bluuebunny/crossref_metadata_2025_split huggingface dataset:
Affordable Care Act Medicaid expansion, access to health care, and financial behavior of the United States adults
Authors: Bin Abdul Baten Redwan , Noman Abdullah , Rahman Mohammad Nakibur 
Published: September 2024

AbstractThe access to care benefits of Affordable Care Act (ACA) Medicaid expansions are important for 45–64-year-old adults who are living below 100% of the Federal Poverty Level, a particularly vulnerable group in the United States (US). Gaining coverage from Medicaid expansions should improve access to healthcare and affect social determinants of health, including financial behavior. We analyzed data from 2009 to 2018 from the National Financial Capability Survey (NFCS) and utilize a difference-in-differences model to compare outcomes changes in states with and without expansion before and after the ACA Medicaid expansions. Overall, Medicaid expansion was associated with increased healthcare access for 45–64-year-olds, potentially resulting in better healthcare experience. Results indicate effects of the Medicaid expansion on the financial behavior of 45–64-year-olds, with evidence of credit card bills being paid in full, higher banking activities, and better financial preparedness. These findings have important implications for financial regulators and healthcare policymakers.
Home Team Effect and Opinion Network after the Sewol Ferry Disaster: A mixed-method study of the influence of symbol and feedback on liberal versus conservative newspapers’ negative opinions
Authors: Cho Ki Woong 
Published: September 2024

AbstractStudies on the symbol and feedback effects on the opinion based on the theory are lacking. Acknowledging that the media express their stance and opinion and that negative opinions are critical to policy change, this paper fills the gap in the literature by illustrating and comparing the effects of emotional and cognitive symbols and positive and negative feedback on the liberal and conservative newspapers’ negative opinions of South Korean President Park Geun-hye’s administration (Park administration) after the Sewol Ferry sank. This study used qualitative and quantitative methods to analyze the archival data, including 424 newspaper editorials and economic data published from April to December 2014. Multiple regression analyses were conducted following a content analysis of newspaper editorials, and network analysis was used to analyze the data. The results mostly supported the hypotheses that symbols and feedback affect the negative opinion on the political discourse, with new findings that deviate from the existing theories. The emotional symbols exerted a stronger influence on the negative opinion compared to cognitive symbols, regardless of the newspaper’s stance. The political system’s response to the positive and negative feedback was not definite; instead, it varied depending on the situation and newspaper perspective. The liberal newspaper responded to symbols and feedback more sensitively compared to the conservative one under the conservative administration. The conservative newspaper expressed more lenient negative opinions towards the conservative administration than the liberal newspaper, supporting the home team effect. These findings have practical and theoretical implications for future studies, highlighting the application of opinion networks in social science.
Introduction
Authors: Fiorentini Ilaria , Zanchi Chiara 
Published: September 2024

Abstract
The relationship between ambiguity and vagueness is traditionally
considered rather complex. It is not always easy to distinguish between the
two phenomena, and the two concepts may seem to overlap. This introduction
aims to clarify what is generally understood by ambiguity and vagueness in
previous scholarship and to emphasize the purpose of the volume, also in
relation to the questions that remain open about the two phenomena. In
presenting the chapters that make up the volume, an overview is given of how
each of them responds to these questions. Finally, an attempt is made to
draw some conclusions about the novel aspects brought about by the volume
and possible future developments.
The role of ambiguity in intentional vagueness
Authors: Voghera Miriam 
Published: September 2024

Abstract
In order to study the relationship between ambiguity and
vagueness, it is necessary to distinguish Systemic Vagueness (SV),
which is a property of any linguistic codes, from Intentional
Vagueness (IntV), which emerges in messages produced by speakers in
response to specific communicative needs. In fact, while ambiguity is one of the possible
manifestations of SV, the expression of IntV tends to avoid
ambiguous elements. This is confirmed empirically by an analysis
carried out on Italian and German spoken corpora to investigate
whether and how many ambiguous elements were used in Vagueness
Expressions (VEs), which shows how the presence of ambiguous terms
in VEs is exiguous in both languages. The almost complete absence of
ambiguity and intentional vagueness co-occurring in this research
seems to confirm the different nature and function of the two
phenomena.
Underspecification and ambiguity of voice markers
Authors: Giomi Riccardo , Inglese Guglielmo 
Published: September 2024

Abstract
Voice markers have a notorious cross-linguistic tendency
towards multifunctionality, in that a given marker can encode more
than one voice operation at a time, such as reflexive and passive.
In addition, diachronic typological research has also shown that
patterns of multifunctionality of voice markers historically come
about following paths that are not necessarily unidirectional.
Taking stock of these premises, in this paper we propose a new
typology of voice markers grounded on the notion of
underspecification and ambiguity, and, by adopting the perspective
of Functional Discourse Grammar, we argue that the lack of
unidirectionality in the grammaticalization of voice markers follows
from their status as interface operators.
Place names in legal texts
Authors: D’Argenio Elisa , Ghezzi Chiara 
Published: September 2024

Abstract
This paper considers the role played by vagueness and
ambiguity when applied to geographic referents. Through a corpus of
Latin purchase and gift contracts, dating to the 8th-10th centuries
and written in the Bergamo and Salerno areas during the Lombard
kingdoms, the study focuses on the formula locus ubi
dicitur lit. ‘place where it is called’, particularly
productive and characteristic in the texts, with the aim of
confronting strategies employed by Northern and Southern notaries.
The analysis shows that notaries use the trigger phrase
locus ubi dicitur as a strategy to highlight a
difficulty in the attribution of a name to a place and, as such, can
be described as a case of intentional vagueness. Relevant in
the vague use of the phrase is the ambiguity of
locus itself which in the documents is highly
polysemous and whose meaning is characterised by an interpretative
indeterminacy which is context-dependent. The analysis shows
that vagueness, when applied to geographic referents, is semantic,
rather than ontic, as it lies in the representation system and, thus
in the representation process, not in its product.
Getting started with spacecraft instrument data: a walkthrough with Voyager 2 magnetometry
Authors: Neel Matthew S 
Published: September 2024

Abstract
With hundreds of data sets available for public consumption, and with missions ranging from the USSR’s Sputnik satellite in 1957 [1] to NASA’s James Webb Space Telescope launched in 2022 [2], it can be difficult and bewildering to know where to start when there is a need to analyze spacecraft instrument data. Many types and generations of technology have been employed in the scientific instruments carried into space since the world’s space agencies were established, and data produced by older instruments are generally less user-friendly in structure and format than data generated by more modern instruments. In this article, we present a general approach to acquiring, understanding, documenting and analyzing instrument data and apply it to a specific example. We chose to explore Voyager 2 data, and the Neptune fly-by in particular, since there is some interest of late in re-examining old data and questioning our assumptions about the ice giants [3, 4]. This walkthrough is intended to assist students and researchers in understanding issues unique to spacecraft data and to help facilitate student projects.
Formation of positionally ordered but orientationally disordered molecular organization on surface
Authors: Duan Jun-Jie , Wang Zi-Cong , Chen Ting , Wang Dong 
Published: September 2024

Abstract
Positionally ordered but orientationally disordered molecular structures are commonly found in materials like liquid crystals and molecular glasses. Understanding these structures and their phase transitions helps in designing materials with a wide range of applications. Herein, we report the formation of positionally ordered but orientationally disordered structures via adsorption and organization of 2,4,6-tri([1,1’-biphenyl]-2-yl)-1,3,5-triazine (TBTA) molecules on different coin metal surfaces. It is found that deposition of TBTA molecules on Au(111), Ag(111), and Cu(111) surfaces leads to similar hexagonal lattices, differing in molecular orientation. The molecules have two orientations on Au(111) and Ag(111) surfaces, giving birth to positionally ordered but orientationally disordered molecular structures. The regularity of the structures on Ag(111) is slightly better than that on Au(111). On Cu(111) surface, however, all molecules exhibit the same orientation, resulting in a long-range ordered hexagonal assembly. The density functional theory calculations demonstrate that the matching between the substrate lattice and the hexagonal lattice of molecular structure is responsible for the different molecular organizations.
Robust massless Dirac fermions in hydro-/halogenated trigonal borophene
Authors: Meng L-B , Liu D X , Ni S , Zhang Z M , Zhou W M 
Published: September 2024

Abstract
The striking electronic characteristics of graphene trigger immense interests and continual explora-tions for new two-dimensional (2D) Dirac materials. By first-principles electronic structure calculations, we here identify a new set of 2D semimetals in hydro-/halogen embedding trigonal δ
6 borophene, namely δ
6-B3X (X = H, F, Cl), that possess the graphene-like massless Dirac fermions. Owing to the central hollow B atoms strongly hybridized to the hydro-/halogen adatoms, adequate charge transfer is induced from the hollow B to the basal honeycomb B sublattice, which electronically stabilizes the 2D sheet and decisively endows a robust (intrinsic and stable-against-strains) graphene-like Dirac cone state. The predicted high energetic, dynamic and thermal stabilities, combined with pretty geometrical match to the commonly utilized Ag/Au(111) substrates, support their experimental viabilities. Our prediction provides a new branch for exploring the intriguing 2D Dirac fermionic states in versatile boron element and its derivatives.
Bolt loosening status classification via wave energy dissipation measurements with temperature-compensated deep learning by piezoelectric active sensing
Authors: Lu Lingxiao , Ying Sancong , Xiao Qian , Hou Chaohuan 
Published: September 2024

Abstract
In industrial applications, bolts, serving as crucial components, endure substantial loads and are susceptible to loosening problems exacerbated by intricate external environmental factors. The active sensing method based on wave energy dissipation exhibits pronounced sensitivity to axial load fluctuations in bolts and demonstrates extensive applicability, with its measurement indicators directly applicable for discerning the bolt’s status. However, environmental factors, notably temperature, can significantly influence signal energy measurements, and the oversight of temperature impact may result in erroneous state discrimination. To tackle this challenge, this paper introduces a cascaded model comprising a temperature compensation subnetwork and a bolt state discrimination subnetwork. The temperature compensation subnetwork takes temperature and signal energy as inputs and outputs the temperature-compensated signal energy, and conveys the outcomes to the bolt state discrimination subnetwork for state classification. In model design, we quantitatively analyzed the number of convolutional blocks and training epochs for the temperature compensation subnetwork with the aim of enhancing the model’s generalization ability, ultimately determining the model architecture. By comparing the experimental results between a single-task model and a model incorporating the temperature compensation subnetwork, we verified the effectiveness of the temperature compensation subnetwork. The experimental outcomes demonstrate that the proposed cascaded model achieved a state classification accuracy of 98.6% on over 1300 temperature-generalized data points. To comprehensively assess our approach, we conducted detailed comparisons with other bolt loosening monitoring methods, elucidating the effectiveness based on data trends and model design. Experimental results demonstrate that the proposed temperature compensation cascaded model accurately identifies bolt states amidst complex temperature variations.
A precise registration method for large-scale urban point clouds based on phased and spatial geometric features
Authors: Xu Mengbing , Han Youmei , Zhong Xueting , Sang Fengyun , Zhang Yuan 
Published: September 2024

Abstract
The dense high-rise buildings and multipath effects in urban areas significantly reduce the positioning signal accuracy of laser scanning systems, leading to layering and offset issues in the collected point cloud data on the same road. In order to acquire comprehensive and consistent three-dimensional information on the objects, thereby providing field inspection data for large-scale road traffic network scenarios, in this paper, an improved point cloud registration method is proposed to divide the registration process into two stages: elevation registration and plane registration. Elevation registration takes the ground point cloud as the registration primitive, reduces the number of point clouds through curvature down-sampling, and constrains the feature point sequence with a fixed range to provide a good initial pose for fine registration. The plane registration first inherits the elevation registration parameters, combining the dynamic distance parameters of spherical region step based on the median, using robust multi-scale loss functions to address residual points, effective adjacent point pairs are selected to obtain the spatial transformation matrix, and realizes accurate registration. Experimental results with multiple sets of urban point cloud data show that the root mean square error of point cloud registration can be controlled within 0.06 m, achieving a relatively superior registration accuracy, it can provide detailed prior data for measurement information analysis.
A category incremental continuous learning model for imbalance arrhythmia detection
Authors: Feng Jianchao , Si Yujuan , Sun Meiqi , Zhang Yu 
Published: September 2024

Abstract
The development of efficient arrhythmia detection systems is crucial for physiological measurements and computer-aided diagnosis. Existing systems rely mainly on offline learning methods and lack the ability to assimilate new data or recognize emerging categories. To address these challenges, this study introduces an arrhythmia detection model that is resistant to data imbalance and has continuous learning capabilities, specifically for incremental learning of new ECG data categories. The system incorporates constraints derived from the new class data and implements a dynamic mechanism for updating connection weights, facilitating the incremental continual learning of classes. Confronted with the problem of models forgetting the original data and overfitting with the added data in continuous learning, we introduce a data balancing method by regularization to balance the model’s memory and learning of the two types of data. Facing the data imbalance problem in continuous learning, we introduce a posteriori probability weighting strategy. This strategy assigns greater importance to high-value samples based on the model’s posterior residual kernel density estimates. Comprehensive testing of the model using various datasets from the MIT-BIH database indicates superior performance in incremental learning tasks. The results reveal that the model not only excels in class incremental learning but also ensures effective balancing across different data classes.
TEOS modification for improved performance in perovskite solar cells: addressing the interface defects and charge transfer issues of SnO2 ETL
Authors: Ebic Murat 
Published: September 2024

Abstract
The remarkable advancements in performance and rapid progress of perovskite solar cells (PSCs) in recent years have captured the interest of the photovoltaics (PVs) community. Nevertheless, defects occurring at the interface between the electron transporting layer (ETL) and perovskite, along with issues related to charge transfer, significantly impede the PV efficiency of these cells. In this study, we investigated the impact of tetraethyl orthosilicate (TEOS) on charge transfer and defect states at the interface by incorporating varying concentrations of TEOS into the SnO2 ETL and modifying the interface between the ETL and perovskite. This process can passivate the defects at the ETL/perovskite (Cs0.05(FA0.85MA0.15)0.95Pb(I0.85Br0.15)3) interface and significantly extend the carrier lifetime. Moreover, TEOS modification plays a promising role in the growth kinetics of the perovskite films. As a result, a power conversion efficiency (PCE) of 20.0% was achieved with admissible phase stability in the presence of TEOS as dopant in SnO2 ETL, while only 17.64% PCE was obtained for TEOS-free control structure. A promising PCE of 19.93% was achieved for ETL/TEOS/perovskite interface modification. This study presents a promising solution to address interface defects and charge transfer issues, which represent significant obstacles to the commercial scalability of PSCs.
Analysis of leakage artifacts and their impact on convergence of algebraic reconstruction in multi-contrast magnetic particle imaging
Authors: Nawwas Lina , Möddel Martin , Knopp Tobias 
Published: September 2024

Abstract

Objective. Magnetic particle imaging (MPI) is a tracer-based medical imaging modality with great potential due to its high sensitivity, high spatiotemporal resolution, and ability to quantify the tracer concentration. Image reconstruction in MPI is an ill-posed problem, which the use of regularization methods can address. Multi-contrast MPI reconstructs the signal from different tracer materials or environments separately, resulting in multi-channel images that enable quantification of, for example, temperature or viscosity. Single- and multi-contrast MPI reconstructions produce different kinds of artifacts. The objective of this work is threefold: first, to present the concept of multi-contrast specific MPI channel leakage artifacts; second, to ascertain the source of these leakage artifacts; and third, to introduce a method for their reduction. Approach. A definition for leakage artifacts is established, and a quantification method is proposed. A comprehensive analysis is conducted to establish a connection between the properties of the multi-contrast MPI system matrix and the leakage artifacts. Moreover, a two-step measurement and reconstruction method is introduced to reduce channel leakage artifacts between multi-contrast MPI channels. Main results. The severity of these artifacts correlates with the system matrix shape and condition number and depends on the similarity of the corresponding frequency components. Using the proposed two-step method on both semi-simulated and measured data a significant leakage reduction and speed up the convergence of the multi-contrast MPI reconstruction was observed. Significance. The multi-contrast system matrix analysis we conducted is essential for understanding the source of the channel leakage artifacts and finding methods to reduce them. Our proposed two-step method is expected to improve the potential for real-time multi-contrast MPI applications.
Hybrid finite element and laplace transform method for efficient numerical solutions of fractional PDEs on graphics processing units
Authors: Vivas-Cruz Luis X , González-Calderón Alfredo , Taneco-Hernández M A , Gómez-Aguilar J F 
Published: September 2024

Abstract
Fractional Partial Differential equations (FPDEs) are essential for modeling complex systems across various scientific and engineering areas. However, efficiently solving FPDEs presents significant computational challenges due to their inherent memory effects, often leading to increased execution times for numerical solutions. This study proposes a highly parallelizable hybrid computational approach that combines the Finite Element Method (FEM) for spatial discretization with Numerical Inversion of the Laplace Transform (NILT) for time-domain solutions, optimized for execution on Graphics Processing Units (GPUs). The NILT method’s high parallelizability, stemming from the independence of its series terms, combined with the robust spatial discretization provided by FEM, enables the efficient and accurate solution of FPDEs on GPUs, demonstrating substantial performance improvements over traditional CPU-based implementations. We observe a generalized pattern in execution time behavior that accounts for both the number of nodes and the number of NILT terms. Specifically, execution time scales quadratically with the number of nodes, while showing only a logarithmic marginal increase with the number of NILT terms These behaviors not only enables consistent performance assessment but also highlights potential areas for algorithm optimization. Validation against exact solutions of fractional diffusion and wave equations, employing Caputo, modified Caputo-Fabrizio, and modified Atangana-Baleanu derivatives, demonstrates the accuracy and convergence of the hybrid FEM-NILT method. Notably, the exact solutions of wave equation are novel in literature. The results highlight the method’s potential for enabling high-precision, large-scale simulations in fractional calculus applications, thereby advancing computational capabilities and efficiency in the field.
Integrability and inverse scattering transform of the modified Benjamin-Ono equation
Authors: Guo Ning 
Published: September 2024

Abstract
This paper presents a Bäcklund transformation, the Lax representation, and conserved quantities for the modified Benjamin-Ono equation. The initial problem of the modified Benjamin–Ono equation on the line was studied by the inverse scattering transform method, presenting a nonlocal Riemann–Hilbert problem to reconstruct the explicit potential function. Furthermore, the exact N-soliton solutions and long–time asymptotic behavior are provided. We also graphically show that the propagation of soliton solutions is consistent with the result of large-time asymptotic forms It is shown that the mBO equation admits solutions in logarithmic form, which incorporates the features of solutions for the BO equation.