bluuebunny/crossref_metadata_2025_split huggingface dataset:
Hollow-type plasma absorption probe for measurement of electron density in low pressure plasmas: a sheath thickness–insensitive technique
Authors: Lee SangHo , Kim SiJun , Park InYong , Eom GeonWoong , Seo Byonghoon , Hur Min , Kang WooSeok , You ShinJae , Kim Dae-Woong 
Published: December 2024

Abstract
We propose a hollow plasma absorption probe (PAP) designed to improve the accuracy of electron density measurement in low-pressure plasmas regardless of the sheath thickness on the planar probe surface. This improvement is achieved through an artificial hollow space acting as a thick sheath to bring the resonant absorption frequency (

f

PAP

) from the hollow PAP close to the surface wave resonant frequency (), insensitive to variation in sheath thickness. Electromagnetic simulations confirmed the efficiency of the hollow design, showing a minimized discrepancy between

f

PAP

and

f

SWR

even with the thin sheath. Optimal configurations with a coaxial core diameter of 5 mm and a hollow depth of 5 mm were found and tested in plasmas ranging from

5
×

10
8

c

m

−
3

to

5
×

10

10

c

m

−
3

. Comparative experiments employing a planar cutoff probe (CP) to directly measure

f

pe

demonstrated good agreement between the electron density derived from the hollow PAP and from the planar CP, compared to that from a conventional planar PAP.
Role of Fe–As banding in electronic structure of Co doped LiFeAs
Authors: Li Li , Zhang Zhihua , He Ming , Lin Long , Tao Hualong , Cui Yan , Wang Hongli , Wang Weifang , Zhou Qingping , Liu Qinghui , Zhou Shugong 
Published: December 2024

Abstract
Experiment shows that the maximum Co concentration of LiFeAs in the superconducting state is around 17%. First principles calculations show that the Fe–As bond length, c-axis length, and electronic structure change gently from 0% to 18% Co doping concentration, but suddenly undergo drastic changes at 20% Co doping. Unlike many 1111 and 122 type iron-based superconductors, the contribution of Fe 3p orbitals to N(E
F) has significantly surpassed that of As 4p orbitals. The rapid decrease in N(E
F) is associated with a sharp contraction of Fe–As bond, and Fe–As bond length has ability to independently adjust N(E
F). The sudden contraction of Fe–As bonds leads to a reverse Lifshitz transition in band, resulting in the fracture and severe shrinkage in the inner layer of the hole Fermi surface. The originally nested structure of the hole Fermi surfaces is destroyed, which may be the main reason for the termination of superconductivity.
Tuning optical and electronic properties of indanthrene derivatives with electron-withdrawing groups (–Cl, –NO2 and –C≡N) for enhanced organic solar cell performance: a DFT approach
Authors: Kushwaha Pankaj Kumar , Shatapathy Dinesh Kumar , Sharma Vinay , Srivastava Sunil Kumar 
Published: December 2024

Abstract
In this study, we focused on improving the electronic and optical properties of the reference compound indanthrene (R) by introducing electron-withdrawing groups (−Cl, −C≡N, −NO2). Density functional theory and time-dependent density functional theory calculations were performed using Gaussian 16 software to study indanthrene derivatives as electron acceptor materials. The electronic and optical properties of the designed molecules (M1-M8) were investigated through frontier molecular orbital analysis, UV-visible absorption spectra, density of states, and transition density matrix analysis, utilizing GaussView 6.0 and Multiwfn 3.8 software. The designed molecules exhibit absorption across the entire visible spectrum, with maxima extending up to ∼737 nm. Their electron affinity values range from 3.0 to 4.0 eV, surpassing the fullerene-based acceptor material. Among the designed molecules, M5 stands out with superior photovoltaic parameters, including a narrow optical band gap (∼1.68 eV), exciton binding energy (0.25 eV), higher electron affinity (3.35 eV), an extended excited state lifetime (17.0 ns) owing to its low electron and hole reorganization energies (λ

e
∼ 0.190 eV, and λ

h
∼ 0.134 eV), and improved short-circuit current density of ∼15.7 mA cm−2. The photovoltaic parameters and power conversion efficiency were assessed using the Scharber and Alharbi models. The calculated device parameters, including light harvesting energy and photovoltaic characteristics (Voc, FF, Jsc, and PCE), suggest that these molecules, with electron-withdrawing groups, show great potential for use as acceptors in organic solar cells, particularly in terms of stability and power conversion efficiency. Notably, M2 and M5, with their PCE values exceeding 16%, emerge as outstanding candidates for device performance, impressively outperforming the other designed molecules.
Enhancing optical properties and antimicrobial efficiency of polyamide-6 for medical applications
Authors: Ahmed Donia U , El-Bakary Mohammed A , El-Sayed Nayera M , Sadik Adel M 
Published: December 2024

Abstract
Polyamide-6 (PA-6) fibers are valued for their high mechanical strength and cost-effectiveness, but their inherent hydrophobicity restricts their applicability. To enhance functionality, a grafting process was applied at both low and high yields, enabling effective treatment of PA-6 fibers with silver nanoparticles (Ag NPs) to impart antimicrobial properties. An in situ approach was employed to embed Ag NPs within the PA-6 fibers. The antimicrobial efficacy of the modified fibers was assessed against multidrug-resistant (MDR) pathogens, including methicillin-resistant, extended-spectrum beta-lactamase-producing, and quinolone- and carbapenem-resistant strains, using the shake flask method with optical density measurements. Fourier-transform infrared spectroscopy (FTIR) characterized the chemical changes associated with grafting and Ag NP incorporation. Scanning electron microscopy (SEM) and energy-dispersive x-ray spectroscopy (EDX) provided insights into fiber morphology and elemental composition, verifying the successful surface loading of Ag NPs. The Multiple Beam Fizeau fringes technique was used to evaluate optical properties, such as refractive index and birefringence, as indicators of structural changes. Although grafting reduced the optical properties initially, subsequent Ag NP treatment restored them. The PA-6-g-PAA 7%-t-Ag NPs fibers exhibited superior optical properties relative to PA-6-g-PAA 20.7%-t-Ag NPs fibers, though with lower antimicrobial impact on sensitive organisms. Conversely, PA-6-g-PAA 20.7%-t-Ag NPs showed significant antimicrobial activity against MDR pathogens. As a result, PA-6-g-PAA 20.7% is identified as the optimal choice, balancing effective antimicrobial properties with enhanced optical performance, suggesting its potential in antimicrobial fiber applications for medical use.
Design and analysis of a quad-band perfect metamaterial absorber with enhanced sensing capabilities in the terahertz regime
Authors: Khalil Muhammad Amir , Hin Yong Wong , Islam Md Shabiul , Lo Yew Chiong , Hoque Ahasanul , Alenezi Abdulmajeed M , Soliman Mohamed S , Islam Mohammad Tariqul 
Published: December 2024

Abstract
This study presents the design and analysis of a Quad-band perfect metamaterial absorber (PMMA) with five distinct absorption peaks, achieving absorption rates consistently above 96%. The absorption performance is thoroughly examined by varying the structural parameters to elucidate the mechanisms underlying the multi-band absorption. Additionally, we investigate the sensing capabilities of the absorber by analyzing its response to changes in the refractive index and thickness of the analyte. Sensitivity and figure of Merit (FOM) are utilized to evaluate the sensing performance. The sensor demonstrates refractive index and thickness sensitivities of 1.5 THz RIU−1 and 0.5 THz RIU−1, respectively, with corresponding FOMs of 97.424 and 91.633. These results surpass those of prior terahertz regime designs, highlighting the superior sensing capabilities of the proposed absorber. The proposed design is promising for sensing, filtering, and stealth technology applications.
Second-order statistical characteristics of a radially polarized Gaussian Schell-model beam with elliptical optical vortex phase in a turbulent atmosphere
Authors: Li Bocheng , Xu Yonggen , Liu Wenli , Hao Nianchi , Zhao Liang 
Published: December 2024

Abstract
Based on the extended Huygens–Fresnel integral method, we have derived analytical formulae for the cross-spectral density matrix of a radially polarized Gaussian Schell-model beam with elliptical optical vortex phase (i.e., partially coherent radially polarized elliptical vortex (PCRPEV) beam) propagating through atmospheric turbulence, and have investigated the evolution laws of statistical characteristics such as the average intensity, degree of coherence (DOC), and degree of polarization (DOP) of the PCRPEV beam in turbulence. The results indicate that atmospheric turbulence causes the average intensity distribution of the PCRPEV beam to split and rotate during propagation, ultimately degenerating into a Gaussian-like distribution. Moreover, the PCRPEV beam with lower ellipticity, larger coherence length, and higher topological charge degenerates into a Gaussian-like beam at a slower rate in turbulence. Additionally, we also find that DOC distribution is related to topological charge, meaning that it can provide a new way to measure topological charge. In addition, we simulate the propagation of the PCRPEV beam through atmospheric turbulence using the complex screen and the multi-phase screens methods to verify the theoretical results. The research indicates that the simulation results are essentially consistent with the theoretical findings. These outcomes hold significant relevance for the advancement of free-space optical communication and remote sensing technologies.
Analysis and application of a 3D chaotic system with an extremely extensive range of amplitudes and offset boosting
Authors: Shi Shuaishuai , Lu Hanyu , Du Chuanhong , Zhang Zefeng , Liu Licai 
Published: December 2024

Abstract
The study of high-dimensional chaotic systems has been the subject of considerable research interest, whereas the complex characteristics of low-dimensional chaotic systems have been largely overlooked. A new 3 dimensional (3D) chaotic system containing only two kinds of nonlinear terms is constructed based on the Lorenz system to enrich the theory of chaotic systems and improve the complex properties of low-dimensional chaotic systems. The system lacks a symmetric structure; however, under the influence of the symmetric parameter α, the system attains a symmetric state and can produce attractors with a symmetric structure. Under the parameter β, the system can realize the regulation of amplitude, frequency, and nonlinear offset boosting of three signals simultaneously. The parameter γ can realize the control of two signal amplitude and frequency at the same time. The system always remains chaotic when the parameters β and γ are varied in a great range. In addition, this 3D chaotic system has offset boosting behavior in arbitrary single and multiple directions, and the offset constant has a wide range of values. These features provide great convenience for secure communications and weak signal engineering applications. Further, analog circuit simulations and DSP (Digital Signal Processor) hardware circuits confirm the parametric modulation of the system and the offset boosting behavior in any direction. Moreover, taking advantage of the extensive offset range, a synchronization controller is designed for the drive and response systems. Finally, the modulation of offsets with a wide range of values realizes the encrypted transmission of binary digital information and lays the foundation for future engineering applications.
Non-parametric full cross mapping (NFCM): a highly-stable measure for causal brain network and a pilot application
Authors: Yang Danni , Lin Wentao , Liu Minghui , Zhou Yuanfeng , Wang Yalin 
Published: December 2024

Abstract

Objective. Measuring causal brain network from neurophysiological signals has recently attracted much attention in the field of neuroinformatics. Traditional data-driven algorithms are computationally time-consuming and unstable due to parameter settings. Approach. To resolve these limits, we proposed a novel parameter-free technique, called ‘non-parametric full cross mapping (NFCM)’. The NFCM adapts current convergent cross-mapping concept, and makes two improvements: (1) an improved phase-space reconstruction with constant embedding parameters and (2) cross-mapping estimate of all embedding vectors on manifolds following simplex projection. Main results. Numerical experiments verify that our NFCM has the highest quantization stability even when perturbed by system noise, and its coefficient of variation is almost lower than that of the six baseline methods. The developed NFCM is finally used in stereoelectroencephalogram analysis of drug-resistant epilepsy in children (DREC). A total of 36 seizures, comprising 18 surgical successes and 18 failures, were included to explore the brain network dynamics. The average causal coupling in epileptogenic zones of successful surgery (0.81 ± 0.04) is significantly higher than that in non-epileptogenic zones (0.40 ± 0.03) with

P
<
0.001

via Mann–Whitney-U-test. While there is no significant difference among the 18 failed surgeries. Significance. The causal brain network measured by our NFCM is confirmed as a credible biomarker for localizing epileptogenic zones in DREC. These findings promise to advance precision medicine for DREC.
Reparametrization Invariant Scaling Symmetry and the Value of the Einstein Cosmological Constant ΛE
Authors: Gueorguiev Vesselin G. 
Published: December 2024

Abstract
The nature of Dark Energy (DE) remains an enigma. This work explores the non-zero Einstein Cosmological Constant (Λ
E
) as a manifestation of DE – viewing it through the lens of Reparametrization Invariant Scaling Symmetry (RISS), where Λ
E
is interpreted as a “kinetic energy” term within the energy density. The scale factor λ(t) relevant for cosmic reparametrization removes Λ
E
from the extended Einstein GR, its defining equations, and their relations to Λ
E
are derived. The value for Λ
E
= 1.8 × 10−52 m−2 is consistent with the current observations for Λ
E
. The current approach avoids the puzzles associated with interpreting Λ
E
as vacuum zero-point energy (often called dark energy). Further applications are related to the Dark Matter problem by insisting on a reparametrization symmetry for the equations of motion, where un-proper (non-co-moving) time parametrization gives rise to fictitious forces.
Building Artificial Intelligence, Machine Learning, and Causal Models to Improve Cardiac Health
Authors: Haynatzki Roman , Windle Thomas A , Dai Ran , Horner Ronnie D , McClay James C , Revesz Peter Z , Haynatzki Gleb , Windle John R 
Published: December 2024

Abstract
The prediction of myocardial infarction (MI) outcomes remains pivotal for advancing treatment strategies in cardiology. This study proposes to compare the variable selection efficacy and predictive power of LASSO logistic regression and XGBoost, incorporating a causal mediation approach to elaborate on the underlying mechanisms influencing MI risks. Leveraging the GUSTO-I dataset on MI patients, this research has employed LASSO logistic regression to facilitate variable selection, aiming to identify critical predictors with substantial impacts on MI outcomes. Alternatively, the XGBoost algorithm has been utilized to assess its approach to variable selection and prediction. Both methods have been evaluated based on their Area Under the Receiver Operating Characteristic Curve (AUC) to determine their predictive accuracy. Furthermore, causal mediation analysis has been integrated to explore the putative effects of key predictors, identified in previous studies. The analysis aimed to reveal which method offers superior predictive performance and how well each can be interpreted in a clinical context. This study can contribute valuable insights into the comparative advantages of using LASSO logistic regression versus XGBoost in the field of cardiovascular disease research. By integrating causal mediation analysis, we aim to extend beyond mere prediction to offer a deeper understanding of the causal relationships and mechanisms at play.
Mathematical Modeling of the Operation of a Hydrophoric Installation
Authors: Nikolaev I N , Raeva E R , Mihova V A 
Published: December 2024

Abstract
In this paper, the performance of a pumping system is considered in its operation with a hydrophore vessel connected in parallel. The filling and emptying processes of the hydrophore and their influence on the flow rate to the system and the pump outlet pressure are experimentally investigated. An automated measuring system is used for the measurements of the flow rate and the pressure. That has cyclically recorded the values at equal time intervals. The measurement cycles are synchronized in time and the maximum errors of the measured quantities are known. From the experimental data, empirical relationships are obtained for flow rate and pressure as a function of time, as well as the relationships between the two quantities. The time periods of each of the two processes and the average cycle length are also empirically determined. Confidence intervals of the flow rate are constructed for vessel filling and emptying, respectively, and measurement errors were accounted for. Codes have been created to determine the filling time of a hydrophore vessel and to calculate confidence intervals for this type of pumping systems, thanks to which all calculations have been automated. The described dependencies can be used in planning future experiments.
Asphalt Concrete Mixtures with Coal Bottom Ash as Fine Aggregate Substitution and Crumb Rubber as Asphalt Substitution
Authors: Saleh Sofyan M , Isya M , Darma Yusria , Salmannur Alfi , Ramadhana Fadillah 
Published: December 2024

Abstract
This research conducting the substitution of coal bottom ash and crumb rubber in asphalt concrete wearing course (AC-WC) mixtures. The objective is to help reduce waste materials and obtaining Marshall parameters that meet the requirements for asphalt mixtures. The percentage variations used for the substitution were 6%, 9%, and 12% coal bottom ash and 5%, 8%, and 11% crumb rubber. In Marshall test used varies asphalt content, the optimum asphalt contents (OAC) obtained were 5.85%, 6.03%, and 6.2%. Then, the OAC was used in asphalt concrete mixtures with coal bottom ash as fine aggregate substitution. The best results were obtained at the combination of 6% coal bottom ash and 5.85% asphalt content. Consequently, the combination was used in the mixtures by adding crumb rubber as the substitution of the asphalt. The results shows that the Marshall parameters obtained by all percentages of crumb rubber substitution have fulfilled the requirements with the highest stability of 1928.16 kg. The durability test on asphalt concrete mixtures with 6% coal bottom ash as fine aggregate substitution and 11% crumb rubber as asphalt substitution with 5.85% asphalt content obtained 92.82%, so that the requirement of ≥90% of the Bina Marga 2018 Specifications Revision 2 (2020) have been fulfilled.
Investigating the thermal performance of a subsea liquid piston air compressor pipeline operating at very high pressure ratios
Authors: Cutajar Charise , Sant Tonio , Aquilina Luke 
Published: December 2024

Abstract
Liquid piston air compression is presently gaining significant interest as a means for long duration energy storage at large scale. However, various aspects attributed to the thermal performance of liquid piston air compressors at high operating pressure ratios remain yet unanswered. This paper presents a transient thermal analysis of a novel, subsea liquid piston air compressor pipeline operating at pressure ratios up to 200. A thermal model implementing different empirical correlations for the convective heat transfer phenomena is presented. The study reveals a major knowledge gap in terms of Nusselt number correlations available to define the internal heat transfer coefficients explicit to liquid piston pipelines. Results from a parametric study suggest that the internal heat transfer inside a liquid piston having a very large length-to-diameter ratio was characterised by natural convection effects. Furthermore, it was found that to attain a thermal efficiency higher than 0.90, the power density had to be limited to not more that 0.22 kW/m3, with a compression time required per stroke being at least 25minutes.
CFD Analysis of a Subsea Liquid Piston Accumulator for Energy Storage Applications
Authors: Aquilina Luke , Sant Tonio , Cutajar Charise 
Published: December 2024

Abstract
Hydro-pneumatic energy storage uses liquid pistons and hydraulic machinery to store energy by compressing air. The technology offers significant potential for co-location with offshore wind farms, where the sea water may be used to augment the heat exchange between the air undergoing compression or expansion and the surrounding environment, hence improving the thermal efficiency by operating at isothermal conditions. A major challenge for the numerical simulations to assess the transient thermal behaviour of such a system is the lack of appropriate models for the convective heat transfer coefficients. This paper addresses this knowledge gap through the use of CFD by simulating a subsea accumulator housing a liquid piston compressing the air from atmospheric conditions up to a pressure of 100 Bar. The adopted numerical approach examines the heat exchange between the air undergoing compression and the surrounding sea water, with the internal and external heat transfer coefficients being derived concurrently. It is noted that the internal heat transfer coefficient is significantly dependent on the state of charge of the accumulator. Yet, quasi-isothermal conditions were predicted by the CFD model for the simulated conditions. The paper provides insight about the complexity of the heat transfer phenomena related to subsea liquid pistons and the need to derive correlations specifically for this application.
Correlation Analysis of Vegetation Index Impact on Rice Paddy Productivity Estimation using Landsat-8 and Sentinel-2A Images (Case Study: Blitar District)
Authors: Rizqika Ayu Karina , Muljo Sukojo Bangun , Ayu Retno Mukti Dyah 
Published: December 2024

Abstract
Rice is consumed by most of the population in Indonesia. The generative phase, the final stage of rice growth cycle, produces raw grains that are processed into rice, forming the basis of rice production. To estimate rice paddy productivity in March 2023, vegetation indices such as the Normalized Difference Vegetation Index (NDVI) and the Optimized Soil-Adjusted Vegetation Index (OSAVI) are used. These indices are crucial as they correlate with rice paddy areas in the generative phase. Sentinel-2A imagery calculations have shown strong correlations, with NDVI at R = 0.61 and OSAVI at R = 0.75. The OSAVI index from Sentinel-2A yielded an average productivity estimate of 31.35 ton/ha with an RMSE of 5.7041, while NDVI gave an average of 63.63 ton/ha with an RMSE of 12.3224. In comparison, Landsat-8 imagery estimates using NDVI showed a moderate correlation (R = 0.54), with an average productivity of 20.75 ton/ha and an RMSE of 3.2321. The OSAVI index with Landsat-8 provided an average estimate of 64.27 ton/ha with an RMSE of 12.3338 and a moderate correlation (R = 0.41). The correlation coefficients from Sentinel-2A are higher than those from Landsat-8, indicating that the choice of imagery significantly affects rice productivity estimates.