bluuebunny/crossref_metadata_2025 huggingface dataset:
Doctoral Students as Carbon Accountants: Calculating Carbon Costs of a PhD in Neuroscience
Authors: Smith William V. , Bebbington Aimee , Sircar Ranjini , Pulver Stefan R.
Published: January 2025

PhD students are drivers of innovation in research; however, the carbon intensity of PhD work is often unclear, especially in specialised STEM disciplines. Over 250,000 doctoral students graduate annually across all academic disciplines; empowering this community to engage in carbon accounting could create a generational force for decarbonization in key areas of production and consumption in research communities. Here, we demonstrate how doctoral students and other researchers can measure the carbon footprint of their work, using one PhD student in aDrosophilaneuroscience laboratory as a case study. We present a comprehensive life-cycle assessment of the equivalent carbon dioxide emissions (CO2e) generated by student research activities over the course of a year, including measurement of scope 1 emissions associated withDrosophilahusbandry; calculation of time- and region-specific scope 2 emissions produced by widely used techniques including calcium imaging, electrophysiology, and optogenetics; and estimation of scope 3 emissions associated with procurement and research-related travel. We found that research-related travel and procurement of laboratory supplies were responsible for the majority of annual emissions, generating up to 1942 kg CO2e and 543 kg CO2e respectively, after accounting for radiative forcing. Using the National Energy Source Operator Carbon Intensity API to account for temporal and geographical variation in the carbon intensity of UK National Grid energy, we found that persistent laboratory energy consumption released 10.99 kg CO2e, with an additional 3.56 kg CO2e scope 2 and 1.56 kg CO2e scope 1 emissions underpinning direct research activities. We discuss the challenges of accurately carbon footprinting research across disciplines in the UK and beyond, highlighting the value of regionally precise open-source energy mix data, and the need for data openness within research supply chains. Finally, we propose a common framework for including carbon life cycle analyses in Carbon Appendices to PhD theses and other publications. We envision doctoral students carrying insights from Carbon Appendices forward into academia and industry to catalyse community-driven decarbonisation of the research sector.
Evidence suggests that the SARS-CoV-2 Spike (S) protein may target coiled-coil regions of numerous cytoskeletal and cytoskeleton-associated proteins
Authors: Brézellec Pierre
Published: January 2025

Understanding the interactions between host and viral envelope proteins is essential to get insights into the dynamics of viral infection. To investigate more closely the mechanisms governing SARS-CoV-2 entry and intracellular trafficking, I reanalyzed the most extensive SARS-CoV-2–human protein–protein interactome dataset currently available. Our investigation centered on the Spike S protein, a key player in initiating viral infection by binding to the host cell membrane receptor Angiotensin-Converting Enzyme 2 (ACE2). I first present evidence demonstrating the statistical overrepresentation of actin-binding proteins among the Spike S partners/interactors. Next, I show that a majority of these partners contains a structural domain sharing high similarity with the C-terminal region of the Myosin II heavy chain, Myosin II being known for its roles in muscle contraction and various cellular motility processes. I subsequently demonstrate that this domain is particularly prevalent in actin-binding proteins, Intermediate Filaments proteins and Kinesins, which all are related to the cytoskeleton known to be involved in diverse cellular functions, including endocytosis and intracellular transport — processes crucial for viral infections. Finally, I highlight that the structural domain mentioned above is a bonafide coiled-coil region. I therefore conclude that Spike S might target proteins possessing such regions. These results align well with our previous findings, which suggested that the C-terminal portion of the Spike S protein shares similarities with the human protein prominin-1/CD133. Notably, CD133 is specifically located on the apical surface of cells and is associated with microvilli, structures characterized by a dense core of cross-linked actin filaments. Collectively, our findings suggest that the interactions between SARS-CoV-2 Spike S and human proteins, potentially mediated by coiled-coil regions, may have been underestimated. This opens up new avenues of research to elucidate the mechanisms underlying SARS-CoV-2 entry and intracellular trafficking.
Trends and variation in andexanet alfa for the reversal of direct oral anticoagulants in NHS Trusts in England
Authors: Fisher Louis , Buka Richard , Byrne Rosalind , Black Stephen , Curtis Helen J , Wood Christopher , Brown Andrew , Bacon Sebastian , Croker Richard , Goldacre Ben , MacKenna Brian , Speed Victoria
Published: January 2025

Andexanet alfa was recommended by the National Institute for Health and Clinical Excellence (NICE) as an option in the management of major gastrointestinal bleeding in patients taking apixaban or rivaroxaban in May 2021. To assess the uptake of andexanet alfa, we analysed pharmacy stock control data from NHS Trusts in England using the openly available Secondary Care Medicines Dataset.

Between May 2021 and July 2024, 14,092 vials of andexanet alfa were issued in NHS Trusts in England. There was wide variation in uptake across NHS Trusts, which likely reflects variation in local protocols.

This study is the first analysis of adoption of a new treatment using the OpenPrescribing Hospitals platform, which is expected to provide a generalisable framework for similar analyses in the future.
Advancing the prediction and understanding of placebo responses in chronic back pain using large language models
Authors: Nunes Diogo A.P. , Furrer Dan , Berger Sara , Cecchi Guillermo , Ferreira-Gomes Joana , Neto Fani , Martins de Matos David , Apkarian A. Vania , Branco Paulo
Published: January 2025

Placebo analgesia in chronic pain is a widely studied clinical phenomenon, where expectations about the effectiveness of a treatment can result in substantial pain relief when using an inert treatment agent. While placebos offer an opportunity for non-pharmacological treatment in chronic pain, not everyone demonstrates an analgesic response. Prior research has identified biopsychosocial factors that determine the likelihood of an individual to respond to a placebo, yet generalizability and ecological validity in those studies have been limited due to the inability to account for dynamic personal and treatment effects—which are well-known to play a role. Here, we assessed the potential of using fine-tuned large language models (LLMs) to predict placebo responders in chronic low-back pain using contextual features extracted from patient interviews, as they speak about their lifestyle, pain, and treatment history. We re-analyzed data from two clinical trials where individuals performed open-ended interviews and used these to develop a predictive model of placebo response. Our findings demonstrate that semantic features extracted with LLMs accurately predicted placebo responders, achieving a classification accuracy of 74% in unseen data, and validating with 70% accuracy in an independent cohort. Further, LLMs eliminated the need for pre-selecting search terms or to use dictionary approaches, enabling a fully data-driven approach. This LLM method further provided interpretable insights into psychosocial factors underlying placebo responses, highlighting nuanced linguistic patterns linked to responder status, which tap into semantic dimensions such as “anxiety,” “resignation,” and “hope.” These findings expand on prior research by integrating state-of-art NLP techniques to address limitations in interpretability and context sensitivity of standard methods like bag-of-words and dictionary-based approaches. This method highlights the role of language models to link language and psychological states, paving the way for a deeper yet quantitative exploration of biopsychosocial phenomena, and to understand how they relate to treatment outcomes, including placebo.
Comparison of Activities of Transcription Factor NF-κB from Two Jellyfish Models
Authors: Williams Leah M. , Wang Wei , Grigoryeva Alexandra V. , Navarro-Rosado Alejandra , Peart Jada A. , Calderon Angela , Gill Catherine L. , Alsante Kristina M. , Lackstrom Aidan T. ,   Molecular Biology Laboratory, Weissbourd Brandon , Wang Mengrui , DiRusso Christopher J. , Cohen Lianne B. , Wunderlich Zeba , Grone Brian P. , Gilmore Thomas D.
Published: January 2025

Herein, transcription factor NF-κB is characterized from two model jellyfish,Aurelia aurita(Aa) andClytia hemisphaerica(Ch). Both jellyfish NF-κB proteins consist primarily of the N-terminal DNA-binding/dimerization domain, and they lack the C-terminal ankyrin repeat inhibitory domain found in vertebrate NF-κB proteins. Both jellyfish NF-κB proteins can bind to a consensus mammalian NF-κB binding site, and their AlphaFold3-predicted structures on DNA are similar to that of mouse NF-κB p50. Neither Aa-nor Ch-NF-κB activated transcription of an NF-κB-site reporter gene in human cells; however, Aa-NF-κB did activate transcription from a GAL4-site reporter gene in yeast, whereas Ch-NF-κB did not. Aa- and Ch-NF-κB were both constitutively located in the nucleus when expressed in vertebrate cells. Homologs of IκB-like proteins from both species interacted with their corresponding NF-κB proteins in co-immunoprecipitation assays in HEK 293T cells. These IκB-like proteins influenced the subcellular localization of their cognate NF-κB proteins in vertebrate cells, and their ankyrin repeat domains were predicted to interact with Ch-NF-κB in a manner similar to mammalian IκB and NF-κB. RNA-sequencing data fromChanimals indicate that Ch-NF-κB is expressed at high levels in early developmental stages, when Ch-IκB expression is low, suggesting that active Ch-NF-κB controls an early developmental process. In contrast, in adult animals the expression of Ch-IκB is high, suggesting that Ch-NF-κB requires a signal in order to become active. Overall, these results provide comparative information on the structure, activity, and mRNA expression of jellyfish NF-κB pathway proteins among jellyfish, and they suggest roles for NF-κB in developing and adult jellyfish.
Lattice study of
J/ψ→γηc
using a method without momentum extrapolation
Authors: Meng Yu , Liu Chuan , Wang Teng , Yan Haobo
Published: January 2025

We present a model-independent method to calculate the radiative transition without the momentum extrapolation for the off shell transition factors. The on shell transition factor is directly obtained from the lattice hadronic function. We apply the method to calculate the charmonium radiative transition J/ψ→γηc. After a continuous extrapolation under three lattice spacings, we obtain the on shell transition factor as V(0)=1.90(4), where the error is the statistical error that already takes into account the a2 error in the continuous extrapolation. Finally, we determine the branching fraction of J/ψ→γηc as Br(J/ψ→γηc)=2.49(11)lat(5)exp%, where the second error comes from the uncertainty of J/ψ total decay width 92.6(1.7) keV.

Published by the American Physical Society
2025
Mass reconstruction of heavy neutral leptons from stopped mesons
Authors: Alves Gustavo F. S. , Dev P. S. Bhupal , Kelly Kevin J. , Machado Pedro A. N.
Published: January 2025

Heavy neutral leptons (HNLs), depending on their mass and mixing, can be efficiently produced in meson decays from the target or absorber in short- to medium-baseline accelerator neutrino experiments, leaving detectable signals through their decays inside the neutrino detectors. We show that the currently running ICARUS experiment at Fermilab can reconstruct the HNL mass and explore new HNL parameter space in the mass range of 70–190 MeV. The mass reconstruction is enabled by two ingredients: (i) simple two-body kinematics of HNL production from stopped kaon decays at the NuMI absorber, followed by HNL decay into a charged-lepton pair and neutrino at the detector, and (ii) high resolution of Liquid Argon Time Projection Chamber (LArTPC) detectors in reconstructing final state particles. Our mass reconstruction method is robust under realistic energy resolution and angular smearing of the charged leptons, and is applicable to any LArTPC detector. We also discuss the synergy between ICARUS and future facilities like DUNE near detector and PIP-II beam dump in probing the HNL parameter space.

Published by the American Physical Society
2025
Two nonlinear optically responsive crown ether inclusion compounds based on a sulfonimide anion assembly
Authors: Zhang Yao , Wang Yan-Juan , Tang Yuan-Yuan , Chen Xiao-Gang
Published: January 2025

Organic amine crown ether supramolecular compounds, based on crystal engineering design, have already made significant research progress in functional devices such as ferroelectrics, ferroelastics and nonlinear optical materials, especially those involving anilinium cations, which have attracted widespread attention. In comparison, benzylammonium cations have been less studied and most counter-ions are inorganic metal salt anions, crystallizing in centrosymmetric space groups without nonlinear optical (NLO) response. By changing the anion, we have obtained two types of crown ether inclusion compounds, namely, benzylammonium bis(methanesulfonyl)azanide–1,4,7,10,13,16-hexaoxacyclooctadecane (1/1), C7H10N+·C2H6NO4S2
−·C12H24O6 or [(BA)(18-crown-6)][DMSA] [BA = benzylammonium and DMSA = bis(methanesulfonyl)azanide] and benzylammonium (methanesulfonyl)(trifluoromethylsulfonyl)azanide–1,4,7,10,13,16-hexaoxacyclooctadecane (1/1), C7H10N+·C2H3F3NO4S2
−·C12H24O6 or [(BA)(18-crown-6)][TfNMs] [TfNMs = (methylsulfonyl)(trifluoromethylsulfonyl)azanide]. Both compounds crystallize in the polar chiral space group P21 at 100 K and exhibit a clear second harmonic generation (SHG) active characteristic, showing potential for use in quadratic nonlinear optical fields. Moreover, this work is the first to report crown-ether-based compounds using TfNMs as the counter-ion, enriching the choice of counter-anion for crown-ether-based compounds.
Reconsideration of the P-clusters in VFe proteins using the bond-valence method: towards their electron transfer and protonation
Authors: Xie Zhen-Lang , Jin Wan-Ting , Zhou Zhao-Hui
Published: January 2025

P-clusters have been statistically analysed using the bond-valence sum (BVS) method together with weighting schemes. The crystallographic data come from the VFe proteins deposited in the Protein Data Bank (PDB) with high resolutions of better than 1.35 Å. Calculations show that the formal oxidation state of a P1+ cluster can be assigned as 2Fe3+6Fe2+ with high electron delocalization, giving the same oxidation state as that of PN clusters in VFe proteins. Further comprehensive comparisons of the bond distances suggest that the hydroxyl groups of the β-153 serine residues in P1+ and PN clusters are in the protonated state, where the Fe6 atoms have the same oxidation state as Fe2+. During the transition from PN to P1+, cleavage of the Fe6—S1 bond is accompanied by the formation of a weak coordination between the Fe6 atom and the hydroxyl group of the β-153 serine residue in the P1+ cluster of the VFe protein. Similarly, oxidation of PN to P1+/P2+ clusters corresponds to the coordination of Fe6(II) by the hydroxyl group of the β-188 serine residue and of Fe5(II) by the peptide amine group of the α-88 cysteine residue in the MoFe protein of Azotobacter vinelandiis without electron and proton transfers.
Adaptive terminal sliding mode control of hypersonic vehicles based on ESO
Authors: Tang Weiqiang , Wang Chengbin , Shan Liuwei , Gao Haiyan
Published: January 2025

Purpose

This paper aims to solve the uncertainty problem of hypersonic vehicle tracking control; an adaptive terminal sliding mode control (TSMC) method based on extended state observer (ESO) is proposed. The combination of adaptive techniques, TSMC and ESO offers an effective approach for managing uncertain systems.

Design/methodology/approach

The dynamic model of a hypersonic vehicle is transformed into two control-oriented subsystems. The control system design incorporates an adaptive technique, an ESO and a TSMC. The ESO estimates the primary uncertainties, while the adaptive technique determines the upper limit of secondary uncertainties. These estimates are used for the design of the TSMC law. In addition, the filter is used to generate the reference trajectory to improve the dynamic performance of the system. The stability of the closed-loop system is proved by the Lyapunov stability theory.

Findings

A robust control system for hypersonic vehicles is developed with guaranteed stability and strong adaptability to various uncertainties such as parameter variations, external disturbances and actuator faults. Furthermore, the proposed system demonstrates enhanced dynamic performance compared to observer-based sliding mode control. Specifically, for the velocity and altitude tracking control, the settling time of the proposed sliding mode control is approximately 100 s and 70 s shorter than that of the observer-based sliding mode control, respectively.

Originality/value

Different from the single equivalent treatment, various uncertainties here are classified and treated with different strategies, which improves the disturbance rejection ability of the control system. This ability is of great significance for enhancing the autonomy, adaptability and reliability of hypersonic vehicles in extreme environments.
Environmental effects of foreign direct investment in India: pollution haven or pollution halo?
Authors: Holtbrügge Dirk , Raghavan Nikhila
Published: January 2025

Purpose

There is controversy over whether foreign direct investment (FDI) increases or reduces environmental degradation in host countries resulting in pollution havens or pollution halos. Based on the concept of scale, technology and composition effects, this paper aims to examine the causal relationship between FDI and carbon dioxide (CO2) emissions in India.

Design/methodology/approach

This paper analyzes panel data of the three most polluting industries between 2005 and 2021 by conducting a Granger causality test.

Findings

The results provide evidence of pollution havens in the manufacturing and transportation industry, and in the metallurgy and chemical sectors within the manufacturing industry.

Research limitations/implications

FDI inflows and CO2 emissions are characterized by large regional variations in India. Hence, future studies of the pollution haven vs pollution halo effect in India could therefore use state-level or even district-level data to test for regional variations.

Practical implications

This paper provides policy recommendations such as increasing the absorptive capacity of local firms to strengthen the technique effect, which would help India combat climate change.

Social implications

Increasing the absorptive capacity of local firms through incentives such as subsidies and environmental requirements in public contracts can lead to job creation in the green technology sector. This can provide new employment opportunities, especially in R&D and sustainable technology fields, boosting the local economy.

Originality/value

The study adds to the understanding of the endogenous relationship between FDI and environmental degradation, the importance of lagged feedback responses and the impact of industry- and sector-specific influences on this relationship.
AI-enabled self-regulated learning: reinforcing a proactive workplace culture – a viewpoint
Authors: Deshmukh Sampada , Mehta Mita
Published: January 2025

Purpose

This viewpoint discusses the influence of Artificial Intelligence (AI) - enabled self-regulated learning (SRL) on fostering proactive workplace learning and organizational agility.

Design/methodology/approach

This viewpoint unpacks how AI-enabled SRL can drive proactive employee learning outcomes, drawing insights through reviewing articles on AI and SRL.

Findings

This paper offers a unique insight into the organizations’ tools to streamline learning by providing real-time support, personalized learning paths, and skill gap analysis, enabling employees to take control of their professional development by aligning individual growth with organizational goals.

Research limitations/implications

This article gives managerial and organizational implications.

Practical implications

This is a viewpoint article and can be further elaborated with impartial learning.

Originality/value

This viewpoint article offers a distinctive and comprehensive approach to emerging research in AI-enabled learning at both individual and organizational levels, integrating with Zimmerman’s Model based on Social Cognitive Theory.
Impact of 6Qs innovation on student achievement in Thai small and medium schools: evidence from the O-NET scores effect size and good practice schools
Authors: Lawthong Nuttaporn , Lapanachokdee Warunee , Saejea Vorachet , Thepsathit Purin
Published: January 2025

Purpose

Drawing from the equitable education fund (EEF) launching 6Qs innovation in the teacher school quality program (TSQP) for small and medium schools, this research aims to analyze the effect size of the ordinary national educational test (O-NET) scores between TSQP schools that implement 6Qs innovation and non-TSQP schools and explain the impact of 6Qs innovation on O-NET scores’ effect size.

Design/methodology/approach

This study adopts an explanatory sequential mixed-method design. The quantitative study investigates the impact of the 6Qs innovation by analyzing the effect sizes of O-NET scores in four subjects of sixth-grade students. The effect size is analyzed by comparing the mean between 221 TSQP schools and non-TSQP schools: 16,197 small and medium schools throughout Thailand. The qualitative study uses a field study with administrators and teachers through in-depth interviews and focus groups in 13 good practice schools.

Findings

The quantitative result shows that 22 to 35% of TSQP schools demonstrated effect size within the standard level, meaning that their O-NET scores are higher than those of non-TSQP schools. Findings from 13 good practice schools indicate that both administrators and teachers have embraced and implemented the 6Qs innovation to establish an organizational culture that emphasizes 6Qs as a coordinating framework, which significantly influences students’ learning outcomes.

Originality/value

Although this research is studied in the Thai context, the 6Qs innovation with implementations extracted from the good practice schools can be generalized to any school in a similar context. A section on such innovation is provided in practical implications.
When extreme events become the norm: how do artisan entrepreneurs adapt identity?
Authors: Mousa Mohamed , Arslan Ahmad , Lange Thomas
Published: January 2025

Purpose

This paper aims to identify the extent to which extreme events in the tourism and hospitality sector force artisan entrepreneurs to re-orient their entrepreneurial identity and how they respond to these extreme events.

Design/methodology/approach

The empirical data comprises of semi-structured interviews with 24 artisan entrepreneurs in Egypt, operating in the following fields: handmade dresses, carpets, papyrus design and sales. Thematic analysis was employed to analyse these interviews.

Findings

The findings indicate a marginal effect on the identity of dress-making artisans from the occurrence of extreme events because they mostly have a stable local demand for their products. Hence, they follow a separation strategy in response to extreme events. The findings further show a moderate influence on the identity of carpet-making artisans who supply a regular demand from mosques and churches for their carpets. At the same time, changing taste and the rise of artificial intelligence make them follow an integration strategy in response to extreme events and associated shocks. The strongest impact of extreme events is found on papyrus artisans who have been forced to re-orient their traditional working methods and expectations in response to extreme events (e.g. a decrease in tourists, Covid-19, the war in Ukraine). Papyrus artisans have no discernible local demand for their products and face decreasing tourist numbers and tough competition from Chinese products, while also lacking discernible government support.

Originality/value

This paper is one of the pioneering studies to link artisan entrepreneurship specific entrepreneurial identity dynamics with extreme events in a local context. This linkage significantly fills a gap in both entrepreneurship, tourism and management literature.
How SMEs’ supply chain specific investment impacts supply chain financing performance: insights from signaling theory
Authors: Lu Qiang , Wang Yangyang , Yang Yudong
Published: January 2025

Purpose

This study aims to investigate how small and medium-sized enterprises (SMEs’) supply chain specific investment (SCSIs) affects supply chain financing performance (SCFP) in the innovative industrial finance model, and further analyze the internal mechanisms and important contextual factors.

Design/methodology/approach

Based on signaling theory, this study constructs a mediating and moderating model to examine the influencing mechanisms of SMEs’ SCSIs on SCFP, including the mediating effect of opportunism and the moderating effect of digital technology deployment (DTD). A multiple regression analysis is conducted to verify the theoretical hypotheses, using questionnaire data collected from 288 SMEs in China.

Findings

The empirical findings indicate that both SMEs’ supply chain asset-specific and relationship-specific investments can significantly promote SCFP. Also, SMEs’ SCSIs can improve SCFP by reducing the occurrence of opportunism perceived by supply chain partners. The breadth of DTD positively moderates the relationship between the two types of SCSIs and SCFP, while the depth of DTD has no significant moderating effect on the relationship between SCSIs and SCFP.

Originality/value

This study has discussed the important and novel issue of how financially distressed SMEs can send effective signals to financial institutions by increasing their SCSIs in supply chain finance mode. By revealing the influencing mechanisms of SMEs’ SCSIs on SCFP, this study contributes to expanding the research on the antecedents of SCFP from the dimension of interorganizational transactions. This study also enriches the perspectives of signaling theory by exploring the interaction between signal sender and signal intermediary.
Social ties as dynamic managerial capabilities and SME performance: unraveling the role of industrial boundary conditions
Authors: Uzkurt Cevahir , Ceyhan Semih , Ekmekcioglu Emre Burak
Published: January 2025

Purpose

As a contribution to the social ties and dynamic capabilities literature, the purpose of this study is to examine the boundary role of the industrial factors (competitive intensity, dependence on suppliers and demand uncertainty) on the relationship between small and medium-sized enterprises (SMEs) social ties (business ties and political ties) and firm performance.

Design/methodology/approach

Data were collected from 1,077 SME top-level managers in Turkiye. The proposed model is analyzed using partial least squares (PLS) path modeling in SmartPLS 4.0 software.

Findings

The results elucidate how demand uncertainty serve to moderate the influence exerted by both business and political ties upon the performance of SMEs. However, the moderating effects of competitive intensity and dependence on suppliers, although initially hypothesized, were not found to have a significant impact on the relationships.

Practical implications

The relevance of social ties of SMEs may depend on the industrial factor. Although both political and business ties are effective on the customer side, these ties may become irrelevant when it comes to competition and supplier relations. In competitive SME settings, where businesses are vying for similar markets, the effectiveness of ties might be questionable. In such cases, SMEs might invest in building in-house capabilities and competencies, rather than relying on their relational networks.

Originality/value

This study contributes to the understanding of how relational networks, which are considered as dynamic managerial capabilities, impact SMEs performance. It also fills an important gap by testing the boundary role of industrial factors on this relationship. The empirical data is collected from the Turkish context, which is also an original aspect of the study, considering most of the social ties literature has a limited focus on a few contexts. The results also indicate new areas for discussion and exploration, indicating potential avenues for further research.
Exploring ChatGPT literacy as predictor and moderator in enhancing informal digital learning of English (IDLE): a partial least square analysis
Authors: Li Xiaomeng , Thien Lei Mee
Published: January 2025

Purpose

This study aims to explore the role of ChatGPT literacy within the technology acceptance model (TAM) framework and its potential for learners of English as a foreign language (EFL), whereby ChatGPT is integrated into their informal digital learning of English activities.

Design/methodology/approach

Data from 543 Chinese EFL learners were collected using a cross-sectional quantitative method. The relationships between six factors, namely, ChatGPT literacy, perceived ease of use, perceived usefulness, attitude, behavioral intention and actual use, were conceptualized and tested based on the TAM framework. The conceptualized model was verified using partial least squares structural equation modeling.

Findings

The findings indicated that ChatGPT literacy is a significant predictor of perceived ease of use and perceived usefulness, which were the two core variables with a significant impact on attitude. Perceived ease of use positively influenced perceived usefulness, indicating the mediating role of perceived usefulness in this path. Attitude significantly and positively influenced behavioral intention, which positively predicted actual use. Moreover, ChatGPT literacy moderated the relationship between behavioral intention and actual use.

Originality/value

This study extends the TAM framework by incorporating ChatGPT literacy as a predictor and moderator between behavioral intention and actual use. Empirical evidence is further offered for including ChatGPT as a language-learning instrument with great potential for EFL learners in extramural EFL learner settings.
Managing difficult conversations on new technology integration: the case of generative AI
Authors: Eapen Tojin Thomas , Finkenstadt Daniel J.
Published: January 2025

Purpose

Managing difficult conversations about new technology integration is crucial for businesses that must adopt disruptive innovations while maintaining organizational integrity. This article explores the “technology integrity” challenge, which involves preserving identity, operational, and relational aspects of business integrity during the new technological integration process. Using Generative AI as an illustrative case, the article provides a six-stage conversation framework, covering authenticity, direction, unification, scalability, transparency, and ethics, to guide organizations in conducting empathetic, inclusive dialogues with internal and external stakeholders.

Design/methodology/approach

This is a conceptual paper for a practitioner audience.

Findings

The article provides a six-stage conversation framework, covering authenticity, direction, unification, scalability, transparency, and ethics to guide organizations in conducting empathetic, inclusive dialogues with internal and external stakeholders.

Originality/value

This article explores the “technology integrity” challenge, which involves preserving identity, operational, and relational aspects of business integrity during the new technological integration process. This is particularly critical for organizations integrating AI technologies.
Critical success factors for students’ knowledge-sharing behaviors: a comparison between undergraduate, graduate and professional course students
Authors: Evangelista Edmund , Mustapha S.M.F.D Syed , Marir Farhi
Published: January 2025

Purpose

The purpose of the research was to explore the critical success factors (CSFs) that enable knowledge-sharing behaviors (KSB) among students and to determine if there are differences in the CSFs that enable KSB among undergraduate, graduate or professional course students.

Design/methodology/approach

The study is based on primary data collection, surveying 281 students using a multiple-choice Likert-style scale.

Findings

Researchers found that factors such as knowledge culture (KC), perceived rewards (PR), quality of technology (QT), trust, networking ties (NT) and competitiveness were critical for KSB. In contrast, collective culture, subjective norms (SN) and the ability to share did not significantly impact KSB. The CSFs common among students at different educational levels were KC, PR, trust and competitiveness. KC was more important for undergraduates and professional course students but less significant for graduate students. Additionally, NT and the QT did not impact KSB among undergraduates.

Originality/value

While several studies have explored CSFs for knowledge-sharing behaviors among students at specific educational levels, there is a lack of comparative empirical research examining KSB and the CSFs affecting students at different educational stages. This study fills a gap in the literature by adopting a comparative approach and presenting common success factors for knowledge sharing among students at various educational levels.
COSST: A tool to facilitate seed provenancing for climate‐smart ecosystem restoration
Authors: Silva Mateus C. , Moonlight Peter , Oliveira Rafael S. , Rowland Lucy , Pennington R. Toby
Published: January 2025

Selecting the best seed sources is a key step in ecological restoration planning especially under climate change. Seed‐provenancing strategies include composite, aiming to reproduce natural gene flow; predictive, focusing on future climate adaptation; and climate‐adjusted, a combination of composite and predictive. Yet, implementing different seed‐provenancing principles remains a challenge.

To fill this methodological gap, we developed the Climate‐Oriented Seed‐Sourcing Tool (COSST), a tool built in R capable of suggesting priority areas for seed sourcing according to composite, predictive, or climate‐adjusted strategies, as well as the restoration site and focal species.

The tool derives its inputs from species distribution models, which require occurrence and climate data only. COSST accommodates multiple climatic variables, weights the variables according to species‐specific sensitivities, and accounts for uncertainties between climate forecasts.

We demonstrated the flexibility of COSST using Caryocar brasiliense (pequi), a tree native to the Brazilian Cerrado, as a case study. The tool identified optimal areas for collecting C. brasiliense seeds and estimated the proportion of seeds to be sourced from various suppliers. We made available an R code for running COSST along with a Shiny application for data visualization.

Synthesis and applications. Our tool can guide where to source seeds for species lacking range‐wide information on genetic structure, which is the case for a substantial proportion of the tropical flora, where ecosystem restoration is of paramount importance.
The role of occupational therapy in providing vocational rehabilitation for people living with inflammatory arthritis: A scoping review
Authors: Somerville Susan , Codd Yvonne , Gowran Rosemary J.
Published: January 2025

Introduction

Inflammatory arthritis significantly impacts work participation resulting in cost to individuals, employers, and society. Vocational rehabilitation seeks to address this need, but its pathways, interventions, and efficacy continue to be under investigation. Contributing variables are complex, identifying the need for a conceptual framework to guide practice. Occupational therapy addresses this complexity, providing theoretical frameworks such as the Person‐Environment‐Occupation‐Performance (PEOP) model to understand the occupation of work supporting well‐being and design interventions. The aim of this scoping review is to map the role of occupational therapy in providing vocational rehabilitation for people living with inflammatory arthritis.

Methods

A scoping review following Arksey and O'Malley's (2005) stages was completed. Major databases and grey literature were systematically searched, and hand‐searches completed. Descriptive and thematic analysis mapped the findings to the PEOP model framework.

Consumer and Community Involvement

There was no consumer or community involvement in this review.

Results

Fourteen studies were included. Major themes aligned to the PEOP model with further analysis synthesised in subthemes. A majority of person‐related interventions to support work performance was observed. This framework identifies the domains of focus in vocational rehabilitation and current gaps. Work instability, employment retention, and self‐efficacy were used to measure effectiveness.

Conclusion

This scoping review presents the evidence regarding vocational rehabilitation for the inflammatory arthritis population in the context of occupational therapy theory to provide a framework for clinical practice. A current focus on person‐focused interventions was identified. The PEOP model provides a clear framework to understand the complexity and nuances of vocational rehabilitation across the domains. Outcome measures for vocational rehabilitation are heterogenous and require further exploration as capturing the intricacy of achieving balance with work participation remains unclear. Further research into vocational rehabilitation programs incorporating all domains of the PEOP model is needed. Consideration of work performance measurements to inform effectiveness and the resulting impact on a person's well‐being is required.
Mechanisms and strategic prospects of cannabinoids use: Potential applications in antimicrobial food packaging—A review
Authors: Dey Moumita , Bera Sharmita , Tyagi Preeti , Pal Lokendra
Published: January 2025

This review focuses on antimicrobial packaging for food safety, critically examining the activity and efficacy of cannabinoids against commonly found microorganisms and exploring their antimicrobial mechanisms. Specifically, the review considers cannabinoids derived from industrial hemp plants, which are characterized by low levels of psychoactive components. It also outlines viable strategies to control the sustained release of cannabinoids from the packaging, enabling extended storage and enhanced safety of food products. Research demonstrates that cannabinoids are effective against both foodborne bacteria and fungi, with their antimicrobial action primarily attributed to microbial membrane instability. Cannabinoids can be utilized to prepare effective antimicrobial films and edible coatings; however, the number of studies in this area remains limited. The potential of cannabinoids to contribute to intelligent packaging systems is also discussed, with an emphasis on the regulatory aspects and challenges associated with incorporating cannabinoids into food packaging. Finally, the review identifies future research directions to address current limitations and advance hemp‐based antimicrobial food packaging solutions.
Automating egg damage detection for improved quality control in the food industry using deep learning
Authors: Cengel Talha Alperen , Gencturk Bunyamin , Yasin Elham Tahsin , Yildiz Muslume Beyza , Cinar Ilkay , Koklu Murat
Published: January 2025

The detection and classification of damage to eggs within the egg industry are of paramount importance for the production of healthy eggs. This study focuses on the automatic identification of cracks and surface damage in chicken eggs using deep learning algorithms. The goal is to enhance egg quality control in the food industry by accurately identifying eggs with physical damage, such as cracks, fractures, or other surface defects, which could compromise their quality. A total of 794 egg images were used in the study, comprising two different classes: damaged and not damaged (intact) eggs. Four different deep learning models based on convolutional neural networks were employed: GoogLeNet, Visual Geometry Group (VGG)‐19, MobileNet‐v2, and residual network (ResNet)‐50. GoogLeNet achieved a classification accuracy of 98.73%, VGG‐19 achieved 97.45%, MobileNet‐v2 achieved 97.47%, and ResNet‐50 achieved 96.84%. According to the results, the GoogLeNet model performed the damage detection with the highest accuracy rate (98.73%). This study encompasses artificial intelligence and deep learning techniques for the automatic detection of egg damage. The early detection of egg damage and accurate interventions highlights the significant importance of using these technologies in the food industry. This approach provides producers with the ability to detect damaged eggs more quickly and accurately, thereby minimizing product losses through timely intervention. Additionally, the use of these technologies offers a more efficient means of classifying and identifying damaged eggs compared to traditional methods.
Children With Sydenham Chorea and Psychiatric Disorders Had Variable Long‐Term Outcomes and Required Multidisciplinary Management
Authors: Mushet Nadine , Morton Michael , Minnis Helen , Gillberg Christopher
Published: January 2025

Aim

Sydenham chorea (SC) is a globally significant, post‐streptococcal, childhood neuropsychiatric condition that is rare in western Europe. This retrospective single‐centre study focused on children with neuropsychiatric features of SC.

Methods

Participants were recruited from neuropsychiatry referrals to a regional paediatric neurology department in Glasgow, Scotland, from 2009 to 2012. Interviews established the course of SC and the children's medical and family histories. Semi‐structured psychiatric interviews explored current and past episodes of psychopathology.

Results

We studied 12 children (seven girls) with a mean age of 13 (range 10–15) years, and an average of six (range 4–10) years after their SC symptoms began. Before they displayed symptoms, seven children had been suspected or diagnosed neurodevelopmental problems and four had separation anxiety. Their physical symptoms were often debilitating. Psychopathology was most severe during their first episode and SC diagnoses were sometimes delayed. Educational problems were frequent. Multiple psychiatric conditions were diagnosed in 11 children and anxiety and attention deficit hyperactivity disorder were the most common. Relapses occurred in nine cases. Additional services that were accessed included cardiology, rheumatology, physiotherapy, occupational therapy and speech therapy. Medication included prophylactic penicillin and symptomatic treatment.

Conclusion

Children with SC and psychiatric disorders had variable long‐term outcomes and required multidisciplinary management.
The neonate respiratory microbiome
Authors: Pirr Sabine , Willers Maike , Viemann Dorothee
Published: January 2025

Over the past two decades, it has become clear that against earlier assumptions, the respiratory tract is regularly populated by a variety of microbiota even down to the lowest parts of the lungs. New methods and technologies revealed distinct microbiome compositions and developmental trajectories in the differing parts of the respiratory tract of neonates and infants. In this review, we describe the current understanding of respiratory microbiota development in human neonates and highlight multiple factors that have been identified to impact human respiratory microbiome development including gestational age, mode of delivery, diet, antibiotic treatment, and early infections. Moreover, we discuss to date revealed respiratory microbiome–disease associations in infants and children that may indicate a potentially imprinting cross talk between microbial communities and the host immune system in the respiratory tract. It becomes obvious how insufficient our knowledge still is regarding the exact mechanisms underlying such cross talk in humans. Lastly, we highlight strong findings that emphasize the important role of the gut–lung axis in educating and driving pulmonary immunity. Further research is needed to better understand the host – respiratory microbiome interaction in order to enable the translation into microbiome‐based strategies to protect and improve human respiratory health from early childhood.
Deeds speak louder than words: Employees' responses to supervisors' word‐oriented and deed‐oriented voice endorsement
Authors: Ni Dan , Zhang Yihua , Wu Wen , Peng Xianting , Zheng Michelle Xue
Published: January 2025

Integrating the voice endorsement literature and behavioral integrity theory, this research first advances the constructs and develops the scales for supervisors' word‐oriented and deed‐oriented voice endorsement in Study 1. In Study 2, we examine how supervisors' word‐oriented and deed‐oriented voice endorsement influence employee voice behavior. Results from a four‐wave field study demonstrate that supervisors' word‐oriented voice endorsement is negatively related to perceived supervisor behavioral integrity, whereas supervisors' deed‐oriented voice endorsement is positively related to perceived supervisor behavioral integrity. Perceived supervisor behavioral integrity enhances employees' willingness to discuss ideas and ultimately promotes their voice behavior. In addition, a higher (versus lower) level of explanation providing weakens the negative impact of supervisors' word‐oriented voice endorsement and strengthens the positive impact of supervisors' deed‐oriented voice endorsement on perceived supervisor behavioral integrity. Theoretical and practical implications are discussed.
Your needs or mine? The role of allies' needs and their perceptions of disadvantaged groups' needs in motivating solidarity‐based actions
Authors: Sağlamöz Ahmed Faruk , Kutlaca Maja , Leite Ana C.
Published: January 2025

We propose a new motivational model that integrates self‐determination theory (with a focus on basic needs) with social‐psychological research on allyship and solidarity to better understand when and why allies may engage in different actions to address social injustice. We theorize that normative (e.g., donations and protesting) and non‐normative (e.g., blocking highways and disrupting events) solidarity‐based actions are motivated by allies' basic needs (measured at the individual and group levels) as well as their perception of disadvantaged groups' basic needs (measured at the individual and group levels). We tested the model in two cross‐sectional studies using two different contexts: English citizens' solidarity (i.e., allies from a high‐status group) with Ukrainian refugees and students' solidarity (i.e., allies from a low‐status group) with the striking university employees in the United Kingdom (Ntotal = 1232). In both studies, we found that the more allies' needs were satisfied, the more likely they were to engage in normative solidarity actions. In contrast, intentions to engage in non‐normative solidarity actions were predicted by frustration of allies' needs. Perceptions of disadvantaged group's needs predicted engagement in both normative and non‐normative actions. Notably, high‐status allies' solidarity was driven by both individual and group‐level needs, whilst low‐status allies were only motivated by group‐level needs.