bluuebunny/crossref_metadata_2025_split huggingface dataset:
Similarity laws of low pressure inductively coupled discharges based on PIC/MCC simulations
Authors: Wen Hui , Schulze Julian , Fu Yangyang , Sun Jing-Yu , Zhang Quan-Zhi 
Published: February 2025

Abstract
A two-dimensional implicit particle-in-cell model is applied for exploring the plasma behavior and similarity laws (SLs) for low pressure inductive radio frequency plasmas. The applicability of the SLs in such discharges is examined for various plasma parameters, including electric field, electron density, electron temperature, electron current density, and electron power density distributions. The results indicate that the discharge characteristics strictly follow similarity relations in geometrically similar systems in low ionization degree ICP discharges at low pressure. Even under conditions where the anomalous skin effect caused by electron inertia and nonlocal transportation exist, the electron kinetics in compared systems remain invariant.
Advanced dual inter-bridge high-k spacer integration for performance enhancement in TreeFETs with sub-10nm channel lengths
Authors: Mounika S , Nanda Umakanta 
Published: February 2025

Abstract
This study presents an innovative Dual Inter-Bridge (DIB) high-k spacer integration in TreeFET, demonstrating enhanced DC and analog/RF performance for sub-10 nm channel lengths. The proposed device features a DIB TreeFET structure with dimensions of 15 nm in width (WNS) and 5 nm in thickness (TNS), along with dual Inter Bridges measuring 25 nm in height (HIB) and 5 nm in width (WIB). Simulations performed using Sentaurus TCAD reveal that the TreeFET achieves a remarkable ION/IOFF ratio of 108, an ION current in the range of 10−5 A and an IOFF current of 10−13 A. The device exhibits a subthreshold swing (SS) of 60.4 mV/decade, attributable to fringing fields in the high-k spacer and DIB design, which enhance electrostatic control and electron mobility in the channel region. A comparative analysis of various spacer materials like HfO2, Si3N4, and SiO2 at varying spacer lengths demonstrates the superiority of HfO2 due to its exceptional dielectric properties, leading to optimized electrostatic control and minimized&#xD;leakage currents. Furthermore, the study examines the impact of gate length variations on device performance, underscoring the scalability of TreeFET in compliance with Moore’s law. The findings highlight the potential of the DIB TreeFET structure as a viable solution for future high-performance, ultra-scaled devices in advanced semiconductor technologies.
Interaction wave solutions of the (2+1)-dimensional Fokas-Lenells equation
Authors: Guan Yaxin , Li Xinyue , Zhao Qiulan 
Published: February 2025

Abstract
In this paper, we investigate the interaction wave solutions of the (2+1)-dimensional Fokas-Lenells equation. These localized wave solutions contain solitons, degenerate solitons, lumps and lump chains. Wefocus on mixed solutions including solitons and degenerate solitons, lumps，and lump chains. The effective method we use to obtain the above solutions is generalized $(n, M)$-fold Darboux transformation. The characteristics and properties of these solutions are discussed analytically and graphically. These solutions can change the strength of the interactions by adjusting parameters and preserve their own properties throughout the interaction process.
Proximal Policy Optimization in Event-Triggered Resource Efficient Communications for Dynamic Platoon Maneuvers
Authors: Muntimadugu Kezia , K V Anusuya 
Published: February 2025

Abstract
&#xD;Abstract—In modern transportation systems, dynamic platooning is a promising approach that leverages adaptable vehicle formations to optimize traffic flow and fuel efficiency. However, reliance on periodic broadcasts to preserve string stability during platoon maneuvers poses a challenge, demanding substantial resources within a constrained spectrum. This paper presents a novel event-triggered approach using Proximal Policy Optimization (PPO) in Reinforcement Learning (RL), specifically designed for dynamic autonomous vehicular platoons on highways and urban roads. In this innovative approach, the first vehicle in the platoon triggers communication instances intelligently only when platoon speed variations threaten string stability. Furthermore, this approach introduces a categorization system that distinguishes the safety and non-safety messages for triggered events, ensuring prioritized transmission. Simulation results demonstrate the efficacy of the trained Platoon Leader (PL) in maintaining string stability, even amidst comprehensive platoon dynamics, achieved through a reduced waiting time for safety messages in the buffer. The cost-benefit analysis of the proposed method demonstrates improved road space utilization, reduced fuel consumption, and a decrease in collisions, addressing critical challenges in modern transportation systems.&#xD;
Enhanced electronic and photoelectrical properties in two-dimensional Zn-doped SnS2
Authors: Chuai Xichen , Yin Peng , Wang Jiawei , Yang Guanhua , Lu Congyan , Geng Di , Li Ling , Liu Can , Wei Zhongming , Lu Nianduan 
Published: February 2025

Abstract
Alloy engineering, with its ability to tune the electronic band structure, is regarded as an effective method for adjusting the electronic and optoelectronic properties of two-dimensional (2D) semiconductors. However, synthesizing metal-site substitution alloys remains challenging due to the low reactivity of metal precursors and the tendency for spatial phase separation during high-temperature growth. Here, we report the preparation of a high-quality metal-site substitution alloy, Zn0.167Sn0.833S2, via the chemical vapor transport method, which exhibits excellent photoresponsivity and enhanced electrical transport properties. Comprehensive characterization techniques, including Raman spectroscopy, X-ray photoelectron spectroscopy (XPS), and electron microscopy, unambiguously confirm the uniform Zn substitution in the as-prepared Zn0.167Sn0.833S2 alloy. Furthermore, the photodetector based on the Zn0.167Sn0.833S2 alloy demonstrated a high on/off ratio of 51 under white light, a wide spectral response range from 350 nm to 900 nm, and a broad dynamic power range of 80 dB under 638 nm illumination. In terms of transport properties, field-effect transistors (FETs) based on Zn0.167Sn0.833S2 achieved a carrier mobility of 6.5 cm2 V-1 s-1, which is six times higher than that of SnS2. This alloy semiconductor showcases significantly enhanced electronic and optoelectronic properties, offering great potential for the development of high-resolution photodetection technologies.
Thermodynamics of Schwarzschild-AdS black hole in non-commutative geometry
Authors: Wang Rui-Bo , Ma Shi-Jie , You Lei , Deng Jian-Bo , Hu Xian-Ru 
Published: February 2025

Abstract
In this paper, we study the thermodynamics of Schwarzschild-anti-de Sitter black holes within the framework of non-commutative geometry. By solving the Einstein's equations, we derive the corrected Schwarzschild-AdS black hole with Lorentzian distribution and analyze the thermodynamics. Our results confirm that if the energy-momentum tensor outside the event horizon is related to the mass of the black hole, the conventional first law of thermodynamics will be violated. The study of criticality reveals that the black hole undergoes a small black hole-large black hole phase transition similar to that of the Van der Waals system, with a critical point and a critical ratio slightly smaller than that of the Van der Waals fluid. As the non-commutative parameter increases, the phase transition process shortens, leading to a critical point, and ultimately to the disappearance of the phase transition. The violation of the conventional first law results in a discontinuity of the Gibbs free energy during the phase transition, indicating the occurrence of zeroth-order phase transition. Moreover, we investigate the Joule-Thomson expansion, obtaining the minimum inversion temperature and the minimum inversion mass.
Long-range correlations with finite-size effects from a superposition of uncorrelated pulses with power-law distributed durations
Authors: Korzeniowska M A , Garcia O E 
Published: February 2025

Abstract
Long-range correlations manifested as power spectral density scaling

1

/

f
β

for frequency f and a range of exponents β are investigated for a superposition of uncorrelated pulses with distributed durations τ. Closed-form expressions for the frequency power spectral density are derived for a one-sided exponential pulse function and several variants of bounded and unbounded power-law distributions of pulse durations

P
τ

(
τ
)
∼
1

/

τ
α

with abrupt and smooth cutoffs. The asymptotic scaling relation

β
=
3
−
α

is demonstrated for

1
<
α
<
3

in the limit of an infinitely broad distribution

P
τ

(
τ
)

. Logarithmic corrections to the frequency scaling are exposed at the boundaries of the long-range dependence regime, β = 0 and β = 2. Analytically demonstrated finite-size effects associated with distribution truncations are shown to reduce the frequency ranges of scale invariance by several decades. The regimes of validity of the

β
=
3
−
α

relation are clarified.
MNEGC: an improved gravity centrality based on node multi-features and network embedding for identifying influential nodes in complex networks
Authors: Lu Pengli , Sun LiHui 
Published: February 2025

Abstract
Identifying influential nodes in complex networks is a highly regarded and challenging problem. The use of gravity models to identify influential nodes has sparked research interest among scholars. However, existing gravity models mostly consider only limited dimensions of nodes and the shortest distance between nodes, which often leads to inaccurate identification. To overcome this problem, we propose a gravity centrality based on node multi-features and network embedding (MNEGC) for identifying key nodes. Firstly, we define the third generalized energy based on the generalized matrix, simultaneously considering the neighborhood coreness and clustering coefficient of nodes, and combining these three metrics to use as the mass of the nodes. Secondly, the Node2vec algorithm is utilized to map the nodes into a low-dimensional vector space and calculate the Euclidean distance between nodes. Finally, the score of the nodes is calculated using the new gravity model. We conduct comparative experiments by comparing the MNEGC algorithm with four gravity models and five state-of-the-art algorithms on nine networks. The experimental results suggest that MNEGC excels in ranking accuracy, monotonicity, imprecision function and precision in identifying the top-10 nodes.
Two-photon polymerization of miniaturized 3D scaffolds optimized for studies on glioblastoma multiforme in spaceflight-like microgravity conditions
Authors: Genchi Giada Graziana , Conci Claudio , Şen Özlem , Nardini Alessandra , Bartolucci Martina , Marino Attilio , Martinez Vazquez Rebeca , Cerullo Giulio , Osellame Roberto , Petretto Andrea , Raimondi Manuela Teresa , Ciofani Gianni 
Published: February 2025

Abstract
The obtainment of innovative models recalling complex tumour architectures and activities in vitro is a challenging drive in the understanding of pathology molecular bases, yet a crucial passage to the identification of targets for advanced oncotherapy. Cell environment recapitulation by 3D scaffolding and gravitational unloading of cell cultures represent powerful means in tumour biomimicry process, but their simultaneous adoption has consistently been explored only in the latest decade. Here, an unprecedented bioengineering approach capitalizing on spaceflight biology practice is proposed for modelling of glioblastoma multiforme, a highly aggressive neoplasm that affects the central nervous system and that has poorly effective pharmacological and radiological countermeasures. Tumour modelling was pursued by the original implementation of two-photon polymerization in fast prototyping of 3D scaffolds on flexible substrates for U87-MG glioma cell culture, and by the exposure of cell-laden scaffolds to simulated microgravity (s-µg). Realistic spaceflight conditions were applied to collect preliminary information suitable to testing of U87-MG cell-laden scaffold in low Earth orbit. Response of glioma cells anchored to 3D scaffolds was investigated by microscopy, quantitative reverse transcription-polymerase chain reaction and proteomic analyses, revealing synergic regulatory effects of cell scaffolding and s-µg on markers of tumour cell growth, metabolism and invasiveness.
Multiband dielectric metasurface in sandwiched scheme fashioned in the visible range
Authors: Gu Xin , Li Jiaqi , Liang Zhouxin , Lin Yuhang , Chen Yujie 
Published: February 2025

Abstract
A multi-resonance-supported multiband device is proposed. Multi-resonance is typically achieved by combining metal with dielectric nanostructures or by using multiple nanostructures formatting a supercell with optimized geometries (size, period, and/or gap) to support various resonances. In this study, we investigate how higher-order multipoles resonated by sandwich-shaped silicon-rich silicon nitride (SRN) metasurfaces embedded in silica cladding can promote multi-resonance in the visible spectrum, achieving nearly triple peaks at RGB (Red, Green, Blue) wavelengths. Such design enhances the structure integration, while the multi-resonant characteristics enable the metasurface to function as a multiband device with a reduced footprint. Through analytical and numerical analyses, we examine the effects of the metasurface's geometric shape, cladding, and sandwich-shaped nanodisks on resonance, providing design strategies for multi-resonant optical devices forwards multi-spectral imaging, optical sensing, and color displays.&#xD;
Prediction of Temperature and Humidity in Footwear Warehouses Based on Improved Arithmetic Optimization Twin Support Vector Machine for Regression
Authors: zhang Xin , Shi Chunyang , Bai Yinuo , Chen Jida 
Published: February 2025

Abstract
Temperature and humidity fluctuations in storage environments significantly impact the material properties and quality of footwear. Temperature and humidity fluctuations in storage environments significantly impact the material properties and quality of footwear. Traditional warehouse management approaches typically rely on fixed environmental control systems, which struggle to adapt to real-time dynamic changes, leading to high energy consumption, Inefficient management, and potential impacts on footwear quality. To address the aforementioned issues, the study employed an improved arithmetic optimization algorithm (AOA) to optimize the twin support vector machine for regression algorithm (LAOA-TSVR) and develop the corresponding prediction model. First, SPSS was used for correlation analysis to identify the primary factors influencing temperature and humidity in the warehouse. Second, to validate the model's prediction accuracy, the algorithm was compared with three common models: backpropagation neural network (BP), radial basis function neural network (RBF), and twin support vector regression (TSVR). The results demonstrate that the LAOA-TSVR exhibits fast convergence, high prediction accuracy, and robust generalization ability. Finally, the model was applied in a real warehouse environment. The results indicate that when the temperature and humidity errors in the warehouse remain within ±10% and ±5%, the endpoint hit rates for warehouse temperature reach 96.8% and 88.1%. while those for warehouse humidity reach 93.6% and 86.3%, respectively. For ±10% errors, the dual hit rate for warehouse temperature and humidity is 92.7%. The model establishes a theoretical foundation for accurately predicting temperature and humidity in warehouse environments, thereby facilitating the optimization of control strategies and improving warehouse management efficiency.&#xD;
Compact Ultra-Wideband Microstrip MIMO Antenna with Triple Notch-Based Characteristic
Authors: ÖZTÜRK Cennet , ÇİMEN SİBEL 
Published: February 2025

Abstract
This paper presents the design of a novel ultra-wideband (UWB) Multiple Input Multiple Output (MIMO) antenna with triple-band notches. In the proposed design, two antenna elements are positioned within a 38 × 29 mm² area, using a common ground plane. I-, C-, and U-shaped slots are incorporated to reject frequencies in the WiMAX, WLAN, and X bands, respectively. Good isolation between the radiator elements is achieved through the implementation of the Defective Ground Structures (DGS) technique and the addition of L-stubs to the ground plane. The proposed MIMO antenna exhibits low isolation, below -20 dB, across its operating band. Moreover, the envelope correlation coefficient (ECC) and diversity gain (DG) values of the designed antenna are less than 0.025 and greater than 9.98 dB, respectively. The scattering parameters and radiation characteristics of the proposed MIMO antenna were tested through a fabricated prototype. The MIMO antenna shows promise for UWB applications due to its compact structure and notch-band features.
Machine Learning-Powered Data Cleaning for LEGEND: A Semi-Supervised Approach Using Affinity Propagation and Support Vector Machines
Authors: León Esteban , Li Aobo , Bahena Schott Miguel Angel , Bos Brady , Busch Matthew , Chapman Jason Robert , Duran Guadalupe Lourdes , Gruszko Julieta , Henning Reyco , Martin Eric Larue , Wilkerson John 
Published: February 2025

Abstract
Neutrinoless double-beta decay (0νββ) is a rare nuclear process that, if observed, will provide insight into the nature of neutrinos and help explain the matter-antimatter asymmetry in the universe. The Large Enriched Germanium Experiment for Neutrinoless Double-Beta Decay (LEGEND) will operate in two phases to search for 0νββ. The first (second) stage will employ 200 (1000) kg of High-Purity Germanium (HPGe) enriched in 76Ge to achieve a half-life sensitivity of 1027 (1028) years. In this study, we present a semi-supervised data-driven approach to remove non-physical events captured by HPGe detectors powered by a novel artificial intelligence model. We utilize Affinity Propagation to cluster waveform signals based on their shape and a Support Vector Machine to classify them into different categories. We train, optimize, test our model on data taken from a natural abundance HPGe detector installed in the Full Chain Test experimental stand at the University of North Carolina at Chapel Hill. We demonstrate that our model yields a maximum sacrifice of physics events of 0.024 + 0.004 - 0.003 % after data cleaning. Our model is being used to accelerate data cleaning development for LEGEND-200 and will serve to improve data cleaning procedures for LEGEND-1000.
Long-Term Changes to Cardiovascular Biomarkers After Hormone Therapy in the Women's Health Initiative Hormone Therapy Clinical Trials
Authors: Nudy Matthew , Aragaki Aaron K. , Jiang Xuezhi , Manson JoAnn E. , Shadyab Aladdin H. , Jung Su Yon , Martin Lisa W. , Wild Robert A. , Womack Catherine , Mouton Charles P. , Rossouw Jacques E. , Schnatz Peter F. 
Published: February 2025

OBJECTIVE:
To assess the long-term changes in cardiovascular biomarkers during the WHI (Women's Health Initiative) hormone therapy (HT) clinical trials of conjugated equine estrogens (CEE) alone and CEE plus medroxyprogesterone acetate (MPA).

METHODS:
HT trial participants from the CEE alone (n=1,188, 0.625 mg/d CEE or placebo) and the CEE+MPA (n=1,508, 0.625 mg/d CEE plus continuous 2.5 mg/d MPA or placebo) trials provided blood samples at baseline and after 1, 3, and 6 years. Low-density lipoprotein cholesterol (LDL-C; primary endpoint), high-density lipoprotein cholesterol (HDL-C), triglycerides, total cholesterol, lipoprotein(a), glucose, insulin, and homeostatic model assessment for insulin resistance were measured. Repeated-measures regression models estimated the geometric means of each log-transformed biomarker by restricted maximum likelihood. A constant treatment effect across visits was used to estimate the overall effect, expressed as a ratio of geometric means, and was complemented with geometric means (95% CIs) by randomization group and corresponding ratios of geometric means (95% CI; HT vs placebo) at each visit.

RESULTS:
During the intervention phase of the CEE-alone trial, randomization to CEE reduced LDL-C by 11% over 6 years (ratio of geometric means 0.89, 95% CI, 0.88–0.91, P<.001). The overall reduction in LDL-C was similar for CEE+MPA relative to placebo (ratio of geometric means 0.88, 95% CI, 0.86–0.89, P<.001). Relative to placebo, HDL-C and triglycerides were 13.0% and 7.0% higher with CEE and CEE+MPA, respectively. The homeostatic model assessment for insulin resistance decreased by 14.0% and 8.0% for CEE-alone and CEE+MPA trial participants, respectively. Relative to placebo, lipoprotein(a) decreased by 15.0% and 20.0% for participants randomized to CEE alone and CEE+MPA, respectively.

CONCLUSION:
Lipoprotein(a), LDL-C, and homeostatic model assessment for insulin resistance were lower and HDL-C levels were higher for HT compared with placebo. Triglycerides increased in both the CEE and CEE+MPA trials, however. Future research should assess whether other progestogens attenuate the effect of estrogen on HDL-C. These results may be used to counsel younger menopausal women with bothersome symptoms who are deciding whether to initiate oral HT within the context of published effects of oral HT on rates of cardiovascular events.

CLINICAL TRIAL REGISTRATION:

ClinicalTrials.gov, NCT00000611.
Psychometric Testing of the Kansas City Cardiomyopathy Questionnaire 12 in A European Population
Authors: Iovino Paolo , Dollaku Hamilton , Rasero Laura , Uchmanowicz Izabella , Alvaro Rosaria , Pucciarelli Gianluca , Vellone Ercole 
Published: February 2025

Introduction
The Kansas City Cardiomyopathy Questionnaire (KCCQ) is one of the most widely used instruments for measuring health-related quality of life of patients with heart failure (HF). However, its 12-item version (KCCQ-12) was not sufficiently tested in European populations, and its invariance in patients with reduced, midrange, and preserved ejection fraction has never been assessed.

Aims
The purpose of this study is to examine the validity and reliability of the KCCQ-12 in a large cohort of Italian patients with HF and assess its measurement invariance across levels of ejection fraction.

Methods
A total of 510 patients (mean age = 72 years, 58% males) completed the KCCQ-12 alongside other measures of depression, anxiety, quality of life, and HF symptom burden. Construct validity was assessed by means of a confirmatory factor analysis and by testing the association of the KCCQ-12 scores with clinical parameters (ie, ejection fraction and mortality at 12 months) as well as measures of anxiety, depression, symptom burden, and general quality of life. Multigroup confirmatory factor analysis was implemented to investigate invariance properties across those with reduced, midrange, and preserved ejection fraction. Omega and model-based internal consistency coefficients were computed to investigate internal consistency reliability.

Results
The confirmatory factor analysis specified according to the original 4-factor model (ie, physical and social limitations, symptom frequency, and quality of life) yielded satisfactory fit indices (root mean square error of approximation = 0.053, comparative fit index = 0.98). Moderate-to-high correlations were found between the KCCQ-12 and the mental and physical component scores of the Short Form 12, as well as other conceptually related constructs, indicating adequate facets of construct validity. Multigroup confirmatory factor analysis tested across patients with different ejection fraction groups, established that the KCCQ-12 was invariant at the partial scalar level. Omega and model-based internal consistency coefficients were adequate, ranging from 0.75 to 0.90 for the subscales, and 0.94 for the whole scale, confirming strong internal consistency reliability.

Conclusions
The KCCQ-12 demonstrated satisfactory psychometric properties in our European sample of patients with HF, providing evidence to support its use in practice and further research.