bluuebunny/crossref_metadata_2025_split huggingface dataset:
Convergent mechanisms, divergent strategies: a comparison of nectar intake between a generalist and a specialized bat species
Authors: Quinche Laura L. , Garzón-Agudelo Felipe , Santana Sharlene E. , López-Arévalo Hugo F. , Rico-Guevara Alejandro 
Published: November 2024

ABSTRACTNectar-feeding bats exhibit a range of specialized adaptations that allow them to efficiently extract nectar from flowers. These adaptations include diverse tongue morphological traits and feeding strategies that reflect varying degrees of specialization for nectarivory. While the feeding mechanisms of highly specialized nectar-feeding bats are well-studied, little is known about the feeding behaviors of non-specialized species likePhyllostomus discolor. This study compares the nectar extraction behaviors ofP. discolorand the specializedAnoura geoffroyi, examining morphological and biomechanical adaptations that affect nectar-feeding efficiency and foraging strategies. Using high-speed videography, we analyzed the feeding behaviors of both species, focusing on tongue kinematics, and feeding efficiency. Both species used a brush-tongue lapping technique but exhibited notable behavioral and kinematic differences, resulting in efficiency variations.P. discolorhas a shorter, less flexible tongue thanA. geoffroyi, though its tongue shows similar mobility capacities (licking frequency). UnlikeA. geoffroyi, which hovers to feed,P. discolorlands, allowing for longer visits and greater nectar extraction per visit. However,P. discolordemonstrated lower feeding efficiency, likely due to its reduced tongue specialization for nectarivory. These findings reveal convergence in the general feeding mechanism but highlight differences in morphological and behavioral specialization that affect feeding kinematics and efficiency. Our study illuminates how foraging strategy and tongue morphology impact feeding efficiency, pointing to evolutionary pathways that promote niche differentiation within nectar- feeding bat communities.
Unraveling Microglial Spatial Organization in the Developing Human Brain with DeepCellMap, a Deep Learning Approach Coupled to Spatial Statistics
Authors: Perochon Theo , Krsnik Zeljka , Massimo Marco , Ruchiy Yana , Romero Alejandro Lastra , Mohammadi Elyas , Li Xiaofei , Long Katherine R , Parkkinen Laura , Blomgren Klas , Lagache Thibault , Menassa David A , Holcman David 
Published: November 2024

AbstractMapping cellular organization in the developing brain presents significant challenges due to the multidimensional nature of the data, characterized by complex spatial patterns that are difficult to interpret without high-throughput tools. We developed DeepCellMap, a deep-learning-assisted tool that integrates multi-scale image processing with advanced spatial and clustering statistics. This pipeline was designed to map microglial organization during normal and pathological brain development but can be adapted to any cell type. Using DeepCellMap, we capture the morphological diversity of microglia, identify strong coupling between proliferative and phagocytic phenotypes, and show that distinct spatial clusters rarely overlap as human brain development progresses. Additionally, we uncover a novel association between microglia and blood vessels in fetal brains exposed to maternal SARS-CoV-2. These findings offer insights into whether various microglial phenotypes form networks in the developing brain to occupy space, and in conditions involving haemorrhages, whether microglia respond to, or influence changes in blood vessel integrity. DeepCellMap is available as open-source software and is a powerful tool for extracting spatial statistics and analyzing cellular organization in large tissue sections, accommodating various imaging modalities. This platform could open new avenues for studying brain development and related pathologies.
Deep learning super-resolution of paediatric ultra-low-field MRI without paired high-field scans
Authors: Briski Ula , Bourke Niall J. , Donald Kirsten A. , Bradford Layla E. , Williams Simone R. , Zieff Michal R. , Deoni Sean C.L. , Williams Steven C.R. ,   Khula South Africa Study Team, Moran Rosalyn J. , Baljer Levente , Váša František 
Published: November 2024

AbstractBrain magnetic resonance imaging (MRI) is essential for diagnosis and neurodevelopmental research, but the high cost and infrastructure demands of high-field MRI scanners restrict their use to high-income settings. To address this, more affordable and energy-efficient ultra-low-field MRI scanners have been developed. However, the reduced resolution and signal-to-noise ratio of the resulting scans limit their clinical utility, motivating the development of super-resolution techniques. The current state-of-the-art super-resolution methods require either three anisotropic ultra-low-field scans acquired at different orientations (axial, coronal, sagittal) to reconstruct a higher-resolution image using multi-resolution registration (MRR), or the training of deep learning super-resolution models using paired ultra-low- and high-field scans. Since acquiring three high-quality ultra-low-field scans is not always feasible, and paired high-field data may not be available for the target population, this study explores the efficacy of using a deep learning model, the 3D UNet, to generate higher-resolution brain scans from just one ultra-low-field scan. The model was trained to receive a single ultra-low-field brain scan of 6-month-old infants and produce a scan of MRR quality. Results showed a significant improvement in the quality of output scans compared to input scans, including increased image quality metrics, stronger correlations in tissue volume estimates across participants, and greater Dice overlap of the underlying tissue segmentations to those of target scans. The study demonstrates that the 3D UNet effectively enhances the resolution of ultra-low-field infant MRI scans. Generating higher-resolution brain scans from single ultra-low-field scans, without needing paired high-field data, reduces scanning time and supports wider MRI use in low- and middle-income countries. Additionally, this approach allows for easier model training on a site- and population-specific basis, enhancing adaptability in diverse settings.
Optimizing longitudinal spin relaxation in miniaturized optically pumped magnetometers
Authors: McWilliam A.P. , Dyer S. , Hunter D. , Mrozowski M. , Ingleby S.J. , Sharp O. , Burt D.P. , Griffin P.F. , McGilligan J.P. , Riis E. 
Published: December 2024

The microfabrication of cesium vapor cells for optically pumped magnetometry relies on optimization of buffer gas pressure in order to maximize atomic coherence time and sensitivity to external magnetic signals. We demonstrate post-bond nitrogen buffer gas pressure tuning through localized heating of an integrated micropill dispenser. We characterize the variation in the intrinsic longitudinal relaxation rate, γ10, and magnetic sensitivity, as a function of the resulting nitrogen buffer gas pressure. Measurements are conducted by employing an optically pumped magnetometer operating in a free-induction-decay configuration. γ10 is extracted across a range of nitrogen pressures between 60 and 700 torr, measuring a minimum of 140 Hz at 115 torr. In addition, we achieve sensitivities as low as 130 fT/Hz at a bias field amplitude of about50μT. With the optimal nitrogen buffer gas pressure now quantified and achievable post-fabrication, these mass-producible cells can be tailored to suit a variety of sensing applications, ensuring peak magnetometer performance.

Published by the American Physical Society
2024
Fuzzy repetitive scheduling for construction projects considering risk preferences and time-cost tradeoffs
Authors: Zou Xin , Zhang Lihui 
Published: November 2024

PurposeThe purpose of this study is to develop a novel approach that addresses time-cost tradeoffs in repetitive construction projects while considering the uncertainty in activity durations and the risk preferences of planners.Design/methodology/approachOur study involves work in three aspects. Firstly, it employs triangular fuzzy numbers to represent activity durations in different units, which facilitates the management of scenarios characterized by limited historical data or the presence of ambiguous information. Secondly, it introduces a fuzzy chance-constrained programming model, which is aimed at minimizing the project budget while ensuring that the risks associated with cost overruns and schedule delays are confined to specified limits. Thirdly, it advances an enhanced genetic algorithm, integrating an electromagnetism-like mechanism and a scheduling repair process, to improve the efficiency and effectiveness of the optimization process.FindingsA real-life street renovation project was analyzed to demonstrate the applicability of the proposed algorithm. The analysis explored three common types of risk preferences: risk-averse, risk-neutral and risk-loving. The results indicate that the proposed algorithm surpasses existing fuzzy repetitive scheduling methods in terms of risk management. It effectively generates schedules that align with the risk preferences of planners and provides worst-case estimates of project performance.Originality/valueThis research makes a significant contribution to the field by developing a fuzzy chance-constrained programming model and an associated optimization algorithm that is specifically designed for time-cost tradeoffs in repetitive construction projects. A key distinction is that this study considers the risk preferences of planners, which sets it apart from previously developed models. As a result, it provides a practical approach for effective risk management.
Fresh start mindset and attitudes toward the banks: the mediating role of optimism judgment bias and face arousal
Authors: Junior Ladeira Wagner , Azhar Mohd , Rasul Tareq , Santini Fernando 
Published: November 2024

PurposeThis paper aims to analyze the effects of a fresh start mindset on attitudes toward the banks. Furthermore, we try to predict how optimism judgment bias and arousal can affect the effects of the fresh start mindset through three research questions.Design/methodology/approachThree experiments explored the effect of the fresh start mindset in the banking sector. Study 1 collects data in a laboratory. Study 2 is an online experiment. Study 3 collects data in a laboratory through facial movements.FindingsOur results clarify research gaps in studies regarding financial decisions by demonstrating that a fresh start mindset increases attitudes toward banks. In this way, a fresh start mindset can influence the optimism judgment bias by promoting underlying mechanisms that highlight the change through new paths regardless of past or present, thus promoting positive attitudes. Our results also confirm a hypothesis that stimulation of a new reality can generate arousal in cognitive processing and consumers’ willingness to interact.Practical implicationsUnderstand how campaigns and nudges around fresh starts can increase marketing campaigns’ success and help customers improve their financial well-being.Originality/valueOur paper demonstrates how previous studies in the banking sector have neglected the fresh start mindset and offers mechanisms to understand the effects of optimism judgment bias and phasic arousal expression on attitudes toward the banks.
What’s driving them? A qualitative approach to explore women entrepreneurs’ motivations in STEM
Authors: Voss Julia , Butz Benjamin , Ettl Kerstin 
Published: December 2024

PurposeEntrepreneurship and the disciplines of science, technology, engineering and mathematics (STEM) are considered important drivers of innovation. At the same time, the representation of women entrepreneurs in STEM remains low. Despite this disparity, a number of women still choose to start ventures and persist in pursuing their innovations in STEM. This study aims to examine the motivational factors that drive women entrepreneurs to approach and consistently pursue their innovations and ventures in STEM.Design/methodology/approachDrawing on the concept of the heterogeneity of motivational factors (Graham and Bonner, 2022) and Social Cognitive Theory (Bandura, 1986, 2001; Wood and Bandura, 1989), 24 semi-structured interviews were conducted with women entrepreneurs in STEM. This approach allowed for an in-depth exploration of the heterogeneous motivational factors influencing women entrepreneurs in STEM.FindingsThe motivations of women entrepreneurs in STEM are multifaceted, interrelated and dynamic. They encompass personal and cognitive, behavioral and environmental factors and partly change over time. This study reveals two levels of heterogeneity: the heterogeneity of women entrepreneurs’ entrepreneurial motivations, and the within-context heterogeneity of women entrepreneurs in STEM themselves.Originality/valueThis study addresses the need for a deeper understanding of women entrepreneurs in STEM. By focusing on nuanced aspects of entrepreneurial motivations that are often overlooked in the existing literature, this research provides valuable insights and discusses implications for theory, policy and education.
The interplay of safety knowledge, attitude and health experience in adoption of protective pesticide behavior: evidence from Pakistani fruit and vegetable farmers
Authors: Imran Muhammad , Mustafa Ghulam , Rehman Shafique Ur , Yasri Yasri 
Published: December 2024

PurposeThis study aims to examine the unique and interaction effects of farmers’ pesticide safety knowledge and their past pesticide-related health problems experienced in the adoption of protective pesticide behaviors. The study further aims to explore whether attitude toward pesticide use mediate the relationship between pesticide safety knowledge and protective behaviors.Design/methodology/approachData were collected from 385 Pakistani fruit and vegetable farmers using a cross-sectional survey design and were analyzed using Partial least squares structural equation modeling (PLS-SEM).FindingsThe empirical analysis revealed that pesticide safety knowledge is positively associated with protective behaviors and farmers’ attitude toward pesticide use partially mediates this relationship. The findings further show that past health problems positively influence the adoption of protective pesticide behaviors, which is amplified when pesticide safety knowledge is high.Research limitations/implicationsThis study findings have significant implications for policy interventions and agricultural extension programs aimed at promoting safer pesticide use.Originality/valueThis research contributes to the previous literature by presenting an integrative framework of the knowledge-attitude-practice model and protection motivation theory to explore the influence of farmers’ pesticide safety knowledge, past pesticide-related health experiences and attitude toward pesticide use on their adoption of protective pesticide behaviors.
The role of AI-enabled health systems in the Jordanian context: the case of digital contact tracing apps
Authors: Al-Okaily Manaf , Shiyyab Fadi Shehab , Salim Nesreen A. , Al-Rahayfeh Amer 
Published: December 2024

PurposeDigital health or digital healthcare, is a broad, multidisciplinary concept that includes concepts from an intersection between technology and healthcare. Digital health applies digital transformation to the healthcare field, incorporating software, hardware and services. The usefulness of digital health technologies such as digital contact tracing apps (CTAs) depends deeply on the acceptance to use them. Accordingly, the main purpose of this study is to explore the usage of CTAs by integrating the protection motivation theory (PMT) and technology acceptance model (TAM) in the Jordanian context.Design/methodology/approachPartial least squares structural equation modelling was employed to test empirically the integrated research model against data collected from 420 respondents, leading to the identification of the important determinants for the usage of CTAs.FindingsThe results reveal that perceived severity and perceived vulnerability have a significant positive impact on the perceived need for CTAs, which, in turn, affects the individuals’ intention to use CTAs. It also reveals that perceived trust in government, perceived privacy and perceived usefulness have a significant positive impact on individuals’ intention to use CTAs, which, in turn, affects the usage of CTAs. In contrast, perceived ease of use did not find any significant relationship, and hence hypothesis H7 was not supported. Lastly, social media awareness has a significant positive impact on perceived usefulness and ease of use.Originality/valueThis study is considered among the first studies in the Jordanian context that integrate the PMT and TAM to gain a better understanding of the critical determinants for the acceptance and usage of CTAs in the context of pandemics.
Gender, anxiety and perceived Islamic values in students’ debt attitudes and behaviour: an ethnographic study of an Indonesian multicultural university
Authors: Rahadi Ashri Putri , Koesrindartoto Deddy Priatmodjo , Wisesa Anggara 
Published: December 2024

Purpose
To mitigate debt repayment ability in underbanked borrowers such as students, debt attitude is used as an initial approach. This study aims to focus on how students’ debt attitudes and behaviours are shaped from a cultural point of view.

Design/methodology/approach
Through qualitative research in one of Indonesia’s multicultural universities, ethnography was used to elicit a stable dominant cultural factor that shapes students’ debt attitudes and behaviours.

Findings
Perceived Islamic values were found to induce debt anxiety but to encourage positive coping strategies such as prioritising debt repayment, minimising consumption and spending and avoiding shirking one’s responsibilities.

Research limitations/implications
Debt is a complex issue, and the authors have simply examined the impact of religion on attitudes and behaviours. Nonetheless, other important variables are considered in the literature, such as family and a debt-friendly atmosphere. This research was constrained by time and finance, so it only relates to ITB students. Additionally, understanding why women were more likely to be anxious because of their embracing of debt-related Islamic values from a religious point of view is absent in the literature, and thus requires future investigation.

Practical implications
The findings offer two practical implications. Firstly, this study could improve the credit assessment process to detect debt anxiety more accurately because the causality of anxiety is known. Furthermore, when detecting debt-relax, creditors may demand a higher financial literacy score to minimise non-payment. Secondly, with regard to financial literacy, Indonesians exhibit low levels, with only 32% considered to be financially literate according to the 2020 OECD assessment. By recognising the stable cultural factor influencing debt attitudes and behaviours, educators, creditors and policymakers can enhance financial literacy programme efficiency with participants’ religious values.

Social implications
In the context of limited financial literacy, Islamic values can be beneficial for society because their perception and practice could induce debt anxiety while generating positive anxiety-coping mechanisms identified as anti-debt behaviours.

Originality/value
Previous research has found correlations between religiosity and attitudes, as well as between gender and attitudes, towards debt. However, to the best of the authors’ knowledge, this study is the first to demonstrate that perceived religiosity causes anti-debt attitudes and behaviours, which is more evident in anxiety-prone women. The findings answer the calls of Harrison et al. (2013, 2015), Harrison and Agnew (2016) and Kettley et al. (2008) to understand why women possess an aversion to taking on debt, especially from the point of view of cultural and societal norms, as posited by Meyll and Pauls (2019).
Focused literature review on accreditation and quality assurance: insights and future research agenda
Authors: Kumar Atul , Paliwal Jaiprakash , Singh Mahesh , Pendse Vishwas , Gade Rajesh , Palav Manesh , Raibagkar Shirish 
Published: December 2024

Purpose
Accreditation, a proven quality strategy, can help educational institutions at all levels in attaining Sustainable Development Goal 4 (SDG4). The purpose of this study, therefore, is to gain insights from the literature on accreditation and quality assurance and understand the focus areas of existing research. The study also aims at finding out research gaps that would serve as future research agenda.

Design/methodology/approach
A focused literature review methodology was adopted. Based on the search terms “accreditation and quality assurance”, 54 literature items were finally selected for review from standard databases like Scopus, Web of Science and Google Scholar.

Findings
Five overarching focus dimensions emerged from the focused review. These were overview studies, accreditation system-based studies, the role of accreditation in quality assurance, the impact of accreditation on quality assurance and other studies. Major gaps in reviews were also found.

Originality/value
The study provides valuable theoretical and practical insights about accreditation and quality assurance and also lays the road map for future research to address the research gaps.
The ultrastructural and proteomic analysis of mitochondria‐associated endoplasmic reticulum membrane in the midbrain of a Parkinson's disease mouse model
Authors: Liu Jin , Liu Yi , Gao Chao , Pan Hong , Huang Pei , Tan Yuyan , Chen Shengdi 
Published: November 2024

AbstractRecent studies indicated that the dysregulation of mitochondria‐associated endoplasmic reticulum membrane (MAM) could be a significant hub in the pathogenesis of Parkinson's disease (PD). However, little has been known about how MAM altered in PD. This study was aimed to observe morphological changes and analyze proteomic profiles of MAM in 1‐methyl‐4‐phenyl‐1,2,3,6‐tetrahydropyridine (MPTP)‐induced PD mouse models. In MPTP‐treated mice, transmission electron microscopy was applied for MAM ultrastructural visualization. Nano ultra‐high performance liquid chromatography‐tandem mass spectrum and bioinformatic analysis were adopted to obtain underlying molecular data of MAM fractions. The loosened, shortened and reduced MAM tethering was found in substantia nigral neurons from MPTP‐treated mice. In midbrain MAM proteomics, 158 differentially expressed proteins (DEPs) were identified between two groups. Specific DEPs were validated by western blot and exhibited significantly statistical changes, aligning with proteomic results. Bioinformatic analysis indicated that membrane, cytoplasm and cell projection were three major localizations for DEPs. Biological processes including metabolism, lipid transport, and immunological and apoptotic signaling pathways were greatly affected. For consensus MAM proteins, the enriched pathway analysis revealed the potential relationship between neurodegenerative diseases and MAM. Several biological processes such as peroxisome function and clathrin‐mediated endocytosis, were clustered, which provided additional insights into the fundamental molecular pathways associated with MAM. In our study, we demonstrated disrupted ER‐mitochondria contacts in an MPTP‐induced PD mouse model. The underlying signatures of MAM were revealed by proteomics and bioinformatic analysis, providing valuable insights into its potential role in PD pathogenesis.