bluuebunny/crossref_metadata_2025_split huggingface dataset:
Mechanical behavior of zirconium hydride phases: insights from molecular dynamics based simulations
Authors: Patil Sanjay , Parashar Avinash 
Published: September 2024

Abstract
This article aims to study the mechanical behavior of zirconium hydride phases, including γ-ZrH, δ-ZrH1.5, and ϵ-ZrH2. Atomistic simulations were performed to analyze the uni-axial tensile behavior of zirconium (Zr) and zirconium hydrides in conjunction with the deformation governing mechanism. The mechanical behavior of Zr and zirconium hydrides was studied with the help of stress–strain curves, dislocation dynamics, and von Mises stress distribution. The atomistic simulation results were subsequently compared with the existing trends in the literature. The hydrogen concentration significantly influences the mechanical properties and deformation governing behavior of zirconium hydrides. Hydride precipitate in the Zr matrix is a barrier to the glissile dislocations, leading to hydrogen embrittlement. This phenomenon intensifies with hydride size and hydrogen concentration, and the effect is more pronounced at lower temperatures.
Terahertz phase imaging of large-aperture liquid crystal modulator with ITO interdigitated electrode
Authors: Le Bourlout A , Pusenkova A , Lafrenière-Greig J , Ropagnol X , Galstian T , Blanchard F 
Published: September 2024

Abstract
We have fabricated and characterized a large-aperture electrooptic phase modulation device operating in the terahertz (THz) frequency range. The device consists of a 1.6 mm thick nematic liquid crystal placed between glass plates with a novel interdigitated electrode design. Using THz time-domain spectroscopy (THz-TDS) coupled with raster scanning imaging, we evaluated phase modulation across a 25 mm diameter LC device and mapped the spatial uniformity of phase shift. Our results confirm the functionality of the LC cell as a controllable quarter-wave plate at 0.26 THz and half-wave plate at 0.52 THz. This work contributes to the development of large-aperture and transmissive LC devices as low-cost phase plates for THz waves and paves the way for future applications in THz modulators.
Room temperature spin injection study across semi-crystalline PVDF-HFP thin films in PVDF-HFP/NiFe bilayers and Ag/(NiFe or Co)/PVDF-HFP/NiFe spin valves
Authors: Roy Jyotirmoy , Ravi Teja Pajjuru , Sahu Savita , S Devadarsan , Basheed G A , Gangineni R B 
Published: September 2024

Abstract
Spin injection across 160 nm thick semi-crystalline Poly(vinylidene fluoride-co-hexafluoropropylene) (PVDF-HFP) is methodically investigated at room temperature in PVDF-HFP/NiFe bilayers and Ag/(NiFe or Co)/PVDF-HFP/NiFe vertical organic spin valves (OSVs) using both the co-planar waveguide ferromagnetic resonance (CPW-FMR: 7–35 GHz) and magnetoresistance (MR) techniques. The structural and microstructural characteristics of PVDF-HFP reveal the formation of mixed non-ferroelectric alpha and ferroelectric beta phases. The spin injection due to the transfer of angular momentum in PVDF-HFP/NiFe is quantified by measuring the spin-mixing conductance (g
↑↓) and the enhancement in Gilbert damping (
α
) parameters from CPW-FMR data. A significant increase in
α
of 26% and g
↑↓ of (2.72 ± 0.45) × 1019 m−2 highlights the efficient spin injection into the PVDF-HFP spacer layer. Further, the MR in OSV structures reveals a room temperature spin injection with a maximum MR of 0.278 ± 0.006% for Ag/Co/PVDF-HFP/NiFe and 0.349 ± 0.039% for the Ag/NiFe/PVDF-HFP/NiFe devices. Furthermore, the spin injection processes are discussed w.r.t to bias voltages, interfaces and microwave frequencies.
A systematic review of data augmentation methods for intelligent fault diagnosis of rotating machinery under limited data conditions
Authors: Ju Zedong , Chen Yinsheng , Qiang Yukang , Chen Xinyi , Ju Chao , Yang Jingli 
Published: September 2024

Abstract
In recent years, research on the intelligent fault diagnosis of rotating machinery has made remarkable progress, bringing considerable economic benefits to industrial production. However, in the industrial environment, the accuracy and stability of the diagnostic model face severe challenges due to the extremely limited fault data. Data augmentation methods have the capability to increase both the quantity and diversity of data without altering the key characteristics of the original data, which is particularly important for the development of intelligent fault diagnosis of rotating machinery under limited data conditions (IFD-RM-LDC). Despite the abundant achievements in research on data augmentation methods, there is a lack of systematic reviews and clear future development directions. Therefore, this paper systematically reviews and discusses data augmentation methods for IFD-RM-LDC. Firstly, existing data augmentation methods are categorized into three groups: synthetic minority over-sampling technique (SMOTE)-based methods, generative model-based methods, and data transformation-based methods. Then, these three methods are introduced in detail and discussed in depth: SMOTE-based methods synthesize new samples through a spatial interpolation strategy; generative model-based methods generate new samples according to the distribution characteristics of existing samples; data transformation-based methods generate new samples through a series of transformation operations. Finally, the challenges faced by current data augmentation methods, including their limitations in generalization, real-time performance, and interpretability, as well as the absence of robust evaluation metrics for generated samples, have been summarized, and potential solutions to address these issues have been explored.
Deep learning-based segmentation for high-dose-rate brachytherapy in cervical cancer using 3D Prompt-ResUNet
Authors: Xue Xian , Sun Lining , Liang Dazhu , Zhu Jingyang , Liu Lele , Sun Quanfu , Liu Hefeng , Gao Jianwei , Fu Xiaosha , Ding Jingjing , Dai Xiangkun , Tao Laiyuan , Cheng Jinsheng , Li Tengxiang , Zhou Fugen 
Published: September 2024

Abstract

Objective. To develop and evaluate a 3D Prompt-ResUNet module that utilized the prompt-based model combined with 3D nnUNet for rapid and consistent autosegmentation of high-risk clinical target volume (HRCTV) and organ at risk (OAR) in high-dose-rate brachytherapy for cervical cancer patients. Approach. We used 73 computed tomography scans and 62 magnetic resonance imaging scans from 135 (103 for training, 16 for validation, and 16 for testing) cervical cancer patients across two hospitals for HRCTV and OAR segmentation. A novel comparison of the deep learning neural networks 3D Prompt-ResUNet, nnUNet, and segment anything model-Med3D was applied for the segmentation. Evaluation was conducted in two parts: geometric and clinical assessments. Quantitative metrics included the Dice similarity coefficient (DSC), 95th percentile Hausdorff distance (HD95%), Jaccard index (JI), and Matthews correlation coefficient (MCC). Clinical evaluation involved interobserver comparison, 4-grade expert scoring, and a double-blinded Turing test. Main results. The Prompt-ResUNet model performed most similarly to experienced radiation oncologists, outperforming less experienced ones. During testing, the DSC, HD95% (mm), JI, and MCC value (mean ± SD) for HRCTV were 0.92 ± 0.03, 2.91 ± 0.69, 0.85 ± 0.04, and 0.92 ± 0.02, respectively. For the bladder, these values were 0.93 ± 0.05, 3.07 ± 1.05, 0.87 ± 0.08, and 0.93 ± 0.05, respectively. For the rectum, they were 0.87 ± 0.03, 3.54 ± 1.46, 0.78 ± 0.05, and 0.87 ± 0.03, respectively. For the sigmoid, they were 0.76 ± 0.11, 7.54 ± 5.54, 0.63 ± 0.14, and 0.78 ± 0.09, respectively. The Prompt-ResUNet achieved a clinical viability score of at least 2 in all evaluation cases (100%) for both HRCTV and bladder and exceeded the 30% positive rate benchmark for all evaluated structures in the Turing test. Significance. The Prompt-ResUNet architecture demonstrated high consistency with ground truth in autosegmentation of HRCTV and OARs, reducing interobserver variability and shortening treatment times.
Assessment of alternative metrics in the application of infrared thermography to detect muscle damage in sports
Authors: Verderber Lukas , da Silva Willian , Aparicio-Aparicio Inmaculada , Germano Andresa M C , Carpes Felipe P , Priego-Quesada Jose Ignacio 
Published: September 2024

Abstract

Objective. The association between muscle damage and skin temperature is controversial. We hypothesize that including metrics that are more sensitive to individual responses by considering variability and regions representative of higher temperature could influence skin temperature outcomes. Here, the objective of the study was to determine whether using alternative metrics (TMAX, entropy, and pixelgraphy) leads to different results than mean, maximum, minimum, and standard deviation (SD) skin temperature when addressing muscle damage using infrared thermography. Approach. Thermal images from four previous investigations measuring skin temperature before and after muscle damage in the anterior thigh and the posterior lower leg were used. The TMAX, entropy, and pixelgraphy (percentage of pixels above 33 °C) metrics were applied. Main results. On 48 h after running a marathon or half-marathon, no differences were found in skin temperature when applying any metric. Mean, minimum, maximum, TMAX, and pixelgraphy were lower 48 h after than at basal condition following quadriceps muscle damage (p < 0.05). Maximum skin temperature and pixelgraphy were lower 48 h after than the basal condition following muscle damage to the triceps sural (p < 0.05). Overall, TMAX strongly correlated with mean (r = 0.85) and maximum temperatures (r = 0.99) and moderately with minimum (r = 0.66) and pixelgraphy parameter (r = 0.64). Entropy strongly correlates with SD (r = 0.94) and inversely moderately with minimum temperature (r = −0.53). The pixelgraphy moderately correlated with mean (r = 0.68), maximum (r = 0.62), minimum (r = 0.58), and TMAX (r = 0.64). Significance. Using alternative metrics does not change skin temperature outcomes following muscle damage of lower extremity muscle groups.
Introduction of a novel longitudinal-flexural-torsional actuator using a magnetostrictive rod
Authors: Karafi Mohammad Reza , Ansari Saeed 
Published: September 2024

Abstract
This paper presents a novel bulk magnetostrictive actuator, utilizing a rod made of Permendur alloy. This actuator demonstrates versatility in accommodating longitudinal, torsional, and flexural deformations. Longitudinal deformation is induced by applying magnetic fields along the material’s axis, exploiting the Joule effect. The axial magnetic field is generated by a coaxial coil surrounding the material. Torsional deformation is achieved by passing current through the magnetostrictive material and applying circumferential magnetic field, following the Wiedeman effect. To induce flexural deformation, a magnetic field is applied at the material’s surface, facilitated by a magnetic coupler. Actuation is executed using DC magnetic fields, granting the actuator control over four degrees of freedom. Numerical analysis conducted utilizing COMSOL software, showed the combined modes and their mutual influences. The actuator’s displacement range reaches a maximum of 12 µms longitudinally, 7 µms flexurally, and 0.15 degrees torsionally. It also exhibits the capability of simultaneous excitation in two or three different modes. The experiments and studies conducted show the potential application of this innovative actuator in precise positioning systems such as microscopes and optical systems.
Loading-unloading contact analysis of functionally graded carbon nanotube reinforced composite (FG-CNTRC)
Authors: Bhadra Rakesh , Jana Tamonash , Mitra Anirban , Sahoo Prasanta 
Published: September 2024

Abstract
The present work deals with a finite element based spherical indentation contact analysis of a functionally graded carbon nanotube reinforced composite (FG-CNTRC) substrate. The gradation in the composite is achieved by varying the distribution of the reinforced CNTs within the matrix material, which is considered to be aluminium in the present study. The finite element modelling and analysis has been performed in finite element software ANSYS platform. The model’s validity has been convincingly substantiated through a comparison with the findings of already published relevant articles from the literature. In the present study, a detailed investigation is conducted for three types of CNT distribution in the substrate: increasing, decreasing, and uniform density with depth. The investigation aims to examine the influence of these distributions on different contact behavioral parameters e.g. contact force, contact area, contact stresses etc The analysis would pave a way for modelling and fabricating appropriate FG-CNTRC substrate for a desired as well as damage resistant surface contact behavior.
A novel design of the electrostatic storage ring using quadrupole deflector
Authors: Jalel Jaafar , Hussein Oday A 
Published: September 2024

Abstract
A novel electrostatic storage ring (ESR) design was created using an electrostatic quadrupole deflector (EQD) and quadrupole doublet lens (QDL). EQD was used to turn the electron beam 90 degrees in order to create an innovative ESR design. The impact of EQD designs on ESR performance was investigated, and the results showed that the performance of ESR was directly affected by the EQD design. The calculations showed that increasing the EQD diameter by 20% led to an enhancement in the electron beam dimensions by 88% for ∆x and 44% for ∆y for the initial angle of the electron beam α = 0.2°. Also, the design achieved its goal of keeping kinetic energy constant, where for an initial kinetic energy of 1000 eV, the difference between the energy of the injected electron beam and the emerging electron beam from the ESR is approximately 1–5 eV, i.e., despite changing the diameter of the EQD, the dimensions of the electron beam improve and the kinetic energy remains constant.
One-dimensional Dunkl quantum mechanics: a path integral approach
Authors: Benchikha A , Hamil B , Lütfüoğlu B C , Khantoul B 
Published: September 2024

Abstract
In the present manuscript, we employ the Feynman path integral method to derive the propagator in one-dimensional Wigner-Dunkl quantum mechanics. To verify our findings we calculate the propagator associated with the free particle and the harmonic oscillator in the presence of the Dunkl derivative. We also deduce the energy spectra and the corresponding bound-state wave functions from the spectral decomposition of the propagator.
Temperature-induced dielectric and electrical behavior of Cs/HPC-copper vanadate nanocomposites
Authors: Al-kalali N A , Abdelghany A M , Bin Anooz S , Abdelaziz M , Oraby A H 
Published: September 2024

Abstract
This study investigates the effects of temperature exposure on the dielectric and electrical properties of Cs/HPC-copper vanadate nanocomposites. The results indicate a direct correlation between the increase in polymer surface roughness and the amount of incorporated copper vanadate nanoparticles. The real dielectric constant and imaginary dielectric constant exhibited a notable increase at lower frequencies, which was attributed to interfacial polarization. At higher frequencies, the decrease was due to space charge polarization. The incorporation of copper vanadate nanoparticles resulted in a significant enhancement of both the real dielectric constant and imaginary dielectric constant highlighting the crucial role of these nanoparticles in the electrical properties of the nanocomposites. The impedance (Z′) and impedance (Z′) measurements indicate a decrease in Z″ with increasing frequency and temperature, suggesting enhanced ionic conductivity and interfacial polarization. The Cole–Cole plots reveal that the dielectric relaxation process in the Cs/HPC-copper vanadate nanoparticles (NPs) follow the non-Debye model. The results provide insights into the charge-transport mechanisms in these nanocomposites and highlight the importance of temperature in controlling their electrical properties.
Exploring uncertainty in glass phase transitions through machine learning
Authors: Qi Rui , Liu Saihua , Yang Chengqiao , Sun Minhua 
Published: September 2024

Abstract
Machine learning methods have shown significant potential and are widely used in modern physics research. However, the uncertainty linked to machine learning, arising from the opacity of its workflow, demands attention and consideration. This study investigates the application of machine learning models in analyzing the glass transition of Cu50Zr50 metallic glass. By employing supervised learning techniques with ResNet50, MobileNetV3, and GoogleNet image extraction models, the study reveals that while machine learning can capture variations in the disordered atomic structure during the transition process, different models may yield divergent results in determining the glass transition temperature. Moreover, variations in atomic sizes within the images can lead to fluctuations in the predicted transition temperatures. These findings highlight the inherent uncertainties associated with using machine learning to analyze continuous phase transitions and stress the importance of ensuring that the extracted structural features align with the physical characteristics of the transition process.
Vibration energy harvester design and experimental study based on double-negative metamaterials
Authors: Chen Ting , Tan Yu , Duan Yongge , Zhou Dengyu , Yan Boqiang 
Published: September 2024

Abstract
This paper proposes an energy harvesting device based on a double-negative metamaterials structure. The negative stiffness behavior of the pre-compressed buckled beam is used to introduce bistability, which broadens the operating frequency band of the energy harvester. Simultaneously, the energy harvester utilizes the stress concentration and tensile-expansion effects inherent in auxetic structures to enhance the output voltage amplitude. Through finite element simulations and dynamic experiments, a comparative analysis of the static and dynamic characteristics of the double-negative buckled beam and auxetic straight beam is performed. Experiments show that, under the excitation of 2.2g acceleration, the working bandwidth and voltage amplitude of the buckled beam increased by 100% and 7.86%, respectively, when juxtaposed with the straight beam, thereby further achieving wide-frequency and high-efficiency energy harvesting.
Classification and reorganization of retired power batteries based on bp and k-means clustering
Authors: Shao Xianrao , Huang Zhili , Wang Dechuan , Sun Zhenning , Jiang Wenrui 
Published: September 2024

Abstract
The article proposes an efficient method for classifying and reorganizing retired power batteries. Firstly, the K-means clustering algorithm is used to enhance electrochemical response consistency in reorganized battery packs by considering the polarization time constant. Secondly, pulse power test parameters and battery health feature parameters estimated by a BP network are utilized for battery classification and reorganization. This approach addresses issues like lengthy grouping time and the inability to determine specific application scenarios. Simulation results show over 97% classification accuracy for individual batteries and good consistency after grouping, indicating high practical value.
The de-icing principle of electrode-to-ice streamers and deep learning-based calculation of ice-melting rate
Authors: Deng Xiaoxu 
Published: September 2024

Abstract
Within the aviation field, dielectric barrier discharge (DBD) plasma stands as a method utilized for de-icing purposes. This paper assesses the ice-melting capability of electrode-to-ice streamers. The methodology employed is predicated upon the phenomenon termed “thermal explosion of the vibrational reservoir”, which manifests an exponential non-linear increase in gas temperature due to the plasma’s thermal instability mechanism. Utilizing a DBD plasma actuator could provide a more comprehensive understanding of the temperature near the streamers. The ice-melting rates are evaluated by utilizing a deep learning-based target segmentation algorithm. The calculated fastest ice-melting rate Rm
is ∼0.97 mm2/s on the plane of the DBD surface, and meanwhile, the highest surface temperature exceeds 200°C. The method of generating these streamers is not exclusively limited to DBD to attain a higher ice-melting rate.
Analysis of the dynamic characteristics of XLPE pellet space charge
Authors: Cheng Lin , Chen Zongrang , Luo Jianyong , Yang Dechao , Liu Nan 
Published: September 2024

Abstract
The accumulation of space charge within XLPE materials can lead to the electric field’s uneven distribution, thereby increasing the risk of insulation problems in cables. However, the damage mechanism of space charge on cable insulation is not understood completely. Therefore, this study is dedicated to analysing the behaviour of space charge accumulation and dissipation in pressed XLPE granular material. The charge movement mechanism within XLPE materials was meticulously analysed with the pulsed electro-acoustic method. Experimental results reveal that the pressed granular XLPE accumulates charges of the same polarity, and that the total charge within the pressed granular XLPE significantly decreases with increasing voltage application time.
Study on reactive power compensation for a grid connected photovoltaic power generation system
Authors: Xie Wei 
Published: September 2024

Abstract
The photovoltaic (PV) industry is developing rapidly, and electricity from decentralized or grid-connected systems is becoming increasingly important. Grid-connected PV systems with active and reactive power compensation can compensate for voltage fluctuation and enhance power system stability. The paper proposes a two-stage, three-phase PV system with reactive power compensation based on the structural properties of conventional PV grid-connected systems. The system achieves maximum power point tracking through real-time detection of PV current and voltage output, load current, and grid voltage and provides active electricity to the grid. It can provide reactive energy required by the grid to compensate for local load reactive current, effectively suppress dynamic voltage fluctuations, improve the electric power quality, and reduce investment outlay. Simulation results are carried out to validate the rationality of the design.
Research on digital twin operation and control method and application of high-voltage cable
Authors: Wang Jian , Liu Bin , Li Danyu 
Published: September 2024

Abstract
A high-voltage cable digital twin operation and control system was established. We analyzed the principles and methods of high-voltage cable digital twin operation and control. Characteristics and construction methods of high-voltage cable digital twin models were studied. We do some analysis on panoramic perception methods for high-voltage cable engineering status. Perception data were collected to analyze the running status of cable lines. High-voltage cable digital twin linkage control technology was built through control interfaces and control strategies. A high-voltage cable digital twin operation and control platform for typical cable tunnels was constructed. The results show that the method based on the research of high-voltage cable digital twin operation and control system can build a digital twin operation and control platform. The system provides good technical support for intelligent operation and control of high-voltage cable projects, which can further improve the stability of cable lines.