bluuebunny/crossref_metadata_2025_split huggingface dataset:
Binuclear Gadolinium Complex by One‐Pot Method: Structure and Magnetic Property
Authors: Hua Lin , He Zhi‐Yong , Geng Feng , Li Yan , Wang Long , Zhu Xiang‐Jun , Li Guo‐Fang , Duan Xian‐Ying , Zhang Hui‐Qing , Chen Hai‐Tao , Zheng Fu‐Wei 
Published: July 2024

AbstractTwo binuclear Gadolinium(III) (Gd) complex [Gd2(L1)2(H2L3)2(NO3)2] (1) and [Gd2(L2)2(H2L3)2(NO3)2] (2) were obtained by using 2‐hydroxybenzaldehyde or 2‐hydroxy‐1‐naphthaldehyde, 2‐aminophenol, pyridin‐2‐ylmethanamine and Gd(NO3)3 ⋅ 6H2O in CH3CN (H2L1=(E)‐2‐((2‐hydroxybenzylidene)amino)phenol, H2L2=(E)‐1‐(((2‐hydroxyphenyl)imino)methyl)naphthalen‐2‐ol, H2L3=pyridin‐2‐ylmethanamine). Structural analysis suggests that all the ligands as protective units protect the central Gd(III) ions at the periphery. Magnetization studies exhibited magnetocaloric effect of 14.45 J ⋅ kg−1 ⋅ K−1 at 4 K under ΔH=7 T for complex 1 and 12.69 J ⋅ kg−1 ⋅ K−1 at 2 K under ΔH=7 T for complex 2. In complexes 1 and 2, although the coordination configurations are the same, the significant difference in MCE may be due to the adjustments of the peripheral ligands leading to changes in the coordination field strength. The electron affinity of the ligands can impact the interaction between the ligands and Gd(III) ions.
Jettiness formulation of the MiNNLOPS method
Authors: Ebert Markus , Rottoli Luca , Wiesemann Marius , Zanderighi Giulia , Zanoli Silvia 
Published: July 2024

Abstract
We present a new formulation of the MiNNLOPS method to match NNLO QCD calculations with parton showers by using jettiness as a resummation variable. The full derivation for colour-singlet processes is presented using 0-jettiness starting from the NNLL′ resummation formula. We show phenomenological results for Drell-Yan and Higgs-boson production at the LHC and compare our predictions to ATLAS and CMS data. Differences to the original MiNNLOPS formulation using the transverse momentum of the colour singlet as resummation variable are discussed. We further present a comparison of MiNNLOPS predictions with Geneva. Finally, we extend the formulation of the MiNNLOPS method to 1-jettiness which is applicable to processes with a colour singlet plus one jet in the final state.
Photon propagator for inflation in the general covariant gauge
Authors: Domazet Silvije , Glavan Dražen , Prokopec Tomislav 
Published: July 2024

Abstract
Photon propagator for power-law inflation is considered in the general covariant gauges within the canonical quantization formalism. Photon mode functions in covariant gauges are considerably more complicated than their scalar counterparts, except for the special choice of the gauge-fixing parameter we call the simple covariant gauge. We explicitly construct the position space photon propagator in the simple covariant gauge, and find the result considerably more complicated than its scalar counterpart. This is because of the need for explicitly inverting the Laplace operator acting on the scalar propagator, which results in Appell’s fourth function. Our propagator correctly reproduces the de Sitter and flat space limits. We use this propagator to compute two simple observables: the off-coincident field strength-field strength correlator and the energy-momentum tensor, both of which yield consistent results. As a spinoff of our computation we also give the exact expression for the Coulomb gauge propagator in power-law inflation in arbitrary dimensions.
An effective cosmological collider
Authors: Craig Nathaniel , Kumar Soubhik , McCune Amara 
Published: July 2024

Abstract
Effective field theories (EFTs) of heavy particles coupled to the inflaton are rife with operator redundancies, frequently obscured by sensitivity to both boundary terms and field redefinitions. We initiate a systematic study of these redundancies by establishing a minimal operator basis for an archetypal example, the abelian gauge-Higgs-inflaton EFT. Working up to dimension 9, we show that certain low-dimensional operators are entirely redundant and identify new non-redundant operators with potentially interesting cosmological collider signals. Our methods generalize straightforwardly to other EFTs of heavy particles coupled to the inflaton.
Dimensionally reducing generalized symmetries from (3+1)-dimensions
Authors: Nardoni Emily , Sacchi Matteo , Sela Orr , Zafrir Gabi , Zheng Yunqin 
Published: July 2024

Abstract
Recently there has been an increasing interest in the study of generalized symmetries in dimensions higher than two. This has lead to the discovery of various manifestations of generalized symmetries, notably higher-group and non-invertible symmetries, in four dimensions. In this paper we shall examine what happens to this structure when the 4d theory is compactified to lower dimensions, specifically to 3d and 2d, where we shall be mainly interested in generalized symmetry structures whose origin can be linked to mixed flavor-gauge anomalies. We discuss several aspects of the compactification, and in particular argue that under certain conditions the discussed generalized symmetry structure may trivialize in the infrared. Nevertheless, we show that even when this happens the presence of the 4d generalized symmetry structure may still leave an imprint on the low-energy theory in terms of additional ’t Hooft anomalies or by breaking part of the symmetry. We apply and illustrate this using known examples of compactifications from four dimensions, particularly, the reduction of 4d $$ \mathcal{N} $$
N
= 1 U(Nc) SQCD on a circle to 3d and on a sphere to 2d.
Renormalization of Higher Currents of the Sine-Gordon Model in pAQFT
Authors: Zanello Fabrizio 
Published: July 2024

AbstractIn this paper, we show that the higher currents of the sine-Gordon model are super-renormalizable by power counting in the framework of pAQFT. First we obtain closed recursive formulas for the higher currents in the classical theory and introduce a suitable notion of degree for their components. We then move to the pAQFT setting, and by means of some technical results, we compute explicit formulas for the unrenormalized interacting currents. Finally, we perform what we call the piecewise renormalization of the interacting higher currents, showing that the renormalization process involves a number of steps which is bounded by the degree of the classical conserved currents.
Soziale Lage, Gesundheit und Gesundheitsverhalten von Kindern und Jugendlichen in Ein-Eltern-Haushalten zum Ende der COVID-19-Pandemie. Ergebnisse der KIDA-Studie 2022–2023
Authors: Rattay Petra , Öztürk Yasmin , Geene Raimund , Blume Miriam , Allen Jennifer , Poethko-Müller Christina , Mauz Elvira , Manz Kristin , Wieland Catherine , Hövener Claudia 
Published: July 2024

Zusammenfassung
Einleitung
In der COVID-19-Pandemie waren Alleinerziehende und ihre Kinder durch die Eindämmungsmaßnahmen und aufgrund oftmals geringer Ressourcen in besonderem Maße Belastungen ausgesetzt. Es wird analysiert, inwieweit sich zum Ende der Pandemie Unterschiede in der sozialen und gesundheitlichen Lage von Kindern und Jugendlichen in Ein-Eltern- und Zwei‑Eltern-Haushalten zeigen.

Methoden
Die Analyse basiert auf Daten der KIDA-Studie, in der 2022/2023 Eltern von 3‑ bis 15-Jährigen und 16- bis 17-Jährige befragt wurden (telefonisch: n = 6992; online: n = 2896). Für die Indikatoren psychosoziale Belastungen, soziale Unterstützung, Gesundheit und Gesundheitsverhalten wurden nach Familienform stratifizierte Prävalenzen berechnet. In Poisson-Regressionen wurde für Geschlecht, Alter, Bildung und Haushaltseinkommen adjustiert.

Ergebnisse
Heranwachsende aus Ein-Eltern-Haushalten sind häufiger durch finanzielle Einschränkungen, familiäre Konflikte und beengte Wohnverhältnisse belastet und erfahren weniger schulische Unterstützung als Gleichaltrige aus Zwei‑Eltern-Haushalten. Sie haben häufiger gesundheitliche Beeinträchtigungen sowie einen erhöhten Versorgungsbedarf und nehmen häufiger psychosoziale Angebote in Anspruch. Sie sind zwar seltener in Sportvereinen aktiv, nehmen jedoch gleich häufig an Sport-AGs in Schulen teil wie Gleichaltrige aus Zwei-Eltern-Haushalten. Die Unterschiede zeigen sich auch bei Kontrolle für Einkommen und Bildung.

Diskussion
Kinder und Jugendliche aus Ein-Eltern-Haushalten können über Bewegungsangebote im schulischen Setting gut erreicht werden. Niedrigschwellige Angebote in Kita, Schule und Kommune sollten daher weiter ausgebaut werden. Weiterhin bedarf es Maßnahmen zur Verbesserung der sozioökonomischen Lage von Alleinerziehenden und ihren Kindern.
Gradient continuity for the parabolic $$(1,\,p)$$-Laplace equation under the subcritical case
Authors: Tsubouchi Shuntaro 
Published: July 2024

Abstract
This paper is concerned with the gradient continuity for the parabolic

$$(1,\,p)$$

(
1
,

p
)

-Laplace equation. In the supercritical case

$$\frac{2n}{n+2}<p<\infty $$

2
n

n
+
2

<
p
<
∞

, where

$$n\ge 2$$

n
≥
2

denotes the space dimension, this gradient regularity result has been proved recently by the author. In this paper, we would like to prove that the same regularity holds even for the subcritical case

$$1<p\le \frac{2n}{n+2}$$

1
<
p
≤

2
n

n
+
2

with

$$n\ge 3$$

n
≥
3

, on the condition that a weak solution admits the

$$L^{s}$$

L
s

-integrability with

$$s>\frac{n(2-p)}{p}$$

s
>

n
(
2
-
p
)

p

. The gradient continuity is proved, similarly to the supercritical case, once the local gradient bounds of solutions are verified. Hence, this paper mainly aims to show the local boundedness of a solution and its gradient by Moser’s iteration. The proof is completed by considering a parabolic approximate problem, verifying a comparison principle, and showing a priori gradient estimates of a bounded weak solution to the relaxed equation.
Modeling cardiac microcirculation for the simulation of coronary flow and 3D myocardial perfusion
Authors: Montino Pelagi Giovanni , Regazzoni Francesco , Huyghe Jacques M. , Baggiano Andrea , Alì Marco , Bertoluzza Silvia , Valbusa Giovanni , Pontone Gianluca , Vergara Christian 
Published: July 2024

AbstractAccurate modeling of blood dynamics in the coronary microcirculation is a crucial step toward the clinical application of in silico methods for the diagnosis of coronary artery disease. In this work, we present a new mathematical model of microcirculatory hemodynamics accounting for microvasculature compliance and cardiac contraction; we also present its application to a full simulation of hyperemic coronary blood flow and 3D myocardial perfusion in real clinical cases. Microvasculature hemodynamics is modeled with a compliant multi-compartment Darcy formulation, with the new compliance terms depending on the local intramyocardial pressure generated by cardiac contraction. Nonlinear analytical relationships for vessels distensibility are included based on experimental data, and all the parameters of the model are reformulated based on histologically relevant quantities, allowing a deeper model personalization. Phasic flow patterns of high arterial inflow in diastole and venous outflow in systole are obtained, with flow waveforms morphology and pressure distribution along the microcirculation reproduced in accordance with experimental and in vivo measures. Phasic diameter change for arterioles and capillaries is also obtained with relevant differences depending on the depth location. Coronary blood dynamics exhibits a disturbed flow at the systolic onset, while the obtained 3D perfusion maps reproduce the systolic impediment effect and show relevant regional and transmural heterogeneities in myocardial blood flow (MBF). The proposed model successfully reproduces microvasculature hemodynamics over the whole heartbeat and along the entire intramural vessels. Quantification of phasic flow patterns, diameter changes, regional and transmural heterogeneities in MBF represent key steps ahead in the direction of the predictive simulation of cardiac perfusion.
Integrating metaheuristics and artificial intelligence for healthcare: basics, challenging and future directions
Authors: Houssein Essam H. , Saber Eman , Ali Abdelmgeid A. , Wazery Yaser M. 
Published: July 2024

AbstractAccurate and rapid disease detection is necessary to manage health problems early. Rapid increases in data amount and dimensionality caused challenges in many disciplines, with the primary issues being high computing costs, memory costs, and low accuracy performance. These issues will arise since Machine Learning (ML) classifiers are mostly used in these fields. However, noisy and irrelevant features have an impact on ML accuracy. Therefore, to choose the best subset of features and decrease the dimensionality of the data, Metaheuristics (MHs) optimization algorithms are applied to Feature Selection (FS) using various modalities of medical imaging or disease datasets with different dimensions. The review starts by giving a general overview of the many approaches to AI algorithms, followed by a general overview of the various MH algorithms for healthcare applications, an analysis of MHs boosted AI for healthcare applications, and using a wide range of research databases as a data source for access to numerous field publications. The final section of this review discusses the problems and challenges facing healthcare application development.
Esophagogastroscopy for predicting endoscopic ultrasonography T-stage by utilizing deep learning methods in esophageal cancer
Authors: Zhang Tiemei , Chen Zhen , Wang Zhuo-Zhi , Jia Xiaoti , Meng Shuai , Zhang Ke , Zhou Dejun , Zhang Jun , Chen Yong-Zi 
Published: July 2024

AbstractEndoscopic ultrasonography (EUS) is commonly utilized in preoperative staging of esophageal cancer, however with additional pain and cost as well as adverse events. Meanwhile, the accuracy of EUS is highly depend on the training and practice of operators and not universally available. Different operators would lead to high inter-observer variability. Therefore, it is desirable to explore an alternative way to determine preoperative T stage in esophageal cancer. Whether conventional endoscopy possess the ability to predict EUS T stage has never been investigated yet. In current study, with the assistance of Artificial intelligence, we have developed a deep learning model to predict EUS T stage based on 9,714 images collected from 3,333 patients. ResNet-152 pre-trained on the ImageNet dataset was trained with the appropriate transfer learning and fine-tuning strategies on the conventional endoscopic images and their corresponding labels (e.g., T1, T2, T3, T4 and Normal). Meanwhile, augmentation strategies including rotation and flipping were performed to increase the number of images to improve the prediction accuracy. Finally, 4,382 T1, 243 T2, 3,985 T3, 1,102 T4, 14,302 controls images were obtained and split into training dataset, validation dataset and independent testing dataset with the ratio of 4:1:1. Our model could achieve a satisfied performance with an area under the receiver-operating curve (AUC) were 0.9767, 0.9637, 0.9597 and 0.9442 for T1, T2, T3 and T4, respectively in independent testing dataset. In conclusion, conventional gastroscopy combined with artificial intelligence have the great potential to predict EUS T stage.
Testing the applicability of ground motion prediction equations for the Hainaut region (Belgium) using intensity data
Authors: Vanneste Kris , Neefs Ben , Camelbeeck Thierry 
Published: July 2024

AbstractIn regions where strong earthquakes occurred before the deployment of dense seismic and accelerometric networks, intensity datasets can help select appropriate ground motion prediction equations (GMPEs) for seismic hazard studies. This is the case for the Hainaut seismic zone, which was one of the most seismically active zones in and around Belgium during the twentieth century. A recent reassessment of the intensity dataset of the area showed that intensities in this region attenuate much faster with distance than in other parts of northwestern Europe. Unfortunately, this characteristic has not yet been taken into account in current hazard maps for Belgium and northern France. Based on this dataset, we evaluate the goodness of fit of published GMPEs with intensities in Hainaut by means of a ground-motion-to-intensity conversion equation (GMICE) and according to different metrics (Likelihood, Log-likelihood and Euclidean-based Distance Ranking) published in literature. We also introduce a new measure to specifically evaluate the distance trend. Our results show that none of the tested GMPEs convincingly fits the intensity dataset, in particular the fast attenuation with distance. Nevertheless, applying the few GMPEs that show a reasonable fit in seismic hazard computations, we observe a decrease of the influence of the Hainaut seismicity on hazard maps for Belgium and northern France. This result is compatible with the earthquake intensity observations for the last 350 years in this part of Europe.
Designing and evaluating ONCologic EMergencies escape room game for undergraduate nursing students: The ONCEM quasi-experimental pilot study
Authors: Dönmez Ayşe Arikan , Çalik Afra , Terzi Kübra , Kapucu Sevgisun 
Published: July 2024

Abstract
The present pilot study aimed to develop, implement, and evaluate an escape room game for oncologic emergencies. This quasi-experimental pilot study was developed and evaluated by teachers for an oncology nursing course. A total of 76 nursing students ​participated in the study. After completing the game, students were given access to the data collection tools including “Introductory Information Form, Instructional Materials Motivation Survey, Student Satisfaction and Self-Confidence in Learning Scale, Simulation Design Scale by clicking on a link at the end of the game. Findings revealed that the students participating in the escape room game were highly motivated, satisfied, and self-confident with learning, and they were also satisfied with the design of the game. There were statistical differences between the total and sub-dimension scores of the variables examined and the scales used (p < 0,05). The current study on the use of an oncological emergencies-themed escape room as a teaching and learning strategy has provided promising insights. In nursing education, traditionally dominated by theoretical and practical intensive content, current study findings underline the value of this innovative strategy in helping students to improve motivation, satisfaction, and confidence in learning.
Exploring the digital divide in primary education: A comparative study of urban and rural mathematics teachers’ TPACK and attitudes towards technology integration in post-pandemic China
Authors: Li Mao 
Published: July 2024

Abstract
This study investigates disparities in Technological Pedagogical Content Knowledge (TPACK) and attitudes towards digital technology integration among primary mathematics teachers in urban and rural China. In response to the post-pandemic era’s rapid technological advances, this research highlights the digital divide in primary education. A survey of 366 teachers assessed TPACK proficiency, technology access, professional development, and demographic impact factors like age and gender. The instrument, refined through Exploratory Factor Analysis (EFA) and confirmed with Confirmatory Factor Analysis (CFA), provided reliable measures. Data analysis employed descriptive statistics and non-parametric tests (Mann-Whitney U and Kruskal-Wallis) to explore differences across demographics. Findings reveal stark contrasts between urban and rural educators. Urban teachers exhibited higher TPACK proficiency and more favourable attitudes towards technology, likely due to enhanced access to resources and professional development. Conversely, rural teachers, challenged by limited access and support, displayed lower proficiency and less positive attitudes. Furthermore, younger teachers showed greater ease with technology integration than older counterparts, with no significant gender differences. The study’s implications highlight the need for tailored professional development in rural areas and equitable policymaking for technology access across all educational environments. These findings illuminate the urban-rural digital divide in China’s primary education and contribute to the global understanding of technology integration in diverse educational settings. Also, this research enriches the academic discourse on technological equity in education, providing a framework for comparative international studies and policy development.
Biomarker responses in Danio rerio following an acute exposure (96 h) to e-waste leachate
Authors: Rielly A. , Dahms-Verster S. , Greenfield R. 
Published: July 2024

AbstractElectronic waste (e-waste) has been identified as an emerging pollutant and is the fastest growing waste stream at the present time. Significant technological development and modernization within the last decade has led to the rapid accumulation of outdated, broken and unwanted electrical and electronic equipment (EEE). Electronic products mainly consist of a range of metal containing components that, when disposed of improperly, could result in metal constituents leached into the environment and posing a health risk to humans and animals alike. Metal exposure can induce oxidative stress in organisms, which could lead to synergistic, antagonistic and additive effects. The metals found highest in abundance in the simulated e-waste leachate, were nickel (Ni), barium (Ba), zinc (Zn), lithium (Li), iron (Fe), aluminium (Al) and copper (Cu). An acute exposure study was conducted over a 96 h period to determine the potential toxicity of e-waste on the test organism Danio rerio. Biomarker analysis results to assess the biochemical and physiological effects induced by e-waste leachate, showed a statistically significant effect induced on acetylcholinesterase activity, superoxide dismutase, catalase activity, reduced glutathione content, glutathione s-transferase, malondialdehyde and glucose energy available. The Integrated Biomarker Response (IBRv2) analysis revealed a greater biomarker response induced as the exposure concentration of e-waste leachate increased.
Role of environment-driven CSR, green servant leadership, and green dynamic capabilities in firm green innovation: Evidence from manufacturing industry
Authors: Yu Tianlun , Abbas Jawad , Rizvi Riffat Abbas , Najam Hina 
Published: July 2024

AbstractConsidering climate change challenges, firms face increasing pressure to adopt eco-friendly practices to revive the natural climate. This empirical research uses the green servant leadership phenomenon by combining eco-friendly, socially responsible initiatives with sustainable innovation. Green dynamic capabilities are taken as a moderator between green servant leadership and green innovative performance. The data was collected from 375 workers in the manufacturing industry in Pakistan. Using descriptive and inferential statistics through SPSS and SMART PLS 4, we examined how green servant leadership might improve eco-sustainability and the firm’s societal accountability. It is identified that social responsibility initiatives backed by green initiatives positively impact innovative green performance. Moreover, green dynamic capabilities strengthen the link between Environment-focused CSR and green servant leadership. The findings highlighted the need for GDC regulation between environment-focused CSR, green Servant leadership, and green creative performance.