bluuebunny/crossref_metadata_2025_split huggingface dataset:
Design of a novel gamma camera with large field of view for 16N diagnosis in the primary loop of nuclear reactor
Authors: Zhang Tao , Tang Lingzhi , Yan Yihong , Bai Xuejie , Wang Dongming , Sun Weiqiang , Jing Futing , Lv Huanwen , Hu Guang , Yan Mingfei , Hu Huasi 
Published: April 2024

The assessment of the concentration and distribution of l6N, derived from 16O in the cooling water exposed to neutron irradiation, is essential for ensuring radiation safety during nuclear reactor operation. The imaging method allows for the visualization of the intensity distribution of these l6N by capturing gamma-rays emitted during their decay process. However, the existing gamma camera is exclusively compatible with gamma-rays below 2 MeV. In this paper, a novel gamma camera featuring a thick double-conical penumbra aperture, a pixelated Lu1.8Y0.2SiO5:Ce scintillator array, and a position-sensitive photomultiplier tube is proposed to address this limitation. This innovative design offers a large field of view (FOV) and is suitable for high energy extended gamma source imaging. The optimization of key parameters of the camera was conducted, and a FOV of 60° and an angular resolution of up to 4.57° were achieved. Imaging simulations, including a simplified model of the primary loop of the pressurized-water reactor by GEANT4 code and image reconstruction using the expectation maximum algorithm, demonstrated that the proposed gamma camera could obtain a satisfactory spatial resolution for diagnosing the distribution of 16N in the primary loop of a nuclear reactor.
Metaphtonymy and semio-cognitive de-legitimation of Donald Trump in the meme discourse of The Daily Show with
Trevor Noah (January 2016–December 2019)
Authors: Elyamany Nashwa , Hamed Maha SalahEldien Mohamed 
Published: April 2024

Abstract
The current research endeavor extends scholarship on political satire and digital memes proposing a more nuanced
semio-cognitive analytical framework for the innovative political image macro memes pertinent to The Daily Show with
Trevor Noah (January 2016–December 2019). Premised on Martynyuk and Melescchenko’s (2021) conceptualization of
metaphtonymy and van Leeuwen’s
(2007) (de)-legitimation strategies, a corpus of 159 image macro meme instances from
The Daily Show with Trevor Noah’s (January 2016 to December 2019) has been examined to show how the
semio-cognitive de-legitimation of Donald Trump and his administration is materialized through creative
meme-inherent metaphtonymies. Key findings include the dominance of four meme-specific metaphtonymic patterns. In tandem, the
overlapping semio-discursive de-legitimation strategies of authorization, moral evaluation, rationalization, and
mythopoeisis are metaphtonymically encoded in the image macro memes of the show’s monologue to: (a) function
as highly medium-specific expressions that respond to challenging events based on thematic and structural templates, and (b)
provide a timely (and even reactionary) response to political debates, creating a negative view of Donald Trump to reduce his
legitimacy as the US president.
France’s “drôle de guerre”
Authors: Augé Anaïs 
Published: April 2024

AbstractThis paper sheds light on the sociopolitical polarisation reflected in the responses to a political metaphor, in French public discourse about covid-19. The aim is to uncover how polarisation may influence metaphorical representation of a political issue. The study focuses on the French President’s metaphor “we are at war”, in his announcement of the national lockdown. Responses to this “war” metaphor in public discourse are analysed following a combination of metaphor theories and argumentation theories. Results show that such responses transformed the ”war” metaphor into the “phoney war” metaphor for covid-19. This yielded four main arguments which 1.established causals links between covid-19 and policies, 2.partially endorsed the metaphor, 3.focused on the President’s discursive pattern, and 4.focused on the President’s status. It is argued that more research is needed into public reception to political discourse, in view of the arguments derived from resistance to metaphor.
Quark star matter in the color-flavor-locked state with a density-dependent quark mass model
Authors: Chu Peng-Cheng , Liu He , Li Xiao-Hua , Ju Min , Wu Xu-Hao , Zhang Xiao-Min 
Published: April 2024

Abstract
The properties of strange quark matter (SQM) and color-flavor-locked (CFL) quark matter are investigated in quark stars (QSs) at zero temperature case within confined-isospin-density-dependent-mass (CIDDM) model. The mass–radius relation of QSs are also studied by considering newly proposed mass–radius constraints in CFL phase. Our results indicate that we can obtain more stable and stiffer equation of state (EOS) by considering CFL phase within CIDDM model at zero temperature. While the GW190814's secondary component with a mass around 2.6 M
⊙ cannot be QSs within CIDDM model in SQM case, it can be well described as QSs by considering CFL phase within CIDDM model in this work. In particular, we further construct a density-dependent pairing energy gap to connect the EOS of SQM and CFL quark matter with constant pairing energy gap Δ, and the results indicate that by extending the paring energy gap to include density dependence, the mass–radius lines within CIDDM model can satisfy most of the mass–radius region constraints in recent pulsar observations.
Hausdorff dimension of recurrence sets
Authors: Hu Zhang-nan , Persson Tomas 
Published: April 2024

Abstract
We consider linear mappings on the 2-dimensional torus, defined by

T
(
x
)
=
A
x

(

mod

1
)

, where A is an invertible

2
×
2

integer matrix, with no eigenvalues on the unit circle. In the case

det
A
=
±
1

, we give a formula for the Hausdorff dimension of the set

{

x
∈

T

2

:
d

(

T

n

(
x
)

,
x
)

<

e

−
α
n

for infinitely many
n

}

.
A privacy preserving quantum aggregating technique with simulation
Authors: Sutradhar Kartick , Venkatesh Ranjitha 
Published: April 2024

Abstract
Quantum aggregation is a basic operation of secure multiparty quantum computation. All the existing techniques are based on the (n,n) threshold, where n is the total number of players. If any of them is corrupted then these techniques cannot execute correctly. However, the proposed technique is based on the (t,n) threshold. If the players are honest then this technique can perform the aggregation. This technique is based on the monotone span program, access structure, linear secret sharing, control-NOT gate, quantum Fourier transform, blind matrix, and Pauli operator. The proposed technique can aggregate the secrets securely and efficiently. We also simulate the proposed technique using IBM quantum computer to verify the correctness and feasibility.
SDR implementation of a light deep learning model based CNN for joint spectrum sensing and AMC
Authors: Nesraoui O , Teguig D , Sadoudi S 
Published: April 2024

Abstract
Automatic modulation classification (AMC) aims to blindly recognize the modulation type of a received signal in wireless systems. It is also a critical component of non-cooperative communication systems after the detection of the presence of a signal. In this paper, we introduce a robust approach, termed DET-AMC (joint Detection and Automatic Modulation Classification), employing Convolutional Neural Networks (CNNs) trained via transfer learning methodology. The main advantage of our approach is its ability to handle a wide range of modulation types, including 10 different schemes generated in Gnuradio and their detection using the same model. Through extensive experimentation, we evaluate the performance of our light CNN-based DET-AMC method across varying signal-to-noise ratio (SNR) levels, as well as in the presence of phase noise and frequency offset. We find that the CNN’s learned features, obtained through transfer learning, exhibit robustness, particularly in low SNR and various challenging conditions, leading to accurate modulation classification. In general, our approach outperforms existing methods by using the effectiveness of deep learning in capturing relevant discriminative features. Additionally, our model offers a robust solution for join detection and AMC by achieving an accurate probability of detection and modulation classification without the need for manual feature engineering or the consideration of frequency offset, phase noise or noise estimation. Our model achieves 100% accuracy for synthetic and real data at an SNR equal to -10 dB for detection, and 100% and 98% for classification of synthetic and real signals at −4 dB, respectively.
Physical adsorption of the Ba atom on Arn surfaces: spectroscopic and geometric properties
Authors: Slama Marwa , Issa Khaled , Ghalla Houcine , Issaoui Nourredine , Rhouma Mounir Ben El Hadj 
Published: April 2024

Abstract
Barium atoms cause several environmental and ecological dangers. Numerous techniques are employed to remove the Ba atom such as physisorption and solvation methods. In this work, we are interested in investigating and exploring the Ba atom’s physical adsorption on argon surfaces. We have tested several optimizations and we have found that the first range of Ar atoms (n = 1–12) presents more than 90% of the energy interaction between Ba and the adsorbent surface. Therefore, we started by computing and analyzing the potential energy surfaces (PESs) of BaArn molecules. Large basis sets and full Configurations Interaction (full-CI) with the pseudo-potential approach were used to perform the PES, the spectroscopic parameters, vibrational energy levels, and electric dipole moment (EDM) for the selected states. The structural properties and relative stability of Ba (6s2
1S)Arn (n = 1–13, 30, 44, and 54) clusters are determined using Monte Carlo simulation based on the Potential Model method (MC-PM). Several clusters (n > 4) were demonstrated to be stable using MC simulations, and the Ba atom is always present on the surface of the remaining Arn cluster. We have found a good concordance between our results and the available theoretical and experimental data. The spectroscopic information of these complexes can be used by experimental researchers for the investigation of optical mechanisms collision, especially the deformation of the Ba spectrum by collision with the argon surface.
S-box design based on logistic skewed chaotic map and modified Rabin-Karp algorithm: applications to multimedia security
Authors: Waheed Adil , Subhan Fazli 
Published: April 2024

Abstract
A substitution box (S-box) serves as the nonlinearity component in a symmetric key encryption scheme; it directly determines the performance and security level of ciphers. Thus, the construction of an S-box with superior performance and efficiency, specifically in terms of high cryptographic properties, is critical. This research proposes a novel method to construct the S-box using the skewed logistic chaotic map and modified Rabin-Karp rolling hash function without disturbing its mathematical structure. First, iterate the skewed logistic map by selecting a seed value and specifying the parameters to generate the chaotic values. The map’s sensitivity to initial conditions and parameters results in a seemingly random and unpredictable chaotic values. Second, hash the chaotic values using Rabin-Karp for generating sequences of numbers within a specific range (0–255 for an 8-bit S-box). Then an S-box is constructed using the hash values. Performance evaluations indicate that the S-box produced through our suggested approach exhibits superior performance, demonstrating robust resistance against various security threats, including but not limited to linear attacks, differential attacks, and others. To demonstrate the effectiveness of the constructed S-box, this paper goes on to employ it in an image encryption application. Security analyses reveal that the developed image encryption algorithm successfully encrypts diverse types of images, producing cipher images characterized by uniformly distributed histograms. Performance assessments illustrate its high-security level, surpassing several state-of-the-art encryption algorithms.
Sodium-based no-core fiber surface plasmon resonance sensor with high sensitivity and narrow FWHM
Authors: Zhang Zhibing , Li Shuguang , Yin Zhiyong 
Published: April 2024

Abstract
Since fiber-optic sensors using noble metal-excited surface plasmon resonance (SPR) effects have encountered bottlenecks in improving performance, we propose a fiber-optic sensor using sodium in combination with a no-core fiber (NCF) to measure both refractive index (RI) and temperature. We deposited sodium thin films on the surface of NCF optical fibers and protected them with polymethyl methacrylate (PMMA) or polydimethylsiloxane (PDMS) for RI sensing or temperature sensing. We performed computational simulations and performance analyses of the sensors using the finite element method, and the results show that the sodium-based SPR sensors have higher sensitivity, wider detection range, and narrower full width at half-maximum (FWHM) than the noble metal SPR sensors. SPR sensors with different sodium film thicknesses have different sensing characteristics, so we can get optical fiber sensors with more flexible transmission characteristics, which helps us arrange sensors more conveniently in practical applications. The simulation and numerical results show that when the sensor is used to measure RI, the average sensitivity of the sensor can reach 7977 nm RIU−1, the maximum sensitivity can reach 23100 nm RIU−1, the narrowest FWHM is 14.23 nm, and the maximum figure of merit (FOM) is 719.42 RIU−1 under different thicknesses of sodium film. The corresponding RI ranges from 1.32 to 1.41. When the temperature measurement range is 0 °C ∼ 100 °C, the average sensitivity can reach 7.86 nm °C−1, the maximum temperature sensitivity can reach 21.1 nm °C−1, and the narrowest FWHM is 17.84 nm. In summary, the proposed sodium-based SPR sensor has flexible and high-performance sensing characteristics, and our research work provides more powerful theoretical support for the application of sodium-based plasma devices.
Synthesis and characterization of myristic acid - infused Al2O3/CuO/MWCNT nanocomposites for energy storage and cooling applications
Authors: Venkatakrishnan Prabakaran , Palanisamy Ponnusamy 
Published: April 2024

Abstract
Phase change materials are highly effective in improving the thermal efficiency of a heat exchanger, making them a choice for enhancing renewable energy to achieve a feasible environment. In this study, myristic acid (MA) was used as a phase change material and aluminium oxide (Al2O3), copper oxide (CuO) of 2.5, 5, 10 wt % and multi-walled carbon nanotubes (MWCNT) of 1.0, 1.5, and 2 wt % were used as the nanoparticles to produce MA-embedded nanocomposite phase change material (NCPCM). The characterization studies, namely x-ray diffraction, Thermal Conductivity, field emission scanning electron microscope (FESEM), Fourier transform infrared spectroscopy (FTIR), Raman spectroscopy, Differential Scanning Calorimetry (DSC) and Thermogravimetric analysis (TGA) were performed on nanocomposite phase change materials to ensure their homogeneous distribution and property enhancement of the fabricated samples. In addition, a Computational Fluid Dynamics (CFD) analysis was conducted to assess the impact of NCPCM on the rates of solidification and melting. The field emission scanning electron microscopy analysis confirms the homogeneous distribution of micro/nanoparticles Al2O3, CuO, and MWCNT with MA. From the x-ray diffraction (XRD) analysis, the homogeneous nature of the fabricated NCPCMs was identified. Fourier transform infrared spectroscopy (FTIR) and Raman Spectroscopy results confirmed the absence of new particle formation due to the physical interaction between nanocomposites and myristic acid. The fabricated NCPCM samples were undergone 500 thermal cycles to ensure their thermal reliability. It is evident from the test results that the addition of nanoparticles to base PCM enhances the thermal properties. The thermal performance of 2 wt% MWCNT-embedded MA was superior to that of aluminium oxide and copper oxide. DSC results revealed that the 2 wt% MWCNT added MA possessed the highest variation of 8.6% in its latent heat storage value compared to pure MA and had a significant variation compared to other fabricated NCPCM compositions. Adding 2 wt% MWCNT to MA has increased the thermal conductivity of pure PCM from 0.15 W mK−1 to 0.38 W mK−1.
Kinetic behavior of secondary electrons in a magnetized voltage-driven discharge using combined rf/dc sources
Authors: Wen Hui , Sun Jing-Yu , Zhang Quan-Zhi 
Published: April 2024

Abstract
This study employed particle-in-cell/Monte Carlo simulations, along with test particle methods, to examine the characteristics of secondary electrons (SEs) in a voltage-driven discharge using combined rf/dc sources and operates in the presence of a magnetic field. The behavior of SEs is significantly influenced by the magnetic field, leading to the emergence of complex branches in temporal electron energy probability distributions and spatiotemporal electron density distributions within the sheath. The number of branches is directly correlated to the cyclotron period. Moreover, the application of a direct current (dc) source thickens the sheath at the dc biased electrode while attenuating the sheath on the opposite side. This leads to an asymmetrical modulation of the kinetic behavior of SEs in the two sheaths, ultimately resulting in a substantial increase in electron energy on the side of the dc biased electrode.
A comprehensive analysis of the ‘coming and going’ phenomenon of the projectile motion of a sphere under air resistance
Authors: DaSilva Claudio J 
Published: April 2024

Abstract
We have analyzed the ‘coming and going’ phenomenon of the projectile motion of a sphere using experimental data correlations that span the entire range of Reynolds numbers. We have modeled the drag force using an analytical expression for the drag coefficient and performed a numerical analysis to compute the critical angle as a function of the sphere’s initial speed, radius, and mass. Our results indicate that the critical angle behaves analogously to the drag coefficient as a function of the Reynolds number. This study is significant as it deals with a drag force not limited to any specific flow regime and may help undergraduate students and science instructors delve deeper into the subject.
Comprehensive investigation of Li-based novel quaternary Heusler LiTiPdZ (Z = Al, Ga, In) compounds for thermoelectric performance
Authors: Suktel Lokanksha , Saini Sapan Mohan 
Published: April 2024

Abstract
In the present article, we used Density Functional Theory and the Boltzmann transport equation to study the structural, electronic, and thermoelectric (TE) properties along with phonon dynamics of recently discovered LiTiPdZ (Z = Al, Ga, In) quaternary Heusler (QH) compounds. We applied generalized gradient approximations (GGA) for band structure and density of states (DOS) calculations. Comprehensive investigations of electronic structure reveal that an indirect band gap of 0.77 eV, 0.793 eV and 0.611 eV for LiTiPdAl, LiTiPdGa, and LiTiPdIn, is there reflecting the semiconducting nature of these compounds. We find that Pd-4d states contribute to the conduction band DOS while Ti-3d states contribute significantly to DOS near Fermi energy (EF) in both valence and conduction band. Phonon dispersion spectra show that all the studied compounds are dynamically stable, as obtained frequency is only in positive range. We have calculated thermoelectric properties up to a fairly high temperature (1600 K), to check the compatibility of these compounds for high temperature TE application. A high value of ZT (∼0.60 1600K) proposes these compounds as potential candidates for high temperature TE applications.
Thin and thick bubble walls II: expansion in the wall width
Authors: Mégevand Ariel , Membiela Federico Agustín 
Published: April 2024

Abstract
We study the dynamics of a cosmological bubble wall beyond the approximation of an infinitely thin wall.
In a previous paper, we discussed the range of validity of this approximation
and estimated the first-order corrections due to the finite width.
Here, we introduce a systematic method to obtain the wall equation of motion and its profile at each order in the wall width.
We discuss in detail the next-to-next-to-leading-order terms.
We use the results to treat the growth of spherical bubbles and the evolution of small deformations of planar walls.
Experimental determination of axion signal power of dish antennas and dielectric haloscopes using the reciprocity approach
Authors: Egge J. , Ekmedžić M. , Gardikiotis A. , Garutti E. , Heyminck S. , Kasemann C. , Knirck S. , Kramer M. , Krieger C. , Leppla-Weber D. , Martens S. , Öz E. , Salama N. , Schmidt A. , Wang H. , Wieching G. 
Published: April 2024

Abstract
The reciprocity approach is a powerful method to determine the expected signal power of axion haloscopes in a model-independent way. Especially for open and broadband setups like the MADMAX dielectric haloscope the sensitivity to the axion field is difficult to calibrate since they do not allow discrete eigenmode analysis and are optically too large to fully simulate. The central idea of the reciprocity approach is to measure a reflection-induced test field in the setup instead of trying to simulate the axion-induced field. In this article, the reciprocity approach is used to determine the expected signal power of a dish antenna and a minimal dielectric haloscope directly from measurements. The results match expectations from simulation but also include important systematic effects that are too difficult to simulate. In particular, the effect of antenna standing waves and higher order mode perturbations can be quantified for the first time in a dielectric haloscope.