bluuebunny/crossref_metadata_2025_split huggingface dataset:
TRAC method in dissipative media—a first analysis in frequency domain and homogeneous media
Authors: Graff Marie , Cullen Mina 
Published: May 2023

Abstract
We propose to explore the time-reversed absorbing condition (TRAC) method in the case of dissipative homogeneous media. In previous work, the TRAC method was derived from the time-reversibility of the (undamped) wave equation and proved to be efficient in both the time-domain and the frequency-domain. Namely, two main utilisations of the TRAC method have been probed: (a) redatuming, i.e. moving virtually the measurements by reconstructing the wavefield and (b) tracking down the location of a possible inclusion inside the domain. In this paper, we focus on the redatuming application and investigate the feasibility of the TRAC method in the case of dissipation. In particular, we will see that performing the classical TRAC method, i.e. ignoring the dissipation, may give satisfactory results, even for larger values of dissipation. An analysis is provided in the frequency-domain and one-space dimension and shows satisfactory updated versions of the TRAC method. Moreover, a systematic error study in two-space dimension is illustrated via numerical examples.
Flow recovery from distal pressure in linearized hemodynamics: an optimal control approach
Authors: Imperiale Sébastien , Manganotti Jessica , Moireau Philippe 
Published: May 2023

Abstract
The goal of this work is to derive a reliable stable and accurate inverse problem strategy for reconstructing cardiac output blood flow entering the ascending aorta from pressure measurements at a distal site of the arterial tree, assumed here to be the descending aorta. We assume that a reduced one-dimensional model of the aorta can be linearized around its steady state, resulting in a wave system with absorbing boundary condition at the outlet. Using this model, we attempt to reconstruct the inlet flow from a pressure measurement at the distal outlet. First, we investigate the observability of the problem and prove that the inversion of the input-output operator for the flow and pressure in the space of time-periodic solutions is ill-posed of degree one. We then develop a variational approach where we minimize the discrepancy between measurements and a simulated state and penalize the error with respect to a periodic state. It is shown that the penalty strategy is convergent and provides an efficient solution for the minimization. Numerical results illustrate the robustness of our approach to noise and the potential of our method to reconstruct inlet flow from real pressure recordings during anesthesia.
Impurity effects on the zeroth pseudo-Landau level in twisted bilayer graphene
Authors: Ji Haijiao , Liu Haiwen , Xie X C 
Published: May 2023

Abstract
We theoretically study the impurity effects on the zeroth pseudo-Landau level (PLL) representation of the flat band in a twisted bilayer graphene (TBG) system. Our research investigates the impact of both short-range and long-range charged impurities on the PLL using the self-consistent Born approximation and random phase approximation. Our findings indicate that short-range impurities have a significant effect on the broadening of the flat band due to impurity scattering. In contrast, the impact of long-range charged impurities on the broadening of the flat band is relatively weak, and the primary impact of the Coulomb interaction is the splitting of the PLL degeneracy when a certain purity condition is satisfied. As a result, spontaneous ferromagnetic flat bands with nonzero Chern numbers emerge. Our work sheds light on the effect of impurities on the quantum Hall plateau transition in TBG systems.
Vortex supersolid in the XY model with tunable vortex fugacity
Authors: Maccari I , Defenu N , Castellani C , Enss T 
Published: May 2023

Abstract
In this paper, we investigate the XY model in the presence of an additional potential term that independently tunes the vortex fugacity favouring their nucleation. By increasing the strength of this term and thereby the vortex chemical potential µ, we observe significant changes in the phase diagram with the emergence of a normal vortex-antivortex lattice as well as a superconducting vortex-antivortex crystal (lattice supersolid) phase. We examine the transition lines between these two phases and the conventional non-crystalline one as a function of both the temperature and the chemical potential. Our findings suggest the possibility of a peculiar tricritical point where second-order, first-order, and infinite-order transition lines meet. We discuss the differences between the present phase diagram and previous results for two-dimensional Coulomb gas models. Our study provides important insights into the behaviour of the modified XY model and opens up new possibilities for investigating the underlying physics of unconventional phase transitions.
A novel whale-based algorithm for optimizing the ANN approach: application to temperature compensation in pressure scanner calibration systems
Authors: Wang Huan , Zeng Qinghua , Zhang Zongyu , Zou Yijun 
Published: May 2023

Abstract
To resolve the nonlinear measured values of pressure scanners with temperature change during pressure measurements, resulting in low accuracy, this paper proposes and develops a new calibration system based on neural networks for pressure scanners. Specifically, we first calibrate the pressure scanner production process, then design the sealing device applicable to the working environment of pressure scanners, and finally install the calibration system of the pressure scanner for calibration experiments to obtain accurate measurement results. In addition, at the algorithmic level, this paper forwards a whale optimization algorithm-based backpropagation neural network method instead of the traditional least squares method to complete the temperature compensation. Both the offline compensation results and the compensated online experimental results exhibit the high measurement accuracy of this temperature compensation method. The full-scale (FS) error is 0.07%, the coefficient of determination (R
2) = 99.27%, with similar results for all channels of the pressure sensor in the temperature environment of −40 °C to 60 °C and absolute pressures ranging from 0 to 1.1 MPa. This result presents a significant reduction in the FS error of 0.25%, R
2 = 91.32% based on the conventional algorithm compensation, and also applies to pressure scanners with wide temperature region, wide range, and high accuracy temperature compensation, which is crucial for their future research of low-cost overall calibration and high accuracy algorithms.
First-principles and machine learning modeling on adsorption of atmospheric gases on two-dimensional Ruddlesden–Popper halide perovskite surface
Authors: Zhang Lei , Li Shenyue , Hu Wenguang 
Published: May 2023

Abstract
The interactions between the atmospheric gases and the halide perovskite materials are receiving attention in these years before the extensive industrial deployment of halide perovskite materials. In this manuscript, we combine first-principles calculation and machine learning techniques to evaluate the interactions between the atmospheric gas molecules and a two-dimensional Ruddlesden–Popper halide perovskite Cs2PbBr4 surface based on the adsorption energies and automatically design advanced molecular descriptors for the target output. The impacts of density functionals are considered while an accurate machine learning model (r = 0.954 and R
2 = 0.951) is obtained based on the XGBRF ensemble algorithm. Importantly, the symbolic regression automatically finds an effective hybrid descriptor that exhibits high correlation with the target output that is comparable with the machine learning model; the symbolic regression-derived descriptor is mathematically simple and chemistry-aware, which complements the debatable ‘black-box’ machine learning model. Both feature importance ranking and symbolic regression indicate the importance of the functional-dependent energy levels of the perovskite systems and the amide/hydroxyl functional groups of the molecules. The present study highlights the viability of combining density functional theory and machine learning techniques to model the low-dimensional perovskite structures under the atmospheric conditions.
Enhanced dehydrogenation properties of MgH2 by the synergetic effects of transition metal carbides and graphene
Authors: Zhu Xueqin , Yang Minjian , Luo Minmin , Wang Yonghong , Li Hong , Ding Juntao , Ma Liqiang 
Published: May 2023

Abstract
Transition metal carbides show remarkable catalysis for MgH2, and the addition of carbon materials can attach excellent cycling stability. In this paper, Mg-doped with transition metal carbides (TiC) and graphene (G) composite (denoted as Mg–TiC–G) is designed to assess the influence of TiC and graphene on the hydrogen storage performance of MgH2. The as-prepared Mg–TiC–G samples showed favorable dehydrogenation kinetics compared to the pristine Mg system. After adding TiC and graphene, the dehydrogenation activation energy of MgH2 decreases from 128.4 to 111.2 kJ mol−1. The peak desorption temperature of MgH2 doped with TiC and graphene is 326.5 °C, which is 26.3 °C lower than the pure Mg. The improved dehydrogenation performance of Mg–TiC–G composites is attributed to synergistic effects between catalysis and confinement.
Autonomous x-ray scattering
Authors: Yager Kevin G , Majewski Pawel W , Noack Marcus M , Fukuto Masafumi 
Published: May 2023

Abstract
Autonomous experimentation (AE) is an emerging paradigm that seeks to automate the entire workflow of an experiment, including—crucially—the decision-making step. Beyond mere automation and efficiency, AE aims to liberate scientists to tackle more challenging and complex problems. We describe our recent progress in the application of this concept at synchrotron x-ray scattering beamlines. We automate the measurement instrument, data analysis, and decision-making, and couple them into an autonomous loop. We exploit Gaussian process modeling to compute a surrogate model and associated uncertainty for the experimental problem, and define an objective function exploiting these. We provide example applications of AE to x-ray scattering, including imaging of samples, exploration of physical spaces through combinatorial methods, and coupling to in situ processing platforms These uses demonstrate how autonomous x-ray scattering can enhance efficiency, and discover new materials.
Homogenization for sub-riemannian Lagrangians
Authors: Sánchez Morgado Héctor 
Published: May 2023

Abstract
We consider Lagrangians that are defined only on the horizontal distribution of a sub-riemannian manifold. The associated Hamiltonian is neither strictly convex nor coercive. We prove a result on homogenization of the Hamilton–Jacobi equation following the approach in Contreras et al (2015 Calc. Var. Partial Differ. Equ.
52 237–52). To establish the result, we need to extend weak KAM and Aubry–Mather theories to the sub-riemannian setting. We obtain a Tonelli theorem to dispend of the Lagrangian dynamics tools used in standard weak KAM theory. In the way towards our main result we observe that, the long time convergence of the Lax-Oleinik semigroup, and the vanishing discount convergence of the discounted value function hold.
The first PET glimpse of a proton FLASH beam
Authors: Abouzahr F , Cesar J P , Crespo P , Gajda M , Hu Z , Kaye W , Klein K , Kuo A S , Majewski S , Mawlawi O , Morozov A , Ojha A , Poenisch F , Polf J C , Proga M , Sahoo N , Seco J , Takaoka T , Tavernier S , Titt U , Wang X , Zhu X R , Lang K 
Published: May 2023

Abstract
We demonstrate the first ever recorded positron-emission tomography (PET) imaging and dosimetry of a FLASH proton beam at the Proton Center of the MD Anderson Cancer Center. Two scintillating LYSO crystal arrays, read out by silicon photomultipliers, were configured with a partial field of view of a cylindrical poly-methyl methacrylate (PMMA) phantom irradiated by a FLASH proton beam. The proton beam had a kinetic energy of 75.8 MeV and an intensity of about 3.5 × 1010 protons that were extracted over 101.5 ms-long spills. The radiation environment was characterized by cadmium–zinc–telluride and plastic scintillator counters. Preliminary results indicate that the PET technology used in our tests can efficiently record FLASH beam events. The instrument yielded informative and quantitative imaging and dosimetry of beam-activated isotopes in a PMMA phantom, as supported by Monte Carlo simulations. These studies open a new PET modality that can lead to improved imaging and monitoring of FLASH proton therapy.
Cancer prediction from few amounts of histology samples through self-attention based multi-routines cross-domains network
Authors: Wang Jianqi , Zhang Quan , Liu Guohua 
Published: May 2023

Abstract
Objective. Rapid and efficient analysis of cancer has become a focus of research. Artificial intelligence can use histopathological data to quickly determine the cancer situation, but still faces challenges. For example, the convolutional network is limited by the local receptive field, human histopathological information is precious and difficult to be collected in large quantities, and cross-domain data is hard to be used to learn histopathological features. In order to alleviate the above questions, we design a novel network, Self-attention based multi-routines cross-domains network (SMC-Net). Approach. Feature analysis module and decoupling analysis module designed are the core of the SMC-Net. The feature analysis module base on multi-subspace self-attention mechanism with pathological feature channel embedding. It in charge of learning the interdependence between pathological features to alleviate the problem that the classical convolution model is difficult to learn the impact of joint features on pathological examination results. The decoupling analysis module base on the designed multi-channel and multi-discriminator architecture. Its function is to decouple the features related to the target task in cross-domain samples so that the model has cross-domain learning ability. Main results. To evaluate the performance of the model more objectively, three datasets are used. Compared with other popular methods, our model achieves better performance without performance imbalance. In this work, a novel network is design. It can use domain-independent data to assist in the learning of target tasks, and can achieve acceptable histopathological diagnosis results even in the absence of data. Significance. The proposed method has higher clinical embedding potential and provides a viewpoint for the combination of deep learning and histopathological examination.
Efficient proton-carbon ions acceleration by the plasma-beat-wave mechanism in the presence of the axial magnetic field
Authors: Mehrangiz Mahsa , Khoshbinfar Soheil 
Published: May 2023

Abstract
It is possible to generate the low-divergence ion bunches through the interaction of equally or slightly different counter-propagating laser pulses. In this paper, in the framework of plasma beat wave, we have numerically simulated the simultaneous acceleration of carbon/hydrogen ion beams. Using a two-dimensional particle-in-cell simulation, we have shown that in an HC plasma mixture with an optimal hydrogen ratio of 1:5, the laser reflectivity coefficient reduces up to about 4.6%. This condition may provide the acceleration of low-divergence H+ and C4+ ions beam. The cut-off energy for protons and C4+ ions are about 27 MeV and 410 MeV, respectively at n
H = 0.2 n
C. The values increase by about 15.6% for protons and 21% for C4+ at n
H = 0.7 n
C. In the presence of an axial magnetic field, the energy absorption arrives at its maximum at the values of Ωs/ω
p = 0.1, where Ωs and ω
p are the gyro-frequency and plasma frequency, respectively. Here, the average kinetic energy of the accelerated ions raises by 17.9% and 7.3% for carbon and proton ions, respectively. Compared to the magnetic field-free case, divergence angles were suppressed at approximately 24.2% and 20.3% for the carbon ions and hydrogen ions, respectively.
AlGaN/GaN superlattice-based multichannel RF transistors for high linearity and reliability: a simplified simulation approach
Authors: Kumar Akhil S , Uren Michael J , Parke Justin , Henry H George , Howell Robert S , Kuball Martin 
Published: May 2023

Abstract
Multichannel RF power amplifiers offer high frequency operation, high current and RF power, combined with excellent linearity. 3D and 2D simulation is used to investigate how changes in device architecture impact both the linearity and off-state reliability, allowing an improved linear design which does not compromise reliability. Linearity is assessed by extraction of

g
m
3

/

g
m

′
′

, and third order intercept (TOI) as a function of gate bias, using a straightforward 2D approximation which is computation time and resource efficient compared to the full 3D simulation normally used for these devices. Off-state reliability is assumed to be linked to dielectric failure, and hence peak electric field as a measure of reliability is evaluated at gate corners and edges using a full 3D simulation. It is found that introducing a channel number-dependent doping in the AlGaN/GaN-based superlattice structure can be used to enable an improved transconductance–linearity. It is also found that there is a strong increase in TOI as gate dielectric thickness or fin width is increased. On the other hand, in order to maintain reliability, increased fin height is found to be essential in order to reduce electric field as dielectric thickness is increased. Finally, a device architecture for improving linearity, power and reduced OFF-state field is suggested.
Performance review of the joints for the ITER poloidal field coils
Authors: Breschi M , Cavallucci L , Adeagbo H , Sedlak K , Bajas H , Vostner A , Ilyin Y 
Published: May 2023

Abstract
For large scale magnets wound with cable-in-conduit conductors, the safe operation of the joints is of paramount importance to guarantee adequate reliability and stability margin of the whole magnet. For this reason, during the R&D activities undertaken for the development of the ITER magnet system, several experimental campaigns were launched to study the AC and DC performance of the joint and limit the risk of thermal runaways at the joints during the tokamak operation. The joint electrical resistance must be limited below specified values to avoid excessive heating generated by the transport current. Moreover, in presence of time-varying fields, different types of losses arise at the joints, which can be associated to their superconducting and resistive parts. The relative importance of these losses depends on the joint manufacturing solution. The aim of this investigation is to analyze the performance at different working conditions of the joints for the connection of the conductors of the poloidal field (PF) coils of the ITER magnet system. This work presents, for the first time, a wide review of the test campaign performed from 2016 to 2021 on the PF joint samples during the three manufacturing phases, namely pre-qualification, qualification and production. The values of electrical resistances and losses under sinusoidal field variations are reported in the paper at different operating conditions, thus building a useful database to assess the joint performances during the machine operation. The data here collected show the impact of the manufacturing techniques on the joint performances and, furthermore, represent a useful tool for the validation of numerical and analytical models of joints.
Augmentation for unmanned aerial vehicle position estimation using MARG and optical flow sensors
Authors: Li Xiang , He Fei , Xu Qing 
Published: May 2023

Abstract
The optical flow sensor can detect the movement of the unmanned aerial vehicle (UAV) on the ground; thus, it is widely used for UAV flight control. The commonly used pinhole model of optical flow sensor describes the optical flow measurement in linear and angular velocities. It is not suitable in the case of discrete-time processing. A novel measurement model for the optical flow sensor is proposed, which directly gives the relationship between the optical flow and the UAV’s translational/angular motions in each sampling period. A data fusion scheme based on cubature transform is also presented, which can augment UAV’s position estimation using optical flow data. The proposed method is proven to be effective through flight tests on UAVs.
Study on a circular surface fitting algorithm
Authors: Lu Zhibing , Qin Yan , Xue Yuqing , Si Zhuang , Li Yanxia , Sun Weiwei 
Published: May 2023

Abstract
Surface fitting techniques are becoming more and more widely used in today’s industry. To make up for the lack of accurate representation of circular holes in circular surfaces in current surface fitting algorithms, this paper improved the original algorithm based on the nonuniform rational B-sample surface fitting by referring to the form of polar coordinates in the step of parameter direction determination to make it more accurate in fitting circular surfaces. Finally, by comparing the traditional method with the improved algorithm in this paper through experimental fitting, the accuracy and practicality of the algorithm can be shown from the results.
Effect of texturing region on friction properties of journal bearings at different rotational speeds
Authors: Wang Suhua , Zhou Zhipeng 
Published: May 2023

Abstract
The effect of texturing area on the friction properties of partially textured bearing at different rotational speeds was investigated theoretically. Four texturing configurations are limited on the bearing surface from the oil film fracture zone of the smooth bearing (200º to 360º) in the rotational direction with different eccentricity ratios. The results show that the friction coefficient of the partially textured bearing can be reduced compared with the smooth bearing. The friction coefficient decreases greater with the increasing texture depth at the fixed rotational speed. When the texturing configuration starts from the oil film fracture zone at the eccentricity ratio of 0.4 or 0.6, the partially textured bearings perform better at different speeds.
Study on “decoupling” of inerter
Authors: Wang Chang 
Published: May 2023

Abstract
The braking device is regarded as the core of the vehicle deceleration, and it also does great help to the stability and reliability of the vehicle. The disc brake is one of the most important brake devices, and its main structure contains a brake disc and a friction block. The working principle is to provide the normal pressure to the friction block through the clamp, and through the friction between the friction block and the brake disc to achieve deceleration and parking. In this process, the vehicle may produce sharp noise, and the unreasonable design may lead to braking instability and noise. Therefore, it is of great engineering value and practical significance to study the dynamic characteristics of disc brakes, add new structures, and put forward the method of system parameter optimization. The main content of this paper is to study the modal coupling in the braking process and optimize it with the mechanical structure with an inerter.