bluuebunny/crossref_metadata_2025_split huggingface dataset:
Extracting weak electromagnetic signals based on RMPSO-SPBSR in virtual anechoic chamber
Authors: Yao Jinjie , Guo Yurong , Bai Jiansheng , Miao Jing , Wang Chenguang 
Published: August 2023

Abstract
To enhance the signal extraction performance at weak noise intensity in virtual anechoic chamber, this study investigates the correlation between the generation conditions of a stochastic resonance (SR) system and its output performance. To achieve optimal resonance effects, an adaptive system called symmetric piecewise bistable SR (SPBSR) is proposed. This system improves its structure by modifying the potential function to facilitate the occurrence of SR. Meanwhile, it combines a regional multi-role strategy and particle swarm optimization algorithm to determine the optimal structural parameters. The adaptive optimization process utilizes update rules that balance global and local optimal solutions, thereby mitigating the tendency to quickly converge to a local optimum. Experimental results demonstrate that the proposed system exhibits excellent performance within a noise intensity range of 0–10 dB, with a correlation coefficient of over 0.75, which can effectively suppress noise interference. In practical signal processing, the system excels at accurately extracting signal characteristics, resulting in improved similarity and smoothness of the detected signal. Both simulation and experimental results validate this algorithm’s strong practical relevance.
Improved cycling performance of silicon-based nanocomposites with pyrolytic polyacrylonitrile for lithium-ion batteries
Authors: Sun Jichang , Li Aohan , Zheng Penglun , Zheng Yun 
Published: August 2023

Abstract
The Si/FeSi2@C composite material offers several advantages due to its unique design. It effectively combines the high capacity and safety features of the Si negative electrode with FeSi2’s stabilizing properties. By incorporating a homogeneous carbon layer, the composite material enhances electrical conductivity and provides structural support, thereby mitigating the detrimental effects of significant volume expansion resulting from repeated insertion and extraction of lithium ions. Furthermore, the composite material contributes to stabilizing the solid-electrolyte interphase (SEI) film, which is a critical factor in battery performance. The improved SEI film stability, combined with the overall enhancement in electronic conductivity, significantly enhances the performance of the negative electrode. Test results demonstrate that the composite, consisting of pyrolyzed polyacrylonitrile and Si/FeSi2 nanoparticles, exhibits excellent electrochemical properties. During the first charging cycle, the composite material achieves a specific capacity of 1280 mAh g−1. Impressively, after 200 cycles, the specific capacity of the composite doubles compared to that of the raw material, indicating a remarkable improvement in cycling stability. These findings highlight the positive impact of rational material design on the performance of the Si/FeSi2@C composites.
ROP-GAN: an image synthesis method for retinopathy of prematurity based on generative adversarial network
Authors: Hou Ning , Shi Jianhua , Ding Xiaoxuan , Nie Chuan , Wang Cuicui , Wan Jiafu 
Published: August 2023

Abstract

Objective. Training data with annotations are scarce in the intelligent diagnosis of retinopathy of prematurity (ROP), and existing typical data augmentation methods cannot generate data with a high degree of diversity. In order to increase the sample size and the generalization ability of the classification model, we propose a method called ROP-GAN for image synthesis of ROP based on a generative adversarial network. Approach. To generate a binary vascular network from color fundus images, we first design an image segmentation model based on U2-Net that can extract multi-scale features without reducing the resolution of the feature map. The vascular network is then fed into an adversarial autoencoder for reconstruction, which increases the diversity of the vascular network diagram. Then, we design an ROP image synthesis algorithm based on a generative adversarial network, in which paired color fundus images and binarized vascular networks are input into the image generation model to train the generator and discriminator, and attention mechanism modules are added to the generator to improve its detail synthesis ability. Main results. Qualitative and quantitative evaluation indicators are applied to evaluate the proposed method, and experiments demonstrate that the proposed method is superior to the existing ROP image synthesis methods, as it can synthesize realistic ROP fundus images. Significance. Our method effectively alleviates the problem of data imbalance in ROP intelligent diagnosis, contributes to the implementation of ROP staging tasks, and lays the foundation for further research. In addition to classification tasks, our synthesized images can facilitate tasks that require large amounts of medical data, such as detecting lesions and segmenting medical images.
Color-guided deformable convolution network for intestinal metaplasia severity classification using endoscopic images
Authors: Li Zheng , Zheng Xiangwei , Mu Yijun , Zhang Mingzhe , Liu Guanqun 
Published: August 2023

Abstract

Objective. Intestinal metaplasia (IM) is a common precancerous condition for gastric cancer, and the risk of developing gastric cancer increases as IM worsens. However, current deep learning-based methods cannot effectively model the complex geometric structure of IM lesions. To accurately diagnose the severity of IM and prevent the occurrence of gastric cancer, we revisit the deformable convolution network (DCN), propose a novel offset generation method based on color features to guide deformable convolution, named color-guided deformable convolutional network (CDCN). Approach. Specifically, we propose a combined strategy of conventional and deep learning methods for IM lesion areas localization and generating offsets. Under the guidance of offsets, the sample locations of convolutional neural network adaptively adjust to extract discriminate features in an irregular way that conforms to the IM shape. Main results. To verify the effectiveness of CDCN, comprehensive experiments are conducted on the self-constructed IM severity dataset. The experimental results show that CDCN outperforms many existing methods and the accuracy has been improved by 5.39% compared to DCN, reaching 84.17%. Significance. To the best of our knowledge, CDCN is the first method to grade the IM severity using endoscopic images, which can significantly enhance the clinical application of endoscopy, achieving more precise diagnoses.
A generalizable new figure of merit for dose optimization in dual energy cone beam CT scanning protocols
Authors: Li Chenguang , Zhou Li , Deng Jun , Wu Hao , Wang Ruoxi , Wang Fei , Yao Kaining , Chen Chen , Niu Tianye , Zhang Yibao 
Published: August 2023

Abstract

Objective. This study proposes and evaluates a new figure of merit (FOMn) for dose optimization of Dual-energy cone-beam CT (DE-CBCT) scanning protocols based on size-dependent modeling of radiation dose and multi-scale image quality. Approach. FOMn was defined using Z-score normalization and was proportional to the dose efficiency providing better multi-scale image quality, including comprehensive contrast-to-noise ratio (CCNR) and electron density (CED) for CatPhan604 inserts of various materials. Acrylic annuluses were combined with CatPhan604 to create four phantom sizes (diameters of the long axis are 200 mm, 270 mm, 350 mm, and 380 mm, respectively). DE-CBCT was decomposed using image-domain iterative methods based on Varian kV-CBCT images acquired using 25 protocols (100 kVp and 140 kVp combined with 5 tube currents). Main results. The accuracy of CED was approximately 1% for all protocols, but degraded monotonically with the increased phantom sizes. Combinations of lower voltage + higher current and higher voltage + lower current were optimal protocols balancing CCNR and dose. The most dose-efficient protocols for CED and CCNR were inconsistent, underlining the necessity of including multi-scale image quality in the evaluation and optimization of DE-CBCT. Pediatric and adult anthropomorphic phantom tests confirmed dose-efficiency of FOMn-recommended protocols. Significance. FOMn is a comprehensive metric that collectively evaluates radiation dose and multi-scale image quality for DE-CBCT. The models and data can also serve as lookup tables, suggesting personalized dose-efficient protocols for specific clinical imaging purposes.
A learnable front-end based efficient channel attention network for heart sound classification
Authors: Liu Aolei , Zhang Sunjie , Wang Zhe , Tang Yiheng , Zhang Xiaoli , Wang Yongxiong 
Published: August 2023

Abstract

Objective. To enhance the accuracy of heart sound classification, this study aims to overcome the limitations of common models which rely on handcrafted feature extraction. These traditional methods may distort or discard crucial pathological information within heart sounds due to their requirement of tedious parameter settings. Approach. We propose a learnable front-end based Efficient Channel Attention Network (ECA-Net) for heart sound classification. This novel approach optimizes the transformation of waveform-to-spectrogram, enabling adaptive feature extraction from heart sound signals without domain knowledge. The features are subsequently fed into an ECA-Net based convolutional recurrent neural network, which emphasizes informative features and suppresses irrelevant information. To address data imbalance, Focal loss is employed in our model. Main results. Using the well-known public PhysioNet challenge 2016 dataset, our method achieved a classification accuracy of 97.77%, outperforming the majority of previous studies and closely rivaling the best model with a difference of just 0.57%. Significance. The learnable front-end facilitates end-to-end training by replacing the conventional heart sound feature extraction module. This provides a novel and efficient approach for heart sound classification research and applications, enhancing the practical utility of end-to-end models in this field.
Structural investigation of ultra-low resistance deeply recessed sidewall ohmic contacts for AlGaN/GaN HEMTs based on Ti/Al/Ti-metallization
Authors: Chen Ding-Yuan , Persson Axel R , Darakchieva Vanya , Persson Per O Å , Chen Jr-Tai , Rorsman Niklas 
Published: August 2023

Abstract
This study presents a novel approach to forming low-resistance ohmic contacts for AlGaN/GaN HEMTs. The optimized contacts exhibit an outstanding contact resistance of approximately 0.15 Ω·mm. This is achieved by firstly recessing the barrier of the heterostructure to a depth beyond the channel. In this way, the channel region is exposed on the sidewall of the recess. The coverage of the Ti/Al/Ti ohmic metalization on the sidewall is ensured through tilting of the sample during evaporation. The annealing process is performed at a low temperature of 550 °C. The approach does not require precise control of the recess etching. Furthermore, the method is directly applicable to most barrier designs in terms of thickness and Al-concentration. The impact of recessed sidewall angle, thickness and ratio of Ti and Al layers, and the annealing procedure are investigated. Structural and chemical analyses of the interface between the ohmic contacts and epi-structure indicate the formation of ohmic contacts by the extraction of nitrogen from the epi-structure. The approach is demonstrated on HEMT-structures with two different barrier designs in terms of Al-concentration and barrier thickness. The study demonstrate large process window in regard to recess depth and duration of the annealing as well as high uniformity of the contact resistance across the samples, rendering the approach highly suitable for industrial production processes.
Modulation of vortex pinning by matrix defects in YBa2Cu3O7 nanocomposite film
Authors: Horide Tomoya , Higashi Kento , Ishimaru Manabu , Okada Tatsunori , Awaji Satoshi , Matsumoto Kaname 
Published: August 2023

Abstract
Nanorods are a very effective pinning center in YBa2Cu3O7 films, and the vortex pinning mechanism should be understood to further improve the critical current density (J
c) in the nanocomposite films. Matrix defects are naturally formed during nanocomposite growth, and in this study the effect of matrix defects on the J
c in the YBa2Cu3O7 films containing nanorods is discussed. YBa2Cu3O7 + BaHfO3 and YBa2Cu3O7 + BaSnO3 films were prepared by varying the laser repetition frequency to control the matrix defects. All the films contained the nanorods. The YBa2Cu3O7 + BaHfO3 film of 2 Hz exhibits high J
c for magnetic field parallel to the c-axis (B//c) due to the nanorods and the isolated random point defects. In the YBa2Cu3O7 + BaHfO3 film of 10 Hz, while the short stacking faults and networked random point defects decreased the J
c for B//c, the short stacking faults improved the J
c for tilted magnetic field. In the YBa2Cu3O7 + BaSnO3 film of 10 Hz, the isolated random point defects improved J
c regardless of the magnetic field direction. While the ab-plane correlated defects are analyzed by the structural observation, the network or isolated nature of the random point defects can be discussed by the normal state resistivity. The matrix defects of YBa2Cu3O7 nanocomposite films should be designed considering the correlated/network/isolated nature which is determined by the morphology and defect concentration.
Improved device-independent randomness expansion rates using two sided randomness
Authors: Bhavsar Rutvij , Ragy Sammy , Colbeck Roger 
Published: August 2023

Abstract
A device-independent randomness expansion (DIRE) protocol aims to take an initial random string and generate a longer one, where the security of the protocol does not rely on knowing the inner workings of the devices used to run it. In order to do so, the protocol tests that the devices violate a Bell inequality and one then needs to bound the amount of extractable randomness in terms of the observed violation. The entropy accumulation theorem lower bounds the extractable randomness of a protocol with many rounds in terms of the single-round von Neumann entropy of any strategy achieving the observed score. Tight bounds on the von Neumann entropy are known for the one-sided randomness (i.e. where the randomness from only one party is used) when using the Clauser–Horne–Shimony–Holt game. Here we investigate the possible improvement that could be gained using the two-sided randomness. We generate upper bounds on this randomness by attempting to find the optimal eavesdropping strategy, providing analytic formulae in two cases. We additionally compute lower bounds that outperform previous ones and can be made arbitrarily tight (at the expense of more computation time). These bounds get close to our upper bounds, and hence we conjecture that our upper bounds are tight. We also consider a modified protocol in which the input randomness is recycled. This modified protocol shows the possibility of rate gains of several orders of magnitude based on recent experimental parameters, making DIRE significantly more practical. It also enables the locality loophole to be closed while expanding randomness in a way that typical spot-checking protocols do not.
Breaking the mass law for broadband sound insulation through strongly nonlinear interactions
Authors: Fang Xin , Li Tao , Hu Bin , Yu Miao , Sheng Peng , Wen Jihong , Cheng Li 
Published: August 2023

Abstract
Sound transmission through panels is governed by the well-known mass law in the mid-frequency range. This paper reveals a possibility of breaking this density-dominant law through strongly nonlinear interaction, while broadening the bandwidth for effective sound insulation. For this purpose, a basic model is established, and corresponding exact analytical methods for bifurcation and stability analyses are proposed. Influences of four typical types of nonlinear interactions on the wave insulation are analytically and numerically investigated. We find that, by introducing strongly nonlinear interactions at appropriate locations, the nonlinear model can not only break the barrier imposed by the mass law, but also entails broadband sound insulation by 2–3 times relative to the optimal linear model. Meanwhile, the sound insulation valley due to the coincident effects can also be eliminated. With bifurcation and effective mass, we clarify that the enhanced wave insulation of the strongly nonlinear models arises from the broader band of super mass induced by strongly nonlinear local resonances, which depends on the bifurcation of periodic solutions. The proposed models and the findings provide a solid basis and new possibilities for wave insulation in complex nonlinear structures and nonlinear acoustic metamaterials.
Performance comparison and analysis of D-type single and dual-core PCF-SPR sensors
Authors: Li Yunqiang , Chen Chuntian , Liu Xin , Gong Aina , Shen Tao 
Published: August 2023

Abstract
Surface plasmon resonance sensors, based on photonic crystal fibers, have demonstrated immense potential in various application fields, owing to their structural design flexibility, operability, and superior sensing capabilities. Despite the potential, the design of photonic crystal fibers with various structures has been a challenging task, due to manufacturing constraints. Thus, this paper aims to explore the design rules of photonic crystal fibers based on surface plasmon resonance, by proposing and designing four photonic crystal fiber sensors with distinct structures. The study investigates the influence of single-core, double-core, and large and small air holes on the sensor’s performance, through theoretical analysis, numerical simulation, data acquisition, and analysis. Through our research, we have discovered that by altering the size of pores surrounding the fiber core, as well as the fiber core’s single-mode and dual-mode configurations, we were able to increase the sensitivity of the sensor from its lowest value of 266 nm RIU−1 to as high as 2066 nm RIU−1, an improvement of nearly eightfold. The findings suggest that the sensor with double-core air hole structure exhibits relatively better performance. This analysis is expected to aid in the design of high-performance photonic crystal fiber-based surface plasmon resonance sensors.
Quantum walk state transfer on a hypercube
Authors: Štefaňák Martin , Skoupý Stanislav 
Published: August 2023

AbstractWe investigate state transfer on a hypercube by means of a quantum walk where the sender and the receiver vertices are marked by a weighted loops. First, we analyze search for a single marked vertex, which can be used for state transfer between arbitrary vertices by switching the weighted loop from the sender to the receiver after one run-time. Next, state transfer between antipodal vertices is considered. We show that one can tune the weight of the loop to achieve state transfer with high fidelity in shorter run-time in comparison to the state transfer with a switch. Finally, we investigate state transfer between vertices of arbitrary distance. It is shown that when the distance between the sender and the receiver is at least 2, the results derived for the antipodes are well applicable. If the sender and the receiver are direct neighbours the evolution follows a slightly different course. Nevertheless, state transfer with high fidelity is achieved in the same run-time.
Polarization characteristics of partially coherent radially and azimuthally polarized beams with vortex phase propagating through atmospheric turbulence
Authors: Xu Qian , Xu Yonggen , Zhao Liang , Liu Wenli , Liu Yongtao 
Published: August 2023

Abstract
Analytical formulas for the normalized spectral Stokes parameters of the partially coherent radially and azimuthally polarized beams with vortex phase (i.e., PCRPV and PCAPV beams) propagating through the turbulent atmosphere are derived. The polarization properties of PCRPV and PCAPV beams in atmospheric turbulence have been studied in detail. Our findings show that different correlation lengths induce nonuniform distribution to degree of polarization (DOP) and the normalized spectral Stokes parameters. And different correlation lengths also cause the polarization singularity splitting. Besides, we find also that the vortex phase will lead to the rotation of distributions of orientation angles and the normalized spectral Stokes parameters of PCRPV and PCAPV beams in turbulence, and the rotation degree will become obvious with increasing topological charge number. It can be found also that larger topological charge number can reduce the speed of polarization singularities destroyed by atmospheric turbulence, meaning that PCRPV and PCAPV beams with a larger topological charge has a stronger ability to resist atmospheric turbulence. Our studies could be important for free-space optical communications and polarization lidar system.
Diversity of exact solutions to the (2+1)-dimensional Ito equation via bilinear neural network method
Authors: Ma Wenbo , Sudao Bilige 
Published: August 2023

Abstract
Recently, searching for exact solutions to nonlinear partial differential equations has gradually become a hot research topic. It is of great scientific research and application value to reveal the law of wave propagation, explain natural phenomena accurately and apply related technologies scientifically. In this paper, bilinear neural network method (BNNM) was employed to obtain some new exact analytical solutions to the (2 + 1)-dimensional Ito equation. Based on the Hirota form of Ito equation, we constructed activation functions f in various forms containing the exp(ξ), sin(ξ), cos(ξ), cosh(ξ) and squares of polynomial functions in multi-layer neurons such as [3-2-2] and [3-2-3] neural network models. The test function f in this work is a new expression. On the other hand, these solutions have not been studied yet. As a result, we obtained several new interaction solutions, such as periodic wave solution, breather solution and bright-dark soliton solution, etc. In addition, the corresponding 3D, density and contour plots of all the solution forms were drawn and their characters and dynamic behaviors were vividly demonstrated.
Controlling the thermal and electric fields in isotropic and anisotropic media
Authors: Raza Muhammad , Rybin Oleg , Ahsan Muhammad , Alonazi Wadi B , Rameen Kiran 
Published: August 2023

Abstract
In this study, we theoretically propose cloaking and concentration devices allowing simultaneous control of electric and thermal fields in spherically inhomogeneous layered medium with isotropic and anisotropic layers. The above combination of layers (isotropic and anisotropic ones) is obtained by the transformation coordinate approach applied to a spherically inhomogeneous layered medium which contains isotropic and anisotropic layers. It is shown that in steady-state conditions, both thermal and electric fields can pass smoothly around the targeted area while preventing any disturbance in the surrounding medium. The constitutive parameters of both fields have been determined analytically. In this work, we have combined two different methodologies to achieve cloaking in ideal state and in homogenized structure for cylindrical and spherical cases. Numerical validation of the obtained solutions using COMSOL software is performed in this study.