bluuebunny/crossref_metadata_2025_split huggingface dataset:
Comparing advanced-era interferometric gravitational-wave detector network configurations: Sky localization and source properties
Authors: Emma Mattia , de Nobrega Tiago Fernandes , Ashton Gregory 
Published: September 2024

The expansion and upgrade of the global network of ground-based gravitational-wave detectors promises to improve our capacity to infer the sky localization of transient sources, enabling more effective multimessenger follow-ups. At the same time, the increase in the signal-to-noise ratio of detected events allows for more precise estimates of the source parameters. This study aims to assess the performance of advanced-era networks of ground-based detectors, focusing on the Hanford, Livingston, Virgo, and KAGRA instruments. We use full Bayesian parameter estimation procedures to predict the scientific potential of a network. Assuming a fixed configuration of the LIGO Hanford and Livingston detectors, we find that the addition of the Virgo detector is beneficial to the sky localization starting from a binary neutron star range of 20 Mpc and improves significantly from 40 Mpc onward for both a single and double LIGO detector network, reducing the inferred mean sky area by up to 95%. Similarly, the KAGRA detector tightens the constraints, starting from a binary neutron star range of 10 Mpc. Looking at highly spinning binary black holes, we find significant improvements with increasing sensitivity in constraining the intrinsic source parameters when adding Virgo to the two LIGO detectors. Finally, we also examine the impact of the low-frequency cutoff data on the signal-to-noise ratio. We find that existing 20 Hz thresholds are sufficient and propose a metric to monitor this to study detector performance. Our findings quantify how future enhancements in detector sensitivity and network configurations will improve the localization of gravitational-wave sources and allow for more precise identification of their intrinsic properties.

Published by the American Physical Society
2024
High-speed reconstruction of long-duration gravitational waves from extreme-mass-ratio inspirals using sparse dictionary learning
Authors: Badger Charles , Font José A. , Sakellariadou Mairi , Torres-Forné Alejandro 
Published: September 2024

Measuring accurate long-duration gravitational waves from extreme mass ratio inspirals (EMRIs) could provide scientifically fruitful knowledge of massive black hole populations and robust tests for general relatively during the LISA mission. However, the immense computational requirements surrounding EMRI data processing and analysis makes their detection and analysis challenging. We further develop and explore a sparse dictionary learning (SDL) algorithm to expeditiously reconstruct EMRI gravitational waveforms lasting as long as 1 year. A suite of year-long EMRI systems are studied to understand the detection and accurate waveform retrieval prospects of the method. We show that full-year EMRIs can be reconstructed within 2 minutes, some with a false alarm rate less than 0.001  yr−1 and with 1.16 day time windows with mismatch as low as 0.06. This provides an encouraging prospect to use the SDL method for long-duration gravitational wave searches like that for EMRIs in this study.

Published by the American Physical Society
2024
Examining the impact of green entrepreneurship drivers on sustainable development in the context of emerging country
Authors: Mondal Sourav , Singh Saumya , Gupta Himanshu 
Published: September 2024

PurposeGreen entrepreneurship (GE) is a novel concept in business and enhances environmentally friendly production and operation activities for “sustainable development” (SD). The aim of this study is to determine the drivers that contribute to the growth and success of “micro, small, and medium enterprises” (MSMEs) in the manufacturing sector in India. The study also examines the mutual and cause-and-effect relationships among these identified drivers.Design/methodology/approachThe study used integrated research methodology and identified nine key drivers of GE (GEDs) through extensive literature reviews, theoretical perspectives (i.e. “resource-based view” (RBV), “natural resource-based view” (NRBV) and “critical success factor theory” (CSFT)), and expert opinions. Further, “total interpretive structural modeling” (TISM) and “matrice d'impacts croisés multiplication appliquée á un classment” (MICMAC) analysis are used here to develop a hierarchical model and cluster the drivers, and fuzzy “decision-making trial and evaluation laboratory” (fuzzy-DEMATEL) is used to develop causal relationships among the drivers. Further, a sensitivity analysis is conducted to ensure the robustness of the results.FindingsResults indicated that green manufacturing and operation capability development, green business process management and attitudes toward developing sustainable business models significantly impacted GE and SD. The findings of this study help managers, policymakers, and practitioners gain an in-depth understanding of the drivers of GE.Research limitations/implicationsThe study considers a limited number of drivers and is specific to Indian manufacturing MSMEs only. Further, a limited number of experts from different enterprises are considered for data analysis. This study is also based on interrelationships and their relative importance based on multicriteria decision-making techniques. This study aids government decision-making, policy formulation and strategic decision-making for manufacturing businesses in achieving SD goals. In addition, this research also encourages green entrepreneurs to start eco-driven companies and facilitate the use of environmentally friendly goods to offset environmental challenges and accomplish sustainable development goals.Originality/valueThis study proposes an integrated methodology that will benefit managers, practitioners and others in developing strategies and innovations to improve and develop green practices. This study further helps with responsive, sustainable business development in various manufacturing MSMEs.
Fracture modeling in composite structures containing orthotropic materials by incorporating strain orthogonal decompositions into phase-field method of interfacial damage
Authors: Vu Ba-Thanh , Le-Quang Hung , He Qi-Chang 
Published: September 2024

PurposeThe phase-field method of interfacial damage is used to simulate the damage in composite structures containing the brittle orthotropic materials and their interface.Design/methodology/approachIn the brittle fracture modeling, the strain tensor is decomposed into positive and negative parts characterizing tension and compression behaviors. By requiring an elastic energy preserving transformation involving the elastic stiffness tensor, these two strain parts must satisfy the orthogonality condition in the sense that the elastic stiffness tensor responds as a metric. However, most of the recent phase-field methods for brittle fracture do not verify this orthogonality condition. Additionally, to describe the damage in structures with anisotropic phases, recent studies have used multiple phase-field variables, with each preferential orientation represented by a phase-field variable to describe the bulk damage of component materials. This approach increases the complexity of simulation procedure. These disadvantages motivate the present study aimed at enhancing the simulation method.FindingsThe present study improves the phase-field method of interfacial damage by (1) incorporating the strain orthogonality condition into the phase-field method; (2) using only one phase-field variable instead of multiple phase-field variables to simulate damage in component orthotropic phases; and (3) investigating the interaction between interfacial damage and bulk damage as well as the effect of orientation tensor of preferential orientation in each orthotropic phase and the interfacial parameters on crack branching in composite structures.Originality/valueThrough several simulation examples, the present simulation method is proven to be accurate, effective, and helps the simulation process simpler than previous relevant methods.
Investment in tax haven jurisdiction by Indian MNCs: a conceptual study
Authors: Shanmugam Velmurugan Palaniappan , Arunima P. 
Published: September 2024

PurposeThis study aims to understand the investments made by Indian MNCs in different tax havens to optimize their tax liabilities. The study also aims to provide insights into the conceptual framework of such practices, highlighting potential benefits and risks and providing policy recommendations that promote transparency, fairness and sustainable economic practices.Design/methodology/approachThe study involves a combination of quantitative and qualitative approaches. The quantitative aspect analyzes investments made by Nifty 50 companies in tax haven jurisdictions from the financial data of the parent company from 2019 to 2023. The qualitative aspect involves a conceptual framework developed from previous studies and examining the role of various organizations in combating tax avoidance. This mixed-method approach enables a comprehensive understanding of the motivations, impacts and regulatory responses related to the use of tax havens.FindingsThe paper provides conceptual and descriptive insights on investments made by Indian MNCs in tax havens during 2019–21 to save tax. The study suggests that while investing in tax havens, businesses give more priority to ease of doing business and other considerations such as a lower tax rate.Research limitations/implicationsThe present study suggests policymakers about the effectiveness of current tax laws and their enforcement, highlighting loopholes and potential avenues for modification.Originality/valueThis paper assesses the reasons for Indian MNCs starting subsidiaries and making investments in different tax haven jurisdictions and suggests appropriate measures to avoid the menace of tax havens.
Holacracy: redefining organizational ontology and epistemology
Authors: Robledo Marco Antonio A. 
Published: September 2024

Purpose
This paper aims to examine Holacracy as a self-management system and its implications for organizational theory. By exploring its distinctive ontology and epistemology, the paper explains how Holacracy redefines organizational structures and contributes to organizational change.

Design/methodology/approach
Adopting a conceptual approach, this essay draws upon existing literature to explore Holacracy’s departure from conventional organizational theories.

Findings
The paper discusses how Holacracy challenges traditional organizational concepts, defining its holarchical approach, and emphasizing dynamic hierarchies and role-based organization. It also highlights Holacracy’s focus on emergent intelligence, continuous feedback loops and structured knowledge acquisition through roles and organization spaces. By examining its unique ontology and epistemology, the paper offers insights into how Holacracy aligns with an emergent paradigm known as integral, metamodern or teal.

Research limitations/implications
Further empirical research is needed to assess its practical implementation and long-term effects on organizational performance and employee well-being. Future studies could also explore challenges and limitations associated with adopting Holacracy in different organizational contexts.

Practical implications
Organizations considering alternative ways of working should examine Holacracy. Implementing Holacracy requires understanding its principles and may involve significant changes, with potential benefits such as increased agility and employee engagement.

Social implications
Holacracy’s departure from traditional structures and approach to power can have broader social implications and contribute to more democratic and participatory cultures.

Originality/value
This paper is a pioneering contribution to the under-researched domain of alternative organizational models. It sheds light on the originality and distinctiveness of Holacracy, highlighting its unique approach to hierarchy, role-based organization and consciousness within organizations.
Street food in the digital era: unraveling the influence of food vloggers credibility and information quality on consumer intentions
Authors: Bhagat Sheetal , Khanna Suvidha , Sharma Priyanka , Bhat Dada Ab Rouf 
Published: September 2024

PurposeThe purpose of this study is to investigate the influence of credibility and information quality (IQ) of online food vloggers on consumer attitude and purchase intention towards street food consumption. It also examines the relationship between consumer attitude and purchase intention influenced by online food vlogger reviews in North India.Design/methodology/approachIn order to evaluate the framework, primary data were gathered from 389 street food consumers located in Jammu, Chandigarh and Delhi – cities situated in northern India. The collected data were then subjected to analysis using the partial least squares-structural equation modeling (PLS-SEM) techniques.FindingsThe results indicate that the perceived value of street food, influenced by the credibility of food vloggers and the quality of information provided, has a positive impact on consumer attitude and purchase intention towards street food consumption. A positive impact of consumer attitude on the purchase and consumption of street food was also observed.Originality/valueThis research offers a thorough investigation into the elements that influence consumers' opinions regarding vloggers endorsements. The findings reveal that consumer's attitudes towards vloggers recommendations are mainly influenced by the quality of information provided, followed by credibility and the intention to make a purchase. Furthermore, this research is of significance to practitioners and academics interested in comprehending consumer behavior in the realms of tourism and food-related endeavors.Peer reviewThe peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-02-2024-0158
Redefining academic trajectories: A comprehensive analysis of the factors and impacts of the gender gap in STEM higher education
Authors: Beroíza-Valenzuela Francisca , Salas-Guzmán Natalia 
Published: September 2024

Purpose
The purpose of this study is to critically analyze the key factors contributing to gender disparities in the science, technology, engineering and mathematics (STEM) fields and propose creative solutions to mitigate these differences. Despite the significance of this issue, it has not received sufficient attention owing to the absence of clarity regarding the factors that exacerbate the gender gap.

Design/methodology/approach
This study used a qualitative methodology that combined the viewpoints of social psychology and educational research to pinpoint and evaluate essential elements. Using a grounded theory approach, semistructured interviews were analyzed, and the obtained data were coded and categorized using ATLAS.ti software.

Findings
This qualitative research identified three key areas: internal and external factors influencing the gender gap, as well as strategic actions within higher education to address these disparities. The innovative contribution of this study lies in its development of a comprehensive theoretical framework that enables the diagnosis, quantification and understanding of these factors and proposes practical measures to mitigate these gender disparities. By promoting greater gender diversity, the proposed model can contribute to more inclusive and sustainable development, which is consistent with the 2030 agenda.

Originality/value
This study highlights the need for a multidimensional approach to address the gender gap in higher education, fills a crucial knowledge gap and provides a theoretical model to guide effective university policies.
Strategic insights: mapping the terrain of artificial intelligence (AI) in banking through mixed method approach
Authors: Meena Rahul , Mishra Akshay Kumar , Raut Rajdeep Kumar 
Published: September 2024

Purpose
The purpose of this paper is to supplement and update previously published articles about artificial intelligence (AI) instruments and operations in banking sectors with the following objectives in mind: to understand the role of AI in banking sectors; to explore the themes and context in this area based on keywords, co-citations and co-words; and to identify future research direction by evaluating the trend and direction of previous research.

Design/methodology/approach
This study adopts a semi-inductive approach with the convolution of bibliometrics and literature review. This study used bibliometrics for the identification of literature across multiple databases and systematic literature review on identified articles to explore heterogeneous sectors within AI in banking and finance.

Findings
This study contributes a literature-based model that accounts for both the broadly in AI application in banking and finance: predictive modeling in risk assessment and detection; financial decision-making; client service delivery; and emerging FinTech applications of AI and machine learning.

Originality/value
This study is among the few to address the literature of tools and application of AI in banking through mixed-methods approach and produce a synthesized model for the same.
The role of tourism entrepreneurial ecosystems to support sales growth of European countries
Authors: Abdelli Mohammed El Amine , Moussavou Jean , Perez-Encinas Adriana , Rodríguez-Crespo Ernesto , Pinto Borges Ana , Akbaba Atilla , Levy-Tadjine Thierry , Chabaud Didier 
Published: September 2024

PurposeOur comprehensive study, which is highly relevant to the current state of the tourism industry, investigated the extensive impact of tourism entrepreneurial ecosystems (TEE) on sales growth in European countries based on a sample of 109 entrepreneurs.Design/methodology/approachWe studied 109 entrepreneurs in the tourism sector in Germany and France and analyzed the data using quantitative methods.FindingsThe results showed that financing and funding, networks, technological and international trade affect the sales growth of the tourism entrepreneurs. In addition, the uneducated workforce, legal and political factors as well as TEE do not influence the sales growth.Originality/valueThese findings have significant and practical implications for entrepreneurs and policymakers in the tourism industry, providing them with valuable insights for decision-making.
A single amino acid substitution in the Borna disease virus glycoprotein enhances the infectivity titer of vesicular stomatitis virus pseudotyped virus by altering membrane fusion activity
Authors: Akiba Yusa , Matsugo Hiromichi , Kanda Takehiro , Sakai Modoka , Makino Akiko , Tomonaga Keizo 
Published: September 2024

AbstractBorna disease virus 1 (BoDV‐1) causes acute fatal encephalitis in mammals, including humans. Despite its importance, research on BoDV‐1 cell entry has been hindered by low infectious viral particle production in cells and the lack of cytopathic effects, which are typically useful for screening. To address these issues, we developed a method to efficiently produce vesicular stomatitis virus (VSV) pseudotyped with glycoprotein (G) of members of the genus Orthobornavirus, including BoDV‐1. We discovered that optimal G expression is required to obtain a high infectivity titer of the VSV pseudotyped virus. Remarkably, the infectivity of the VSV pseudotyped virus with G from the BoDV‐1 strain huP2br was significantly higher than that of the VSV pseudotyped virus with G from the He/80 strain. Mutational analysis demonstrated that the methionine at BoDV‐1–G residue 307 increases the infectivity titer of VSV pseudotyped with BoDV‐1–G (VSV–BoDV‐1–G). A cell‒cell fusion assay indicated that this residue plays a pivotal role in membrane fusion, thus suggesting that high membrane fusion activity and a broad pH range for membrane fusion are crucial for achieving a high infectivity titer of VSV–BoDV‐1–G. This finding may be extended to increase the infectivity titer of VSV pseudotyped virus with other orthobornavirus G. Our study also contributes to identifying functional domains of BoDV‐1–G and provides insight into G‐mediated cell entry.
Broker and institutional investor short selling
Authors: Marshall Ben R. , Nguyen Nhut H. , Visaltanachoti Nuttawat , Zhu Jennifer 
Published: September 2024

AbstractBrokers have access to order‐flow data, which they can use to enhance their short‐selling returns. However, New Zealand brokers also have a fiduciary duty to place their clients' interests before their own. We compare the short‐selling returns and trading behaviours of brokers and institutional investors who predominantly focus on profit‐making. Our results show no significant return difference between broker and institutional short sales and indicate that broker short sales are apparently to stabilise the market. Short selling is associated with improved market quality, and this improvement is more pronounced when brokers short sell more than institutional investors.
Cross‐protection of AIT‐induced antibodies to related allergens requires a high degree of structural identity
Authors: Demir Hilal , Radauer Christian , Strobl Maria R. , Scheurer Stephan , Kinaciyan Tamar , Bohle Barbara 
Published: September 2024

AbstractBackgroundIn contrast to sublingual immunotherapy (SLIT) with recombinant Mal d 1 (rMal d 1‐SLIT), SLIT with rBet v 1 (rBet v 1‐SLIT) induced Mal d 1‐cross‐reactive antibodies without IgE‐blocking activity. To elucidate whether the development of cross‐protective IgG responses depends on the degree of molecular identity of allergens we compared the cross‐reactivity, cross‐blocking activity, and affinity of SLIT‐induced antibodies with allergens of varying amino acid sequence identities to Bet v 1 and Mal d 1, namely Cor a 1.04 (hazelnut), Pru av 1 (cherry), and Dau c 1 (carrot).MethodsAllergen‐specific antibodies were quantified by ELISA. IgE blocking was analyzed by inhibition of allergen‐induced basophil activation and IgE‐facilitated allergen‐presentation to T cells. The affinity of SLIT‐induced antibodies was studied by acidic dissociation ELISA and competition ELISA. Identical surface areas on allergens were predicted using an in‐house designed script based on structural alignments.ResultsrBet v 1‐SLIT‐induced IgG antibodies cross‐reacted with all allergens except Dau c 1. rMal d 1‐SLIT‐induced antibodies predominantly cross‐reacted with Pru av 1 and displayed significantly higher IgE blocking to Pru av 1 than rBet v 1‐SLIT‐induced antibodies. rMal d 1‐SLIT‐induced IgG1 showed higher affinity to Mal d 1 and Pru av 1. Surface analysis revealed 84% identical area on Mal d 1 and Pru av 1. Furthermore, we identified two surface areas potentially containing epitopes present on these allergens and absent on Bet v 1.ConclusionIn summary, our findings suggest that a relatively high threshold of similarity is required to establish effective cross‐blocking antibodies to related allergens. Apparently, the structural identity between Bet v 1 and Mal d 1 is below this threshold. Therefore, this study may explain why immunotherapy with birch pollen allergen often fails to reduce birch pollen‐related apple allergy.