability by integrating the risk factors extracted from each client’s notes, creating a combined data layer of structured risk factors and free-text notes. This integration improved the prediction performance, evidenced by an increased F1-score of 0.687.ConclusionOur findings suggest that further fine-tuning a large language model on a domain-specific clinical corpus can improve the foundational model’s performance in clinical tasks. This specialized adaptation significantly improves our domain-specific model’s performance in tasks such as malnutrition risk identification and malnutrition prediction, making it useful for identifying and predicting malnutrition among older people living in residential aged care or long-term care facilities.
Ownership structure and financial distress: is the tale from Sub-Saharan Africa different?
Authors: Abdulkadir Mohammed , Kariuki Samuel Nduati , Kariuki Peter Wang’ombe 
Published: July 2024

PurposeThe paper investigates the effect of ownership structure on the financial distress of firms listed in sub-Saharan Africa.Design/methodology/approachUsing secondary data from 106 non-financial firms listed in 9 selected SSA countries from 2016 to 2021, the research using paired t-tests and conditional logistic regression model analysed a sample of 174 distressed observations matched with 174 non-distressed observations.FindingsT-tests determined significant differences between distressed and non-distressed groups concerning institutional, foreign, and local ownership. Conditional logistic results established that institutional, foreign, and state ownership significantly reduce distress. However, managerial ownership does not influence financial distress while a significant positive relationship is observed between local ownership and financial distress.Originality/valueThis is the first study to investigate the influence of ownership structure, including local ownership, on financial distress in SSA, employing a unique methodology of matched design and conditional logistic regression analysis. Furthermore, the paper presents cross-country evidence from emerging frontier markets, highlighting the importance of governance frameworks in firms’ stability.
MD-LDA: a supervised LDA topic model for identifying mechanism of disease in TCM
Authors: Li Meiwen , Xia Liye , Wu Qingtao , Wang Lin , Zhu Junlong , Zhang Mingchuan 
Published: July 2024

PurposeIn traditional Chinese medicine (TCM), the mechanism of disease (MD) constitutes an essential element of syndrome differentiation and treatment, elucidating the mechanisms underlying the occurrence, progression, alterations and outcomes of diseases. However, there is a dearth of research in the field of intelligent diagnosis concerning the analysis of MD.Design/methodology/approachIn this paper, we propose a supervised Latent Dirichlet Allocation (LDA) topic model, termed MD-LDA, which elucidates the process of MDs identification. We leverage the label information inherent in the data as prior knowledge and incorporate it into the model’s training. Additionally, we devise two parallel parameter estimation algorithms for efficient training. Furthermore, we introduce a benchmark MD identification dataset, named TMD, for training MD-LDA. Finally, we validate the performance of MD-LDA through comprehensive experiments.FindingsThe results show that MD-LDA is effective and efficient. Moreover, MD-LDA outperforms the state-of-the-art topic models on perplexity, Kullback–Leibler (KL) and classification performance.Originality/valueThe proposed MD-LDA can be applied for the MD discovery and analysis of TCM clinical diagnosis, so as to improve the interpretability and reliability of intelligent diagnosis and treatment.
Sling Aircraft: gearing up for the big time
Authors: Murimbika McEdward , Beswick Claire , Thomson Richard 
Published: July 2024

Learning outcomes
At the end of this case study discussion, students should be able to critically analyse the strategic options for a global small and medium-sized enterprise seeking competitive advantage in a highly specialised industry, determine the strategic management and operational approaches to introducing a new product line using the case study options as an example, determine the best investment approach for a global operational strategy considering the financial analysis of associated costs and the best form of financial capital/investment in terms of risks and control references and carry out a financial analysis and make evidence-based decisions with respect to addressing how strategic recommendations will affect the future of a firm’s competitive advantage.

Case overview/synopsis
In 2021, Mike Blyth and his business partners, James Pitman and Andrew Pitman, were facing new challenges the business had never faced before. Despite the global upheaval and economic devastation caused by the COVID-19 pandemic, 2020 had been a productive year for the South African small-aircraft manufacturer. Globally, sales of Sling Aircraft’s aeroplanes had been good and the company had just finished a development prototype of a high-wing four-seater. Blyth, Andrew and James felt certain that there was space in the market for a five-seater aeroplane and they were meeting to discuss how to set up the business for further success. The strategic choices required to take the company in the new direction seemed clear and obvious, but it became apparent that they faced a dilemma regarding how to set up or restructure the company for success by exploiting the new opportunity without putting all of the hard work of the past 15 years in jeopardy.

Complexity academic level
This teaching activity is aimed at Master of Business Administration (MBA) and Master of Management.

Supplementary materials
Teaching notes are available for educators only.

Subject code
CSS 11: Strategy.
Students' reflections of quality (RoQ) in work-integrated learning (WIL): a systematic review and framework
Authors: Eady Michelle J. , Drewery David , Burney Monica , Li Wincy , Livingstone Kimberley 
Published: July 2024

PurposeIn light of the expanding prominence of work-integrated learning (WIL), the pedagogical model that integrates work experiences into an academic curriculum, this paper presents a systematic review that uncovers little-explored students’ reflections of quality (RoQ).Design/methodology/approachDrawing on the concept of wayfinding rocks and Bronfenbrenner’s (1979) ecological systems theory, the “students’ RoQ (pronounced [ROK]) WIL model” offers guidance for future research, policy development and educational interventions aimed at optimizing students' experiences of WIL.FindingsThis paper highlights RoQ WIL through student voice. The outcomes offer a model, contributing insights for institutions, employers and students involved in WIL experiences.Research limitations/implicationsWhile the study addresses specific limitations such as the use of specific search terms and potential biases, future research is needed to explore cultural capital’s influence on WIL quality. A focus on broadening the scope of data collection to include a more comprehensive range of student perspectives is needed.Practical implicationsThe paper suggests practical implications for institutions, employers and educators in designing WIL programs that prioritize student perspectives, ultimately enhancing the quality of WIL experiences.Originality/valueBy focusing on students' RoQ in WIL, this paper fills a significant gap in the literature and provides a foundation for future research and practice in optimizing WIL engagement and outcomes.
Designing a model for enhancing intention to accept renewable energy technologies in rural communities of Ilam province, Iran
Authors: Torfei Monfared Kobra , Vahedi Marjan , Eshraghi Samani Roya , Moradnezhadi Homayoon 
Published: July 2024

Purpose
The purpose of this research is to investigate factors influencing the intention of villagers to use renewable energy. In this regard, by using the modified model of planned behavior, perceived behavioral control factors, perceived usefulness, perceived ease, mental norm and attitude toward energy sources for the intention of villagers to use energy sources. Therefore, the impact of each of these five variables was investigated in the form of research hypotheses.

Design/methodology/approach
This research has been done using a quantitative paradigm and a descriptive-correlation method. The statistical population of the study consisted of households (384) living in rural areas of Ilam province. A multistage cluster method was used to select the sample size. The data collection tool was a researcher-made questionnaire that was developed based on the research background and research problem. Face validity of the research tool by professors of Islamic Azad University of Ilam and construct validity and reliability of research tools were confirmed by Cronbach’s alpha coefficient and composite reliability. Data were analyzed statistically using SPSS26 and SmartPLS3 software.

Findings
The results showed that the intention to use renewable energies (REs) among the rural peoples of Ilam province is affected by factors such as mental norms, attitude, perceived usefulness and perceived behavioral control and there is a positive and significant relationship between them.

Originality/value
In Iran, there is a lot of potential for usage of RE in rural communities, but compared to fossil fuels, had a small share in the current energy supply (Rezaei et al., 2022). RE technologies have not been sufficiently accepted and used by Iranian rural people (Rezaei and Ghafranfarid, 2018). Se the public acceptance of RE technologies is vital for successful process energy transfer (Huijts et al., 2012), non-acceptance of RE by society is a major obstacle to establishing RE technologies in Iran (Savari and Razmavar, 2022). It is expected that this research will fill the gap in the research literature.
Impact of climate risk on financial performance – evidence from select energy companies from select G-20 countries
Authors: Bauri Somnath , Mondal Amitava , Fatma Ummatul 
Published: July 2024

Purpose
The recent meeting of G-20 world leaders, held in New Delhi, in 2023, highlighted that the physical effect of climate change has considerable macro-economic costs at the national and global levels and they have also pledged to accelerate the clean, sustainable and inclusive energy transition along a variety of pathways. Climate change could pose various emerging risks to the firm’s operational and financial activities, specifically for those which are belonging to the energy sector. Thus, this study aims to investigate the impact of climate risks on the financial performance of select energy companies from G-20 countries.

Design/methodology/approach
The study considered 48 energy companies from G-20 countries as the sample for the period of 2017 to 2021. To measure the climate change-related physical risks, the study has considered the ND-GAIN climate vulnerability score and the firm’s financial performance has been measured by return on assets, return on equity, return on capital used and price-to-book ratio. To examine the impact of climate risks on the financial performance of the sample companies, the authors have used pooled ordinary least squares (OLS) and fixed/random effect regression analysis and required data diagnosis tests are also performed.

Findings
The empirical results suggested that climate risks negatively impacted the financial performance of the sample companies. The market performances of the firms are also being impacted by the physical climate change. The results of panel data regression analysis also confirmed the robustness of the empirical results derived from the pooled OLS analysis suggesting that firms that operated in a less climate-risky country, financially performed better than the firms that operated in a more climate-risky country.

Practical implications
The paper has significant practical implications like it could be helpful for the policymakers, investors, suppliers, researchers and other stakeholders in developing deeper insights about the impact of climate risks on the energy sectors from an international perspective. This study may also help the policymakers in developing policies for the management of climate risk for the energy sector.

Originality/value
This study adds insights to the existing literature in the area of climate risks and firm’s financial performance. Moreover, this may be the first study that attempts to evaluate the impact of climate risks on the financial performance of select energy companies from the G-20’s perspective.
Tourist acceptance of using ride-sharing services in a tourism destination: hedonia vs eudaimonia and technophilia vs technophobia
Authors: Herjanto Halimin , Amin Muslim , Ali Faizan , Cobanoglu Cihan , Djalil Muslim A. A. 
Published: July 2024

Purpose
This study aims to examine how affective and technological attitudes influence tourists’ intentions to use ride-sharing services. The authors also explore the moderating effects of perceived freedom and digital literacy on these relationships.

Design/methodology/approach
The sample consisted of local and international tourists using ride-sharing services in Bali, Indonesia. The authors used convenience sampling to distribute questionnaires to the respondents, collecting 258 responses. Out of these, 222 responses were fully completed and suitable for analysis.

Findings
The results revealed that hedonia, eudaimonia, technophilia and technophobia each differently influence tourists’ intentions to use ride-sharing services. Perceived freedom and digital literacy moderate the strength of these relationships.

Research limitations/implications
This research builds on previous studies by investigating how various aspects of happiness affect tourists' intentions to use ride-sharing services. It also emphasizes the role of perceived freedom and digital literacy in moderating the relationship between happiness, technology adoption attitudes and ride-sharing intentions.

Originality/value
This study contributes to the existing ride-sharing literature by integrating two dimensions of affective attitude (hedonia and eudaimonia) and technology adoption attitude (technophilia and technophobia) to examine their effects on tourists’ intentions to use ride-sharing services.
Development and psychometric validation of a scale for sources of resistance to change in higher education institutions
Authors: González Favián , Pardo-del-Val Manuela , Redondo Ana 
Published: July 2024

PurposeThe purpose of the present study was to develop a measurement model to identify sources of resistance to change (RC) based on a previous systematic review.Design/methodology/approachThe sample comprised 121 participants (faculty, students, graduates, and employees). Twenty-three items were assessed in four distinct stages: observation, exploration, confirmation, and communication. Exploratory and confirmatory factor analysis ensured the validity and reliability of the measurement process.FindingsThe final 14-item model consisted of four groups: “Personalities averse to change”; “Limited participation in the change process”; “Dominant sociocultural predisposition”; and “Weak managerial commitment to change.”Practical implicationsIt is hoped that the study will encourage further diagnostic examinations and assessments of the structural relationships associated with RC.Originality/valueThe present study expands our understanding of RC source typologies, the majority of which have focused on the individual and the organization. Higher education institutions bear a responsibility to initiate change to align with evolving environmental demands, but their endeavors are often subject to obstacles and delays stemming from individual and collective influences. To manage efficiently the conceptualization, planning, implementation, and management of change initiatives, we must comprehend and assess the primary sources of RC within such institutions.