bluuebunny/crossref_metadata_2025 huggingface dataset:
Wind turbine anomaly detection and identification based on graph neural networks with decision interpretability
Authors: Jiang Guoqian , Yi Zichen , He Qun
Published: August 2024

Condition monitoring of wind turbines with supervisory control and data acquisition (SCADA) data has attracted increasing interest due to its great benefits in improving operation reliability and reducing unplanned downtimes of wind turbines. However, existing SCADA data-based studies focus primarily on anomaly detection, and few studies have attempted to identify the underlying causes of the anomaly. To this end, this paper proposes a new system-level wind turbine anomaly detection and identification method based on an emerging graph neural network with decision interpretability (DIGNN). A correlation-based GNN is first used to capture complex inter-sensor correlations in SCADA data. More importantly, a decision interpretability module is designed to further analyze anomaly causes and effects through a twp-step global and local anomaly decision process. It can greatly improve the interpretability of the model and provide more accurate and meaningful decision results for maintenance purposes. The effectiveness and robustness of the proposed model were verified by four fault cases with SCADA datasets from a real wind farm. The experimental results demonstrated that the proposed model can provide earlier warning of anomalies with lower false alarm rates and accurate anomaly identification with good interpretability, providing valuable help for field maintenance.
Research on pile bearing capacity prediction improved by grey wolf optimization in the SSA-LSSVM model
Authors: Feng Xu , Liu Yongqi , Li Houjun , Cai Shuangyang , Yu Lei
Published: August 2024

Pile foundations in soft soil often encounter challenges regarding abnormal bearing capacity, significantly impacting the safety of engineering projects. The bearing capacity of pile foundations is influenced by various factors, often characterized by complexity and unpredictability. Therefore, this study proposes a comprehensive model, termed GWOASSA-LSSVM, based on grey wolf optimization (GWO)-enhanced sparrow search algorithm (SSA) and least squares support vector model (LSSVM). By introducing a grey wolf hierarchy to enhance the global search capability of the sparrow search algorithm and automating the optimization of parameters (γ, δ) in the LSSVM model using GWO, the GWOASSA-LSSVM predictive model is established. Evaluation metrics including correlation, and correlation between pile bearing capacity and the predictive target are considered, with pile bearing capacity as the predictive target. The GWOASSA-LSSVM model is compared with SSA-LSSVM, LSSVM, and back propagation neural network (BPNN). Results indicate that the GWOASSA-LSSVM model outperforms SSA-LSSVM, LSSVM, and BPNN across metrics such as coefficient of determination (R
2), variance accounted for (VAF), performance index (PI), index of agreement (IOA), index of scatter (IOS), mean absolute percentage error (MAPE), root mean square error (RMSE), and a20-index, demonstrating its capability for accurate prediction of pile bearing capacity.
Global solutions to the three-dimensional inhomogeneous incompressible Phan-Thien–Tanner system with a class of large initial data
Authors: Chen Yuhui , Li Minling , Yao Qinghe , Yao Zheng-an
Published: August 2024

In this paper, we consider the global well-posedness of the three-dimensional inhomogeneous incompressible Phan-Thien–Tanner (PTT) system with general initial data in the critical Besov spaces. The question of whether or not PTT system is globally well posed for large data is still open. When the density ρ is away from zero, we denote by

ϱ
:=

1
ρ

−
1.

More precisely, we prove that the PTT system admits a unique global solution, provided that the initial data ϱ
0, the initial horizontal velocity

u

h
0

, the product

ω

u

30

of the coupling parameter ω and the initial vertical velocity u
30, and the initial symmetric tensor of constraints τ
0 are sufficiently small. In particular, this result includes the global well-posedness of the PTT system for small initial data in the case where

ω
∈
[
0
,
1
)

and for large initial vertical velocity in the case where ω tends to zero. As a by-product, our results can be applied to the so-called Oldroyd-B system.
The hyperbolic umbilic singularity in fast-slow systems
Authors: Jardón-Kojakhmetov Hildeberto , Kuehn Christian , Steinert Maximilian
Published: August 2024

Fast-slow systems with three slow variables and gradient structure in the fast variables have, generically, hyperbolic umbilic, elliptic umbilic or swallowtail singularities. In this article we provide a detailed local analysis of a fast-slow system near a hyperbolic umbilic singularity. In particular, we show that under some appropriate non-degeneracy conditions on the slow flow, the attracting slow manifolds jump onto the fast regime and fan out as they cross the hyperbolic umbilic singularity. The analysis is based on the blow-up technique, in which the hyperbolic umbilic point is blown up to a 5-dimensional sphere. Moreover, the reduced slow flow is also blown up and embedded into the blown-up fast formulation. Further, we describe how our analysis is related to classical theories such as catastrophe theory and constrained differential equations.
Arduino-based investigation of transmission lines and impedance matching
Authors: Alencar Thonimar V
Published: August 2024

Transmission lines play a crucial role in radio-frequency energy transmission between source and load. These systems connect essential physical phenomena like the formation of standing waves and the attenuation of electromagnetic waves in material media with practical considerations such as impedance matching and signal integrity. Understanding these systems requires knowledge of fundamental concepts like inductance, capacitance, and impedance. The absence of impedance matching between the line and load leads to a modulated amplitude in the resulting signal owing to interference between the injected and reflected signals. Here, we present an experiment utilizing an Arduino platform as a signal generator and a data acquisition interface to analyze a radio frequency transmission line. By employing a few-meter-long coaxial cable as the transmission line and a digital oscilloscope with a high sampling rate (several giga-samples per second), we demonstrate how to determine the reflection coefficient as a function of the load impedance. The reflection coefficient enables determination of the return loss, underscoring the significance of impedance matching for optimal performance among the source, transmission line, and the load.
Deep learning method with integrated invertible wavelet scattering for improving the quality of in vivo cardiac DTI
Authors: Deng Zeyu , Wang Lihui , Kuai Zixiang , Chen Qijian , Ye Chen , Scott Andrew D , Nielles-Vallespin Sonia , Zhu Yuemin
Published: August 2024

Objective. Respiratory motion, cardiac motion and inherently low signal-to-noise ratio (SNR) are major limitations of in vivo cardiac diffusion tensor imaging (DTI). We propose a novel enhancement method that uses unsupervised learning based invertible wavelet scattering (IWS) to improve the quality of in vivo cardiac DTI. Approach. Our method starts by extracting nearly transformation-invariant features from multiple cardiac diffusion-weighted (DW) image acquisitions using multi-scale wavelet scattering (WS). Then, the relationship between the WS coefficients and DW images is learned through a multi-scale encoder and a decoder network. Using the trained encoder, the deep features of WS coefficients of multiple DW image acquisitions are further extracted and then fused using an average rule. Finally, using the fused WS features and trained decoder, the enhanced DW images are derived. Main result. We evaluate the performance of the proposed method by comparing it with several methods on three in vivo cardiac DTI datasets in terms of SNR, contrast to noise ratio (CNR), fractional anisotropy (FA), mean diffusivity (MD) and helix angle (HA). Comparing against the best comparison method, SNR/CNR of diastolic, gastric peristalsis influenced, and end-systolic DW images were improved by 1%/16%, 5%/6%, and 56%/30%, respectively. The approach also yielded consistent FA and MD values and more coherent helical fiber structures than the comparison methods used in this work. Significance. The ablation results verify that using the transformation-invariant and noise-robust wavelet scattering features enables us to effectively explore the useful information from the limited data, providing a potential mean to alleviate the dependence of the fusion results on the number of repeated acquisitions, which is beneficial for dealing with the issues of noise and residual motion simultaneously and therefore improving the quality of

i
n

v
i
v
o

cardiac DTI. Code can be found in https://github.com/strawberry1996/WS-MCNN.
Overview of results from the 2023 DIII-D negative triangularity campaign
Authors: Thome K E , Austin M E , Hyatt A , Marinoni A , Nelson A O , Paz-Soldan C , Scotti F , Boyes W , Casali L , Chrystal C , Ding S , Du X D , Eldon D , Ernst D , Hong R , McKee G R , Mordijck S , Sauter O , Schmitz L , Barr J L , Burke M G , Coda S , Cote T B , Fenstermacher M E , Garofalo A , Khabanov F O , Kramer G J , Lasnier C J , Logan N C , Lunia P , McLean A G , Okabayashi M , Shiraki D , Stewart S , Takemura Y , Truong D D , Osborne T , Van Zeeland M A , Victor B S , Wang H Q , Watkins J G , Wehner W P , Welander A S , Wilks T M , Yang J , Yu G , Zeng L ,   the DIII-D Team
Published: August 2024

Negative triangularity (NT) is a potentially transformative configuration for tokamak-based fusion energy with its high-performance core, edge localized mode (ELM)-free edge, and low-field-side divertors that could readily scale to an integrated reactor solution. Previous NT work on the TCV and DIII-D tokamaks motivated the installation of graphite-tile armor on the low-field-side lower outer wall of DIII-D. A dedicated multiple-week experimental campaign was conducted to qualify the NT scenario for future reactors. During the DIII-D NT campaign, high confinement (

H

98
y
,
2

≳

1), high current (

q

95

<

3), and high normalized pressure plasmas (

β

N

>

2.5) were simultaneously attained in strongly NT-shaped discharges with average triangularity

δ

avg

= −0.5 that were stably controlled. Experiments covered a wide range of DIII-D operational space (plasma current, toroidal field, electron density and pressure) and did not trigger an ELM in a single discharge as long as sufficiently strong NT was maintained; in contrast, to other high-performance ELM-suppression scenarios that have narrower operating windows. These strong NT plasmas had a lower outer divertor X-point shape and maintained a non-ELMing edge with an electron temperature pedestal, exceeding that of typical L-mode plasmas. Also, the following was achieved during the campaign: high normalized density (

n

e

/

n

GW

of at least 1.7), particle confinement comparable to energy confinement with

Z

eff

∼
2

, a detached divertor without impurity seeding, and a mantle radiation scenario using extrinsic impurities. These results are promising for a NT fusion pilot plant but further questions on confinement extrapolation and core-edge integration remain, which motivate future NT studies on DIII-D and beyond.
Detection of a low-frequency ion instability in a magnetic nozzle
Authors: Caldarelli A , Filleul F , Takahashi K , Boswell R W , Charles C , Cater J E , Rattenbury N
Published: August 2024

A low-frequency ion instability, with frequency

f

I

between the ion gyrofrequency and the lower hybrid frequency

f

c
,
i

<

f

I

≪

f

LH

, is detected in an argon plasma expanding in a magnetic nozzle for magnetic fields between

240
<

B

z

,
max

<
700

 G. The frequency of the instability exhibits a linear dependence with magnetic field strength, and the wave amplitude has a radial maximum that would match the location of a conical density structure, i.e. high-density cones. For all of the magnetic field cases analysed, the high-frequency spectra showed upper and lower sidebands centred around the driving frequency and at a separation equal to the instability frequency, 27.12 MHz

±

f

I

 kHz. Measurements of the perpendicular wavenumber would satisfy, for certain magnetic field strengths, the dispersion relation of both an electrostatic ion cyclotron wave (ICW) and of an ion acoustic wave. It is hypothesised that the observed low-frequency wave could be an acoustic-like instability propagating perpendicular to the magnetic field, which develops as an ICW at some magnetic field strengths. From the data collected, it is suggested that the high-frequency sidebands may be caused by modulation of the low-frequency wave.
Gate-based quantum neurons in hybrid neural networks
Authors: Lu Changbin , Hu Mengjun , Miao Fuyou , Hou Junpeng
Published: August 2024

Quantum computing is conceived as a promising and powerful next-generation platform for information processing and it has been shown that it could bring significant accelerations to certain tasks, compared to its classical counterparts. With recent advances in noisy intermediate-scale quantum (NISQ) devices, we can process classical data from real-world problems using hybrid quantum systems. In this work, we investigate the critical problem of designing a gate-based hybrid quantum neuron under NISQ constraints to enable the construction of scalable hybrid quantum deep neural networks (HQDNNs). We explore and characterize diverse quantum circuits for hybrid quantum neurons and discuss related critical components of HQDNNs. We also utilize a new schema to infer multiple predictions from a single hybrid neuron. We further compose a highly customizable platform for simulating HQDNNs via Qiskit and test them on diverse classification problems including the iris and the wheat seed datasets. The results show that even HQDNNs with the simplest neurons could lead to superior performance on these tasks. Finally, we show that the HQDNNs are robust to certain levels of noise, making them preferred on NISQ devices. Our work provides a comprehensive investigation of building scalable near-term gate-based HQDNNs and paves the way for future studies of quantum deep learning via both simulations on classical computers and experiments on accessible NISQ devices.
An investigation on anisotropic FMR linewidth in Fe ultrathin film grown on GaAs substrate
Authors: Huang Zhaocong , Tang Xuejian , Liang Jian , Zhao Xupeng , Yue Jinjin , Li Zhuoyi , Zhao Jianhua , Xu Yongbing , Wu Jing , Zhai Ya
Published: August 2024

Understanding the dynamic properties of magnetic films with the thickness down to nanometer scale is of both fundamental interests, as well as of great importance for the development of spintronic devices. In this study, we report the emergence of anisotropic magnetization dynamics by exploring a quasi-two-dimensional single-crystalline Fe/GaAs(001) interface with varying Fe layer thicknesses ranging from 0.7 to 3.0 nm using ferromagnetic resonance (FMR) technique. Various linewidth contributions, including intrinsic isotropic Gilbert damping, extrinsic inhomogeneous broadening and anisotropic two-magnon scattering are considered for the accurate fitting. We analyze and discuss the different mechanisms of linewidth and its field orientation dependence. Especially we propose a phenomenological expression for the anisotropic two-magnon scattering linewidth consisting of two-fold and four-fold symmetry parameters, which achieves a better understanding of the mechanism of anisotropic two-magnon scattering linewidth in the single crystal ultrathin film. Our analytical methods and results not only provide an effective approach for spin dynamic study in spintronics, but also enrich the understanding of the mechanisms of magnetization relaxation in other ferromagnetic metal/semiconductor interface systems.
An equivalent circuit model based design method for wideband absorber using resistive FSS
Authors: Liu Ning , Li Jiaxin , Sheng Xianjun , Fu Haoran
Published: August 2024

In this paper, a design method for wideband absorbers based on equivalent circuit model (ECM) is proposed. Based on the design requirements, a general ECM is established. Then, the optimized circuit parameters can be obtained by using the particle swarm optimization (PSO) algorithm. Meanwhile, the ECM combined with PSO algorithm can also realize the electromagnetic performance evaluations. Finally, the according mapping unit topologies are designed. Among them, a superior wideband absorber is selected, which consists of two layers of FSS loaded with resistive film, a single dielectric plate, an air layer and a metal layer. The fractional bandwidth (FBW) of the absorber is 149.3% (3.09–20.36 GHz), the total thickness is 9.35 mm. The experiment results consistent well with the simulation results, verifying the universality and effectiveness of the proposed design method.
A comprehensive study on dry sliding wear and in-vitro degradation of AZ31 composite with 6 wt% Sn and 1.5 wt% TiO2 fabricated by stir casting
Authors: K Thoufiq Mohammed , Manisekar K
Published: August 2024

This experimental study investigates the dry sliding wear behaviour of novel AZ31 composite with 6 wt% Sn and 1.5 wt% TiO2 samples, focusing on the influence of sliding distance and normal load. Additionally, the research examines degradation rates during a 120-hour immersion period in simulated body fluid (SBF). The wear volume loss increased significantly with higher loads and longer sliding distances, showing a 142% rise from 1000 m to 2000 m and 76% from 2000 m to 3000 m under a 5 N load, peaking at a 25 N load over 5000 m. The specific wear rate dropped by 39% from 5 N to 15 N but increased with distance due to thermal softening, while the coefficient of friction decreased from 0.284 at 1000 m to 0.213 at 5000 m under 5 N. FESEM analysis revealed a transition from abrasive to delamination wear, with a protective oxide layer forming during sliding. Sn in the composite formed hard Mg2Sn intermetallic compounds, affecting crack formation and propagation under higher loads. Wear debris analysis showed both abrasive and delamination wear mechanisms, highlighting the protective role of the oxide layer. The degradation rate increased rapidly during the initial immersion stage in simulated body fluid (SBF), reaching 15.9 mm year−1 after 24 h, and then stabilizing after 48 h. Hydrogen evolution rose sharply from 0.28 ml cm−12 at 2 h to 7.6 ml cm−12 within 24 h, with a 92% increase by 48 h and an additional 38% increase from 48 to 72 h. Post-immersion FESEM analysis showed corroded surfaces with protective layers, cracks, and pitting corrosion. Magnesium hydroxide (Mg(OH)2) and hydroxyapatite played crucial roles in inhibiting corrosion. This analysis provides insights into the wear, and degradation dynamics of the AZ31-6Sn/1.5TiO2 composite, with implications for engineering applications and the development of biodegradable implants in biomedical fields.
Nonlinear interactions of an n-layer X-shape low-frequency vibration isolator equipped with a nonlinear vibration absorber at 1:1 internal resonance: analytical and numerical investigations
Authors: Saeed Nasser A , Ellabban Y Y , Moatimid G M , Hou Lei , Mohamed A F
Published: August 2024

This work addresses, for the first time, the nonlinear dynamics of an

n
−

layers bioinspired

X
−

shape low-frequency vibration isolation system equipped with a nonlinear vibration absorber. The comprehensive mathematical model governing the two-degree-of-freedom system has been derived using Lagrangian mechanics. The method of averaging was applied to obtain an accurate analytical solution for the derived mathematical model. Utilizing the established analytical solution, the dynamical characteristics of the

X
−

shape vibration isolator have been explored both as a single-degree-of-freedom system and after coupling with the proposed vibration absorber, as a two-degree-of-freedom system. The influence of different system parameters, including the number of structure layers, the initial inclination angle, the

X
−

shape rod length, and the absorber stiffness and damping coefficients, on the vibration isolation performance has been investigated. The main findings indicate that while the single-degree-of-freedom

X
−

shape low-frequency vibration isolator performs well in eliminating low-frequency vibration excitations, it exhibits strong vibration levels when the base excitation frequency exceeds the structure's natural frequency. Additionally, it was found that coupling a highly damped linear vibration absorber to the

X
−

shape isolator not only eliminates the strong oscillations of the structure when subjected to high-frequency base excitations but also enhances the structure's low-frequency vibration isolation performance. Moreover, it was reported that integrating a nonlinear vibration absorber with either soft or hard spring characteristics instead of a linear one may degrade the vibration isolation performance of the structure rather than enhance it. Finally, numerical validation of all the analytical results was performed, which showed excellent correspondence with the analytical findings.
Path integral solution for a Dirac particle in a Generalized Inverse Quadratic Yukawa potential
Authors: Aid Salah Eddine , Boukabcha Hocine , Bentridi Salah Eddine
Published: August 2024

In this work, the analytical solutions of the Dirac equation with the spin and pseudospin symmetry for the Generalized Inverse Quadratic Yukawa (GIQY) potential have been investigated. The problem was approximately addressed using path integral formalism. We present the energy eigenvalues expression along with the upper and lower radial wave functions for any given k-state. The Schrödinger solutions for the GIQY potential and Dirac’s solutions for Kratzer potential, Yukawa potential, inversely quadratic Yukawa potential, and Coulomb potential have also been calculated and compared to results from previous investigations.
Insight into compensation behaviors and hysteresis characteristics of an Ising-type borophene monolayer
Authors: An Ying , Wang Wei , Miao Hai-ling , Hao Zi-ming , Li Bo-chen
Published: August 2024

Boron is another novel two-dimensional material after graphene with splendid chemical and physical properties and potential applications in magnetism, electronics, energy materials and other fields. Studying the magnetic properties of borophene is important to improve the relevant theories and experiments. In this paper, we extend a single spin-3/2 Ising model to analyze the magnetic characteristics of the borophene monolayer by using Monte Carlo simulation. The influence of crystal field, exchange coupling and external magnetic field on the magnetization, magnetic susceptibility and internal energy are studied separately and the phase diagrams are presented. The calculation indicates that the system presents the compensation temperature and triple-loop hysteresis behaviors.
Martensitic phase mechanism of ternary FeCrMn thin films influenced by the substrate rotation speeds: structural and magnetic properties
Authors: Kaplan Nadir , Köçkar Hakan
Published: August 2024

In order to investigate the martensitic phase mechanism of the ternary FeCrMn thin films sputtered under the effect of substrate rotation speeds, the structural and related magnetic properties were studied. A range of thin films were deposited at varying rotational speeds of 0, 15, 30, and 45 rpm on flexible amorphous polymer substrates through the use of DC magnetron sputtering. The films were 50 nm thick and were produced at 0.09 nm s−1. The crystal structures showed that all films have a mixture of the body-centred tetragonal (bct) and tetragonal structure. The peak intensity of bct (110) martensitic α’phase increased with the increase of the rotation speeds whereas the tetragonal (430) and (333) peaks stayed almost stable. And, the morphologic surface analysis displayed that the smooth surface turned into a rough surface with the increase of the rotation speeds. After the measurements of hysteresis loops, the films obtained by sputtering of austenitic target have ferromagnetic character with increasing saturation magnetization, MS and coercivity, HC as the substrate rotation speeds increase. With increasing rotation speeds, the increase of the MS from 148 to 242 emu cm−3 and the rise of the HC of the films from 21 to 185 Oe might be explained by the increase of the grain sizes with the increase of % martensitic α’phase caused by increasing rotation speeds. The ternary FeCrMn thin films exhibit increasing % martensitic α’phase and corresponding ferromagnetic properties with increasing substrate rotation speeds. It is concluded that the nanostructured films of FeCrMn have different properties from those of their bulk counterparts under the influence of substrate rotation speeds. Therefore, the martensitic mechanism of the films can easily be controlled by changing rotation speed for potentially flexible new device applications such as spintronics, magnetic hetero-structures, magnetic separators, etc.
Effect of Stone-Wales defects on the mechanical properties of TiAl/CNT core-shell nanowires
Authors: Wang Nan , Gao Tinghong , Yan Wanjun , Ding Yi , Xie Quan
Published: August 2024

In this study, the effect of Stone-Wales (SW) defects on the mechanical properties of TiAl/CNT core-shell nanowire was studied using molecular dynamics simulations. Our study revealed that SW defects can reduce the ultimate tensile strength and the fracture strain of TiAl/CNT core-shell nanowires. Notably, the ultimate tensile strength of TiAl/CNT core-shell nanowires initially decreased and then increased with the increasing number of SW defects. Conversely, the effect of SW defects on the Young’s modulus of TiAl/CNT core-shell nanowires was less pronounced, with the Young’s modulus showing little dependence on the presence of SW defects. The effect on the mechanical properties is a result of the combined effect of lattice changes, Stair-rod and Hirth dislocations, laminar faults and voids brought by the SW defects. These results provide new insights for further design and fabrication of advanced materials.
An ab initio analysis of the electronic, optical, and thermoelectric characteristics of the Zintl phase CsGaSb2
Authors: Al-Essa Sumayah , Saad Essaoud Saber , Bouhemadou Abdelmadjid , Ketfi Mohammed Elamin , Maabed Said , Djilani Fatima , Bin-Omran Saad , Radjai Missoum , Allali Djamel , Khenata Rabah , Al-Douri Yarub
Published: August 2024

We present and analyze the findings of a comprehensive ab initio computation that examines the electronic, optical, and thermoelectric characteristics of a recently synthesized Zintl compound known as CsGaSb2. The electronic and optical characteristics were examined using the DFT-based FP-L/APW+loapproach. Toaddress the exchange–correlation effects, we employed the GGA-PBEsol and TB-mBJ approaches.The CsGaSb2 semiconductor exhibits an indirect bandgap of 0.695 eV when analyzed with the GGA-PBEsol approach, and a bandgap of 1.254 eV when analyzed with the TB-mBJ approach.The PDOS diagrams were used to discover the origins of the electronic states that make up the energy bands. The charge density study reveals that the Ga-Sb link within the [GaSb2] block is mostly governed by a covalent character, whereas the cation Cs+ and polyanion [MSb2]−bonding is predominantly ionic. The frequency dependence of macroscopic linear optical coefficients was evaluated over a broad range of photon energies from 0 to 25 eV. The thermoelectric characteristics were investigated via the Boltzmann kinetic transport theoryassuming a constant relaxation time.The compound’s figure of merit at a temperature of 900 K is roughly 0.8.
Analysis of the periodic variation of pellet ablation radiation intensity in ASDEX Upgrade
Authors: Lang P.T. , Conway G.D. , Kardaun O.J.W.F. , Maraschek M. , Pégourié B. , Ploeckl B. , Samulyak R. ,   the ASDEX Upgrade Team
Published: August 2024

In a future fusion reactor, the main fuelling method will likely rely on the injection of solid hydrogen pellets. Current predictions assume that this goal can be achieved, since being based on a technology which is already largely developed. However, this belief is founded on modelling tools that are usually aligned to the observation made in existing devices and then extrapolated to reactor conditions. This approach needs a sound consideration of its intrinsic restrictions and any observed feature not reproduced by the utilised codes should be applied to check their validation and possibly contribute to their refinement. One specific feature still lacking an explanation of a reasonable and self-consistent mechanism in the current models is the appearance of a phenomenon called striations, which are high frequency variations in the radiation emitted during the pellet ablation process. In order to provide a sound and reliable database for further considerations, a dedicated analysis of this effect has been performed on the mid-size tokamak ASDEX Upgrade. Therefore, such cases have been selected with the relevant signal recorded with sufficient temporal resolution during experiments covering a wide variation of plasma and pellet parameters which are regarded to be potentially influential on the striation pattern. In addition, it was ensured that for any specific case the observed behaviour was reproducible for several individual ablation events under identical conditions. In all cases considered, the observed radiation-intensity variations appear with a typical pattern showing a broad peak of frequencies in the range 50–150 kHz. This characteristic unveils a notable resilience against any parameter variation. This new collection of data can now act as firm basis to corroborate future modelling code-validation efforts. In addition, the analysis method can provide a relatively simple way of reviewing future modelling predictions.
A long-pulse small edge-localized-mode high-confinement plasma with detachment feedback control by floating potential in an experimental advanced superconducting tokamak in a metal wall environment
Authors: Ding G.F. , Xu G.S. , Tao Y.Q. , Wu K. , Yu L. , Lin X. , Meng L.Y. , Wang L. , Yang Q.Q , Chen R. , Liang R.R. , Li K.D. , Zang Q. , Zhou Z.Q. , Yuan Q.P. , Xu J.C.
Published: August 2024

One of the key challenges facing magnetic fusion research is to demonstrate the compatibility between high confinement and radiative divertors in long-pulse discharges with a metal wall environment. A small edge-localized-mode (ELM) high-confinement plasma with an energy confinement factor H
98 ∼ 1.1 and Greenwald density fraction f
GW ∼ 0.65 maintained for 26 s is obtained in the upgraded lower divertor of the Experimental Advanced Superconducting Tokamak (EAST), and periodical detachment is achieved through active control of neon impurity seeding in this long-pulse discharge. For the divertor region, partial detachment is achieved periodically on the outer divertor target plates with the plasma temperature near the outer strike point decreasing to below 5 eV and the peak surface temperature on the outer divertor target plates maintained below 350 °C. The peak heat flux of the lower outer divertor decreases significantly and its profile along the target becomes very flat in the detached state. Two low-frequency (<10 kHz) fluctuations that are related to the rippling mode caused by a resistive instability appear in the detached state. For the pedestal region, the electron pressure profile is flatter and the ELM amplitude is smaller in the detached state than that in the attached state. Edge-coherent mode appears in the attached state and disappears in the detached state. To achieve this experimentally, a new impurity seeding feedback control scheme is applied, where the floating potential measured by divertor Langmuir probes is used as a feedback sensor, which is more reliable in long-pulse discharges with high heat fluxes and thus more suitable for application in future devices. This study provides a new approach for the actively controlled radiative divertor as a solution to the divertor heat loads of future fusion reactors.
Ensemble seasonal forecasting of typhoon frequency over the western North Pacific using multiple machine learning algorithms
Authors: Xiao Zhixiang , Wang Ziqian , Luo Xiaoli , Yao Cai
Published: August 2024

This study introduces an ensemble prediction methodology employing multiple machine learning algorithms for forecasting the frequency of typhoons (TYFs) over the western North Pacific (WNP) during June‒November. Potential predictors were initially identified based on the relationships between the year-by-year variation (DY) of the TYFs and preseason (March–May) environmental factors. These predictors were subsequently further refined, resulting in the selection of eight key predictors. Prediction models were constructed using twenty machine learning algorithms, utilizing data from 1965 to 2010. These trained models were then applied to perform hindcasts of TYFs from 2011 to 2023. The forecasted DY was added to the observed TYF of the preceding year to obtain the current year’s TYF. The results indicate that the TYFs predicted by the multi-model ensemble (MME) closely align with the observation during the hindcast period. Compared to individual models, the MME improves the prediction skill for the DY by at least 5.56% and up to 56.92%. Furthermore, the mean bias of the MME for TYF is notably smaller than that of the ECMWF’s most recent seasonal forecasting system (SEAS5) in the years of 2017‒2023. The superior performance of the ensemble prediction approach was also validated through leave-one-out cross-validation. This research underscores the potential of ensemble prediction approach utilizing multiple machine learning algorithms to improve the forecasting skill of TYF over the WNP.
Systematic large flavor fTWA approach to interaction quenches in the Hubbard model
Authors: Osterkorn Alexander , Kehrein Stefan
Published: August 2024

We study the nonequilibrium dynamics after an interaction quench in the two-dimensional Hubbard model using the recently introduced fermionic truncated Wigner approximation (fTWA). To assess the range of validity of the method in a systematic way, we consider the SU(N) Hubbard model with the fermion degeneracy N as a natural semiclassical expansion parameter. Using both a numerical and a perturbative analytical approach we show that fTWA is exact at least up to and including the prethermalization dynamics. We discuss the limitations of the method beyond this regime.
Novel ASEP-inspired solutions of the Yang-Baxter equation
Authors: Barik Suvendu , Garkun Alexander S , Gritsev Vladimir
Published: August 2024

We explore the algebraic structure of a particular ansatz of the Yang-Baxter equation (YBE), which is inspired by the Bethe Ansatz treatment of the asymmetric simple exclusion process spin-model. Various classes of Hamiltonian density arriving from the two types of R-matrices are found, which also appear as solutions of the constant YBE. We identify the idempotent and nilpotent categories of such constant R-matrices and perform a rank-1 numerical search for the lowest dimension. A summary of the final results reveals general non-Hermitian spin-1/2 chain models.
In vitro three-dimensional volumetric printing of vitreous body models using decellularized extracellular matrix bioink
Authors: Kong Jeong Sik , Kim Joeng Ju , Riva Leonardo , Ginestra Paola Serena , Cho Dong-Woo
Published: August 2024

Hyalocytes, which are considered to originate from the monocyte/macrophage lineage, play active roles in vitreous collagen and hyaluronic acid synthesis. Obtaining a hyalocyte-compatible bioink during the 3D bioprinting of eye models is challenging. In this study, we investigated the suitability of a cartilage-decellularized extracellular matrix (dECM)-based bioink for printing a vitreous body model. Given that achieving a 3D structure and environment identical to those of the vitreous body necessitates good printability and biocompatibility, we examined the mechanical and biological properties of the developed dECM-based bioink. Furthermore, we proposed a 3D bioprinting strategy for volumetric vitreous body fabrication that supports cell viability, transparency, and self-sustainability. The construction of a 3D structure composed of bioink microfibers resulted in improved transparency and hyalocyte-like macrophage activity in volumetric vitreous mimetics, mimicking real vitreous bodies. The results indicate that our 3D structure could serve as a platform for drug testing in disease models and demonstrate that the proposed printing technology, utilizing a dECM-based bioink and volumetric vitreous body, has the potential to facilitate the development of advanced eye models for future studies on floater formation and visual disorders.
Analyzing the likelihood of OAM mode energy transfer in turbulent environments with stochastic Cn
2
Authors: Kupferman Judy , Arnon Shlomi
Published: August 2024

Orbital angular momentum (OAM) is a crucial property of electromagnetic waves used in various applications such as free space communication, light detection and ranging, and remote sensing. However, turbulence can disrupt OAM-based systems by causing energy transfer between OAM modes, significantly impacting emerging fields in the optical spectrum. While traditional analyses assumed a constant turbulence parameter (Cn
2), recent research highlights its stochastic nature in specific scenarios. Our study introduces a new model that considers the stochastic nature of Cn
2. By incorporating this characteristic, our approach provides better predictions of system performance and valuable insights for accurately characterizing and designing communication and remote sensing systems in weak turbulent environments, enhancing their reliability and efficiency.
A combinatorial approach to validate the surface plasmon resonance (SPR) biosensor response
Authors: Chopra Aditi , Mohanta Girish C , Pal Sudipta S
Published: August 2024

One of the fundamental challenges of working with surface plasmon resonance (SPR) biosensors is their inherent lack of specificity. Being very sensitive to minute refractive index (RI) changes in their surrounding medium, SPR biosensors are highly susceptible to variations in pH, temperature, and buffer composition. Therefore, it is often necessary to include an additional validation step downstream to SPR biosensing, particularly for clinical analysis. In this proof-of-study work, we have tried to evaluate the utility of surface-enhanced Raman scattering (SERS) tags as secondary labels for validating SPR biosensor response. Accordingly, a Fibre-optic SPR (FO-SPR) biosensor set-up was fabricated by immobilizing anti-BSA antibodies on the sensor platform for capturing and sensing biotinylated-BSA as a model analyte. Subsequently, the bound analyte and the concomitant shift in SPR response were validated by employing streptavidin-functionalized SERS tags. Intriguingly, apart from validation of the SPR response, the SERS tags also significantly improved the sensitivity of the SPR response and provided semi-quantitative information on the bound analyte. Although utilizing SERS tags undermines the label-free tag of SPR biosensors, the huge improvement in sensitivity and specificity of the sensor makes it suitable for clinical analysis. Furthermore, SERS measurements with a portable Raman spectrometer utilized in this study further highlight the potential of this approach for achieving point-of-care (POC) sensing.
FMD-UNet: fine-grained feature squeeze and multiscale cascade dilated semantic aggregation dual-decoder UNet for COVID-19 lung infection segmentation from CT images
Authors: Wang Wenfeng , Mao Qi , Tian Yi , Zhang Yan , Xiang Zhenwu , Ren Lijia
Published: August 2024

With the advancement of computer-aided diagnosis, the automatic segmentation of COVID-19 infection areas holds great promise for assisting in the timely diagnosis and recovery of patients in clinical practice. Currently, methods relying on U-Net face challenges in effectively utilizing fine-grained semantic information from input images and bridging the semantic gap between the encoder and decoder. To address these issues, we propose an FMD-UNet dual-decoder U-Net network for COVID-19 infection segmentation, which integrates a Fine-grained Feature Squeezing (FGFS) decoder and a Multi-scale Dilated Semantic Aggregation (MDSA) decoder. The FGFS decoder produces fine feature maps through the compression of fine-grained features and a weighted attention mechanism, guiding the model to capture detailed semantic information. The MDSA decoder consists of three hierarchical MDSA modules designed for different stages of input information. These modules progressively fuse different scales of dilated convolutions to process the shallow and deep semantic information from the encoder, and use the extracted feature information to bridge the semantic gaps at various stages, this design captures extensive contextual information while decoding and predicting segmentation, thereby suppressing the increase in model parameters. To better validate the robustness and generalizability of the FMD-UNet, we conducted comprehensive performance evaluations and ablation experiments on three public datasets, and achieved leading Dice Similarity Coefficient (DSC) scores of 84.76, 78.56 and 61.99% in COVID-19 infection segmentation, respectively. Compared to previous methods, the FMD-UNet has fewer parameters and shorter inference time, which also demonstrates its competitiveness.
Evaluation of TOPAS MC tool performance in optical photon transport and radioluminescence-based dosimetry
Authors: Khodaei A , Moradi F , Oresegun A , Zubair H T , Bradley D A , Ibrahim S A , Abdul-Rashid H A
Published: August 2024

Radiation therapy plays a pivotal role in modern cancer treatment, demanding precise and accurate dose delivery to tumor sites while minimizing harm to surrounding healthy tissues. Monte Carlo simulations have emerged as indispensable tools for achieving this precision, offering detailed insights into radiation transport and interaction at the subatomic level. As the use of scintillation and luminescence dosimetry becomes increasingly prevalent in radiation therapy, there arises a need for validated Monte Carlo tools tailored to optical photon transport applications. In this paper, an evaluation process of the TOPAS (TOol for PArticle Simulation) Monte Carlo tool for Cerenkov light generation, optical photon transport and radioluminescence based dosimetry is presented. Three distinct sources of validation data are utilized: one from a published set of experimental results and two others from simulations performed with the Geant4 code. The methodology employed for evaluation includes the selection of benchmark experiments, making use of opt3 and opt4 Geant4 physics models and simulation setup, with observed slight discrepancies within the calculation uncertainties. Additionally, the complexities and challenges associated with modeling optical photons generation through luminescence or Cerenkov radiation and their transport are discussed. The results of our evaluation suggests that TOPAS can be used to reliably predict Cerenkov generation, luminescence phenomenon and the behavior of optical photons in common dosimetry scenarios.
Classification of optic neuritis in neuromyelitis optica spectrum disorders (NMOSD) on MRI using CNN with transfer learning and manipulation of pre-processing on augmentation
Authors: Feng Yang , Chow Li Sze , Gowdh Nadia Muhammad , Ramli Norlisah , Tan Li Kuo , Abdullah Suhailah
Published: August 2024

Neuromyelitis optica spectrum disorder (NMOSD), also known as Devic disease, is an autoimmune central nervous system disorder in humans that commonly causes inflammatory demyelination in the optic nerves and spinal cord. Inflammation in the optic nerves is termed optic neuritis (ON). ON is a common clinical presentation; however, it is not necessarily present in all NMOSD patients. ON in NMOSD can be relapsing and result in severe vision loss. To the best of our knowledge, no study utilises deep learning to classify ON changes on MRI among patients with NMOSD. Therefore, this study aims to deploy eight state-of-the-art CNN models (Inception-v3, Inception-ResNet-v2, ResNet-101, Xception, ShuffleNet, DenseNet-201, MobileNet-v2, and EfficientNet-B0) with transfer learning to classify NMOSD patients with and without chronic ON using optic nerve magnetic resonance imaging. This study also investigated the effects of data augmentation before and after dataset splitting on cropped and whole images. Both quantitative and qualitative assessments (with Grad-Cam) were used to evaluate the performances of the CNN models. The Inception-v3 was identified as the best CNN model for classifying ON among NMOSD patients, with accuracy of 99.5%, sensitivity of 98.9%, specificity of 93.0%, precision of 100%, NPV of 99.0%, and F1-score of 99.4%. This study also demonstrated that the application of augmentation after dataset splitting could avoid information leaking into the testing datasets, hence producing more realistic and reliable results.
Evaluation of suitable sites for concentrated solar power desalination systems: case study of Mauritania
Authors: Ntaghry Khadijetou , Thiam Ababacar , Habib Sidahmed Mohamed Sidi , Faye Kory , Faye Mactar
Published: August 2024

It is imperative to address the critical problem of water scarcity in sub-Saharan Africa, especially in light of the aggravating effects of climate change brought on by the extraction of fossil fuels. In order to ensure the availability of drinkable water in these places, this research proposes integrating concentrated solar power (CSP) with desalination systems (DS). Present research is focused on identifying and evaluating potential locations for DS/CSP implementation within Mauritania by employing a comprehensive, multi-criteria decision-making framework. This framework synthesizes mathematical approaches from multi-criteria analysis with geospatial analysis techniques, considering a range of factors including environmental impact, economic viability, demographic demands, and climatic conditions. Research findings reveal that 10% of the Mauritanian, approximately 103070 km2, presents optimal conditions for the deployment of DS/CSP facilities. The study delineates the coastal regions as prime candidates for seawater desalination plants, while the densely populated southeastern areas are identified as suitable for brackish water desalination systems. Conversely, the less inhabited northern territories hold the potential for decentralized brackish water desalination plants. Hence this study provides a holistic approach for DS/CSP systems installation to manage water scarcity as well as energy security issues in Mauritania. And also provides basis for formulating future policies in the region.