bluuebunny/crossref_metadata_2025_split huggingface dataset:
Characteristics of Wave‐Particle Power Transfer as a Function of Electron Pitch Angle in Nonlinear Frequency Chirping
Authors: Wu Zeyin , Wu Yifan , Tao Xin 
Published: February 2025

AbstractWhistler mode chorus waves, common in Earth's and planetary magnetospheres, play a crucial role in energetic electron dynamics. These waves exhibit distinctive narrowband features, intense amplitudes, and frequency chirping. While numerous studies have explored chorus wave generation, an important yet often overlooked parameter is the resonant electron pitch angle. Motivated by this gap, we conduct particle‐in‐cell (PIC) simulations to identify the key pitch angle governing wave‐particle power transfer during interactions with chorus waves. Our findings reveal that the characteristic pitch angle, which dominates power transfer, aligns with the pitch angle that minimizes the nonlinear parameter during the central portion of a chirping element. This insight supports the use of a representative pitch angle in nonlinear theories of chorus waves to estimate wave properties.
Attenuation of Hydro‐Sediment Dynamics Progradation Over Mangrove Wetland
Authors: Jiang Wenting , Huang Zuming , Dai Zhijun , Luo Jiejun , Zeng Wenjun , Liang Xixing 
Published: February 2025

AbstractMangrove wetlands are one of the vital ecological resources that effectively trap sediment and attenuate the dynamic of waves and currents, thus protecting coastal areas from the onslaught of typhoons. Despite their importance, there is a dearth of knowledge regarding how mangrove dynamics influence hydro‐sediment dynamics and dissipation effects. Here, the wave, current, and sediment data, along with sediment particle size and mangrove vegetation parameters are used to analyze the variation of hydro‐sediment dynamics along the mangrove wetland. Our findings reveal that bottom flow velocities exhibit a continuous clockwise dispersion in a disordered pattern from the bare flats into the mangrove interior, influenced by the increasing density of mangroves. Furthermore, the hydro‐sediment elements exhibit pronounced tidal asymmetry, with the values of bottom velocity, suspended sediment concentration, and suspended sediment flux (SSF) shifting from being higher during flood tides to being higher during ebb tides due to tidal motion. Meanwhile, we found that the SSF at the mangrove edge may be the main source of the elevation changes at the mangrove interior. The vertical structure of Aegiceras corniculatum significantly affects sediment transport, with a notable decrease in SSF in areas with dense canopies. This study contributes to the body of knowledge on mangrove dynamics and their impact on sediment transport and hydro‐sediment damping, providing valuable insights for mangrove conservation and restoration efforts.
Wavelet Multi‐Scale Analysis of the Linear Gravity Anomalies of the Moon
Authors: Wan Yan , Chen Bo , Xu Changyi , Du Jinsong 
Published: February 2025

AbstractThe history of the thermal and dynamic evolution of the Moon is partly recorded by lunar linear structures. Identification and analysis of subsurface linear structures and their associated gravity anomalies provide insights into the early evolution of the Moon. However, the current understanding of their deep extensions is limited. In this study, we employ gravity data and the 2D continuous wavelet transform technique to analyze the subsurface extension of linear structures. Four significant linear gravity anomalies (LGAs) are studied, including the north (FN) and south (FS) anomalies located in the lunar farside and the northwest (NNW) and northeast (NNE) anomalies in the nearside. Our results indicate that the top depths and widths of the mass sources associated with these linear structures can be determined. The intrusion depths of all four LGAs vary along their strike, with the shallowest intrusion depth reaching 8–10 km. For the FN anomaly, the top depths of the intrusive body range from 8 to 20 km, while intrusion widths vary between 30 and 50 km. Wavelet analysis for the FS anomaly indicates an intrusive source with a top width and depth of ∼30 and 10 km. For the NNW anomaly, the source body has top depths of 10–20 km with varying top widths at different sections (25∼50 km). As for the NNE structure, our results suggest substantial top widths between 75 and 150 km alongside relatively shallow top depths of 8–15 km. These LGAs are likely attributed to vertical magma intrusions connected at their bases to the crust‐mantle interface.
Coupled Lake‐Atmosphere‐Land Physics Uncertainties in a Great Lakes Regional Climate Model
Authors: Pringle William J. , Huang Chenfu , Xue Pengfei , Wang Jiali , Sargsyan Khachik , Kayastha Miraj B. , Chakraborty T. C. , Yang Zhao , Qian Yun , Hetland Robert D. 
Published: February 2025

AbstractThis study develops a surrogate‐based method to assess the uncertainty within a convective permitting integrated modeling system of the Great Lakes region, arising from interacting physics parameterizations across the lake, atmosphere, and land surface. Perturbed physics ensembles of the model during the 2018 summer are used to train a neural network surrogate model to predict lake surface temperature (LST) and near‐surface air temperature (T2m). Average physics uncertainties are determined to be 1.5C for LST and T2m over land, and 1.9C for T2m over lake, but these have significant spatiotemporal variations. We find that atmospheric physics parameterizations alone are the dominant sources of uncertainty (45%–53%), while lake and land parameterizations account for 33% and 38% of the uncertainty of LST and T2m over land respectively. Interactions of atmosphere physics parameterizations with those of the land and lake contribute to an additional 13%–17% of the total variance. LST and T2m over the lake are more uncertain in the deeper northern lakes, particularly during the rapid warming phase that occurs in late spring/early summer. The LST uncertainty increases with sensitivity to the lake model's surface wind stress scheme. T2m over land is more uncertain over forested areas in the north, where it is most sensitive to the land surface model, than the more agricultural land in the south, where it is most sensitive to the atmospheric planetary boundary and surface layer scheme. Uncertainty also increases in the southwest during multiday temperature declines with higher sensitivity to the land surface model.
Development of composite electrolyte membranes with functional polymer nanofiber frameworks
Authors: Kawakami Hiroyoshi 
Published: February 2025

Abstract
Solid electrolyte membranes based on polymers have shown promise owing to their high-energy demand and the sustainable and cost-effective nature of these materials. However, polymer electrolyte membranes composed of a polymer matrix have not progressed for the following reasons: (1) the low ion conductivity of polymer materials cannot achieve the level required for practical use, and (2) it is difficult to satisfy both battery performance and membrane durability simultaneously because of the trade-offs between ion conductivity and membrane stability. In recent years, research on composite electrolyte membranes composed of polymer nanofibers and a polymer matrix has attracted significant interest because of their improved ion conductivity, excellent membrane durability, and ability to fabricate thinner membranes. Polymeric nanofiber-containing polymer electrolyte membranes are expected to be applied not only to electrolyte membranes for fuel cells and water electrolysis, including alkaline-type electrolyte membranes for water electrolysis, but also to all-solid-state Li-ion batteries and all-solid-state Li-air batteries. This focus review presents the latest information on these topics.
Addressing the Gaps in the Vitamin B12 Deficiency 2024 NICE Guidelines: Highlighting the Need for Better Recognition, Diagnosis, and Management of Pernicious Anaemia
Authors: Thain Alfie , Hart Kathryn , Ahmadi Kourosh R. 
Published: February 2025

Abstract
The 2024 NICE guidelines on vitamin B12 deficiency have significant implications for the diagnosis and management of pernicious anaemia (PA), the commonest non-dietary cause of such deficiency. This perspective discusses the guidelines in relation to PA itself, suggests that clearer diagnostic protocols are required, and calls for clinician education to improve the patient journey for those with PA.
High-throughput numerical modeling of the tunable synaptic behavior in 2D MoS2 memristive devices
Authors: Spetzler Benjamin , Sangwan Vinod K. , Hersam Mark C. , Ziegler Martin 
Published: February 2025

Abstract
Memristive devices based on two-dimensional (2D) materials have emerged as potential synaptic candidates for next-generation neuromorphic computing hardware. Here, we introduce a numerical modeling framework that facilitates efficient exploration of the large parameter space for 2D memristive synaptic devices. High-throughput charge-transport simulations are performed to investigate the voltage pulse characteristics for lateral 2D memristors and synaptic device metrics are studied for different weight-update schemes. We show that the same switching mechanism can lead to fundamentally different pulse characteristics influencing not only the device metrics but also the weight-update direction. A thorough analysis of the parameter space allows simultaneous optimization of the linearity, symmetry, and drift in the synaptic behavior that are related through tradeoffs. The presented modeling framework can serve as a tool for designing 2D memristive devices in practical neuromorphic circuits by providing guidelines for materials properties, device functionality, and system performance for target applications.
Foundations of a knee joint digital twin from qMRI biomarkers for osteoarthritis and knee replacement
Authors: Hoyer Gabrielle , Gao Kenneth T. , Gassert Felix G. , Luitjens Johanna , Jiang Fei , Majumdar Sharmila , Pedoia Valentina 
Published: February 2025

Abstract
This study forms the basis of a digital twin system of the knee joint, using advanced quantitative MRI (qMRI) and machine learning to advance precision health in osteoarthritis (OA) management and knee replacement (KR) prediction. We combined deep learning-based segmentation of knee joint structures with dimensionality reduction to create an embedded feature space of imaging biomarkers. Through cross-sectional cohort analysis and statistical modeling, we identified specific biomarkers, including variations in cartilage thickness and medial meniscus shape, that are significantly associated with OA incidence and KR outcomes. Integrating these findings into a comprehensive framework represents a considerable step toward personalized knee-joint digital twins, which could enhance therapeutic strategies and inform clinical decision-making in rheumatological care. This versatile and reliable infrastructure has the potential to be extended to broader clinical applications in precision health.
A twenty-first century structural change in Antarctica’s sea ice system
Authors: Raphael Marilyn N. , Maierhofer Thomas J. , Fogt Ryan L. , Hobbs William R. , Handcock Mark S. 
Published: February 2025

Abstract
From 1979 to 2016, total Antarctic sea ice extent experienced a positive trend with record winter maxima in 2012 and 2014. Record summer minima followed within the period 2017-2024, raising the possibility that the Antarctic sea ice system might be changing state. Here we use a Bayesian reconstruction of Antarctic sea ice extent which extends the record back to 1899, to show that the sequence of extreme minima in summer Antarctic sea ice extent is unlikely to have happened in the 20th century. We show that they represent a structural change in the sea ice system, manifest by increased persistence in the sea ice extent anomalies and a strongly reduced tendency to return to the mean state. Further, our analysis suggests that we may no longer rely on the past, long-term, behavior of the sea ice system to predict its future state. Extreme conditions may characterize the future state of Antarctic sea ice.
Asymptotic Stabilization for Uncertain Nonlinear Systems With Input Quantization
Authors: Yan Fei , Wang Shuo , Gu Guoxiang 
Published: February 2025

ABSTRACTThis paper investigates the problem of asymptotic stabilization for a class of uncertain nonlinear systems involving logarithmic quantization at the system input. Different from the existing results and approaches, a Lyapunov function candidate and an adaptive control law are developed to adaptively estimate the uncertain parameters and to asymptotically stabilize the uncertain nonlinear system, in which the control input also involves uncertain parameters, possibly in the nonlinear form. It is shown that asymptotic stabilization can be achieved under some mild conditions, even though the adaptively estimated parameters do not converge to the true system parameters. A sufficient condition is obtained for the asymptotic stabilizability, in terms of the quantization density and the multiplicative parameter error bound at the control input. More importantly, the proposed adaptive control law is suboptimal for the corresponding LQR control and achieves the ‐norm to be strictly smaller than , provided that , for the uncertain linearized closed‐loop system, effectively suppressing energy bounded disturbances. Finally, two simulation examples are worked out to illustrate the effectiveness of the proposed method.
Research on Arc Ignition Characteristics of Cables’ Insulation Under Different Temperatures Considering Thickness
Authors: Liu Jingli , Zhong Yuyao , Shan Yu , Xie Qing , Li Yan 
Published: February 2025

ABSTRACTInternal arc faults in cables are a significant cause of cable fires, with the cable temperature being time‐dependent due to varying loading levels. Thus, it is necessary to study the characteristics of arc‐induced cable ignition considering the influence of temperature, which have been rarely addressed in previous studies. In this paper, an experimental platform for alternating current arc generation is established. This platform records and analyses the arc development's morphological characteristics, the voltage and current waveform changes at both electrode ends, and the electrodes' temperature distribution. Moreover, two types of cable insulation materials, i.e. cross‐linked polyethylene (XLPE) and polyvinyl chloride (PVC) with different thickness and temperature, are tested to study the arc‐induced ignition characteristics of cables. By comparing ignition times and combustion intensities within the same time frame, the characteristics of arc‐induced ignition are analysed. It can be concluded that the insulation temperature accelerates the arc‐ignition process significantly. For XLPE, the ignition time under 70°C can be reduced around 11%. Thick XLPE (1.6 mm) can delay the ignition time up to 1.5 times compared with thin one (0.8 mm). PVC exhibits similar behaviour but demonstrates greater resistance to arc‐induced ignition than XLPE.
From prediction to experimental realization of ferroelectric wurtzite Al1−xGdxN alloys
Authors: Lee Cheng-Wei , Smaha Rebecca W. , Brennecka Geoff L. , Haegel Nancy M. , Gorai Prashun , Yazawa Keisuke 
Published: February 2025

AlN-based alloys find widespread application in high-power microelectronics, optoelectronics, and electromechanics. The realization of ferroelectricity in wurtzite AlN-based heterostructural alloys has opened up the possibility of directly integrating ferroelectrics with conventional microelectronics based on tetrahedral semiconductors, such as Si, SiC, and III–Vs, enabling compute-in-memory architectures, high-density data storage, and more. The discovery of AlN-based wurtzite ferroelectrics has been driven to date by chemical intuition and empirical explorations. Here, we demonstrate the computationally-guided discovery and experimental demonstration of new ferroelectric wurtzite Al1−xGdxN alloys. First-principles calculations indicate that the minimum energy pathway for switching changes from a collective to an individual switching process with a lower overall energy barrier, at a rare-earth fraction x with x &gt; 0.10–0.15. Experimentally, ferroelectric switching is observed at room temperature in Al1−xGdxN films with x &gt; 0.12, which strongly supports the switching mechanisms in wurtzite ferroelectrics proposed previously [Lee et al., Sci. Adv. 10, eadl0848 (2024)]. This is also the first demonstration of ferroelectricity in an AlN-based alloy with a magnetic rare-earth element, which could pave the way for additional functionalities such as multiferroicity and opto-ferroelectricity in this exciting class of AlN-based materials.
PALADIN: A novel plug-and-play 3D CS-MRI reconstruction method
Authors: Wu Jia-Mian , Yin Shibai , Jiang Tai-Xiang , Liu Guisong , Zhao Xi-Le 
Published: February 2025

Abstract
Compressive sensing magnetic resonance imaging (CS-MRI) accelerates data acquisition by reconstructing high-quality images from a limited set of $k$-space samples. To solve this ill-posed inverse problem, the plug-and-play (PnP) framework integrates image priors using convolutional neural network (CNN) denoisers. However, CNN denoisers often prioritize local details and may neglect broader degradation effects, leading to visually plausible but structurally inaccurate artifacts. Additionally, the theoretical convergence of PnP methods remains a significant challenge.&#xD;In this work, we propose a novel method, Plug-And-pLAy 3D MRI recoNstruction (PALADIN), to bridge the gap between denoising and MRI reconstruction. Our model employs the tensor tubal nuclear norm (TNN) to capture intrinsic correlations in 3D MRI data. It also incorporates two implicit regularizers. The first leverages CNN denoisers to exploit image priors. The second, introduced here for the first time, is formulated as a CS-MRI reconstruction subproblem and solved using a deep learning-based method to preserve global spatial structure.&#xD;We solve the proposed model using the alternating direction method of multipliers (ADMM). We extend existing theoretical results to prove the algorithm's convergence to a fixed point under reasonable assumptions.&#xD;Experiments on two datasets with three sampling masks show that our method outperforms state-of-the-art MRI reconstruction methods. Ablation studies confirm that the TNN and the two implicit regularizers work together to improve reconstruction quality.
Fundamental aspects of Aharonov-Bohm quantum machines: Thermoelectric heatengines and diodes
Authors: Bedkihal Salil , Behera Jayasmita , Bandyopadhyay Malay 
Published: February 2025

Abstract
The study of heat-to-work conversion has gained considerable attention in recent years, highlighting&#xD;the potential of nanoscale systems to achieve energy conversion in steady-state devices without&#xD;the involvement of macroscopic moving parts. The operation of these devices is predicated on the&#xD;steady-state flows of quantum particles, including electrons, photons, and phonons. This review&#xD;examines the theoretical frameworks governing these steady-state flows within various mesoscopic&#xD;or nanoscale devices, such as thermoelectric heat engines, particularly in the context of quantum dot&#xD;Aharonov-Bohm interferometric configurations. Naturally, quantum interference effects hold great&#xD;promise for enhancing the thermoelectric transport properties of these quantum devices by allowing&#xD;more precise control over energy levels and transport pathways, thus improving heat-to-work conversion.&#xD;Driven quantum dot Aharonov-Bohm networks offer an ideal platform for studying these&#xD;engines, thanks to their ability to maintain quantum coherence and provide precise experimental&#xD;control. Unlike bulk systems, nanoscale systems such as quantum dots reveal distinct quantum interference&#xD;phenomena, including sharp features in transmission spectra and Fano resonances. This&#xD;review highlights the distinction between optimization methods that produce boxcar functions and&#xD;coherent control methods that result in complex interference patterns. This review reveals that the&#xD;effective design of thermoelectric heat engines requires careful tailoring of quantum interference and&#xD;the magnetic field-induced effects to enhance performance. In addition, We focus on the fundamental&#xD;questions about the bounds of these thermoelectric machines. Particular emphasis is given to how&#xD;magnetic fields can change the bounds of power or efficiency and the relationship between quantum&#xD;theories of transport and the laws of thermodynamics. These machines with broken time-reversal&#xD;symmetry provides insights into directional dependencies and asymmetries in quantum transport.&#xD;We offer a thorough overview of past and current research on quantum thermoelectric heat engines&#xD;using the Aharonov-Bohm effect and present a detailed review of three-terminal Aharonov-Bohm&#xD;heat engines, where broken time-reversal symmetry can induce a coherent diode effect. Our review&#xD;also covers bounds on power and efficiency in systems with broken time-reversal symmetry. We&#xD;close the review by presenting open questions, summaries, and conclusions.
Distance measurement between metal tips via plasmon-enhanced NV fluorescence
Authors: Ji Lumin , Zhao Liye , Huang Pu , Wang Yuhai 
Published: February 2025

Abstract
High-precision displacement sensing serves as a cornerstone for measuring numerous physical quantities. Through plasmon-enhanced fluorescence, we propose a nitrogen-vacancy (NV)-based highly sensitive and microwave-free distance measurement scheme for metal tips with a sub-wavelength scale size. The best sensitivity is estimated to be $ 72\ \rm{fm/\sqrt{Hz}}$ with a high bandwidth of $ 21 \ \rm{GHz}$ through simulations and numerical analyses. The study reveals that the sensor performance remains insensitive to fluctuations in plasmon resonance wavelength, indicating the system's inherent tolerance to structural deviations, potentially stemming from manufacturing imperfections. Furthermore, a greater quantum radiation efficiency leads to an improved sensitivity and a wider working range. This low-noise, no-damage, and robust scheme with a high frequency bandwidth has potential applications in on-chip inertial devices and basic physical research.
Investigating the structural and dielectric properties of electrospun nanofibers based on P(VDF-TrFE)/conjugated polymer for optoelectronic applications
Authors: Salim Ehab , Alshehri Naif Ahmed 
Published: February 2025

Abstract
This study investigates the fabrication of semiconductive nanofiber films created from polyvinylidene fluoride-trifluoro ethylene (P(VDF-TrFE)) and Poly [N-9′-heptadecany l-2, 7-carbazole-alt-5, 5- (4′, 7′-di-2-thieny l-2′, 1′, 3′-benzothiadiazole)] (PCDTBT) using the electrospinning technique. Scanning electron microscopy (SEM) revealed that films ranging from 200 to 400 nm in diameter exhibit a smooth fiber topology. Attenuated total reflectance for Fourier transform infrared (ATR-FTIR) spectra showed symmetric, antisymmetric, and non-significant chemical interactions. X-ray diffraction (XRD) analysis revealed a ferroelectric β phase and amorphous structure, with no distinct Bragg diffraction peak. The UV-Vis spectra indicated the presence of semicrystalline P(VDF-TrFE) in the electrospun nanofiber film, where the carbazole units and conjugated main chains resulted in PCDTBT absorption at 415 nm and 589 nm. Blending PCDTBT with P(VDF-TrFE) lowered the band gap and enhanced Urbach energy (EU). Incorporating PCDTBT with P(VDF-TrFE) improved the DC conductivity from 1.42×10-4 S cm-1 to 1.07×10-3 S cm-1. Polarization at the semiconductor-insulator interface improved the nanofiber blend's characteristics, including a lower bulk resistance (Rb) and a greater dielectric constant than P(VDF-TrFE). These Nanofibers may be employed in transparent electrodes and coatings for optoelectronic devices that need visible spectrum transparency and UV protection.