bluuebunny/crossref_metadata_2025_split huggingface dataset:
Various edge low-frequency fluctuations during transition to a detached divertor in Experimental Advanced Superconducting Tokamak
Authors: Ding G.F. , Chen R. , Ye Y. , Xu G.S. , Wu X.Q. , Yang Q.Q. , Yu L. , Meng L.Y. , Wang L. , Lin X. , Wang P. , Lan H. 
Published: March 2023

Abstract
Various edge low-frequency fluctuations with distinct characteristics exist in different detached divertor states. Three edge low-frequency fluctuations (

f
<

10 kHz), namely low-frequency quasi-coherent fluctuation (LFCF), low-frequency broadband frequency fluctuation (LFBF), and low-n X-point mode (LNXM) on Experimental Advanced Superconducting Tokamak (EAST), are systematically assessed. The basic features of these fluctuations, such as spectral width, location, mode number, propagating direction, and particle transport capacities, are examined. LFCF occurs when the inner strike point is energy detached or nearly energy detached with

T

et

,

inner

∼

8–15 eV (

T

et,inner

is the electron temperature of the inner strike point), and a large electron temperature gap between the inner and outer strike points

with

Δ

T

et

>

25 eV (

Δ

T

et

is the electron temperature gap between the inner and outer strike points) is essential for the occurrence of LFCF. By contrast, LFBF occurs when the inner strike point is energy detached with

T

et

,

inner

<

8 eV, while the outer strike point is nearly energy detached or attached. The

Δ

T

et

of LFBF is generally lower than that of LFCF, which is

<

25 eV. LNXM is related only to the radiative divertor with impurity seeding and considered to be excited by the geodesic acoustic mode proposed in earlier work (Sun 2021 Nucl. Fusion
61 014002; Diallo 2020 28th IAEA Fusion Energy Conf.), or the coupling of impurity radiation condensation instability and drift waves proposed in a previous work (Ye 2021 Nucl. Fusion
61 116032). In addition, the possible physical mechanisms of LFBF and LFCF are proposed, with LFBF being the purely growing rippling mode and LFCF being the mode formed by the coupling of the rippling mode to the drift waves. Related research may be beneficial to better clarify the various low-frequency fluctuations that occur during different divertor states.
The Distance Spectral Radii of Hypercacti
Authors: Zhang Hongxiao , Zhang Lei , Ren Haizhen 
Published: March 2023

Abstract
Hypergraphs can model many concepts in computer science, engineering, psychology, etc. The spectral theory is an important research topic, which is widely used in combinatorial mathematics, computer science and social science. This paper mainly concerns the structure of extremal hypergraphs determined by the distance spectral of hypergraphs. A hypercactus is a connected k-uniform hypergraph with any two cycles sharing at most one common vertex. For hypercacti with a fixed number of vertices and cycles, we completely determine the hypercactus structure with minimum distance spectral radius.
Numerical Solution of Backward Problem of a Multi-term Time-space Fractional Diffusion Equation
Authors: Yang Yuxuan , Li Yushan , Qin Xianru 
Published: March 2023

Abstract
There have been many studies from a variety of perspectives about the fractional diffusion equation for the backward problem. This work looks at the backward problem in a multi-term time-space fractional diffusion equation (TSFDE), which uses the observational final data. This paper proposes a numerical solution based on a Tikhonov regularization technique combined with an optimal perturbation algorithm (OPA) to take care of this poorly posed problem. An implicit finite difference technology is introduced by the matrix transfer technique as a numerical approach to solving the problem of the initial boundary value. It is both highly effective and relatively stable, as our suggested numerical method’s numerical results illustrate.
Estimation of Relative Attitude Information of Cooperative Nodes in UAV Cluster
Authors: Wang Jiyuan , Liu Yilin , Lin Yufan , Song Chuanfei , Yue Zhongmin , Liu Daxue 
Published: March 2023

Abstract
In the collaborative UAV swarm, every node could locate accurately by sharing the accurate navigation information from the leader, through the spatial geometric constraints structured by relative observation. However, the attitude of the followers which only carry cheap navigation sensors can not be optimized through this method. Low-precision attitude system has wide application prospects in military and civil fields such as robots, UUV and UAV, but the existing filtering methods cannot maintain high accuracy of attitude when the carrier move for a long time or maneuvers with high dynamics. This paper provides a method to obtain the relative attitude Euler Angle between the leader and the follower using the visual vector obtained by binocular camera and the target recognition algorithm. In this paper, the simulation and experiment of the proposed method are carried out. The experimental results show that under the good visual conditions, the relative attitude Euler Angle error obtained by identifying distinguishable targets is less than 2 degrees, which meets the demand of attitude determination for cooperative navigation.
Quantile-based Clustering for Functional Data via Modelling Functional Principal Components Scores
Authors: Hael Mohanned A. , Qiang Ma Hai , AL-kuhali Hamas A. , Rizk Zeinab 
Published: March 2023

Abstract
Clustering tasks of functional data arise naturally in many applications, and efficient classification approaches are needed to find groups. The current paper combines the quantile-based model with the principal component analysis of functional data (FPCA). In our proposed procedures, the projection of functional data is first approximated based on (rotated) FPCA. The quantile-based model is then implemented on the space of rotated scores to identify the potential features of underlying clusters. The proposed method overcomes the limitation of using direct basis function expansion such as Fourier, B-spline, or linear fitting, besides representing a nonparametric clustering alternative based on a quantile approach. The proposed method’s performance has been evaluated in a comprehensive simulation study and afterward compared with existing functional and non-functional clustering methods. The simulation study results showed that the proposed method performs well in terms of correct classification rate and computing time average. Finally, a real-world application concerning temporal wind speed data has been analyzed to demonstrate the proposed method’s advantages and usefulness.
Research on Deformation Law of Loess Layer with Buried Pipeline under Earthquake
Authors: Zhang Simeng , Zhang Yong , Lv Yumin , Liu Hao , Huo Jiangtao 
Published: March 2023

Abstract
Previous earthquake damage studies have shown that loess has strong seismic vulnerability under strong earthquakes, and the water pipelines buried in loess are prone to engineering disasters due to displacement around the soil. Therefore, it is necessary to study and analyze the deformation law of the loess layer with buried pipelines under earthquake. In this paper, based on the actual project of the water pipeline Hanjiang-to-Weihe River Water Diversion Project, using FLAC3D finite difference software, taking vertical dynamic displacement, dynamic stress, and dynamic acceleration as indexes, the deformation law of loess layer with water pipeline buried under earthquake is studied. The results show that: With the continuous attenuation of seismic wave energy, the dynamic displacement of the model gradually increases from bottom to top, and the maximum displacement is located at the top of the model. After the earthquake, the soil showed obvious uneven settlement, and the uneven settlement gradually decreased with the increase of soil depth. The overall dynamic stress of the model shows a trend of decreasing from top to bottom. Based on the above analysis results, this paper studies the influence of five factors, such as seismic amplitude, Young’s modulus of soil, cohesion, internal friction angle, and pipeline radius, on the seismic subsidence of loess with buried pipelines. The results show that the primary and secondary order of factors influencing seismic subsidence of loess is seismic amplitude, cohesion, internal friction angle, pipeline radius, and Young’s modulus.
Study on Numerical Simulation Approach to Interaction Effects between Ships
Authors: Zhuo Yongqiang , Zhang Xiufeng , Lu Jianhua 
Published: March 2023

Abstract
To forecast the hydrodynamic interference between ships accurately and intuitively so as to study the ship maneuvering considering the effect of ship-ship interaction, it is significant for navigation safety in restricted water. This paper adopted an easy way to fully simulate interference between the ships. By taking advantage of the Computational Fluid Dynamics approach, the governing equations of viscous flow and the equations of motion of the ships are solved. The ship-ship motion induced by the hydrodynamic forces is numerically simulated so as to study the characteristic of the interaction effects between ships. To verify the validity of the present numerical methods, the numerical results about the influences on the hydrodynamic force and moment are illustrated and analyzed. The simulated results are acknowledged by the experienced ship operators.
Dynamics Modeling and Simulation for the Near Space Airship with Pressure Resistance Mechanism
Authors: Shi Zhiguang , Dong Ruonan , Guo Shushan , Guo Zhen , Yang Yujie 
Published: March 2023

Abstract
The key problem of the near space airship is the maintenance of the safe pressure and the formed buoyancy of the capsule caused by helium “over hot / over cold” under the change of external thermal radiation environment during the circadian cycle station-keeping. In order to solve this problem, this paper takes a typical near-space airship with a pressure resistance mechanism as the research object. Firstly, ten-degree freedom describing its motion is determined under reasonable assumptions. Secondly, the multi-body dynamics model of the airship is established based on the second Lagrange equation. Finally, the model is numerically simulated in MATLAB / Simulink. The simulation results show that the multi-body dynamics model of the airship in this paper effectively reflects and simulates the motion characteristics of the near-space airship with a pressure regulating mechanism under the action of the environmental wind field, which provides a theoretical basis for further research of this kind of object.
Automatic Brain Tumour Subregion Segmentation from Multimodal MRIs Fusing Muti-channel and Spatial Features
Authors: Liu Rongsheng , Liu Xiaowei , Peng Chengfeng , Li Anping , Liao Yong 
Published: March 2023

Abstract
It is very necessary for disease diagnosis, monitoring and treatment planning to locate and segment brain tumours from 3D MRI images accurately. 3D segmentation from MRIs means classifying each voxel in 3D space, it is very conducive to the relevant biological measurements and further analysis of the lesion. Until now, brain tumour segmentation from 3D biomedical images has been a challenging worldwide task due to the tumour features’ variousness, which varies part of U-Net and concatenates these features, which are upsampled to the same scale. To grasp the channel weight and ROIs, the bottleneck of the network is an improved dual path attention module, which convergence the advantages of channel attention and spatial attention. The proposed model has been validated in the online dataset of BraTS 2018. The mean dice score of enhancing tumours is 0.772. The mean dice score of the whole tumour is 0.907. The mean dice score of the tumour core is 0.819. The effectiveness of the proposed method is proved by quantitative and qualitative evaluation.
Research on Short-term Time Series Forecasting Method Based on Feature Fusion of Electric Power
Authors: Ru Chuanhong , Qin Jiansong , Lu Peng , Zhou Dongcheng , Zhang Yan 
Published: March 2023

Abstract
In the power industry, time series forecasting has many application scenarios, such as accurate electricity consumption forecasting and load forecasting, which can provide a reference for power grid staff and reduce decision-making costs. To improve the accuracy of short-term load forecasting, this paper proposes a hybrid forecasting model based on an improved encoder-decoder architecture model and a Temporal Convolutional Network. Based on the gate recurrent unit, the model in this paper introduces the encoder-decoder architecture, adds the attention mechanism for improving the prediction accuracy, and performs feature fusion with the Temporal Convolutional Network, building a dual-feature fusion model finally. Experiments show that the method proposed in this paper reduces the evaluation metrics RMSE, MAPE and MAE by 7.7%, 15.2%, and 13.9% respectively compared to the Long Short-Term Memory Networks. Compared with the Temporal Convolutional Network, it is reduced by 2.6%, 4.8%, and 4%.
Paper-based wearable ultra-sensitive strain sensors for fitness monitoring
Authors: Javaid Aqsa , Zulfiqar Muhammad Hamza , Saleem Muhammad Shoaib , Khan Muhammad Atif , Zubair Muhammad , Mehmood Muhammad Qasim , Massoud Yehia 
Published: March 2023

Abstract
Emerging technologies that exhibit features of biodegradability and eco-friendliness are potential game changers. Paper is a cost-effective and easily available material that has proved itself a promising candidate for manufacturing strain sensors due to its easy integration into flexible electronics. In this work, an ultra-sensitive and highly stable strain sensor is presented. Easily available materials are used for sensors development and very easy and simple fabrication. The modified interdigital capacitor structure is fabricated on a simple printing paper, whereas copper tape is used as an electrode material. In the anticipated work, the milestones of high sensitivity, durability, and fast response time are achieved. The proposed flexible strain sensor is eco-friendly, bio-degradable, inexpensive, and responds well to applied strain. The proposed work exhibits a fast response time of 0.56 s. The high gauge factor value of 3040.26 and stability up to 5000 cycles. The proposed prototype has been also implemented on the human body for monitoring physical activities and fitness exercises. The proposed strain sensor is an outstandingly good option for assimilation into wearable systems like remote healthcare systems, electromechanical sensing, and human physical monitoring.
Towards a scalable discrete quantum generative adversarial neural network
Authors: Chaudhary Smit , Huembeli Patrick , MacCormack Ian , Patti Taylor L , Kossaifi Jean , Galda Alexey 
Published: March 2023

Abstract
Quantum generative adversarial networks (QGANs) have been studied in the context of quantum machine learning for several years, but there has not been yet a proposal for a fully QGAN with both, a quantum generator and discriminator. We introduce a fully QGAN intended for use with binary data. The architecture incorporates several features found in other classical and quantum machine learning models, which up to this point had not been used in conjunction. In particular, we incorporate classical noise reuploading in the generator, auxiliary qubits in the discriminator to enhance expressivity, and a direct connection between the generator and discriminator circuits, obviating the need to access the generator’s probability distribution. We show that, as separate components, the generator and discriminator perform as desired. We empirically demonstrate the expressive power of our model on both synthetic data as well as low energy states of an Ising model. Our demonstrations suggest that the model is not only capable of reproducing discrete training data, but also of potentially generalizing from it.
Electrode configuration study for three-dimensional imaging of on-chip ECT
Authors: Hor Xian Feng , Leow Pei Ling , Ali Mohamed Sultan Mohamed , Chee Pei Song , Din Shahrulnizahani Mohammad , Gooi Wen Pin 
Published: March 2023

AbstractConventional electrical capacitance tomography (ECT) is widely used for monitoring the fluids flow in a pipeline. As the emergence of microfluidics, the tomography system has been miniaturized and integrated into the microfludic platform for imaging purposes. The on-chip ECT is designed to monitor the permittivity distribution of the micro-platform by integrating the planar electrodes with the sensing region. However, limited research has been reported on the electrode design of on-chip ECT, especially for three-dimensional imaging. Thus, this study investigated the electrode design of an on-chip ECT that is capable for image reconstruction in three-dimensions. Four different electrode configurations with different numbers of electrode and arrangements are investigated by simulation to determine the appropriate configuration for three-dimensional imaging. The electrode dimension is optimized based on the sensitivity distribution using the sensitivity variation parameter (SVP). The simulation results shows that the electrode configuration with dual sensing planes enable three-dimensional imaging. The central electrode of each sensing plane is crucial for restoring a floating object. In experiment, the imaging object that was positioned at different vertical and horizontal locations was reconstructed successfully with an average correlation coefficient of 0.4370 using linear back projection (LBP) algorithm. This work has disclosed the appropriate electrode configuration for the three-dimensional imaging of an on-chip ECT system.
Patterns of Major Frozen Section Interpretation Error: An In-Depth Analysis From a Complex Academic Surgical Pathology Practice
Authors: Dehan Lauren M , Lewis James S , Mehrad Mitra , Ely Kim A 
Published: March 2023

Abstract

Objectives
To establish baseline error rates due to misinterpretation and to identify scenarios in which major errors were most common and potentially preventable.

Methods
Our database was queried over a 3-year period for major discrepancies due to misinterpretation. These were stratified by histomorphologic setting, service, availability/type of prior material, and years of experience and subspecialization of the interpreting pathologist.

Results
The overall discordance rate between frozen section (FS) and final diagnoses was 2.9% (199/6,910). Seventy-two errors were due to interpretation, of which 34 (47.2%) were major. Major error rates were highest on the gastrointestinal and thoracic services. Of major discrepancies, 82.4% were rendered in subdisciplines outside those of the FS pathologist. Pathologists with fewer than 10 years’ experience made more errors than those with more experience (55.9% vs 23.5%, P = .006). Major error rates were greater for cases without previous material compared to those with a prior glass slide (47.1% vs 17.6%, P = .009). Common histomorphologic scenarios in which disagreements were made involved discriminating mesothelial cells from carcinoma (20.6%) and accurately recognizing squamous carcinoma/severe dysplasia (17.6%).

Conclusions
To improve performance and decrease future misdiagnoses, monitoring discordances should be a continuous component of surgical pathology quality assurance programs.
Latent disconnectome prediction of long-term cognitive-behavioural symptoms in stroke
Authors: Talozzi Lia , Forkel Stephanie J , Pacella Valentina , Nozais Victor , Allart Etienne , Piscicelli Céline , Pérennou Dominic , Tranel Daniel , Boes Aaron , Corbetta Maurizio , Nachev Parashkev , Thiebaut de Schotten Michel 
Published: March 2023

Abstract
Stroke significantly impacts the quality of life. However, the long-term cognitive evolution in stroke is poorly predictable at the individual level. There is an urgent need to better predict long-term symptoms based on acute clinical neuroimaging data. Previous works have demonstrated a strong relationship between the location of white matter disconnections and clinical symptoms. However, rendering the entire space of possible disconnection-deficit associations optimally surveyable will allow for a systematic association between brain disconnections and cognitive-behavioural measures at the individual level. Here we present the most comprehensive framework, a composite morphospace of white matter disconnections (disconnectome) to predict neuropsychological scores 1 year after stroke. Linking the latent disconnectome morphospace to neuropsychological outcomes yields biological insights that are available as the first comprehensive atlas of disconnectome-deficit relations across 86 scores—a Neuropsychological White Matter Atlas. Our novel predictive framework, the Disconnectome Symptoms Discoverer, achieved better predictivity performances than six other models, including functional disconnection, lesion topology and volume modelling. Out-of-sample prediction derived from this atlas presented a mean absolute error below 20% and allowed personalize neuropsychological predictions. Prediction on an external cohort achieved an R2 = 0.201 for semantic fluency. In addition, training and testing were replicated on two external cohorts achieving an R2 = 0.18 for visuospatial performance.
This framework is available as an interactive web application (http://disconnectomestudio.bcblab.com) to provide the foundations for a new and practical approach to modelling cognition in stroke. We hope our atlas and web application will help to reduce the burden of cognitive deficits on patients, their families and wider society while also helping to tailor future personalized treatment programmes and discover new targets for treatments. We expect our framework’s range of assessments and predictive power to increase even further through future crowdsourcing.