bluuebunny/crossref_metadata_2025_split huggingface dataset:
Who says ejque?
Authors: Wright Robyn 
Published: November 2024

Abstract
This paper examines language attitudes of 386 participants from all regions of Spain toward a phonetic variant
used in the Madrid area, velarized coda /s/. Results show that velarized /s/ aids in the identification of a Madrid origin and,
moreover, that velarized /s/ speakers are considered lower status, less pleasant, less confident, more of a tough-guy, less
desirable as friends, less compatible with the listener and worse storytellers. Nearly all of these traits interact with listener
gender in which women show the strongest variable effect. In addition, ethnocentrism is found to play a role in listener
judgments, irrespective of the coda /s/ variant used.
Study of microstructural evolution during operation of electrically connected components and analysis of failure mechanism
Authors: Xie Tao , Zhou Xiaoyu , Jin Shoufeng , He Kanghang , Wu Juzhen , Wang Qingyu , Liu Peng , Peng Zongren 
Published: November 2024

Abstract
As a key current-carrying structure of high-voltage bushings, the reliability of electrical connection components is crucial to the safe and stable operation of power equipment. To obtain the microstructural evolution of electrical connection components with different deterioration states, CUD strap contactors were deteriorated in different ways, and electron backscatter diffraction technique was used to test the microstructure of strap contactors with different deterioration states. The results showed that compared to the unused contactors, the contact resistance of the contactors under the combined effect of friction and high temperature increased 203.12 times and was in a failed state. During the process from unused state to wear deterioration, high temperature deterioration, and then to eventual failure of the contactors, the average grain size gradually grows from 8.15 μm to 25 μm, the dislocation density gradually decreases from 2.38 × 1014 m−2 to 1.04 × 1014 m−2, and there are a significant proportion of the recrystallized organization. These changes are detrimental to the mechanical properties of the contactors. In addition, the distribution of grain boundaries in the contact area proves the occurrence of over-temperature phenomenon in this area, which will accelerate the deterioration of the contactors and eventually lead to the failure of the component. The relevant conclusions can provide a theoretical basis for the design of electrical connection structure of strap contacts as well as the study of deterioration mechanism.
A lightweight hybrid model-based condition monitoring method for grinding wheels using acoustic emission signals
Authors: Xu Fan , Wu Jianwei , Hong Duo , Zhao Feng , Wu Junhui , Yan Jianguo , Hu Weifei 
Published: November 2024

Abstract
Various data-driven methods based on acoustic emission (AE) signals have been proposed to monitor and accurately identify the wear stages of the grinding wheel. However, extracting effectively generalized and discriminative features from AE signals remains a challenging task. This paper proposes a new lightweight hybrid deep learning model that combines enhanced convolution with enhanced vision transformer (ViT) to effectively address the above challenges. Specifically, the key contributions of this paper are three-fold: (1) A two-stage signal preprocessing mechanism based on variational mode decomposition and continuous wavelet transform is proposed to improve the signal-to-noise ratio and feature representation of the AE signals. (2) To prevent model overfitting, a new regularization strategy based on stabilizing sparse convolutional weights and a weight penalty mechanism is designed. This approach improves the hybrid mode’s capacity to extract generalized features. (3) To concentrate on capturing multi-scale discriminative features between different wear conditions, a parameter-efficient residual convolution module based on the dropout depthwise convolution is designed, which is utilized to reconstruct the encoder of the ViT. In particular, to improve the training efficiency of the model, a lightweight mechanism using a stage-stride decreasing strategy is used to compress the spatial dimensions of the feature maps in the attention mechanism. The ablation experiment demonstrates the rationality of the proposed model structure. Comparative experiments show that the proposed method achieves a diagnostic accuracy of 99.6% on the test set and outperforms other state-of-the-art deep learning methods.
Comparing attendance versus exam performance for topics within first year physics courses
Authors: Gladys M J , Dastoor P C 
Published: November 2024

Abstract
This paper revisits the relationship between lecture attendance and final exam performance of students attending first year Advanced Physics classes at The University of Newcastle. The results compare attendance to non-attendance for topics within the Advanced Physics courses and indicate that, on average, students attending lectures always score higher than students not attending with variations on the size of this effect depending on topic such that the gap is generally larger for topics not covered in secondary school. This correlation may indicate the importance for students to attend classes covering new material.
FLIP: a novel method for patient-specific dose quantification in circulating blood in large vessels during proton or photon external beam radiotherapy treatments
Authors: García-Cardosa Marina , Meiriño Rosa , Calvo Felipe A , Antolín Elena , Aguilar Borja , Vidorreta Marta , Cuevas Roberto , Barbés Benigno , Huesa-Berral Carlos , Azcona Juan Diego , Burguete Javier 
Published: November 2024

Abstract

Purpose. To provide a novel and personalized method (FLIP, FLow and Irradiation Personalized) using patient-specific circulating blood flows and individualized time-dependent irradiation distributions, to quantify the dose delivered to blood in large vessels during proton or photon external beam radiotherapy. Methods. Patient-specific data were obtained from ten cancer patients undergoing radiotherapy, including the blood velocity field in large vessels and the temporal irradiation scheme using photons or protons. The large vessels and the corresponding blood flow velocities are obtained from phase-contrast MRI sequences. The blood dose is obtained discretizing the fluid into individual blood particles (BPs). A Lagrangian approach was applied to simulate the BPs trajectories along the vascular velocity field flowlines. Beam delivery dynamics was obtained from beam delivery machine measurements. The whole IS is split into a sequence of successive IEs, each one with its constant dose rate, as well as its corresponding initial and final time. Calculating the dose rate and knowing the spatiotemporal distribution of BPs, the dose is computed by accumulating the energy received by each BP as the time-dependent irradiation beams take place during the treatment. Results. Blood dose volume histograms from proton therapy and photon radiotherapy patients were assessed. The irradiation times distribution is obtained for BPs in both modalities. Two dosimetric parameters are presented: (i) D
3%, representing the minimum dose received by the 3% of BPs receiving the highest doses, and (ii) V
0.5 Gy, denoting the blood volume percentage that has received at least 0.5 Gy. Conclusion. A novel methodology is proposed for quantifying the circulating blood dose along large vessels. This methodology involves the use of patient-specific vasculature, blood flow velocity field, and dose delivery dynamics recovered from the irradiation machine. Relevant parameters that affect the dose received, as the distance between large vessels and CTV, are identified.
Transport properties of high Mach number hypersonic air plasmas
Authors: Petrova Tzvetelina B , Petrov George M , Peñano Joseph R 
Published: November 2024

Abstract
The collisional and transport properties of hypersonic plasmas have been simulated by an air plasma chemistry model, which includes collisions with electrons, ions and neutral species, elastic scattering, vibrational relaxation and a transport model. Species and thermal fluxes at the surface of the vehicle have been investigated as a function of post-shock gas temperature and species sticking coefficient for a fixed altitude of 50 km. At temperatures below about 5000 K, the leading species are vibrationally excited nitrogen molecules, while at higher temperatures the atomic oxygen and nitrogen dominate. Large fluxes of oxygen atoms have been observed in the simulations, on the order of 1020 cm
−

2 s
−

1, which may lead to high rates of surface oxidation. Another subject of this study is temperature equilibration. For electrons, equilibration takes tens of microseconds, while the vibrational temperature equilibration time vary widely; from a few microseconds to hundreds of microseconds, depending on the gas temperature. Finally, the adiabatic parameter γ was calculated for post-shock gas temperatures 5000 K and 10 000 K and total gas density

1.2
×

10

17

c

m

−
3

. For post-shock gas temperature 5000 K, only a slight reduction of γ from the ideal gas value of γ = 1.4 is observed, while for 10 000 K it drops to γ ≅ 1.26, which has a considerable impact on plasma properties. It was further established that the vibrational kinetics plays a leading role. While a single excited vibrational level of the N2 molecule captures the salient properties of the plasma, a detailed vibration kinetics is required for high-fidelity simulations.
A computational approach to optimize the linearity in dual-gate InAlGaN/AlN/GaN HEMTs
Authors: Awasthi Shivansh , Hsu Heng-Tung , Tsao Yi-Fan , Chiu Ping-Hsun , Gupta Ankur 
Published: November 2024

Abstract
This paper investigates the effect of the proposed dual gate structures in enhancing the linearity of InAlGaN/AlN/GaN high-electron-mobility transistors (HEMTs) using TCAD analysis. Through the comprehensive analysis of the dual gate structure with the additional gate placed between the gate–source (DG-GS) and gate–drain (DG-GD) regions, the impact on the linearity performance has been compared with that of a standard single gate (SG) structure. The dual gate configuration exhibits a flatter and broader transconductance (g
m) profile than the SG configuration. The reduction in the third-order intermodulation levels is confirmed with the polynomial fitting method. The f
T/f
max of the DG-GS case is simulated to be 52/102 GHz, which shows that such configuration does not deteriorate the RF performance. Comprehensive simulations are carried out to study the device physics and assess the mechanism behind the linearity improvement. The large signal model has been developed to examine the large signal RF performance as well as linearity performance metrics. An improvement of 9.6 dB in the carrier-to-intermodulation (C/I) ratio and that of 2.4 degrees in the amplitude-to-phase modulation at 6 dB backoff from P
sat have been observed as compared to the SG configuration. Such characteristics have evidenced that the optimized dual-gate configuration with the second gate placed between the source and gate can effectively improve the linearity performance of the InAlGaN/AlN/GaN HEMT configurations.
Effects of simplicial centrality on robustness of higher-order multiplex world trade networks
Authors: Ren Zhuoming , Wang Wan , Weng Tongfeng , Du Wenli 
Published: November 2024

Abstract
World trade networks are exhaustively described by pairwise interactions, and overlook higher-order structure from the outcome of collective interactions at the level of groups of nodes like multilateral trade agreements. To address this limitation, we collect multiplex world trade networks, including the bilateral regional trade agreement network, which represents pairwise interactions; the multilateral regional trade agreement network, which naturally represents a higher-order network structure; and the import and export trade network, which represents pairwise interactions and additional complexities. The analysis of simplicial centrality, including degree, closeness, and subgraph at 0, 1, and 2-simplex levels, reveals that intra-level correlations are high, while inter-levels may exhibit significant disparities. Nodes with low centrality at higher-order levels could influence network robustness due to the diversity of interactions and higher-order dependencies. Simplicial centrality on robustness of multiplex world trade networks under random and targeted attacks reveals that the complex connectivity of higher-order levels renders them more vulnerable post-attack. An optimization strategy of the rebalancing of network centrality is proposed to enhance the robustness, and the simulation shows risks posed to central nodes are minimized and opportunities for peripheral nodes to partake in global trade are broadened.
Continuous-variable electromechanical quantum thermal transistors
Authors: Nie Wenjie , Xu Junxi , Zhan Huiya , Chen Aixi , Lan Yueheng 
Published: November 2024

Abstract
We present a scheme to realize quantum thermal transistor effects in a continuous-variable electromechanical system including two microwave cavities and one mechanical oscillator. The thermal noise fluxes between the quantum system and its baths are evaluated by quantum master equation. It is shown that the thermal noise flux at one microwave cavity as an emitter can be dissipated into the other as a collector by combining the heating Stokes and cooling anti-Stokes processes. The indirect energy transfers between the two microwave modes can be significantly amplified by small energy changes at the mechanical oscillator as the base. The extremely high amplification depends sensitively on the detunings of the two microwave modes, which provides a new tool for precision measurements. This study opens the door for constructing quantum thermal transistors using various continuous-variable systems and is well accessible based on current experimental techniques.
Entanglement polygon inequalities for a class of mixed states
Authors: Shi 石 Xian 现 
Published: November 2024

Abstract
The study on the entanglement polygon inequality of multipartite systems has attracted much attention. However, most of the results are on pure states. Here we consider the property for a class of mixed states, which are the reduced density matrices of generalized W-class states in multipartite higher dimensional systems. First we show the class of mixed states satisfies the entanglement polygon inequalities in terms of Tsallis-q entanglement, then we propose a class of tighter inequalities for mixed states in terms of Tsallis-q entanglement. At last, we get an inequality for the mixed states, which can be regarded as a relation for bipartite entanglement.
Database of ternary amorphous alloys based on machine learning
Authors: Gong 巩 Xuhe 旭菏 , Li 李 Ran 然 , Xiao 肖 Ruijuan 睿娟 , Zhang 张 Tao 涛 , Li 李 Hong 泓 
Published: November 2024

Abstract
The unique long-range disordered atomic arrangement inherent in amorphous materials endows them with a range of superior properties, rendering them highly promising for applications in catalysis, medicine, and battery technology, among other fields. Since not all materials can be synthesized into an amorphous structure, the composition design of amorphous materials holds significant importance. Machine learning offers a valuable alternative to traditional “trial-and-error” methods by predicting properties through experimental data, thus providing efficient guidance in material design. In this study, we develop a machine learning workflow to predict the critical casting diameter, glass transition temperature, and Young’s modulus for 45 ternary reported amorphous alloy systems. The predicted results have been organized into a database, enabling direct retrieval of predicted values based on compositional information. Furthermore, the applications of high glass forming ability region screening for specified system, multi-property target system screening and high glass forming ability region search through iteration are also demonstrated. By utilizing machine learning predictions, researchers can effectively narrow the experimental scope and expedite the exploration of compositions.
Pressure-induced structural transitions and metallization in ZrSe2
Authors: Gao 高 Yiping 一平 , Liu 刘 Chenchen 晨晨 , Tian 田 Can 灿 , Zhu 朱 Chengcheng 程程 , Huang 黄 Xiaoli 晓丽 , Cui 崔 Tian 田 
Published: November 2024

Abstract
High-pressure studies of two-dimensional materials have revealed numerous novel properties and physical mechanisms behind them. As a typical material of transition metal dichalcogenides (TMDs), ZrSe2 exhibits high carrier mobility, rich electronic states regulated by doping, and high potential in applications at ambient pressure. However, the properties of ZrSe2 under pressure are still not clear, especially for the structural and electrical properties. Here, we report the investigation of ZrSe2 under pressure up to 66.5 GPa by in-situ x-ray diffraction, Raman, electrical transport measurements, and first-principles calculations. Two structural phase transitions occur in ZrSe2 at 8.3 GPa and 31.5 GPa, from P-3m1 symmetry to P21/m symmetry, and finally transformed into a non-layer I4/mmm symmetry structure. Pressure-induced metallic transition is observed at around 19.4 GPa in phase II which aligns well with the results of the calculation. Our work will help to improve the understanding of the evolution of the structure and electrical transport properties of two-dimensional materials.
Improving performance of screening MM/PBSA in protein–ligand interactions via machine learning
Authors: Chen 陈 Yuan-Qiang 远强 , Xu 徐 Yao 耀 , Ma 马 Yu-Qiang 余强 , Ding 丁 Hong-Ming 泓铭 
Published: November 2024

Abstract
Accurately estimating protein–ligand binding free energy is crucial for drug design and biophysics, yet remains a challenging task. In this study, we applied the screening molecular mechanics/Poisson–Boltzmann surface area (MM/PBSA) method in combination with various machine learning techniques to compute the binding free energies of protein–ligand interactions. Our results demonstrate that machine learning outperforms direct screening MM/PBSA calculations in predicting protein–ligand binding free energies. Notably, the random forest (RF) method exhibited the best predictive performance, with a Pearson correlation coefficient (r
p) of 0.702 and a mean absolute error (MAE) of 1.379 kcal/mol. Furthermore, we analyzed feature importance rankings in the gradient boosting (GB), adaptive boosting (AdaBoost), and RF methods, and found that feature selection significantly impacted predictive performance. In particular, molecular weight (MW) and van der Waals (VDW) energies played a decisive role in the prediction. Overall, this study highlights the potential of combining machine learning methods with screening MM/PBSA for accurately predicting binding free energies in biosystems.
Estimating cognitive workload using a commercial in-ear EEG headset
Authors: Tremmel Christoph , Krusienski Dean J , schraefel mc 
Published: November 2024

Abstract

Objective. This study investigated the potential of estimating various mental workload levels during two different tasks using a commercial in-ear electroencephalography (EEG) system, the IDUN ‘Guardian’. Approach. Participants performed versions of two classical workload tasks: an n-back task and a mental arithmetic task. Both in-ear and conventional EEG data were simultaneously collected during these tasks. In an effort to facilitate a more comprehensive comparison, the complexity of the tasks was intentionally increased beyond typical levels. Special emphasis was also placed on understanding the significance of γ band activity in workload estimations. Therefore, each signal was analyzed across low frequency (1–35 Hz) and high frequency (1–100 Hz) ranges. Additionally, surrogate in-ear EEG measures, derived from the conventional EEG recordings, were extracted and examined. Main results. Workload estimation using in-ear EEG yielded statistically significant performance levels, surpassing chance levels with 44.1% for four classes and 68.4% for two classes in the n-back task and was better than a naive predictor for the mental arithmetic task. Conventional EEG exhibited significantly higher performance compared to in-ear EEG, achieving 80.3% and 92.9% accuracy for the respective tasks, along with lower error rates than the naive predictor. The developed surrogate measures achieved improved results, reaching accuracies of 57.5% and 85.5%, thus providing insights for enhancing future in-ear systems. Notably, most high frequency range signals outperformed their low frequency counterparts in terms of accuracy validating that high frequency γ band features can improve workload estimation. Significance. The application of EEG-based Brain–Computer Interfaces beyond laboratory settings is often hindered by practical limitations. In-ear EEG systems offer a promising solution to this problem, potentially enabling everyday use. This study evaluates the performance of a commercial in-ear headset and provides guidelines for increased effectiveness.
Multi-body dynamic assessment of vessel-floater accessibility for floating wind
Authors: Moreno Carlos Pérez , Lange Johannes , Snedker Thor , Bayati Ilmas 
Published: November 2024

Abstract
The floating wind industry faces several challenges in the road map to full maturity of commercial-scale floating projects. Accessing the floating offshore wind turbines poses larger risks due to the added degrees of freedom of the platform, with respect to bottom-fixed technology. When a vessel approaches, the platform’s motion leads to the introduction of multi-body dynamic effects. This work deals with the modeling of the vessel-platform dynamics for the VolturnUS-S 15MW platform and IEA15MW Reference Wind Turbine and a generic Crew Transfer Vessel (CTV) by means of performing a fully coupled assessment. The hydrodynamic properties are computed by solving the multi-body radiation-difraction problem. The inertial and hydrodynamic properties are included in an OrcaFlex model to perform a time-domain analysis under several sea states. A P-controller represents the helmsman pushing the vessel against the access point. The contact forces are modeled using a linear fender system to represent slip-and-stick events during the CTV’s push-on maneuver. The resulting relative motions are analyzed, and industry-typical limits are considered to quantify accessibility levels. The results show that peak wave period and wave heading play a major role in the accessibility scores.
Offshore wind project installations: an advanced approach for weather risk assessments
Authors: de la Torre-Castro L. , Behm L. , Kaczenski J. , Wiggert M. 
Published: November 2024

Abstract
This paper presents the development of a sequence-based simulation tool for the weather risk assessment of offshore work processes. The approach developed at the Fraunhofer Institute for Wind Energy Systems is the Advanced Weather Time Series Scheduling (Ad-WATSS) method. For statistical significance, this method combines hindcast weather time series of many years with the weather restrictions associated with offshore activities. The method is incorporated into the software tool COAST, where a project plan schedule is simulated by placing activities according to their operational limits, constraints and relationships, and minimum-required time for each operation. A scenario of an offshore wind installation project in the North Sea is used as reference test case for a weather risk assessment using the developed tool and ERA5 weather data. The assessment is then compared with the weather window statistics approach, based on the same weather data sets. The results from both approaches are analysed and compared on a project and task level detail. The results from the sequence-based simulations show that the method is able to capture the long-term variability and extreme events in weather conditions, making it a reliable tool for the simplification of the weather data-based planning, validation, and assessment of offshore projects.