bluuebunny/crossref_metadata_2025 huggingface dataset:
The MYCN/Aurora-A complex is a cyclin activating kinase for CDK12
Authors: Müller Mareike , Eing Lorenz , Uhl Leonie , Schmitz Maximilian , Kaneva Iliyana , Byrne Dominic P. , Fleischhauer Daniel , Burgess Selena G. , Fischer Sophia , Gebauer Nick , Nancy-Portebois Vanessa , Kaltheuner Ines H. , Ha Stefanie Ahn , Schülein-Völk Christina , Solvie Daniel , Richards Mark W. , Vidal Raphael , Brand Matthias , Papadopoulos Dimitrios , Bayliss Richard , Eyers Patrick A. , Eyers Claire E. , Geyer Matthias , Eilers Martin , Büchel Gabriele
Published: January 2025

Deregulated MYCN is a driver of aggressive pediatric and adult neuroendocrine tumors, but critical oncogenic processes downstream of MYCN remain poorly defined. In neuroblastoma, MYCN interacts with and activates the Aurora-A kinase. Here we show that Aurora-A is a CDK-activating kinase for CDK12 by phosphorylating T893 in the T-loop, thereby enhancing its kinase activity. Aurora-A-dependent activation of CDK12 controls phosphorylation of T4 of RNA polymerase and recruits transcription termination complexes, thereby preventing transcription-replication conflicts. Enhanced crosslinking and immunoprecipitation sequencing reveals that Aurora-A associates with splice sites on nascent RNA. RNA-bound Aurora-A is catalytically inactive. MYCN competes with RNA for binding to Aurora-A and displaces Aurora-A from RNA in cells, promoting its CDK12 kinase activity. Combining Aurora-A and CDK12 inhibition potently suppresses the growth ofMYCN-amplified neuroblastoma cells and patient-derived xenografts. Our data demonstrate that an Aurora-A/CDK12-dependent transcription termination pathway is a critical and targetable dependency of MYCN-driven tumors.
In vitroActivity of Citrus IntegroPectin against Lung Cancer Cells
Authors: Di Sano Caterina , D’Anna Claudia , Petri Giovanna Li , Angellotti Giuseppe , Meneguzzo Francesco , Ciriminna Rosaria , Pagliaro Mario
Published: January 2025

Citrus IntegroPectin bioconjugates obtained through acoustic cavitation in water of different citrus fruit (lemon, red orange, and sweet orange) processing waste show substantial anticancer activityin vitroagainst human non- small cell lung cancer cells. Dissolved in aqueous phase at different concentrations, all IntegroPectin phytocomplexes tested affected long-term proliferation and cell migration of adenocarcinoma cells of line A549. Compared to sweet orange, IntegroPectin from lemon and red orange were more effective in reducing colony formation activity. Pointing to significant reduction in cancer cell progression, these results support further investigation of these new low methoxyl pectins rich in citrus flavonoids and RG-I regions for the treatment of lung cancer.

Abstract Figure
Protein-Formatted Biomarker Enrichment Tag for the Detection of Carcinoembryonic Antigen
Authors: Liu Chang , Barricella Sara , Cortez-Jugo Christina , Steer David L. , He Lizhong
Published: January 2025

The streptavidin-biotin interaction has long been a cornerstone of immunoassays, valued for its exceptionally high affinity and specificity, and has been widely used in routine diagnostic assays for decades. However, elevated biotin levels in plasma, often resulting from oral supplements, can interfere with streptavidin-biotin binding, compromising signal detection in these assays. To address this limitation, we present a biotin-insensitive antigen enrichment system based on the ultra-strong binding pair barnase (Bn) and barstar (Bs) for effective antigen capture. This high-affinity system enables efficient detection of nanobody-antigen complexes with picomolar sensitivity, as demonstrated by the detection of carcinoembryonic antigen (CEA, CEACAM5). When paired with a fluorescent secondary nanobody reporter, the system achieved a detection limit as low as 98.9 pM, with a limit of detection (LOD) of 17.8 ng/mL, representing a four-order-of-magnitude improvement in sensitivity compared to light interferometry-based binding analysis. Both Bn and Bs are small (<15 kDa), single-chain proteins that can be generically incorporated into immunoactive molecules. Compared to the traditional biotin-streptavidin system, the Bn-Bs system offers enhanced specificity, improved stability, and reduced cost and complexity.
Aggressive interference as a strategy for enhancing resource gain
Authors: Rakocinski Chet F
Published: January 2025

The functional response, or rate of resource acquisition for a consumer should decline proportionately in the presence of other consumers vying for the same resources. Aggressive behavior should be adaptive when it serves as a leverage mechanism for enhancing resource gain above what would be obtained under a premise of equal access. Model development expands on the implications of this assertion to make several predictions pertaining to the expression and magnitude of gainful aggressive interference with respect to leverage strength,consumer density, and resource density.
hmde: Hierarchical Methods for Differential Equations
Authors: O’Brien Tess , Kar Fonti , Warton David , Falster Daniel
Published: January 2025

R package implementing a hierarchical Bayesian longitudinal model for repeat observation data. The package provides a selection of differential equation models that are then fit using the hierarchical model.
A simple age-structured, temperature-dependent population growth model of brown rice hopper (Nilaparvata lugens(Stål))
Authors: Wei Xiaojing , Balanza Jane Girly , Ngoc Vu Thi Bich , Giles James , Swaans Cornelis
Published: January 2025

Brown rice hopper (BRH), a key insect pest to rice, is known can change its longevity and fecundity due to rising temperature. Here we modeled the response of BRH population growth to temperature using an age-structured population growth model, based on reported responses of BRH development time, survival, and fecundity to temperature. We applied this model to predict historical level of BRH population growth in the Mekong River Delta (MRD) and compared the predictions with historically observed percentages of rice fields infested by BRH. The model was able to capture the seasonal variation in BRH infestation and the optimal temperature for BRH activities (app. 26.5°C). These results highlighted the importance of temperature in regulating BRH population growth. The model, with further improvements as discussed, could be used for projecting BRH activity under rising temperatures or predicting BRH outbreaks due to seasonal temperature anomalies.
Autoantibody hotspots reveal origin and impact of immunogenic XIST ribonucleoprotein complex
Authors: Yan Bingyu , Lee Jinwoo , Srinivasan Suhas , Shi Quanming , Dou Diana R. , Davuluri Srijana , Nandyala Swarna , Woods Adrianne , Leatherman Gwendolyn , Zhao Yanding , Reggiardo Roman E. , Sawant Manasi , Thiam Hawa R. , Shah Ami A. , Fiorentino David F. , Chung Lorinda S. , Chang Howard Y.
Published: January 2025

Four out of five patients with autoimmune diseases are women. The XIST ribonucleoprotein (RNP) complex, comprising the female-specific long noncoding RNA XIST and over 100 associated proteins, may drive several autoimmune diseases that disproportionately affect women, who have elevated levels of autoantibodies against the XIST RNP. However, the structural distribution, potential origin, and clinical significance of XIST RNP autoantibodies remained unexplored. Here, we find that XIST RNP is associated with autoantigens associated with six female-biased autoimmune conditions. Mapping autoantibody targets to their occupancy sites on XIST shows that these autoantigens are concentrated at discrete “hotspots” along the XIST lncRNA, notably the A-repeat. Cell type-specific protein expression data nominated neutrophils as a predominant source of hotspot antigens, and we confirmed the presence of both XIST and hotspot antigens in neutrophil extracellular traps during NETosis, an immunogenic programmed cell death pathway triggered by neutrophil activation upon which neutrophils extrude their nuclear content. Furthermore, we found that levels of autoantibodies against a top hotspot antigen, SPEN, that binds the A-repeat, correlate with severe digital ischemia in systemic sclerosis in two independent cohorts. Together, these data show a plausible mechanism for the origin of AXA, guided by RNA structure and RNA-protein interactions, and show that antibodies to XIST RNP holds promise for disease endotyping and prognostication in female-biased autoimmune conditions.

One Sentence Summary

Novel autoantibodies target hotspots on XIST ribonucleoprotein complex in female-biased autoimmune diseases.
Fluorogenic Interacting Protein Stabilization for Orthogonal RNA Imaging
Authors: Zhou Wen-Jing , Wu Mei-Yan , Shao Xin-Juan , Tang Li-Juan , Wang Fenglin , Jiang Jian-Hui
Published: January 2025

Live imaging of RNAs is crucial to interrogate their cellular functions, and approaches allowing fluorogenic RNA imaging with high orthogonality and contrast remains underexplored. We propose a fluorogenic interacting protein stabilization (FLIPS) strategy that enables orthogonal RNA imaging in live cells with fluorescence-labeled RNA interacting proteins (RIPs) stabilized by cognate RNA motifs. We show that the RNA motif stabilizes the otherwise degraded cognate RIP fused to a poly(arginine)- extended C-terminal degron, and the stabilizing effect is enhanced with circular permutation of the RIP. This design affords a generally applicable strategy for different RNA motifs and RIPs, enabling orthogonal and multi-color fluorescence-activated RNA imaging. Our strategy is broadly demonstrated for multiplexed, high-contrast RNA detection and imaging, single molecule RNA imaging and RNA dynamic translocation tracking in live cells. The versatility of our system highlights its potential for interrogating RNA biology and developing RNA-based imaging tools.
HoloMoA: Fast holography and deep-learning-based tool for the novelty detection of mechanism of action of antimicrobial candidates
Authors: Sedaghat Zohreh , Courbon Benoît , Botrel Héloise , Dugua Hélène , Tulinski Pawel , Alibaud Laethitia , Pagani Lucia , Mercer Derry , Guyard Cyril , Védrine Christophe , Dixneuf Sophie
Published: January 2025

We propose an innovative technology to classify the Mechanism of Action (MoA) of antimicrobials and predict their novelty, called HoloMoA. HoloMoA is a rapid, robust, inexpensive, and versatile tool based on the combination of time-lapse Digital Inline Holographic Microscopy (DIHM) and Deep Learning (DL). In combination with proper image reconstruction, DIHM enables a label-free, time-resolved visualization of bacterial cell morphology and phase map (i.e. refractive index × thickness) to reveal phenotypic responses to antimicrobials, while DL techniques are powerful tools to extract discriminative features from image sequences and classify them. We assessed the performance of HoloMoA technology on Escherichia coli (E. coli) ATCC 25922 treated for up to 2 hours with 22 antibiotic molecules representing 5 functional classes (i.e. Cell Wall synthesis inhibitors, Cell Membrane inhibitors, Protein synthesis inhibitors, DNA and RNA synthesis inhibitors). First, using reconstructed phase images as input to a 3D Convolutional Neural Network classifier, we detected the MoA of known antibiotics with 89% accuracy. Secondly, we showed how our CNN models combined with a Siamese neural network architecture can be used for the novelty assessment of the MoA of a candidate antibiotic. The HoloMoA novelty detection tool succeeded in detecting trimethoprim-sulfamethoxazole (Folic Acid synthesis inhibitors) as belonging to a novel functional class (i.e. different from the 5 aforementioned classes). We demonstrated that combining DHIM and DL gives a promising tool for determining the MoA of new antimicrobial candidates provided that a large image database for known antimicrobials is available.
Engineered spermidine-secretingSaccharomyces boulardiiameliorate colitis and colon cancer in mice
Authors: Mohaqiq Mahdi , Palou Roger , Li Ruizhen , Zhang Guijun , Vaishnav Het , Parweez Florance , Moyana Terence , Carragher Damian , Cameron D.W. , Ramsay Timothy , van der Sloot Almer , Murthy Sanjay , Coombes Brian , Tyers Mike , Liu X. Johné
Published: January 2025

Experimental studies suggest that the probiotic yeastSaccharomyces boulardiican mitigate the symptoms of inflammatory bowel disease. However, these results are equivocal andS boulardiiprobiotic therapy has not gained widespread acceptance in clinical practice. To assess whether the therapeutic properties ofS boulardiimight be improved upon, we engineeredS boulardiito overproduce and secrete spermidine, a pro-regenerative natural metabolite. We employed CRISPR gene deletion and transposon-mediated gene integration to manipulate expression of key enzymes in the polyamine synthetic and transport pathways. We tested the engineered yeast by oral gavage of mice treated with azoxymethane and dextran sulfate sodium to induce chronic colitis and colon cancer. We demonstrate that oral delivery of spermidine-secretingS boulardiiin mice populates the gastrointestinal tract with viable spermidine-secretingS boulardiicells and raises free spermidine levels in the gastrointestinal tract. Strikingly, spermidine-secretingS boulardiistrains were significantly more effective than wild-typeS boulardiiin reducing dextran sulfate sodium-induced colitis as well as colitis-associated colon cancer in mice. These results suggest that in situ spermidine secretion by engineered synthetic biotic yeast strains may be an effective and low-cost therapy to mitigate inflammatory bowel disease and colon cancer.
Expression of the p53 Network Aging-associated Genes “shaken, not stirred” in a 3-Week Microgravity Simulation Human Study
Authors: Kuznetsov Nik V.
Published: January 2025

Background

The hostile space environment affects human health and aging. NASA has named five main hazards astronauts will face in space, including space radiation and changes in gravity. However, the contribution of each of these factors, along with others, to the overall impact on biomolecular and cellular processes is not always clear.

Objective

To explore the effects of microgravity on the transcriptomes of healthy volunteers, with a focus on aging-related gene expression in p53 cell signaling pathways.

Methods

Ten healthy young men were exposed to simulated microgravity (SMG) for three weeks and blood samples were collected at five time point before, during and after the course of SMG. T cells were purified from the peripheral blood samples and total RNA was isolated and sequenced followed by bioinformatics analysis of volunteers’ global transcriptomes.

Results

A differential expression of p53 network genes was observed. The expression of nearly 30 genes involved in p53 gene network was affected during a 3-week course of simulated microgravity environment in dry immersion including classic p53 downstream target genes involved in cellular senescence: GADD45, p21, PUMA, IGF1 and other targets and potential target genes.

Conclusion

For the first time, the p53-associated cell signaling pathways and gene network in human T cells were reported to be affectedin vivoby dry immersion SMG. It is evident that the relatively mild effects of simulated weightlessness on the human body are sufficient to activate these pathways and influence aging-related genes in the p53 gene network. These findings should not be dismissed, as they could open the door to the discovery of a novel category of drugs - MG-senolytics.
Allosteric factors in the calcium/calmodulin-responsive kinase II hub domain determine selectivity of GHB ligands for CaMKIIα
Authors: Gauger Stine Juul , Palmelund Line B. , Tian Yongsong , Marek Aleš , Namini Mathias R , Griem-Krey Nane , Kickinger Stefanie , Mortensen Jonas S. , Frølund Bente , Wellendorph Petrine
Published: January 2025

The Ca2+/CaM-dependent protein kinase II alpha (CaMKIIα) is a highly important synaptic protein, which comprises a unique holoenzyme structure organized via the central hub domain. Recently, a distinct binding pocket in the CaMKIIα hub domain was identified for the endogenous neuromodulator γ-hydroxybutyric acid (GHB) and related synthetic analogues. Key interacting residues in CaMKIIα were revealed, but the pronounced selectivity towards thealphavariant of CaMKII has remained unresolved. Aimed at elucidating the molecular determinants for this selectivity, we here conducted binding studies to CaMKII-HEK whole-cell homogenates using two different in-house-developed GHB-related radioligands, [3H]HOCPCA and [3H]O-5-HDC, in combination with site-directed mutagenesis. Binding to CaMKIIα with the smaller-type radioligand [3H]HOCPCA validated key involvement of the four known residues (His395, Arg433, Arg453 and Arg469), but also revealed a role for the upper hub flexible loop containing the CaMKIIα-specific residue Trp403 (Leu in all other CaMKII isozymes). Insertion of the corresponding residues (L467W/C533R) into CaMKIIβ failed to introduce [3H]HOCPCA binding. However, with the larger-type radioligand, [3H]O-5-HDC, specific binding in CaMKIIβ (L467W/C533R) was achieved. Thus, of the four native CaMKII isozymes, only CaMKIIα accommodates GHB ligands. The study identifies the CaMKIIα flexible pocket loop as a distantly located “allosteric” factor in determining selectivity of GHB analogues for CaMKIIα. It sheds light on a remarkable interplay of the entire hub cavity for accommodation of ligands, and corroborates GHB analogues as CaMKIIα-selective.
Investigating the factors influencing teachers’ adoption of gamification strategies in higher education: insights from Korthagen’s onion model
Authors: Desgourdes Clément , Carmagnac Liliane , O'Neill Caroline Rosaleen
Published: January 2025

Purpose

Interest in gamification as a relevant and innovative pedagogical tool has increased in recent years among academics and educators. While considerable literature has focused on the effectiveness of gamified learning, little is known about the motivations behind its adoption. By examining teachers’ perspectives, which are often overlooked, we investigated the factors influencing teachers’ adoption of gamification strategies.

Design/methodology/approach

We adopted Korthagen’s onion model as the main theoretical lens to identify the influencing factors. A qualitative study involving interviews with 15 French higher education teachers was conducted to achieve our purpose.

Findings

The results were organized within the six layers of the onion model, through which we demonstrated the factors influencing teachers’ adoption of gamification. The institutional environment and teachers’ internal characteristics (beliefs, values, identity and mission) were identified as the determinants of gamification use.

Originality/value

Unlike most gamification studies, this research contributes to the literature by considering teachers’ perspectives and integrating the Korthagen model into the educational setting. We also propose an integrative theoretical approach that uncovers synergies between the Korthagen model and the educational leadership literature.
How big data impacting CSR application in listed companies in emerging countries: evidence from Vietnam
Authors: Phan Hai Hong , Tran Hung Ngoc
Published: January 2025

Purpose

This study aims to use the SmartPLS method for empirical analysis and explore the impact of various factors on the enhancement of corporate social responsibility (CSR) application among listed companies in Vietnam. With the increasing scrutiny over CSR disclosures and the pivotal role of internal and external factors, the research seeks to uncover how factors such as management’s perception, big data application, firm characteristics, organisational culture and stakeholder pressure significantly influence CSR application.

Design/methodology/approach

The research assesses the relationships among these factors by drawing on a sample of 255 listed Vietnamese companies across various sectors. Partial least squares structural equation modeling (SmartPLS) is applied to analyse the data and uncover the impact of the identified factors on CSR application.

Findings

The findings demonstrate that big data applications, organisational cultures and firm characteristics significantly impact CSR applications. Additionally, management’s perception, directly and indirectly, influences CSR applications through its effect on big data applications.

Research limitations/implications

The study is limited to listed companies in Vietnam, which may affect the generalizability of the findings to other contexts. Further research is needed to validate these findings in different markets and settings.

Practical implications

These results provide valuable insights for corporate governance practitioners in Vietnam and similar emerging markets. By highlighting the critical role of big data applications in CSR practices, the study suggests pathways for enhancing corporate governance frameworks to improve CSR applications.

Social implications

Improved CSR practices driven by the factors identified in this study can lead to more sustainable and socially responsible business operations.

Originality/value

This study contributes to the existing literature by using the SmartPLS method to analyse the impact of various factors on CSR applications in an emerging market. It emphasises the importance of big data applications in shaping effective CSR practices and offers valuable recommendations for corporate governance enhancements.
Digital transformation, international competition and productivity progress: evidence from Health Silk Road
Authors: Wan Lu , Fang Yanqi , Ban Nannan , Cheng Guo , Huang Guohua
Published: January 2025

Purpose

This paper aims to explore the relationship between digital transformation, international competition and productivity progress by examining the dual margins of export, thereby identifying the digital development pathway for key industrial chains within the context of regional medical and health cooperation.

Design/methodology/approach

By constructing models incorporating both the extensive margin and intensive margin, this paper delves into the reasons underlying changes in product trade value and variety within international market competition. Utilizing export data for medical products from China to Belt and Road Initiative partner countries spanning from 2007 to 2020, an industry–destination–time panel benchmark model is established to assess the impact of digital transformation on product expansion and international competition.

Findings

The findings reveal the following insights. First, digital transformation positively impacts the intensive margin of medical products, whereas it does not exert a positive influence on the extensive margin. Second, the impact mechanism test indicates that digital transformation fosters the intensive export margin by enhancing the technical efficiency of exports but exhibits an inverted U-shaped effect on technological progress. Third, digital transformation demonstrates a notable non-linear characteristic, with a substantial increase in the lifting effect once a certain threshold is surpassed.

Originality/value

While previous research has extensively explored the effects of digital transformation on export trade, this study uniquely integrates the concepts of the intensive and extensive margins of export, thereby enriching the research insights derived from existing literature. It focuses on the nonlinear effects and threshold dynamics of digital transformation, particularly in relation to total factor productivity. Additionally, the paper makes a contribution to the understanding of the Health Silk Road by incorporating the health index.
A method for calibrating robotic kinematic parameters based on a multi-error source model and an optimized measurement pose set
Authors: Cheng Bo , Wang Bo , Chen Shujun , Zhang Ziqiang , Xiao Jun
Published: January 2025

Purpose

The purpose of this study is to improve the accuracy of industrial robot kinematic parameter identification and position accuracy by solving the problem of insufficient consideration of error sources in the kinematic parameter identification model and optimizing the selection of measurement pose set.

Design/methodology/approach

In this study, a kinematic calibration method for industrial robots considering multiple error sources is proposed. Based on the Modified Denavit Hartenberg (MD-H) model, a robot kinematics identification model including joint reduction ratio error, target ball installation error and coordinate system transformation error is established. Taking the optimal observability index O1 and the minimum flexible deformation as the optimization objectives, a measurement pose set optimization method based on Non-dominated Sorting Genetic Algorithm II (NSGA-II) is proposed to obtain a measurement pose set with higher identification accuracy.

Findings

Through experiments conducted with the Nantong Zhenkang ZK1400-6 robot as the test subject, the kinematic parameters identified by the optimized measurement pose set are more accurate than the randomly selected measurement pose set, and the positioning accuracy of the robot is improved from 2.11 to 0.31 mm, an increase of 85.3%.

Originality/value

This study introduces a position error model that comprehensively accounts for the error sources causing positioning inaccuracies. Building on this foundation, a novel flexible deformation index is proposed to quantify the flexible deformation in the measurement pose set, thereby reducing the impact of such deformation on the position error in the model. To the best of the authors’ knowledge, for the first time, this study presents an optimization method for the measurement pose set based on NSGA-II, using the flexible deformation index and observability index as objectives for multi-objective optimization, simultaneously optimizing the pose error and Jacobian matrix in the error model.
Unravelling the relationship among corporate sustainability initiatives, executive compensation and corporate carbon performance: new insights from African countries
Authors: Saa Vida Y. , Morrison Emmanuel A. , Adu Douglas A. , Joseph Damilola
Published: January 2025

Purpose

Although listed firms in Africa are increasingly establishing board sustainability committees, their impact on corporate outcomes in the region remains relatively understudied. This study investigates the effect of executive compensation (EC) and board sustainability committee initiatives (BSCIs) on both self-reported greenhouse gas emission reduction initiatives (SRGI) and actual greenhouse gas emissions (GHGE).

Design/methodology/approach

Through the lens of resource-based view and legitimacy and stakeholder theoretical perspectives, the study conducts a fixed-effects model over a dataset of 2,310 firm-year observations from African countries between 2002 and 2022.

Findings

The findings show that while EC has a negative impact on SRGI, it does not have a similar effect on outcome-based GHGE reduction. The study observes that SRGI has no effect on actual GHG emissions. We add a fresh dimension to the literature by documenting that BSCIs are associated with greater outcome-based GHGE but do not seem to improve symbolic SRGI. The evidence shows that BSCIs have no moderating impact on the association between symbolic SRGI and outcome-based GHGE. Finally, the study establishes that the predicted associations vary across different periods.

Originality/value

This study helps unpack the role of the board sustainability committee, which Orazalin et al. (2024) show has key economic implications. The findings help stakeholders including corporate boards, executives and regulators to understand how board sustainability committee characteristics and EC are associated with GHG emissions. The results are particularly essential as this study demonstrates the need for specific standards for disclosing GHG emission-related information, notably in the non-existence of mandatory GHG reporting.
The role of AI adoption in transforming the accounting profession: a diffusion of innovations theory approach
Authors: Assidi Soufiene , Omran Mohamed , Rana Tarek , Borgi Hela
Published: January 2025

Purpose

This study aims to examine the impact of Artificial Intelligence (AI) adoption on Tunisia’s accounting profession, using the diffusion of innovations theory (DIT) to explore opportunities and challenges.

Design/methodology/approach

A survey of 400 academics and professional accountants in Tunisia was conducted, focusing on three key areas: the effect of AI on professional roles and tasks, the enhancement of digital work environments and the development of educational programs. Structural equation modelling (SEM) was used to test the relationships among these variables, providing robust statistical insights.

Findings

The results indicate that AI adoption leads to a 75.7% improvement in the functionality and responsibilities of accounting professionals, a 72.1% enhancement in digital workplace productivity and a 58.4% increase in educational program effectiveness. Despite these positive outcomes, the study identifies significant challenges, including a 63.2% concern related to change management and a 59.8% need for substantial training and technical resources investment. To address these challenges, the findings advocate for targeted professional development programs, collaborative policymaking to establish implementation guidelines and a curriculum overhaul to equip future accountants with AI competencies.

Research limitations/implications

The findings suggest Tunisian organisations should invest in AI to achieve substantial efficiency and risk management gains. Practitioners, instructors and students are expected to increase their technology expertise to develop more effective accounting procedures in light of AI issues. Collaboration among policymakers, regulators and practitioners is essential to establish clear implementation guidelines.

Originality/value

This study offers theoretical contributions by applying the DIT to AI adoption within an emerging economy, providing a unique perspective on how AI drives digital transformation in the accounting sector. In addition, it delivers practical implications by identifying strategies for overcoming barriers to AI adoption, such as fostering organisational readiness, ensuring access to training resources and enhancing professional collaboration to enable successful AI integration.
Handling changes on and changes of the market: market–political ambidexterity in the Swedish market for solar energy
Authors: Kihlström Victoria , Åberg Susanne
Published: January 2025

Purpose

Firms regularly have to handle business-related market changes on the market, such as new market entrants, increased competition, changing prices and changing demand. However, firms active on a market subject to political interventions, resulting in changes of the market, also have to handle different support systems with subsidies, taxes, regulations, etc. As these interventions affect both firms and customers, it is important for firms to adapt to them, but if they continue to change, firms also need to adapt to changing conditions. The purpose of the paper is to study how firms handle continuous market changes and shifting governmental interventions through market–political ambidexterity.

Design/methodology/approach

Based on a qualitative approach, 13 in-depth interviews focusing on how firms handle market changes and political interventions over time were conducted during two time periods. The data was coded in several steps, using systematic combining.

Findings

The empirical results reveal that firm size is crucial in developing market–political ambidexterity; small firms lack the resources needed to handle all changes in an ambidextrous way. Changes on the market require firms to be active, whereas changes of the market, e.g. interventions, require internal stability in the firms. Changes on the market are easier to handle, wherefore there seems to be a need for firms to develop political exploration and exploitation activities related to market–political ambidexterity.

Originality/value

This study contributes to industrial marketing by increasing our understanding of how SMEs handle the simultaneous but sometimes contradicting demands from market changes and political interventions by developing market–political ambidexterity.
Optimising efficiency and patient-centredness in general hospitals: insights from data envelopment and matrix analysis
Authors: Lee Hyunseo , Sohn Minsung , Choi Mankyu
Published: January 2025

Purpose

Medical institutions face management challenges from intense competition and an unclear link between patient-centredness and profitability. This study examined the association between efficiency and patient-centredness in general hospitals and identified management strategies to optimise both.

Design/methodology/approach

Data from the 2021 patient experience evaluation by the Health Insurance Review and Assessment Service and financial statements from the Korea Health Industry Development Institute for general hospitals in South Korea were used. Efficiency scores and patient-centredness were determined for 256 general hospitals using data envelopment analysis (DEA), and their relationships were analysed through matrix analysis. The Kruskal–Wallis and Mann–Whitney tests assessed group differences identified through matrix analysis.

Findings

Efficiency and patient-centredness can be improved concurrently. Hospitals in the highest efficiency group reported significantly higher average inpatient revenue per 100 beds (179.67) and net profit (158.84) than those in lower-performing groups (p < 0.001). Optimal management of hospital beds and specialised diagnostic equipment per 100 beds was associated with higher efficiency scores, while a greater number of doctors and nurses positively influenced patient-centredness metrics. Therefore, general hospitals should invest in personnel and resources to enhance efficiency and patient-centredness, achieving optimal financial and operational outcomes.

Originality/value

This study combines DEA and matrix analysis to explore the link between hospital efficiency and patient-centredness, using recent data on patient experience and financials from South Korean hospitals. It identifies strategies to enhance both dimensions.
Supporting teachers in higher education: design of an institutional programme from a socio-technical perspective
Authors: López Flores Nidia Guadalupe , Óskarsdóttir María , Islind Anna Sigridur
Published: January 2025

Purpose

The acceleration of technology adoption in higher education, prompted by the global shift to online teaching during the COVID-19 pandemic, called for responsive programmes to address pedagogical challenges. This paper aims to present the design process and initial adoption of an institutional programme created to support instructors in providing educational resources for online and hybrid undergraduate courses at Reykjavik University.

Design/methodology/approach

By adopting a socio-technical perspective, the programme encompasses teacher support and digital platform use. Additionally, the programme aimed to enhance the student experience by increasing course consistency and facilitating data collection for future research on learning analytics.

Findings

The findings demonstrate the programme’s successful adoption, effectively strengthening teachers’ practices. Key contributions include a teacher-centric perspective on technology challenges and a socio-technical conceptualisation informed by teachers’ experiences during the pandemic.

Originality/value

This research provides valuable insights for teachers, administrators and researchers developing similar initiatives for effective professional development of faculty in online and hybrid teaching environments.
FRT*: fast reactive tree for mobile robot replanning in unknown dynamic environments
Authors: Li Zheng , Chen Yanjie , Zhang Zhixing , Zhong Hang , Wang Yaonan
Published: January 2025

Purpose

This study aims to introduce the fast reactive tree (FRT*) algorithm for enhancing replanning speed and reducing the overall cost of navigation in unknown dynamic environments.

Design/methodology/approach

FRT* comprises four key components: inverted tree build, convex hull construction, dead nodes inform activation and lazy-rewiring replanning. First, an initial path is found from the inverted tree where the valid structure is preserved to minimise re-exploration areas during the replanning phase. As the robot encounters environment changes, convex hulls are extracted to sparsely describe impacted areas. Next, the growth direction of the modified tree is biased by the inform activation of dead nodes to avoid unnecessary exploration. In the replanning phase, the tree structure is optimized using the proposed lazy-rewiring replanning to find a high-quality path with low computation burden.

Findings

A series of comprehensive simulation experiments demonstrate that the proposed FRT* algorithm can efficiently replan short-cost feasible paths in unknown dynamic environments. The differential wheeled mobile robot with varying reference linear velocities is used to validate the effectiveness and adaptability of the proposed strategy in real word scenarios. Furthermore, ablation studies are conducted to analyze the significance of the key components of FRT*.

Originality/value

The proposed FRT* algorithm introduces a novel approach to addressing the challenges of navigation in unknown dynamic environments. This capability allows mobile robots to safely and efficiently navigate through unknown and dynamic environments, making the method highly applicable to real-world scenarios.
On Arrhenius steady hydromagnetic heat transfer to natural convection flow in a stretching upright sheet: viscous dissipation and Newtonian heating
Authors: Omowaye Adeola John , Adesina Adedayo Naheem , Aleem Taoqer Ayobami , Omowaye Joshua Ayodeji , Ayinde Samuel Olukayode
Published: January 2025

Purpose

The purpose of this study is to investigate the impact of Arrhenius kinetics on hydromagnetic free convection of an electrically conducting fluid flowing past a vertically stretched sheet maintained at a constant temperature, considering viscous dissipation. In this study, the understanding of the Biot number is essential for comprehending and enhancing heat transfer processes in a flow. Mastering this concept is crucial for the efficient design and management of various industrial and natural systems. The effect of Newtonian heating is accurately addressed by adjusting the traditional temperature boundary condition.

Design/methodology/approach

The presiding inconsistent Partial differential equations are contrasted to ordinary differential equations by similitude changes and the solutions are completed numerically by fourth-order Runge-Kutta (RK-4) and shooting procedures. Tables and graphs feature vividly in annotating the outcomes of changing parameters on the flow.

Findings

Notably, the Biot number significantly impacts temperature gradients and distribution, which subsequently affect the flow’s velocity and thermal characteristics; that is, velocity and temperature contours increase directly to an upsurge in the Biot number. Contrasting with existing work, a perfect harmony is experienced. Arrhenius kinetics are essential for predicting and managing fluid flow behaviour in systems where reactions are sensitive to temperature. Grasping this relationship helps engineers and scientists enhance process efficiency, ensure safety and optimize fluid-based systems. Similarly, Newtonian heating significantly impacts fluid flow by affecting temperature distribution, viscosity, buoyancy-driven flows and flow stability. Mastering the control of this heating process is vital in both natural and engineered fluid systems. Technical applications of this research include variation cooling and atomic power generation refrigeration.

Originality/value

The distinguishing quality of this research lies in the scrutiny of Arrhenius steady hydromagnetic heat transfer to natural convection flow in a stretching upright sheet: viscous dissipation and Newtonian heating. To best of the authors’ understanding, a problem like this has not been considered. The findings in this work will give useful information to scientists and engineers.
Intraspecific variability across seasons and geographically distinct populations can modify species contributions to ecosystems
Authors: Sanders Trystan , Solan Martin , Godbold Jasmin A.
Published: January 2025

Environmental change profoundly alters biodiversity and, by extension, species contributions to ecosystem functioning. While it is well‐established that these impacts can be geographically and temporally nuanced, most assessments of species contributions to ecosystems assume that species traits are temporally and spatially fixed, and those that do acknowledge intraspecific variability have failed to fully determine its relevance to ecosystem functioning.

Here, using three geographically distinct populations of sediment‐dwelling invertebrates, we combine a laboratory experiment with Bayesian hierarchical modelling to empirically quantify the prevalence of intraspecific trait variability in relation to geographic locality and seasonal conditions. Furthermore, we assessed the role of intraspecific trait variability in mediating sediment particle mixing, nutrient generation and benthic oxygen uptake.

We found that geographic and seasonal variability in body size and sediment particle reworking modified macrofaunal contributions to sediment total oxygen uptake and nutrient generation. These associations, however, were not consistent across all measured traits and ecosystem functions.

Our findings highlight asymmetries in both the absolute magnitude and/or direction of species responses to changing seasonal conditions, indicating that the relative functional contributions species make to ecosystems can be temporally or spatially transient and may, therefore, diverge from expectations based on contemporary functional group typologies.

These findings highlight a critical knowledge gap in our understanding of the key sources of variability affecting functionally important aspects of species behaviour and physiology and call for the development of dynamic ecological assessment and management approaches that account for individual as well as species responses to changing environments.

Read the free Plain Language Summary for this article on the Journal blog.
Frankenstein matrices: Among‐population life history variation affects the reliability and predictions of demographic models
Authors: Rosa Giacomo , Schmidt Benedikt R. , Léna Jean‐Paul , Monod‐Broca Benjamin , Vignoli Leonardo , Tournier Emilie , Bonnaire Eric , Buschmann Holger , Kinet Thierry , Laudelout Arnaud , Fonters Remi , Biancardi Carlo , Di Cerbo Anna R. , Langlois Dominique , Thirion Jean‐Marc , Morin Lucy , Pichenot Julian , Moquet Julien , Cayuela Hugo , Canessa Stefano
Published: January 2025

Population matrix models are routinely used to study the demography of wild populations and to guide management choices. When vital rates are unknown for a specific population or life history stage, researchers often replace them with estimates from other populations of the same species. Such ‘hybrid’ matrices might ignore among‐population life history variation and lead to incorrect inferences.

In this study, we examined the real‐world effect of using hybrid matrices on demographic inference and management decisions, using a large dataset on yellow‐bellied toad (Bombina variegata) populations, an amphibian species whose life history depends on human land use. We estimated stage‐specific survival and recruitment for 18 populations across different habitat types. We then assessed how estimated population growth rates and elasticities changed when population‐specific vital rates were replaced by estimates from other populations, chosen randomly or based on habitat, demographic or geographic proximity.

The use of hybrid matrices mixing demographic estimates from different populations and habitats biased predictions. The mean bias was relatively minor even when sampling randomly across all populations, because our large dataset represented the whole range of life histories and errors cancelled out on average. However, borrowing estimates from geographically close or demographically similar populations substantially reduced the risk of extreme errors. Borrowing from populations from similar habitat types could also reduce bias, but results varied depending on the exact habitat types concerned.

Our study illustrates how habitat‐specific among‐population variation in life history affects the reliability of population matrices commonly used in evolutionary demography, ecology and conservation. When the use of hybrid population matrices cannot be avoided, their creation can be informed by additional information about ecological or demographic patterns, helping reduce bias. When such information is not available, we recommend that studies should consider the whole space of parameter estimates (the complete range of estimates available), thus transparently describing the true uncertainty surrounding demographic estimates.
Cacao grafting increases crop yield without compromising biodiversity
Authors: Ocampo‐Ariza Carolina , Müller Sophie , Yovera Fredy , Thomas Evert , Vansynghel Justine , Maas Bea , Steffan‐Dewenter Ingolf , Tscharntke Teja
Published: January 2025

Yields of tropical tree crops decline with time, often forcing smallholders to establish new deforestation‐derived plantations. Consequently, alternative strategies reconciling crop yield and biodiversity conservation are essential. Grafting is a common propagation method to boost yield in crops as cacao, but it alters tree structure potentially affecting associated insect diversity.

We investigated how grafting affects cacao yield and biodiversity, modulated by local management and landscape, that is shade‐tree cover and distance to nearest forest. Within nine organic agroforests in Peru, we monitored the number of pods yielded over 2 years by ~190 trees per plot, and compared production levels with non‐grafted trees. We collected arthropods on 54 trees shortly after grafting and replicated surveys in the dry and rainy season, with standardized diurnal and nocturnal inspection of tree branches. We expected grafting would increase yield after a brief gap, while the arthropod community associated with freshly grafted cacao would differ from that of full‐grown cacao trees.

Cacao grafting increased yields after 2 years by an average of 45% more than adjacent non‐grafted trees. Compared to non‐grafted trees, arthropod abundance was 25% lower 3 months after grafting and 12% lower after 6 months, indicating a recovery of arthropod communities shortly after grafting. Similar patterns were observed for species richness (22% and 12%) and Hill–Shannon diversity (18% and 13%). Abundance of phytophagous insects (mainly aphids) was unchanged with grafting. However, we found 46% fewer beetles and 39% fewer predatory arthropods (mainly spiders) on young—but not old—grafted cacao, indicating a possible decrease in pest control services by predatory arthropods at early grafting stages.

We observed richer, more diverse, but less abundant arthropods during nocturnal surveys than on diurnal surveys. Arthropods were richer, more abundant and diverse in the rainy season than in the dry season. Increasing shade‐tree cover decreased arthropod diversity but did not affect species richness or abundance. Shorter distances from forest decreased richness and diversity, but not abundance, possibly due to higher pressure from vertebrate predators nearby forests.

Synthesis and applications. Grafting is a successful approach for rejuvenating old, unproductive cacao trees, enhancing smallholder income opportunities and thus reducing pressure for new deforestation‐based plantations. Grafting briefly reduced arthropod abundance and diversity, but recovered in a short time. Hence, rejuvenation of cacao trees by grafting should be promoted and implemented as a promising strategy for more sustainable social‐ecological cacao management, with economic and ecological benefits for smallholders.