bluuebunny/crossref_metadata_2025_split huggingface dataset:
Placental Nutrient Transport and Signaling in a Guinea Pig Model of Fetal Growth Restriction with Repeated Placental Nanoparticle-mediated IGF1 Treatment
Authors: Davenport Baylea N , Wilson Rebecca L , Williams Alyssa A , Jones Helen N 
Published: January 2025

ABSTRACTRoughly 10% of all pregnancies are affected by fetal growth restriction (FGR). The primary etiology of FGR is placental insufficiency: the placenta not providing the appropriate amount of nutrients and oxygen to the fetus. There is currently no treatment for FGR or placental insufficiency. Because of the placentas pivotal role in FGR and supplying nutrients to the fetus, it offers an excellent target for therapeutic intervention. Using a guinea pig maternal nutrient restriction model and a repeated placental nanoparticle-mediated IGF1 treatment, placental IGF1 signaling and nutrient transport pathways were characterized to understand changes with FGR and treatment. This study elucidates the signaling mechanisms in which repeated placental nanoparticle-mediated IGF1 treatment leads to correct fetal growth. Overall, this study resulted in sex-specific kinase signaling and nutrient transporter changes within the placenta in both FGR and treatment groups. Combined with our previous studies using this treatment, we demonstrate the basic molecular signaling of this treatment and recapitulate the plausibility of this therapy for future human translation.
Selective Targeting of Pathogenic Tau Seeds via a Novel VHH
Authors: Gupta Ankit , Liu Richard , Keely Devin , Sunderman Victoria , Tak Yogesh , Kostantoulea Katerina , Terpack Sandi Jo , White Charles L. , Russ William P. , Rizo Josep , Louros Nikolaos , Vaquer-Alicea Jaime , Diamond Marc I. 
Published: January 2025

AbstractIn Alzheimer’s disease (AD) and related tauopathies, progressive pathology has been linked to prion mechanisms, whereby ordered tau assemblies, or “seeds,” form in one cell and transit to neighboring or connected cells where they serve as templates for their own replication. Despite intensive efforts to develop early diagnosis and effective treatment, none has emerged. This is due partly to the structural heterogeneity of tau seeds and limitations in selectively targeting their pathogenic conformations. Here we report the discovery of a camelid variable heavy domain of heavy chain (VHH) that preferentially binds tau seeds of AD, corticobasal degeneration (CBD), and PS19 tauopathy mouse brains. From a published synthetic VHH yeast display library, we identified VHH clones that bound 2N4R tau monomer. After counter-screening for immunoprecipitation of seeding from human brain, we identified two seed-selective anti-tau VHH—VHH(510) and VHH(50)—that preferentially bound pathological tau. We enhanced the stability of these VHHs through framework mutations without affecting their seed-binding characteristics. We characterized VHH(510) in detail, determining that it binds the carboxy terminus of tau, maintains robust seed avidity even in the presence of competing monomer, and stains pathological tau inclusions in mouse and human AD tissues. These results highlight the power of seed-selective VHH to bind pathogenic tau, paving the way for future therapeutic and diagnostic applications across a wide range of neurodegenerative disorders.
Unveiling the dark side of virtual work climate: the mediating role of blurred work-nonwork boundaries
Authors: Li Rui-Xiao , Lim Yet-Mee , Tan Garry Wei-Han 
Published: January 2025

PurposeThis research investigates the dark sides of virtual work climate by examining how blurred work-nonwork boundaries serve as a turning point leading to amotivation at work.Design/methodology/approachThis quantitative study involved 487 employees from small and medium-sized enterprises in China who completed a self-administered questionnaire. Data were analyzed using the partial least squares structural equation modeling (PLS-SEM) method.FindingsThe study found that virtual work climate positively influences workplace flexibility. However, blurred work-nonwork boundaries mediate the relationship between workplace flexibility and psychological demands, transforming the positive effects of virtual work climate in terms of flexibility into negative outcomes. Psychological demands from both work and nonwork domains contribute to amotivation at work.Practical implicationsThe study provides practical insights for managers on satisfying employees’ needs for flexible working arrangements within a virtual work climate by advocating for clear policies that establish distinct work-nonwork boundaries, thereby ensuring employee motivation is not compromised.Originality/valueThis research unveils the dark sides of the virtual work climate, extending the self-determination through the lens of the “too-much-of-a-good-thing” theory. The findings suggest that blurred work-nonwork boundaries may be the turning point where the virtual work climate leads to amotivation at work.
Driving regional advancement: exploring the impact of science and technology parks in the outermost regions of Europe
Authors: Lopes João M. , Gomes Sofia , Ferreira João J.M. , Dabic Marina 
Published: January 2025

PurposeEurope’s outermost regions are often geographically isolated, and they face challenges when it comes to fostering innovation. This study aims to evaluate the impact of Science and Technology Parks (STPs) on the stimulation of innovation performance and the regional development of innovation in the outermost European regions. This study contributes to the development and interpretation of STP literature, which is especially relevant for policymakers operating within these regions.Design/methodology/approachWe collected the data from six Regional Innovation Scoreboard reports (RIS, 2012; RIS, 2014; RIS, 2016; RIS, 2017; RIS, 2019; and RIS 2021), available at https://ec.europa.eu, for the following outermost regions of Europe: the Autonomous Regions of Azores and Madeira (Portugal), the Canary Islands (Spain) and the Outermost Regions of France, which encompass Martinique, Mayotte, Guadeloupe, French Guiana, Saint-Martin and Reunion Island.FindingsThe results demonstrate that, for STPs to positively impact regional policies for innovation and regional development, policymakers must make significant investments into research and development (R&D). The outermost European regions display characteristics that negatively affect innovation performance and regional development. Furthermore, we found that innovative products and services are negatively affected by these regions, as they deploy only a limited number of resources. We also conclude that the impact of STPs on the outermost European regions depends on the policies of regional governments. STPs represent important inputs to formulating and implementing innovation strategies for regional development.Research limitations/implicationsThis study has some limitations. This research only analyses the European Union's (EU’s) outermost regions, and we have only included data extracted from the Regional Innovation Scoreboard from 2007 to 2021. Disaggregated data for the five outermost regions in France was not available. This would have increased the sample and made the results even more robust, had the information been available.Practical implicationsThe results propose that regional actors in the outermost regions (industry–government–academia) better articulate their resources (which are more scarce) and their priorities with regard to Science, Technology and Innovation, thus accelerating innovation and development of their regions.Originality/valueIn this panel data study, we adopt a methodology that enables the evaluation of STP performance under different levels of intensity of gross domestic expenditure on research and development activities in the context of the RIS. In this study, the RIS refers to the peripheral regions of the EU. This study therefore aims to evaluate the impact of STPs in stimulating innovation performance and regional development in the outermost regions of Europe.
Historical geopolitical risk acts and world crude oil production: evidence from the international level
Authors: Sweidan Osama D. 
Published: January 2025

Purpose
The purpose of this study is to empirically investigates the influence of geopolitical risk acts (GPR) on world crude oil production. GPRs are a proxy for waging wars and military actions, thus it is expected to have a clear impact on world crude oil production (WCOP).

Design/methodology/approach
The current study formulates a theoretical model, and its parameters are estimated using three methodologies – traditional autoregressive distributed lag (ARDL) model, Dynamic ARDL model, and Frequency domain causality test – across the period 1973–2023 to ensure robust findings.

Findings
The results illustrate that GPRs constrain the global crude oil supply. The final impact relies on the positive interaction term between GPRs and international economic activity from one side and the negative interaction term with crude oil prices from the other. Likewise, the findings show that geopolitical threats reduce producing crude oil. Furthermore, this research deliberates on policy implications stemming from these findings.

Originality/value
Examining existing literature reveals a gap in understanding the relationship between geopolitical risk and crude oil production. Most of the studies in this research strand focus on investigating the impact on oil price volatility.
Artificial intelligence for personalized learning: a systematic literature review
Authors: Hardaker Glenn , Glenn Liyana Eliza 
Published: January 2025

PurposeThe purpose of this systematic literature review is to identify the antecedents that have enabled the adoption of artificial intelligence (AI) in Higher Education (HE) institutions at both a macro and micro level. The term adoption is in reference to the diffusion of technology that is actively chosen for use by the targeted demographic. Within the context of this paper, adoption is largely referring to the factors that influence the acceptance and use of AI as a tool for personalized learning.Design/methodology/approachTo develop our understanding and appreciation of the valuable impact that AI potentially has upon personalized learning the following systematic literature review was conducted. An acceptable systematic literature review is a comprehensive method of fully analysing and evaluating all available research in the chosen area or specific research query.FindingsThe findings from this study have particular implications for personalized learning in the adoption and diffusion of AI and an increasing integration of macro, structural, and micro, individual. Developing and managing AI in education is seen, from the literature, to becoming more embedded in the teaching and learning process. The paper identifies the following: antecedents that supports the adoption of AI for personalized learning; application of AI technologies in the teaching and learning process; AI technologies that enable personalized instruction and learning; generative AI that supports intuitive learning through tracking data.Originality/valuePersonalized learning remains focused on customizable “choice-driven” learning and education. In addition, personalized learning and instruction is defined as being a responsive and structured method that adapts to each individual learner’s method of learning so that all may achieve their capabilities and actively participate. This solidifies the intrinsic connection between teaching and learning through personalized technologies such as AI.
Regional heterogeneities in returns to education in Zambia: a quantile regression analysis
Authors: Nsokolo Denny S. , Simo-Kengne Beatrice , Chama-Chiliba Chitalu Miriam 
Published: January 2025

PurposeThis study determines the existence of regional heterogeneities in returns to education in Zambia. It seeks to analyse the differential impact of education on wages across different geographical regions of Zambia. Adopting a regional approach, the study employs novel empirical methods to understand the pecuniary benefits of education at the sub-national level.Design/methodology/approachThe study analyses data from Zambia’s 2021 Labour Force Survey. It employs modified human capital models and quantile regression techniques to examine how returns to education differ across regions and the wage distribution.FindingsResults show a distinctive heterogeneous pattern in which returns to education are higher in urban regions, followed by peri-urban, and lowest in the rural region. Results further show that returns to education increase with the level of education and are highest at the tertiary level. Quantile regression estimates reveal that returns to education vary across income levels within regions, suggesting a necessity for tailored policy interventions. Additionally, individuals’ health conditions display direct effects on their earnings potential.Originality/valueThis study adopts a modified human capital model to account for the health dimension, which has received less attention in past returns to education research. Furthermore, a regional approach is employed to capture within-country variations necessary for designing policy interventions aimed at addressing region-specific challenges.Peer reviewThe peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-03-2024-0262
The GreenComp Evaluation Roadmap: a roadmap for in-depth holistic evaluation of the integration of the GreenComp framework in higher-education curricula
Authors: Mertens Anouk , Eppinga Maarten B. , Arens Patrick , de Scisciolo Tobia , John Nigel , Sultan Salys , Buys Nadine , Mijts Eric N. 
Published: January 2025

Purpose
The GreenComp framework identifies 12 competences for sustainability as common ground for higher-education curricula. The framework can be used for self-assessment and the review of curricula. However, a step-by-step method to conduct such a self-assessment is not yet available for the GreenComp framework specifically. Therefore, the authors present the GreenComp Evaluation Roadmap allowing to evaluate the extent to which the frameworks’ competences for sustainability are integrated in higher-education curricula. The application of the GreenComp Evaluation Roadmap to a curriculum taught at the University of Aruba, allows to report on the benefits, limitations and future potential of the approach.

Design/methodology/approach
The proposed mixed-method approach combines hybrid qualitative and quantitative data collection on the integration of the 12 competences for sustainability of the GreenComp framework in higher-education curricula. The authors showcase its potential through application of the GreenComp framework as an evaluation tool to a science, technology, engineering and mathematics-based bachelor program taught at the University of Aruba.

Findings
The GreenComp Evaluation Roadmap not only allows for an evaluation of the curriculum and identification of competence gaps. It also supports educators to conduct a self-reflection on individual course(s) and the program as a whole. The paper shows promising results that the roadmap developed could be a reproducible approach. Moreover, it provides guidance to other higher education institutes for self-evaluation and self-reflection on how the competences for sustainability are integrated in their curricula and how this can be enhanced in the future.

Originality/value
The need to integrate sustainability throughout higher-education curricula is broadly recognized. The GreenComp Evaluation Roadmap contributes to the literature by offering a methodological approach to evaluate the integration of the 12 competences for sustainability throughout a curriculum.
Predicting the churn patterns of monetizers and non-monetizers: exploring the influence of behavioral variability in churn prediction
Authors: Wu Ruei-Yan , Hu Ya-Han , Chou En-Yi 
Published: January 2025

PurposeAlthough prior research has employed various variables to predict player churn, the dynamic evolution of the behavioral patterns of players has received limited attention. In this study, churn prediction models are developed by incorporating the progress level, in-game purchase, social interaction, behavioral pattern and behavioral variability (BV) of players in social casino games (SCGs). The study distinguishes churn prediction between two player groups: monetizers and non-monetizers.Design/methodology/approachThis study employs three machine learning techniques—logistic regression, decision trees and random forests—using real-world player data from an SCG company to construct churn prediction models. Two experiments were conducted. In Experiment 1, BV was combined with four other variable categories to effectively predict churn behaviors across all players (n = 52,246). In Experiment 2, churn prediction models were developed separately for monetizers (n = 16,628) and non-monetizers (n = 35,618).FindingsThe findings from Experiment 1 indicate that incorporating BV significantly improves the overall performance of churn prediction models. Experiment 2 demonstrates that churn prediction models achieve better performance and predictive accuracy for monetizers and non-monetizers when BV is calculated over the 3-day to 7-day and 7-day to 14-day windows, respectively.Originality/valueThis study introduces BV as a novel variable category for churn prediction, emphasizing within-person variability and demonstrating its effectiveness in enhancing model performance. Churn prediction models were independently constructed for monetizers and non-monetizers, utilizing different time windows for variable extraction. This approach improves predictive performance and highlights key differences in critical variables influencing churn across the two player groups. The findings provide valuable insights into churn management strategies tailored for monetizers and non-monetizers.
Popular reporting in the public sector: a systematic literature review and reflections for future research
Authors: Joaquim Ricardo , Jorge Susana , Pimentel Liliana Marques 
Published: January 2025

Purpose
This study aims to characterize, quantitatively and qualitatively, the existing research on popular reporting (PR) in the public sector, to synthesize and evaluate its current state. An overview of published research in this field will ultimately allow us to identify trends and opportunities for future research.

Design/methodology/approach
The paper combines both quantitative and qualitative analyses of scientific papers selected from the Web of Science (WoS) and Scopus databases. It analyzes mainly the evolution of production over the years, areas of knowledge, authors and their affiliations, methodological approaches, countries and jurisdictions and research topics explored.

Findings
PR in the public sector is a topic still in an early stage of research (only 19 papers in the last eighteen years), by a very limited number of authors. Studies have mainly focused the USA and the local governments. Qualitative methods, namely case studies, have prevailed. Most of the empirical approaches have addressed possible characteristics and content of the PR. Non-empirical papers broadly have suggested PR as a tool to increase accountability.

Research limitations/implications
Given its potential contribution to accountability in the public sector, it seems important that PR becomes an institutionalized practice. For this, it is necessary to deeper understand and study this matter. The development of effective practice guidance and standards by regulators and the like, would be leveraged by the contribution of academics by increasing research on this topic. The research would benefit from more authors interested in the topic and an extension to countries other than the USA and Italy, and jurisdictions other than the local governments.

Originality/value
To the best of the authors’ knowledge, no study so far has sought to characterizing the existing research on PR in the public sector. This study contributes by identifying trends and gaps in this research field, proposing topics for future development, which can help academics to develop research that adds to the advancement of this field. Research gaps identified point to a need to empirically confirm the impact of PR on accountability. Also, exploring about the content of PR may in the future include, among other topics, the perspective of the politicians and public managers. In addition, studying the reasons why preparers do not adhere to PR and whether jurisdictions’ institutional factors influence this decision, can advance in understanding the issues of implementing PR in the context of public sector overall.
Adoption and impact of generative artificial intelligence on blockchain-enabled supply chain efficiency
Authors: Gao Cong , Keoy Kay-Hooi , Lim Ai-Fen 
Published: January 2025

Purpose
The purpose of this study is to investigate the primary determinants influencing the acceptance of generative artificial intelligence (GAI) adoption within Blockchain-enabled environments. Further research will examine the impact of GAI adoption on supply chain efficiency (SCE) through the enhancement of Blockchain.

Design/methodology/approach
Drawing on innovation diffusion theory (IDT), this study used partial least square structural equation modelling (PLS-SEM) to look into the hypotheses. The data were gathered via online questionnaires from employers of Chinese supply chain enterprises that have already integrated Blockchain.

Findings
The findings of this study demonstrate that relative advantages (RAs), compatibility, trialability and observability have a significant positive effect on GAI adoption, while complexity harms GAI adoption. Above all, the GAI adoption has significantly enhanced Blockchain, thus effectively improving SCE.

Practical implications
The outcomes from this study furnish enterprises and organizations with valuable insights to proficiently integrate GAI and Blockchain capability, optimize supply chain management and bolster market competitiveness. Also, this study will help accelerate the successful integration of business processes and attain Sustainability Development Goals 9, industrial growth and industrial diversification.

Originality/value
To the extent of the author’s knowledge, the current status of the GAI study remains largely exploratory, and there is limited empirical evidence on integrating Blockchain capability and GAI. This research bridges the knowledge gap by fully revealing the optimal integration of these two transformative technologies to leverage their potential advantages in supply chain management.