bluuebunny/crossref_metadata_2025_split huggingface dataset:
Multi-task contrastive learning for semi-supervised medical image segmentation with multi-scale uncertainty estimation
Authors: Xing Chengcheng , Dong Haoji , Xi Heran , Ma Jiquan , Zhu Jinghua 
Published: August 2023

Abstract

Objective. Automated medical image segmentation is vital for the prevention and treatment of disease. However, medical data commonly exhibit class imbalance in practical applications, which may lead to unclear boundaries of specific classes and make it difficult to effectively segment certain tail classes in the results of semi-supervised medical image segmentation. Approach. We propose a novel multi-task contrastive learning framework for semi-supervised medical image segmentation with multi-scale uncertainty estimation. Specifically, the framework includes a student-teacher model. We introduce global image-level contrastive learning in the encoder to address the class imbalance and local pixel-level contrastive learning in the decoder to achieve intra-class aggregation and inter-class separation. Furthermore, we propose a multi-scale uncertainty-aware consistency loss to reduce noise caused by pseudo-label bias. Main results. Experiments on three public datasets ACDC, LA and LiTs show that our method achieves higher segmentation performance compared with state-of-the-art semi-supervised segmentation methods. Significance. The multi-task contrastive learning in our method facilitates the negative impact of class imbalance and achieves better classification results. The multi-scale uncertainty estimation encourages consistent predictions for the same input under different perturbations, motivating the teacher model to generate high-quality pseudo-labels. Code is available at https://github.com/msctransu/MCSSMU.git.
A Bayesian formulation for perturbed current tomography in tokamaks
Authors: Bohlsen N , Hole M 
Published: August 2023

Abstract
An initial investigation into the application of Bayesian inference to the reconstruction of the spatial distribution of current perturbations in tokamaks from diagnostic signals is presented. Previous work in Bayesian equilibrium current tomography is extended to the case of a complex phasor representation of harmonically time varying current distributions. A forward function to predict the response of magnetic diagnostics is constructed using only electrodynamics and not reduced models of ideal MHD. The extension of this forward function to incorporate a fully kinetic model of the plasma state is suggested. The response of soft x-ray diagnostics, and the motional Stark effect diagnostic to the current perturbations are also predicted and the integration of all diagnostics into a single estimate of the current perturbation is proposed. Simulations with synthetic diagnostics in simple geometry demonstrate that the perturbed current distribution can be reconstructed subject to prior assumptions regarding solution smoothness.
Spatiotemporal corona discharge characteristics of nanoelectrode: array carbon nanotubes
Authors: Li Dingchen , Li Chuan , Li Jiawei , Xiao Menghan , Wang Pengyu , Liu Zhi , Zhang Ming , Yang Yong , Yu Kexun 
Published: August 2023

Abstract
Corona discharge is a widely-used phenomenon that requires a sharp electrode to generate a strong electric field (106 V m−1) at high voltages (typically in the tens of kV). The advent of nanoelectrodes has overcome the technical limitations of traditional electrodes, dramatically improving the density of discharge points and enabling low voltage (several kV) corona discharges with nanometer-sized tips. Consequently, nanoelectrode discharge technology has the potential to revolutionize the miniaturization of plasma equipment in the future. However, research on the discharge characteristics of nanoelectrodes is still relatively sparse. This paper focuses on an array of carbon nanotubes (ACNTs) and proposes a numerical simulation model based on the hybrid hydrodynamics model and ion migration model. The accuracy and efficiency of this model are demonstrated by a high degree of agreement between the results from numerical simulations and experiments. In addition, the corona discharge characteristics of ACNTs are studied and discussed, particularly the spatiotemporal evolution of charged particles near the tip. This paper may provide a method of analysis for optimizing and broadly applying nanoelectrodes.
Optimization of Nb/Al-AlO
x
/Nb Josephson junctions through wafer-scale anodic oxidation: a systematic characterization and performance analysis
Authors: Chen Jian , Wang Zhenyu , Xu Da , Qiao Huan , Li Jinjin , Zhong Qing , Wang Shijian , Zeng Jiusun , Cai Jinhui , Zhang Mingyu , Wang Yeru , Li Xu , Zhong Yuan , Cao Wenhui , Wang Xueshen 
Published: August 2023

Abstract
The Nb/Al-AlO
x
/Nb (SIS) Josephson junction is a crucial component in many types of superconducting devices. However, it can be easily damaged during the plasma fabrication processes. Anodic oxidation is an effective method for protecting SIS junctions by oxidizing Nb and Al from the junction profile. We used a custom wafer-scale anodic oxidation system and a neutral electrolyte to study the oxidation process of Nb films and Nb-Al(-AlO
x
)-Nb junctions. The oxidation process was thoroughly characterized by considering factors such as morphology and electrical properties. Anodization spectroscopy revealed varying oxidation sections from the top Nb layer to the bottom layer, extending across the Al-AlO
x
interlayer. This indicates that a 4 nm Al layer is sufficient to cover the surface of the bottom Nb film. High-resolution transmission electron microscopy and energy dispersive spectroscopy revealed that the Nb2O5 layer produced from the oxidation of the bottom Nb layer penetrated the Al2O3 layer and migrated to the top surface as the oxidation voltage increased. The top Nb layer of the SIS junction was also subjected to oxidation, despite the presence of a protective photoresist. Following the anodic oxidation process, the entire wafer surface was coated with an insulating Nb2O5 film. This film provided protection for the SIS junctions during the subsequent microfabrication process. The fabricated junction array, consisting of 128 junctions, demonstrated uniform electrical properties benefiting from the anodic oxidation process. This systematic analysis will further the research and practical applications of SIS junctions.
Floquet topological superconductors with many Majorana edge modes: topological invariants, entanglement spectrum and bulk-edge correspondence
Authors: Wu Hailing , Wu Shenlin , Zhou Longwen 
Published: August 2023

AbstractOne-dimensional (1D) Floquet topological superconductors possess two types of degenerate Majorana edge modes at zero andπquasienergies, leaving more room for the design of boundary time crystals and quantum computing schemes than their static counterparts. In this work, we discover Floquet superconducting phases with large topological invariants and arbitrarily many Majorana edge modes in periodically driven Kitaev chains (KCs). Topological winding numbers defined for the Floquet operator and Floquet entanglement Hamiltonian are found to generate consistent predictions about the phase diagram, bulk-edge correspondence and numbers of zero andπMajorana edge modes of the system under different driving protocols. The bipartite entanglement entropy further shows non-analytic behaviors around the topological transition point between different Floquet superconducting phases. These general features are demonstrated by investigating the KC with periodically kicked pairing or hopping amplitudes. Our discovery reveals the rich topological phases and many Majorana edge modes that could be brought about by periodic driving fields in 1D superconducting systems. It further introduces a unified description for a class of Floquet topological superconductors from their quasienergy bands and entanglement properties.
The impact of quantized magnetic pressure on the stimulated Brillouin scattering of electromagnetic waves
Authors: Rozina Ch , Maroosh A , Poedts S , Shah H A 
Published: August 2023

Abstract
Within the frame work of Landau quantization theory of Fermi gas, we formulate here the exotic physics of magnetic stimulated Brillouin scattering instability (MSBS) arising due to the nonlinear interaction of high frequency electromagnetic waves (EMWs) with degenerate, strongly magnetized electron-ion plasma. Quantum magneto hydrodynamic model (QMHD) is followed to develop the basic differential equations of quantized magnetosonic waves (QMWs) in the presence of super strong magnetic (SSH) field, whereas Maxwell equations are used to derive the governing differential equation of pump EMWs. The nonlinear interaction of EMWs and QMWs is addressed by employing the phasor matching technique. The obtained dispersion relation of MSBS shows that for a fixed density of fermions, the SSH field alone suppresses the MSBS instability as a function of quantized magneto ion velocity (C

He
) and the Alfven speed (V

A
) via three-wave decay and modulational instabilities. However, for particular condition the MSBS instability is found to increase as a function of SSH field. Next, the analytical results are verified numerically and graphically for soft x-rays in the environment of neutron star. The present MSBS analysis may be critical in neutron stars, radio pulsars and magnetars having super strong magnetic field i.e. even larger than the quantum threshold value i.e, H ∼ 4.4 × 1013
G, or in any application where the enhancement or suppression of SBS may be important.
Analysis of electromagnetic waves reflected by re-entry plasma sheath based on CSO-FDTD
Authors: Zhang Jie , Li Miao , Han Bing 
Published: August 2023

Abstract
A transmission model of terahertz waves in the plasma sheath is established based on a cascaded finite time domain difference method and analyzed the transmission characteristics of electromagnetic waves under the action of an external magnetic field and collision frequency. The flow field around the hypersonic aircraft is simulated and the characteristics of the flow field as the altitude changes of the aircraft are analyzed based on the flow field distribution of the RAM-C (Rapid Attenuation Measurement) vehicle. The results show the transmission characteristics of terahertz waves in plasma that will be affected by flight height, plasma parameters, external magnetic field, and collision frequency. In addition, under the action of an external magnetic field and the different collision frequency, the transmission characteristics of the left-handed terahertz wave will be improved. The application of the magnetic field will introduce an absorption peak in the right-handed terahertz wave, and it will move to the high frequency direction with the increase of the magnetic induction intensity.
On the dynamic mode-III crack in the elastic continuum consisting of sandy properties
Authors: Yadav Ram Prasad , Renu  
Published: August 2023

Abstract
The aim of the present investigation is to come up with a mathematical model for the dynamic mode III crack in an elastic continuum consisting of dry sandy properties. For the analysis of the propagating mode-III crack due to the propagating Love-type wave in an elastic continuum consisting of dry sandy properties, the results for the stress intensity factor (SIF) and crack opening displacement (COD) have been developed in closed form. The complex variable integral transform mathematical methods consisting of the two-sided Fourier integral transform, along with the Weiner-Hopf technique, serve as a salient feature of the adopted mathematical treatment for determining the SIF and COD in the closed form. Moreover, the expressions for the SIF and COD for the limiting static mode-III crack have also been obtained and deduced for special cases of elastic medium. The effects of existing parameters, viz. dry sandiness parameter, depth of crack, crack velocity on the SIF and COD . The effect of physical materials parameters has been shown numerically as well as graphically.
Localized waves and interaction solutions to an integrable variable coefficients Jimbo-Miwa equation
Authors: Liu Jinzhou , Yan Xinying , Jin Meng , Xin Xiangpeng 
Published: August 2023

Abstract
In this paper, the reduced variable coefficients Jimbo-Miwa (vcJM) equation is studied. Firstly, the integrability of the reduced vcJM equation is verified by Painlevé analysis. Based on the Hirota bilinear method and the long wave limit method, the N-soliton solutions, rational and semirational solutions of the vcJM equation are obtained. By choosing different parameters and coefficient functions, some of different kinds of local waves, including of solition, breather wave and lumps, of the equation are obtained. Furthermore, the interaction solutions between different local waves are obtained. The dynamical behavior of the interaction between different local waves is studied by modifying the time parameters and the process is displayed by figures.
511 keV line and primordial black holes from first-order phase transitions
Authors: Tseng Po-Yan , Yeh Yu-Min 
Published: August 2023

Abstract
511 keV gamma-ray excess from the Galactic center is a long
lasting anomaly without satisfying astrophysical explanation.
Hawking evaporation of hypothetical primordial black hole (PBH) with
mass 1.0 × 10-17 ≲ M
PBH/M
⊙ ≲
8.0 × 10-17 and fractional abundance 10-3 ≲
f
PBH ≲ 1.0, gives rise substantial
non-relativistic electrons/positrons annihilating into diphoton,
well reproduces the 511 keV line. However, it is obscure of the
mechanism behind to form PBH with meteoritical mass in the early
Universe. In this work, we investigated the production mechanism of
PBHs through a cosmological first-order phase transition induced by
quartic effective thermal potential via a scalar field in dark
sector. We found the phase transition with vacuum energy,
𝒪(1) ≲ B
1/4/MeV ≲ 𝒪 (100), produces the desired monochromatic PBH mass and
abundance fraction. Correlated signatures of gravitational wave and
extragalactic gamma-ray, respectively coming from phase transition
and black hole evaporation, are within μAres and
AMEGO/e-ASTROGAM/COSI/XGIS-THESUS projected sensitivities. Finally,
we include the PBH mass function from FOPT and found it can not
improve the explanation to 511 keV excess.
New MGCAMB tests of gravity with CosmoMC and Cobaya
Authors: Wang Zhuangfei , Mirpoorian Seyed Hamidreza , Pogosian Levon , Silvestri Alessandra , Zhao Gong-Bo 
Published: August 2023

Abstract
We present a new version of MGCAMB, a patch for the Einstein-Boltzmann solver CAMB for cosmological tests of gravity. New features include a new cubic-spline parameterization allowing for a simultaneous reconstruction of μ, Σ and the dark energy density fraction Ω
X
as functions of redshift, the option to work with a direct implementation of μ, Σ (instead of converting to μ, γ first), along with the option to test models with a scalar field coupled only to dark matter, and the option to include dark energy perturbations when working with w ≠ -1 backgrounds, to restore consistency with CAMB in the GR limit. This version of MGCAMB comes with a Python wrapper to run it directly from the Python interface, an implementation in the latest version of CosmoMC, and can be used with Cobaya.
Constraining an Einstein-Maxwell-dilaton-axion black hole at the Galactic Center with the orbit of the S2 star
Authors: Fernández Fernández Rebeca , Della Monica Riccardo , de Martino Ivan 
Published: August 2023

Abstract
We derive new constraints on the dilaton parameter appearing in the spherically-symmetric
black hole solution of Einstein-Maxwell-dilaton-axion gravity, by studying the geodesic motion of
the S2 star in the Galactic Center. Einstein-Maxwell-dilaton-axion black holes represent a
compelling alternative to the standard black hole paradigm in General Relativity. This theory
emerges from the low energy effective action of the heterotic string theory and has been proven to
predict peculiar observational features from the direct imaging of black hole shadows. At a
fundamental level, Einstein-Maxwell-dilaton-axion includes additional electromagnetic, dilatonic
and axionic fields coupled to the space-time metric. When considering charged non-rotating black
hole solutions, the additional fields endow the metric with one extra parameter b, called
dilaton parameter, that is theoretically bound to 0 < b < M. Using publicly available astrometric
data for S2 we derive an upper bound on b ≲ 12M at 95% confidence level and we
demonstrate that only including the measurement of the relativistic orbital precession for S2 is
sufficient to reduce this bound to b ≲ 1.4M at the same confidence level. Additionally,
using a mock data mimicking future observations of S2 with the GRAVITY interferometer, we show
that improved astrometric precision can help further narrow down the allowed dilaton parameter
range to b ≲ 0.033M after monitoring the S2 orbit for one and a half period.
Transverse-field XY spin chain with the competing long-range interactions: multi-criticality around the XX-symmetric point
Authors: Nishiyama Yoshihiro 
Published: August 2023

Abstract
The transverse-field XY spin chain with competing antiferromagnetic long-range interactions,

J
r

∝
1

/

r
α

(r: distance between spins), and the exponent α was investigated numerically. The main concern is to clarify the character of the transverse-field-driven phase transition for the small-α regime around the XX-symmetric point, η = 0 (η: XY-anisotropy parameter). To cope with the negative-sign problem, we employed the exact-diagonalization method, which enables us to evaluate the fidelity susceptibility χ

F
. Because the fidelity susceptibility does not assume any order parameter after a phase transition, it detects the multi-criticality around the XX-symmetric point in a systematic manner. As a preliminary survey, with η = 0.5 and α = 2 fixed, we made the scaling analysis of χ

F
. The scaling behavior of χ

F
shows that the transverse-field-driven phase transition belongs to the 2D-Ising universality class. Thereby, with the properly crossover-scaled η, the χ

F
data is cast into the crossover scaling formula for the small-α regime. The multi-critical exponents fed into the scaling formula are argued through referring to related studies.
Chicken Manure Disease Recognition Model Based on Improved ResNeXt50
Authors: Chen Xiuzhe , Yang Xiaoxia 
Published: August 2023

Abstract
The feces of sick chickens often show a certain degree of morbidity. It is an effective method to identify sick chickens by deep learning. Concerning the environmental factors of chicken manure shooting that have a great influence, this paper proposes the introduction of a mixed attention mechanism into the ResNeXt50 network model and applies it to the chicken manure data set. While using residual structure learning, the model enhances the perception and learning ability of the input image. The results showed that the overall accuracy of the ResNeXt50-3A model on the test set reached 97.4%, which was 17.3, 1.5, 28.6, and 1.5 percentage points higher than the RegNetY_400MF, Vgg19, ViT (Vision Transformer) and ResNeXt50 models respectively. The ResNeXt50-3A model has high recognition accuracy and can provide support for the accurate identification of diseased chickens in all aspects of chicken breeding, replacing manual detection of diseased chickens.
Optimization of BP Neural Network for Wind Power Output Prediction Based on Particle Swarm Optimization Algorithm
Authors: Liu Kai , Su Hongsheng 
Published: August 2023

Abstract
Because wind power has strong uncertainty and uncontrollability, there are great difficulties in the process of grid connection and power dispatching. The existing prediction models have some shortcomings, such as insufficient precision and poor convergence. In this paper, an improved short-term prediction model is proposed. The correlation coefficient is determined by the grey correlation method, and then the optimal coefficient is calculated by optimizing the backpropagation network using a particle swarm optimization algorithm. Comparing the prediction results of the new model with those of a single BP network and the POS optimization BP network, it can be concluded that the new model is more precise than the other models.
Application of Improved Genetic Algorithm and Ant Colony Algorithm in Multi-objective Path Planning
Authors: Pang Xueting , Chen Chao , Tong Xin , Shi Liangxiong , Liu Xingzhu 
Published: August 2023

Abstract
Due to the shortcomings of GA in path planning, there are too many control variables and it is easy to fall into local areas. We introduce the idea of a gene bank and store the new chromosomes generated each time in the gene bank. The idea of linear regression is proposed to predict the probability of crossover and mutation of the next generation. At the same time, a method of increasing chromosome diversity is proposed, which avoids the problem that it is difficult to set the control variable parameters reasonably and fall into local optimum when the GA is applied in path planning. To overcome the shortcomings of ACO in path planning, an ACO with improved heuristic function and transition probability was proposed, and the method of the real-time environment was given. Through the traveling salesman problem, the improved GA and ACO are combined to apply to path planning. The experimental results show that the fusion of GA and ACO in this paper is superior to ordinary GA and ACO in all aspects of path planning.
Automatic Bridge Detection of SAR Images Based on Interpretable Deep Learning Algorithm
Authors: Li Zhonghao , Chen Lifu , Long Fengqi , Li Zengqi , Jina Haixin 
Published: August 2023

Abstract
As a typical feature target in SAR images, the accurate detection and localization of bridge targets are of important research value for the management of transportation facilities and battlefield reconnaissance. Since most of the current bridge target detection algorithms use horizontal frames, they cannot achieve accurate localization of bridges. There is a large amount of background information in the data set annotation, which is not conducive to the training of the network. In this paper, an in-depth analysis of the interpretable deep learning algorithm is presented to show that the use of rotating detection frames is more beneficial to the automatic detection of targets with large aspect ratios such as bridges. The algorithm framework first performs feature extraction of bridge targets through the Yolov5 network, and then passes the feature maps containing target information into the proposed regression prediction visualization module to obtain detection result maps and heat maps. In the experiments, the SAR images of the Foshan area are used to verify the results, and the advantages of the rotating detection frame in terms of localization and inspection performance are analysed by comparing the IoU and the heat map.