bluuebunny/crossref_metadata_2025 huggingface dataset:
Leveraging Artificial Intelligence as a Safety Net for Incidentally Identified Lung Nodules at a Tertiary Center
Authors: Woodhouse Palina , Paez Rafael , Meyers Patrick , Lentz Rob J , Shoajaee Samira , Sharp Kenneth , Baldi Nikki , Maldonado Fabien , Grogan Eric L
Published: January 2025

Background:

Artificial intelligence (AI)-powered platforms may be used to ensure that clinically significant lung nodules receive appropriate management. We studied the impact of a commercially available AI natural language processing tool on detection of clinically significant indeterminate pulmonary nodules (IPNs) based on radiology reports and provision of guideline-consistent care.

Study Design:

All computed tomography (CT) scans performed at a single tertiary care center in the outpatient or emergency room setting between 20-Feb-2024 and 20-March-2024 were processed by the AI natural language processing algorithm. CT radiology reports mentioning a lung nodule or focal indeterminate lesion were flagged. All flagged reports were reviewed by a lung nodule expert two weeks after nodule identification. IPNs were classified as “appropriately followed” if follow-up imaging, referral to a nodule clinic, or other guideline-consistent care was ordered. IPNs were classified as “not appropriately followed” if no acknowledgement of the reported nodule was documented in the electronic health record within two weeks of being flagged.

Results:

The AI software processed 76,507 unique radiology reports, identified 2,585 CT scans with chest imaging, and found 389 IPNs. Review determined that 272 (70%) nodules were appropriately followed while 117 (30%) were not appropriately followed. Of the 117 nodules without documented follow-up, 67 (57%) were > 8mm and 24 (20.5%) were > 15mm. IPNs that would not have received follow-up in the absence of the AI software generated 43 additional clinical appointments and 3 procedures.

Conclusion:

At a large tertiary care center, 30% of clinically significant incidental pulmonary nodules that would have otherwise been missed were brought to the attention of lung nodule clinicians by an AI software, allowing for initiation of appropriate follow-up.
Genetics of Prader–Willi and Angelman syndromes: 2024 update
Authors: Godler David E. , Singh Deepan , Butler Merlin G.
Published: January 2025

Purpose of review

Prader–Willi (PWS) and Angelman (AS) syndromes arise from errors in 15q11-q13 imprinting. This review describes recent advances in genomics and how these expand our understanding of these rare disorders, guiding treatment strategies to improve patient outcomes.

Recent findings

PWS features include severe infantile hypotonia, failure to thrive, hypogonadism, developmental delay, behavioral and psychiatric features, hyperphagia, and morbid obesity, if unmanaged. AS presents severe intellectual disability, motor dysfunction, seizures, absent speech, and a characteristic happy demeanor. Standard-of-care testing involves SNRPN promoter methylation, microarray and genomic analyses for individuals presenting with these features. These tests identify syndromic-specific DNA methylation patterns and molecular genetic classes responsible for disease etiology. This review provides an update on studies of genotype–phenotype relationships and novel genomic technologies used for diagnostic purposes.

We give an overview and update on the genetics and underlying mechanisms associated with symptoms and potential treatments with focus on features reported to be different between specific molecular genetic classes. The review also describes laboratory testing methods for diagnosis of these imprinting disorders with implications for clinical practice.
HIV capsids: orchestrators of innate immune evasion, pathogenesis and pandemicity
Authors: Morling Kate L. , ElGhazaly Mohamed , Milne Richard S. B. , Towers Greg J.
Published: January 2025

Human immunodeficiency virus (HIV) is an exemplar virus, still the most studied and best understood and a model for mechanisms of viral replication, immune evasion and pathogenesis. In this review, we consider the earliest stages of HIV infection from transport of the virion contents through the cytoplasm to integration of the viral genome into host chromatin. We present a holistic model for the virus–host interaction during this pivotal stage of infection. Central to this process is the HIV capsid. The last 10 years have seen a transformation in the way we understand HIV capsid structure and function. We review key discoveries and present our latest thoughts on the capsid as a dynamic regulator of innate immune evasion and chromatin targeting. We also consider the accessory proteins Vpr and Vpx because they are incorporated into particles where they collaborate with capsids to manipulate defensive cellular responses to infection. We argue that effective regulation of capsid uncoating and evasion of innate immunity define pandemic potential and viral pathogenesis, and we review how comparison of different HIV lineages can reveal what makes pandemic lentiviruses special.
grepq: A Rust application that quickly filters FASTQ files by matching sequences to a set of regular expressions
Authors: Crosbie Nicholas D.
Published: January 2025

Regular expressions (regex) (Kleene 1951) have been an important tool for finding patterns in biological codes for decades (Hodgman 2000 and citations therein), and unlike fuzzy-finding approaches, do not result in approximate matches. The performance of regular expressions can be slow, however, especially when searching for matching patterns in large files.grepqis a Rust application that quickly filters FASTQ files by matching sequences to a set of regular expressions.grepqis designed with a focus on performance and scalability, is easy to install and easy to use, enabling users to quickly filter large FASTQ files, to enumerate named and unnamed variants and update the order in which patterns are matched against sequences through in-builttuneandsummarisecommands.grepqis open-source and available onGitHubandCrates.io.
The Demodifier: a tool for screening modification-induced alternate peptide taxonomy in palaeoproteomics
Authors: Evans Miranda
Published: January 2025

In palaeoproteomic research, the accuracy of taxonomic matches is crucial, as research questions frequently hinge on which species were utilised by ancient people. However, protein modifications including deamidation of glutamine and asparagine, and conversion of glutamine or glutamic acid to pyroglutamic acid, can change the sequence of peptides, leading to spurious taxonomic detections and potentially inaccurate archaeological interpretations. While a handful of examples of this phenomenon have been reported in the literature, the issue is potentially much wider reaching than currently realised. In reality, any time a peptide containing a deamidated glutamine or asparagine residue, an unmodified glutamic acid or aspartic acid residue, or a pyroglutamic acid modification is detected by proteomic search software, the sequence, and therefore potentially its taxonomy, may be incorrect, which could potentially lead to unsound archaeological interpretations.The Demodifieris a fast, open-access tool which solves this issue by screening for modification-induced alternate peptide taxonomy, enabling archaeologists to make informed interpretations of the taxonomies of proteins detected in ancient samples. To assess its utility,the Demodifieris tested against an archaeological dataset containing all unique peptides reported in palaeoproteomic studies of dental calculus and vessels. The results reveal that modification-induced alternate peptide taxonomies are severely under-reported, occurring 15% more frequently than previously understood. Modifications were found to produce three different types of inaccurate taxonomic matches: those which yielded completely different taxonomic lowest common ancestors to the input peptide, those which were more taxonomically specific than the input peptide, and those which were less taxonomically specific than the input peptide.The Demodifiertherefore enables the detection of potentially inaccurate peptide taxonomies, avoiding spurious archaeological interpretations in future studies.
System-size dependence of energy loss and correlations of heavy mesons at energies available at the CERN Large Hadron Collider
Authors: Zhao Jiaxing , Aichelin Joerg , Gossiaux Pol Bernard , Werner Klaus
Published: January 2025

We study the system size dependence of heavy quark (HQ) observables at a center-of-mass energy of sNN=5.02 TeV to explore whether it can provide further constraints on the physical processes which are involved: energy loss of HQs in the quark gluon plasma (QGP), hadronization, and hadronic rescattering. We use the EPOS4HQ approach to study p−p and 0–10% central O-O, Ar-Ar, Kr-Kr, and Pb-Pb reactions and investigate in detail the momentum change of heavy quarks from creation until their detection as part of a hadron as well as the enhancement of heavy baryon production at low pT. We investigate furthermore the origin and the system size dependence of the azimuthal correlations between the heavy quark Q and the heavy antiquark Q¯ and how one can bypass the problem that correlations are washed out due to the combinatorial background. We conclude that a systematic study of the system size dependence of the momentum loss allows separating the momentum loss due to the passage through the QGP from the momentum change due to hadronization, and that the QQ¯ correlations yield insight into the different pQCD processes in which the heavy quarks are created.

Published by the American Physical Society
2025
All-loop renormalization group invariants for the MSSM
Authors: Rystsov D. M. , Stepanyantz K. V.
Published: January 2025

For the minimal supersymmetric Standard Model, from the gauge couplings, Yukawa couplings, and the coefficient μ in the part of the superpotential quadratic in the Higgs superfields, we construct combinations which (for certain renormalization prescriptions) do not depend on the renormalization point in all loops. In other words, these combinations are the renormalization group invariants. Similar invariants are also constructed for the next-to-minimal supersymmetric Standard Model. The derivation is based on the nonrenormalization of the superpotential and the Novikov-Shifman-Vainshtein-Zakharov equations. We argue that the scale invariance of the considered combinations takes place in the class of the higher derivatives+minimal subtractions of logarithms scheme. This fact has been verified in the lowest orders, up to and including the one in which the dependence on the renormalization prescription becomes essential. It is also demonstrated that in the DR¯ scheme the renormalization group invariance does not take place starting from the approximation, where the scheme dependence manifests itself.

Published by the American Physical Society
2025
Charge-conserving equilibration of quantum Hall edge states
Authors: Idrisov Edvin G. , Levkivskyi Ivan P. , Sukhorukov Eugene V.
Published: January 2025

We address the experimentally relevant situation, where a nonequilibrium state is created by injecting charge current into a chiral quantum Hall edge state. We show that the commonly accepted picture of the full equilibration of a nonequilibrium state at finite distances contradicts the charge-conservation requirement. We propose and solve the transmission line model that accounts for the local equilibration process and the charge- and energy-conserving dynamics of the collective mode. We find that the correction of the electron distribution function to its eventual equilibrium form scales down slowly as 1/L at long distances L.

Published by the American Physical Society
2025
Recurrences Reveal Shared Causal Drivers of Complex Time Series
Authors: Gilpin William
Published: January 2025

Unmeasured causal forces influence diverse experimental time series, such as the transcription factors that regulate genes or the descending neurons that steer motor circuits. Combining the theory of skew-product dynamical systems with topological data analysis, we show that simultaneous recurrence events across multiple time series reveal the structure of their shared unobserved driving signal. We introduce a physics-based unsupervised learning algorithm that reconstructs causal drivers by iteratively building a recurrence graph with glasslike structure. As the amount of data increases, a percolation transition on this graph leads to weak ergodicity breaking for random walks—revealing the shared driver’s dynamics, even from strongly corrupted measurements. We relate reconstruction accuracy to the rate of information transfer from a chaotic driver to the response systems, and we find that effective reconstruction proceeds through gradual approximation of the driver’s dynamical attractor. Through extensive benchmarks against classical signal processing and machine learning techniques, we demonstrate our method’s ability to extract causal drivers from diverse experimental datasets spanning ecology, genomics, fluid dynamics, and physiology.

Published by the American Physical Society
2025
Macromolecular crystallography from an industrial perspective – the impact of synchrotron radiation on structure-based drug discovery
Authors: Käck H. , Sjögren T.
Published: January 2025

Structure-based drug design has been an integral part of drug discovery for over three decades, contributing to the development of numerous approved drugs. Here we discuss the evolution, as well as the current state, of structure-based drug design within the pharmaceutical industry, using data from AstraZeneca's internal repository for crystal structures to provide additional context. Over the past 20 years, the company has transitioned from a mixed in-house and synchrotron data collection model to a `synchrotron-only' approach, enabled by technological advancements at synchrotron facilities. We provide real-world examples of structure delivery to projects, including a high-throughput project and a case where a single structure was pivotal for discovering a candidate drug. We conclude that, despite recent developments in single-particle cryo-EM and deep-learning structure prediction methods, macromolecular crystallography remains a critical tool for drug discovery.
Identification of off-site construction disputes: technical, managerial and external dispute causes
Authors: Yildiran Merve Pelinsu , Demirdogen Gokhan
Published: January 2025

Purpose

While off-site construction (OSC) offers a promising solution to many problems plaguing traditional construction (e.g. low productivity, waste and safety risks), a lack of standards and knowledge about OSC, especially regarding disputes, hinders its wider adoption. This study aims to address this gap by identifying and analyzing the importance levels of technical, managerial and external disputes specific to OSC projects.

Design/methodology/approach

Three steps methodology was employed in the study. Focus group discussion (FGD) technique was used to identification and finalize dispute causes found from literature and collect data for the next step. In the study, two multi-criteria decision-making MCDM (methods) [a hybrid approach-Pythagorean fuzzy analytic hierarchy process (AHP) and fuzzy Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS)] were employed. While Pythagorean fuzzy AHP was used to calculate the weights of criteria, fuzzy TOPSIS analysis was used to calculate the weights of main and sub-dispute causes. Instead of using the classical AHP method, the Pythagorean fuzzy AHP method was employed due to its superiority in capturing the inherent uncertainty and ambiguity of decision-makers, giving flexibility to decision-makers with linguistic variables instead of expecting exact evaluation scores and flexibility in the integration with other methods. During the analysis of the weights of the main and sub-dispute causes, the fuzzy TOPSIS method was preferred. The fuzzy TOPSIS method involves a quicker and more straightforward decision-making process. Also, the fuzzy TOPSIS method allows the consideration of numerous alternatives and evaluation criteria and uncertainty in the decision-making process.

Findings

The analysis reveals that technical disputes pose the biggest challenge in off-site construction compared to managerial or external disputes. Specifically, “late completion, delivery and installation of components” emerged as the most significant technical dispute. Within managerial disputes, “poor planning and management of the project” ranked highest, while “the complexity of legal expressions” was the most prominent external dispute factor.

Originality/value

In the literature, three studies offer some insight on OSC disputes by analyzing the litigation cases. Nonetheless, the results can be misleading, because some disputes can be resolved before the litigation process. Therefore, the study findings can aid in foreseeing technical, managerial and external factors and in generating robust OSC contracts by considering these issues.
Happy to co-create: the influence of product co-creation over consumer hedonic adaptation
Authors: Kieling Ana Paula , Boeing Ricardo
Published: January 2025

Purpose

Researchers have been exploring the consequences of the hedonic adaptation process at length. This phenomenon is characterized by the reduction of pleasure with consumption experiences over time. Meanwhile, co-creation initiatives seem to be gaining traction in brand strategies. However, little is known about how individuals experience the co-creation effects in consumption. The purpose of this study is to analyse the impact of consumer co-creation experiences on predicting hedonic adaptation. Also, it aims to provide insights into the emotional aspects of consumption.

Design/methodology/approach

Three mixed-design experimental studies were conducted to explore the effects of co-creation on consumer hedonic adaptation, affective forecasting and emotional responses. Study 1 and Study 2 were conducted online with American participants. Study 3 was conducted in a laboratory setting in Brazil.

Findings

The research demonstrated that individuals predict that the path to consumption adaptation will be longer when co-creating their products co-create. However, this effect varies depending on the type of product. As for the emotional aspect, consumers attribute more positive emotions than negative ones in the context of co-creation.

Research limitations/implications

This study manipulated different conditions considering specific product types. Future research should apply this framework to other products and services to confirm the generalization of the study’s findings. Also, the authors encourage future studies that explore emotions in different co-creation scenarios.

Practical implications

Elucidating how co-creation impacts consumers’ hedonic adaptation empowers companies to leverage co-creation to cultivate positive consumer attitudes and brand loyalty. Marketing campaigns can highlight the emotional benefits of ownership and personalization. It also provides a sustainable perspective for companies, which seeks consumers who remain present over time and trust the company. Furthermore, co-creation can be used strategically for innovation management. By co-creating limited-edition trial products, companies can involve new customers, foster a sense of ownership and potentially mitigate hedonic adaptation, while gathering valuable insights for new product development.

Originality/value

This research advances the limited literature on co-creation and customer hedonic adaptation, which lies at the interface between consumer behaviour and product development. It explores how product co-creation affects consumers’ predictions and shopping experiences concerning pleasure decrease, including product value and company feedback. Additionally, it examines the role of emotions in co-creation and hedonic adaptation. This research contributes by demonstrating the impact of co-creation on adaptation, affective forecasting and emotional responses during consumption.
Tattoo-inspired surface texturing on oil-impregnated PTFE for advanced tribological properties
Authors: Tian Zhiqing , Xu Bin , Fan Xiaobing , Pan Bingli , Zhao Shuang , Wang Bingchan , Liu Hongyu
Published: January 2025

Purpose

This paper aims to investigate the crucial roles of textured surfaces on oil-impregnated polytetrafluoroethylene (PTFE) created by a facile tattoo strategy in improving tribological properties.

Design/methodology/approach

Pored PTFE (PPTFE) was prepared by mixing powder PTFE and citric acid and experienced a cold-press sintering molding process. Subsequently, textured surfaces were obtained with using a tattoo strategy. Surface-textured PPTFE was thus impregnated with polyethylene glycol 200, yielding oil-impregnated and pore-connected PPTFE.

Findings

This study found that oil-impregnated and surface-textured PPTFE exhibited excellent tribological performances with an 82% reduction in coefficient of friction and a 72.5% lowering in wear rate comparing to PPTFE.

Originality/value

This study shows an efficient strategy to improve the tribological property of PTFE using a tattoo-inspired surface texturing method.

Peer review

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-10-2024-0378/
CEO duality in family firms: implications for earnings management and firm performance in Thai market
Authors: Kitiwong Weerapong , Prasertsoontorn Thanu , Ratsamewongjan Ausanee , Inya Puritud , Jiraporn Pornsit
Published: January 2025

Purpose

As the debate over CEO duality’s impact on firm performance is still ongoing, the purpose of this study is to redefine CEO duality in Thai family firms and examine its impact on the relationship between earnings management and firm performance.

Design/methodology/approach

This study uses a sample of 1,360 firm-year observations from listed firms on the Stock Exchange of Thailand. A fixed effect regression is used to obtain the empirical results. The results of this study are further validated using two-stage least squares estimation, subsample regression and an alternative measure of family firms.

Findings

This study finds that firms with CEO duality are more likely to engage in REM, supporting Agency Theory. However, family-controlled firms with CEO duality engage less in REM in pursuit of firm performance. This study’s findings highlight the potential benefits of CEO duality in family firms as a mechanism to support Socioemotional Wealth of the controlling family. Therefore, the mandatory ban on CEO duality may have unintended consequences for family firms.

Originality/value

This paper provides further evidence on the impact of CEO duality on the relationship between earnings management and firm performance in Thailand’s family-dominated stock market. A new definition of CEO duality is proposed, including firms where the CEO is related to the chair of the board. This boarder definition provides more comprehensive measurement compared to the traditional definition which may fail to capture the full scope of influence exerted by controlling family, as they may obscure CEO duality by appointing individuals with kinship ties to the CEO as the chair of the board.
Digital inventory audits: an alternative approach to physical observation in audit evidence gathering
Authors: Fotoh Lazarus Elad
Published: January 2025

Purpose

This study examines whether digital streaming and observation technologies can serve as an alternative approach for collecting inventory audit evidence, the challenges faced in their adoption and the factors contributing to their non-adoption.

Design/methodology/approach

This study adopts a two-stage, mixed-method approach, beginning with pilot study interviews that informed the comprehensive survey with qualitative and quantitative data. Quantitative data were analyzed using descriptive statistics, t-tests and Pearson’s correlation coefficient, while qualitative data were analyzed using qualitative content analysis.

Findings

Our findings revealed a positive perspective concerning the effectiveness and reliability of these technologies for inventory audits and the efficiency of internal controls within them, despite challenges such as obtaining a holistic view of the warehouse, observing obsolescence, ensuring inventory completeness and general reliability concerns. Additionally, preferences for physical inventory audits and skepticism about these technologies’ potential to enhance audit quality were identified as factors contributing to their non-adoption.

Research limitations/implications

These findings have important implications for cost-conscious firms because they reveal that carefully adopting intermediate technologies can enhance the audit process. Our findings are relevant to audit regulators and firms interested in determining whether such technologies enhance audit efficiency and quality. This study highlights the need for updated auditing standards and directives and technologies that meet auditing requirements.

Originality/value

This study contributes to the literature by uncovering whether less advanced technologies can be used as an alternative approach to collect audit evidence. Consequently, the finding adds to the growing body of literature underscoring the potential of technologies, even less sophisticated ones, to enhance the efficiency and effectiveness of audits, despite their challenges. Additionally, it underscores the need for clear regulatory standards, suggests that auditors embrace emerging technologies and acquire relevant skills and offers insights for technology developers on audit firms’ concerns regarding digital technologies.
Principals’ distributed leadership and the effectiveness of school innovation management: the mediating role of school organisational culture
Authors: Lu Shao-Hung , Chen Chien-Chih
Published: January 2025

Purpose

This study explored the relationships between principals’ distributed leadership, school organisational culture and the effectiveness of school innovation management. A questionnaire was administered to gather data from public junior high school teachers in Taiwan.

Design/methodology/approach

Using the stratified random sampling method, 1,557 questionnaires were sent to 98 schools in Taiwan, and 1,018 valid questionnaires were obtained. All data were analysed using descriptive statistics and structural equation modelling.

Findings

School organisational culture significantly mediated the relationship between principals’ distributed leadership and the effectiveness of school innovation management. This mediating role was confirmed through multiple mediation analyses, highlighting the essential link between leadership practices and school innovation outcomes.

Originality/value

This study provides new insights into how distributed leadership by school principals can enhance the effectiveness of school innovation management by cultivating a solid organisational culture. The results underscore the importance of distributed leadership in fostering an environment conducive to school innovation.
Deciphering stakeholder voice on the challenges of transformative healthcare 5.0 ecosystem: a quality function deployment analyses
Authors: Ojha Ravindra , Agarwal Alpana
Published: January 2025

Purpose

The healthcare ecosystem continues to evolve with new technological developments with the support of its stakeholders. The technology-driven and patient-centric Healthcare 5.0 (H5.0) ecosystem is undergoing a transformation promising enormous benefits. However, the need to identify and understand the inherent challenges and barriers faced in the journey of H5.0 implementation and the relevant countermeasures for accelerated implementation has become critical.

Design/methodology/approach

The current research paper has utilised the Delphi approach for the collection of information and applied a well-proven quality function deployment (QFD) methodology for analysis.

Findings

The house of quality (HOQ) tool from the QFD has highlighted the critical H5.0 challenges which contribute to, approximately, 60% of the total weight. The identified top five process descriptors from the developed HOQ also contribute, approximately 60% among overall countermeasures. A useful H5.0 implementation progress (HIP) index has been recommended for tracking the progress made in the H5.0 implementation journey.

Originality/value

This research is among the first that has provided the application of the HOQ approach in the QFD methodology in the domain of H5.0. It has provided useful insights to the stakeholders. Furthermore, the development of a simple and practical HIP index is another useful value addition.
Why is learning from patient safety incidents (still) so hard? A sociocultural perspective on learning from incidents in healthcare organizations
Authors: Rowland Paula , Lan Melissa F. , Wan Cecilia , Pozzobon Laura
Published: January 2025

Purpose

Despite robust quality improvement efforts in healthcare, learning from patient safety incidents remains difficult. Our study explores counter-vailing powers shaping learning processes and possibilities in healthcare organizations, with a focus on social, political and organizational dynamics of learning.

Design/methodology/approach

Deploying concepts of situated curriculum, boundary work and interconnected knowledge practices, we interviewed staff and physicians (n = 15) in a large Academic Health Science Centre in Canada about their experiences of incident investigations and resultant information sharing. Our analytical strategy was abductive, drawing connections to sociology of the professions and learning sciences literature.

Findings

Incident investigation and follow-up processes are relatively robust for learning about incidents in the organization. However, learning from incidents remains difficult, complicated by the professional politics of incident classification, counter-vailing policies related to privacy, the organization of improvement work towards reporting, and an organizational focus on incidents with severe outcomes.

Practical implications

Participants advocated for a broader view of incidents, moving beyond classification and investigation based on severity of outcome to also include incidents that are “learning rich”. To that end, we argue for more research on the role of Patient Safety Specialists in organizational learning and more collaborations with learning sciences.

Originality/value

This paper illuminates ways in which robust information dissemination structures are an important but insufficient condition for learning from incidents. The argument goes beyond a prescriptive approach to learning from incidents to instead explore the competing visions and values implicated with improvement practices.
Principal’s pro-social drive: bridging social responsibility and entrepreneurship in school-community leadership dynamics
Authors: Kubilay Sevda , Durnali Mehmet
Published: January 2025

Purpose

Within the professional paradigm of education, school principals have an important role and responsibility in shaping the organizational climate, culture and practices in schools as well as occupying an important place in the school-community discourse. To this end, this research aimed to reveal the mediating role of pro-social motivations in the relationship between school principals’ social responsibility and involvement in social entrepreneurship.

Design/methodology/approach

A descriptive-correlational structural equation model was deployed to test a novel theory bearing upon existing research. To this end, data from 424 Turkish school principals, collected via a survey, were analyzed using descriptive, correlational and predictive algorithms in SPSS and AMOS.

Findings

The findings revealed a strong positive relationship between social responsibility and pro-social motivation and an even stronger link between social responsibility and social entrepreneurship. Additionally, pro-social motivation significantly mediated the relationship between the constructs of interest.

Practical implications

These results hold valuable implications for designing effective schools–community relations and school principal training aligned with 21st century educational professional trends.

Originality/value

An original empirical study that combines all these said concepts and perspectives has not been conducted with school principals before. This research contributes to the tremendous potential of school principals to shape a brighter future by finding proactive solutions to persistent inequalities in society through educational responsibility and entrepreneurial leadership in the Turkish context.
Adaptive learning engine for driving marketing channel performance: a machine learning approach
Authors: Dairo Adeolu Olukorede , Szűcs Krisztián
Published: January 2025

Purpose

This paper aims to develop and implement a machine learning recommendation engine – an adaptive learning engine that drives business revenue through the ranking and recommendation of offers at a granular customer level across the inbound marketing channels.

Design/methodology/approach

A data set of over 300,000 unique sample of mobile customers was extracted and prepared. The gradient boosting machine (GBM) algorithm was developed, consolidated, deployed and experimented on two inbound marketing channels.

Findings

Research examining machine learning implementation and operationalisation within the large consumer base is seemingly silent. This paper bridges this gap by developing and implementing a machine learning adaptive engine across two inbound marketing channels. The performance of the inbound channels revealed the significant importance of digital campaigns that are driven by machine learning algorithms. Machine learning techniques can be well positioned as an integral part of a large consumer base marketing operations with real-time one-to-one marketing capability.

Research limitations/implications

The study explores the use of machine learning, a cutting-edge subset of artificial intelligence (AI), to drive consumer business revenue across different marketing channels. Further research should explore these marketing channels in greater depth by considering other branches of AI in driving consumer business revenue.

Practical implications

This study demonstrates the value, ease and application of a machine learning deployment in a consumer business with a large customer base in driving business revenue. It also shows customers' practical response to offerings across channels and the importance of the digital channel to firms with a large customer base.

Originality/value

The paper defines how machine learning extracts can be deployed and operationalised by marketers to drive business revenue. This approach is unique, realistic, easy to deploy and will guide future research in this space.
Barriers to innovation in Brazilian small- and medium-sized enterprises
Authors: Silva Deoclécio Junior Cardoso da , Matos Guilherme Paraol de , Gibbon Artur Roberto de Oliveira , Veiga Claudimar Pereira da , Teixeira Clarissa Stefani , Lopes Luis Felipe Dias , Pique Josep Miquel
Published: January 2025

Purpose

This research investigates the barriers impeding innovation within small- and medium-sized enterprises (SMEs) in Brazil, exploring 54 innovation-related barriers categorized into six distinct groups to offer substantial insights and analyses pertinent to the decision-makers, researchers and SMEs.

Design/methodology/approach

This research employed a mixed quantitative and exploratory approach, utilizing fuzzy Delphi, fuzzy analytic hierarchy process (AHP) and fuzzy decision-making trial and evaluation laboratory (DEMATEL) methods. The fuzzy Delphi method confirmed the categories and barriers through quantitative analysis, the fuzzy AHP ranked the validated obstacles and the fuzzy DEMATEL method identified causal connections among the top-priority barriers.

Findings

Out of 54 barriers, 23 significantly impacted SMEs. The “Financing and Financial” category was the most significant barrier, with “Access to Financing” being the most critical impediment. The barrier with the most influence was “Instability of Fiscal Policies,” and the highest causal priority was “Survival of the Priority Business,” identifying the government’s unstable fiscal policy as the principal barrier confronting SMEs in Brazil.

Originality/value

The primary challenges for Brazilian SMEs center on financing, fiscal policies and maintaining ongoing operations. By addressing these barriers and fostering a resilient business environment, SMEs’ innovation capabilities and competitiveness can be enhanced, serving as key drivers for sustainable economic growth in fluctuating economic conditions. This study contributes to the literature by highlighting and validating the main barriers to SME innovation, providing highly relevant information about the innovation process.
Process capability analysis of additive manufacturing process: a machine learning−based predictive model
Authors: Abdolahi Alireza , Soroush Hossein , Khodaygan Saeed
Published: January 2025

Purpose

Predicting dimensional and geometrical errors in 3D printing parts during the design stage can significantly enhance the product’s quality. This study aims to predict the form deviation and process capability in additive manufacturing (AM) specimens considering layer thickness, laser power and scan speed parameters in the laser powder bed fusion (LPBF) method. Various machine learning (ML) techniques are implemented to estimate the form deviation and process capability with the highest accuracy in 3D-printed cylindrical parts as a case study.

Design/methodology/approach

The workflow started by simulating the LPBF AM process using a finite element modeling approach. Then, different ML algorithms like artificial neural networks are used to predict the form deviation. The process capability value is forecasted using some classification ML models and process capability indices (PCIs) for cylindrical parts. Finally, concentricity tolerance classification is performed for cylindrical parts, which can ensure quality control issues in the production stage.

Findings

Results present an accuracy of about 93% for predicting form deviations and 95% accuracy for predicting PCI C_pm in PCI classification based on random forest model as an ML algorithm.

Originality/value

The noteworthy point of the research is accessing the form deviation due to AM and process capability evaluation in the AM process before the production stage, which has not been studied before based on the author’s knowledge. So that the product quality is evaluated based on the shape deviation and its tolerances in the AM process digital chain.
Treatment of facial reactive B‐cell rich lymphoid proliferation with dapsone
Authors: Sugaya Makoto , Nagashima Akari , Nakamura Risae , Yano Megumi , Morita Takashi , Niijima Yasuko , Takekoshi Tomonori , Kanda Naoko , Tanaka Masaru
Published: January 2025

Reactive B‐cell rich lymphoid proliferation (rB‐LP), once called pseudolymphoma, is a benign lymphoproliferative disorder, which is histologically characterized by dense dermal infiltrate forming reactive germinal centers with tingible body macrophages. The disease frequently involves the face, scalp, and ear lobes. Treatment includes topical or intralesional steroids, surgical resection, ultraviolet therapy, laser treatment, and radiation therapy. Cases with multiple skin lesions, however, are difficult to treat with local therapies. Oral steroids are sometimes used, although the variety of side effects and recurrence during decreases in the dosage are the main problem. Here we report seven cases of rB‐LP treated with dapsone, which has anti‐inflammatory effect. Although the number of cases was limited, there was a trend that patients with multiple nodules on both sides of the face showed a good response. The limitations of this study include it being a case series from a single institute, and possible effects of topical steroids. We can, however, safely say that dapsone may be useful in some patients with rB‐LP.
ATL_FISHREF: A 12S mitochondrial reference dataset for metabarcoding Atlantic fishes frequently caught during scientific surveys in the Bay of Biscay
Authors: Rozanski Romane , Eme David , Richards Eilish , Deschez Marie‐Emilie , Rufino Marta M. , Trenkel Verena M. , Lorance Pascal , Marques Virginie , Spitz Jerôme , Cornette Florence , Albouy‐Boyer Séverine , Polanco Fernandez Andrea , Ernande Bruno , Pellissier Loic , Albouy Camille
Published: January 2025

The biodiversity crisis driven by anthropogenic pressures significantly threatens marine ecosystems. The rate of climate change and anthropogenic impacts outpace our traditional observation tools' capabilities, underscoring the urgency for new assessment methods. Environmental DNA (eDNA; DNA traces released by organisms) metabarcoding, a non‐invasive method widely developed over the last decade, represents a promising biomonitoring tool thanks to a large spatio‐temporal coverage, high detection of rare species and its time and cost‐effectiveness. However, capturing fish diversity using eDNA requires genetic reference databases, currently lacking. Improving reference databases relies on opportunistic sampling enabling the reporting of sequences for new species. The data provided here consists of barcoding 86 species of fishes over the 12S mitochondrial DNA gene. We generated 156 sequences of the mitochondrial 12S gene adapted to the “Teleo” barcodes from fishes sampled in the Bay of Biscay (BoB; Northeast Atlantic, France) between 2017 and 2019. In addition, we provided each individual the barcode details (Genbank accession number, chromatograms), a photograph, 5 ecomorphological measures and 11 life‐history traits documenting ecological functions (e.g., dispersion, habitat use, diet). Furthermore, we provided the sampling metadata (e.g., date, time, gear, coordinates, depth) and environmental variables measured in situ (e.g., conductivity, water/air temperature). This data set is valuable to improve the Northeast Atlantic eDNA genetic database, thus helping to better understand the effects of environmental forcing in the BoB, a transition zone housing mixed assemblages of boreal, temperate, and subtropical fish species susceptible to display variability in functional traits to adapt to changing conditions. The detailed Metadata for this abstract published in the Data Article section of the journal is available in MetaCat in JaLTER at https://jalter.diasjp.net/data/ERDP-2024-09.
Feeling and Healing in Different Spaces and Phases: How Individuals Coped With the Pandemic Cognitively, Affectively, and Conatively
Authors: Kim Sungsu , Jin Yan , Valentini Chiara , Choi Sung In , Badham Mark , Colleoni Elanor , Romenti Stefania
Published: January 2025

This research investigates individuals' reactions and coping strategies during a prolonged health crisis over distinct temporal phases (i.e., early and late stages of the pandemic) and geographical locations (i.e., Australia, Finland, Italy, South Korea, Sweden, and the United States). Using the infectious disease threat (IDT) appraisal model as a guide, we conducted two separate studies at different intervals to investigate the coping strategies individuals utilised in response to the COVID‐19 pandemic. Findings revealed cross‐country differences in cognitive (i.e., COVID‐19 risk perception and vaccine uncertainty), affective (i.e., hope, fear, shame, and anger), and conative (i.e., preventive behavioural intentions, vaccination intentions, and preventive behavioural engagement) outcomes, shaped by cultural and policy influences. Mediation and moderation analyses showed that the coping mechanism of cognitive appraisal indirectly influenced conative coping through affective responses, which could be contingent on pandemic fatigue. This research contributes to crisis and health communication literature by offering a more nuanced understanding of how individuals across different countries cope with and manage a long‐lasting public health crisis and provides key takeaways for advancing pandemic communication theory and practice.
Consensus on Symptom Selection for Endometriosis Questionnaires: A Modified e‐Delphi Study
Authors: Zhu Tong , Marschall Henrik , Hansen Karina E. , Horne Andrew W. , Saraswat Lucky , Zondervan Krina T. , Missmer Stacey A. , Hummelshoj Lone , Bokor Atilla , Østrup Camilla S. , Melgaard Anna , Rytter Dorte
Published: January 2025

Objective

To build consensus on most important symptoms and related consequences for use in questionnaires to characterise individuals with suspected and confirmed endometriosis in the general population.

Design

A questionnaire of 107 symptoms and related consequences of endometriosis was collaboratively developed by patients, medical doctors and researchers and further assessed in a two‐round e‐Delphi study. Participants assessed the relevance of the symptoms, and a priori it was decided that 70% was the threshold for inclusion of a symptom.

Setting

Participants represented 7 countries, including Australia, Denmark, France, Hungary, the United Kingdom, the United States, and Turkey.

Population

Individuals with endometriosis, medical doctors and researchers with expertise in endometriosis.

Methods

A modified e‐Delphi study.

Main Outcome Measures

Consensus‐based selection of symptoms for endometriosis questionnaires.

Results

Seventy‐six participants completed the first Delphi round and 65 completed the second round. Four symptoms met consensus in the first round (menstrual pain, pain during sexual intercourse, cyclic pain during defecation, and infertility), with two additional symptoms reaching consensus in the second round (cyclic pain and increased doctor/health care contacts for abdominal/pelvic pain).

Conclusion

This study highlighted six symptoms relevant for inclusion in endometriosis research questionnaires: menstrual pain, pain during sexual intercourse, cyclic pain during defecation, cyclic pain, infertility, and a high number of doctor/health care visits due to abdominal/pelvic pain. Recognising a broad range of potential symptoms is essential for raising awareness and supporting early detection efforts.