bluuebunny/crossref_metadata_2025_split huggingface dataset:
Quantifying the relationship between time to command-following and outcomes after TBI: the “1%” rule
Authors: Snider Samuel B. , Deng Hansen , Hammond Flora M. , Kowalski Robert G. , Walker William C. , Zafonte Ross D. , Okonkwo David O. , Giacino Joseph T. , Puccio Ava M. , Bodien Yelena G. 
Published: June 2024

AbstractImportanceRecovery of command-following after traumatic brain injury (TBI) is an important prognostic indicator, however, the relationship between time to command-following and long-term functional outcome is not clear.ObjectiveEvaluate the association between command-following and outcome 1-year after TBI.DesignCohort study of participants with moderate-severe TBI in the TBI Model Systems (TBIMS) who were followed 1-year post injury, and validation in an independent dataset from the Brain Trauma Research Center (BTRC) database.SettingTBIMS is a multi-center study of participants with moderate-severe TBI treated in an inpatient rehabilitation hospital. The BTRC database is derived from a single US level 1 trauma center and includes patients with severe TBI.ParticipantsTBIMS: N=9,052 (mean±SD age 38±18 years, 76% male, 67% white); BTRC: N=228 (mean age 37±17 years, 76% male, 91% white). Participants did not follow commands on acute hospital admission and survived to discharge.ExposureDays to command-following during hospitalization.Main OutcomeGlasgow Outcome Scale Extended (GOSE) score <4 (i.e., death or dependency) 1-year post TBI.ResultsParticipants in TBIMS were more likely than those in BTRC to follow commands during acute hospitalization (90% vs 63%; p<0.001) and had a shorter median time to command-following (5 vs 9.5 days; p< 0.001). For each additional week without command-following, the odds ratio for death or dependency at 1 year was 1.30 (95% CI: [1.26,1.35]; p<0.001) in TBIMS and 1.49 ([1.15, 1.97]; p=0.003) in BTRC. Time to command-following had an AUC of 0.61 [0.59, 0.63] in TBIMS and 0.65 [0.53, 0.76]) in BTRC. Each additional day without command-following was associated with a 1.18% (1.16%, 1.20%) increase in the proportion of participants with death or dependency at 1-year in TBIMS and 1.05% (0.99%, 1.11%) in BTRC.ConclusionTime to command-following after moderate-severe TBI is associated with 1-year outcomes, but the predictive accuracy of absence of command-following on any single post-injury day is limited. In two independent cohorts, the likelihood of death or dependency increased by ∼1% for each additional day without command-following. Clinicians should be cautious when prognosticating based on the absence of command-following in the first five weeks after TBI.
Abnormality Detection in Time-Series Bio-Signals using Kolmogorov-Arnold Networks for Resource-Constrained Devices
Authors: Huang Zhaojing , Cui Jiashuo , Yu Leping , Herbozo Contreras Luis Fernando , Kavehei Omid 
Published: June 2024

AbstractThis study uses Kolmogorov-Arnold Networks (KANs) to analyze electrocardiogram (ECG) signals in order to detect cardiac abnormalities. These novel networks have demonstrated potential for application in biosignal analysis, particularly ECG, due to their flexibility and smaller parameter requirements, making them candidates for wearable devices. The network structure comprises a simple KAN model with a single hidden layer of 64 neurons. It was trained on the Telehealth Network of Minas Gerais (TNMG) dataset and tested for generalization on the Chinese Physiological Signal Challenge 2018 (CPSC) dataset. The KAN model delivered reasonably promising results, achieving an F1-score of 0.75 and an AUROC of 0.95 on the TNMG dataset. During the out-of-sample generalization test on the CPSC dataset, it achieved an F1-score of 0.62 and an AUROC of 0.84. It has also shown resistance to missing data channels by maintaining a reasonable performance, down to only a single lead left of ECG data instead of the initial 12 leads. Compared with traditional Multi-Layer Perceptrons (MLP) and Neural Circuit Policy (NCP, aka. Liquid Time Constant Networks), KANs exhibit superior flexibility, adaptability, interpretability, and efficiency. Their compact size and reduced computational requirements make them potential candidates for deployment on hardware, particularly in personalized medical devices.
From Sleep Patterns to Heart Rhythms: Predicting Atrial Fibrillation from Overnight Polysomnograms
Authors: Koscova Zuzana , Rad Ali Bahrami , Nasiri Samaneh , Reyna Matthew A. , Sameni Reza , Trotti Lynn M. , Sun Haoqi , Turley Niels , Stone Katie L. , Thomas Robert J. , Mignot Emmanuel , Westover Brandon , Clifford Gari D. 
Published: June 2024

AbstractBackgroundAtrial fibrillation (AF) is often asymptomatic and thus under-observed. Given the high risks of stroke and heart failure among patients with AF, early prediction and effective management are crucial. Importantly, obstructive sleep apnea is highly prevalent among AF patients (60–90%); therefore, electrocardiogram (ECG) analysis from polysomnography (PSG), a standard diagnostic tool for subjects with suspected sleep apnea, presents a unique opportunity for the early prediction of AF. Our goal is to identify individuals at a high risk of developing AF in the future from a single-lead ECG recorded during standard PSGs.MethodsWe analyzed 18,782 single-lead ECG recordings from 13,609 subjects at Massachusetts General Hospital, identifying AF presence using ICD-9/10 codes in medical records. Our dataset comprises 15,913 recordings without a medical record for AF and 2,056 recordings from patients who were first diagnosed with AF between 1 day to 15 years after the PSG recording. The PSG data were partitioned into training, validation, and test cohorts. In the first phase, a signal quality index (SQI) was calculated in 30-second windows and those with SQI<0.95 were removed. From each remaining window, 150 hand-crafted features were extracted from time, frequency, time-frequency domains, and phase-space reconstructions of the ECG. A compilation of 12 statistical features summarized these window-specific features per recording, resulting in 1,800 features. We then updated a pre-trained deep neural network and data from the PhysioNet Challenge 2021 using transfer-learning to discriminate between recordings with and without AF using the same Challenge data. The model was applied to the PSG ECGs in 16-second windows to generate the probability of AF for each window. From the resultant probability sequence, 13 statistical features were extracted. Subsequently, we trained a shallow neural network to predict future AF using the extracted ECG and probability features.ResultsOn the test set, our model demonstrated a sensitivity of 0.67, specificity of 0.81, and precision of 0.3 for predicting AF. Further, survival analysis for AF outcomes, using the log-rank test, revealed a hazard ratio of 8.36 (p-value of 1.93 × 10−52).ConclusionsOur proposed ECG analysis method, utilizing overnight PSG data, shows promise in AF prediction despite a modest precision indicating the presence of false positive cases. This approach could potentially enable low-cost screening and proactive treatment for high-risk patients. Ongoing refinement, such as integrating additional physiological parameters could significantly reduce false positives, enhancing its clinical utility and accuracy.
Nocturnal synchronization between hippocampal ripples and cortical delta power is a biomarker of hippocampal epileptogenicity
Authors: Iwata Takamitsu , Yanagisawa Takufumi , Fukuma Ryohei , Ikegaya Yuji , Oshino Satoru , Tani Naoki , Khoo Hui M. , Sugano Hidenori , Iimura Yasushi , Suzuki Hiroharu , Kishima Haruhiko 
Published: June 2024

AbstractObjectiveHippocampal ripples are biomarkers of epileptogenicity in patients with epilepsy, and physiological features characterize memory function in healthy individuals. Discriminating between pathological and physiological ripples is important for identifying the epileptogenic (EP) zone; however, distinguishing them from waveforms is difficult. This study hypothesized that the nocturnal synchronization of hippocampal ripples and cortical delta power classifies EP and physiological hippocampi.MethodsWe enrolled 38 patients with electrodes implanted in the hippocampus or the parahippocampal gyrus between April 2014 and March 2023 at our institution. We classified 11 patients (11 hippocampi) into the EP group, who were pathologically diagnosed with hippocampal sclerosis, and five patients (six hippocampi) into the non-epileptogenic (NE) group, whose hippocampi had no epileptogenicity. Hippocampal ripples were detected using intracranial electroencephalography of the hippocampal or parahippocampal electrodes and presented as ripple rates per second. Cortical delta power (0.5–4 Hz) was assessed using cortical electrodes. The Pearson correlation coefficient between the ripple rates and the cortical delta power (CRD) was calculated for the intracranial electroencephalographic signals obtained every night during the recordings.ResultsHippocampal ripples detected from continuous recording for approximately 10 days demonstrated similar frequency characteristics between the EP and NE groups. However, CRDs in the EP group (mean [standard deviation]: 0.20 [0.049]) were significantly lower than those in the NE group (0.67 [0.070],F(1,124) = 29.6,p< 0.0001 (group),F(9,124) = 1.0,p= 0.43 (day); two-way analysis of variance). Based on the minimum CRDs during the 10-day recordings, the two groups were classified with 94.1% accuracy.ConclusionCRD is a biomarker of hippocampal epileptogenicity.Key PointsThe correlation between hippocampal ripple rate and cortical delta power was evaluated for approximately 10 days in patients with drug-resistant epilepsy.Mean correlation coefficients were significantly lower in the epileptogenic group than in the non-epileptogenic group.The minimum value of the correlation coefficients predicts hippocampal sclerosis.
Cultural values and the P-O fit: comparative NLP analysis of German online job advertisements
Authors: Herold Marcel , Roedenbeck Marc 
Published: June 2024

PurposeWithin the Person-Organization fit framework and Signalling Theory, this study investigates the performance of word dictionaries detecting cultural values in online job advertisements as one form of external communication of an organization. Based upon a merge of the dictionaries, a corporate value analysis of Germany is conducted.Design/methodology/approachThe study builds on a dataset (n > 151 k) of online job advertisements which were scraped from a German job portal. It was pre-processed according to natural language processing standards. For analysing the values of an organization a dictionary based word count was applied. Therefore, the current state-of-the-art dictionaries were tested, and an enhanced dictionary was developed and translated from English to German. Finally, a cluster analysis was conducted.FindingsThis study supports the possibility of measuring cultural values in texts where the enhanced dictionary based on Ponitzovskiy shows the best results. It thereby supports the use of the Universal Value Structure model (Schwartz, 1992) as well as the Signalling Theory (Guest et al., 2021), that values spread across 10 core or 4 aggregated dimensions are communicated via online job advertisements. Finally, the study offers a profile of the German corporate culture average as well as 4 cultural clusters and separate organizations, all with different profiles.Originality/valueThis study develops an enhanced dictionary based on a large dataset of online job advertisements for analysing the external communication of values or culture of an organization for improving the Person-Organization fit.
Computational approach and convergence analysis for interval-based solution of the Benjamin–Bona–Mahony equation with imprecise parameters
Authors: Vana Rambabu , Perumandla Karunakar 
Published: June 2024

PurposeTo provide a new semi-analytical solution for the nonlinear Benjamin–Bona–Mahony (BBM) equation in the form of a convergent series. The results obtained through HPTM for BBM are compared with those obtained using the Sine-Gordon Expansion Method (SGEM) and the exact solution. We consider the initial condition as uncertain, represented in terms of an interval then investigate the solution of the interval Benjamin–Bona–Mahony (iBBM).Design/methodology/approachWe employ the Homotopy Perturbation Transform Method (HPTM) to derive the series solution for the BBM equation. Furthermore, the iBBM equation is solved using HPTM to the initial condition has been considered as an interval number as the coefficient of it depends on several parameters and provides lower and upper interval solutions for iBBM.FindingsThe obtained numerical results provide accurate solutions, as demonstrated in the figures. The numerical results are evaluated to the precise solutions and found to be in good agreement. Further, the initial condition has been considered as an interval number as the coefficient of it depends on several parameters. To enhance the clarity, we depict our solutions using 3D graphics and interval solution plots generated using MATLAB.Originality/valueA new semi-analytical convergent series-type solution has been found for nonlinear BBM and interval BBM equations with the help of the semi-analytical technique HPTM.
Do gender-inclusive HRM and fairness perception trigger paradigm shifts in female employees' psychological empowerment patterns and career progression?
Authors: Rasheed Muhammad Athar , Bajwa Sami Ullah , Elahi Natasha Saman 
Published: June 2024

PurposeDrawing on the ability-motivation-opportunity model, this study investigates how gender-inclusive human resource management practices and overall fairness perception promote the career progression of female employees via psychological empowerment.Design/methodology/approachPartial least structural equation modelling (PLS-SEM) was applied to two-waves data collected from 308 respondents from Pakistan to confirm hypotheses.FindingsFindings suggest that gender-inclusive HRM practices substantially affect female employees' psychological empowerment and career progression. Psychological empowerment is a mediating mechanism that explains the effect of gender-inclusive HRM practices on female employees' career progression. Finally, overall fairness perception further amplifies the effect of gender-inclusive HRM practices on psychological empowerment and career progression.Practical implicationsThe study provides evidence to policymakers that organizations may promote psychological empowerment and career progression of female employees by implementing gender-inclusive HRM practices and promoting overall fairness perception.Originality/valueThis study contributes to achieving the SDGs by examining the impact of gender-inclusive HRM practices and overall fairness perception on female employees' psychological empowerment and career progression. Specifically, it aligns with “Goal 5 - achieve gender equality and empower all women and girls” and “Goal 8 - promote sustained, inclusive, and sustainable economic growth, full and productive employment, and decent work for all”.
Shared goals and vision in supply chain: a mediation model of prevention-oriented practices and compliance-oriented practices
Authors: Luo Charles , Zhang Dongli , Linderman Kevin , Ni John 
Published: June 2024

PurposeManufacturers face increasing demands to address inefficiencies and improve environmental performance across their supply chains. However, there remains a significant gap in empirical research examining how collaboration in the supply chain affects various environmental practices and their consequent impacts on performance. This study aims to address the gap by examining how shared goals and vision drives compliance-oriented and prevention-oriented practices, subsequently affecting environmental performance and operational costs—critical for fostering antifragility and resilience in today’s environment.Design/methodology/approachAn empirical study has been performed based on a sample of survey data from 279 manufacturers from fifteen countries and regions. Applying structural equation modeling analysis to the sample dataset, this study examines the mediating role of two distinct types of environmental practices between shared goals and visions and manufacturers’ environmental performance and operational cost.FindingsThis study delineates distinct pathways through which shared goals and vision affect various types of environmental practices, and consequently lead to different performance outcomes: (1) environmental impact of manufacturing activities depends on the collective efforts of the manufacturers and their supply chain partners; (2) shared goals and vision among supply chain partners facilitates both environmental performance and operational cost through prevention-oriented practice; (3) shared goals and vision in supply chain benefits operational cost performance primarily through prevention-oriented practice, but less likely through compliance-oriented practice.Practical implicationsThis study reveals two distinct pathways through which the shared goals and vision impact various performance outcomes, providing valuable guidance to businesses aiming to balance operational cost and environmental performance — crucial for resilience in today's turbulent environment.Originality/valueThis study not only corroborates existing theories of the Natural Resource-Based View and collaborative networks but also provides a detailed depiction of how collaboration across the supply chain promotes a diverse range of environmental practices and yields varied performance outcomes. It offers vital insights for supply chain participants to effectively navigate environmental challenges, enabling them to cultivate resilience and proactively address environmental issues.
How consumers evaluate costs in complex services: the case of mutual fund fees
Authors: Nilsson Jonas , Carlsson Hauff Jeanette , Carlander Anders 
Published: June 2024

Purpose
In modern societies, consumer well-being is dependent on choices regarding complex services, such as investments, health care, insurance and lending. However, evaluating costs of such services is often difficult for consumers due to a combination of limited cognitive resources and complexity of the service. The purpose of this study is to empirically examine to what extent three specific consequences of complexity influence consumer tendencies to make mistakes when evaluating the costs (or price) of complex services.

Design/methodology/approach
Three studies were conducted (survey: n = 153, experiment: n = 332 and conjoint analysis: n = 225), all focusing on how consumers evaluate costs in the complex mutual fund setting.

Findings
The authors find that consumers struggle with estimating and using cost information in decision-making in the complex services setting. Consumers of complex services frequently underestimate the costs over the long-term, may see costs as a signal of service quality and are susceptible to influence from presentation formats when evaluating costs.

Research limitations/implications
The study investigates mutual funds, which is one example of a complex service. In order to get a full picture of how consumers deal with costs in complex setting, future research needs to expand this focus to other types of complex services.

Practical implications
The results have implications for both marketers of complex services and policymakers. For marketers, this paper highlights that competing with a low-cost strategy may be difficult in the complex services setting as consumers may lack the ability to actually evaluate what they pay over the long term. For policymakers, increased simplification of prices may be an attractive option. However, it is important that this simplification is done in a way that increases the possibility to compare prices.

Originality/value
As complexity influences several aspects of decision-making, an understanding of how consumers evaluate costs in complex settings is dependent on taking a multidimensional research approach. This paper makes a novel contribution to the literature on pricing by showing that consumers struggle with multiple aspects when evaluating costs in complex contexts. Understanding these effects is important to policy, as well as to research on the cognitive value of simplicity that is currently gaining traction in marketing research.
Going beyond the untold facts in PLS–SEM and moving forward
Authors: Hair Joe F. , Sarstedt Marko , Ringle Christian M. , Sharma Pratyush N. , Liengaard Benjamin Dybro 
Published: June 2024

Purpose
This paper aims to discuss recent criticism related to partial least squares structural equation modeling (PLS-SEM).

Design/methodology/approach
Using a combination of literature reviews, empirical examples, and simulation evidence, this research demonstrates that critical accounts of PLS-SEM paint an overly negative picture of PLS-SEM’s capabilities.

Findings
Criticisms of PLS-SEM often generalize from boundary conditions with little practical relevance to the method’s general performance, and disregard the metrics and analyses (e.g., Type I error assessment) that are important when assessing the method’s efficacy.

Research limitations/implications
We believe the alleged “fallacies” and “untold facts” have already been addressed in prior research and that the discussion should shift toward constructive avenues by exploring future research areas that are relevant to PLS-SEM applications.

Practical implications
All statistical methods, including PLS-SEM, have strengths and weaknesses. Researchers need to consider established guidelines and recent advancements when using the method, especially given the fast pace of developments in the field.

Originality/value
This research addresses criticisms of PLS-SEM and offers researchers, reviewers, and journal editors a more constructive view of its capabilities.
The role of financial literacy in consumer financial fraud exposure (via email) and victimisation: evidence from Spain
Authors: Rey-Ares Lucía , Fernández-López Sara , Álvarez-Espiño Marcos 
Published: June 2024

PurposeThe ongoing evolution of the Internet and the subsequent digitalisation of financial services, along with the ever-increasing innovation of financial products, have rendered consumers more vulnerable to a wider range of fraud in the banking sector and, particularly, to consumer financial fraud (CFF). This paper aims to analyse the factors that may contribute to CFF exposure and victimisation among Spaniards, with a special focus on financial literacy.Design/methodology/approachThis paper provides a comprehensive overview of leading publications on the topic, followed by empirical analyses using regression models with a sample of 6,207 Spanish individuals drawn from the Survey of Financial Competences.FindingsObjective and subjective financial knowledge are positively correlated with CFF exposure via email but do not protect against CFF victimisation. Similarly, financial knowledge overconfidence is positively related to the former but fails to constitute a driver of the latter. Financial inclusion, measured by the number of financial products held, not only increases the risk of this exposure but also contributes to its subsequent victimisation.Originality/valueTo the best of the authors' knowledge, no previous paper has analysed the relationship between CFF and financial literacy by differentiating two types of vulnerabilities to fraud (exposure and victimisation) while considering different constructs of financial literacy. Dissecting these two domains may explain why the same financial literacy construct can have different effects at both stages of financial fraud and, furthermore, how different financial literacy constructs may affect the same stage of financial fraud.