bluuebunny/crossref_metadata_2025_split huggingface dataset:
Braf-mutant Schwann cells divert to a repair phenotype to induce congenital demyelinating neuropathy
Authors: Marechal Elise , Quintana Patrice , Aldea Daniel , Mondielli Grégoire , Bernard-Marissal Nathalie , Moreno Mathias , Delague Valérie , Weiss Lauren A. , Barlier Anne , Etchevers Heather C. 
Published: April 2024

AbstractRASopathies are developmental disorders associated with mutations leading to constitutive activation of the Mitogen Activated Protein Kinase (MAPK) signaling pathway. Peripheral nerve enlargement and damage are recently reported symptoms in germline RASopathy patients. We characterized mouse models in which a frequent mutation of the MAPK effector Braf (V600E) in mosaic RASopathies is expressed in embryonic progenitors of Schwann cells. Postnatal mice develop an early, fully penetrant degenerative peripheral neuropathy. Symptoms appear before weaning, with sciatic nerve enlargement, loss of hindlimb muscle strength, and failure to thrive relative to littermates. The V600E catalytic domain mutation promotes expansion of a Jun+ Schwann cell repair state at the expense of mature, myelinating Schwann cells, preventing full peripheral myelination. Associated with the germline RASopathy cardio-facio-cutaneous syndrome, theBRAF(Q257R) mutation also prevents terminal differentiation of Schwann cells from patient-derived induced pluripotent stem cells. This study supports the likelihood that some of the genetic heterogeneity in human peripheral neuropathies may be imputed to somatic mosaicism in a contextually underexplored pathway. It also provides a mechanistic explanation for RASopathy-associated neuropathies.
Uncovering Effects of Schizophrenia upon a Maximally Significant, Minimally Complex Subset of Default Mode Network Connectivity Features
Authors: Seraji Masoud , Ellis Charles A. , Sendi Mohammad S.E. , Miller Robyn L. , Calhoun Vince D. 
Published: April 2024

AbstractA common analysis approach for resting state functional magnetic resonance imaging (rs-fMRI) dynamic functional network connectivity (dFNC) data involves clustering windowed correlation time-series and assigning time windows to clusters (i.e., states) that can be quantified to summarize aspects of the dFNC dynamics. However, those methods can be dominated by a select few features and obscure key dynamics related to less dominant features. This study presents an iterative feature learning approach to identify a maximally significant and minimally complex subset of dFNC features within the default mode network (DMN) in schizophrenia (SZ). Utilizing dFNC data from individuals with SZ and healthy controls (HC), our approach uncovers a subset of features that has a greater number of dFNC states with disorder-related dynamics than is found when all features are present in the clustering. We find that anterior cingulate cortex/posterior cingulate cortex (ACC/PCC) interactions are consistently related to SZ across the most significant iterations of the feature learning analysis and that individuals with SZ tend to spend more time in states with greater intra-ACC anticorrelation and almost no time in a state of high intra-ACC correlation that HCs periodically enter. Our findings highlight the need for nuanced analyses to reveal disorder-related dynamics and advance our understanding of neuropsychiatric disorders.
Investigations of
Λ
states with spin-parity
32±
Authors: Azizi K. , Sarac Y. , Sundu H. 
Published: April 2024

The present study provides spectroscopic investigations of spin-32 Λ baryons with both positive and negative parities. The analysis mainly focuses on three states, namely 1P, 2P, and 2S, and corresponding masses are calculated using the QCD sum rule method. To implement the method, we apply two types of interpolating currents with octet and singlet quantum numbers and compare the corresponding results with the reported masses of experimentally observed states. From the comparisons, it is extracted that the results of interpolating current with octet quantum numbers are in good agreement with the experimentally measured masses. The masses obtained with this interpolating current are m=1513.64±8.76  MeV for 1P state with JP=32−, m′=1687.91±0.31  MeV for 2P state with JP=32− and m˜=1882.37±11.95  MeV for 2S state with JP=32+ and they are consistent with the experimental masses of Λ(1520), Λ(1690), and Λ(1890), respectively, which confirm their spin-parity quantum numbers. Besides, we calculate the corresponding current coupling constants, which are utilized as inputs in the calculations of different form factors defining the widths of the states under study.

Published by the American Physical Society
2024
Morphology of nanoporous glass: Stochastic 3D modeling, stereology and the influence of pore width
Authors: Neumann Matthias , Gräfensteiner Phillip , Santos de Oliveira Cristine , Martins de Souza e Silva Juliana , Koppka Sharon , Enke Dirk , Huber Patrick , Schmidt Volker 
Published: April 2024

Excursion sets of Gaussian random fields are used to model the three-dimensional (3D) morphology of differently manufactured porous glasses (PGs), which vary with respect to their mean pore widths measured by mercury intrusion porosimetry. The stochastic 3D model is calibrated by means of volume fractions and two-point coverage probability functions estimated from tomographic image data. Model validation is performed by comparing model realizations and image data in terms of morphological descriptors which are not used for model fitting. For this purpose, we consider mean geodesic tortuosity and constrictivity of the pore space, quantifying the length of the shortest transportation paths and the strength of bottleneck effects, respectively. Additionally, a stereological approach for parameter estimation is presented, i.e., the 3D model is calibrated using merely two-dimensional (2D) cross-sections of the 3D image data. Doing so, on average, a comparable goodness of fit is achieved as well. The variance of the calibrated model parameters is discussed, which is estimated on the basis of randomly chosen, individual 2D cross-sections. Moreover, interpolating between the model parameters calibrated to differently manufactured glasses enables the predictive simulation of virtual but realistic PGs with mean pore widths that have not yet been manufactured. The predictive power is demonstrated by means of cross-validation. Using the presented approach, relationships between parameters of the manufacturing process and descriptors of the resulting morphology of PGs are quantified, which opens possibilities for an efficient optimization of the underlying manufacturing process.

Published by the American Physical Society
2024
The influence of rolling on the corrosion and wear resistance of the MAO coating on ZM5 alloy
Authors: Zhang Bo , Zheng Yuqian , Cui Zhiyuan , Song Dongdong , Liu Faqian , Li Weihua 
Published: April 2024

Purpose
The impact of rolling on the performance of micro arc oxidation (MAO) coatings on ZM5 alloy has been underreported. The purpose of this study is to explore the correlation between rolling and the failure mechanism of MAO coatings in greater depth.

Design/methodology/approach
The influence of rolling on the corrosion and wear properties of MAO coating was investigated by phase structure, bond strength test (initial bond strength and wet adhesion), electrochemical impedance spectroscopy and wear test. The change of the surface electrochemical properties was studied by first principles analysis.

Findings
The results showed that the MAO coating on rolled alloy had better corrosion and wear resistance compared to cast alloy, although the structure and component content of two kinds of MAO coating are nearly identical. The difference in interface bonding between MAO coating and Mg substrate is the primary factor contributing to the disparity in performance between the two types of samples. Finally, the impact of the rolling process on MAO coating properties is explained through first-principle calculation.

Originality/value
A comprehensive explanation of the impact of the rolling process on MAO coating properties will provide substantial support for enhancing the application of Mg alloy anticorrosion.

Graphical abstract
Distribution fitting and ANOVA test to analyze pavement sensing patterns for condition assessments
Authors: Zhang Dada , Ho Chun-Hsing 
Published: April 2024

Purpose The purpose of this paper is to investigate the vehicle-based sensor effect and pavement temperature on road condition assessment, as well as to compute a threshold value for the classification of pavement conditions.Design/methodology/approach Four sensors were placed on the vehicle’s control arms and one inside the vehicle to collect vibration acceleration data for analysis. The Analysis of Variance (ANOVA) tests were performed to diagnose the effect of the vehicle-based sensors’ placement in the field. To classify road conditions and identify pavement distress (point of interest), the probability distribution was applied based on the magnitude values of vibration data.Findings Results from ANOVA indicate that pavement sensing patterns from the sensors placed on the front control arms were statistically significant, and there is no difference between the sensors placed on the same side of the vehicle (e.g., left or right side). A reference threshold (i.e., 1.7 g) was computed from the distribution fitting method to classify road conditions and identify the road distress based on the magnitude values that combine all acceleration along three axes. In addition, the pavement temperature was found to be highly correlated with the sensing patterns, which is noteworthy for future projects.Originality/value The paper investigates the effect of pavement sensors’ placement in assessing road conditions, emphasizing the implications for future road condition assessment projects. A threshold value for classifying road conditions was proposed and applied in class assignments (I-17 highway projects).
Tourist confidence: a scale development, testing and application
Authors: Liu-Lastres Bingjie , Cahyanto Ignatius , Edwards Chase 
Published: April 2024

Purpose
Tourist confidence plays an important role in people’s decision-making, including decisions related to consuming tourism products. However, little research has explored this concept in depth to provide proper guidance on its operation and measurement. This paper aims to explore the concept of tourist confidence, develop and test a measurement and test the effects of tourist confidence on people’s travel intentions at different periods of time.

Design/methodology/approach
This study used repeated cross-sectional data and collected responses from three waves of national surveys of U.S. residents in 2021.

Findings
The results revealed three underlying dimensions of tourist confidence: (1) confidence in tourism/hospitality service providers, (2) self-confidence in tourist competency and (3) confidence in travel safety. The validity and reliability of the instrument were deemed satisfactory. The results also indicate the positive associations between tourist confidence and people’s travel decisions.

Originality/value
This study developed a measurement that is specific to the domain of tourist confidence. The findings of this paper reveal the multidimensional nature of tourist confidence. When translated into practice, the findings of this study can help practitioners understand how to effectively enhance tourist confidence in challenging, difficult and uncertain times.
Accelerate or delay? Big step internationalization and the speed of subsequent foreign expansion—evidence from Chinese MNEs
Authors: Zhao Shifang , Yu Shu 
Published: April 2024

Purpose
In recent decades, emerging market multinational enterprises (EMNEs) have predominantly adopted a big step internationalization strategy to expand their business overseas. This study aims to examine the effect of big step internationalization on the speed of subsequent foreign direct investment (FDI) expansion for EMNEs. The authors also investigate the potential boundary conditions.

Design/methodology/approach
The authors use the random effects generalized least squares (GLS) regression following a hierarchical approach to analyze the panel data set conducted by a sample of publicly listed Chinese firms from 2001 to 2012.

Findings
The findings indicate that implementing big step internationalization in the initial stages accelerates the speed of subsequent FDI expansion. Notably, the authors find that this effect is more pronounced for firms that opt for acquisitions as the entry mode in their first big step internationalization and possess a board of directors with strong political connections to their home country’s government. In contrast, the board of director’s international experience negatively moderates this effect.

Practical implications
This study provides insights into our scholarly and practical understanding of EMNEs’ big step internationalization and subsequent FDI expansion speed, which offers important implications for firms’ decision-makers and policymakers.

Originality/value
This study extends the internationalization theory, broadens the international business literature on the consequences of big step internationalization and deepens the theoretical and practical understanding of foreign expansion strategies in EMNEs.
What is the link between entrepreneurial knowledge, business planning and entrepreneurial intentions? An empirical study on Indian Higher Education Institutions
Authors: Kaur Manpreet , Chawla Sonia 
Published: April 2024

PurposeThe study seeks to conduct an empirical investigation on the impact of entrepreneurship education (EE) through its components, i.e. entrepreneurial knowledge (EK) and business planning (BP) on entrepreneurial intentions (EI) in India.Design/methodology/approachAn electronic questionnaire was used to collect data from 340 engineering students and partial least square-structural equation modeling (PLS-SEM) was used to analyze the collected data.FindingsThe findings revealed that EK and BP have no direct impact on EI, however, they have an indirect influence through attitude towards entrepreneurship (ATE) and perceived behavioral control (PBC), whereas subjective norms (SN) have no mediation impact on the relationships.Research limitations/implicationsThis research has been conducted on students of engineering background only, future studies can be carried out by incorporating more attitudinal and environmental determinants with larger data sizes from diverse educational streams.Practical implicationsThis study is of immense significance to policymakers and educational establishments in designing the purposefully designed EE courses that can drive the entrepreneurial intentionality of students.Originality/valueThe study adds to the paucity of research on the systematic elaboration of EE construct underlining the specific impact of EK and BP as EE dimensions on students' EI. To the best of authors' awareness, this kind of investigation has not been conducted in indian higher educational institution (HEI) context.
Designing an algorithm for predicting plane ticket prices using feedforward neural network modeling
Authors: Mojoodi Amin , Jalalian Saeed , Kumail Tafazal 
Published: April 2024

PurposeThis research aims to determine the ideal fare for various aircraft itineraries by modeling prices using a neural network method. Dynamic pricing has been studied from the airline’s point of view, with a focus on demand forecasting and price differentiation. Early demand forecasting on a specific route can assist an airline in strategically planning flights and determining optimal pricing strategies.Design/methodology/approachA feedforward neural network was employed in the current study. Two hidden layers, consisting of 18 and 12 neurons, were incorporated to enhance the network’s capabilities. The activation function employed for these layers was tanh. Additionally, it was considered that the output layer’s functions were linear. The neural network inputs considered in this study were flight path, month of flight, flight date (week/day), flight time, aircraft type (Boeing, Airbus, other), and flight class (economy, business). The neural network output, on the other hand, was the ticket price. The dataset comprises 16,585 records, specifically flight data for Iranian airlines for 2022.FindingsThe findings indicate that the model achieved a high level of accuracy in approximating the actual data. Additionally, it demonstrated the ability to predict the optimal ticket price for various flight routes with minimal error.Practical implicationsBased on the significant alignment observed between the actual data and the tested data utilizing the algorithmic model, airlines can proactively anticipate ticket prices across all routes, optimizing the revenue generated by each flight. The neural network algorithm utilized in this study offers a valuable opportunity for companies to enhance their decision-making processes. By leveraging the algorithm’s features, companies can analyze past data effectively and predict future prices. This enables them to make informed and timely decisions based on reliable information.Originality/valueThe present study represents a pioneering research endeavor that investigates using a neural network algorithm to predict the most suitable pricing for various flight routes. This study aims to provide valuable insights into dynamic pricing for marketing researchers and practitioners.
Too tired to not reconsider the way we work: mothers’ lessons learned teleworking during COVID-19
Authors: Rosen Lisa H. , Scott Shannon R. , Poe Darian , Shukla Roshni , Honargohar Michelle , Ahmed Shazia 
Published: April 2024

PurposeWorking mothers experienced dramatic changes to their daily routines during the COVID-19 pandemic. Many began to work from home as they simultaneously tried to balance work demands with tending to their children. The purpose of the current study was to examine working mothers’ experiences during the pandemic.Design/methodology/approachIn order to examine working mothers’ experiences of telework during the pandemic, we conducted a focus group study. 45 working mothers participated, and they answered questions about their experiences.FindingsThree themes emerged from the focus groups: (1) motivation shifts amongst working mothers; (2) difficulty balancing roles as mother and employee; and (3) workplace expectations and support. Many mothers reported that their overall motivation as employees had decreased and that they experienced difficulty in fully attending to their work and their child(ren)’s needs. As mothers navigated the stress of working during the pandemic, they reported varying levels of workplace support and many credited working with other parents as a primary contributor to feeling supported.Originality/valueThe findings from the current study add to the growing body of literature documenting the dark side of teleworking for mothers who struggled immensely with work–life balance. This study builds on past research by allowing mothers to share their experiences in their own words and offering suggestions for how organizations can support mothers in navigating these ongoing challenges as teleworking continues to remain prevalent. The narratives collected hold important implications for practices and policies to best support the needs of mothers as they continue to work and care for their children within the home.
From tourists to nomads: unveiling the transformative potential of digital nomads in travel and tourism
Authors: Arslan Erdal 
Published: April 2024

PurposeThe primary objective of the current study is to unveil this relatively new phenomenon in the context of travel and tourism. In line with this purpose, the study provides a comprehensive overview of the concept of digital nomadism through a tourism perspective, discusses the relationship between digital nomadism, travel and tourism, examines the opportunities and threats of digital nomadism, and finally uncovers its transformative impact.Design/methodology/approachThis conceptual study examined secondary data, i.e. existing literature. In this data, the focus has been on the tourism aspect of the digital nomad phenomenon.FindingsThe results suggest that digital nomadism introduces a novel perspective on the nature of travel and tourism mobility, along with a distinct tourist typology characterized by unique traits. Moreover, the results indicate that, while digital nomadism contributes to the local economy and cultural change on the one hand, it poses challenges in terms of regulations and taxation on the other. In this context, one can conclude that legislators should establish regulations for the employment of digital nomads, while managers should engage in activities that attract potential digital nomads on an international scale.Originality/valueThe study comprehensively reviews relevant literature in various ways, conducts a conceptualization of digital nomad tourists and makes a noteworthy theoretical contribution within the context of tourism. It addresses the gaps in the existing literature, particularly in specific contexts such as the legal status of digital nomads, taxation, prevention of gentrification, cultural exchanges, identity transformation and the impact on travel and tourism.
Split‐sample reliability estimation in health care quality measurement: Once is not enough
Authors: Nieser Kenneth J. , Harris Alex H. S. 
Published: April 2024

AbstractObjectiveTo examine the sensitivity of split‐sample reliability estimates to the random split of the data and propose alternative methods for improving the stability of the split‐sample method.Data Sources and Study SettingData were simulated to reflect a variety of real‐world quality measure distributions and scenarios. There is no date range to report as the data are simulated.Study DesignSimulation studies of split‐sample reliability estimation were conducted under varying practical scenarios.Data Collection/Extraction MethodsAll data were simulated using functions in R.Principal FindingsSingle split‐sample reliability estimates can be very dependent on the random split of the data, especially in low sample size and low variability settings. Averaging split‐sample estimates over many splits of the data can yield a more stable reliability estimate.ConclusionsMeasure developers and evaluators using the split‐sample reliability method should average a series of reliability estimates calculated from many resamples of the data without replacement to obtain a more stable reliability estimate.