bluuebunny/crossref_metadata_2025_split huggingface dataset:
A method for extracting and screening main feature points based on salient geometric characteristics and NAD features
Authors: Wang Ziyang , Ren Bingyin , Dai Yong 
Published: August 2024

Abstract
Point cloud alignment is an important task in the field of industrial automation and computer vision recognition. Aiming at the lack of robustness of traditional alignment algorithms in the face of cylindrical objects such as motors or highly symmetric objects, which in turn is prone to poor alignment accuracy or even alignment failure, a method of extracting and screening main feature points based on salient geometric properties is proposed to provide high-precision inputs for point cloud alignment and to improve the position estimation accuracy of symmetric targets. The salient geometric planes and curved surfaces in the target are utilized as the basis of feature point selection to extract more robust main feature points; and different feature descriptors are adopted to describe the feature points based on the target characteristics, which greatly preserves the original main contour and geometric information. A local feature descriptor normalized angle descriptor is designed based on the normal vector, normal angle and Euclidean distance of the point cloud, which is able to effectively remove the incorrect correspondences due to symmetry and feature similarity. Finally, the algorithm for obtaining the global maximum consensus set (GROR) based on the node and edge reliability of the correspondence graph is used to complete the coarse registration, and the iterative closest point algorithm is utilized to complete the fine registration. Experimental results on motor point clouds taken from different viewpoints show that the proposed registration strategy is visually and numerically superior to existing state-of-the-art methods, especially when there is only a single-frame point cloud of the target.
A fast forward-looking super-resolution imaging method on a high-speed platform
Authors: Wang Lequn , Wang Wei , Shao Xuehui , Hu Ziying 
Published: August 2024

Abstract
Radar forward-looking imaging has raised many concerns in the civilian field. However, when employing forward-looking imaging methods on a high-speed platform, traditional Doppler compensation methods can result in significant compensation errors and exceed the Doppler compensation boundary. At the same time, the forward-looking geometric configuration results in the mutual coupling of range and Doppler information and the corresponding Doppler convolution matrix needs to be constructed per range cell. In addition, the large matrix dimensions of the convolution matrix result in enormous computational complexity. This paper proposes a fast super-resolution method based on high-speed platform Doppler compensation and a low-rank approximation batch processing (LRA-Batch) framework. First, the Doppler compensation matrix for high-speed platforms to eliminate Doppler centroid spatial variations in the range direction is constructed. Then, the Doppler convolution matrix only needs to be constructed once after compensation. The forward-looking imaging model under high-speed platforms has been improved through the above-mentioned method. Next, the sparse reconstruction optimization problem corresponding to the forward-looking super-resolution imaging model is reformulated into the matrix form, and the matrix dimension is reduced through low-rank approximation. Subsequently, the 2D echo data can be processed directly, avoiding the high computational complexity associated with line-by-line processing. The relevant simulation experiments to evaluate the performance of the proposed method have been designed. Simulation results prove that the proposed LRA-Batch method can obtain effective reconstruction results under low operational complexity.
Experimental study on plasma characteristics in the extraction region of a high-power RF negative ion source based on electrostatic probe
Authors: Peng Xufeng , Xu Yongjian , Xie Yahong , Wei Jianglong , Li Yufan , Yang Yuwen , Liu Bo , Xie Junwei , Wu Bin 
Published: August 2024

Abstract
The plasma characteristics of the extraction region in high-power RF negative ion source have a significant impact on the production and extraction of negative hydrogen ions. This study utilized electrostatic probe to investigate the effect of RF power, source pressure, magnetic filter field and bias voltage on the plasma parameters of the extraction region (without cesium), and also studied the variation of plasma parameters with position and time. The results indicate that as RF power increases, the plasma density in the extraction region significantly rises, but it also leads to an increase in the electron temperature (

T

e

) of the extraction region (which increases the loss of negative hydrogen ions); increasing the source pressure can effectively increase the electron density (

N

e

) in the extraction region and reduce

T

e

as expected; increasing the magnetic filter field can effectively reduce the

T

e

in the extraction region, but after the plasma grid current exceeds 1900 A, the change in

T

e

is not significant; although increasement of the bias voltage can effectively suppress the

N

e

in the extraction region, it causes

T

e

to rise; moreover, the distribution of plasma parameters in the extraction region is relatively uniform; in addition, the variation of plasma parameters with time is not obvious. These findings not only deepen the understanding of the physical mechanisms of plasma behavior in the extraction region of negative ion sources, but also provide important theoretical and experimental bases for the optimization of high-power RF negative ion sources.
Numerical investigation of vacuum ultra-violet emission in Ar/O2 inductively coupled plasmas
Authors: Osca Engelbrecht Michel , Jenderny Jonathan , Hylla Henrik , Filla Dominik , Awakowicz Peter , Korolov Ihor , Ridgers Christopher P , Gibson Andrew R 
Published: August 2024

Abstract
Controlling fluxes of vacuum ultraviolet (VUV) radiation is important in a number of industrial and biomedical applications of low pressure plasma sources because, depending on the process, VUV radiation may be desired, required to a certain degree, or unwanted. In this work, the emission of VUV radiation from O atoms is investigated in low-pressure Ar/O2 inductively coupled plasmas via numerical simulations. For this purpose, a self-consistent Ar/O2 plasma-chemical reaction scheme has been implemented in a zero dimensional plasma chemical kinetics model and is used to investigate VUV emission from excited O atoms (3s 5S

2
0

and 3s 3S

1
0

) at 130 and 135 nm. The model is extensively compared with experimental measurements of absolute VUV emission intensities, electron densities and Ar excited state densities. In addition, oxygen VUV emission intensities are investigated as a function of pressure, Ar/O2 mixture, and power deposition and the dominant reaction pathways leading to oxygen VUV emission are identified and described. In general terms, absolute oxygen VUV emission intensities increase with power and oxygen fraction over the ranges investigated and peak emission intensities are found for pressures between 5–50 Pa. The emission is dominated by the 130 nm resonance line from the decay of the O(3s 3S

1
0

) state to the ground state. Besides, at low pressure (0.3–1 Pa), the flux of oxygen VUV photons to surfaces is much lower than that of positive ions, whereas oxygen VUV fluxes dominate at higher pressure,

≳

5–50 Pa depending on O2 fraction. Finally, oxygen atom fluxes to surfaces are, in general, larger than those of VUV photons for the parameter space investigated.
Unveiling correlated two-dimensional topological insulators through fermionic tensor network states—classification, edge theories and variational wavefunctions
Authors: Xu Chao , Ma Yixin , Jiang Shenghan 
Published: August 2024

Abstract
The study of topological band insulators has revealed fascinating phases characterized by band topology indices and anomalous boundary modes protected by global symmetries. In strongly correlated systems, where the traditional notion of electronic bands becomes obsolete, it has been established that topological insulator phases persist as stable phases, separate from the trivial insulators. However, due to the inability to express the ground states of such systems as Slater determinants, the formulation of generic variational wave functions for numerical simulations is highly desirable. In this paper, we tackle this challenge for two-dimensional topological insulators by developing a comprehensive framework for fermionic tensor network states. Starting from simple assumptions, we obtain possible sets of tensor equations for any given symmetry group, capturing consistent relations governing symmetry transformation rules on tensor legs. We then examine the connection between these tensor equations and non-chiral topological insulators by constructing edge theories and extracting quantum anomaly data from each set of tensor equations. By exhaustively exploring all possible sets of equations, we achieve a systematic classification of non-chiral topological insulator phases. Imposing the solutions of a given set of equations onto local tensors, we obtain generic variational wavefunctions for the corresponding topological insulator phases. Our methodology provides an important step toward simulating topological insulators in strongly correlated systems. We discuss the limitations and potential generalizations of our results, paving the way for further advancements in this field.
Emotion recognition of EEG signals based on contrastive learning graph convolutional model
Authors: Zhang Yiling , Liao Yuan , Chen Wei , Zhang Xiruo , Huang Liya 
Published: August 2024

Abstract

Objective. Electroencephalogram (EEG) signals offer invaluable insights into the complexities of emotion generation within the brain. Yet, the variability in EEG signals across individuals presents a formidable obstacle for empirical implementations. Our research addresses these challenges innovatively, focusing on the commonalities within distinct subjects’ EEG data. Approach. We introduce a novel approach named Contrastive Learning Graph Convolutional Network (CLGCN). This method captures the distinctive features and crucial channel nodes related to individuals’ emotional states. Specifically, CLGCN merges the dual benefits of CL’s synchronous multisubject data learning and the GCN’s proficiency in deciphering brain connectivity matrices. Understanding multifaceted brain functions and their information interchange processes is realized as CLGCN generates a standardized brain network learning matrix during a dataset’s learning process. Main results. Our model underwent rigorous testing on the Database for Emotion Analysis using Physiological Signals (DEAP) and SEED datasets. In the five-fold cross-validation used for dependent subject experimental setting, it achieved an accuracy of 97.13% on the DEAP dataset and surpassed 99% on the SEED and SEED_IV datasets. In the incremental learning experiments with the SEED dataset, merely 5% of the data was sufficient to fine-tune the model, resulting in an accuracy of 92.8% for the new subject. These findings validate the model’s efficacy. Significance. This work combines CL with GCN, improving the accuracy of decoding emotional states from EEG signals and offering valuable insights into uncovering the underlying mechanisms of emotional processes in the brain.
Effect of parallel flow on resonant layer responses in high beta plasmas
Authors: Lee Yeongsun , Park Jong-Kyu , Na Yong-Su 
Published: August 2024

Abstract
Resonant layers in a tokamak respond to non-axisymmetric magnetic perturbations by amplifying the mode amplitude and balancing the plasma rotation through magnetic reconnection and force balance, respectively. This resonant response can be characterized by local layer parameters and especially by a single quantity in the linear regime, the so-called inner-layer Δ. The computation of Δ under two-fluid drift-MHD formalism has been progressed by reducing the order of the system in the phase space, where the shielding current is approximated as being only carried by electrons, a posteriori. In this study, we relax the approximation and compute Δ accounted for by the parallel flow associated with the ion shielding current. The posteriori is numerically verified in great agreement with the original SLAYER developed in a previous paper (J.-K. Park 2022 Phys. Plasmas
29 072506). Extending the resonant layer response theory to high β plasmas, our research findings answer two important questions: how the parallel flow influences the resonant layer response and why the parallel flow effect appears in high β plasmas. The complicated plasma compression in high β regime allows the parallel flow response to give rise to the ion shielding current, which not only shifts the zero-crossing condition of the ExB flow but also enhances the field penetration threshold. Technically, the Riccati matrix transformation method is adapted to handle the numerical stiffness due to the increased order of the system. The high fidelity of this numerical method makes use of further extension of the model to higher-order systems to take other physical phenomena into account. This work is envisaged to predict the resonant layer response under high β fusion reactor conditions.
Electron transport barrier and high confinement in configurations with internal islands close to the plasma edge of W7-X
Authors: Chaudhary N. , Hirsch M. , Andreeva T. , Geiger J. , Wolf R.C. , Wurden G.A. ,   the W7-X Team
Published: August 2024

Abstract
The low magnetic shear in the Wendelstein 7-X (W7-X) stellarator makes it feasible to shape the separatrix by the large islands constituting an island-divertor, and this can be exploited to access various magnetic configurations, including samples of different internal island sizes and locations. To investigate the configuration effects on the plasma confinement, a configuration scan was performed by changing the coil currents to vary the rotational transform between values

5

/

4

and

5

/

6

at the plasma boundary with different power levels (2, 4, 6 MW) of electron cyclotron resonance heating (ECRH) at a maximum plasma density of

8
×

10

19

m

−
2

. neutral beam injection (NBI) heating was also applied during some configurations of the scan to create a density ramp and access high densities beyond the X2 ECRH cutoff. For the magnetic configurations, where the

5

/

5

and

5

/

6

island chains were moved closer to separatrix but remaining inside the last closed flux surface, the electron cyclotron emission shows that an electron temperature,

T

e

, pedestal develops already during ECRH heated plasma buildup phase indicating a transport barrier, and the barrier sustains irrespective of changed plasma heating conditions such as NBI in the later part of discharge. The transport barrier is broken by subsequent fast crashes, observed with multiple plasma diagnostics with characteristics such as tokamak edge localized modes, and the corresponding crash amplitude and frequency vary with plasma pressure. The impact of the transport barrier on plasma confinement can be seen through the increased core

T

e

profile, which could be responsible for the overall increase in the stored diamagnetic energy by approximately 10% for these configurations. After the plasma heating is terminated, a backwards transition to a degraded confinement state is also observed. These observations indicate a configuration triggered high confinement mode in low shear W7-X. This work focuses on the occurrence of this transport barrier for different magnetic configurations and its relation to internal magnetic islands.
Effect of the downstream blockage induced under-rib convection on oxygen feeding in a PEMFC with parallel flow field
Authors: Ding Zhonghang , Ye Qiang 
Published: August 2024

Abstract
In the parallel flow field of a proton exchange membrane fuel cell (PEMFC), liquid water could totally block a channel, potentially inducing under-rib convection between the blocked channel and adjacent unblocked ones. This work establishes a three-dimensional PEMFC model with three parallel-connected channels on the cathode side, specifically focusing on the middle channel, which simulates blockage caused by liquid water. Our findings indicate that the blockage-induced under-rib convection could reach velocities up to 0.1 m s−1, suggesting that it plays a key role in maintaining oxygen supply to the catalyst layer despite the blockage. However, reducing the gas diffusion layer’s permeability to a tenth of its intrinsic value significantly weakens this convection, leading to localized oxygen starvation and up to 15% performance loss. These findings highlight the critical role of under-rib convection in mitigating the adverse effects of channel blockages on PEMFC performance and underscore the need for optimized design and operational strategies to manage liquid water within the cell.
Research on variable pressure oil supply servo system based on accumulator
Authors: Wang Qiang , Zhu Pengcheng , Chen Liugang , Zhang Xingbin , Wang Shufen 
Published: August 2024

Abstract
In some special engineering applications, actuators are required to operate at high speed and heavy load in a short period of time, and in order to save the installed power of the pumping station, the accumulator can be used as a power source. In order to effectively overcome the influence of the accumulator oil supply pressure on the system accuracy, a variable pressure oil supply servo system based on the accumulator is designed. The results show that the designed controller has faster response speed and higher control accuracy than the PID controller, and can effectively overcome the influence of the drop of oil supply pressure of the accumulator.
Optimal scheduling of building integrated energy system considering the interaction of electric energy and heat energy
Authors: Zhang Qi , Wu Gaoxiang , Li Zhe , Yang Huaxiao , Dai Jian 
Published: August 2024

Abstract
This research focuses on optimizing smart building energy systems to improve energy efficiency, lower operational costs, and support environmental sustainability. We’ve developed an intelligent energy management framework by integrating advanced control strategies and technologies. This framework spans energy generation, conversion, storage, and utilization, allowing for coordinated scheduling of electricity and thermal energy from various sources. Through mathematical modeling, we accurately describe the real-time operational characteristics of system devices. Our simulation experiments confirm the effectiveness of these optimization strategies, showing significant performance enhancements across diverse operating conditions. This study offers strong theoretical support for designing and managing smart building energy systems, contributing positively to the sector’s future development and sustainability.
Research on SOC-constrained SOP estimation technique based on static operating conditions
Authors: Yang Chao , Ye Zhihao , Xiong Xin , Wang Zerun 
Published: August 2024

Abstract
In this study, we explore a novel method for estimating the System Operating Power (SOP) in battery management systems (BMS) by leveraging measurements of open circuit voltage (OCV), state of charge (SOC), and battery current. Through the analysis of battery performance during dynamic stress test (DST) conditions, this method calculates the continuous maximum currents for both charging and discharging scenarios. Subsequently, it estimates the peak power for these processes. By comparing these estimates with experimental data, it is evident that the proposed algorithm significantly enhances the precision of SOP estimations. This improvement not only boosts the accuracy of the SOP calculations but also contributes to the optimization of the BMS, enhancing the overall performance and longevity of the power batteries.
Study on the flexible control method of thermal storage technology participating in the power grid
Authors: Chen Guoqing 
Published: August 2024

Abstract
Energy storage technology is significant in the construction of new power systems. Heat storage is one of the technical energy storage routes, which can help the power grid to shift the peak and fill the valley. However, the flexible control method of heat storage technology participating in the power grid has not been deeply investigated. In this study, a flexible control model is built and the control strategy is proposed. The flexible control model introduces a load aggregator to realize flexible load control and benefit all the participants through the four-market trading mode. The flexible control strategy is different based on different scenarios, including the new energy consumption period, peak cutting period, and ordinary period. The case analysis shows that when the aggregator subsidizes the user at 0.25 yuan/kWh in the heating season, the overall benefit is the largest and the income distribution among all the participants is the most reasonable.
Study on the effect of hydrogen doping on engine emission characteristics
Authors: Zhang Qian , Wang Shangxue , Sun Tingting , Liu Zhiyu 
Published: August 2024

Abstract
The emission characteristics of the entire engine after hydrogen blending combustion in the intake system under different loads and external characteristic operating conditions were studied through experimental methods. The research results show that under various operating conditions of hydrogen/oxygen mixed combustion, CO and HC emissions show significant reduction rates at medium and low speeds, with maximum reduction rates of 11.5% and 46.67%, respectively. At medium and low speeds, hydrogen has a more significant impact on emissions than that at higher speeds and high loads. Experiments have shown that adding an appropriate amount of hydrogen to the engine intake can significantly enhance the combustion process of the mixture, improve cycle thermal efficiency, and as a result, reduce CO and HC emissions.
Research on the flow and heat transfer performance of variable geometry high-pressure turbine blade tip area of gas turbine
Authors: Li Yujie , Wang Wen , Liu Yalei 
Published: August 2024

Abstract
Carrying out the research of geometric turbine region flow and heat transfer research, and optimizing the configuration of the end zone is of great significance to improve turbine performance. In response to the complex second flow and heat transfer caused by the interval space of geometric turbine blades, this article starts from the perspective of reducing the pneumatic loss of the end zone and improving the heat transfer. The numerical method is used to study the adjustment of the turbine non-uniform import conditions, which can be adjusted. Studies have found that the configuration of the static leaf end zone weakens the cross-speed flow and leakage flow of the interval space of the rear end. At the same time, the coverage of the cooling gas on the wall surface of the end zone is also reduced. The separation of front side of the interval space is separated, and the average heat transfer coefficient of the wall surface is reduced, which has the best air thermal performance.