bluuebunny/crossref_metadata_2025_split huggingface dataset:
Impact of inorganic and organic pollutants from a Belgian wastewater treatment plant on adjacent surface and groundwaters
Authors: Luo Mingyue , Su Yiqi , Vandeputte Delphine Jenny , Jia Yuwei , Li Guanlei , Baeyens Willy , Huysmans Marijke , Elskens Marc , Gao Yue 
Published: January 2024

AbstractUnder the pressure of global droughts and water shortage, it is essential to evolve toward a sustainable and robust water system. One possible avenue is the maximum reuse of treated wastewater, but the quality of which determines its reuse. Therefore, inorganic (Cd, Pb, Cr, Ni, Cu, and As) and organic (xenoestrogens and polycyclic aromatic contaminants, PACs) contaminants were monthly monitored in an effluent of the wastewater treatment plant (WWTP), the surrounding surface waters and the local groundwater in Belgium. Dissolved and particulate concentrations of inorganic contaminants in these water bodies were analyzed. In addition, Diffusive Gradients in Thin-films (DGT) was used in situ to obtain bioavailable metal fractions. In the WWTP effluent and surface waters, only Ni exceeds the Annual Average-Environmental Quality Standard (AA-EQS), while in the groundwater, dissolved As was the predominant element. Moreover, in the surface and effluent waters the highest lability degrees were observed for Cd and Ni. The concentrations of these metal species in the effluent water were lower than in the other water bodies. Micro-organic pollutants, xenoestrogens and PACs were analyzed by dual Estrogen and Aryl hydrocarbon Receptor - Chemical Activated LUciferase gene eXpression (ER & AhR-CALUX) assays. Since the annual averaged (AA) bioequivalent concentration of E2 (0.18 ng/L) is below the AA-EQS standard (0.4 ng/L), and the bioequivalent concentration of benzo[a]pyrene never exceeded the maximum admissible concentration (MAC), the reclamation and reuse of treated wastewater for groundwater replenishment and agricultural irrigation should pose no environmental problems, at least in a short-term.
Linear integral operators on $$L_p$$ spaces representing polynomial covariance type commutation relations
Authors: Djinja Domingos , Silvestrov Sergei , Tumwesigye Alex Behakanira 
Published: January 2024

AbstractIn this work, we present methods for constructing representations of polynomial covariance type commutation relations $$AB=BF(A)$$

A
B
=
B
F
(
A
)

by linear integral operators in Banach spaces $$L_p$$

L
p

. We derive necessary and sufficient conditions on the kernel functions for the integral operators to satisfy the covariance type commutation relation for general polynomials F, as well as for important cases, when F is arbitrary affine or quadratic polynomial, or arbitrary monomial of any degree. Using the obtained general conditions on the kernels, we construct concrete examples of representations of the covariance type commutation relations by integral operators on $$L_p$$

L
p

. Also, we derive useful general reordering formulas for the integral operators representing the covariance type commutation relations, in terms of the kernel functions.
Exploring what makes learning meaningful for postgraduate business students in higher education
Authors: Zeivots Sandris , Tyrrell Jessica , Wardak Dewa 
Published: January 2024

AbstractWhile research exists on what constitutes meaningful learning, our study reveals the term meaningful is an ill-defined concept that is interpreted in multiple ways, often from a teacher-centric perspective. Less is known about what constitutes meaningfulness in the context of higher education, particularly in business education. This qualitative study seeks to identify postgraduate student perspectives on what is meaningful in higher education to inform the design of authentic and transformative learning experiences. Focus groups were conducted to gain insights into students’ most meaningful learning experiences across four postgraduate business subjects. We conducted a thematic analysis of the student data by inductively coding the transcripts and comments. Students derived the most value from learning experiences that incorporated real-world connections, social encounters, or productive challenges. We also found that students’ discussions of meaningfulness were relatively superficial, suggesting that postgraduate students may not be primed to consider meaningfulness in relation to their learning. We thus problematise the term meaningful and conclude by proposing ‘learning highs’ as a new tentative conceptual frame for future research identifying learning situations in which meaningful experiences occur.
VERITE: a Robust benchmark for multimodal misinformation detection accounting for unimodal bias
Authors: Papadopoulos Stefanos-Iordanis , Koutlis Christos , Papadopoulos Symeon , Petrantonakis Panagiotis C. 
Published: January 2024

AbstractMultimedia content has become ubiquitous on social media platforms, leading to the rise of multimodal misinformation (MM) and the urgent need for effective strategies to detect and prevent its spread. In recent years, the challenge of multimodal misinformation detection (MMD) has garnered significant attention by researchers and has mainly involved the creation of annotated, weakly annotated, or synthetically generated training datasets, along with the development of various deep learning MMD models. However, the problem of unimodal bias has been overlooked, where specific patterns and biases in MMD benchmarks can result in biased or unimodal models outperforming their multimodal counterparts on an inherently multimodal task, making it difficult to assess progress. In this study, we systematically investigate and identify the presence of unimodal bias in widely used MMD benchmarks, namely VMU-Twitter and COSMOS. To address this issue, we introduce the “VERification of Image-TExt pairs” (VERITE) benchmark for MMD which incorporates real-world data, excludes “asymmetric multimodal misinformation” and utilizes “modality balancing”. We conduct an extensive comparative study with a transformer-based architecture that shows the ability of VERITE to effectively address unimodal bias, rendering it a robust evaluation framework for MMD. Furthermore, we introduce a new method—termed Crossmodal HArd Synthetic MisAlignment (CHASMA)—for generating realistic synthetic training data that preserve crossmodal relations between legitimate images and false human-written captions. By leveraging CHASMA in the training process, we observe consistent and notable improvements in predictive performance on VERITE; with a 9.2% increase in accuracy. We release our code at: https://github.com/stevejpapad/image-text-verification
Third-Country Regime and Equivalence: The Swiss Perspective
Authors: Darbellay Aline 
Published: January 2024

AbstractThis paper discusses the role of the third-country regime and equivalence from the Swiss perspective. It provides an analysis of the evolution of the Swiss approach. The various reactions to EU developments have ranged from the attempt to implement a reciprocity principle, to the resort to unilateral recognition. An overarching purpose of the Swiss equivalence framework has consisted of the relentless pursuit of a competitiveness objective. Yet the decline of equivalence as a market access mechanism has led to favouring other market access routes. This paper concludes that the recent reforms have initiated a roadmap towards an increasing autonomy of Swiss financial market law.
Deep Q-learning with hybrid quantum neural network on solving maze problems
Authors: Chen Hao-Yuan , Chang Yen-Jui , Liao Shih-Wei , Chang Ching-Ray 
Published: January 2024

AbstractQuantum computing holds great potential for advancing the limitations of machine learning algorithms to handle higher dimensions of data and reduce overall training parameters in deep learning (DL) models. This study uses a trainable variational quantum circuit (VQC) on a gate-based quantum computing model to investigate the potential for quantum benefit in a model-free reinforcement learning problem. Through a comprehensive investigation and evaluation of the current model and capabilities of quantum computers, we designed and trained a novel hybrid quantum neural network based on the latest Qiskit and PyTorch framework. We compared its performance with a full-classical CNN with and without an incorporated VQC. Our research provides insights into the potential of deep quantum learning to solve a maze problem and, potentially, other reinforcement learning problems. We conclude that reinforcement learning problems can be practical with reasonable training epochs. Moreover, a comparative study of full-classical and hybrid quantum neural networks is discussed to understand these two approaches’ performance, advantages, and disadvantages to deep Q-learning problems, especially on larger-scale maze problems larger than 4$$\times $$
×
4.
Accuracy Analysis for Explicit-Implicit Finite Volume Schemes on Cut Cell Meshes
Authors: May Sandra , Laakmann Fabian 
Published: January 2024

AbstractThe solution of time-dependent hyperbolic conservation laws on cut cell meshes causes the small cell problem: standard schemes are not stable on the arbitrarily small cut cells if an explicit time stepping scheme is used and the time step size is chosen based on the size of the background cells. In May and Berger (J Sci Comput 71: 919–943, 2017), the mixed explicit-implicit approach in general and MUSCL-Trap (monotonic upwind scheme for conservation laws and trapezoidal scheme) in particular have been introduced to solve this problem by using implicit time stepping on the cut cells. Theoretical and numerical results have indicated that this might lead to a loss in accuracy when switching between the explicit and implicit time stepping. In this contribution, we examine this in more detail and will prove in one dimension that the specific combination MUSCL-Trap of an explicit second-order and an implicit second-order scheme results in a fully second-order mixed scheme. As this result is unlikely to hold in two dimensions, we also introduce two new versions of mixed explicit-implicit schemes based on exchanging the explicit scheme. We present numerical tests in two dimensions where we compare the new versions with the original MUSCL-Trap scheme.
Experimental sensing quantum atmosphere of a single spin
Authors: Zhu Kehang , Yang Zhiping , Jiang Qing-Dong , Chai Zihua , Li Zhijie , Zhao Zhiyuan , Wang Ya , Shi Fazhan , Duan Chang-Kui , Rong Xing 
Published: January 2024

AbstractUnderstanding symmetry-breaking states of materials is a major challenge in the modern physical sciences. Quantum atmosphere proposed recently sheds light on the hidden world of these symmetry broken patterns. Yet, no experiment has been performed to demonstrate its potential. In our experiment, we prepare time-reversal-symmetry conserved and broken quantum atmosphere of a single nuclear spin and successfully observe their symmetry properties. Our work proves in principle that finding symmetry patterns from quantum atmosphere is conceptually viable. It also opens up entirely new possibilities in the potential application of quantum sensing in material diagnosis.
Better-than-chance prediction of cooperative behaviour from first and second impressions
Authors: Schniter Eric , Shields Timothy W. 
Published: January 2024

Abstract
Could cooperation among strangers be facilitated by adaptations that use sparse information to accurately predict cooperative behaviour? We hypothesise that predictions are influenced by beliefs, descriptions, appearance and behavioural history available for first and second impressions. We also hypothesise that predictions improve when more information is available. We conducted a two-part study. First, we recorded thin-slice videos of university students just before their choices in a repeated Prisoner's Dilemma with matched partners. Second, a worldwide sample of raters evaluated each player using videos, photos, only gender labels or neither images nor labels. Raters guessed players’ first-round Prisoner's Dilemma choices and then their second-round choices after reviewing first-round behavioural histories. Our design allows us to investigate incremental effects of gender, appearance and behavioural history gleaned during first and second impressions. Predictions become more accurate and better-than-chance when gender, appearance or behavioural history is added. However, these effects are not incrementally cumulative. Predictions from treatments showing player appearance were no more accurate than those from treatments revealing gender labels and predictions from videos were no more accurate than those from photos. These results demonstrate how people accurately predict cooperation under sparse information conditions, helping explain why conditional cooperation is common among strangers.
Pharmacogenomic and epigenomic approaches to untangle the enigma of IL-10 blockade in oncology
Authors: Elemam Noha M. , Mekky Radwa Y. , Rashid Gowhar , Braoudaki Maria , Youness Rana A. 
Published: January 2024

Abstract
The host immune system status remains an unresolved mystery among several malignancies. An immune-compromised state or smart immune-surveillance tactics orchestrated by cancer cells are the primary cause of cancer invasion and metastasis. Taking a closer look at the tumour-immune microenvironment, a complex network and crosstalk between infiltrating immune cells and cancer cells mediated by cytokines, chemokines, exosomal mediators and shed ligands are present. Cytokines such as interleukins can influence all components of the tumour microenvironment (TME), consequently promoting or suppressing tumour invasion based on their secreting source. Interleukin-10 (IL-10) is an interlocked cytokine that has been associated with several types of malignancies and proved to have paradoxical effects. IL-10 has multiple functions on cellular and non-cellular components within the TME. In this review, the authors shed the light on the regulatory role of IL-10 in the TME of several malignant contexts. Moreover, detailed epigenomic and pharmacogenomic approaches for the regulation of IL-10 were presented and discussed.
The relationship between caffeine and its metabolites and bone mineral density in postmenopausal women: a cross-sectional analysis from the NHANES database
Authors: Liao Sheng , Zhou Jianhong , Chen Hui , Wei Wei , Ye Feng , Zhang Yidong , Zhang Zhongrong 
Published: January 2024

Abstract
We aim to explore the association between caffeine and its metabolites and bone mineral density (BMD) in postmenopausal women. Data of 4286 postmenopausal women were extracted from the National Health and Nutrition Examination Survey (NHANES) database in 2009–14 in this cross-sectional study. Weighted linear regression and stepwise regression analyses were used to screen the covariates. Weighted univariate and multivariate linear regression analyses were used to explore the associations between caffeine and its metabolites and BMD. The evaluation index was estimated value (β) with 95 % confidence intervals (CIs). We also explored these relationships in age subgroups. The median BMD level among the eligible women was 0⋅7 gm/cm2. After adjusting for covariates including age, body mass index (BMI), fat intake, Calcium (Ca) supplements, diabetes mellitus (DM), angina pectoris, parental history of osteoporosis (OP), anti-osteoporosis therapy, poverty income ratio (PIR), vitamin D (VD) supplements, coronary heart disease (CHD), and previous fracture, we found that caffeine intake was not significantly related to the BMD reduction (β = 0, P = 0⋅135). However, caffeine metabolites, including MethyluricAcid3, MethyluricAcid7, MethyluricAcid37, Methylxanthine3, and Methylxanthine37, were negatively associated with the BMD (all P < 0⋅05). In addition, MethyluricAcid37 and Methylxanthine37 were negatively associated with BMD in females aged <65 years old, while MethyluricAcid3 and Methylxanthine3 were noteworthy in those who aged ≥65 years old. The roles of caffeine and its metabolites in BMD reduction and OP in postmenopausal women needed further exploration.
‘That’s Not Something That’s Necessarily on the Radar’: Educators’ Perspectives on Dysgraphia
Authors: Kalenjuk Elvira , Subban Pearl , Laletas Stella , Wilson Sue 
Published: January 2024

AbstractThis qualitative study focused on educators’ perspectives of teaching students with dysgraphia. Dysgraphia can be referred to as a specific learning disorder (SLD) in writing and includes difficulties with handwriting, spelling, and/or composition skills. To explore the educators’ experiences, an interpretative phenomenological analysis method was implemented. This involved generating semistructured interviews and locating key concepts from these interviews, in tandem with researcher reflections. The results indicated that educators developed their self-efficacy in supporting students with dysgraphia on the job, augmented by self-guided and external searches for information about dysgraphia. The participants described their colleagues as generally unable to provide them with dysgraphia-specific knowledge due to a lack of awareness of dysgraphia within schools. Two of the three educators pursued Multisensory Structured Language training, departing the classroom to work in private tuition. Three teachers offered strategies for supporting students with dysgraphia, such as explicit, systematic, scaffolded, and repetitive instruction coupled with assistive technologies or lined paper and slant boards. The study concluded that dysgraphia-specific professional learning, coupled with collective efficacy, could proactively build teachers’ capacity and self-efficacy in supporting dysgraphia within an inclusive education context. These measures would more aptly support students with dysgraphia to reach their potential.
Whither dominance? An enduring evolutionary legacy of primate sociality
Authors: Altschul Drew M. 
Published: January 2024

Abstract
This article discusses dominance personality dimensions found in primates, particularly in the great apes, and how they compare to dominance in humans. Dominance traits are seen in virtually all primate species, and these dimensions reflect how adept an individual is at ascending within a social hierarchy. Among great apes, dominance is one of the most prominent personality factors but, in humans, dominance is usually modeled as a facet of extraversion. Social, cultural, and cognitive differences between humans and our closest ape relatives are explored, alongside humanity’s hierarchical and egalitarian heritage. The basic characteristics of dominance in humans and nonhuman great apes are then described, alongside the similarities and differences between great apes. African apes live in societies each with its own hierarchical organization. Humans were a possible exception for some of our history, but more recently, hierarchies have dominated. The general characteristics of high-dominance humans, particularly those living in industrialized nations, are described. Dominance itself can be subdivided into correlated subfactors: domineering, prestige, and leadership. Various explanations have been posed for why dominance has declined in prominence within human personality factor structures, and several possibilities are evaluated. The value of dominance in personality research is discussed: dominance has links to, for instance, age, sex, aggression, self-esteem, locus of control, stress, health, and multiple socioeconomic status indicators. The piece concludes with recommendations for researchers who wish to assess dominance in personality.
‘The very term mensuration sounds engineer-like’: measurement and engineering authority in nineteenth-century river management
Authors: Dishington Rachel 
Published: January 2024

AbstractMeasurement was vital to nineteenth-century engineering. Focusing on the work of the Stevenson engineering firm in Scotland, this paper explores the processes by which engineers made their measurements credible and explains how measurement, as both a product and a practice, informed engineering decisions and supported claims to engineering authority. By examining attempts made to quantify, measure and map dynamic river spaces, the paper analyses the relationship between engineering experience and judgement and the generation of data that engineers considered to be ‘tolerably correct’. While measurement created an abstract and simplified version of the river that accommodated prediction, this abstraction had to be connected to and made meaningful in real river space despite acknowledged limitations to measuring practice. In response, engineers drew on experience gained through the measuring process to support claims to authoritative knowledge. This combination of quantification and experience was then used to support interventions in debates over the proper use and management of rivers. This paper argues that measurement in nineteenth-century engineering served a dual function, producing both data and expertise, which were both significant in underpinning engineering authority and facilitating engineers’ intervention in decision making for river management.
The Multidirectional Diaspora: Writing Chinese Migration History in a Time of Global Racial Reckoning
Authors: Zhou Taomo 
Published: January 2024

In On not speaking Chinese, cultural studies scholar Ien Ang characterizes migrant scholars as ‘tactical interventionists’; instead of making counter-hegemonic claims, they usually bring out the contradictions and the violence inherent in all posited truths. In the spirit of this claim, I thought long and hard about how to make the best use of my connections to both worlds – my lived experience of growing up in China and my access to academic resources in English-language academia. As James Gethyn Evans will show in his essay in this roundtable, ‘decolonizing’ the field of Chinese history should involve the dual tasks of questioning the hegemonic narratives propagated by the People’s Republic of China (PRC) government and the concentration of knowledge production in the Global North. Without the participation of PRC-based scholars, the current ‘decolonization’ movement would become a Western enterprise just like colonization.
In vitro evaluation of nanocomposites of linseed mucilage and k-carrageenan loaded with Achyrocline satureioides nanoemulsion: a gradual-release candidate of antimicrobials for the treatment of bovine mastitis
Authors: Machado Gabriela Tasso Pinheiro , Ferreira Roberto Gabriel , Veleirinho Maria Beatriz , Honorato Luciana Aparecida , Ramos Roberta de Oliveira , Silva Marcos Antônio Segatto , Kuhnen Shirley 
Published: January 2024

AbstractThis research paper presents the development and evaluation of pioneering nanocomposites (NCs) based on the combination of k-carrageenan and linseed mucilage. When loaded with macela extract nanoemulsion they present an innovative approach for the sustained release of antimicrobial herbal constituents, specifically tailored for bovine mastitis treatment. The NCs, encompassing various ratios of k-carrageenan and linseed mucilage polymers (8:2, 7:3, and 5:5 w/w) with 1.25 mg of macela extract/g of gel, underwent in vitro assessment, emphasizing viscosity, degradation speed, release of herbal actives from macela nanoemulsion and antimicrobial activity. The NCs exhibited thermoreversible characteristics, transitioning from liquid at 60°C to a gel at 25°C. NCs allowed a gradual release of phenolic compounds, reaching approximately 80% of total phenolics release (w/v) within 72 h. NCs inhibited the growth of MRSA (ATCC 33592) until 8 h of incubation. No toxic effect in vitro of NCs was found on MAC-T cells. Thus, the developed materials are relevant for the treatment of bovine mastitis, especially in the dry period, and the data support future evaluations in vivo.