bluuebunny/crossref_metadata_2025_split huggingface dataset:
Probe of axion-like particles in vector boson scattering at a muon collider
Authors: İnan S C , Kisselev A V 
Published: July 2023

Abstract
We have examined the sensitivity of the axion-like particles (ALP) couplings to electroweak gauge bosons in the diphoton production at a future muon collider. The collisions at the μ
+
μ
− energies of 3 TeV, 14 TeV, and 100 TeV are addressed. The differential cross sections versus the invariant mass of the final photons and total cross section versus minimal diphoton invariant mass are presented. We have derived the exclusion regions for the ALP-gauge boson coupling. The obtained bounds are much stronger than the current experimental bounds in the ALP mass region 10 GeV to 10 TeV. The partial-wave unitarity constraints on the ALP-gauge boson coupling are estimated. We have shown that the unitarity is not violated in the region of the ALP coupling studied in the present paper.
The decay A
0 → h
0
Z(∗) in the inverted hierarchy scenario and its detection prospects at the large hadron collider
Authors: Akeroyd A G , Alanazi S , Moretti Stefano 
Published: July 2023

Abstract
Searches are being carried out at the large hadron collider (LHC) for the decay of the CP-odd scalar (A
0) in two-Higgs-doublet models (2HDMs) with natural flavour conservation (NFC) in the channel A
0 → h
0
Z (with

m

h

0

=
125

GeV

and Z on-shell). In the absence of any signal, limits on the parameter space of

[
tan
β
,
cos
(
β
−
α
)
,

m

A

0

]

in each 2HDM are derived for

m

A

0

>
225

GeV

. In this work, we consider the scenario of inverted hierarchy with

m

h

0

<
125

GeV

and

m

H

0

=
125

GeV

in which the decay A
0 → h
0
Z(∗) (i.e. including the case of an off-shell Z) can have a large branching ratio in the 2HDM (Type I) for

m

A

0

<
225

GeV

. We calculate the signal cross section

σ
(
gg
→

A

0

)

×
BR
(

A

0

→

h

0

Z
(

∗

)
)
×
BR
(

h

0

→
b

b

¯

)

in the 2HDM (Type I) with NFC and compare its magnitude with the cross section for the case of normal hierarchy (

m

h

0

=
125

GeV) that is currently being searched for at the LHC. For the experimentally unexplored region

m

A

0

<
225

GeV it is shown that the above cross section for signal events in the scenario of inverted hierarchy can be of the order of a few picobarns. Such sizeable cross sections are several orders of magnitude larger than the cross sections for the case of normal hierarchy, thus motivating an extension of the ongoing searches for A
0 → h
0
Z(∗) to probe the scenario of inverted hierarchy.
Revisiting proton–proton fusion in chiral effective field theory
Authors: Acharya Bijaya , Marcucci Laura Elisa , Platter Lucas 
Published: July 2023

Abstract
We calculate the S-factor for proton–proton fusion using chiral effective field theory interactions and currents. By performing order-by-order calculations with a variety of chiral interactions that are regularized and calibrated in different ways, we assess the uncertainty in the S-factor from the truncation of the effective field theory expansion and from the sensitivity of the S-factor to the short-distance axial current determined from three- and four-nucleon observables. We find that S(0) = (4.100 ± 0.024(syst) ± 0.013(stat) ± 0.008(g

A
)) × 10−23 MeV fm2, where the three uncertainties arise, respectively, from the truncation of the effective field theory expansion, use of the two-nucleon axial current fit to few-nucleon observables and variation of the axial coupling constant within the recommended range. The increased value of S(0) compared to previous calculations is mainly driven by an increase in the recommended value for the axial coupling constant and is in agreement with a recent analysis based on pionless effective field theory.
Anisotropy of upper critical fields and interface superconductivity in FeSe/SrTiO3 grown by PLD
Authors: Kobayashi Tomoki , Nakagawa Hiroki , Ogawa Hiroki , Nabeshima Fuyuki , Maeda Atsutaka 
Published: July 2023

Abstract
In this study, we grow FeSe/SrTiO3 with thicknesses of 4–19 nm using pulsed laser deposition and investigate their magneto-transport properties. The thinnest film (4 nm) exhibit negative Hall effect, indicating electron transfer into FeSe from the SrTiO3 substrate. This is in agreement with reports on ultrathin FeSe/SrTiO3 grown by molecular beam epitaxy. The upper critical field is found to exhibit large anisotropy (

γ
>

11.9), estimated from the data near the transition temperature (

T

c

). In particular, the estimated coherence lengths in the perpendicular direction are 0.15–0.27 nm, which are smaller than the c-axis length of FeSe, and are found to be almost independent of the total thicknesses of the films. These results indicate that superconductivity is confined at the interface of FeSe/SrTiO3.
Quasi-harmonic approach to evaluate pyroelectric properties in Janus CrSeBr monolayer
Authors: Jain Ayushi , Mandal Dipankar , Bera Chandan 
Published: July 2023

Abstract
Two-dimensional materials are emerging as promising dielectric materials and have enormous possibilities in wearable micro and nanoelectronics, sensor, and detectors. The theoretical calculation is performed to investigate the pyroelectric coefficient and pyroelectric figure of merit (FOM) of Janus CrSeBr monolayer. Quasi-harmonic approximation (QHA) is used to calculate primary (p1) and secondary (p2) pyroelectric coefficients. Spontaneous polarization is calculated for different temperatures using QHA. Pyroelectric coefficient (1.21 µC m−2 K at 300 K) is obtained for CrSeBr monolayer, which is

∼

5

times higher compared to MoSSe monolayer. A high FOM is found for CrSeBr monolayer

(

F
v

=
0.035

m2 C−1),

(

F
i

=
1.97

pm V−1). High FOM for voltage responsivity of CrSeBr monolayer could be beneficial for several commercial applications.
A machine learning approach for correcting glow curve anomalies in CaSO4:Dy-based TLD dosimeters used in personnel monitoring
Authors: Pathan Munir S , Pradhan S M , Selvam T Palani , Sapra B K 
Published: July 2023

Abstract
The study presents a novel approach to analysing the thermoluminescence (TL) glow curves (GCs) of CaSO4:Dy-based personnel monitoring dosimeters using machine learning (ML). This study demonstrates the qualitative and quantitative impact of different types of anomalies on the TL signal and trains ML algorithms to estimate correction factors (CFs) to account for these anomalies. The results show a good degree of agreement between the predicted and actual CFs, with a coefficient of determination greater than 0.95, a root mean square error less than 0.025, and a mean absolute error less than 0.015. The use of ML algorithms leads to a significant two-fold reduction in the coefficient of variation of TL counts from anomalous GCs. This study proposes a promising approach to address anomalies caused by dosimeter, reader, and handling-related factors. Furthermore, it accounts for non-radiation-induced TL at low dose levels towards improving the dosimetric accuracy in personnel monitoring.
Optical fiber reflectometry detecting static and dynamic Rayleigh spectra
Authors: Zhang Chao , Ito Fumihiko , Yoshimura Yuichi 
Published: July 2023

Abstract
Civil structures e.g. bridges, tunnels, and dams are essential to human societies. Currently, these complex engineered structures are challenged by aging issues. It is crucial to monitor the conditions of such structures in realtime to ensure their protection and conduct sufficient maintenance and rehabilitation when they begin to show omens of degradation or damage. Observation of Rayleigh scattering spectra from optical fibers using fiber Rayleigh reflectometry enables distributed sensing of static and dynamic strain in structural health monitoring for civil structures. Its key performance indices are the spatial resolution, the strain dynamic range, the measurement range, and the refresh rate. This article reviews tunable-wavelength optical time-domain reflectometry and coherent optical frequency-domain reflectometry and discusses the performance indices of each method in terms of the performance indices listed above. After analytical derivation, we have found that signal-to-noise ratios of both schemes are the same, which is a valuable discovery. In addition, we enumerate and review recent major industrial developments of both schemes.
Discrete element approach to simulate coupled hygrothermal transfer: application to conventional and composite materials
Authors: Ammar A , Leclerc W , Haddad H , Jbeli A , Guessasma M 
Published: July 2023

Abstract
This contribution deals with the development of a numerical approach based on discrete element method to study the hygrothermal behaviour of conventional and composite materials. For this purpose, we consider the context of magnesium aluminate and polyamide 6 reinforced with 30% of short glass fibre respectively. A coupled hygrothermal model based on boundary layer theory and the analogy between the Fickian mass and heat transfers is proposed. In addition, the original Halo approach introduced in the context of heat conduction is adapted to determine water concentration gradient fields with a suitable level of description. The proposed model is validated in terms of water concentration and water gradient fields for both materials by comparison with numerical and experimental results through the modelling of drying and absorption processes. Results exhibit the relevance of the proposed approach to provide such information with a suitable level of precision.
Quantitative characterization of hierarchical multiscale surfaces of micro and nanostructured materials
Authors: Papavieros G , Constantoudis V , Vouroutzis N , Gogolides E 
Published: July 2023

Abstract
Hierarchical surfaces have recently attracted a lot of interest, mainly due to their ability to exhibit multifunctionality combining different properties. However, despite the extensive experimental and technological appeal of hierarchical surfaces, a systematic and thorough quantitative characterization of their features is still missing. The aim of this paper is to fill this gap and build a theoretical framework for the classification, identification and quantitative characterization of hierarchical surfaces. The main questions addressed in the paper are the following: given a measured experimental surface how can we detect the presence of hierarchy, identify the different levels comprising it and quantify their characteristics? Special emphasis will be given on the interaction of different levels and the detection of the information flow between them. To this end, we first use a modeling methodology to generate hierarchical surfaces of a wide spectrum of characteristics with controlled features of hierarchy. Then we applied the analysis methods based on Fourier transform, correlation functions and multifractal (MF) spectrum properly designed to this aim. The results of our analysis reveal the importance of the hybrid use of Fourier and correlation analysis in the detection and characterization of different types of surface hierarchy as well as the critical role of MF spectrum and higher moment analysis, in the detection and quantification of the interaction between hierarchy levels.
Sparked ZnO nanoparticles-based electrochemical sensor for onsite determination of glyphosate residues
Authors: Traiwatcharanon Pranlekha , Velmurugan Sethupathi , Zacharias Margit , Wongchoosuk Chatchawal 
Published: July 2023

Abstract
Glyphosate (N-(phosphonomethyl)glycine) is well known nonselective and broad-spectrum herbicide that has been extensively used in agricultural areas around the world to increase agricultural productivity. However, the utilization of glyphosate can cause environmental contamination and health problems. Therefore, the detection of glyphosate with a fast, low-cost, and portable sensor is still important. In this work, the electrochemical sensor has been developed by modifying of working surface on the screen-printed silver electrode (SPAgE) with a mixtures solution between zinc oxide nanoparticles (ZnO-NPs) and poly(diallyldimethylammonium chloride) (PDDA) by the drop-casting process. The ZnO-NPs have been prepared based on a sparking method by using pure zinc wires. The ZnO-NPs/PDDA/SPAgE sensor shows a wide range of glyphosate detection (0 μM–5 mM). The limit of detection of ZnO-NPs/PDDA/SPAgE is 2.84 μM. The ZnO-NPs/PDDA/SPAgE sensor exhibits high selective towards glyphosate with minimal interference from other commonly used herbicides including paraquat, butachlor-propanil and glufosinate-ammonium. Furthermore, the ZnO-NPs/PDDA/SPAgE sensor demonstrates a good estimation of glyphosate concentration in real samples such as green tea, corn juice and mango juice.
Fully convolutional neural network and PPG signal for arterial blood pressure waveform estimation
Authors: Zhou Yongan , Tan Zhi , Liu Yuhong , Cheng Haibo 
Published: July 2023

Abstract

Objective. The quality of the arterial blood pressure (ABP) waveform is crucial for predicting the value of blood pressure. The ABP waveform is predicted through experiments, and then Systolic blood pressure (SBP), Diastolic blood pressure, (DBP), and Mean arterial pressure (MAP) information are estimated from the ABP waveform. Approach. To ensure the quality of the predicted ABP waveform, this paper carefully designs the network structure, input signal, loss function, and structural parameters. A fully convolutional neural network (CNN) MultiResUNet3+ is used as the core architecture of ABP-MultiNet3+. In addition to performing Kalman filtering on the original photoplethysmogram (PPG) signal, its first-order derivative and second-order derivative signals are used as ABP-MultiNet3+ enter. The model’s loss function uses a combination of mean absolute error (MAE) and means square error (MSE) loss to ensure that the predicted ABP waveform matches the reference waveform. Main results. The proposed ABP-MultiNet3+ model was tested on the public MIMIC II databases, MAE of MAP, DBP, and SBP was 1.88 mmHg, 3.11 mmHg, and 4.45 mmHg, respectively, indicating a small model error. It experiment fully meets the standards of the AAMI standard and obtains level A in the DBP and MAP prediction standard test under the BHS standard. For SBP prediction, it obtains level B in the BHS standard test. Although it does not reach level A, it has a certain improvement compared with the existing methods. Significance. The results show that this algorithm can achieve sleeveless blood pressure estimation, which may enable mobile medical devices to continuously monitor blood pressure and greatly reduce the harm caused by Cardiovascular disease (CVD).
Calculated cross sections for electron collisions with the BeN molecule
Authors: Chakrabarti K , Dinda S 
Published: July 2023

Abstract
We report a low energy electron collision calculation with the BeN molecule in its X

4

Σ
−

ground state using the molecular R-matrix method at a single geometry, namely, the equilibrium

R
e

=
3.045

a
0 of the molecule. Using a suitable target model, we have calculated the elastic cross section and cross sections for electron impact excitation in several low-lying excited states of BeN. Cross sections for electron impact dissociation is derived from the electronic excitation cross sections. In addition, molecular data on bound sates of BeN and e-BeN negative ion resonances and widths at the target equilibrium Re
that may be relevant for other studies are also provided.
Optimization of elastic wave propagation in a reconfigurable medium by genetic algorithms with adaptive mutation probability
Authors: Rus Janez , Fleury Romain 
Published: July 2023

Abstract
We introduce a reconfigurable medium for the manipulation of elastic propagation properties of Lamb waves. It is based on a shape memory polymer (SMP) with temperature-dependent Young’s modulus. Waves are excited by a laser pulse and detected by a laser vibrometer. A two-dimensional temperature field is controlled by a scanning heating laser. We use genetic algorithms to determine optimal distributions of mechanical properties for the following criteria: the wave amplitude has to be maximized at a given location and at the same time minimized at one or two other locations. Due to the reconfigurability of the medium, the optimization process is performed directly on the object of optimization, and not on a numerical or analytical representative, based on a direct measurement of the fitness. The optimized configuration makes the waves propagate away from (or around) the point of minimization towards the point of maximization. We improve the genetic algorithm by adapting the mutation probability of individual genes according to specific criteria, which depend on the surrounding genes (distributed in two dimensions). This provides the advantages: concentrating the mutations in the areas of genetic inconsistencies and counterbalancing the error of the fitness measurement. The method is applicable for the intelligent design of wave energy harvesters, ultrasonic transducers, and analogue wave computing devices.
The effect of temperature on guided wave signal characteristics in presence of disbond and delamination for health monitoring of a honeycomb composite sandwich structure with built-in PZT network
Authors: B Ramana Raja , Patil Sheetal , Kashyap Pankhi , Tallur Siddharth , Banerjee Sauvik 
Published: July 2023

Abstract
Guided wave (GW) based structural health monitoring (SHM) techniques being developed by researchers frequently use amplitude and group velocity variations between healthy and damage-affected GW modes to detect and localise damage. Nonetheless, external variables such as temperature and moisture influence these features, which were not considered in previous studies, particularly in the presence of damage in honeycomb composite sandwich structures (HCSSs). Therefore, a coordinated numerical and experimental study was carried out in an effort to examine the characteristics of GW propagation in an HCSS for two damages: a disbond between the face sheet and the core, and delamination between the face sheet layers for a temperature range of 0 ∘C–90 ∘C. Computationally efficient two-dimensional numerical models were developed using COMSOL Multiphysics that takes into account a variety of temperature-related phenomena, such as thermal stresses and changes in the material properties of honeycomb sandwich and piezoelectric wafer transducers (PZTs). The amplitude and group velocity of the fundamental anti-symmetric (A0) mode are found to increase in the presence of a disbond and decrease in the presence of face sheet delamination. However, it is observed that there is a linear decrease in the amplitude of A0 mode for both the healthy and damaged cases with an increase in temperature. Since the A0 mode is widely employed for interrogation due to its defect sensitivity, an amplitude and group velocity adjustment equation with temperature change is proposed. Finally, considering the amplitude difference of normalised A0 mode, the two damages are localised within a network of PZTs by using a probability-based signal difference coefficient method, which is found to be efficient and reliable for SHM of HCSS under variable temperature conditions.
Smart fault detection of HTS coils using artificial intelligence techniques for large-scale superconducting electric transport applications
Authors: Yazdani-Asrami Mohammad , Fang Lurui , Pei Xiaoze , Song Wenjuan 
Published: July 2023

Abstract
Superconducting coil is an essential and critical component in any superconducting apparatus used in large-scale power applications such as in superconducting machines of propulsion systems, in fault current limiters of the distribution system for future cryo-electric aircraft, or in windings of superconducting transformers for power grid applications. The superconducting coils in winding of large-scale power devices operate in kind of harsh environments from both temperature—considering liquid hydrogen or gaseous helium as coolant—(thermal stress) and electro-magneto-mechanical stress, point of views. Reliable operation of the coils in winding is of vital importance for the reliability of the superconducting device and the safety of the application that the device is used for. If the superconducting coil confronts a fault or an abnormal condition in the laboratory-level operation, it is straightforward to test the coil by measuring its critical current, AC loss, etc, to find whether it is damaged or not. However, there would be an urgent need to have faster and more intelligent fault detection and condition monitoring approaches with the possibility to become fully autonomous and real-time, in large-scale power applications, especially in sensitive applications such as in future cryo-electric aircraft, or in the fusion industry. To reach such intelligent fault-finding approaches, artificial intelligence-based techniques have been foreseen to be a promising solution. In this paper, we have developed an intelligent fault detection technique for finding a faulty superconducting coil, named the frequency-temporal classification method. This method has two main steps: first, this paper utilizes the discrete Fourier transform and independent component analysis to convert measurement signals of the healthy and faulty coils from (1) the time-series domain to the frequency domain; and (2) into time-series source signals. Second, this paper trains the support-vector machine using the derived frequency components. This trained model is then used for making fault detection for other superconducting coils. The developed technique can classify a fault with 99.2% accuracy.
Low-resistance joints for YBCO-coated conductors with Ag nanoparticle paste
Authors: Wang Wentao , Wang Ming , Han Leilei , Chen Yu , Liu Lian , Yang Fan , Li Mingyu , Yu Zhou , Zhao Yong 
Published: July 2023

Abstract
Due to the limited available piece length of YBCO-coated conductors (i.e. tapes or wires) and the different requirements for magnetic field, joints are inevitable for manufacturing high-temperature superconducting magnets. In this study, a sintering nano-silver (Ag) process was developed and used to connect YBCO tapes stabilized by anAg layer with low-temperature and short-time sintering of Ag nanoparticle (NP) paste. The thermodynamic characteristics of Ag NP paste were explored using a TG/DSC setup. The effects of sintering temperature, mechanical pressure and lapped length on microstructures and electrical properties of joints were comprehensively investigated. It is found that the pre-volatilization of low-boiling-point solvent in the paste is beneficial to improve the densification of sintered structure, thus contributing to increasing the critical current I
c of the joint. With increasing sintering temperature, the I
c of the joint will be close to that of the virgin tape, and the joint resistance experiences small fluctuations, but joint connectivity is enhanced. As the temperature reaches 205 °C, I
c decreases to 84% of the virgin tape, and joint resistance increases obviously. In addition, the axial tension strength at room temperature is improved with the increase in mechanical pressure, while the resistance does not demonstrate distinct variation. Considering the electromechanical properties, the optimal joining process is determined as sintering at 180 °C and 30 MPa for 10 min. The joint with this technology possesses a closely connected interface and a well-sintered nano-Ag microstructure with pores. By further extending the lapped length, a YBCO joint resistivity as low as ∼10.56 nΩ cm2 is obtained, which is around a quarter of that of the soldering joint, and the process is much easier than that of the Ag diffusion joint.