bluuebunny/crossref_metadata_2025 huggingface dataset:
Spatial, temporal, and voltage-dependent measurement of the reduced electric field of nanosecond pulsed discharges with a pulse width of 5 ns in synthetic air at atmospheric pressure
Authors: Sasamoto Ryo , Hirakawa Yoichi , Wang Douyan , Namihira Takao
Published: December 2024

The reduced electric field E/N is one of the important parameters for understanding the occurrence, propagation, state, and plasma chemical reaction of discharge and plasma phenomena. The measurement of the E/N using the nitrogen emission intensity ratio has been used to help understand various discharge and plasma phenomena. Among various discharge and plasma phenomena, nanosecond pulsed discharges are expected to be used in gas processing, environmental purification, surface treatment, agriculture, and medical applications. However, the E/N of nanosecond pulsed discharges with very short pulse widths has not been clarified. In this work, the intensity ratio of nitrogen is used to investigate the E/N of primary and secondary streamer discharges nanosecond pulses generated between a coaxial cylindrical reactor in terms of spatial, temporal, and voltage dependence. Therefore, the maximum E/N of the positive nanosecond pulsed primary streamer discharge generated at the center of the electrode was 522–834 Td. The E/N at the coaxial cylinder’s center was also higher than the E/N near the outer electrode. As the applied voltage increased, the E/N of nanosecond pulsed discharges also increased. From these results, the reasons why nanosecond pulse discharges are effective in applications (ex. Ozone generation and NOx treatment) are discussed.
Improved insulator defect detection network considering target characteristics and sample location classification
Authors: Yu Tianchen , Wu Wei
Published: December 2024

Insulators are crucial components of the power system. An enhanced insulator detection network, based on YOLOv8, addresses unequal training samples, inadequate target localization and classification accuracy in the existing insulator unmanned aerial vehicle inspection algorithm. Firstly, the ADown down-sampling component and DynamicConv are incorporated into the backbone network to enhance feature representation. Secondly, Focal-IoU and Adaptive Training Sample Selection are used during training to adjust the weight of each sample based on their quantity and difficulty level, enhancing focus on rare and challenging targets. Finally, to address difficult target localization and classification, design a task-aligned detection head called ‘Align Head’ to strengthen the link between localization and classification branches. Experiments show that the proposed method increases mAP@0.5 (mean average precision at a threshold of 0.50) by 7.5% over the baseline, with an FPS of 81.57, demonstrating superior performance.
A multi-robot conflict elimination path planning approach for dynamic environments
Authors: Yang Liu , Yang Mengru , Wang Annan
Published: December 2024

Path planning plays a crucial role in multi-robot systems, and its effectiveness directly impacts the system’s performance. A multi-robot conflict-elimination path planning method (CEPP) for dynamic environments is proposed. The method fuses the adaptive dynamic-window algorithm (ADWA) with the Repulsive function-based optimized A* algorithm (R–A*) to deal with multi-robot path planning (MRPP) and introduces a safe area radius and priority strategy to solve the multi-robot collision conflict problem. Among them, ADWA first adds the time cost and target point distance evaluation function to the original evaluation function and introduces adaptive weights to accelerate the efficiency of the robot in finding the target point. Then a target point detection waiting mechanism is introduced to solve the problem that the robot cannot find the endpoint. Finally, the effectiveness of the CEPP algorithm for MRPP in dynamic environments is verified by simulation. Meanwhile, the CEPP algorithm is compared and analyzed with the traditional fusion algorithm (A*-DWA), and the simulation results show that the average running time and path length of this method are better than the A*-DWA algorithm.
A road defect detection algorithm incorporating partially transformer and multiple aggregate trail attention mechanisms
Authors: Wang Xueqiu , Gao Huanbing , Jia Zemeng , Zhao Jiayang
Published: December 2024

Road infrastructure, fundamental to daily life, inevitably sustains damage over time. Timely and precise identification and remediation of road defects are critical to prolong the lifespan of roads and ensure driving safety. Given the limitations of the widely-used You Look Only Once (YOLO) algorithm, including its insufficient receptive field and suboptimal detection accuracy, this paper introduces a novel road defect detection method. First, we propose a new attention mechanism, aggregate multiple coordinate attention, that effectively retains and concatenates channel information while preserving localization data, thereby enhancing the focus on intrinsic features. Second, we design a cross stage partial—partially transformer block (CSP_PTB) that combines CNNs and transformers to yield richer and more varied feature representations. Finally, we develop a novel neck structure, the re-calibrated feature pyramid network (Re-Calibration FPN), which selectively combines boundary and semantic information for finer object contour delineation and positional recalibration. Experimental results show that the S version of the algorithm in this paper achieves a detection accuracy of 73.2% on the road defect dataset, which is 4.2% higher than the YOLOv8 algorithm. Additionally, with an FPS of 80, it meets the requirements for real-time detection, achieving a good balance between detection speed and detection accuracy. Additionally, it exhibits excellent generalizability and robustness on the UAV asphalt pavement distress and PASCAL VOC 2007 datasets.
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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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%.
Current, quantum transport and entropic force of bosonic system interacting with two thermal reservoirs
Authors: Bhattacharya Jayarshi , Gangopadhyay Gautam , Gangopadhyay Sunandan
Published: December 2024

This paper investigates the dynamics of current and quantum transport factor in a bosonic system consisting of a central system interacting with two reservoirs at different temperatures. We derive a master equation describing the time evolution of the density matrix of the system, accounting for the interactions and energy transfer between the components. We quantify the current, representing the flow of bosons through the system and analyse its dependence on the system's parameters and temperatures of the thermal reservoirs. In the steady state regime, we derived an expression for the quantum transport factor of the energy transfer process. Our analysis show that quantum effects, such as the dependence on temperature can significantly impact this factor. In particular, we observe that the transport factor of the quantum system is greater than the corresponding factor when the temperature goes to infinity, where the factor has an identical form with the Carnot efficiency of an ideal heat engine. We then derived the Fokker-Planck equation to find out the Glauber-Sudarsan P-representation. In the steady state of the equation, the probability distribution comes out to be in Gaussian form. We then calculated the entropic force for this probability distribution which gives the Hooke's law in the steady state, in agreement with the fact that our system is a harmonic oscillator.
Scaling laws for optimal Herschel–Bulkley yield stress fluid flow in self-similar tree-like branching networks
Authors: Garg Ashish
Published: December 2024

Fractal networks fluid flows have attracted significant research interest, yet most studies often assume a constant viscosity or power-law fluid flows. This research explores yield stress fluid flows in fractal tube networks, which are commonly found in engineered microfluidic devices and various industrial processes. We analyze optimal flow conditions and structures in tree-like branching networks using Herschel-Bulkley fluid model to understand yield stress materials. We focus on maximizing flow conductance under volume constraints, assuming steady, incompressible, fully developed laminar flow in circular tubes. We propose a conjecture that if the tube-wall stress, remains the same in the network for all branches, then an optimal solution exists and we derive the theoretical formulations for it. We find that the flow conductance is extremely sensitive to the geometry of the network. The effective conductance initially rises as the daughter-parent radius ratio increases, but eventually, it begins to decline. The peak conductance occurs at a specific radius ratio. We find that optimal network geometry depends on the number of branch splits N, and independent of the power-law index n and the yield stress τ

y
. This optimal condition leads to an equal pressure drop as well as equal tube-volume across each branching generation level. Our results are validated with existing theory and extended to encompass shear-thinning and shear-thickening behaviors for any number of splits N with and without yield stress. Additionally, we derive relationships between geometrical and flow characteristics for parent and daughter tubes, including wall stresses, length ratios. These findings provide valuable design principles for efficient transport systems involving yield stress fluids.
Statistical inference and optimal plans for improved adaptive type-II progressive censored data following Kumaraswamy-G family of distributions
Authors: Irfan Mohd , Dutta Subhankar , Sharma Anup Kumar
Published: December 2024

The present paper attempts to study the parametric inference for Kumaraswamy's generalized family of distribution under an improved adaptive Type-II progressive censored sample. Under the frequentist approach, maximum likelihood estimates and maximum product spacing estimates of unknown model parameters are computed using Newton-Raphson methods. The existence and uniqueness properties of maximum likelihood estimates are deduced. Approximate confidence intervals for parameters are created via a variance-covariance matrix and bootstrap resampling methods. Under squared error and LINEX loss function, the Bayes estimates are investigated using independent gamma priors distribution for the unknown parameters. The Markov Chain Monte Carlo (MCMC) approximation technique has been used to compute the Bayes estimates and produce the highest posterior density credible intervals. The efficacy of the suggested approach is assessed using an extensive simulation study. The convergence of the MCMC sample is judged through the different diagnostic plots. Three optimality criteria have been presented to choose the most suitable progressive scheme from various sampling plans. A real-life situation representing the tensile strength of polyester fibres is used to show the application of the recommended work in a real-world scenario.
Testing gravity with realistic gravitational waveforms in Pulsar Timing Arrays
Authors: Hu Wayne , Liang Qiuyue , Lin Meng-Xiang , Trodden Mark
Published: December 2024

We consider the effects of relaxing the assumption that gravitational waves composing the
stochastic gravitational wave background (SGWB) are uncorrelated between frequencies in analyses
of the data from Pulsar Timing Arrays (PTAs). While uncorrelated monochromatic plane waves are
often a good approximation, a background composed of unresolved astrophysical sources cannot be
exactly uncorrelated since an infinite plane wave propagates no temporal signal. We consider how
relaxing this assumption allows us to extract potential information about modified dispersion
relations and other fundamental physics questions, as both the group and phase velocity of waves
become relevant. After developing the formalism we carry out simple Gaussian wavepacket examples
and then consider more realistic waveforms, such as that from binary inspirals. When the
frequency evolves only slowly across the PTA temporal baseline, the monochromatic assumption at an
effective mean frequency remains a good approximation and we provide scaling relations that
characterize its accuracy.
Cosmological constraints from calibrated Ep
- E
iso gamma-ray burst correlation by using DESI 2024 data release
Authors: Alfano Anna Chiara , Luongo Orlando , Muccino Marco
Published: December 2024

Recent outcomes by the DESI Collaboration have shed light on a possible slightly evolving
dark energy, challenging the standard ΛCDM paradigm. To better understand dark energy
nature, high-redshift observations like gamma-ray burst data become essential for mapping the
universe expansion history, provided they are calibrated with other probes. To this aim, we
calibrate the Ep
- E
iso (or Amati) correlation through model-independent Bézier
interpolations of the updated Hubble rate and the novel DESI data sets. More precisely, we provide
two Bézier calibrations: i) handling the entire DESI sample, and ii) excluding the point at
z
eff = 0.51, criticized by the recent literature. In both the two options, we let the comoving
sound horizon at the drag epoch, rd
, vary in the range rd
∈ [138, 156] Mpc. The Planck
value is also explored for comparison. By means of the so-calibrated gamma-ray bursts, we thus
constrain three dark energy frameworks, namely the standard ΛCDM, the ω
0CDM and
the ω
0
ω
1CDM models, in both spatially flat and non-flat universes. To do so, we
worked out Monte Carlo Markov chain analyses, making use of the Metropolis-Hastings
algorithm. Further, we adopt model selection criteria to check the statistically preferred
cosmological model finding a preference towards the concordance paradigm with a zero curvature
parameter. Nonetheless, the criteria also show a weak preference towards the non-flat ΛCDM
and the flat ω
0CDM scenario, leaving open to the possibility of such models as
alternatives to the flat concordance paradigm. Finally, we compared the constraints got from the
prompt emission Ep
- E
iso correlation with those from the prompt-afterglow emission
LX
- TX
- Lp
correlation.
Discerning the Very-high-energy Component via the Variation of γ-Rays in PKS 1510−089
Authors: Deng Junhao , Jiang Yunguo
Published: December 2024

The discovery and identification of very-high-energy (VHE) γ-ray emission of blazars is important for understanding active galactic nucleus jets. Based on Fermi-LAT observations, we find that PKS 1510−089 exhibits a softer-when-brighter trend at the low γ-ray flux level and changes to the harder-when-brighter trend at the high γ-ray flux level. Such a trend transition could be naturally explained by the presence of the VHE component, recently confirmed by the H.E.S.S. Collaboration. To reproduce the trend transition, we construct a two-component model that includes the high-energy (HE) component and the VHE component and consider two variation mechanisms including the change of the Doppler factor and the intrinsic peak frequency. The result is that such a trend transition in the Fermi-LAT range can be better explained by the shift of the peak frequency of the HE component. Combining the broadband spectral energy distribution analysis, we suggest that the HE component may originate from the jet at the broad-line region scale, and the VHE component may originate from the jet at the dust torus scale. The advantage of the spectral variation method enables us to discover the rich VHE emission across blazars.
Enhanced pedestal transport driven by edge collisionality on Alcator C-Mod and its role in regulating H-mode pedestal gradients
Authors: Miller M.A. , Hughes J.W. , Rosenthal A.M. , Mordijck S. , Reksoatmodjo R. , Wigram M. , Dunsmore J. , Sciortino F. , Wilcox R.S. , Odstrčil T.
Published: December 2024

Experimental measurements of plasma and neutral profiles across the pedestal are used in conjunction with 2D edge modeling to examine pedestal stiffness in Alcator C-Mod H-mode plasmas. Enhanced D

α
experiments on Alcator C-Mod observed pedestal degradation and loss in confinement below a critical value of net power crossing the separatrix,

P

net

=

P

net

crit

≈
2.3

MW, in the absence of any external fueling. New analysis of ionization and particle flux profiles reveal saturation of the pedestal electron density,

n

e

ped

, despite continuous increases in ionization throughout the pedestal, inversely related to

P

net

. A limit to the pedestal

∇

n

e

emerges as the particle flux,

Γ

D

, continues to grow, implying increases in the effective particle diffusivity,

D

eff

. This is well-correlated with the separatrix collisionality,

ν

sep

∗

and a turbulence control parameter, α

t
, implying a possible transition in type of turbulence. The transition is well correlated with the experimentally observed value of

P

net

crit

. SOLPS-ITER modeling is performed for select discharges from the power scan, constrained with experimental electron and neutral densities, measured at the outer midplane. The modeling confirms general growth in

D

eff

, consistent with experimental findings, and additionally suggests even larger growth in χ

e
at the same

P

net

crit

.
A Time-over-Threshold asynchronous front-end in 28 nm CMOS for the readout of pixel detectors in extreme radiation environments
Authors: Gaioni L. , Galliani A. , Ratti L. , Re V. , Traversi G. , Falchieri D. , Frontini L. , Stabile A.
Published: December 2024

This work describes the design, in a 28 nm CMOS technology, of a front-end channel for the readout of pixel sensors in future particle accelerators. The channel being developed leverages the Time-Over-Threshold technique for the numerical conversion of the detector signal amplitude, and includes a low-noise charge sensitive amplifier featuring a compact gain stage architecture. The front-end circuit features an equivalent noise charge not exceeding 70 electrons r.m.s. for a detector capacitance of 50 fF, with a threshold dispersion of the order of 20 electrons r.m.s. A prototype chip including a matrix of 8x32 readout channels has been submitted for fabrication. The design of the front-end channel, together with the main simulation results, is discussed in the paper.
MLEM-based image reconstruction algorithm for fast neutron scattering imaging
Authors: Shin Jimin , Sim Hayoung , Shin Sunlee , Seo Hee , Kim Soo Mee
Published: December 2024

Fast neutrons preserve the initial source information (e.g., position, energy, and time)
due to their relatively low probability of interaction with surrounding materials and their
straight path. When measuring fast neutrons using scattering reactions, there is no need to slow
them down to thermal neutrons. This allows for the obtainment of more accurate information. A
neutron scattering imager usually consists of two pixelated scatter detectors. The energy and
scattering angle of the neutrons can be determined from the energy of the protons produced by the
scattering reaction in the first detector, the time of flight between the two detectors, and the
distance between the interaction positions. From these measured quantities, conical surfaces can
be drawn, and the source location can be determined roughly from the overlapping of all such
surfaces drawn. Maximum Likelihood Expectation Maximization (MLEM) is an iterative statistical
algorithm to reconstruct the source distribution from the measured events in the neutron
scattering imager. In this study, we developed an MLEM algorithm for fast neutron (≤ 20 MeV) scattering image reconstruction using a system matrix with consideration of the scattering
cross-section and angular resolution. Then, we compared the resolution of the MLEM images with
that of simple back-projection (SBP) images.
Performance of the DAQ system of the PANDA Micro-Vertex Detector
Authors: Caselle M. , Manzhura O. , Calvo D. , Dellacasa G. , Chilingaryan S. , Cossio F. , Kopmann A. , Lenta F. , Mazza G. , Peter M. , Sidorenko V. , Stockmanns T. , Tröll N. , Unger K.L. , Zaunick H.-G. , Becker J. , Brinkmann K.-T. ,   the PANDA collaboration
Published: December 2024

The Micro-Vertex Detector (MVD) is the innermost subdetector of the PANDA (anti-Proton ANnihilations at DArmstadt) detector at FAIR. Its microstrip sensors are read out by custom front-end electronics called ToASt (Torino ASIC for Strip readout) [1]. The ToASt chips are locally managed by an MDC (Module Data Concentrator) [2]. The MDC processes incoming event data and forwards them to the off-detector readout cards based on the AMC (Advanced Mezzanine Card) standard. Both the MDC and the AMC readout card are currently under development at KIT [3].
The complete readout chain, including the double-sided microstrip sensor read by the ToASt chips and the FPGA implementation of the MDC, was successfully tested during a 2023 beam test at COSY (Forschungszentrum Jülich). This proof-of-concept validation of the MDC logic paves the way for the forthcoming ASIC version of the MDC, which is planned for submission in February 2025.
Extensive performance characterization of the current readout chain has been achieved with the MDC-FPGA optically connected to an AMD-Xilinx ZCU102 evaluation card [4], which emulates the AMC off-detector card, through a Versatile Link+ Demo Board (VLDB+) [5].
This contribution presents the MDC-ASIC design, its integration with both the front-end and back-end electronics and the performance results of the complete readout chain.
Effect of synthesis strategies on morphology and antibacterial properties and photocatalytic activity of graphitic carbon nitride (g-C3N4)
Authors: Anbarteh Rojin , Aftabi-Khadar Maryam , Hosseini-Hosseinabad Seyed Morteza , Seza Ashkan , Rahmani Fard Soheil , Minaeian Sara
Published: December 2024

Different morphologies of graphitic carbon nitride (g-C3N4), including bulk g-C3N4 (B-CN), ultrathin nanosheet g-C3N4 (N-CN), and porous g-C3N4 (P-CN) were synthesized through a facile one-step approach. They were then employed as efficient photocatalysts under visible light to degrade methylene blue and deactivate Staphylococcus aureus (S. aureus) and Escherichia coli (E. coli) bacteria. The synthesized powders were characterized using various industry standard techniques and field emission scanning electron microscopy (SEM) analysis successfully represented the various morphologies of g-C3N4. Furthermore, the antibacterial activities of synthesized samples were examined, and the results revealed that B-CN, N-CN, and P-CN powders could eliminate around 64%, 82%, and 99% of E. coli under visible light irradiation and about 30%, 56, and 67% in dark conditions. On the other hand, the bacterial reduction rate of S. aureus was approximately 61%, 74%, and 99% for B-CN, N-CN, and P-CN powders under visible light irradiation and about 38%, 60%, and 77% in dark conditions. The SEM analysis revealed that P-CN caused E. coli and S. aureus bacteria to rupture, completely separating their internal contents from the cell membrane. g-C3N4 photocatalytic antibacterial agents can be utilized as a unique potential solution for nosocomial infection management.
An injectable sodium-mangiferin homopolymeric hydrogel accelerated skin full-thickness wound healing in guinea pig model
Authors: Wang Ning-Xiang , Huang Mei-Rong , Huang Min , Lv Jun-Mei , Wei Pei-Ning , Li Sun-Han , Ding Shilei , Yang Tao
Published: December 2024

In the treatment of joints, mucosa, and full-thickness wounds, traditional implant surgery presents not only inconvenience but also a significant risk of wound infection. Additionally, the pharmaceutical application of mangiferin (MGF) has been severely restricted due to its poor water solubility. In this study, we report the synthesis and characterization of sodium-mangiferin (MGF-Na(S)) using the salt formation method. This novel compound exhibits a solubility of up to 80 mg ml−1, which is remarkably 800 times higher than that of MGF. Subsequently, MGF-Na(S) was combined with water to synthesize an injectable sodium-mangiferin homopolymeric hydrogel (MGF-Na(HG)). The hydrogel was further characterized, and its wound-healing properties were investigated. The results indicate that MGF-Na(HG) effectively extends the residence time of therapeutic agents on the wound surface, thereby enhancing wound healing. Moreover, this hydrogel forms a protective gel layer that prevents exogenous bacterial reinfection, providing an optimal environment for wound healing. Furthermore, the hydrogel demonstrated excellent self-healing and injectable properties, highlighting its potential for managing postoperative wounds. The successful utilization of this injectable, self-healing, and antibacterial MGF-Na(HG) in wound healing offers a novel approach for the application of MGF.