bluuebunny/crossref_metadata_2025_split huggingface dataset:
A multi-task learning model with feature separation constraint for parameter prediction of gas–liquid two-phase flow
Authors: Jiang Xiaojing , Li Mengyu , Li Wei , Li Yuanzong , Wang Ruiqi , Chen Hanqing , Gao Zhongke 
Published: December 2024

Abstract
Precise measurement of gas void fraction is crucial for the control and optimization of various industrial processes. However, due to the intricate dynamics inherent in two-phase flow, measuring gas void fraction remains a challenging task. In this work, we propose a novel deep learning model called Feature Separation Constraint Network (FSCN). First, we conduct gas–liquid two-phase flow experiments in vertical upward pipelines, where temporal and spatial signals about the fluid are collected using a four-sector distributed conductivity sensor. Second, a spatio-temporal convolutional neural network is employed to extract features, and flow pattern classification serves as an auxiliary task to provide global features for gas void fraction prediction. Subsequently, an expert network structure with a feature separation constraint is designed to enhance prediction performance. Finally, comparative analyses with competitive baselines demonstrate FSCN’s superior capability in gas void fraction estimation. A series of ablation experiments confirm the efficacy of each component.
Assessment of spatially resolved temporal light modulation in extended scenes by fast imaging measurements
Authors: Schrader Christian , Pendsa Stefan , Ledig Johannes 
Published: December 2024

Abstract
Modern LED-based light sources often use variants of pulse-width modulation to control the operation current in the LEDs and by this the light output and colour of the lamp. The light emission of the LEDs follows this variable driving current which results in a temporal light modulation (TLM). These can lead to effects in the light’s perception by a human observer, e.g. stroboscopic effects, which can range from annoying to harmful. Therefore, the assessment of TLM is needed in the design phase of lighting installations like indoor and outdoor lighting or in automotive context. This work explores the possibility to use cameras for the spatially resolved measurement of TLM. To deal with the insufficient sampling rate and the need for low-pass filtering in the time domain, an approach for periodic signals to use equivalent-time sampling is chosen. Two variants of this method are explained in detail and exemplary measurements of TLM waveforms are presented. The measurement of waveforms with a cut-off frequency of about 20 kHz is demonstrated. Despite the used demonstrator setup did not implement a

V
(
λ
)

-matching, it allowed to gain insights on the TLM of sources in a scene. The main limitation is the relatively small dynamic range that can be measured without manual adjustments to the device settings. This will require some future development to add some automatic attenuators.
Ab initio computational study of hydration thermodynamics in cubic yttria-stabilized zirconia
Authors: Marinopoulos A G 
Published: December 2024

Abstract
Hydration is a major process that controls defect equilibria in oxides through the exchange of oxygen and hydrogen species between the solid and its gaseous environment. For yttria-stabilized zirconia (YSZ), the presence of intrinsic oxygen vacancies that provide charge compensation to the acceptor dopants and the inherent structural disorder pose significant problems towards an understanding of how hydration operates at the atomistic level. First-principles calculations and ab-initio thermodynamics are employed in order to study the hydration reaction in cubic YSZ and the two types of defects appearing therein as reactants and products, the oxygen vacancies and protons, respectively, yielding the defect-formation energies, defect-induced deformation tensors and chemical expansion coefficients. The calculations are based on density-functional theory using a semilocal density functional and a screened-exchange functional approach and take into account the intrinsic structural disorder of the YSZ lattice. The various terms to the free energy of the hydration reaction are determined as a function of temperature and water-vapor partial pressure. The calculations provide estimates of the enthalpy and entropy of hydration in cubic YSZ examining how the solid-state and gas-phase contributions affect the free-energy balance. The final results are discussed in connection with experimental observations of hydration effects in YSZ and other oxides.
Building robust surrogate models of laser-plasma interactions using large scale PIC simulation
Authors: Smith Nathan , Lancaster Kate , Morris Stuart , Arran Chris , Ridgers Chris 
Published: December 2024

Abstract
As the repetition rates of ultra-high intensity lasers increase, simulations used for the prediction of experimental results may need to be augmented with machine learning to keep up. In this paper, the usage of Gaussian process regression in producing surrogate models of laser-plasma interactions from particle-in-cell (PIC) simulations is investigated. Such a model retains the characteristic behaviour of the simulations but allows for faster on-demand results and estimation of statistical noise. A demonstrative model of Bremsstrahlung emission by hot electrons from a femtosecond timescale laser pulse in the

10

20

−

10

23

Wcm

−
2

intensity range is produced using 800 simulations of such a laser-solid interaction from 1D hybrid-PIC. While the simulations required 84 000 CPU-hours to generate, subsequent training occurs on the order of a minute on a single core and prediction takes only a fraction of a second. The model trained on this data is then compared against analytical expectations. The efficiency of training the model and its subsequent ability to distinguish types of noise within the data are analysed, and as a result error bounds on the model are defined.
Stability of the experimental and numerical spheromaks with shear toroidal flow induced by magnetic reconnection
Authors: Ahmadi T , Cai Y , Ono Y , Tanabe H 
Published: December 2024

Abstract
This work presents a laboratory experiment on the magnetic reconnection of two self-sustained, tilt-unstable spheromaks. Experimental observations, confirmed by a developed 3D Hall-MHD model, demonstrate that magnetic reconnection of these spheromaks suppresses the tilt instability by reducing the amplitudes of disruptive low-number toroidal modes. The strong toroidal component of outflow jets generates a shear toroidal velocity, which may disrupt the coherent structure of these modes, leading to their suppression. The damping rate of toroidal magnetic perturbations was found to be exponentially related to the shear toroidal velocity. Following the end of reconnection, the growth rate of the modes is linearly proportional to the decrease in shear velocity.
Exploring the use of low-temperature atmospheric plasma polymerization for the reduction of parasitic currents in type-II superlattice devices
Authors: Gillies R , McKay K , Asku K , Srivastava V , Kesaria M , Sandall I 
Published: December 2024

Abstract
Type-II superlattice (T2SL) devices have the potential to be the new generation of semiconductor-based devices, however fabrication of these devices leads to surface defects that can create surface leakage channels. Passivation methods that are typically used in traditional semiconductors have proved unsuccessful. In this paper we present the initial findings of a low-temperature atmospheric pressure plasma polymerisation process capable of removing the unwanted oxide layers and depositing a thin layer of polymer to protect the surface. We examine the effect of monomer flow rate on the plasma optical emission and electrical characteristics and investigate the deposition chemistry. Finally, we demonstrate the effectiveness of the plasma treatment on T2SL devices and underpin the potential for this technique. These results were presented at the 50th IOP Plasma Physics Conference, April 2024.
Electrostatic instability of non-spherical dust in sub-stellar clouds
Authors: Stark C R , Diver D A , Swayne M I 
Published: December 2024

Abstract
Charged dust clouds play an important role in the evolution of sub-stellar atmospheres through electrical discharges such as lightning events or inter-grain discharges. The consequent plasma activation presents an alternative source of disequilibrium chemistry, potentially triggering a set of chemical reactions otherwise energetically unavailable. The aim of this paper is to address the problem of the electrostatic stability of charged spheroidal dust grains in sub-stellar clouds and its impact on inter-grain electrostatic discharges, the available area for atmospheric gas-phase surface chemistry, the particle eccentricity distribution function and observed polarization signatures. This paper has derived the criterion for the allowed values of dust eccentricity that are electrostatically stable as a function of grain size

a
∈
[
0.2
,
1.8
]

μ

m, floating potential

ϕ

f

∈
[
1
,
10
]

V and tensile strength

Σ

s

=

10

3

Pa. As a consequence of electrostatic instability we also calculate the expected electric field enhancement at the spheroidal poles, the increased surface area of a dust grain, the truncation of the particle eccentricity distribution function and the resultant degree of polarization. Dust grains with an eccentricity below a critical value will be electrostatically stable; whereas, grains with an eccentricity above a critical value will be unstable. For example, for a 1 µm charged dust grain with surface potential of 1 V, the maximum allowable eccentricity is 0.987. As a consequence, electric field strength enhancement at the pole is limited to a factor of 3.5; the surface area for surface chemistry and the synthesis of chemical products is increased by a factor of 1.45; and the degree of polarization is reduced by a factor of 0.65. The results presented here are applicable not only to spheroidal dust grains but any non-spherical dust grains where non-uniform surface electric fields or inhomogeneous tensile strengths could be susceptible to electrostatic instability. In this context electrostatic erosion presents a mechanism that may produce bumpy, irregularly shaped or porous grains.
Electron collision cross sections and electronic states of BH: an R-matrix study for fusion edge plasmas
Authors: Chakrabarti K , Mukherjee N , Bhattacharyya A , Tennyson J 
Published: December 2024

Abstract
A detailed collision calculation of electron impact on BH at the BH equilibrium

R

e

=
2.3285

a
0

is presented. First a good quality wave function for the target BH molecule is developed at the configuration interaction level. Then the R-matrix method is used to obtain collision cross sections for elastic scattering and state-to-state excitation to several excited electronic states of BH. The differential cross sections for elastic scattering below 10 eV and momentum transfer cross section are also obtained. Our calculations further yield two BH− anionic bound states and a few e-BH anionic resonances which have not been previously reported. We obtain potential energy curves (PECs) for the two BH− bound states of

2

Π

and

4

Σ
−

symmetries, and the PEC for the resonant BH− state of

2

Π

symmetry. These data will aid studies of edge plasma characteristics in tokamaks where boronization is used for wall conditioning.
Wehrl entropy and entanglement complexity of quantum spin systems
Authors: Xu Chen , Yu Yiqi , Zhang Peng 
Published: December 2024

Abstract
The Wehrl entropy of a quantum state is the Shannon entropy of its coherent-state distribution function, and remains non-zero even for pure states. We investigate the relationship between this entropy and the many-particle quantum entanglement, for N spin-1/2 particles. Explicitly, we numerically calculate the Wehrl entropy of various N-particle (

2
⩽
N
⩽
20

) entangled pure states, with respect to the SU(2)

⊗
N

coherent states. Our results show that for the large-N (

N
≳
10

) systems the Wehrl entropy of the highly chaotic entangled states (e.g.

2

−
N

/

2

∑

s
1

,

s
2

,

…

,

s
N

=↑
,
↓

|

s
1

,

s
2

,

…

,

s
N

⟩

e

−
i

ϕ

s
1

,

s
2

,

…

,

s
N

, with

ϕ

s
1

,

s
2

,

…

,

s
N

being random angles) are substantially larger than that of the very regular entangled states (e.g. the Greenberger–Horne–Zeilinger state). Therefore, the Wehrl entropy can reflect the complexity of the quantum entanglement of many-body pure states, as proposed by Sugita (2003 J. Phys. A: Math. Gen.
36 9081). In particular, the Wehrl entropy per particle (WEPP) can be used as a quantitative description of this entanglement complexity. Unlike other quantities used to evaluate this complexity (e.g. the degree of entanglement between a subsystem and the other particles), the WEPP does not necessitate the division of the total system into two subsystems. We further demonstrate that many-body pure entangled states can be classified into three types, based on the behavior of the WEPP in the limit

N
→
∞

: states approaching that of a maximally mixed state, those approaching completely separable pure states, and a third category lying between these two extremes. Each type exhibits fundamentally different entanglement complexity.
RangeViT++: refining the early convolutional stem help ViT see better
Authors: Ma Chunyun , Shi Xiaojun , Chen Lu , Song Shuai , Wang Yingxin , Hu Jiaxiang , Yun Xialun 
Published: December 2024

Abstract
Achieving efficient and accurate semantic segmentation of LiDAR point clouds is a crucial fundamental technology in autonomous driving and robotics. In the paper, We have designed the convolutional stem of patch embedding before the ViT in order to enhance RangeViT and improve its performance in point cloud semantic segmentation. And we have named this improved version RangeViT++. Firstly, a Multi Residual Channel Interaction Attention Module (MRCIAM) is introduced to replace original context module of RangeViT, utilizing a multi-branch structure to separately process the various channels of the range image in order to consider their modality and data distribution differences. Secondly, the Meta-Kernel module is introduced to mitigate information loss caused by the traditional CNN’s incomplete adaptation to point cloud range images, which fail to fully exploit the inherent 3D geometric information of point clouds. Lastly, during the training process, a boundary loss is incorporated to alleviate the boundary ambiguity of different classes/objects induced by the mutual conversion between point clouds and range images. Extensive qualitative and quantitative experiments conducted on challenging SemanticKITTI and SemanticPOSS dataset have verified effectiveness of our method. Superior performance is present over baseline RangeViT, which indicates refining the early convolutional stem could improve the performance of ViT on LiDAR point cloud semantic segmentation. The source code and trained model will be available at https://github.com/mafangniu/RangeViT2.git
Image encryption algorithm based on a l dimensional chaotic map and double-base DNA coding
Authors: Meng Ruoyu , Zhang Xiaoqiang , Xu Anni 
Published: December 2024

Abstract
Digital images are widely used in many fields, and image security is becoming more and more important. To enhance the security and robustness, this paper proposes an image encryption algorithm based on a new l dimensional chaotic map and double base complementation DNA coding. Firstly, an equation of l dimensional chaotic map is proposed, and two-dimensional equations are chosen as the first choice for encryption. Secondly, a double-base DNA encoding method is proposed to solve the weakness that DNA encoding rules are more vulnerable to brute force attacks. Thirdly, a DNA cube image encryption algorithm on three-dimensional space is designed. Finally, the experiments and performance analyses of the proposed image encryption algorithm are carried out. The key space is notably extensive, approximately 2456, and the information entropy of the encrypted image approaches 8, while the correlation between adjacent pixels is nearly 0. Furthermore, the proposed algorithm demonstrates remarkable resilience against clipping and noise attacks. Consequently, our algorithm is both secure and robust, making it well-suited for image transmission in network environments that demand high levels of security and robustness.
Decay of iron pentacarbonyl clusters upon interaction with heavy ions
Authors: Sala Leo , Lyshchuk Hlib , Nag Pamir , Rousseau Patrick , Maclot Sylvain , Domaracka Alicja , Kočišek Jaroslav 
Published: December 2024

Abstract
The present work is a continuation of our studies with iron pentacarbonyl, a model organometallic precursor for Focused Ion Beam-Induced Deposition (FIBID). Interactions of He2+(16 keV), Ne+(6 keV), Ne4+(40 keV), Ar2+(12 keV) and Ar8+(64 keV) projectile ions with [Fe(CO)5]n clusters are studied using TOF mass spectrometry. The clusters represent an intermediate between the gas phase and the bulk environment and can be used as a proxy for the processes in complex environments such as e.g. the nanostructure deposition. The addition of environment in the present study results in the observation of fragments with high kinetic energies ejected from clusters, an overall reduction of the fragmentation, and observation of a range of fragments associated with C-O bond dissociation, not observed for isolated molecules. On the other hand, the high efficiency of the Ne+ projectile in fragmenting the Fe(CO)5 isolated molecule is also observed in clusters.
Investigating the higher dimensional Kadomtsev–Petviashvili–Sawada–Kotera–Ramani equation: exploring the modulation instability, Jacobi elliptic and soliton solutions
Authors: Qasim Muhammad , Yao Fengping , Baber Muhammad Zafarullah , Younas Usman 
Published: December 2024

Abstract
In this paper, the Jacobi elliptic function expansion technique is used to obtain the exact solutions of the sixth order (3+1)-dimensional Kadomtsev–Petviashvili–Sawada–Kotera–Ramani equation. Modulation instability is also discussed for this equation. The main purpose is to find novel exact solutions to this equation by means of a finite series expansion of degree n in terms of Jacobi elliptic functions. Single and combined Jacobi elliptic function solutions are obtained. The JEFE method is found to be highly effective for exact analytical solutions of nonlinear partial differential equations and its flexibility permits the development of several variations for specific problem types. The studied equation is reduced to nonlinear ordinary differential equation of integer order by using the traveling wave transformation. We observe that the solutions obtained are precise, and include periodic wave solutions, quasi-periodic wave solutions and solitary waves. Oscillatory phenomena in systems such as plasma physics and optics can be described by periodic wave solutions. Quasi periodic solutions occur in complex systems with multiple interacting frequencies, which are important in turbulence and nonlinear resonance. Solitary waves (solitons) are stable, localized waves that are critical to fluid dynamics, nonlinear optics, and plasma physics, and that model stable wave propagation in many applications. In addition, graphical representations of some solutions are presented to show the direct viewing analysis of the solutions. The results confirm that the proposed technique is a powerful tool for solving a large variety of NPDEs in mathematical physics, and may have applications to other nonlinear evolution equations.
RESAKey GAN: enhancing color image encryption through residual self-attention generative adversarial networks
Authors: Liu Tongzhe , Chen Junyao , Wu Ximei , Long Bofeng , Wang Lujie , He Chenchen , Deng Xuan , Deng Hongwei , Chen Zhong 
Published: December 2024

Abstract
Color image encryption techniques have garnered significant attention due to their importance in safeguarding sensitive visual data. This paper introduces RESAKey GAN, a novel generative adversarial network that leverages the Residual Self-Attention mechanism to generate highly secure cryptographic keys for color image encryption. RESAKey GAN employs a redesigned architecture based on Wasserstein GAN with Gradient Penalty, addressing issues such as mode collapse and training instability. The network incorporates three novel loss functions tailored for image encryption tasks, enhancing key randomness, correlation, sensitivity, and visual appearance. Experiments conducted on the SIPI dataset demonstrate that RESAKey GAN generates private keys with excellent security, robust scrambling and diffusion performance, enabling effective encryption of diverse image scenarios using a simple XOR operation. Our approach mitigates concerns associated with traditional key generation algorithms and showcases the potential of deep learning in advancing color image encryption techniques.
Exploring the photovoltaic potential of CuSbS2 using SCAPS-1D and DFT simulations
Authors: Islam M T , Sk Mukaddar 
Published: December 2024

Abstract
As the world accelerates its shift toward cleaner, renewable energy, the pursuit of cost-effective, eco-friendly, and highly efficient thin film photovoltaics (TFPV) has become more urgent than ever. In this race, copper antimony sulfide (CuSbS2) stands out with its high absorption coefficient, abundant availability, and low-cost making it a suitable candidate for use as a thin-film absorber layer. However, CuSbS2 solar cells currently achieve only around 3% efficiency, which is far from sufficient. The challenges lie in improper band offsets, high defect densities in the absorber layer, and suboptimal back metal contacts, all of which hinder the efficiency of CuSbS2 (CAS) solar cells. In this work, the structural, electronic and optical properties of the CuSbS2 absorbing layer were thoroughly examined through formation energy, band structure, density of states calculations and absorption coefficient. These analyses reveal that CuSbS2 is a highly promising photovoltaic material, thanks to its optimal direct electronic band gap. The initial simulations closely matched experimental results, providing a solid foundation for further analysis. Optimizing conduction and valence band offsets, along with the thickness and carrier density in the buffer and hole transport layers, led to an impressive efficiency jump from 3.22% to 9.56%. This study delved into how the thickness, carrier density, and defect concentration in the bulk absorber affect photovoltaic performance, uncovering vital correlations that boost efficiency. Finally, fine-tuning the series and shunt resistance and optimizing the back contact work function resulted in a dramatic improvement, achieving an impressive overall efficiency of 19.23%.