bluuebunny/crossref_metadata_2025_split huggingface dataset:
Imaging in a Rare Case of Neonatal Arterial Tortuosity Syndrome
Authors: Inserra Maria Cristina , Di Mari Alessia , Passaniti Giulia , Cannizzaro Maria Teresa , La Rosa Giuliana , Poli Daniela , Gitto Placido , Patanè Laura , Romeo Placido 
Published: October 2023

AbstractArterial tortuosity syndrome (ATS) is a very rare autosomal recessive disorder that affects the connective tissue. The incidence of ATS is not well known and to date only 106 patients have been described in the literature. ATS affects medium and large size arteries, leading to widespread elongation and intensification of the average vessel tortuousness, responsible of several loops and kinks. Like other connective tissue disorders, ATS can present with joint laxity, hernias, pectus excavatum, scoliosis or other musculoskeletal abnormalities, and ocular defects. Due to the extreme variability of clinical symptoms and the fact that ATS has no curative management, prompt diagnosis is of tremendous importance to prevent disease-associated complications. In this situation, imaging techniques have a central role. In this study, we describe a rare case of a male newborn with tortuosity and lengthening of the main arterial and venous medium and large caliber branches with associated aortic coarctation who passed away prematurely. The finding of aortic coarctation in a newborn with ATS has rarely been described in the literature.
Capturing the interactions in the BaSnF4 ionic conductor: Comparison between a machine-learning potential and a polarizable force field
Authors: Lian Xiliang , Salanne Mathieu 
Published: October 2023

BaSnF4 is a prospective solid state electrolyte for fluoride ion batteries. However, the diffusion mechanism of the fluoride ions remains difficult to study, both in experiments and in simulations. In principle, ab initio molecular dynamics could allow to fill this gap, but this method remains very costly from the computational point of view. Using machine learning potentials is a promising method that can potentially address the accuracy issues of classical empirical potentials while maintaining high efficiency. In this work, we fitted a dipole polarizable ion model and trained machine learning potential for BaSnF4 and made comprehensive comparisons on the ease of training, accuracy and efficiency. We also compared the results with the case of a simpler ionic system (NaF). We show that contrarily to the latter, for BaSnF4 the machine learning potential offers much higher versatility. The current work lays foundations for the investigation of fluoride ion mobility in BaSnF4 and provides insight on the choice of methods for atomistic simulations.
Meaning integration in pseudocoordination
Authors: Kinn Torodd 
Published: October 2023

Abstract
Pseudocoordination in Scandinavian languages looks like VP
coordination but has a number of characteristics which have led some
researchers to regard it as not representing coordination. Research on
pseudocoordination has often focused on grammaticalization of the first
verb. But most researchers have concluded that very few such verbs actually
exhibit any notable degree of grammaticalization. This indicates that
grammaticalization is secondary, and it and calls for an improved
understanding of non-grammaticalized pseudocoordination – in itself and as a
precursor to grammaticalization. This article argues that pseudocoordination
represents VP coordination with additional semantic integration:
facilitation and backgrounding.
The fight metaphor in translation: From patriotism to pragmatism
Authors: Wu Yang 
Published: October 2023

Abstract
The fight metaphors discussed in this article are linguistic expressions of physical conflict, a revolutionary legacy that still lingers in contemporary Chinese political discourse. This article takes a critical cognitive-linguistic approach to fight metaphors in translation, analysing a dataset comprising the Chinese governmental and Communist Party of China’s congressional reports and their official English-language translations from 2004 to 2020. The discussion highlights conceptual metaphor’s representational role and its ideological potential in discourse, and operationalises the English-based metaphor identification procedure (Steen et al. 2010) for Mandarin texts. Drawing on corpus-based evidence, the article argues that fight metaphors in the source texts (STs) legitimise and consolidate Beijing’s dominance of domestic power by generating positive representations and reproducing patriotic ideology. The translations of those metaphors transform Beijing’s image, assertive in the STs, into a non-aggressive one for the international readership. The target texts (TTs) also reproduce favourable representations from the STs to justify China’s unique political system and to satisfy a pragmatic need – that of constructing positive images for the Chinese authority and China internationally.
Impact of air exposure on growth rate and electrical properties of SnO2 thin films by atmospheric pressure spatial atomic layer deposition
Authors: Tran Thi My Hang , Nguyen Ngoc Linh , Mac Trung Kien , Duong Duc Anh , Nguyen Thien Thanh , Duong Anh-Tuan , Bui Hao Van , Nguyen Viet Huong 
Published: October 2023

Abstract
SnO2 thin film is one of the most studied transparent conductive materials that can be deposited using vacuum-free techniques such as atmospheric pressure spatial atomic layer deposition (AP-SALD). This work studies SnO2 thin films prepared from tin(II) acetylacetonate and water vapor, with a particular focus on the impact of air exposure during the AP-SALD process on the growth rate and electrical properties of the films. In-situ resistance measurements and ex-situ Hall effect characterization demonstrated that longer exposure time of the growing film surface to the open air (t
air) at 240 °C led to conductivity degradation, while the film thickness decreases. The theoretical calculations show that −OH and

O

2

dm

(oxygen molecule adsorbed on the five-coordinated Sn atom, also called O2 dimer) are the two most stable surface structures. The formation of

O

2

dm

is shown as the most thermodynamically favorable oxygen-related species on SnO2(110) surface formed when the film is exposed to the open air, giving rise to both the decrease of film thickness (associated with the desorption of −OH surface groups) and the increase of film resistivity versus t
air. The optimized polycrystalline SnO2 sample demonstrated relatively good electrical performance, including an electrical resistivity of 9.3 × 10−3 Ω.cm, carrier density of 9.2 × 1019 cm−3, and Hall mobility of 7.3 cm2 V−1 s−1 at a growth temperature as low as 240 °C. Our findings reveal the critical impact of processing in the open air on the electrical conductivity of the obtained SnO2 films by AP-SALD coating technology.
Improved genetic algorithm for 2D resin flow model optimization in VARTM process
Authors: Liu Meijun , Cheng Liwei , Xu Jiazhong 
Published: October 2023

Abstract
In this study, a combination of block-centered grid modeling and an enhanced genetic algorithm (GA) is introduced with the aim of optimizing the random permeability field within the Vacuum Assisted Resin Transfer Molding (VARTM) infusion model to enhance the accuracy of predicted resin flow distribution. Within the established 2D-VARTM model, random permeability values in the x and y directions are assigned to each grid. The model is then solved using the central difference method in conjunction with the upstream weighting method to predict the resin flow distribution. Subsequently, an improved GA based on heuristic mutation strategies was designed and validated. This algorithm employs the discrepancy between model predictions and actual sampling results as its fitness function and integrates heuristic strategies for iterative optimization. Simulation results revealed a significant improvement in the predictive accuracy of the model, with a jump from an initial 87.49%–97.19%. In practical applications, the predictive accuracy of the model reached 95.25%. This research offers an effective optimization approach for VARTM models and underscores the potential applicability of the enhanced GA in related fields.
High photoresponsivity MoS2 phototransistor through enhanced hole trapping HfO2 gate dielectric
Authors: Long Pei-Xuan , Lai Yung-Yu , Kang Pei-Hao , Chuang Chi-Huang , Cheng Yuh-Jen 
Published: October 2023

Abstract
Phototransistor using 2D semiconductor as the channel material has shown promising potential for high sensitivity photo detection. The high photoresponsivity is often attributed to the photogating effect, where photo excited holes are trapped at the gate dielectric interface that provides additional gate electric field to enhance channel charge carrier density. Gate dielectric material and its deposition processing conditions can have great effect on the interface states. Here, we use HfO2 gate dielectric with proper thermal annealing to demonstrate a high photoresponsivity MoS2 phototransistor. When HfO2 is annealed in H2 atmosphere, the photoresponsivity is enhanced by an order of magnitude as compared with that of a phototransistor using HfO2 without annealing or annealed in Ar atmosphere. The enhancement is attributed to the hole trapping states introduced at HfO2 interface through H2 annealing process, which greatly enhances photogating effect. The phototransistor exhibits a very large photoresponsivity of 1.1 × 107 A W−1 and photogain of 3.3 × 107 under low light illumination intensity. This study provides a processing technique to fabricate highly sensitive phototransistor for low optical power detection.
Implications of fitting a two-compartment model in single-shell diffusion MRI
Authors: Chad Jordan A , Sochen Nir , Chen J Jean , Pasternak Ofer 
Published: October 2023

Abstract
It is becoming increasingly common for studies to fit single-shell diffusion MRI data to a two-compartment model, which comprises a hindered cellular compartment and a freely diffusing isotropic compartment. These studies consistently find that the fraction of the isotropic compartment (f) is sensitive to white matter (WM) conditions and pathologies, although the actual biological source of changes in f has not been validated. In this work we put aside the biological interpretation of f and study the sensitivity implications of fitting single-shell data to a two-compartment model. We identify a nonlinear transformation between the one-compartment model (diffusion tensor imaging, DTI) and a two-compartment model in which the mean diffusivities of both compartments are effectively fixed. While the analytic relationship implies that fitting this two-compartment model does not offer any more information than DTI, it explains why metrics derived from a two-compartment model can exhibit enhanced sensitivity over DTI to certain types of WM processes, such as age-related WM differences. The sensitivity enhancement should not be viewed as a substitute for acquiring multi-shell data. Rather, the results of this study provide insight into the consequences of choosing a two-compartment model when only single-shell data is available.
Superconductor-ferromagnet hybrids for non-reciprocal electronics and detectors
Authors: Geng Zhuoran , Hijano Alberto , Ilić Stefan , Ilyn Maxim , Maasilta Ilari , Monfardini Alessandro , Spies Maria , Strambini Elia , Virtanen Pauli , Calvo Martino , González-Orellána Carmen , Helenius Ari P , Khorshidian Sara , de Araujo Clodoaldo I Levartoski , Levy-Bertrand Florence , Rogero Celia , Giazotto Francesco , Bergeret F Sebastián , Heikkilä Tero T 
Published: October 2023

AbstractWe review the use of hybrid thin films composed of superconductors and ferromagnets for creating non-reciprocal electronic components and self-biased detectors of electromagnetic radiation. We begin by introducing the theory behind these effects, as well as discussing various potential materials that can be used in the fabrication of these components. We then proceed with a detailed discussion on the fabrication and characterization of Al/EuS/Cu and EuS/Al/Co-based detectors, along with their noise analysis. Additionally, we suggest some approaches for multiplexing such self-biased detectors.
Noise suppression by differential detection of simultaneous electromagnetically induced transparency and absorption in counterpropagating bichromatic light
Authors: Li Qinglin , Yun Peter , Yang Tenghui , Hao Qiang , Zhang Shougang , Gu Sihong 
Published: October 2023

Abstract
Well-established electromagnetically induced transparency (EIT) and absorption (EIA) have been applied to various applications including quantum computing, light storage, and precision measurement. Here, we propose and implement a differential detection scheme based on coexisting EIT and EIA signals in a double-Λ system with counterpropagating bichromatic laser fields, in which a differential coherent population trapping (diff-CPT) signal is extracted with a desired enhanced amplitude and highly suppressed common-mode noise. Compared to that of either EIT or EIA, the observed signal-to-noise ratio of the proposed method’s diff-CPT signal improved by one order of magnitude, which would benefit the implementation of high-performance CPT clocks. This technique may also be applied to magnetometers and precision spectroscopy.
Semiclassical theory of frequency combs generated by parametric modulation of optical microresonators
Authors: Sumetsky M 
Published: October 2023

Abstract
An optical microresonator, which parameters are periodically modulated in time, can generate optical frequency comb (OFC) spectral resonances equally spaced by the modulation frequency. Significant recent progress in realization of OFC generators based on the modulation of microresonator parameters boosted interest to their further experimental development and theoretical understanding of underlying phenomena. However, most of theoretical approaches developed to date were based on the lumped parameter models which unable to evaluate, analyse, and optimize the effect of spatial distribution of modulation inside microresonators. Here we develop the multi-quantum semiclassical theory of parametrically excited OFCs which solves these problems. As an application, we compare OFCs which are resonantly or adiabatically excited in a racetrack microresonator (RTM) and a Surface Nanoscale Axial Photonics (SNAP) bottle microresonator (SBM). The principal difference between these two types of microresonators consists in much slower propagation speed of whispering gallery modes along the SBM axis compared to the speed of modes propagating along the RTM waveguide axis. We show that, due to this difference, similar OFCs can be generated by an SBM with a much smaller size compared to that of the RTM. Based on the developed theory, we analytically express the OFC spectrum of microresonators through the spatial distribution of modulated parameters and optimize this distribution to arrive at the strongest OFCs generated with minimum power consumption.
Gauss-Bonnet Dark Energy and the speed of gravitational waves
Authors: Terente Díaz José Jaime , Dimopoulos Konstantinos , Karčiauskas Mindaugas , Racioppi Antonio 
Published: October 2023

Abstract
Gauss-Bonnet Dark Energy has been a popular model to explain
the accelerated expansion of the Universe. Quite generically it also
predicts the speed of gravitational waves c
GW to be different
from the speed of light. This fact alone led some authors to exclude
such models in view of the new tight observational constraints on
c
GW. However, the behaviour of c
GW depends on the choice of
the Gauss-Bonnet (GB) coupling function. It is possible to construct
models where c
GW is always equal to the speed of light. More generally,
c
GW is a time dependent function with instances where both speeds
coincide. Nevertheless, we observe that the bound on c
GW excludes
scenarios where the GB term directly affects the expansion of the
Universe, even if the constraint on the variation of the coupling
function does not appear to be strong. We perform the dynamical systems
analysis to see if the expansion of the Universe could be affected
indirectly by modulating the behaviour of the scalar field, which
modulates the GB coupling. It is shown that either the bounds on c
GW
are violated by many orders of magnitude, or it might be very difficult
to find models that are consistent with other cosmological observations.
Harvesting energy driven by Comisso-Asenjo process from Kerr-MOG black holes
Authors: Khodadi Mohsen , Mota David F. , Sheykhi Ahmad 
Published: October 2023

Abstract
Magnetic reconnection is a process that plays a critical role in
plasma astrophysics by converting magnetic energy into plasma
particle energy. Recently, Comisso and Asenjo demonstrated that
rapid magnetic reconnection within a black hole's ergosphere can
efficiently extract energy from a rotating black hole. In this
paper, by considering a Kerr black hole in the MOdified gravity
(MOG) framework, we investigate the impact of the MOG parameter
α on the rotational energy extraction via the
Comisso-Asenjo process (CAP). To model energy extraction from supermassive black holes located in the center of galaxies, we set the value of α within the range inferred from the recent observation of Sgr A* by the Event Horizon Telescope (EHT). Our
results indicate that the Kerr-MOG black hole is a more efficient
host for CAP-based rotational energy extraction compared to the
Kerr black hole, since it amplifies the power of energy extraction
and efficiency of the plasma energization process. We show that,
from the energy extraction viewpoint, the CAP is more efficient
than the Blandford-Znajek process (BZP). The latter is another
magnetic field-based energy extraction model which is widely
believed to be an engine for powering the high-energy
astrophysics jets emerging from the supermassive black holes at
active galactic nuclei. In particular, we show that the ratio of
the energy extraction power of CAP to BZP in the presence of the
MOG parameter is greater than that of the Kerr black hole. Our
results promise this phenomenological message that the
MOG-induced correction on the Kerr black hole background plays an
important role in favor of energy extraction via the CAP.
Formation of trapped vacuum bubbles during inflation, and consequences for PBH scenarios
Authors: Escrivà Albert , Atal Vicente , Garriga Jaume 
Published: October 2023

Abstract
A class of inflationary scenarios for primordial black hole (PBH) formation include a small barrier in the slope of the potential. There, the inflaton slows down, generating an enhancement of primordial perturbations. Moreover, the background solution overcomes the barrier at a very low speed, and large backward quantum fluctuations can prevent certain regions from overshooting the barrier. This leads to localized bubbles where the field remains “trapped” behind the barrier. In such models, therefore, we have two distinct channels for PBH production: the standard adiabatic density perturbation channel and the bubble channel. Here, we perform numerical simulations of bubble formation, addressing the issues of initial conditions, critical amplitude and bubble expansion. Further, we explore the scaling behaviour of the co-moving size of bubbles with the initial amplitude of the field fluctuation. We find that for small to moderate non-Gaussianity f
NL ≲ 2.6, the threshold for the formation of vacuum bubbles agrees with previous analytical estimates [1] to 5% accuracy or so. We also show that the mass distribution for the two channels is different, leading to a slightly broader range of PBH masses when both contributions are comparable. The bubble channel is subdominant for small f
NL, and becomes dominant for f
NL ≳ 2.6. We find that the mass of PBHs in the bubble channel is determined by an adiabatic overdensity surrounding the bubble at the end of inflation. Remarkably, the profile of this overdensity turns out to be of type-II. This represents a first clear example showing that overdensities of type-II can be dominant in comparison with the standard type-I. We also comment on exponential tails and on the fact that in models with local type non-Gaussianity (such as the one considered here), the occurrence of alternative channels can easily be inferred from unitarity considerations.
Dam UAV Image Stitching Technology Studies Based on Weak Texture
Authors: Liu Si Min , Zhou Shuai , Jiang Kun Hong , Li Xiang , Peng Zhang Jun , Liu Zhi Gui , Li Li 
Published: October 2023

Abstract
Extraction of image feature point pairs is an important step in the image alignment process. In this paper, we propose a grid-based adaptive threshold feature detection method for weakly textured images using a single threshold extraction algorithm that cannot propose uniformly distributed feature points. Finally, the designed experiments show that the feature points extracted by this method have a lower dispersion than the traditional KAZE algorithm by 70% and a higher alignment accuracy than the traditional KAZE algorithm by 10%.
High-resolution remote sensing image land cover classification based on EAR-HRNetV2
Authors: Zhu Wanling , Jia Yuan 
Published: October 2023

Abstract
The application of land cover classification is very extensive, it can be used in land resources management, urban planning, agricultural and other fields. The multi-scale variation of targets in high-resolution remote sensing images leads to low accuracy in land cover classification tasks. In response to this problem, an improved semantic segmentation model named EAR-HRNetV2 is proposed based on HRNetV2. Firstly, the attention mechanism is added to the Bottleneck residual and Basic residual modules to obtain more efficient features. Then, the atrous spatial pyramid pooling is added to the model. And it is modified to cope with the gridding issue caused by the dilation convolution. Finally, the refinement module is used to combine features from different stages and further extract semantic features. The experiments show that on the WHDLD public dataset, compared with five semantic segmentation models, the EAR-HRNetV2 model is effective with Kappa coefficient, F1-score, overall accuracy, and mean intersection over union reaching 77.85%, 73.00%, 87.92%, and 60.28%. Compared with HRNetV2, the mean intersection over union of EAR-HRNet increases by 2.93 percentage points, the F1-score increases by 2.67 percentage points, the Kappa coefficient increases by 2.37 percentage points, and the overall accuracy increases by 1.19 percentage points. EAR-HRNetV2 network provides a feasible solution for the land cover classification.
A network traffic identification method based on AutoEncoder - a feature selection algorithm
Authors: Yang Tao , Jiang Rui , Deng HongLi , Tang XiaoMei 
Published: October 2023

Abstract
Traffic identification methods consider a large number of traffic features, resulting in low identification efficiency. To address the efficiency problem of traffic recognition, this paper proposes an efficient network traffic recognition method, AutoEncoder-based traffic recognition (AE-NTI). The method first preprocesses the original dataset and converts it into a two-dimensional grayscale image. Then, feature selection is performed by an improved feature selection algorithm based on AutoEncoder. The algorithm consists of a feature scorer, which globally scores all features, and a feature selector, which selects the highest scoring features to reconstruct the original data. Finally, the convolutional neural network structure is adjusted so that the network traffic can be identified. The experimental results show that the method has significantly improved in recognition accuracy and model fitting speed.