bluuebunny/crossref_metadata_2025_split huggingface dataset:
Rayleigh wave attenuation and phase velocity maps of the greater Alpine region from ambient noise
Authors: Roisenberg Henrique Berger , Magrini Fabrizio , Molinari Irene , Boschi Lapo , Cammarano Fabio 
Published: November 2024

AbstractWe use seismic ambient noise data from 724 publicly available broadband seismic stations across central Europe to create detailed phase velocity and attenuation maps of Rayleigh waves, focusing on short periods down to 3 s. We interpret these maps in terms of the underlying physical processes relevant to the nature of continental crust. Through a regionalized interpretation based on tectonic settings, we highlight the significant role of fluid-filled fractures in the attenuation of surface waves. Our findings indicate a close connection between the time elapsed since the last tectonic activity in the European crust and the attenuation coefficient values. Additionally, we observe a pronounced decrease in attenuation coefficient values at periods below 6 s. The anti-correlation between attenuation coefficient and phase velocity in recently active tectonic regions suggests that fluid-filled fractures are likely the dominant factor governing seismic attenuation in the European crust.
Household-specific barriers to citizen-led flood risk adaptation
Authors: Howard Ben C. , Awuni Cynthia A. , Agyei-Mensah Samuel , Bryant Lee D. , Collins Alexandra M. , Yidana Sandow Mark , Yiran Gerald A. B. , Buytaert Wouter 
Published: November 2024

AbstractAdaptation is essential to mitigate the effects of climate change, such as increasing flood risk. In response to widespread maladaptation, citizen-led approaches are increasingly championed, whereby people on the frontline of climate change determine their own objectives and strategies of adaptation. Enabling equitable and effective citizen-led adaptation requires an understanding of the barriers for different groups of people but this is currently lacking, especially in low- and middle-income countries. Using responses to a co-produced household survey (n = 286) in Tamale, Ghana, we show that barriers to citizen-led adaptation interventions (n = 11) differ between households which we relate to important components of adaptive capacity. Overall, awareness, education, and networks are the most important barriers, but resources and time are important for poor households of fewer members. Barriers also differ between interventions and overall structural interventions are preferred over behavioural. This work can inform policies and actions to support effective and equitable citizen-led adaptation.
Fabrication of a symmetric supercapacitor device using MnO2/cellulose nanocrystals/graphite electrodes via sputtering for energy storage
Authors: Choudhary Nitesh , Tomar Akshay , Singh Shiva , Chandra Ramesh , Maji Pradip K. 
Published: November 2024

This work focuses on MnO2/CNCs/graphite hybrid electrodes with high capacitance and excellent cyclic retention for energy storage. MnO2 was deposited via RF magnetron sputtering to prepare the robust device.
A bionic palladium metal–organic framework based on a fluorescence sensing enhancement mechanism for sensitive detection of phorate
Authors: Li Mengyao , Wang Zhijie , Tang Hongyu , Yang Jingru , Luo Xianwei , Tian Youjia , Yang Mingxin , Jiang Jinhong , Wang Meng , Zheng Lingna , Ma Chenyan , Xing Gengmei , Wang Hongbin , Li Juan 
Published: November 2024

Palladium-based MOF fluorescent nanoprobes achieve fluorescence enhancement through a mechanism similar to the bioluminescence of Chrysaora pacifica. The linear detection range is from 100 ppb to 0.01 ppb, the detection limit is as low as 0.0017 ppb.
Enhanced blur‐robust monocular depth estimation via self‐supervised learning
Authors: Sung Chi‐Hun , Kim Seong‐Yeol , Shin Ho‐Ju , Lee Se‐Ho , Kim Seung‐Wook 
Published: November 2024

AbstractThis letter presents a novel self‐supervised learning strategy to improve the robustness of a monocular depth estimation (MDE) network against motion blur. Motion blur, a common problem in real‐world applications like autonomous driving and scene reconstruction, often hinders accurate depth perception. Conventional MDE methods are effective under controlled conditions but struggle to generalise their performance to blurred images. To address this problem, we generate blur‐synthesised data to train a robust MDE model without the need for preprocessing, such as deblurring. By incorporating self‐distillation techniques and using blur‐synthesised data, the depth estimation accuracy for blurred images is significantly enhanced without additional computational or memory overhead. Extensive experimental results demonstrate the effectiveness of the proposed method, enhancing existing MDE models to accurately estimate depth information across various blur conditions.
PitRSDNet: Predicting intra‐operative remaining surgery duration in endoscopic pituitary surgery
Authors: Wijekoon Anjana , Das Adrito , Herrera Roxana R. , Khan Danyal Z. , Hanrahan John , Carter Eleanor , Luoma Valpuri , Stoyanov Danail , Marcus Hani J. , Bano Sophia 
Published: November 2024

AbstractAccurate intra‐operative Remaining Surgery Duration (RSD) predictions allow for anaesthetists to more accurately decide when to administer anaesthetic agents and drugs, as well as to notify hospital staff to send in the next patient. Therefore, RSD plays an important role in improved patient care and minimising surgical theatre costs via efficient scheduling. In endoscopic pituitary surgery, it is uniquely challenging due to variable workflow sequences with a selection of optional steps contributing to high variability in surgery duration. This article presents PitRSDNet for predicting RSD during pituitary surgery, a spatio‐temporal neural network model that learns from historical data focusing on workflow sequences. PitRSDNet integrates workflow knowledge into RSD prediction in two forms: (1) multi‐task learning for concurrently predicting step and RSD; and (2) incorporating prior steps as context in temporal learning and inference. PitRSDNet is trained and evaluated on a new endoscopic pituitary surgery dataset with 88 videos to show competitive performance improvements over previous statistical and machine learning methods. The findings also highlight how PitRSDNet improves RSD precision on outlier cases utilising the knowledge of prior steps.
Ground moving target indication of polarimetric interferometric synthetic aperture radar using joint scattering vector
Authors: Xu Jing , Cheng Long , Yu Chunhui , Zhang Shiwei 
Published: November 2024

AbstractGround moving target indication (GMTI) plays a critical role in both civilian applications and military applications. The accuracy of complex images coregistration is a major factor for multichannel synthetic aperture radar (SAR) GMTI. Moreover, polarimetric interferometric SAR (PolInSAR) represents a growing strength in multi‐function radar systems. In response to this, we propose a new SAR‐GMTI approach tailored for the PolInSAR system. To address the deterioration in clutter suppression performance caused by the coregistration errors, we construct a joint scattering vector (JSV) for polarimetric SAR (PolSAR) by incorporating the neighbouring vectors of the central pixel. Subsequently, the covariance matrix of JSV is estimated and subjected to eigen‐decomposed. Clutter suppression of the PolInSAR system for GMTI is performed using eigen‐subspace projection, where the JSV is projected onto noise subspace. This method is robust against coregistration errors since all ground moving target information is encapsulated within the JSV. Furthermore, the improvement factors with different clutter backgrounds (by changing the signal‐to‐clutter‐plus‐noise‐ratio, SCNR) are analysed. The effectiveness of the proposed JSV‐based method is validated using simulated PolInSAR data.
DDANet: A deep dilated attention network for intracerebral haemorrhage segmentation
Authors: Liu Haiyan , Zeng Yu , Li Hao , Wang Fuxin , Chang Jianjun , Guo Huaping , Zhang Jian 
Published: November 2024

AbstractIntracranial haemorrhage (ICH) is an urgent and potentially fatal medical condition caused by brain blood vessel rupture, leading to blood accumulation in the brain tissue. Due to the pressure and damage it causes to brain tissue, ICH results in severe neurological impairment or even death. Recently, deep neural networks have been widely applied to enhance the speed and precision of ICH detection yet they are still challenged by small or subtle hemorrhages. The authors introduce DDANet, a novel haematoma segmentation model for brain CT images. Specifically, a dilated convolution pooling block is introduced in the intermediate layers of the encoder to enhance feature extraction capabilities of middle layers. Additionally, the authors incorporate a self‐attention mechanism to capture global semantic information of high‐level features to guide the extraction and processing of low‐level features, thereby enhancing the model's understanding of the overall structure while maintaining details. DDANet also integrates residual networks, channel attention, and spatial attention mechanisms for joint optimisation, effectively mitigating the severe class imbalance problem and aiding the training process. Experiments show that DDANet outperforms current methods, achieving the Dice coefficient, Jaccard index, sensitivity, accuracy, and a specificity of 0.712, 0.601, 0.73, 0.997, and 0.998, respectively. The code is available at https://github.com/hpguo1982/DDANet.
Impacts of band edge fluctuations on CdSeTe solar cell performance and models
Authors: Rosenblatt Nathan , Hack James , Lee Chungho , Zhang Yong-Hang , Metzger Wyatt K. 
Published: November 2024

Thin film solar cells often have high densities of dopants and native defects that result in carrier compensation and local electrostatic fields, which produce band edge fluctuations observable as tails in luminescence and absorption spectra. The analysis here shows that these fluctuations can reduce the open-circuit voltage (Voc) by tens to hundreds of millivolts and alter the Voc temperature coefficients. Although the extrapolation of Voc to 0 K is often used to gauge interface recombination, reductions in this value can also be explained by band edge fluctuations. In addition, these fluctuations can explain pronounced anomalous trends between carrier concentration and Voc in state-of-the-art CdSeTe:As solar cells, representing a significant departure from device models that do not include them. The analysis can be applied to other thin film technologies. To improve CdSeTe solar cell performance, it is critical to assess band edge fluctuations and address carrier compensation and defect chemistry to mitigate their impact.
Partial absence of cosine problem in 3D Lorentzian spin foams
Authors: Jercher Alexander F , Simão José D , Steinhaus Sebastian 
Published: November 2024

Abstract
We study the semi-classical limit of the recently proposed coherent spin foam model for (2+1) Lorentzian quantum gravity. Specifically, we analyze the gluing equations derived from the stationary phase approximation of the vertex amplitude. Typically these exhibit two solutions yielding a cosine of the Regge action. However, by inspection of the algebraic equations as well as their geometrical realization, we show in this note that the behavior is more nuanced: when all triangles are either spacelike or timelike, two solutions exist. In any other case, only a single solution is obtained, thus yielding a single Regge exponential.
On the null space of the backprojection operator and Rubin’s conjecture for the spherical mean transform
Authors: Agrawal Divyansh , Ambartsoumian Gaik , Krishnan Venkateswaran P , Singhal Nisha 
Published: November 2024

Abstract
The spherical mean transform associates to a function f its integral averages over spheres. We consider the spherical mean transform for functions supported in the unit ball

B

in

R

n

for odd n, with the centers of integration spheres restricted to the unit sphere

S

n
−
1

. In this setup, Rubin employed properties of Erdélyi–Kober fractional integrals and analytic continuation to re-derive the explicit inversion formulas proved earlier by Finch, Patch, and Rakesh using wave equation techniques. As part of his work, Rubin stated a conjecture relating spherical mean transform, its associated backprojection operator and the Riesz potential. Furthermore, he pointed to the necessity of a detailed analysis of injectivity of the backprojection operator as a crucial step toward the resolution of his conjecture. This article addresses both questions posed by Rubin by providing a characterization of the null space of the backprojection operator, and disproving the conjecture through the construction of an explicit counterexample. Crucial to the proofs is the range characterization for the spherical mean transform in odd dimensions derived recently by the authors.
Sensor management method based on TD3 in multi-target tracking
Authors: Zhang Xindi , Chen Hui , Zhang Wenxu 
Published: November 2024

Abstract
This paper proposes an innovative sensor management method utilizing deep reinforcement learning to optimize the performances of multi-target filters based on random finite sets. Within the theoretical framework of partially observable Markov decision processes, the twin delayed deep deterministic policy gradient reinforcement learning algorithm is employed to decide optimal sensor management strategies in continuous space. For each control command, predicted ideal measurement set is generated to update posterior multi-target density. The divergence between the predicted multi-target posterior density and the updated posterior multi-target density is used as a reward function to guide the decision of sensor management strategies. The simulation results demonstrate that, compared to other algorithms, the proposed method is more effective in enhancing the performance of multi-target tracking.
Identification of blade vibration parameters based on improved blade tip timing technology and two-factor analysis method
Authors: Xu Shuben , Wei Daitong , Li Hongkun , Chen Yugang 
Published: November 2024

Abstract
Long-term complex alternating loads will significantly impact the lifespan of blades. As a non-contact measurement method, blade tip timing (BTT) is regarded as an efficient technique for blade vibration monitoring as it reflects the condition of blades. Most of the existing parameter identification methods need several sensor and strict probe layout requirements; thus, an inappropriate sensor layout may fail BTT measurements. Using fewer sensors can reduce the impact on the compressor casing strength and the cost of test system. Considering arrangement, cost, and safety restrictions, in this work, a novel blade vibration parameters identification method via a single BTT sensor is proposed. A method of improved BTT technology is presented which obtain two-channel vibration displacement sequence using a single sensor. The elliptic model between two-channel vibration displacement sequence is established. Based on the model, the relationship between blade vibration parameters and elliptic geometric parameters is derived. Numerical simulation and experimental results show that the method is highly feasible and robust. The advantage of this method is that it utilizes only one sensor and achieves high accuracy identification of blade vibration parameter, which provides a new idea to blade vibration monitoring.
Effects of dual plasticizers for improved PVC gel-based varifocal tiny lens
Authors: Tudu Gouri , Jung Eun-Jin , Heo Yong Hae , Kim Sang-Youn 
Published: November 2024

Abstract
Electroactive polyvinyl chloride (PVC) gel-based varifocal lenses are attractive due to their excellent transparency, simple fabrication, compact structure, and good flexibility. In this work, dibutyl adipate (DBA) and propylene carbonate (PC) were utilized to plasticize PVC for fabricating transparent, soft, and flexible gels by solvent casting method. The PVC gels were characterized by various experimental techniques to investigate their optical, electrical, mechanical, and thermal properties. Further, the PVC gels were examined to construct a compact plano-convex tiny lens structure for varifocal lens application under electrical stimulation. The work revealed that the introduction of a co-plasticizer PC improves the overall dielectric property as well as transparency of the PVC gels. The observed enhancement in dielectric constant of the PC incorporated gels increased up to 6 times of the only DBA plasticized PVC gel (D9) while the transmittance value is ∼5% higher than that of D9 gel. Moreover, the optimal ratio of DBA and PC in PVC gel was found to be 8.6:0.4:1 (wt%) and the optimized D8.6P0.4 gel induces better actuation properties resulting in improved focal length variation for the developed lens. The proposed adaptive tiny lens could change its focal length from 3 mm to 20.5 mm with increasing input voltage from 0 V to 1000 V. The developed tiny lens exhibited excellent optical characteristics including fast response speed and good stability. Moreover, this study broadens the scope for property tuning strategies for the electroactive polymer design and application.
Constrained measurement incompatibility from generalised contextuality of steered preparation
Authors: Mukherjee Sumit , Pan A K 
Published: November 2024

Abstract
In a bipartite Bell scenario involving two local measurements per party and two outcomes per measurement, the measurement incompatibility in one wing is both necessary and sufficient to reveal the nonlocality. However, such a one-to-one correspondence fails when one of the observers performs more than two measurements. In such a scenario, the measurement incompatibility is necessary but not sufficient to reveal the nonlocality. In this work, within the formalism of general probabilistic theory (GPT), we demonstrate that unlike the nonlocality, the incompatibility of N arbitrary measurements in one wing is both necessary and sufficient for revealing the generalised contextuality for the sub-system in the other wing. Further, we formulate an elegant form of inequality for any GPT that is necessary for N-wise compatibility of N arbitrary observables. Moreover, we argue that any theory that violates the proposed inequality possess a degree of incompatibility that can be quantified through the amount of violation. We claim that it is the generalised contextuality that provides a restriction to the allowed degree of measurement incompatibility of any viable theory of nature and thereby super-select the quantum theory. Finally, we discuss the geometrical implications of our results.
The dynamics of pinned charge density wave in NbSe3 nanoribbons revealed by noise spectroscopy
Authors: Shi Zhenzhong , Zhu Liang , Marley Peter M , Farley Katie , Banerjee Sarbajit , Sambandamurthy G 
Published: November 2024

Abstract
Systematic nonlinear transport and broadband noise measurements are performed on single nanoribbon devices of the charge density wave (CDW) conductor NbSe3 over a wide range of excitation levels and temperatures. The nonlinear voltage–current characteristics elucidate the depinning process of the two CDWs and the temperature dependence of their threshold electric fields. Within the temperature and electric field range where the CDW is anticipated to be entirely pinned by residual impurities, a non-monotonic behavior in the noise magnitude versus electric field is observed. This phenomenon is attributed to the proliferation of thermally activated phase slip events, enhanced by the size effect in nanodevices. The idea is corroborated by the observation of a smeared activated behavior described by the Dutta–Horn relation. Certain aspects of the temperature dependence of the noise magnitude deviate from a simple activated behavior, suggesting a multifaceted origin of the resistance fluctuations in CDW systems at the nanometer scale. These findings provide valuable insights into the dynamics of CDW in nanodevices.
A highly sensitive dual-core PCF-SPR sensor based on ITO and Au for detecting refractive index and temperature
Authors: Cheng Caner , Huang Chuanyang , Zhang Qiunan , Liao Xiangyu , Yang Jun , Shao Weijia , Tang Jian , Shao Laipeng , Hu Junhui , Wang Yongmei 
Published: November 2024

Abstract
Sensors have been instrumental in driving technological progress and enhancing quality of life by delivering precise data and enabling intelligent responses across a multitude of disciplines. In alignment with the advancement of technology and the demands of both industrial production and everyday life, a dual-core PCF-SPR sensor was developed. The sensor, based on D-type photonic crystal fiber and incorporating ITO and Au, was designed for the simultaneous detection of refractive index and temperature. Research results demonstrate that by using the finite element method, the maximum sensitivity of the structure in the refractive index detection range of 1.33–1.39 reached 18,100 nm RIU−1, and the maximum sensitivity in the temperature detection range of 10 °C-50 °C reached −12.3 nm °C−1. The refractive index and temperature detection channels operate independently of each other. This sensor architecture enables simultaneous dual-parameter measurement of refractive index and temperature, is lightweight and highly sensitive, and possesses potential applications in cancer cell detection and tsunami prevention.
Analytical solutions and molecule states of the (3+1)-dimensional variable coecient Date-Jimbo-Kashiwara-Miwa equation
Authors: Ma Hongcai , Su Nan , Deng Aiping 
Published: November 2024

Abstract
In the article, the (3+1)-dimensional variable coefficient Date-Jimbo-Kashiwara-Miwa (vcDJKM) equation is researched systematically. The Hirota bilinear method is utilized to construct N-soliton solutions and by imposing appropriate condition, the resonant Y-type solitons and the mixed solutions formed from resonant Y-type solitons are obtained. In addition, the positive quadratic function is exploited to search for lump solutions as well as the new degenerating breather method is employed to derive lump solutions. More importantly, with the help of velocity resonant principle, soliton molecules, breather molecules and lump molecules can be derived. Considering various forms of variable coefficients, these obtained solutions with all kinds of shapes, including S-type, parabolic-type and periodic-type are demonstrated by three-dimensional graphics, density and contour plots. And the results of this research can further advance the investigation of nonlinear partial differential equations with variable coefficients.