bluuebunny/crossref_metadata_2025_split huggingface dataset:
Semi-supervised lung adenocarcinoma histopathology image classification based on multi-teacher knowledge distillation
Authors: Wang Qixuan , Zhang Yanjun , Lu Jun , Li Congsheng , Zhang Yungang 
Published: August 2024

Abstract

Objective. In this study, we propose a semi-supervised learning (SSL) scheme using a patch-based deep learning (DL) framework to tackle the challenge of high-precision classification of seven lung tumor growth patterns, despite having a small amount of labeled data in whole slide images (WSIs). This scheme aims to enhance generalization ability with limited data and reduce dependence on large amounts of labeled data. It effectively addresses the common challenge of high demand for labeled data in medical image analysis. Approach. To address these challenges, the study employs a SSL approach enhanced by a dynamic confidence threshold mechanism. This mechanism adjusts based on the quantity and quality of pseudo labels generated. This dynamic thresholding mechanism helps avoid the imbalance of pseudo-label categories and the low number of pseudo-labels that may result from a higher fixed threshold. Furthermore, the research introduces a multi-teacher knowledge distillation (MTKD) technique. This technique adaptively weights predictions from multiple teacher models to transfer reliable knowledge and safeguard student models from low-quality teacher predictions. Main results. The framework underwent rigorous training and evaluation using a dataset of 150 WSIs, each representing one of the seven growth patterns. The experimental results demonstrate that the framework is highly accurate in classifying lung tumor growth patterns in histopathology images. Notably, the performance of the framework is comparable to that of fully supervised models and human pathologists. In addition, the framework’s evaluation metrics on a publicly available dataset are higher than those of previous studies, indicating good generalizability. Significance. This research demonstrates that a SSL approach can achieve results comparable to fully supervised models and expert pathologists, thus opening new possibilities for efficient and cost-effective medical images analysis. The implementation of dynamic confidence thresholding and MTKD techniques represents a significant advancement in applying DL to complex medical image analysis tasks. This advancement could lead to faster and more accurate diagnoses, ultimately improving patient outcomes and fostering the overall progress of healthcare technology.
Non-contrasted computed tomography (NCCT) based chronic thromboembolic pulmonary hypertension (CTEPH) automatic diagnosis using cascaded network with multiple instance learning
Authors: Zhao Mayang , Song Liming , Zhu Jiarui , Zhou Ta , Zhang Yuanpeng , Chen Shu-Cheng , Li Haojiang , Cao Di , Jiang Yi-Quan , Ho Waiyin , Cai Jing , Ren Ge 
Published: August 2024

Abstract

Objective. The diagnosis of chronic thromboembolic pulmonary hypertension (CTEPH) is challenging due to nonspecific early symptoms, complex diagnostic processes, and small lesion sizes. This study aims to develop an automatic diagnosis method for CTEPH using non-contrasted computed tomography (NCCT) scans, enabling automated diagnosis without precise lesion annotation. Approach. A novel cascade network (CN) with multiple instance learning (CNMIL) framework was developed to improve the diagnosis of CTEPH. This method uses a CN architecture combining two Resnet-18 CNN networks to progressively distinguish between normal and CTEPH cases. Multiple instance learning (MIL) is employed to treat each 3D CT case as a ‘bag’ of image slices, using attention scoring to identify the most important slices. An attention module helps the model focus on diagnostically relevant regions within each slice. The dataset comprised NCCT scans from 300 subjects, including 117 males and 183 females, with an average age of 52.5 ± 20.9 years, consisting of 132 normal cases and 168 cases of lung diseases, including 88 cases of CTEPH. The CNMIL framework was evaluated using sensitivity, specificity, and the area under the curve (AUC) metrics, and compared with common 3D supervised classification networks and existing CTEPH automatic diagnosis networks. Main results. The CNMIL framework demonstrated high diagnostic performance, achieving an AUC of 0.807, accuracy of 0.833, sensitivity of 0.795, and specificity of 0.849 in distinguishing CTEPH cases. Ablation studies revealed that integrating MIL and the CN significantly enhanced performance, with the model achieving an AUC of 0.978 and perfect sensitivity (1.000) in normal classification. Comparisons with other 3D network architectures confirmed that the integrated model outperformed others, achieving the highest AUC of 0.8419. Significance. The CNMIL network requires no additional scans or annotations, relying solely on NCCT. This approach can improve timely and accurate CTEPH detection, resulting in better patient outcomes.
A nonlinear structural pulse-like seismic response prediction method based on pulse-like identification and decomposition learning
Authors: Liu Bo , Xu Qiang , Chen Jianyun , Wang Yin , Chen Jiansheng , Zhang Tianran 
Published: August 2024

Abstract
Accurate and fast prediction of structural response under seismic action is important for structural performance assessment, however, existing deep learning-based prediction methods do not consider the effect of pulse characteristics of near-fault pulse-like ground motions on structural response. To address the above issues, a new method based on wavelet decomposition and attention mechanism-enhanced decomposition learning, i.e. WD–AttDL, is proposed in this study to predict structural response under pulse-like ground motions. This method innovatively combines a WD-based velocity pulse-identification method with decomposition learning, where decomposed pulses and high-frequency features are used as inputs to the neural-network model, thus simplifying the identification of pulse features for the model. The decomposition learning model integrates several types of neural network components such as convolutional neural network feature extraction submodule, long short-term memory neural network temporal learning submodule and self-attention mechanism submodule. In order to verify the accuracy and validity of the proposed methodology, three sets of case studies were carried out, including elasto-plastic time-history analyses of planar reinforced concrete (RC) frame structures, a three-dimensional RC frame structure, and two types of masonry seismic isolation structures. Compared with existing structural seismic response models, WD–AttDL synergistically integrates the advantages of different modules and thus offers a higher prediction accuracy. In particular, it reduces the peak error of the predicted response, which is important for the evaluation of structural performance. In addition, WD–AttDL has a great potential for application in fast vulnerability and reliability analysis of pulse-like earthquakes in nonlinear structures.
On the time-dependent sliding contact behavior of three-phase polymer matrix smart composites
Authors: Hu Chi , Shen Huoming , Wang Yuxing , Zhang Guoyong , Liu Juan , Zhang Xin 
Published: August 2024

Abstract
Three-phase smart composites consisting of magnetostrictive and piezoelectric reinforcements embedded with a polymer matrix can achieve specific multifunctional properties in response to external stimuli, which are well-suited for the application of sensors, actuators, and electronic devices. The materials exhibit complex behaviors characterized by electro-magneto-viscoelasticity coupling during the contact of these smart structures. This paper proposes a novel hybrid element method for numerically analyzing the frictionless sliding contact problem stemming from the viscoelastic behavior and multiphase interactions of polymer matrix smart composites. The study aims to fully investigate the effects of material properties, sliding velocities, and action time on the contact behavior of materials via the integration of the conjugate gradient method with the discrete convolution-fast Fourier transform algorithm. The analytical viscoelastic frequency response functions are derived by substituting elastic solutions with the time-dependent relaxation modulus. Numerical results show that three-phase polymer matrix smart composites exhibit lower contact pressure and higher surface electric/magnetic potential than three-phase magneto-electro-elastic composites. Sliding velocity and action time strongly influence the distribution of pressure/stress and electric/magnetic potential.
Shear wave velocity in a functionally graded piezoelectric semiconductor plate clamped on a rigid base
Authors: Shukla Shreya , Sahu Sanjeev A 
Published: August 2024

Abstract
This paper investigates the propagation of horizontally polarized shear waves in a piezoelectric semiconductor (PSC) layered structure. The modal consists of a pre-stressed PSC thin plate atop an elastic dielectric half-space joined perfectly at the interface. It is postulated that the material parameters and initial stress exhibit an exponential variation exclusively along the depth. The velocity equation of the considered wave is analytically obtained based on the traction-free boundary conditions. Numerical examples have been employed to examine the influences of several parameters, including semiconducting properties, material gradient index, initial stresses, external biasing electric field, and PSC film thickness, on the characteristics of the wave. Graphs have been generated to visualize the dependency of wave velocity and attenuation on these factors. The wave’s velocity and damping properties are significantly influenced by the thickness and steady state carrier density of the PSC plate. Besides yielding critical results, current findings are instrumental in designing high-frequency SAW devices.
Modes, bounds, and synthesis of optimal electromagnetic scatterers
Authors: Gustafsson Mats 
Published: August 2024

Abstract
This paper presents an optimal synthesis of material distributions in obstacles for maximal extinction, scattering, or absorption. The material synthesis is based on an explicit construction utilizing the current distribution derived from physical bounds excited from the far-field. The bounds are expressed in radiation modes for materials restricted by their resistivity and characteristic modes for materials restricted by the contrast. The results are valid for arbitrary shapes, and analytical expressions are provided for spherical shapes.
Efficient approach for generating vortex sources with arbitrary orbital angular momentum in acoustic experiments
Authors: Hao Zhanlei , Li Songsong , Xu Yadong , Zhu Shan , Chen Huanyang 
Published: August 2024

Abstract
In theoretical research framework of acoustics or optics, how to provide stable and efficient experimental vortex sources with arbitrary orbital angular momentum (OAM) (especially with larger OAM) is a highly challenging research topic. Here, we propose and demonstrate the general principle of two different methods to generate vortex sources with arbitrary OAM, based on the point-sources array and acoustic metamaterials, respectively. Specifically, the general synthetic law is summarized from the analytical perspective behind generating two-dimensional vortex waves using different point sources with different phases, and the design flexibility of acoustic metamaterials is also utilized to provide an ideal solution for generating vortex sources with larger OAM. Besides, we qualitatively and quantitatively determine the OAM of generated vortex waves through simple formulas, and briefly discuss the applicability and stability of two different methods with complementary advantages. The principles of vortex sources generation revealed in this work provide direct theoretical support for the experimental exploration of interactions between multiphysics fields and complex media, with potential applications in vortex fields manipulation and OAM detection.
Effects of Nd-doping on crystal phase, structure and photocatalytic performance of TiO2 powders prepared by sol-gel method
Authors: Si Yuqi , Mamat Mamatrishat , Baikeli Yiliyasi , Feng Guangwen 
Published: August 2024

Abstract
In this work, 0.3–2 mol% neodymium (Nd) doped titanium dioxide (TiO2) powder was prepared by sol–gel method. The XRD showed that the anatase phase occur for the Nd doped TiO2 powders, and the Nd doping suppressed the original rutile phase for the pure TiO2 powder. SEM and TEM revealed that Nd doping reduced the tendency of severe aggregation and increased the specific surface area compare with pure TiO2 powder, and the Gibbs free energy difference did not reach the critical value of the phase transition driving force, while the adjustment of the Ti-O bond length caused by the addition of Nd3+ impeded the transformation of TiO2 to rutile phase. The photocatalytic activity test results for Methylene blue show that the 0.5 mol% Nd doped TiO2 had the best photocatalytic activity with the degradation efficiency of 96.2%.
Coupled awareness-epidemic spreading with the consideration of self-isolation behavior
Authors: Xian Jiajun , Wang Teng , Zhang Wei , Chen Kunwei , Meng Nan , Sun Jiawen , Yang Dan , Liu Ming , Ye Jinlin , Wang Wei 
Published: August 2024

Abstract
Epidemic transmission and the associated awareness diffusion are fundamentally interactive. There has been a burgeoning interest in exploring the coupled epidemic-awareness dynamic. However, current research predominantly focuses on self-protection behavior stimulated by awareness, paying less attention to self-isolation behavior. Given the constraints of government-mandated quarantine measures, spontaneous self-isolation actions assume greater significance in the long-term response to epidemics. In response, we propose a coupled awareness-epidemic spreading model with the consideration of self-isolation behavior and subsequently employ a Micro Markov Chain Approach to analyze the model. Extensive experiments show that self-isolation behavior can effectively raise the epidemic threshold and reduce the final outbreak scale. Notably, in multiplex networks with positive inter-layer correlation, the inhibitory effect is the greatest. Moreover, there exists a metacritical point, only when the awareness diffusion probability exceeds the critical value of this point, the epidemic threshold will increase with the increase of awareness diffusion probability. In addition, the growth of the average degree of the virtual-contact layer can reduce the value of this metacritical point. This research emphasizes the significant role of self-isolation behavior in curbing epidemic transmission, providing valuable perspectives for epidemic prevention through the interplay of awareness and epidemic spreading.
Ion temperature gradient modes modulational stability with kappa-distribution
Authors: Aziz K , Mahmood A , Saqib K , Abbas A 
Published: August 2024

Abstract
We investigated the modulational stability and instability of the ion temperature gradient (ITG) mode in electron-ion plasma. Ions are dynamic species, whereas electrons follow a Kappa distribution. We used the reduction perturbation approach to determine the linear dispersion relation for the fluid under consideration. The nonlinear Schrodinger equation describes nonlinear features such as nonlinear modulational stability or instability in the ITG mode. The product of dissipation and nonlinear coefficients, known as LM, contains both modulational stability and instability in the ion temperature gradient mode. Theoretical results are expanded numerically, showing the influence of various plasma parameters on modulational stability and instability, particularly the superthermality coefficient κ

e
. The current observations may be extended to space and laboratory plasma for modification.
Noether symmetries, conservation laws and geometric properties of the Banados-Teitelboim-Zanelli black hole metric
Authors: Bakhshandeh-Chamazkoti Rohollah 
Published: August 2024

Abstract
This study provides a comprehensive analysis of the Banados-Teitelboim-Zanelli (BTZ) black hole, a significant solution in three-dimensional gravity. We begin with a detailed exploration of the BTZ black hole metric, highlighting its derivation and physical properties, such as its horizon structure and thermodynamic characteristics. The thermodynamics of BTZ black holes, including temperature, entropy, and free energy, are analyzed to understand their stability and behavior. A central focus of this work is the application of Noether symmetry principles to the BTZ black hole. We systematically compute the Noether symmetries of the BTZ metric and discuss their physical implications, including their role in conservation laws and stability analysis. This includes an examination of perturbations and their impact on the stability of the black hole, as well as a detailed geodesic analysis that leverages Noether symmetries to simplify the study of particle motion in this spacetime. Additionally, we investigate the first integrals associated with the BTZ black hole metric, elucidating their significance for the dynamics and conservation laws within this framework. The geometric analysis is further expanded through the Cartan structure equations, providing insight into the intrinsic geometric properties of the BTZ black hole and associated curvature tensors. Overall, this work integrates thermodynamic, symmetric, and geometric analyses to offer a unified understanding of the BTZ black hole’s structure and behavior, contributing to the broader field of black hole physics in lower-dimensional spacetimes.
Solution of one-dimensional Kondo lattice model, ground state calculation
Authors: Karnaukhov Igor N 
Published: August 2024

Abstract
The ground state of the Kondo chain is calculated taking into account the formation of local singlet states of electrons and moments. Singlets are entangled local states of electrons and moments arranged chaotically and varying in time. Two-particle scattering matrix of electrons forming singlets is calculated using the Bethe Ansatz. It is shown that electrons do not hybridize with local moments, and a lattice with a double cell is not formed. In the Kondo insulator a charge gap is calculated for an arbitrary value of the exchange integral. In the case of strong interaction the gap is determined by the single-particle energy of the singlet, for weak interaction—by correlations (the gap is proportional to the square of the exchange integral).
Cylindrical Blume-Capel Nanotube with core/shell structure: compensation temperature and hysteresis loops
Authors: El Kihel K , Salama M , Hachem N , El Bouziani M 
Published: August 2024

Abstract
The critical, compensation and hysteresis behaviors of the Blume-Capel model with mixed spins

S

k

S

=
±
2
,
±
1
,
0

and

σ

i

C

=
±
3

/

2
,
±
1

/

2

, on a cylindrical nanotube with core–shell structure were studied using the mean-field approximation based on the Gibbs-Bogoliubov inequality. The effects of the single-ion anisotropies and the exchange coupling on phase diagrams, magnetizations and hysteresis loops were investigated. The first-order and second-order phase transitions and critical end-point were found, therefore, the system does not give any tricritical point. Furthermore, the model’s results anticipate the presence of the compensation phenomena and multi-cycle hysteresis behaviors.
Puzzle of the cornell potential on the heavy and heavy-light meson spectra
Authors: A Alkathiri Ali , El-Sherif L S , Bakry A M , Ismail Atef , Allosh M 
Published: August 2024

Abstract
We computed the eigenvalues and eigenfunctions via the Cornell potential, approximately, using Numerov approach. The experimental data for the quantum states 3
S
1 were utilized to fit the mass spectra. Results were compared with observed data and the results obtained from other potential functions in the existing literature for the heavy (

c

c
¯

,

b

b
¯

and

b

c
¯

) as well as heavy-light (B, Bs, D and Ds) meson states. The yielded meson spectra based on this potential are matching well with the available experimental data.
Investigation on the optical properties of group-III nitride materials based on fully-connected neural network
Authors: Li Yi , Ge Mei , Wang Meiyu , Deng Honghai , Guo Xinglong , Zhu Youhua 
Published: August 2024

Abstract
In order to accurately simulate the optical properties of nitride optoelectronic devices, such as the reflection spectrum of distributed Bragg reflectors (DRBs), the optical constant is generally considered an important parameter. In this work, the fully-connected neural network is adopted to predict the real and imaginary parts of ordinary dielectric function (DF) of III-nitrides across the full composition range and wide spectral range. The input parameters include Al-component, Ga-component, In-component, and photon energy. The predicted dielectric constant is basically consistent with the results calculated by the analytical model reported in the literature. Then, the band gaps of 6 eV, 3.4 eV and 0.73 eV for AlN, GaN, and InN were determined by using the Tauc formula. The fitted bowing parameters are 0.94 eV, 4.3 eV, and 1.6 eV for AlGaN, InAlN, and InGaN alloys, respectively. Finally, using the predicted dielectric constant, the calculated reflection spectrum of the DBR structures is in agreement with the experimental results in the literature.
Effect of temperature on braking performance of the comb-type disc magnetorheological brake
Authors: Zhu Xinyue , Yang Xiaolong , Cao Zhiqiang 
Published: August 2024

Abstract
To investigate the effect of internal temperature variation of the comb-type disc magnetorheological brake on braking performance, firstly we simulate the temperature field analysis of magnetorheological brake by using the finite element method, and verify the reasonableness of the simulation using experiments. Secondly, the temperature variation of comb magnetorheological brakes during intermittent 5 min braking and continuous braking and the effect of temperature on the braking torque were investigated experimentally. The experimental results show that as the number of braking increases, the maximum temperature inside the brake increases until saturation, while the braking torque decreases. This research helps to enhance the realization of braking stability over the effective operating temperature range.
Investigating novel Mo2X3S (X = Se, Te) materials: probing the influence of chalcogen substitution on electronic, optical, and thermoelectric properties
Authors: Mohamed Abdelhay Salah , Gul Banat , Salman Khan Muhammad , Ahmad Hijaz , Awang Mohd Khalid , Abbas Faheem 
Published: August 2024

Abstract
The excellent thermal performance and adjustable optoelectronic characteristics distinguish the ternary semiconductors. Using the state-of-the-art density functional theory, the optoelectronic, and thermoelectric characteristics of new Mo2X3S (X = Se, Te) ternary chalcogenides are studied. The predicted band gap values with TB-mBJ for Mo2Se3S and Mo2Te3S materials were 1.41 eV and 2.10 eV, respectively. For their possible employment in optoelectronic applications, the components of the complex dielectric function and the vital optical characteristics were calculated and studied. For an increase in the band gap and with the replacement of Se to Te, the peaks in ε
1(ω) shifted to higher energies. Mo2Se3S and Mo2Te3S both show stronger absorption in the UV and visible ranges. Based on the observed peaks in the reflection spectrum, they may used as ultraviolet-reflecting materials with good efficacy. Both Mo2Se3S and Mo2Te3S have positive Seebeck coefficient values, they exhibit p-type conduction. The Mo2Te3S material displays a maximum Seebeck coefficient at about 500 K compared to Mo2Se3S, which leads to a maximum ZT.