bluuebunny/crossref_metadata_2025_split huggingface dataset:
FlexibleCP: A data augmentation strategy for traffic sign detection
Authors: Shi Jingyi , Rao Huanle , Jing Qinyang , Wen Ziqiang , Jia Gangyong 
Published: September 2024

AbstractIn the field of traffic sign detection, effective data augmentation can improve the model's detection capacity, enabling the model to distinguish and locate traffic signs more precisely and enhancing driving safety. However, due to the small size and low representation of traffic signs in the dataset, standard common data augmentation techniques are not suitable for traffic sign detection. To address this issue, a novel data augmentation strategy called flexible cut and paste (FlexibleCP) is proposed. The overall enhancement approach is shifted from multi‐image fusion to target cropping and pasting. By introducing parameters to control the target pasting ratio and scaling ratio, the diversity of small target data and their size variations are enriched. Additionally, target size and type filters are added to enable targeted enhancement for different sizes and types of targets. This study, evaluates the proposed strategy using two representative traffic sign detection datasets, namely CTSD and GTSDB. The experimental results demonstrate a significant improvement in both detection and recognition performance of the model: on the CTSD dataset, the models trained with FlexibleCP data enhancement achieve 88.9% and 64.5% mAP0.5 and mAP0.5:0.95, respectively, which are 3.5% and 2.5% better than those trained with mosaic data enhancement; on the GTSDB dataset mAP0.5 and mAP0.5:0.95 reached 89.2% and 56.0%, respectively, an improvement of 4.0% and 3.9% over mosaic.
Theoretical wavelet ℓ1-norm from one-point probability density function prediction
Authors: Sreekanth Vilasini Tinnaneri , Codis Sandrine , Barthelemy Alexandre , Starck Jean-Luc 
Published: September 2024

Context. Weak gravitational lensing, which results from the bending of light by matter along the line of sight, is a potent tool for exploring large-scale structures, particularly in quantifying non-Gaussianities. It is a pivotal objective for upcoming surveys. In the realm of current and forthcoming full-sky weak-lensing surveys, convergence maps, which represent a line-of-sight integration of the matter density field up to the source redshift, facilitate field-level inference. This provides an advantageous avenue for cosmological exploration. Traditional two-point statistics fall short of capturing non-Gaussianities, necessitating the use of higher-order statistics to extract this crucial information. Among the various available higher-order statistics, the wavelet ℓ1 -norm has proven its efficiency in inferring cosmology. However, the lack of a robust theoretical framework mandates reliance on simulations, which demand substantial resources and time.
Aims. Our novel approach introduces a theoretical prediction of the wavelet ℓ1-norm for weak-lensing convergence maps that is grounded in the principles of large-deviation theory. This method builds upon recent work and offers a theoretical prescription for an aperture mass one-point probability density function.
Methods. We present for the first time a theoretical prediction of the wavelet ℓ1-norm for convergence maps that is derived from the theoretical prediction of their one-point probability distribution. Additionally, we explored the cosmological dependence of this prediction and validated the results on simulations.
Results. A comparison of our predicted wavelet ℓ1 -norm with simulations demonstrates a high level of accuracy in the weakly nonlinear regime. Moreover, we show its ability to capture cosmological dependence. This paves the way for a more robust and efficient parameter-inference process.
Supervised machine learning on Galactic filaments
Authors: Berthelot L. , Zavagno A. , Artières T. , Dupé F.-X. , Gray M. , Russeil D. , Schisano E. , Arzoumanian D. 
Published: September 2024

Context. Filaments host star formation and are fundamental structures of galaxies. Their diversity, as observed in the interstellar medium, from very low-density structures to very dense hubs, and their complex life cycles make their complete detection challenging over this large diversity range.
Aims. Using 2D H2 column density images obtained as part of the Herschel Hi-GAL survey of the Galactic plane (Gp), we want to detect, simultaneously and using a single model, filaments over a large range of column density and contrast over the whole Gp. In particular, we target low-contrast and low-density structures that are particularly difficult to detect with classical algorithms.
Methods. The whole H2 column density image of the Gp was subdivided into individual patches of 32 × 32 pixels. Following our proof of concept study aimed at exploring the potential of supervised learning for the detection of filaments, we propose an innovative supervised learning method based on adding information by encoding the position of these patches in the Gp. To allow the segmentation of the whole Gp, we introduced a random procedure that preserves the balance within the model training and testing datasets over the Gp plane. Four architectures and six models were tested and compared using different metrics.
Results. For the first time, a segmentation of the whole Gp has been obtained using supervised deep learning. A comparison of the models based on metrics and astrophysical results shows that one of the architectures (PE-UNet-Latent), where the position encoding was done in the latent space gives the best performance to detect filaments over the whole range of density and contrast observed in the Gp. A normalized map of the whole Gp was also produced and reveals the highly filamentary structure of the Gp in all density regimes. We successfully tested the generalization of our best model by applying it to the 2D 12CO COHRS molecular data obtained on a
58.°8 portion (in longitude) of the plane.
Conclusions. We demonstrate the interest of position encoding to allow the detection of filaments over the wide range of density and contrast observed in the Gp. The produced maps (both normalized and segmented) offer a unique opportunity for follow-up studies of the life cycle of Galactic filaments. The promising generalization possibility tested on a molecular dataset of the Gp opens new opportunities for systematic detection of filamentary structures in the big data context available for the Gp.
The young exoplanetary system TOI-4562: Confirming the presence of a third body in the system
Authors: Fermiano V. , Saito R. K. , Ivanov V. D. , Caceres C. , Almeida L. A. , Aires J. , Beamin J. C. , Minniti D. , Ferreira T. , Andrade L. , Borges B. W. , de Almeida L. , Jablonski F. , Schlindwein W. 
Published: September 2024

Context. Young planetary systems represent an opportunity to investigate the early stages of (exo)planetary formation because the gravitational interactions have not yet significantly changed the initial configuration of the system.
Aims. TOI-4562 b is a highly eccentric temperate Jupiter analogue orbiting a young F7V-type star of < 700 Myr in age with an orbital period of Porb ∼ 225 days and an eccentricity of e = 0.76, and is one of the largest known exoplanets to have formed in situ.
Methods. We observed a new transit of TOI-4562 b using the 0.6-m Zeiss telescope at the Pico dos Dias Observatory (OPD/LNA) in Minas Gerais, Brazil, and combine our data with Transiting Exoplanet Survey Satellite (TESS) and archive data, with the aim being to improve the ephemerides of this interesting system.
Results. The O − C diagram for the new ephemeris is consistent with the presence of a giant planet in an outer orbit around TOI-4562. TOI-4562 c is a planet with a mass of M = 5.77 MJup, an orbital period of Porb = 3990 days, and a semi-major axis of a = 5.219 AU.
Conclusions. We report the discovery of TOI-4562 c, the exoplanet with the longest orbital period discovered to date via the transit timing variation (TTV) method. The TOI-4562 system is in the process of violent evolution with intense dynamical changes – judging by its young age and high eccentricity – and is therefore a prime target for studies of formation and evolution of planetary systems.
Endoscopic ultrasonography-guided coil embolization and cyanoacrylate injection versus cyanoacrylate injection alone for gastric varices: a randomized comparative study
Authors: Jhajharia Ashok , Yadav Sumit , Singh Shashank , Ashdhir Prachis , Nijhawan Sandeep 
Published: September 2024

Abstract
Background Bleeding from gastric varices is life-threatening, with significant rebleeding risk despite standard cyanoacrylate glue injection therapy. Our aim was to evaluate the efficacy and safety of endoscopic ultrasonography (EUS)-guided coil embolization with cyanoacrylate injection (Coil+CYA) compared with EUS-guided cyanoacrylate injection alone (CYA) for the treatment of gastric varices.
Methods The study was conducted at a tertiary referral center in India, using a single-blinded, prospective, and parallel-group randomized design. A total of 50 patients were randomly assigned (1 : 1) to Coil+CYA or CYA. The primary outcome was clinical success (i.e. variceal obliteration). Secondary outcomes involved technical success, gastric variceal recurrence during follow-up, rebleeding episodes, reintervention, and survival.
Results Post-intervention, gastric variceal obliteration assessed by EUS was higher in the Coil+CYA group (100% vs. 92.3%; P = 0.49), with both groups achieving 100% technical success. Rebleeding episodes during 0–12 and 12–24 weeks were comparable in the two groups. At 12 weeks, on EUS, variceal reappearance was less common in the Coil+CYA group (12.5% vs. 19.2%; P = 0.70). Significantly fewer reinterventions were needed in the Coil+CYA group (20.8% vs. 53.8%; P = 0.03). The time to reintervention was significantly longer in the Coil+CYA group (P = 0.01), and the survival time was also longer (P = 0.04).
Conclusions EUS-guided coil embolization with cyanoacrylate injection achieved superior clinical success, reducing the need for reintervention and resulting in improved survival compared with cyanoacrylate injection alone.
Specific physiological responses to alkaline carbonate stress in rice (Oryza sativa) seedlings: organic acid metabolism and hormone signalling
Authors: Wang Dan , Xu Miao , Xu Teng-yuan , Lin Xiu-yun , Musazade Elshan , Lu Jing-mei , Yue Wei-jie , Guo Li-quan , Zhang Yu 
Published: September 2024

In recent years, alkaline soda soil has stimulated numerous biological research on plants under carbonate stress. Here, we explored the difference in physiological regulation of rice seedlings between saline (NaCl) and alkaline carbonate (NaHCO3 and Na2CO3) stress. The rice seedlings were treated with 40 mM NaCl, 40 mM NaHCO3 and 20 mM Na2CO3 for 2 h, 12 h, 24 h and 36 h, their physiological characteristics were determined, and organic acid biosynthesis and metabolism and hormone signalling were identified by transcriptome analysis. The results showed that alkaline stress caused greater damage to their photosynthetic and antioxidant systems and led to greater accumulation of organic acid, membrane damage, proline and soluble sugar but a decreased jasmonic acid content compared with NaCl stress. Jasmonate ZIM-Domain (JAZ), the probable indole-3-acetic acid-amido synthetase GH3s, and the protein phosphatase type 2Cs that related to the hormone signalling pathway especially changed under Na2CO3 stress. Further, the organic acid biosynthesis and metabolism process in rice seedlings were modified by both Na2CO3 and NaHCO3 stresses through the glycolate/glyoxylate and pyruvate metabolism pathways. Collectively, this study provides valuable evidence on carbonate-responsive genes and insights into the different molecular mechanisms of saline and alkaline stresses.
Feasibility of loop-gain tuning for general measurement systems inspired by quantum locking for DECIGO
Authors: Ishikawa T , Kawasaki Y , Tsuji K , Shimizu R , Umemura K , Wu B , Iwaguchi S , Michimura Y , Nagano K , Enomoto Y , Komori K , Doki S , Furusawa A , Kawamura S 
Published: September 2024

Abstract
A series of quantum locking theories have been proposed to enhance the quantum-noise-limited target sensitivity of the DECi-hertz Interferometer Gravitational wave Observatory. The quantum locking that uses a square completion optimizes the sensitivity across all frequencies. However, a substantial amount of data-series must be post-processed since the square completion is a form of signal processing technique. This paper approaches the optimal sensitivity across all frequencies from an alternative perspective: by optimizing the frequency dependence of a servo gain in a feedback loop. The optimal servo gain is formulated by comparing the alternative method with the square completion method for the same optical setup. This will be shown in general noise issues extending the framework of the quantum locking. We find that the optimal servo gain forms a non-feasible filter but has certain characteristics. We also find that the noise of the measurement signal deteriorates proportionally to the noise measured in the feedback loop when the servo gain is slightly imperfect.
A unified spectral approach for quasinormal modes of Morris–Thorne wormholes
Authors: Batic Davide , Dutykh Denys 
Published: September 2024

Abstract
In this paper, we undertake a comprehensive examination of quasinormal modes (QNMs) linked to Morris–Thorne, also known as Bronnikov–Ellis wormholes, delving into scalar, electromagnetic, and gravitational perturbations using the spectral method. Our research corrects inaccuracies previously reported in the literature and addresses areas where the Wentzel–Kramers–Brillouin (WKB) approximation proves inadequate. Moreover, we introduce and evaluate a novel spectral technique designed to consolidate recent advancements in formulating QNM boundary conditions at both the wormhole throat and space-like infinity. This innovative approach bridges critical gaps in existing methodologies and enhances the accuracy and applicability of QNM analysis in the study of wormhole physics.
Independent friction-restitution modeling of collisions: application to planar sphere rebound on a massive surface
Authors: Doménech-Carbó Antonio 
Published: September 2024

Abstract
The most widely used impulse-based description of impact events expresses it in terms of the coefficient of restitution (normal and tangential) and friction. This model leads to significant variations of the coefficients of tangential restitution and friction with the impact angle. An alternative formulation is presented based on the idea that friction and restitution can be treated as ‘mechanisms’ operating simultaneously but independently throughout the impact. The resulting independent friction restitution closure describes the impact for both stick and slip regimes using the same set of ‘constant’ coefficients of restitution (normal and tangential) and friction. The model yields theoretical predictions in agreement with reported experimental data including several results considered as ‘anomalous’ in the literature.
Reconstruction of the doping profile in Vlasov–Poisson system
Authors: Lai Ru-Yu , Li Qin , Sun Weiran 
Published: September 2024

Abstract
We study the inverse problem of recovering the doping profile in the stationary Vlasov–Poisson equation, given the knowledge of the incoming and outgoing measurements at the boundary of the domain. This problem arises from identifying impurities in the semiconductor manufacturing. Our result states that, under suitable assumptions, the doping profile can be uniquely determined through an asymptotic formula of the electric field that it generates.
Empirical interatomic potential development and classical molecular dynamics simulation of monolayer group-III monochalcogenides: insights into thermal transport properties
Authors: Karaaslan Yenal 
Published: September 2024

Abstract
This research addresses the lack of comprehensive studies utilizing classical molecular dynamics simulations for monolayer group-III monochalcogenide materials. These materials, including GaS, GaSe, and InSe, have shown promise for diverse applications but lack well-defined empirical interatomic potentials in the literature. This study is concentrated on the development of empirical interatomic potential parameters for these materials using the particle swarm optimization method, filling a gap in the literature regarding classical molecular dynamics simulations. The parameters are optimized based on fundamental physical characteristics such as the lattice constants, bond lengths, phonon dispersions, and the equation of state, obtained from first-principles calculations. The developed potential parameters are then employed to predict lattice thermal conductivity through non-equilibrium classical molecular dynamics simulations, providing insights into the thermal transport properties of these materials.
In-situ construction of novel Sb2(S,Se)3/CdSe S-scheme heterojunction with enhanced photoelectrochemical performance
Authors: Yang Yuanhao , Ma Zhen , Wei Xueling , Sun Qian , Zhang Dekai , Liu Enzhou , Miao Hui 
Published: September 2024

Abstract
Antimony selenosulfide (Sb2(S,Se)3) was considered to have great potential for photoelectrochemical (PEC) water splitting applications due to its excellent chemical stability, good light absorption, abundant reserves and non-toxicity. However, Sb2(S,Se)3 faces some limitations in the field of PEC, such as the serious recombination problem of photogenerated carriers. Therefore effectively restraining its deep-level defects is the crucial for enhancing its PEC properties. In this paper, We successfully fabricated Sb2(S,Se)3/CdSe S-scheme heterojunction via one-step hydrothermal method, which improves its solar absorption capacity, facilitates efficient carrier separation. And, Sb2(S,Se)3/CdSe S-scheme heterojunction can suppress the adverse effects of deep-level defects on the PEC performance of Sb2(S,Se)3. Under simulated solar irradiation, the light current density can reach 4.02 mA cm−2 (33.5 times that of monomeric Sb2(S,Se)3) at 1.23 VRHE, accompanied by low initial voltage and extremely high surface charge injection efficiency. This study is of great significance for the application of Sb2(S,Se)3 in the PEC field.
Study of intricate extraordinary Hall effect and magnetization switching behavior in graded GdFeCo ferrimagnet
Authors: Bhatt Ramesh Chandra , Ye Lin-Xiu , Lin Jia-Hong , Hai Ngo Trong , Wu Jong-Ching , Wu Te-ho 
Published: September 2024

Abstract
This study delves into the unique properties of the GdFeCo Hall bar with a vertical composition gradient. Our exploration includes a detailed analysis of the temperature-dependent extraordinary Hall effect (EHE) response and magnetization-switching behavior. The findings reveal a FeCo-rich state at room temperature, characterized by an asymmetric drop at 20 Oe and a magnetic compensation temperature (T
comp) around 150 K. The presence of triple hysteresis loops at 280 K and 270 K, along with unexpected changes in the EHE resistance difference (ΔRXY
) at temperatures distant from T
comp, hint at complex compositional effects similar to the artificial skyrmion-like Hall effect. The temperature points for zero ΔRXY
values at ±30 kOe and ±4 kOe show a difference of 18 K, suggesting a spin-flop effect at compensation. Detailed analysis near T
comp uncovers multiple loops, indicating coexisting Gd and FeCo sublattices with varied compositions. The magnetization switching experiments demonstrate field-driven switching and a limited role of electrical current in the system. These unique findings enhance our understanding of compositionally controlled ferrimagnets for spintronic applications.
A brief review of microstructure design in transition metal-based magnetocaloric materials
Authors: Gong Yong , Miao Xuefei , Qian Fengjiao , Xu Feng , Caron Luana 
Published: September 2024

Abstract
Magnetic cooling, a solid-state refrigeration technology based on the magnetocaloric effect, has attracted significant attention in space cooling due to its high energy-efficiency and environmental friendliness. Transition metal-based magnetocaloric materials (MCMs) with the merit of low-cost have emerged as promising candidates for efficient magnetic refrigeration applications. This review explores the intricate relationship between microstructure and multiple properties (e.g. magnetocaloric properties, mechanical stability, thermal conductivity, and functional reversibility) of these materials. A variety of microstructural manipulation approaches (e.g. crystallographic texture, precipitates, micropores, atomic-scale defects, size effect, and composites) are examined for their effects on the comprehensive performance of MCMs. We show that microstructure design provides an effective tool to achieve excellent performance in multiple aspects, which may facilitate the commercialization of transition-metal based MCMs.
Bearing RUL prediction and fault diagnosis system based on parallel multi-scale MIMT lightweight model
Authors: Deng Xingchao , Zhu Guanhua , Zhang Qinghua 
Published: September 2024

Abstract
In contemporary industrial production, the significance of safety is increasingly evident, as the degradation and failure of machinery and equipment pose potential safety hazards. Consequently, there is a growing trend toward real-time monitoring, prediction, and diagnosis of industrial equipment to mitigate the unpredictable impacts on life and property safety caused by sudden failures. To address this issue, this paper proposes a real-time degradation anomaly detection system based on parallel multiscale autoencoders, along with a lightweight model for parallel multiscale multi-input multi-task applications in bearing Remaining Useful Life (RUL) prediction and fault diagnosis. Firstly, the multiscale autoencoder method is employed to simulate actual working conditions and reconstruct original vibration signals, thereby establishing intervals for detecting abnormal degradation. The interval [0, µ +3σ] interval is utilized to assess abnormal degradation based on reconstruction errors, with the first Prediction Time determined adaptively. Secondly, a method for constructing dimensionless auxiliary datasets is introduced, which adopts a multi-input format based on deep separable convolution for feature extraction from original vibration signals, kurtosis, and peak values. This approach enhances the prediction and diagnostic performance of the lightweight model. Finally, a multi-task output method that combines clustering and regression is implemented to achieve RUL prediction and fault diagnosis for bearings. The proposed method addresses the limitations of traditional bearing RUL prediction and diagnosis techniques, demonstrating both theoretical innovation and practical engineering applications. Validation on two bearing datasets confirms the effectiveness of the proposed method.
Salt-coated air oxidation nanodiamond surface purification with a photoluminescence spectroscopy quality control
Authors: Savinov S A , Kolomiets T Yu , Bi Dongxue , Sychev V V 
Published: September 2024

Abstract
Emerging fields of quantum technologies and biomedical applications demand pure nanodiamonds (NDs) with well-defined surface chemistry. Therefore, an inexpensive, scalable and eco-friendly ND surface purification technology is required. In this study, we report our method, salt-coated air oxidation (SCAO) thermal annealing, to achieve uniform purification of a ND surface without the loss of diamond material. A photoluminescence (PL) spectroscopy quality control method is proposed to evaluate the degree of purification. The presence of an isoemission point in the set of nitrogen vacancy (NV) center PL spectra, obtained through the photochromic effect, is examined as a surface purity indicator. The ratio of the NV centers in NDs after the SCAO treatment was determined by decomposing the PL spectra using the non-negative matrix factorization technique.