bluuebunny/crossref_metadata_2025_split huggingface dataset:
Unraveling threats in parasocial relationships: a study on social media influencers
Authors: Farivar Samira , Wang Fang , Turel Ofir 
Published: December 2024

PurposeWith growing concerns about users’ well-being on social media, research stresses the importance of threat appraisals as a crucial first step in motivating self-protective actions. This study, in view of the prevalence of parasocial relationships between followers and social media influencers, aims to unravel the complex dynamics of followers’ threat perceptions within these relationships. Specifically, it examines how factors such as perceived self-efficacy to disengage and the positive affect of social media use influence threat appraisals.Design/methodology/approachA theoretical model is proposed based on appraisal theory to examine the impact of parasocial relationships on threat perception in engagement. It is empirically tested with data from 186 Instagram users.Findings The study reveals an overall positive relationship between parasocial relationships and perceived threat. This relationship is moderated by followers’ perception of self-efficacy to disengage – followers with a high sense of self-efficacy to disengage experience a decrease in threat perception as their parasocial relationships strengthen, whereas followers with a low sense of self-efficacy to disengage report an increase in threat perception with higher levels of parasocial relationships. This interplay is pronounced when followers experience average or below-average levels of positive affect on social media but diminishes when the positive affect is high.Originality/value This work contributes insights into social media influencers, threat appraisal dynamics and digital well-being research. Bridging a critical gap in existing knowledge, the study identifies the pivotal roles of followers’ self-efficacy to disengage and positive affect in shaping their threat appraisals toward parasocial relationships with social media influencers. This not only advances theoretical frameworks but also enhances our understanding of the nuanced dynamics of user reactions to parasocial engagements. Our findings offer practical insights for researchers, practitioners and platform developers aiming to cultivate healthy and responsible social media engagement in the digital era, ultimately contributing to individual well-being.
Artificial intelligence adoption and revenue growth in European SMEs: synergies with IoT and big data analytics
Authors: Ardito Lorenzo , Filieri Raffaele , Raguseo Elisabetta , Vitari Claudio 
Published: December 2024

PurposeThe conventional notion that adopting Artificial Intelligence (AI) positively affects firm performance is often confronted with various examples of failures. In this context, large-scale empirical evidence of the economic performance implications of adopting AI is poor, especially in the context of Small and Medium Sized Enterprises (SMEs). Drawing upon the Resource-Based View and the Digital Complementary Asset literature, we assessed whether the adoption of AI affects SMEs’ revenue growth.Design/methodology/approachFirst, we examine the relationship between the adoption of AI and SMEs’ revenue growth. Second, we assess whether AI complements the Internet of Things (IoT) and Big Data Analytics (BDA). We use firm-level data from the European Commission in 2020 on 11,429 European SMEs (Flash Eurobarometer 486).FindingsAmong the key findings, we found that ceteris paribus, the adoption of AI positively affects SMEs’ revenue growth and, in conjunction with IoT and BDA, appears to be even more beneficial.Originality/valueOur results suggest that AI fosters SME growth, especially in combination with IoT and BDA. Thus, SME managers should be aware of the positive impacts of investments in AI and make decisions accordingly. Likewise, policymakers are aware of the positive effects of SMEs’ reliance on AI, so they may design policies and funding schemes to push this digitalization of SMEs further.
FinTech and CO2 emission: evidence from (top 7) mobile money economies in Africa
Authors: Coffie Cephas Paa Kwasi , Yeboah Frederick Kwame , Emuron Abraham Simon Otim , Ahiabenu Kwami 
Published: December 2024

Purpose
The impact of FinTech in sub-Saharan Africa has primarily been limited to financial inclusion. Contrarily, this study aims to deviate from this norm to estimate how FinTech affects carbon emissions in the subregion. This provides policy recommendations for FinTech regulators, service providers and practitioners to consider optimal products and services that reduce carbon emissions.

Design/methodology/approach
A balanced panel data set from 2009 to 2020 is used and estimated with the fully modified ordinary least squares estimator after checking for cross-sectional dependence, unit root, stationarity and cointegration.

Findings
Results from the estimation suggest a negatively significant relationship between financial technology and carbon emissions in these countries. However, domestic credit to the private sector revealed a statistically insignificant relationship with carbon emissions for the same period. Further, foreign direct investment reduces carbon emissions but gross domestic product and trade openness increase carbon emissions in these countries.

Originality/value
The impact of FinTech in sub-Saharan Africa has primarily been limited to financial inclusion. Contrarily, this study deviates from this norm and estimates how FinTech affects carbon emissions in the subregion.
Pricing decisions and fairness concerns: supply chain power structures
Authors: Han Bing , Chi Tianze , Hu Fangjie , Wang Mengjun 
Published: December 2024

PurposeThis paper divides the dyadic supply chain into three power structures according to the relative channel power of the supply chain members and consequently examines the optimal supply chain pricing decisions when both suppliers and retailers are concerned with fairness issues.Design/methodology/approachThree models are constructed, namely the Stackelberg game model with the supplier as the leader, the Nash game model with the balance of power and another Stackelberg game model with the retailer as the leader. The equilibrium solutions are solved, and their results are analyzed.FindingsThe retail price of a product increases with an increase in the fairness concerns of the leader in a supply chain in which the supplier or retailer is the leader, while the fairness concerns of the member with less channel power have no effect on the retail price. In a power-balanced supply chain, both suppliers and retailers increase their retail prices as their fairness concerns increase. The relative size of the members’ fairness concerns affects member profits and total supply chain profits.Originality/valueThe main contributions are as follows: First, this paper proposes a new approach to studying supply chain pricing strategy, considering fairness concerns and power structure. Secondly, three game models are constructed. The Nash equilibrium solution is introduced to study the fairness of supply chain participants in pricing decisions and overall supply chain profitability. Finally, the supply chain management theory is expanded by this study on pricing decisions and supply chain performance.
Leveraging green artificial intelligence for green competitive advantage: testing a mediated moderation model
Authors: Salehzadeh Reza , Javani Maliheh , Esmailian Hassan 
Published: December 2024

PurposeIn today’s competitive business landscape, organizations are increasingly recognizing the strategic advantage of implementing sustainable practices to gain a competitive edge. This study aims to investigate the effect of green artificial intelligence (AI) on achieving a green competitive advantage, examining the mediating roles of green organizational learning, green product innovation and green process innovation. Additionally, the research explores the moderating role of perceived green climate in the relationship between green AI and these mediating factors.Design/methodology/approachThis research examined companies in Isfahan, Iran, that have varying levels of artificial intelligence adoption within their business processes. The target population consisted of 148 senior managers from these companies. This study uses structural equation modeling to examine the proposed model.FindingsGreen AI positively impacted green organizational learning and green process innovation but not green product innovation. In addition, the results showed that green organizational learning, green product innovation and green process innovation had positive effects on green competitive advantage. Finally, the results showed that the perceived green climate did not play a moderating role in the relationship between green AI and these mediating factors.Practical implicationsOrganizations should prioritize green AI initiatives, foster a culture of green learning and invest in green innovation to achieve sustainable growth and outpace competitors in the environmentally conscious marketplace.Originality/valueThis study positions itself at the forefront of research on green AI and green competitive advantage. It offers a unique framework by examining the combined effects of green AI, green learning and both product and process innovation on achieving a sustainable competitive advantage.
Screening study of hydroxytyrosol metabolites from in vitro fecal fermentation and their interaction with intestinal barrier repair receptor AhR
Authors: Song Yuqing , Li Mengting , Liu Jingle , Wang Juan , Zhou Aimei , Cao Yong , Duan Shan , Wang Qun 
Published: December 2024

AbstractOlive oil polyphenol hydroxytyrosol (HT) significantly repairs intestinal barrier function, but its absorption in the stomach and small intestine is limited. The metabolites of unabsorbed HT that reach the colon are crucial, yet their effects on colonic microbiota and intestinal barrier repair remain unclear. This study utilized in vitro simulated digestion and colonic fecal fermentation to investigate HT's digestion and fermentation. Results indicated that 79.25% of HT potentially reached the colon intact. Further 16S rDNA, targeted, and untargeted metabolomics analyses showed that HT can be decomposed by colonic microbiota, producing aromatic hydrocarbon metabolites and regulating gut microbiota structure. It promotes the growth of gut microbiota, such as Bacteroides, Faecalibacterium, Klebsiella, and Lachnospira, which degrade HT. Additionally, HT's intervention conversely affected the production of tryptophan‐derived metabolites and short‐chain fatty acids (SCFAs). Subsequently, computer‐simulated molecular docking technology was used to simulate the binding affinity between HT metabolites and derived metabolites and the intestinal barrier repair‐related receptor aryl hydrocarbon receptor (AhR). Indole‐3‐acetic acid, indole‐3‐acetaldehyde, skatole, kynurenine, and homovanillic acid could tightly bind to the amino acid residues of the AhR receptor, with binding energies all ˂−6.0 kcal/mol, suggesting that these metabolites may enhance the intestinal barrier function through the AhR signaling pathway.
Genetic diversity, genotyping and evolutionary history of the global population of Orthotospovirus tomatomaculae genomic segments
Authors: Siampour Majid , Noorbakhsh Sajedeh , Izadpanah Keramatollah 
Published: December 2024

AbstractTomato spotted wilt virus (Orthotospovirus tomatomaculae; TSWV) is a destructive pathogen that affects over 1000 plant species worldwide. To elucidate its evolutionary mechanisms, genetic diversity and emergence timeline, we examined around 100 TSWV isolates with complete genome sequences available in GenBank. This study also included the complete genome of a TSWV isolate, IRP4, which has recently been implicated in an outbreak affecting greenhouse‐grown bell peppers in Iran. Pairwise genetic divergence analysis revealed varying levels of genetic differences among TSWV RNA segments. Phylogenetic and sequence analysis determined that the global TSWV population consists of three major groups based on each of the three RNA segments (L, M, and S). Results suggested multiple introductions of the virus into different regions, indicating that the geographical origin of the isolates is not the sole factor determining their phylogenetic grouping. The large incongruences observed in the phylogeny of the TSWV segments and the analysis of genetic diversity patterns highlight extensive reassortment events in TSWV. As a result, 11 genotypes were identified within the TSWV population. The Iranian IRP4 isolate, along with nine other isolates from Europe, Asia, and South America shared a common genotype designated L3‐M1‐S1. This suggests that this potentially reassortant genotype has undergone long‐distance intercontinental movement. Similar to IRP4, the majority of TSWV isolates with the L3‐M1‐S1 genotype were also obtained from pepper, suggesting a potential role of the host plant in the evolution of this genotype. Furthermore, temporal analysis suggests that the existing population of TSWV, circulating between 1996 and 2023, originated from a common ancestor that existed 107–284 years ago. The population size of TSWV experienced a significant expansion for 10–15 years since 1980 and then remained constant until recently.
Single‐centre retrospective review of dupilumab‐induced ocular surface disease in an Australian adult cohort with moderate‐to‐severe atopic dermatitis
Authors: Arasu Alexis , Awad Andrew , Tran Vanessa , Ross Gayle 
Published: December 2024

AbstractTreatment and management outcomes or patients with atopic dermatitis has significantly improved with the inclusion of dupilumab into the pharmaceutical benefits scheme, as a safe and effective treatment. Ocular surface disease remains one of the most frequent adverse events seen with dupilumab, and impacts quality of life and can interrupt treatment. This retrospective review aims to further characterise the experience and risk factors of dupilumab‐induced ocular surface disease to inform management and support long‐term use for patients, improving overall treatment outcomes.
Towards standardization of person‐reported outcomes (PROs) in pediatric diabetes research: A consensus report
Authors: Barnard‐Kelly Katharine , Marrero David , de Wit Maartje , Pouwer Frans , Khunti Kamlesh , Hermans Norbert , Pierce Jessica S. , Laffel Lori , Holt Richard I. G. , Battelino Tadej , Naranjo Diana , Fosbury Jacqueline , Fisher Lawrence , Polonsky William , Weissberg‐Benchell Jill , Hood Korey K. , Schnell Oliver , Messer Laurel H. , Danne Thomas , Nimri Revital , Skovlund Soren , Mader Julia K. , Sherr Jennifer L. , Schatz Desmond , O'Neill Simon , Doble Emma , Town Marissa , Lange Karin , de Beaufort Carine , Gonder‐Frederick Linda , Jaser Sarah S. , Liberman Alon , Klonoff David , Elsayed Nuha A. , Bannuru Raveendhara R. , Ajjan Ramzi , Parkin Christopher , Snoek Frank J. 
Published: December 2024

AbstractBackgroundDiabetes ranks among the most common chronic conditions in childhood and adolescence. It is unique among chronic conditions, in that clinical outcomes are intimately tied to how the child or adolescent living with diabetes and their parents or carers react to and implement good clinical practice guidance. It is widely recognized that the individual's perspective about the impact of trying to manage the disease together with the burden of self‐management should be addressed to achieve optimal health outcomes. Standardized, rigorous assessment of behavioural and mental health outcomes is crucial to aid understanding of person‐reported outcomes alongside, and in interaction with, physical health outcomes. Whilst tempting to conceptualize person‐reported outcomes as a focus on perceived quality of life, the reality is that health‐related quality of life is multi‐dimensional and covers indicators of physical or functional health status, psychological well‐being and social well‐ being.MethodsIn this context, this Consensus Statement has been developed by a collection of experts in diabetes to summarize the central themes and lessons derived in the assessment and use of person‐reported outcome measures in relation to children and adolescents and their parents/carers, helping to provide a platform for future standardization of these measures for research studies and routine clinical use.ResultsThis consensus statement provides an exploration of person‐reported outcomes and how to routinely assess and incorporate into clincial research.
Lateralization‐specific adaptation in auditory cortical evoked potentials: Comparison with frequency‐specificity
Authors: İlhan Barkın , Kurt Saliha , Bolay Yavuz , Ungan Pekcan 
Published: December 2024

Abstract‘Opponent channels model’ (OCM) is the widely accepted model for cortical representation of sound lateralization. Stimulus‐specific ‘release from adaptation’ (RFA) in cortical responses has been used in previous studies to test the predictions of this model. However, these attempts were shown to be prone to confounds of spurious responses such as those to auditory motion and sound onset. The present study aims to determine whether a multiple‐adaptor RFA algorithm could be employed for relatively confound‐free quantification of the population response of lateralization‐specific auditory cortical neurons, and provide useful data for estimation of the OCM hemifield tuning curves. Two experiments were conducted on 12 volunteers with normal hearing. In Exp.1, quadruple tone pips of either low or high frequency were presented as adaptor, followed by a single tone pip of either frequency as probe. In Exp.2, tone pips were replaced with dichotic click train pips with left‐leading and right‐leading interaural time difference (ITD). Frequency‐ and ITD‐specific RFA in cortical responses N1 and P2 was quantified using global field magnitude difference between ERPs to mismatched and matched adaptor‐probe pairs.RFA level measured was lower for ITD mismatch than frequency mismatch. Nonetheless, it allowed measurement of ITD‐specific cortical neurons' population response, without any spurious response confound. We proposed a method for extraction of ITD‐specific response magnitude from the N1 response to a lateralized sound. Using it, one can reliably measure the activity of lateralization‐specific cortical neurons, i.e. elicited by moderate ITD changes. This allows estimation of hemifield tuning curves in OCM using ERP data.
Input Tariff Cuts and the Spatial Distribution of Skilled Labor: Evidence From China
Authors: Liu Wenhan , Xiao Wei , Qin Zhilong 
Published: December 2024

ABSTRACTAs China's economy advances toward high‐quality development, how to promote the rational spatial distribution of skilled labor to achieve sustainable regional economic growth has become an urgent issue. This study utilizes microdata from the 2000–2015 Chinese census and tariff data from China covering the same period to empirically regress input tariff cuts on changes in the proportion of skilled labor in cities. The results show that for every 1% decrease in input tariffs, the proportion of skilled labor in cities increases by 0.78%, accounting for 15.22% of the spatial distribution of skilled labor. Mechanism analysis indicates that input tariff cuts facilitate technological progress and subsequently increase skilled labor demand. From an equilibrium perspective, increased skilled labor demand attracts skilled worker inflows, thereby increasing the proportion of skilled labor in cities. Additionally, input tariff cuts have a more significant impact on cities with low trade costs, a high historical proportion of skilled labor, and high labor market flexibility. These findings provide favorable evidence of the micro‐level impact of input tariff cuts on regional skilled labor markets, offering important policy insights into how developing countries similar to China can optimize the spatial distribution of skilled labor through input tariffs.
Papillary and ductal patterns of mesonephric‐like adenocarcinomas are often overlooked: a retrospective revaluation of over 1000 endometrial carcinomas
Authors: Akbari Ardalan , Pors Jennifer , Lum Amy , Leung Samuel , Cochrane Dawn , Jamieson Amy , McAlpine Jessica , Kommoss Stefan , Huvila Jutta , Huntsman David , Talhouk Aline , Singh Naveena , Gilks C Blake , Hoang Lynn 
Published: December 2024

AimsMesonephric‐like adenocarcinoma (MLA) of the endometrium is often a diagnostic challenge, due to its morphological resemblance to other more common Müllerian neoplasms. This study aimed to retrospectively identify overlooked MLA in a large endometrial carcinoma cohort, using a combination of immunohistochemistry (IHC), morphology and KRAS sequencing.Methods and resultsIHC was conducted on 1094 endometrial carcinomas, identifying 16 potential MLA cases based on GATA3+ and/or TTF1+ and ER− staining patterns, which subsequently underwent detailed histological review, KRAS sequencing and ProMisE molecular classification. Of the IHC screen‐positive cases, one was positive for both GATA3 and TTF1, nine were positive for GATA3 only and six were positive for TTF1 only. All IHC screen‐positive cases were POLE wild‐type. All five tumours in the NSMP category showed morphological features of MLA, while the three MMRd and eight p53abn tumours did not show MLA morphology. The five cases diagnosed as MLA on review were all originally diagnosed as low‐grade endometrioid adenocarcinoma probably because of rare morphological patterns, being predominantly papillary or ductal. Four of the five cases harboured a KRAS mutation.ConclusionThis study highlights the importance of a comprehensive diagnostic approach for accurately identifying endometrial MLA and for pathologists to be aware of papillary and ductal patterns in endometrial carcinoma assessment. Further exploration into the molecular landscape of MLA is essential for refining diagnostic criteria and developing targeted therapies.
Nucleases: From Primitive Immune Defenders to Modern Biotechnology Tools
Authors: Hernandez Frank J. 
Published: December 2024

ABSTRACTThe story of nucleases begins on the ancient battlefields of early Earth, where simple bacteria fought to survive against viral invaders. Nucleases are enzymes that degrade nucleic acids, with restriction endonucleases emerging as some of the earliest defenders, cutting foreign DNA to protect their bacteria hosts. However, bacteria sought more than just defence. They evolved the CRISPR‐Cas system, an adaptive immune mechanism capable of remembering past invaders. The now‐famous Cas9 nuclease, a key player in this system, has been harnessed for genome editing, revolutionising biotechnology. Over time, nucleases evolved from basic viral defence tools into complex regulators of immune function in higher organisms. In humans, DNases and RNases maintain immune balance by clearing cellular debris, preventing autoimmunity, and defending against pathogens. These enzymes have transformed from simple bacterial defenders to critical players in both human immunity and biotechnology. This review explores the evolutionary history of nucleases and their vital roles as protectors in the story of life's defence mechanisms.