bluuebunny/crossref_metadata_2025_split huggingface dataset:
Ab initio spin-mapping non-adiabatic dynamics simulations of photochemistry
Authors: Weight Braden M. , Mandal Arkajit , Hu Deping , Huo Pengfei 
Published: February 2025

We perform on-the-fly non-adiabatic molecular dynamics simulations using the recently developed spin-mapping formalism. Two quantum dynamics approaches based on this mapping formalism, (i) the fully linearized Spin-LSC and (ii) the partially linearized Spin-PLDM, are explored using the quasi-diabatic propagation scheme. We have performed dynamics simulations in four ab initio molecular models for which benchmark ab initio multiple spawning (AIMS) data have been published. We find that the spin-LSC and the previously reported symmetric quasi-classical (SQC) approaches provide nearly equivalent population dynamics. While we expected the more involved spin-PLDM method to provide superior accuracy compared to the other mapping-based approaches, SQC and spin-LSC, we found that it performed with equivalent accuracy compared to the AIMS benchmark results. We further explore the underpinnings of the spin-PLDM correlation function by decomposing its N2 density matrix-focused initial conditions, where N is the number of states in the quantum subsystem. Finally, we found an approximate form of the spin-PLDM correlation function, which simplifies the simulation and reduces the computational costs from N2 to N.
The predictive power of intercultural sensitivity on preservice EFL teachers’ plurilingual and pluricultural
competence
Authors: Eren Ömer 
Published: February 2025

Abstract
Multilingualism is becoming more ubiquitous and studies on this nexus have proliferated, with a focus on
plurilingual individuals’ behaviors within their contexts of interaction. However, there is a paucity of research regarding the
effects of the intrinsic relationship between affective dimensions of culture and multilingualism. To address this research gap,
the current study investigated the predictive power of intercultural sensitivity on preservice EFL teachers’
(n = 241) plurilingual and pluricultural competence through quantitative and qualitative analyses. Several
regression analyses revealed that dimensions of intercultural sensitivity significantly predicted the variance in plurilingual and
pluricultural competence with medium explanatory power. Multivariate analyses examined the contributions of demographic variables
(gender, bilingualism vs. multilingualism, hometown, the sojourn experience) to the overall model, and findings indicated that the
sojourn experience contributed to higher plurilingual competence as well as higher self-confidence. Plurilingual individuals seem
to have higher pluricultural competence and are more attentive compared to bilinguals. However, gender and hometown did not reveal
a significant relationship. Participants’ reflections reiterated the findings through three main constructs: (1) Collectivist
Pluricultural Identity, (2) Emotions and Multilingual Awareness, and (3) Unitary Translanguaging Practices.
What makes a good L2 listener?
Authors: Wu Yu , Wang Yang 
Published: February 2025

Abstract
Listening poses significant challenges for L2 learners and is difficult to improve (Graham, 2011). Research shows that L2 Chinese learners’ listening performance lags behind speaking and
reading even after four years of college study (Winke et al., 2020). However, the
factors influencing listening comprehension remain underexplored (Cai, 2015; Wang & Treffers-Daller, 2017). This study investigates the impact of oral
proficiency, vocabulary size, metacognitive awareness, and test anxiety on listening comprehension among 89 CSL learners. Results
from multiple regression analyses indicate that oral proficiency and vocabulary size are significant predictors of listening
performance. For less proficient listeners, oral proficiency was crucial, while vocabulary size was most significant for advanced
listeners. The importance of step-by-step vocabulary development and proficiency-guided language output opportunities is
discussed.
Assessing interactive listening in beginning-level L2 Chinese
Authors: Wang Wei , Yeh Meng 
Published: February 2025

Abstract
Interactive listening (IL) is understood as the interactional process in which listeners not just listen and comprehend but also actively monitor the ongoing talk, display understanding of it, clarify meaning, and advance conversation. Despite its importance in L2 learning, IL does not have much presence in standardized proficiency tests. This study thus aims to develop a rating scale for assessing IL with data drawn from beginning-level L2 Chinese learners’ unscripted conversations with L1 interlocutor. Using the framework of conversation analysis, this study identifies three aspects of IL in which different groups of learners vary most distinctively, that is, 1) the variety of listener responses used; 2) the ways in which understanding and engagement are demonstrated; and 3) sequential orientation. A rating scale with specific descriptors is then proposed.
The impact of generative AI-powered chatbots on L2 comprehensibility
Authors: Sonsaat-Hegelheimer Sinem , Kurt Şebnem 
Published: February 2025

Abstract
While generative AI-based chatbots expand opportunities for L2 pronunciation practice, not all are designed for
language learning or provide explicit feedback. Through a comparison of two chatbots, Pronounce, which offers
explicit pronunciation feedback, and Gemini, a general-purpose chatbot whose real-time transcription may serve as
implicit feedback, this study explored whether practice with these chatbots had an impact on L2 English learners’
comprehensibility and whether any improvements were influenced by the presence of explicit feedback. Three groups of learners
participated: two experimental groups, each practicing with one of the chatbots, and one control group. Although comprehensibility
ratings indicated no statistically significant improvements at the group level based on training or the specific chatbot used,
individual learners demonstrated improvements. These advancements were noted among motivated learners who completed most of their
speaking sessions. Learners had positive impressions of their experience with the chatbots and believed that their practice
contributed to their pronunciation improvement.
Straintronic magnetic tunnel junctions for analog computation: A perspective
Authors: Bandyopadhyay Supriyo 
Published: February 2025

Abstract
The straintronic magnetic tunnel junction (s-MTJ) is an MTJ whose resistance state can be changed continuously or gradually from high to low with a gate voltage that generates strain the magnetostrictive soft layer. This unusual feature, not usually available in MTJs that are switched abruptly with spin transfer torque, spin-orbit torque or voltage-controlled-magnetic-anisotropy, enables many analog applications where the typically low tunneling magneto-resistance ratio of MTJs (on/off ratio of the switch) and the relatively large switching error rate are not serious impediments unlike in digital logic or memory. More importantly, the transfer characteristic of a s-MTJ (conductance versus gate voltage) always sports a linear region that can be exploited to implement analog arithmetic, vector matrix multiplication and linear synapses in deep learning networks very effectively. In these applications, the s-MTJ is actually superior to the better known memristors and domain wall synapses which do not exhibit the linearity and/or the analog behavior.
A deep learning model for inter-fraction head and neck anatomical changes in proton therapy
Authors: Burlacu Tiberiu , Hoogeman Mischa , Lathouwers Danny , Perkó Zoltán 
Published: February 2025

Abstract

Objective: To assess the performance of a probabilistic deep learning based algorithm for predicting inter-fraction anatomical changes in head and neck patients.&#xD;&#xD;Approach: A probabilistic daily anatomy model for head and neck patients (DAMHN) is built on the variational autoencoder architecture. The model approximates the generative joint conditional probability distribution of the repeat computed tomography (rCT) images and their corresponding masks on the planning CT images (pCT) and their masks. The model outputs deformation vector fields, which are used to produce possible rCTs and associated masks. The dataset is composed of 93 patients (i.e., 315 pCT - rCT pairs), 9 (i.e., 27 pairs) of which were set aside for final testing. The performance of the model is assessed based on the reconstruction accuracy and the generative performance for the set aside patients. &#xD;&#xD;Main results: The model achieves a DICE score of 0.83 and an image similarity score (NCC) of 0.60 on the test set. The generated parotid glands, spinal cord and constrictor muscle volume change distributions and center of mass shift distributions were also assessed. For all organs, the medians of the distributions are close to the true ones, and the distributions are broad enough to encompass the real observed changes. Moreover, the generated images display anatomical changes in line with the literature reported ones, such as the medial shifts of the parotids glands. &#xD;&#xD;Significance: DAMHN is capable of generating realistic anatomies observed during the course of the treatment and has applications in anatomical robust optimization, treatment planning based on plan library approaches and robustness evaluation against inter-fractional changes.
Detecting ionized bubbles around luminous sources during the reionization era using HI 21 cm signal
Authors: Mishra Arnab , Murmu Chandra Shekhar , Datta Kanan K. , Choudhuri Samir , Majumdar Suman , Nasreen Iffat , Ali Sk. Saiyad 
Published: February 2025

Abstract
Measuring the properties of the intergalactic medium (IGM) and sources during the Epoch of Reionization (EoR) is of immense importance. We explore the prospects of probing the IGM and sources through redshifted 21 cm observations of individual ionized bubbles surrounding known luminous sources during the EoR.
Accordingly, we simulate HI 21 cm maps, foreground contaminants, and system noise which are specific to the uGMRT and SKA1-Low observations. Following the subtraction of the foreground from the total visibility, we employ a visibility-based matched filter technique to optimally combine the desired HI 21 cm signal while minimizing the system noise.
Our analysis suggests that these ionized bubbles can be detected with more than 5σ significance using approximately ∼ 2000 and ∼ 3000 hours of observation time with the uGMRT at redshift 7.1 and 8.3, respectively, when the mean neutral hydrogen fraction outside the targeted bubble is ∼ 0.9. The SKA1-Low should be able to detect these bubbles with more than 8 σ significance using only ∼ 100 hrs of observations. The total observing time increases both for the uGMRT and SKA1-Low when the mean neutral hydrogen fraction outside the targeted bubble decreases. Further, we investigate the impact of foreground subtraction on the detectability and find the signal-to-noise ratio decreases when smaller bandwidth is used. More importantly, we show that the matched filtering method can measure ionized bubble radius and constrain HI-neutral fraction reasonably well, providing deeper insights into the source properties and the intergalactic medium.
Ionospheric effect on the synthetic Epoch of Reionization observations with the SKA1-Low
Authors: Pal Samit Kumar , Datta Abhirup , Mazumder Aishrila 
Published: February 2025

Abstract
The redshifted 21 cm signal of neutral hydrogen can be used as a direct probe of the intergalactic medium during Cosmic Dawn (CD) and Epoch of Reionization (EoR). However, detecting this inherently weak signal has numerous challenges. The major ones include accurate foreground removal from low-frequency radio observations and systematics arising from instrumental effects. The Earth's ionosphere poses a major obstacle at these low radio frequencies. Thus, a systematic study of ionospheric effects on these sensitive low-frequency observations is critical, given that the construction of the Square Kilometre Array (SKA1-Low) is in full progress. We use the end-to-end pipeline, called 21cmE2E, to study the effect of time-varying ionospheric corruption on the 21 cm power spectrum recovery. We use two models: a) a catalogue-based model focused on source position shift due to the refractive effect of the ionosphere and b) a realistic ionospheric condition generated using Kolmogorov's turbulence model. We assess the effect of the imperfections thus generated on the extraction of Hi 21 cm signal power spectrum. Our study shows that beyond “median ionospheric offset” (θ
MIO ≲ 0.1”), the 21 cm signal from the EoR is unaffected by residual ionospheric effects. Our study emphasizes the need for the development of efficient ionospheric calibration algorithms for the upcoming SKA1-Low observations to extract the Hi 21 cm power spectra from the CD/EoR.
High-energy and ultra-high-energy neutrinos from Primordial Black Holes
Authors: Wu Quan-feng , Xu Xun-Jie 
Published: February 2025

Abstract
Primordial Black Holes (PBHs) are capable of emitting
extremely energetic particles independent of their interactions with
the Standard Model. In this work, we investigate whether PBHs evaporating
in the early universe could be responsible for some of the observed
high-energy neutrinos above the TeV or PeV scale in the present universe.
We compute the energy spectrum of neutrinos directly emitted by PBHs
with a monochromatic mass function and estimate the wash-out point,
which determines the maximum energy of the spectrum. We find that
the spectrum generally extends to high energies following a power
law of E

ν

-3 until it reaches the wash-out point, which
crucially depends on the PBH mass. For PBHs of 1013 grams, the
spectrum can extend up to the PeV scale, though the flux is too low
for detection. We also consider an indirect production mechanism involving
dark particles that are emitted by PBHs and decay into neutrinos at
a much later epoch. This mechanism allows lighter (such as those in
the gram to kilogram range) PBHs to produce more energetic neutrino
fluxes without being washed out by the thermal plasma in the early
universe. In this scenario, we find that ultra-high-energy neutrinos
around or above the EeV scale can be generated, with sufficiently
high fluxes detectable by current and future high-energy neutrino
observatories such as IceCube and GRAND.
Precision Assessment of Micro-Thruster Performance: A Comparative Study of In-FEEP Thrust Measurement Methods with Force-feedback Pendulum
Authors: Cai Bo-Song , Shen Yan , Zhong Yuan , Liu Jian-Ping , Wang Yu-Qing , Li Zhu , Tu Liang-Cheng , Yang ShanQing 
Published: February 2025

Abstract
Accurate thrust assessment is crucial for characterizing the performance of micro-thrusters. This paper presents a comprehensive evaluation of the thrust generated by a needle-type Indium Field Emission Electric Propulsion (In-FEEP) micro-thruster using three methods based on a pendulum: direct thrust measurement, indirect plume momentum transfer, and beam current diagnostics. The experimental setup utilized capacitive displacement sensors for force detection and a voice coil motor as a feedback actuator, achieving a resolution better than 0.1 μN. Key performance factors such as ionization and plume divergence of ejected charged particles were also examined. The study revealed that the high applied voltage induces significant electrostatic interference, becoming the dominant source of error in direct thrust measurements. Beam current diagnostics and indirect plume momentum measurements were conducted simultaneously, showing strong agreement within a deviation of less than 0.2 μN across the operational thrust range. The results from all three methods were consistent within the error margins, verifying the reliability of the indirect measurement approach and the theoretical thrust model based on In-FEEP’s electrical parameters.
Visual synapse based on reconfigurable organic photovoltaic cell
Authors: Pu Xiangrong , Shu Fan , Wang Qifan , Liu Gang , Zhang Zhang 
Published: February 2025

Abstract
The hierarchical and coordinated processing of visual information by the brain demonstrates its superior ability to minimize energy consumption and maximize signal transmission efficiency. Therefore, it is crucial to develop artificial visual synapses that integrate optical sensing and synaptic functions. This study fully leverages the excellent photoresponsivity properties of the PM6 : Y6 system to construct a vertical photo-tunable organic memristor and conducts in-depth research on its resistive switching performance, photodetection capability, and simulation of photo-synaptic behavior, showcasing its excellent performance in processing visual information and simulating neuromorphic behaviors. The device achieves stable and gradual resistance change, successfully simulating voltage-controlled long-term potentiation/depression (LTP/LTD), and exhibits various photo-electric synergistic regulation of synaptic plasticity. Moreover, the device has successfully simulated the image perception and recognition functions of the human visual nervous system. The non-volatile Au/PM6 : Y6/ITO memristor is used as an artificial synapse and neuron modeling, building a hierarchical coordinated processing SLP-CNN cascade neural network for visual image recognition training, its linear tunable photoconductivity characteristic serves as the weight update of the network, achieving a recognition accuracy of up to 93.4%. Compared with the single-layer visual target recognition model, this scheme has improved the recognition accuracy by 19.2%.
6-inch AlN epitaxial films with low dislocation densities via MOCVD
Authors: Lu Shunpeng , Ben Jianwei , Jiang Ke , Zhang Shanli , Zhang Ruojia , Hao Jialong , Liu Zhongxu , Sun Wenchao , Nie Zikai , Sun Xiaojuan , Li Dabing 
Published: February 2025

Abstract
High-quality AlN epitaxial layers with low dislocation densities and uniform crystal quality are essential for next-generation optoelectronic and power devices. This study reports the epitaxial growth of 6-inch AlN films on 17 nm AlN/sapphire templates using metal−organic chemical vapor deposition (MOCVD). Comprehensive characterization reveals significant advancements in crystal quality and uniformity. Atomic force microscopy (AFM) shows progressive surface roughness reduction during early growth stages, achieving stabilization at a root mean square (RMS) roughness of 0.216 nm within 3 min, confirming successful 2D growth mode. X-ray rocking curve (XRC) analysis indicates a marked reduction in the (0002) reflection full width at half maximum (FWHM), from 445 to 96 arcsec, evidencing effective dislocation annihilation. Transmission electron microscopy (TEM) demonstrates the elimination of edge dislocations near the AlN template interface. Stress analysis highlights the role of a highly compressive 17 nm AlN template (5.11 GPa) in facilitating threading dislocation bending and annihilation, yielding a final dislocation density of ~1.5 × 107 cm−2. Raman spectroscopy and XRC mapping confirm excellent uniformity of stress and crystal quality across the wafer. These findings demonstrate the feasibility of this method for producing high-quality, large-area, atomically flat AlN films, advancing applications in optoelectronics and power electronics.
Determination of Multi-elements in Boron Carbide Reinforced Aluminum Matrix Composites by Inductively Coupled Plasma Emission Spectrometry
Authors: Chen Qianqian , Guo Xingjie , Pan Hengpei , Zhang Yi , Zhang Jianhao , Liu Pan 
Published: February 2025

Abstract
Boron carbide reinforced aluminum matrix composites have the respective characteristics of boron carbide and aluminum alloys, and have been widely used in the nuclear field. The content of alloy components such as iron, manganese, zinc, chromium, copper, silicon, titanium, magnesium and boron is crucial to the quality control of products. Based on inductively coupled plasma atomic emission spectrometry (ICP-AES), the analysis of multi-elements in boron carbide reinforced aluminum matrix composites has been studied in this paper. RF power, atomization gas flow rate, plasma gas flow rate, observation height and other instrumental parameters were optimized and determined. The specific parameters were as follows: RF power 1.15 kW, atomization gas flow rate 0.7 L/min, plasma gas flow rate 11.0 L/min, observation height 7 mm, carrier gas: argon, pump speed: 12 r/min, stabilization time: 10 s, reading time: 6 s, lifting delay: 20 s, observation mode: radial, repetition times: 3 times, analysis spectrum lines: Fe 259.940 nm, Mn 257.610 nm, Zn 206.200 nm, Cr 267.716 nm, Cu 327.395 nm, Si 288.158 nm, Ti 327.280 nm, Mg 280.270 nm, B 249.772 nm, background correction mode: fitting. The linear correlation coefficient of the calibration curve is not less than 0.999 in the linear range of each element. A rapid method for the determination of multi-elements in boron carbide reinforced aluminum matrix composites by inductively coupled plasma emission spectrometry (ICP-AES) has been established. The quantitative limit, precision and accuracy can meet the needs of practical inspection.
Salivary metabolites profiling for diagnosis of COPD：an exploratory study
Authors: Zhang Zherong , Lv Yan , Gong Meng , Li Juan , Zhang Yayun , Wu Songze , Zhang Yu , Cheng Deyun , Fan Tao 
Published: February 2025

Abstract
Introduction: Pulmonary function tests (PFTs) are the gold standard for diagnosing of Chronic obstructive pulmonary disease (COPD). Given its limitation in some scenarios, it is imperative to develop new high-throughput screening methods for biomarkers in diagnosing COPD. This study aims to explore the feasibility of screening novel diagnostic biomarkers based on salivary metabolomics for the limited availability of PFTs and difficulties in implementation at primary care facilities.&#xD;&#xD;Methods: Participants were recruited from the outpatient department of West China Hospital. Saliva samples were collected to analyze the metabolites through the UPLC-Q-Exactive Orbitrap-MS platform. The raw data from the mass spectrometer was preprocessed with R software after peak extraction. The Wilcoxon rank sum test, Fold change analysis, PCA and OPLS-DA were used to identify potential biomarkers. The ROC curve was used to assess the diagnostic efficacy of the predictive model generated by potential biomarkers.&#xD;&#xD;Results: Saliva samples were collected from 66 patients with COPD and 55 healthy volunteers. Significant differences in the salivary metabolome between COPD patients and healthy controls were identified, with 261 differential metabolites recognized, 16 of which were considered as potential biomarker. The diagnostic model generated by these 16 biomarkers can successfully distinguish COPD patients from healthy people. &#xD;&#xD;Conclusions &#xD;Salivary metabolomic profiling is likely to emerge as a promising method for screening potential diagnostic biomarkers of COPD. Further prospective studies with large sample size are needed to verify the predictive value of these biomarkers in COPD diagnosis.&#xD;