bluuebunny/crossref_metadata_2025_split huggingface dataset:
SpatialPrompt: spatially aware scalable and accurate tool for spot deconvolution and clustering in spatial transcriptomics
Authors: Swain Asish Kumar , Pandit Vrushali , Sharma Jyoti , Yadav Pankaj 
Published: September 2023

AbstractSpatial transcriptomics has advanced our understanding of tissue biology by enabling sequencing while preserving spatial coordinates. In sequencing-based spatial technologies, each measured spot typically consists of multiple cells. Deconvolution algorithms are required to decipher the cell-type distribution at each spot. Existing spot deconvolution algorithms for spatial transcriptomics often neglect spatial coordinates and lack scalability as datasets get larger. We introduce SpatialPrompt, a spatially aware and scalable method for spot deconvolution as well as domain identification for spatial transcriptomics. Our method integrates gene expression, spatial location, and single-cell RNA sequencing (scRNA-seq) reference data to infer cell-type proportions of spatial spots accurately. At the core, SpatialPrompt uses non-negative ridge regression and an iterative approach inspired by graph neural network (GNN) to capture the local microenvironment information in the spatial data. Quantitative assessments on the human prefrontal cortex dataset demonstrated the superior performance of our tool for spot deconvolution and domain identification. Additionally, SpatialPrompt accurately decipher the spatial niches of the mouse cortex and the hippocampus regions that are generated from different protocols. Furthermore, consistent spot deconvolution prediction from multiple references on the mouse kidney spatial dataset showed the impressive robustness of the tool. In response to this, SpatialPromptDB database is developed to provide compatible scRNA-seq references with cell-type annotations for seamless integration. In terms of scalability, SpatialPrompt is the only method performing spot deconvolution and clustering in less than 2 minutes for large spatial datasets with 50,000 spots. SpatialPrompt tool along with the SpatialPromptDB database are publicly available as open sourcesoftwarefor large-scale spatial transcriptomics analysis.
A study on blockchain-based marketplace governance platform adoption: a multi-industry perspective
Authors: Saurabh Kumar , Upadhyay Parijat , Rani Neelam 
Published: September 2023

PurposeDecentralised autonomous organisations (DAOs) are internet-native self-governing enterprises where individual groups, communities, agencies, consumers and providers work together using blockchain-led smart contracts (SCs). This study aims to examine the role of DAO marketplaces in technology-led autonomous organisation design for enterprise technology sourcing industries, with algorithmic trust and governance.Design/methodology/approachThe authors examined the importance of an enterprise marketplace governance platform for technology sourcing using DAO as a decentralised/democratised business model. A total of 98 DAO products/services are evaluated across 11 industries that envisage DAO as a strategic choice for the governance of decentralised marketplace platforms.FindingsThe research findings validate how a DAO-led enterprise marketplace governance platform can create a cohesive collaboration between consumers (enterprises) and providers (solution vendors) in a disintermediated way. The proposed novel layered solution for an autonomous governance-led enterprise marketplace promises algorithmic trust-led, self-governed tactical alternatives to a strategic plan.Research limitations/implicationsThe research targets multiple industry outlooks to understand decentralised autonomous marketplace governance and develop the theoretical foundation for research and extensive corporate suitability.Practical implicationsThe research underpinnings boost the entrepreneurs’ ability to realise the practical potential of DAO between multiple parties using SCs and tokenise the entire product and service offerings over immutable ledger technologies.Originality/valueTo the best of the authors’ knowledge, this research is unique and the first of its kind to study the multi-industry role of algorithmic trust and governance in enterprise technology sourcing marketplaces driven by 98 decentralised and consensus-based DAO products across 11 industries.
Does female descendent entrepreneur's self-compassion and financial literacy matter for succession success?
Authors: Ahmad Zeshan , Sharif Shahbaz , Ahmad Iftikhar , Abbas Syed Muhammad Waseem , Shaheen Mussrat 
Published: September 2023

PurposePresent study investigated the influence of female descendent entrepreneur's self-compassion on the perceived succession success of small-family businesses (S-FB) with the mediating mechanism of financial literacy.Design/methodology/approachThe primary data was collected from 319 female descendent entrepreneurs who were designated as chairwomen, and managing director positions in their retails sector S-FBs. The purposive sampling technique was used to collect the data. The provided hypotheses are tested using the partial least square structural equation modeling (PLS-SEM) technique. This study followed multiple regression analyses to see the influence of self-compassion (mindfulness, self-isolation, self-judgment and over-identification) on financial literacy and perceived succession success.FindingsThe results reveal that female descendent entrepreneurs mindfulness and over-identification significantly increase but self-isolation decreases the likelihood of successful succession transition. Moreover, female descendent entrepreneur's financial literacy increases mindfulness and overidentification while it decreases self-isolation and improves the likelihood of succession success. However, financial literacy does not influence self-judgmental traits and perceived succession success.Practical implicationsThis study highlights a vital issue, how the financial literacy of female descendent entrepreneurs manages their self-compassion and increases the likelihood of succession success. In addition, it covers a research gap and helps the S-FBs to improve their survival rate by focusing on the descendent entrepreneur's self-compassion and financial literacy.Originality/valueThis study contributes to the body of knowledge by emphasizing predictors that influence the successful succession transition to subsequent generations. This study determines the influence of self-compassion of female descendent entrepreneurs on perceived succession success and financial literacy as a mediator by using the self-control theory. The study can be useful to family business consultants, policymakers and family businesses.
Relaxation, morning recovery state and customer- and coworker-directed extra-role service behavior: the moderating effect of work–family interface
Authors: Park Hyewon , Hur Won-Moo , Rhee Seung-Yoon 
Published: September 2023

PurposeThis study aims to investigate the impact of overnight off-work relaxation on the performance of frontline service employees (FLEs). Specifically, the authors focused on FLEs' customer-directed extra-role service behavior (C-ERSB) and coworker-directed extra-role service behavior (CW-ERSB) as indicators of outstanding service performance. Drawing on the conservation of resources (Hobfoll, 1989) and ego depletion theories (Baumeister, 2002), the authors hypothesized that the positive effect of overnight relaxation on ERSBs will be mediated by the state of recovery. Additionally, the authors examined the boundary conditions of these relationships by testing the moderating effects of work–family conflict (WFC) and family–work conflict (FWC).Design/methodology/approachThe study employed an episodic sampling method. One hundred thirty-five FLEs completed two daily surveys (before- and after-work) over five consecutive workdays, yielding 636 time-lagged day-level observations. Multilevel path modeling was performed to analyze the mediation and second-stage moderated mediation effects.FindingsResults showed that overnight off-work relaxation was positively related to FLEs' next-day C-ERSB and CW-ERSB via next-morning recovery state. The positive relationship between overnight off-work relaxation and the next-morning recovery state was weaker for FLEs who experienced overnight WFC. FWC during work hours weakened the positive relationship between the next-morning recovery state and CW-ERSB, but not the relationship between the next-morning recovery state and C-ERSB.Originality/valueThe study used an episodic sampling method to reveal the significance of off-work relaxation, recovery and family–work interface on FLEs' ERSBs, a critical yet underexplored phenomenon in service literature. This study sheds light on the pathways to achieve exceptional service performance by revealing the importance of overnight off-work relaxation and the conditions that promote ERSBs.
Causal inference in the age of big data: blind faith in data and technology
Authors: Chao Fan , Wang Weibin , Yu Guang 
Published: September 2023

PurposeIn the era of big data, there is doubt about the significance of causal inference as a paramount scientific task in the social sciences. Meanwhile, data-mining techniques rooted in big data and artificial intelligence (AI) have infiltrated numerous aspects of social science research. This study aims to expound the criticality of discerning causal relationships – beyond mere correlations – and scrutinizes the ramifications of big data and AI in the identification of causality.Design/methodology/approachThis study discusses the challenges and opportunities for causality identification in the era of big data under the framework of potential outcomes model and structural causal model.FindingsFirst, even in the age of big data, correlations that lack interpretability, robustness and feasibility cannot substitute causality. Second, the richness of the sample size does not help solve the problem of systematic bias in the process of causal inference. Furthermore, current AI research targets correlations rather than causality, thus creating difficulties in advancing from observations to counterfactuals.Originality/valueThis study provides insights into the impact of big data era on causal inference in the social sciences, with a view toward enhancing the pool of theoretical concepts available to researchers in relevant fields and accurately guiding the direction of scientific research in these fields.
Study on creep behaviors of nickel-based single-crystal alloys considering microstructure evolution
Authors: Ai Xing , Wang Shuaishuai , Luo Fenghua , Pei Haiqing , Li Zhenwei 
Published: September 2023

Purpose The purpose of this study is to describe the mechanism of single-crystal high-temperature creep deformation, predict the creep life more accurately and study the creep constitutive and lifetime models with microstructure evolution.Design/methodology/approachThe mechanical properties of nickel-based single-crystal superalloy are closely related to the γ' phase. Creep tests under four different temperature and stress conditions were carried out. The relationship between creep temperature, stress and life is fitted by numerical method, and the creep activation energy is obtained. The creep fracture surface, morphology and evolution of strengthening phase (γ') and matrix phase (γ) during different creep periods were observed by scanning electron microscope. With the increase of creep temperature, the rafting time is advanced. The detailed morphology and evolution of dislocations were observed by transmission electron microscope (TEM).FindingsWith the increase of creep temperature, the rafting time is advanced. The detailed morphology and evolution of dislocations were observed by TEM. Dislocations are mainly concentrated in the γ channel phase, especially at high temperature and low stress.Originality/valueA creep constitutive model based on the evolution of γ' phase size and γ channel width was proposed. Compared with the experimental results, the predicted creep life is within 1.4 times error dispersion band.
A serial mediation model of the linkage between entrepreneurial education, self-efficacy, attitudes and intentions: does gender matter? A multi-group analysis
Authors: Duong Cong Doanh 
Published: September 2023

Purpose
This paper aims to use the Social Cognitive Career Theory and a serial mediation model to explore how entrepreneurial self-confidence and attitudes mediate the connection between entrepreneurial education and entrepreneurial intention. Additionally, the study seeks to examine how gender impacts these relationships.

Design/methodology/approach
To test the formulated hypothesis and the serial mediation effect, a sample of 1,266 master’s students from nine universities/institutions across three primary regions of Vietnam was used. The structural equation modeling technique, with Gaskin (2019)'s plugin and a 5,000-bootstrapping sample, was applied. Also, a multi-group analysis was used to illustrate the differences between male and female students in the relationships between variables.

Findings
The research reveals that entrepreneurial education plays a contributive role in increasing entrepreneurial self-efficacy, entrepreneurial attitudes and startup intentions. Entrepreneurial self-efficacy and entrepreneurial attitudes also serve as serial mediators in the entrepreneurial education-intention relation. Moreover, this study demonstrates the significant moderation role of gender in these links.

Practical implications
The outcomes of the current research hold significance for educators, policymakers and practitioners, as they can use these findings to encourage individuals to engage in entrepreneurial activities and to improve the overall entrepreneurial ecosystems.

Originality/value
The current research sheds new light on the entrepreneurship and gender literature by using the Social Cognitive Career Theory to elucidate the serial mediating role of entrepreneurial self-efficacy and entrepreneurial attitudes in the relation between entrepreneurial education and entrepreneurial intentions.
Adiponectin‐expressing Treg‐containing T cell fraction inhibits tumor growth in orthotopically implanted triple‐negative breast cancer
Authors: Chikaishi Wakana , Higashi Toshiya , Hayashi Hirokatsu , Hanamatsu Yuki , Futamura Manabu , Matsuhashi Nobuhisa , Saigo Chiemi , Takeuchi Tamotsu 
Published: September 2023

AbstractBackgroundIn our previous study, we identified a population of adiponectin expressing regulatory T cells (Tregs) residing within thymic nurse cell complexes, which were capable of inhibiting the development of breast cancer in vitro. Triple‐negative breast cancer (TNBC) with no proper treatment at present is characterized by the absence of estrogen receptor, progesterone receptor, and human epidermal growth factor receptor‐2. In this study, we aimed to investigate the potential of a cultured T cell fraction comprising adiponectin‐expressing Tregs, referred to as A‐TregTF (adiponectin‐expressing Treg‐containing T cell fraction), in inhibiting the progression of TNBC in vivo.MethodsThe efficacy of a spontaneously expanding T cell fraction comprising adiponectin‐expressing Treg in inhibiting tumor growth was analyzed in a murine orthotopic 4 T1‐Luc TNBC model.ResultsThe treatment with T cell fraction containing adiponectin‐expressing Tregs significantly inhibited the growth and metastasis of orthotopically transplanted 4 T1‐Luc tumor cells. Histopathological examination further revealed that the adiponectin‐expressing Tregs infiltrated the tumor tissue via a cell‐in‐cell mechanism and were found to be specifically localized around the necrotic areas.ConclusionsBased on our findings, the T cell fraction comprising adiponectin‐expressing Tregs, represents a potential candidate for adoptive cell therapy against TNBC.
Bootstrapping outperforms community‐weighted approaches for estimating the shapes of phenotypic distributions
Authors: Maitner Brian S. , Halbritter Aud H. , Telford Richard J. , Strydom Tanya , Chacon Julia , Lamanna Christine , Sloat Lindsey L. , Kerkhoff Andrew J. , Messier Julie , Rasmussen Nick , Pomati Francesco , Merz Ewa , Vandvik Vigdis , Enquist Brian J. 
Published: September 2023

AbstractEstimating phenotypic distributions of populations and communities is central to many questions in ecology and evolution. These distributions can be characterized by their moments (mean, variance, skewness and kurtosis) or diversity metrics (e.g. functional richness). Typically, such moments and metrics are calculated using community‐weighted approaches (e.g. abundance‐weighted mean). We propose an alternative bootstrapping approach that allows flexibility in trait sampling and explicit incorporation of intraspecific variation, and show that this approach significantly improves estimation while allowing us to quantify uncertainty.We assess the performance of different approaches for estimating the moments of trait distributions across various sampling scenarios, taxa and datasets by comparing estimates derived from simulated samples with the true values calculated from full datasets. Simulations differ in sampling intensity (individuals per species), sampling biases (abundance, size), trait data source (local vs. global) and estimation method (two types of community‐weighting, two types of bootstrapping).We introduce thetraitstrapR package, which contains a modular and extensible set of bootstrapping and weighted‐averaging functions that use community composition and trait data to estimate the moments of community trait distributions with their uncertainty. Importantly, the first function in the workflow,trait_fill, allows the user to specify hierarchical structures (e.g. plot within site, experiment vs. control, species within genus) to assign trait values to each taxon in each community sample.Across all taxa, simulations and metrics, bootstrapping approaches were more accurate and less biased than community‐weighted approaches. With bootstrapping, a sample size of 9 or more measurements per species per trait generally included the true mean within the 95% CI. It reduced average percent errors by 26%–74% relative to community‐weighting. Random sampling across all species outperformed both size‐ and abundance‐biased sampling.Our results suggest randomly sampling ~9 individuals per sampling unit and species, covering all species in the community and analysing the data using nonparametric bootstrapping generally enable reliable inference on trait distributions, including the central moments, of communities. By providing better estimates of community trait distributions, bootstrapping approaches can improve our ability to link traits to both the processes that generate them and their effects on ecosystems.
Dental referrals for patients with diabetes: survey of barriers and enablers for medical and health professionals
Authors: Davies K , McGowan K , Dover T , McGowan T , Tadakamadla SK 
Published: September 2023

AbstractBackgroundOral health care improves diabetes management; however, medical and other health practitioners do not commonly refer their patients with diabetes for oral health care. This study aimed to understand barriers to and enablers of dental referrals for patients with diabetes.MethodsQuantitative data were collected from a cross‐sectional survey of health care providers attending a virtual Grand Rounds on the relationship between oral health and diabetes. Attendees were invited to complete and share a Forms survey. Barriers to and enablers of dental referrals were compared for 18 health professionals working in inpatient/ward settings to 23 working in community/primary care settings using the chi‐square test.ResultsAcross both work settings, only 12% of respondents often or always discussed the importance of oral health and only 8% often or always referred their patients with diabetes for dental care. Time barriers, awareness and knowledge of how/where to send dental referrals were significant barriers, while online referral pathways, more education and availability of brochures for the patient to take home were identified as key enablers for dental referrals.ConclusionsOnline referral pathways, targeted oral health education and resources for medical and health professionals caring for patients with diabetes may increase the number of patients being referred for dental care as part of their diabetes managements. © 2023 Australian Dental Association.
Mopane (Colophospermum mopane): A potential winner under climate change in southern Africa
Authors: Jinga Percy , Mureva Admore , Manyangadze Tawanda 
Published: September 2023

AbstractDistribution and abundance under climate change of particularly non‐timber forest product tree species is vital since they sustain many livelihoods, especially in rural sub‐Saharan Africa. The aim of the study was to determine the current and future natural range of mopane (Colophospermum mopane (J. Kirk ex Benth.) J. Léonard, Fabaceae), a dominant tree species in mopane woodlands of southern Africa. An ensemble model was built in ‘biomod2’ from eight algorithms and used to estimate the current and future distribution. Seven bioclimatic variables and 269 occurrence records were used to calibrate individual models that were later combined into an ensemble model. The ensemble model was projected to two time periods, 2041–2060 and 2081–2100, under two shared socio‐economic pathways (SSPs), SSP2‐4.5 and SSP5‐8.5, and three general circulation models (GCMs). The ensemble model showed high performance (KAPPA = 0.770, ROC = 0.961, TSS = 0.792, ACCURACY = 0.900). A map of the current distribution shows occurrence predominantly in low‐lying areas, including the Zambezi, Save and Limpopo valleys, Okavango and Cuvelai basins, and in southern and central Mozambique. Projection maps show expansion under all SSPs, GCMs and time periods. Averaged across GCMs in 2041–2060, the range expanded by 22.37% under SSP2‐4.5, and by 19.94% under SSP5‐8.5. In 2081–2100, the range expanded by 20.43% under SSP2‐4.5, and by 27.62% under SSP5‐8.5. Notably, the range expansion was highest under SSP5‐8.5, an SSP that envisages unmitigated greenhouse gas release and the largest mean global temperature increase. It is highly likely that mopane is not directly threatened by climate change. Indirect climate change threats, however, remain uncertain.
Getting back ‘home’ after emergency laparotomy: how many never make it?
Authors: Holmes Merran , Rugendyke Anya , Ming Yan Joyce , Howley Peter , Gani Jon , Pockney Peter ,   the Hunter Emergency Laparotomy Audit Collaborator Group
Published: September 2023

AbstractBackgroundEmergency laparotomy (EL) is performed on about 15 500 patients in Australia each year. Aside from mortality there is significant concern about the possibility that previously independent patients discharged after EL will become reliant on long‐term dependent care. This study aimed to establish the proportion of patients not returning to their pre‐admission residence, a proxy for dependent care, following EL.MethodsData were collected on all adult patients who underwent EL across four Australian hospitals over 2 years. A total of 113 data points were collected including pre‐hospital residence, discharge destination, mortality and place of residence at 90 and 365 days.ResultsA total of 782 patients underwent EL, the mean age was 64 years. Pre‐admission, 95.5% of patients were living in their own home. Inpatient mortality was 7.0% and at discharge 72.4% of patients returned directly back to their pre‐hospital residence. At 90 days, mortality was 10.5%, and 87% of patients had returned to their pre‐hospital residence, including all patients under 70 years of age. By 365 days, overall mortality was 16.8%, and only 1.5% of patients (all aged >70 years) had not returned to their pre‐hospital residence.ConclusionPatients who survive 90 and 365 days following EL nearly all return to their pre‐hospital residence, with only a very small proportion of previously independent patients entering dependent care. This should help inform shared decision‐making regarding emergency laparotomy in the acute setting.