bluuebunny/crossref_metadata_2025_split huggingface dataset:
Factors affecting adoption intention of electric vehicle: a cross-cultural study
Authors: Higueras-Castillo Elena , Singh Vedant , Singh Virender , Liébana-Cabanillas Francisco 
Published: September 2023

AbstractIn recent years, the surge in the adoption of electric vehicles has played a vital role in reducing fossil fuel consumption and greenhouse gas emissions. However, limited cross-national research has been conducted on the determinants of electric vehicle adoption in developing and developed countries. This study examines the factors influencing the intention to adopt electric vehicles in India (378 participants) and Spain (265 participants). This study develops an integrated model that combines the unified theory of acceptance and use of technology (UTAUT2) and the value-belief-norm (VBN) model while accounting for the impact of national culture. The model is tested using structural equation modeling. The results indicate the integrated UTAUT2-VBN model is a valuable tool for explaining the differences in adoption intention across cultures. Moreover, the national cultural system plays a significant moderating role in most relationships within the model. This study offers valuable insights into the factors influencing electric vehicle adoption in different cultural contexts, which can inform policies and strategies to promote sustainable transportation.
Improving the accuracy of the FMO binding affinity prediction of ligand-receptor complexes containing metals
Authors: Paciotti R. , Marrone A. , Coletti C. , Re N. 
Published: September 2023

AbstractPolarization and charge transfer strongly characterize the ligand-receptor interaction when metal atoms are present, as for the Au(I)-biscarbene/DNA G-quadruplex complexes. In a previous work (J Comput Aided Mol Des2022, 36, 851–866) we used the ab initio FMO2 method at the RI-MP2/6-31G* level of theory with the PCM [1] solvation approach to calculate the binding energy (ΔEFMO) of two Au(I)-biscarbene derivatives, [Au(9-methylcaffein-8-ylidene)2]+ and [Au(1,3-dimethylbenzimidazole-2-ylidene)2]+, able to interact with DNA G-quadruplex motif. We found that ΔEFMO and ligand-receptor pair interaction energies (EINT) show very large negative values making the direct comparison with experimental data difficult and related this issue to the overestimation of the embedded charge transfer energy between fragments containing metal atoms. In this work, to improve the accuracy of the FMO method for predicting the binding affinity of metal-based ligands interacting with DNA G-quadruplex (Gq), we assess the effect of the following computational features: (i) the electron correlation, considering the Hartree–Fock (HF) and a post-HF method, namely RI-MP2; (ii) the two (FMO2) and three-body (FMO3) approaches; (iii) the basis set size (polarization functions and double-ζ vs. triple-ζ) and (iv) the embedding electrostatic potential (ESP). Moreover, the partial screening method was systematically adopted to simulate the solvent screening effect for each calculation. We found that the use of the ESP computed using the screened point charges for all atoms (ESP-SPTC) has a critical impact on the accuracy of both ΔEFMO and EINT, eliminating the overestimation of charge transfer energy and leading to energy values with magnitude comparable with typical experimental binding energies. With this computational approach, EINT values describe the binding efficiency of metal-based binders to DNA Gq more accurately than ΔEFMO. Therefore, to study the binding process of metal containing systems with the FMO method, the adoption of partial screening solvent method combined with ESP-SPCT should be considered. This computational protocol is suggested for FMO calculations on biological systems containing metals, especially when the adoption of the default ESP treatment leads to questionable results.
Psychosocial Determinants of Sleep Behavior and Healthy Sleep Among Adolescents: A Two-Wave Panel Study
Authors: Delfmann Lea Rahel , Verloigne Maïté , Deforche Benedicte , Hunter Simon C. , Cardon Greet , de Boer Janneke , Vandendriessche Ann 
Published: September 2023

AbstractTo date, it remains unknown which psychosocial determinants identified by several leading behavior change theories are associated with different sleep parameters among adolescents. Therefore, this study investigates whether changes in knowledge about healthy sleep, attitude toward healthy sleep and going to bed on time, self-efficacy to engage in healthy sleep behavior, perceived parental and peer norms, perceived barriers (e.g., worrying, fear of missing out), and perceived support (e.g., bedtime rules, encouragement) related to healthy sleep are associated with changes in adolescents’ sleep duration on school days and free days and sleep quality over a period of 1 year. Two-wave data of 1648 Flemish adolescents (mean age = 15.01, SD = 0.65, 46.3% female) were analyzed using linear models. Increased levels of parental social support, positive attitude towards and perceived advantages of healthy sleep, norm-knowledge, and perceived peer behavior were associated with sleep duration, with parental social support having the strongest association. Increased levels of perceived barriers were associated with decreased levels of sleep quality parameters, and increased levels of self-efficacy, positive attitude, and parental modeling were associated with improved sleep quality parameters, with perceived barriers having the strongest association. The current results indicate that behavior change theories are useful in the context of adolescent sleep behavior and suggest that perceived parental support (i.e., bedtime rules) and perceived barriers are most strongly associated with adolescents’ sleep duration and/or quality.
On the stability of relativistic perfect fluids with linear equations of state $$p=K\rho $$ where $$1/3<K<1$$
Authors: Marshall Elliot , Oliynyk Todd A. 
Published: September 2023

AbstractFor $$1/3<K<1$$

1
/
3
<
K
<
1

, we consider the stability of two distinct families of spatially homogeneous solutions to the relativistic Euler equations with a linear equation of state $$p=K\rho $$

p
=
K
ρ

on exponentially expanding FLRW spacetimes. The two families are distinguished by one being spatially isotropic while the other is not. We establish the future stability of nonlinear perturbations of the non-isotropic family for the full range of parameter values $$1/3<K<1$$

1
/
3
<
K
<
1

, which improves a previous stability result established by the second author that required K to lie in the restricted range (1/3, 1/2). As a first step towards understanding the behaviour of nonlinear perturbations of the isotropic family, we construct numerical solutions to the relativistic Euler equations under a $$\mathbb {T}{}^2$$

T

2

-symmetry assumption. These solutions are generated from initial data at a fixed time that is chosen to be suitably close to the initial data of an isotropic solution. Our numerical results reveal that, for the full parameter range $$1/3<K<1$$

1
/
3
<
K
<
1

, the density gradient $$\frac{\partial _{x}\rho }{\rho }$$

∂
x

ρ

ρ

associated to a nonlinear perturbation of an isotropic solution develops steep gradients near a finite number of spatial points where it becomes unbounded at future timelike infinity. This behavior of the density gradient was anticipated by Rendall (Ann Henri Poincaré 5(6):1041–1064, 2004), and our numerical results confirm his expectations.
Farming system change under different climate scenarios and its impact on food security: an analytical framework to inform adaptation policy in developing countries
Authors: Abbas Máriam , Ribeiro Paulo Flores , Santos José Lima 
Published: September 2023

AbstractDeveloping countries are considered extremely vulnerable to climate change, due to their socioeconomic context (high levels of poverty) and high dependence of their livelihoods on natural resources. Rural areas in these countries concentrate most of the poorest and food-insecure people in the world, with farmers being among the most vulnerable to climate change. The impacts of climate change are expected to be spatially heterogeneous. In this sense, this paper aims at exploring the direct, marginal effect of climate change on farming system choice and its implications to food security in Mozambique, using a space-for-time approach. Our results suggest that major changes are to be expected in farming system choice and their spatial distribution due to climate change, which will potentially impact the livelihoods and food security status of smallholder farmers. Farming systems including food/cash crops and/or livestock, which are among the most food secure, will tend to be replaced by other systems in all climate scenarios. Mixed farming systems (including food and livestock) and livestock-oriented systems, mostly food insecure, predominant in arid areas are expected to expand with climate change. Food security and innovation stress maps were sketched out from the modelling results, identifying priority areas for public intervention. We also highlight how our approach can be an effective and easily replicable framework to address this type of issues in other developing regions facing similar problems.
A framework for generating large-scale microphone array data for machine learning
Authors: Kujawski Adam , Pelling Art J. R. , Jekosch Simon , Sarradj Ennes 
Published: September 2023

AbstractThe use of machine learning for localization of sound sources from microphone array data has increased rapidly in recent years. Newly developed methods are of great value for hearing aids, speech technologies, smart home systems or engineering acoustics. The existence of openly available data is crucial for the comparability and development of new data-driven methods. However, the literature review reveals a lack of openly available datasets, especially for large microphone arrays. This contribution introduces a framework for generation of acoustic data for machine learning. It implements tools for the reproducible random sampling of virtual measurement scenarios. The framework allows computations on multiple machines, which significantly speeds up the process of data generation. Using the framework, an example of a development dataset for sound source characterization with a 64-channel array is given. A containerized environment running the simulation source code is openly available. The presented approach enables the user to calculate large datasets, to store only the features necessary for training, and to share the source code which is needed to reproduce datasets instead of sharing the data itself. This avoids the problem of distributing large datasets and enables reproducible research.
Text-aided Group Decision-making Process Observation Method (x-GDP): a novel methodology for observing the joint decision-making process of travel choices
Authors: Parady Giancarlos , Oyama Yuki , Chikaraishi Makoto 
Published: September 2023

AbstractJoint travel decisions, particularly related to social activities remain poorly explained in traditional behavioral models. A key reason for this is the lack of empirical data, and the difficulties associated with collecting such data in the first place. To address this problem, we propose Text-aided Group Decision-making Process Observation Method (x-GDP), a novel survey methodology to collect data on joint activities from all members of a given clique. More specifically, on a Zoom-moderated experiment, participant cliques are asked to coordinate an activity (or set of activities) using a group chat interface. The experiment requires not only the coordination but the execution of the planned activity, thus guaranteeing a real discussion that takes into consideration the preferences and constraints of clique members. Through this method we are able to observe not only the outcome of the choice process, but also the decision-making process itself in a quasi-naturalistic manner, including the alternatives that compose the choice set, individual and clique characteristics that might affect the choice process, as well as the discussion behind the choice via texts. In this paper we introduce the results of an x-GDP survey implementation focusing on joint eating-out activities in the Greater Tokyo Area. Preliminary data analysis clearly illustrates the heterogeneity of the choice processes among groups and how members’ spatiotemporal constraints, individual and relational characteristics, as well as the bargaining process affect choice outcomes. Given the unique characteristics of the collected data, we discuss how x-GDP can be used to (i) identify and categorize group decision-making patterns, (ii) model group decisions explicitly considering the decision-making process, (iii) estimate joint accessibility measures and (iv) analyze choice set generation processes.
An analysis of international mobility and research productivity in computer science
Authors: Finocchi Irene , Ribichini Andrea , Schaerf Marco 
Published: September 2023

AbstractIn this article, we study the international mobility of researchers in the field of computer science (CS). Our analysis hinges upon Scopus data spanning a time period of 30 years (1991–2020) and involves a total of 969,835 researchers and 8,412,543 publications. Our contribution is two-fold. First, we characterize mobility as a fairly common phenomenon in CS, we highlight a strong correlation with standard bibliometric indicators at all seniority levels and a lower propensity of female researchers to relocate internationally than their male colleagues. Second, we analyze individual career paths building from them a mobility graph and identifying common patterns, such as the most traveled connections between different countries, whether they are equally traversed in both directions and the most frequently visited countries. The temporal evolution of the above patterns within our 30-year time frame is also investigated. The United States emerged as a preferred destination for internationally mobile authors, with strong connections to China (from the early 2000s), Canada, and several prominent European countries, most notably the United Kingdom, Germany, and France.
How to frame innovation in mathematics
Authors: Fisseni Bernhard , Sarikaya Deniz , Schröder Bernhard 
Published: September 2023

AbstractWe discuss conceptual change and progress within mathematics, in particular how tools, structural concepts and representations are transferred between fields that appear to be unconnected or remote from each other. The theoretical background is provided by the frame concept, which is used in linguistics, cognitive science and artificial intelligence to model how explicitly given information is combined with expectations deriving from background knowledge. In mathematical proofs, we distinguish two kinds of frames, namely structural frames and ontological frames. The interaction between both kinds of frames can drive mathematical interpretation. We first discuss two examples where structural frames (formulaic notation) drive ontological development (the discovery or exploration of mathematical objects). The development of Boole’s Boolean algebra may at first appear as a metaphorical treatment of the (then) new area of logic. In the analysis, we discuss how different (aspects of) certain algebraic frames change in the transfer, how arising difficulties are solved and overall argue that Boole uses the numerical algebra frame as a research template for the discovery of a system for calculations in logic. Following Ifrah, we analyse the discovery of zero as an extension to the number ontology as driven by the development of notation. Both structural and ontological frames are extended and simplified as notation progresses. Finally, we discuss two examples from infinite combinatorics, viz. topological graph theory, and one foundational issue. In both examples, the two simultaneous frames about one object are maintained independently. They motivate different research questions, but may also fruitfully interact: shifting between multiple synchronously maintained perspectives acts as a motor of innovation. The analysis shows how a frame-based approach allows to model how different perspectives drive mathematical innovation because they highlight different aspects, questions and heuristics.
A Computational Study of Cluster Dynamics in Structural Lubricity: Role of Cluster Rotation
Authors: Oo Wai , Baykara Mehmet , Gao Hongyu 
Published: September 2023

AbstractWe present a computational study of sliding between gold clusters and a highly oriented pyrolytic graphite substrate, a material system that exhibits ultra-low friction due to structural lubricity. By means of molecular dynamics, it is found that clusters may undergo spontaneous rotations during manipulation as a result of elastic instability, leading to attenuated friction due to enhanced interfacial incommensurability. In the case of a free cluster, shear stresses exhibit a non-monotonic dependency on the strength of the tip-cluster interaction, whereby rigid clusters experience nearly constant shear stresses. Finally, it is shown that the suppression of the translational degrees of freedom of a cluster’s outermost-layer can partially annihilate out-of-plane phonon vibrations, which leads to a reduction of energy dissipation that is in compliance with Stokesian damping. It is projected that the physical insight attained by the study presented here will result in enhanced control and interpretation of manipulation experiments at structurally lubric contacts.
Harnessing distributional semantics to build context-aware justifications for recommender systems
Authors: Musto Cataldo , Spillo Giuseppe , Semeraro Giovanni 
Published: September 2023

AbstractThis paper introduces a methodology to generate review-based natural language justifications supporting personalized suggestions returned by a recommender system. The hallmark of our strategy lies in the fact that natural language justifications are adapted to the different contextual situations in which the items will be consumed. In particular, our strategy relies on the following intuition: Just like the selection of the most suitable item is influenced by the contexts of usage, a justification that supports a recommendation should vary as well. As an example, depending on whether a person is going out with her friends or her family, a justification that supports a restaurant recommendation should include different concepts and aspects. Accordingly, we designed a pipeline based on distributional semantics models to generate a vector space representation of each context. Such a representation, which relies on a term-context matrix, is used to identify the most suitable review excerpts that discuss aspects that are particularly relevant for a certain context. The methodology was validated by means of two user studies, carried out in two different domains (i.e., movies and restaurants). Moreover, we also analyzed whether and how our justifications impact on the perceived transparency of the recommendation process and allow the user to make more informed choices. As shown by the results, our intuitions were supported by the user studies.
Bacterial diseases in marine fish species: current trends and future prospects in disease management
Authors: Hegde Avani , Kabra Suhani , Basawa Renuka Manjunath , Khile Dnyanada Anil , Abbu Rahil Ummar Faruk , Thomas Naomi Ann , Manickam Nava Bharati , Raval Ritu 
Published: September 2023

AbstractThe fisheries sub-sector of aquaculture—i.e., the pisciculture industry, contributes significantly to a country’s economy, employing a sizable proportion of the population. It also makes important contributions to household food security because the current demand for animal protein cannot be fulfilled by harvesting wild fish from riverines, lakes, dams, and oceans. For good pond management techniques and sustaining fish health, the fisherfolk, and the industry require well-established regulatory structures, efficient disease management strategies, and other extended services. In rearing marine fish, infections resulting from disease outbreaks are a weighty concern because they can cause considerable economic loss due to morbidity and mortality. Consequently, to find effective solutions for the prevention and control of the major diseases limiting fish production in aquaculture, multidisciplinary studies on the traits of potential fish pathogens, the biology of the fish as hosts, and an adequate understanding of the global environmental factors are fundamental. This review highlights the various bacterial diseases and their causative pathogens prevalent in the pisciculture industry and the current solutions while emphasising marine fish species. Given that preexisting methods are known to have several disadvantages, other sustainable alternatives like antimicrobial peptides, synthetic peptides, probiotics, and medicinal treatments have emerged to be an enormous potential solution to these challenges.
Graphical abstract
Extraction of rare earth elements from monazite leach liquor using functionalized chitosan sorbents derived from shrimp waste
Authors: Matter Emad A. , Dhmees Abdelghaffar S. , Salem Waheed M. , El-Magied Mahmoud O. Abd , Ahmed Gaber Hashem Gaber 
Published: September 2023

AbstractWith the growing need for high-purity rare-earth elements (REEs), the separation of these REEs has received much attention recently. The objective of this research is to produce chitosan from shrimp waste, then modify it with different functionality, and investigate the adsorption properties of chitosan adsorbents towards La(III) ions. First, from shrimp waste, chitosan (ch) with a significant degree of deacetylation, purity, and solubility was produced. The purified chitosan was cross-linked with epichlorohydrin (ep), and then, it was modified with 3,6,9,12-tetraazatetradecane-1,14-diamine (HA) to produce polyaminated chitosan (HA@ep@Ch). The polycarboxylated/imine chitosan (CM@HA@ep@Ch) was obtained by treating polyaminated chitosan with chloroacetic acid in isopropyl alcohol. The chitosan adsorbents were characterized and applied for lanthanum recovery from synthetic and monazite leach liquor samples. The factors controlling the recovery process were studied and discussed. The performance of the adsorbents was achieved through equilibrium, dynamic, and isothermal studies. HA@ep@Ch and CM@HA@ep@Ch showed good performance for lanthanum recovery with a maximum capacity of 114.52 and 141.76 mg/g at 330 K, respectively. The isotherm parameters refer to the monolayer of lanthanum adsorbed into the adsorbents through chelation and ion exchange mechanisms. A 0.5-M HCl solution was found effective to elute 95.8% of the adsorbed lanthanum on HA@ep@Ch, and 93.4% of the adsorbed lanthanum on CM@HA@ep@Ch. The adsorbents showed greater selectivity in extracting La, Ce, Pr, Nd, and Sm (62–75%) from REE leach liquid compared to extracting other REEs (20–41%).