bluuebunny/crossref_metadata_2025_split huggingface dataset:
Studying the breakdown electric field in uniform and non-uniform air gaps
Authors: Riba Jordi-Roger 
Published: June 2024

Abstract
High voltage is essential in power grids, but it inevitably leads to high electrical stress and the associated risk of electrical discharges. Due to the complexity of the phenomena involved in electrical discharges, there are no analytical formulas for predicting the electric field strength at which they initiate, so experimental data and numerical methods are required for this purpose. According to many sources, electrical discharges can occur in air at normal pressure and temperature when the electric field strength is approximately 3 kV mm−1 or greater. This paper analyzes and discusses this threshold in detail by examining relevant electrode geometries used in high voltage applications from experimental data found in the scientific literature and using 2D finite element analysis simulations. Uniform, quasi-uniform, and non-uniform field gaps are analyzed to help students draw conclusions and gain insight into the nature of gas breakdown and the applicability of the 3 kV mm−1 threshold. The approach proposed in this paper is well suited for a practical session or group project for undergraduate or even graduate courses. Despite the important effects and design implications of electrical discharges on high voltage equipment, apparatus and systems, this topic is often not covered in sufficient detail in regular courses.
Uncertainty quantification for goal-oriented inverse problems via variational encoder-decoder networks
Authors: Afkham Babak Maboudi , Chung Julianne , Chung Matthias 
Published: June 2024

Abstract
In this work, we describe a new approach that uses variational encoder-decoder (VED) networks for efficient uncertainty quantification for goal-oriented inverse problems. Contrary to standard inverse problems, these approaches are goal-oriented in that the goal is to estimate some quantities of interest (QoI) that are functions of the solution of an inverse problem, rather than the solution itself. Moreover, we are interested in computing uncertainty metrics associated with the QoI, thus utilizing a Bayesian approach for inverse problems that incorporates the prediction operator and techniques for exploring the posterior. This may be particularly challenging, especially for nonlinear, possibly unknown, operators and nonstandard prior assumptions. We harness recent advances in machine learning, i.e. VED networks, to describe a data-driven approach to large-scale inverse problems. This enables a real-time uncertainty quantification for the QoI. One of the advantages of our approach is that we avoid the need to solve challenging inversion problems by training a network to approximate the mapping from observations to QoI. Another main benefit is that we enable uncertainty quantification for the QoI by leveraging probability distributions in the latent and target spaces. This allows us to efficiently generate QoI samples and circumvent complicated or even unknown forward models and prediction operators. Numerical results from medical tomography reconstruction and nonlinear hydraulic tomography demonstrate the potential and broad applicability of the approach.
Impact of quantum size effects to the band gap of catalytic materials: a computational perspective*
Authors: Inico Elisabetta , Saetta Clara , Di Liberto Giovanni 
Published: June 2024

Abstract
The evolution of nanotechnology has facilitated the development of catalytic materials with controllable composition and size, reaching the sub-nanometer limit. Nowadays, a viable strategy for tailoring and optimizing the catalytic activity involves controlling the size of the catalyst. This strategy is underpinned by the fact that the properties and reactivity of objects with dimensions on the order of nanometers can differ from those of the corresponding bulk material, due to the emergence of quantum size effects. Quantum size effects have a deep influence on the band gap of semiconducting catalytic materials. Computational studies are valuable for predicting and estimating the impact of quantum size effects. This perspective emphasizes the crucial role of modeling quantum size effects when simulating nanostructured catalytic materials. It provides a comprehensive overview of the fundamental principles governing the physics of quantum confinement in various experimentally observable nanostructures. Furthermore, this work may serve as a tutorial for modeling the electronic gap of simple nanostructures, highlighting that when working at the nanoscale, the finite dimensions of the material lead to an increase of the band gap because of the emergence of quantum confinement. This aspect is sometimes overlooked in computational chemistry studies focused on surfaces and nanostructures.
Impact of electrical polarization in the production of hydroxyapatite on ZnO substituted 45S5 bioglass
Authors: Singh Akanksha , Jaiswal Shubham , Singh Preetam , Pyare Ram 
Published: June 2024

Abstract
In the present investigation, we show the role of dielectric permittivity in the growth of hydroxyl carbonate apatite over ZnO-substituted 45S5 bioglass. ZnO is incorporated here in 45S5 bioglass because of its incipient dielectricity. Zinc is a necessary element for the formation, mineralization, development and maintenance of healthy bones. Here, the bioactive glass ZBG, having the general composition of 46.1 SiO2, 26.9 CaO, 2.6 P2O5, 24.4-X Na2O, and X ZnO (here X = 0 to 3 mole %), was synthesized using the traditional melting technique. The ZBG bioglass samples underwent electro-thermal poling with a voltage value of 10 kV at a temperature of 500 °C for 1 h. The impact of substituting Na2O with ZnO on the in-vitro bioactive property following submersion in simulated bodily fluid (SBF) was examined using the Fourier transform of infrared spectroscopy (FTIR) and x-ray diffraction (XRD). A comparison has been made between the dielectric constant (ε) and alternating current conductivity of unpolarized and polarized hydroxyl carbonate apatite (HCA) formed samples subjected to a 90 kV cm−1 polarisation field. Additionally, the influence of electrical poling on the ZBG samples that were created was examined via the use of XRD, scanning electron microscopy (SEM), energy-dispersive x-ray spectroscopy (EDX), and atomic force microscopy (AFM) research. The dielectric characteristics of bioactive glasses were improved by substituting Na2O with ZnO, as seen in the study. The ZBG samples immersed in SBF solution enhance the hydroxyl calcium phosphate precipitation process due to electrical interaction with the polarized sample. This result shows us that N-poled samples are more suitable for orthopaedic applications. Thus, our main aim of the present investigation is to increase the bioactivity of 45S5 glasses substituted with ZnO after polarization, which will be more suitable for orthopaedic implants.
Research on quantum correlations and Uhlmann phase in two-fermion mixed state system
Authors: Yao Wei-Min , Fan Xiao-Gang , Song Xue-Ke , Wang Dong , Ye Liu 
Published: June 2024

Abstract
Geometric phase, characterized by its unique properties has been an interesting subject since the discovery of Berry phase. A state inevitably becomes a mixed state in the environment. Uhlmann phase can be applied to mixed states and may be the generalization of Berry phase. In this paper, we use a pair of interacting spin-1/2 fermions, where one particle is influenced by an external magnetic field, while the other remains unaffected, to investigate quantum correlations and Uhlmann phase, we define g, p as the ratio of the particle coupling intensity to the magnetic field, and q as the depolarization parameter. Through calculation, we get the specific parameter range q of steering and Bell nonlocality under the depolarized noise channel,

q
∈

0
,
1
−

4
+

g

2

4
+
2

g

2

(steering) and

q
∈

0
,
1
−

4
+

g

2

4
+
3

g

2

(Bell nonlocality). Moreover, by using Uhlmann phase, we obtain a simple discrimination criterion of the steerability (Bell nonlocality) of the mixed system.
Memory effect of gravitational wave pulses in PP-wave spacetimes
Authors: Datta Sucheta , Guha Sarbari 
Published: June 2024

Abstract
In this paper, we study the gravitational memory effect in pp-wave spacetimes due to the passage of a pulse having the form of a ramp profile through this spacetime. We have analyzed the effect of this pulse on the evolution of nearby geodesics, and have determined analytical solutions of the geodesic equations in the Brinkmann coordinates. We have also examined the changes in the separation between a pair of geodesics and their velocity profiles. The separation (along x or y-direction) increases monotonically from an initial constant value. In contrast, the relative velocity grows from zero and settles to a final non-zero constant value. These resulting changes are retained as memory after the pulse dies out. The nature of this memory is similar to that determined by earlier workers using Gaussian, square, and other pulse profiles, thereby validating the universality of gravitational wave memory.
Automatic classification of multi-carrier modulation signal using STFT spectrogram and deep CNN
Authors: Tailor Anshul , Dua Mohit , Verma Pankaj 
Published: June 2024

Abstract
In the realm of communication systems, categorizing Multi-Carrier Modulation (MCM) signals without cooperative communication poses a significant technical challenge. In this paper, we introduce a novel approach for accurately categorizing five distinct MCM signals, including Orthogonal Frequency Division Multiplexing (OFDM), Filter Bank Multicarrier (FBMC), Filtered Orthogonal Frequency Division Multiplexing (FOFDM), Windowed Orthogonal Frequency Division Multiplexing (WOLA), and Universal Filtered Multicarrier (UFMC). Each signal is considered with two types of subcarrier waveforms, Quadrature Amplitude Modulation 16 (QAM16) and Quadrature Amplitude Modulation 64 (QAM64), resulting in a total of 10 unique MCM signals for classification. Our proposed methodology leverages Short-Time Fourier Transform (STFT) spectrograms for feature extraction at the frontend, while at the backend, we employ three variants of Convolutional Neural Network (CNN) models; CNN, CNN with Dropout (CNN_d), CNN with both Dropout and L1 Regularization (CNN_dL1) and one deep CNN model; Xception, individually. We aim to provide an efficient and reliable means of categorizing MCM signals, with practical applications in signal processing and communication systems. Extensive simulations demonstrate the effectiveness of our approach, achieving remarkable accuracies. Notably, the Xception model exhibits the highest accuracy among the four models considered. Specifically, we attain an accuracy of 98% at 10 dB SNR using the Xception model. These results underscore the efficacy of our proposed methodology and highlight the potential for its deployment in real-world scenarios.
Atmospheric turbulence recognition with deep learning models for sinusoidal hyperbolic hollow Gaussian beams-based free-space optical communication links
Authors: Elmabruk Kholoud , Adem Kemal , Kılıçarslan Serhat 
Published: June 2024

Abstract
The integration of artificial intelligence technology to improve the performance of free-space optical communication (FSO) systems has received increasing interest. This study aims to propose a novel approach based on deep learning techniques for detecting turbulence-induced distortion levels in FSO communication links. The deep learning-based models improved and fine-tuned in this work are trained using a dataset containing the intensity profiles of Sinusoidal hyperbolic hollow Gaussian beams (ShHGBs). The intensity profiles included in the dataset are the ones of ShHGBs propagating for 6 km under the influence of six different atmospheric turbulence strengths. This study presents deep learning-based Resnet-50, EfficientNet, MobileNetV2, DenseNet121 and Improved+MobileNetV2 approaches for turbulence-induced disturbance detection and experimental evaluation results. In order to compare the experimental results, an evaluation is made by considering the accuracy, precision, recall, and f1-score criteria. As a result of the experimental evaluation, the average values for accuracy, precision, recall and F-score with the best performance of the improved method are given; average accuracy 0.8919, average precision 0.8933, average recall 0.8955 and average F-score 0.8944. The obtained results have immense potential to address the challenges associated with the turbulence effects on the performance of FSO systems.
Performance optimization of AlGaAs and Al

x

Ga
1−x

As based SM-TM-DG-JL-TFET for an analog/RF applications
Authors: Tamilarasi R , Karthik S 
Published: June 2024

Abstract
This study aims to enhance the efficiency of the Double Gate-Junctionless-Tunnel Field Effect Transistor (DG-JL-TFET) by optimizing the utilization of AlGaAs and GaAs/Si/AlGaAs-based Single Material and Tri-Material (SM and TM) configurations.In order to overcome the drawbacks of present TFET architectures, such as their limited ability to drive current and their ambipolar behaviour, and to enhance the on-state current, To execute our suggested SM-TM-DG-JL-TFET configuration. The TM structure exhibits a greater on-state current (I

on
) and a lower SubthersholdSwing (SS) in comparison to SM structures. This study quantifies the Unit-gain-current-cut-off-frequency (f

t
) and Maximum oscillation frequency

f

max

by manipulating geometric parameters such as gate length(l

g
), gate-oxide thickness, and Channel thickness. The TM structure exhibits a significantly greater on-state current (I

on
) of 14 × 10−3 A. Compared to SM structures, while simultaneously reducing the off-state current (I

off
), subthreshold swing (SS), and threshold voltage (V

t
). TM structures exhibit higher values of f

t
and

f

max

in DG-JL-TFET due to their enhanced output conductance compared to SM structures. The device exhibits potential for future low-power-RF applications due to its significant values of f

t
and

f

max

.
Dust particle surface potential in an argon-helium plasma using the (r,q)-distribution function
Authors: Raffah Bahaaudin M , Abid A A , Khan Abdullah , Esmaeili Amin , Al-Hadeethi Yas , Qureshi M N S 
Published: June 2024

Abstract
In this paper, the dust particle surface potential for argon-helium plasma is evaluated analytically and numerically in the context of negatively charged dust particles by employing a power-law

r
,
q

-distribution function. Recent studies have reported the argon-helium plasma and conducted a brief theoretical and experimental survey. To deepen our understanding further, this study aims to analyze the argon-helium plasma comprehensively using the same pattern but with the

r
,
q

-distribution function. For this purpose, the current balance equations are derived for electron, helium and argon ions, when these charge species attain the quasineutrality condition. We numerically examined the currents of plasma species for a broad range of effective distribution function parameters

r

and

q
.

It is revealed that the surface potential of dust particles is significantly affected by the parameters

r

and

q
,

helium ion-to-electron temperature ratio, argon ion-to-electron temperature ratio, and helium ion to argon ion number density ratio. By incorporating the multi-ion (argon-helium) species, the significance of low-temperature non-Maxwellian dusty (complex) plasma is briefly examined.
CRB: A new rumor blocking algorithm in online social networks based on competitive spreading model and influence maximization
Authors: Dong 董 Chen 晨 , Xu 徐 Gui-Qiong 桂琼 , Meng 孟 Lei 蕾 
Published: June 2024

Abstract
The virtuality and openness of online social platforms make networks a hotbed for the rapid propagation of various rumors. In order to block the outbreak of rumor, one of the most effective containment measures is spreading positive information to counterbalance the diffusion of rumor. The spreading mechanism of rumors and effective suppression strategies are significant and challenging research issues. Firstly, in order to simulate the dissemination of multiple types of information, we propose a competitive linear threshold model with state transition (CLTST) to describe the spreading process of rumor and anti-rumor in the same network. Subsequently, we put forward a community-based rumor blocking (CRB) algorithm based on influence maximization theory in social networks. Its crucial step is to identify a set of influential seeds that propagate anti-rumor information to other nodes, which includes community detection, selection of candidate anti-rumor seeds and generation of anti-rumor seed set. Under the CLTST model, the CRB algorithm has been compared with six state-of-the-art algorithms on nine online social networks to verify the performance. Experimental results show that the proposed model can better reflect the process of rumor propagation, and review the propagation mechanism of rumor and anti-rumor in online social networks. Moreover, the proposed CRB algorithm has better performance in weakening the rumor dissemination ability, which can select anti-rumor seeds in networks more accurately and achieve better performance in influence spread, sensitivity analysis, seeds distribution and running time.
Detecting short-term gravitational waves from post-merger hyper-massive neutron stars with a kilohertz detector
Authors: Chen 陈 Yikang 奕康 , Zhu 朱 Zong-Hong 宗宏 
Published: June 2024

Abstract
Gravitational waves emanating from binary neutron star inspirals, alongside electromagnetic transients resulting from the aftermath of the GW170817 merger, have been successfully detected. However, the intricate post-merger dynamics that bridge these two sets of observables remain enigmatic. This includes if, and when, the post-merger remnant star collapses to a black hole, and what are the necessary conditions to power a short gamma-ray burst, and other observed electromagnetic counterparts. Our focus is on the detection of gravitational wave (GW) emissions from hyper-massive neutron stars (NSs) formed through binary neutron star (BNS) mergers. Utilizing several kilohertz GW detectors, we simulate BNS mergers within the detection limits of LIGO-Virgo-KARGA O4. Our objective is to ascertain the fraction of simulated sources that may emit detectable post-merger GW signals. For kilohertz detectors equipped with a new cavity design, we estimate that approximately 1.1%–32% of sources would emit a detectable post-merger GW signal. This fraction is contingent on the mass converted into gravitational wave energy, ranging from 0.01M
sun to 0.1M
sun. Furthermore, by evaluating other well-regarded proposed kilohertz GW detectors, we anticipate that the fraction can increase to as much as 2.1%–61% under optimal performance conditions.
Micron-sized fiber diamond probe for quantum precision measurement of microwave magnetic field
Authors: Lu 卢 Wen-Tao 文韬 , Xia 夏 Sheng-Kai 圣开 , Chen 陈 Ai-Qing 爱庆 , He 何 Kang-Hao 康浩 , Xu 许 Zeng-Bo 增博 , Chen 陈 Yi-Han 艺涵 , Wang 汪 Yang 洋 , Ge 葛 Shi-Yu 仕宇 , An 安 Si-Han 思瀚 , Wu 吴 Jian-Fei 建飞 , Ma 马 Yi-Han 艺菡 , Du 杜 Guan-Xiang 关祥 
Published: June 2024

Abstract
We present a quantitative measurement of the horizontal component of the microwave magnetic field of a coplanar waveguide using a quantum diamond probe in fiber format. The measurement results are compared in detail with simulation, showing a good consistence. Further simulation shows fiber diamond probe brings negligible disturbance to the field under measurement compared to bulk diamond. This method will find important applications ranging from electromagnetic compatibility test and failure analysis of high frequency and high complexity integrated circuits.
Observation of H i around three Satellite Galaxies of M31 with FAST: Andromeda II, NGC 205, and NGC 185
Authors: Liu Ziming , Wang Jie , Jing Yingjie , Xu Chen , Liang Tiantian , Chen Qingze , Liu Zerui , Hou Zhipeng , Wang Yougang 
Published: June 2024

Abstract
With the exceptional sensitivity of the Five-hundred-meter Aperture Spherical radio Telescope, we conducted observations of the neutral hydrogen (H i) in the circumgalactic medium of Andromeda’s (M31) satellite galaxies, specifically Andromeda II, NGC 205, and NGC 185. Initially, three drift scans were executed for these satellites, with a detection limit of 4 × 1018 cm−2 (approximately 1.88 × 103
M
⊙ of H i mass), followed by a more in-depth scan of a specific region. We discovered a C-shaped H i arc structure sharing a position and line-of-sight velocity similar to a stellar ring structure around Andromeda II, hinting at a potential connection with Andromeda II. In the context of NGC 205, we identified two mass concentrations in the northeast direction, which could be indicative of tidal streams resulting from the interaction between this galaxy and M31. These new lumps discovered could be very helpful in solving the missing interstellar medium problem for NGC 205. Observations regarding NGC 185 are consistent with previous studies, and we did not detect any additional H i material around this galaxy. These observational results enhance our understanding of the evolution of these satellite galaxies and provide insight into their historical interactions with the galaxy M31.
Formation of Superthin Galaxies in IllustrisTNG
Authors: Hu Jianhong , Xu Dandan , Li Cheng 
Published: June 2024

Abstract
Superthin galaxies are observed to have stellar disks with extremely small minor-to-major axis ratios. In this work, we investigate the formation of superthin galaxies in the TNG100 simulation. We trace the merger history and investigate the evolution of galaxy properties of a selected sample of superthin galaxies and a control sample of galaxies that share the same joint probability distribution in the stellar-mass and color diagram. Through making comparisons between the two galaxy samples, we find that present-day superthin galaxies had similar morphologies as the control sample counterparts at higher redshifts, but have developed extended flat “superthin” morphologies since z ∼ 1. During this latter evolution stage, superthin galaxies undergo an overwhelmingly higher frequency of prograde mergers (with orbit-spin angle θ
orb ≤ 40°). Accordingly the spins of their dark matter halos have grown significantly and become noticeably higher than those of their normal disk counterparts. This further results in the buildup of their stellar disks at larger distances much beyond the regimes of normal disk galaxies. We also discuss the formation scenario of those superthin galaxies that live in larger dark matter halos as satellite galaxies therein.