bluuebunny/crossref_metadata_2025_split huggingface dataset:
High-pressure synthesis and characterizations of a new ternary Ce-based compound Ce3TiAs5
Authors: Fu L C , Shi L C , Chen X M , Duan L , Peng Y , Zhang J , Song J , Deng Z , Zhang S J , Zhao J F , Liu Y , Zhang J F , Zhu J L , Wang X C , Jin C Q 
Published: September 2024

Abstract
We report the structure and properties of a new Ce-based compound Ce3TiAs5 synthesized under high-pressure and high-temperature conditions. It crystallizes in a hexagonal Hf5Sn3Cu-anti type structure with zig-zag like Ce chains along the c axis. This compound is metallic and undergoes a magnetic phase transition at T
N = 13 K. A metamagnetic transition occurs at ∼0.7 T. The Sommerfeld coefficient for the compound is determined to be about 215 mJ/(Ce-mol*K2), demonstrating a heavy Fermion behavior. The resistivity is featured with two humps, which arises from the synergistic effect of crystal electric field and magnetic scattering. The magnetic ordering temperature T
N gradually increases in the sequence of Ce3TiPn5 with Pn = Bi, Sb, and As, which implies that the Ruderman–Kittel–Kasuya–Yosida interaction should be still predominant in Ce3TiAs5.
Research on digital twin-assisted bearing fault diagnosis method based on virtual-real mapping
Authors: Shang Zhiwu , Wang Xunbo , Pan Cailu , Cheng Hongchuan , Wang Ziyu 
Published: September 2024

Abstract
The deployment of intelligent fault diagnosis for bearings within the industrial field is significantly challenged by the issue of limited sample sizes. Digital twin (DT) technology facilitates the replication of rotating machinery operations within a virtual environment, thereby enabling the acquisition of equivalent or superior information regarding physical entities at a reduced cost, introducing a novel method for fault diagnosis in scenarios characterized by limited sample sizes. Nevertheless, the disparity in data distribution across virtual and physical realms poses challenges to deploying DT-based fault diagnosis methods. In response to this challenge, this paper proposes a DT-assisted bearing fault diagnosis method based on virtual-real mapping. Firstly, a bearing dynamics model is constructed in the virtual space using finite element methods to reflect the bearing’s vibration response in physical space. Secondly, an efficient multi-scale attention cycle-consistent generative adversarial network with a perceptual loss function is proposed as a bridge between virtual and physical spaces, reducing the data distribution differences through data mapping. Finally, a multi-index evaluation framework was established to validate the effectiveness of the simulation data after mapping, and through two case studies, the proposed method’s ability to effectively address the small sample issue was confirmed.
Simple and efficient step detection algorithm for foot-mounted IMU
Authors: Shi Ling-Feng , Yan Xu , Zhou Wen , Shi Yifan 
Published: September 2024

Abstract
This paper presents a concise, efficient, and adaptive step detection algorithm based on foot-mounted inertial measurement unit sensors. The proposed method maps the temporal values of pedestrian motion and gait diversity into two variables: the distance between peaks and valleys, and the slope. Compared to traditional sliding window methods, this approach amplifies the differences between normal and abnormal steps, allowing it to adapt to various indoor activities such as fast walking, slow walking, running, jogging, standing still, and turning. By incorporating adaptive factors, it addresses the challenge of detecting steps while going up and down stairs. The proposed algorithm overcomes the limitations of traditional adaptive threshold methods that require different temporal and peak thresholds for various gait conditions. By utilizing the significant differences in distance and slope, it effectively resolves the issue of detecting steps during stationary periods. Unlike neural network-based gait classifiers, this algorithm does not need to account for multiple gait conditions, thereby simplifying the training process. Experimental results demonstrate that the algorithm achieves an average accuracy of over 99% under mixed indoor walking conditions and over 98% accuracy in long-term outdoor walking conditions.
A robust factor graph optimization method of GNSS/INS/ODO integrated navigation system for autonomous vehicle
Authors: Huo Zhen , Jin Lisheng , Wang Huanhuan , Sun Xinyu , He Yang 
Published: September 2024

Abstract
The GNSS/INS/ODO integrated navigation system provides accurate positioning for autonomous vehicles. However, the observation quality of GNSS and ODO can decrease in complex environments and various driving conditions, leading to a decline in the accuracy and robustness of the integrated navigation system. An FGO-Robust method is proposed to resolve this challenge by fusing the INS/ODO-Slip factor and adaptive GNSS factor. The INS/ODO-Slip factor compensates for ODO measurement values by estimating the wheel slip ratio in real-time during optimization, thereby reducing ODO measurement errors’ impact on factor graph optimization. Additionally, the adaptive GNSS factor minimizes the impact of GNSS outliers in the optimization process by designing a dynamic observation weight function. The vehicle experiments are conducted to evaluate the performance of the proposed method in different simulated conditions with ODO and GNSS measurement failures. The experimental results demonstrate that the FGO-Robust method can effectively improve the positioning accuracy of the integrated navigation system under various measurement failure conditions, with improvements of 83.4%, 66.1%, and 68.1% relative to FGO. Moreover, the FGO-Robust method improves the robustness of the integrated navigation system in complex environments and various driving conditions.
Structural and excitonic properties of the polycrystalline FAPbI3 thin films, and their photovoltaic responses
Authors: Huang Yi-Chun , Yen I-Jane , Tseng Chih-Hsien , Wang Hui-Yu , Chandel Anjali , Chang Sheng Hsiung 
Published: September 2024

Abstract
Faormamadinium based perovskites have been proposed to replace the methylammonium lead tri-iodide (MAPbI3) perovskite as the light absorbing layer of photovoltaic cells owing to their photo-active and chemically stable properties. However, the crystal phase transition from the photo-active α-FAPbI3 to the non-perovksite δ-FAPbI3 still occurs in un-doped FAPbI3 films owing to the existence of crack defects, which degrads the photovoltaic responses. To investigate the crack ratio (CR)-dependent structure and excitonic characteristics of the polycrystalline FAPbI3 thin films deposited on the carboxylic acid functionalized ITO/glass substrates, various spectra and images were measured and analyzed, which can be utilized to make sense of the different devices responses of the resultant perovskite based photovoltaic cells. Our experimental results show that the there is a trade-off between the formations of surface defects and trapped iodide-mediated defects, thereby resulting in an optimal crack density or CR of the un-doped α-FAPbI3 active layer in the range from 4.86% to 9.27%. The decrease in the CR (tensile stress) results in the compressive lattice and thereby trapping the iodides near the PbI6 octahedra in the bottom region of the FAPbI3 perovskite films. When the CR of the FAPbI3 film is 8.47%, the open-circuit voltage (short-circuit current density) of the resultant photovoltaic cells significantly increased from 0.773 V (16.62 mA cm−2) to 0.945 V (18.20 mA cm−2) after 3 d. Our findings help understanding the photovoltaic responses of the FAPbI3 perovskite based photovoltaic cells on the different days.
Nanoheteroepitaxy of Ge and SiGe on Si: role of composition and capping on quantum dot photoluminescence
Authors: Ryzhak Diana , Aberl Johannes , Prado-Navarrete Enrique , Vukušić Lada , Corley-Wiciak Agnieszka Anna , Skibitzki Oliver , Zoellner Marvin Hartwig , Schubert Markus Andreas , Virgilio Michele , Brehm Moritz , Capellini Giovanni , Spirito Davide 
Published: September 2024

Abstract
We investigate the nanoheteroepitaxy (NHE) of SiGe and Ge quantum dots (QDs) grown on nanotips (NTs) substrates realized in Si(001) wafers. Due to the lattice strain compliance, enabled by the nanometric size of the tip and the limited dot/substrate interface area, which helps to reduce dot/substrate interdiffusion, the strain and SiGe composition in the QDs could be decoupled. This demonstrates a key advantage of the NHE over the Stranski–Krastanow growth mechanism. Nearly semi-spherical, defect-free, ∼100 nm wide SiGe QDs with different Ge contents were successfully grown on the NTs with high selectivity and size uniformity. On the dots, thin dielectric capping layers were deposited, improving the optical properties by the passivation of surface states. Intense photoluminescence was measured from all samples investigated with emission energy, intensity, and spectral linewidth dependent on the SiGe composition of the QDs and the different capping layers. Radiative recombination occurs in the QDs, and its energy matches the results of band-structure calculations that consider strain compliance between the QD and the tip. The NTs arrangement and the selective growth of QDs allow to studying the PL emission from only 3–4 QDs, demonstrating a bright emission and the possibility of selective addressing. These findings will support the design of optoelectronic devices based on CMOS-compatible emitters.
Establishment of a Raman nanosphere based immunochromatographic system for the combined detection of influenza A and B viruses’ antigens on a single T-line
Authors: Li Ziyue , Zhu Aolin , Zhao Binbin , Zhang Yongwei , Zhang Qian , Zhou Hao , Liu Tingwei , Li Jiutong , Zhou Xuelei , Shi Qian , Li Yongxin , Liang Mengjie , Zhang Xin , Lu Dongmei , Li Xinxia 
Published: September 2024

Abstract
A simple and rapid system based on Raman nanosphere (R-Sphere) immunochromatography was developed in this study for the simultaneous detection of Influenza A, B virus antigens on a single test line (T-line). Two types of R-Sphere with different characteristic Raman spectrum were used as the signal source, which were labeled with monoclonal antibodies against FluA, FluB (tracer antibodies), respectively. A mixture of antibodies containing anti-FluA monoclonal antibody and anti-FluB monoclonal antibody (capture antibody) was sprayed on a single T-line and goat anti-chicken IgY antibody was coated as a C-line, and the antigen solution with known concentration was detected by the strip of lateral flow immunochromatography based on surface-enhanced Raman spectroscopy (SERS). The T-line was scanned with a Raman spectrometer and SERS signals were collected. Simultaneous specific recognition and detection of FluA and FluB were achieved on a single T-line by analyzing the SERS signals. The findings indicated that the test system could identify FluA and FluB in a qualitative manner in just 15 minutes, with a minimum detection threshold of 0.25 ng ml−1, excellent consistency, and specificity. There was no interference with the other four respiratory pathogens, and it exhibited 8 times greater sensitivity compared to the colloidal gold test strip method. The assay system is rapid, sensitive, and does not require repetitive sample pretreatment steps and two viruses can be detected simultaneously on a single T-line by titrating one sample, which improves detection efficiency, and provide a reference for developing multiplexed detection techniques for other respiratory viruses.
Isomonodromic and isospectral deformations of meromorphic connections: the

sl

2

(

C

)

case
Authors: Marchal Olivier , Alameddine Mohamad 
Published: September 2024

Abstract
We consider non-twisted meromorphic connections in

sl

2

(

C

)

and the associated symplectic Hamiltonian structure. In particular, we provide explicit expressions of the Lax pair in the geometric gauge supplementing results of Marchal et al (2022 arXiv:2212.04833) where explicit formulas have been obtained in the oper gauge. Expressing the geometric Lax matrices requires the introduction of specific Darboux coordinates for which we provide the explicit Hamiltonian evolutions. These expressions allow to build bridges between the isomonodromic deformations and the isospectral ones. More specifically, we propose an explicit change of Darboux coordinates to obtain isospectral coordinates for which Hamiltonians match the spectral invariants. This result solves the issue left opened in Bertola et al (2023 J. Math. Phys.
64 083502) in the case of

sl

2

(

C

)

.
Performance evaluation of image co-registration methods in photoacoustic mesoscopy of the vasculature
Authors: Lefebvre T L , Sweeney P W , Gröhl J , Hacker L , Brown E L , Else T R , Oraiopoulou M-E , Bloom A , Lewis D Y , Bohndiek S E 
Published: September 2024

Abstract

Objective. The formation of functional vasculature in solid tumours enables delivery of oxygen and nutrients, and is vital for effective treatment with chemotherapeutic agents. Longitudinal characterisation of vascular networks can be enabled using mesoscopic photoacoustic imaging, but requires accurate image co-registration to precisely assess local changes across disease development or in response to therapy. Co-registration in photoacoustic imaging is challenging due to the complex nature of the generated signal, including the sparsity of data, artefacts related to the illumination/detection geometry, scan-to-scan technical variability, and biological variability, such as transient changes in perfusion. To better inform the choice of co-registration algorithms, we compared five open-source methods, in physiological and pathological tissues, with the aim of aligning evolving vascular networks in tumours imaged over growth at different time-points. Approach. Co-registration techniques were applied to 3D vascular images acquired with photoacoustic mesoscopy from murine ears and breast cancer patient-derived xenografts, at a fixed time-point and longitudinally. Images were pre-processed and segmented using an unsupervised generative adversarial network. To compare co-registration quality in different settings, pairs of fixed and moving intensity images and/or segmentations were fed into five methods split into the following categories: affine intensity-based using (1) mutual information (MI) or (2) normalised cross-correlation (NCC) as optimisation metrics, affine shape-based using (3) NCC applied to distance-transformed segmentations or (4) iterative closest point algorithm, and deformable weakly supervised deep learning-based using (5) LocalNet co-registration. Percent-changes in Dice coefficients, surface distances, MI, structural similarity index measure and target registration errors were evaluated. Main results. Co-registration using MI or NCC provided similar alignment performance, better than shape-based methods. LocalNet provided accurate co-registration of substructures by optimising subfield deformation throughout the volumes, outperforming other methods, especially in the longitudinal breast cancer xenograft dataset by minimising target registration errors. Significance. We showed the feasibility of co-registering repeatedly or longitudinally imaged vascular networks in photoacoustic mesoscopy, taking a step towards longitudinal quantitative characterisation of these complex structures. These tools open new outlooks for monitoring tumour angiogenesis at the meso-scale and for quantifying treatment-induced co-localised alterations in the vasculature.
Fraction of reverse impedance change (FRIC): a quantitative electrical impedance tomography measure of intrapulmonary pendelluft
Authors: Adler Andy , Becher Tobias , Händel Claas , Frerichs Inéz 
Published: September 2024

Abstract

Objective. Pendelluft is the movement of air between lung regions, and electrical impedance tomography (EIT) has shown an ability to detect and monitor it. Approach. In this note, we propose a functional EIT measure which quantifies the reverse airflow seen in pendelluft: the Fraction of Reverse Impedance Change (FRIC). Main
Results. FRIC measures the fraction of reverse flow in each pixel waveform (as an image) or globally (as a single parameter). Significance. Such a measure is designed to be a more specific measure than previous approaches, to enable comparative studies of the pendelluft, and to help clarify the effect of ventilation strategies.
Detection of sleep arousal from STFT-based instantaneous features of single channel EEG signal
Authors: Ali Md Hussain , Uddin Md Bashir 
Published: September 2024

Abstract

Objective. Sleep arousal, a frequent interruption in sleep with complete or partial wakefulness from sleep, may indicate a breathing disorder, neurological disorder, or sleep-related disorders. These phenomena necessitate the detection of sleep arousals. Uses of deep learning methods to detect features inhibits the scope to understand the specific distinctive nature of the signals and reduces the interpretability of the model. To evade these inconsistencies and to improve the classification performance of the sleep arousal detection model, a model has been proposed in this study on the prospect of understandable features that are useful in detecting sleep arousals. Approach. Time–frequency analysis of the electroencephalogram signals was performed using short-time Fourier transform (STFT). From the STFT coefficients, the spectrogram and instantaneous properties (frequency, bandwidth, power spectrum, band energy, local maxima, and band energy ratios) were investigated. From these properties, instantaneous features were generated by statistical analysis. Additive feature sets and reduced feature sets, formed by adding features successively and reducing features using the analysis of variance test respectively, were subjected to a tri-layered neural network classifier to evaluate the capability of the features to detect sleep arousal and normal sleep segments. Main results. The reduced feature set (Set 6) has proved to be efficacious in facilitating superior classification performance metrics (accuracy, sensitivity, specificity, and AUC of 89.14%, 83.52%, 89.49%, and 93.84% respectively). Significance. This efficient model can be incorporated with an automatic sleep apnea detection system where the estimation of hypopnea requires the detection of sleep arousal.
Examination of sex differences in fatigability and neuromuscular responses during continuous, maximal, isometric leg extension
Authors: Benitez Brian , Kwak Minyoung , Succi Pasquale J , Mitchinson Clara J , Weir Joseph P , Bergstrom Haley C 
Published: September 2024

Abstract

Objective. This study examined sex-related differences in fatigability and neuromuscular responses using surface electromyographic (sEMG) and mechanomyographic (sMMG) amplitude (AMP) and frequency (MPF) during fatiguing, maximal, bilateral isometric leg extensions. Approach. Twenty recreationally active males and females with resistance training experience performed continuous, maximal effort, bilateral isometric leg extensions until their force reduced by 50%. Linear mixed effect models analyzed patterns of force, sEMG, and sMMG AMP and MPF responses in the dominant limb. An independent samples t-test compared time-to-task failure (TTF) between sexes. Main Results. There were no significant differences in TTF between males and females. However, males experienced a greater rate of force loss compared to females. Furthermore, sEMG AMP and MPF and sMMG AMP responses followed similar linear trends for both sexes, while sMMG MPF showed non-linear responses with sex-dependent differences. Significance. These data suggest that although TTF was similar, males had a higher rate of force reduction, likely due to greater absolute strength. Furthermore, despite parallel changes in sEMG AMP and MPF, as well as sMMG AMP, the divergent responses observed in sMMG MPF highlight sex-dependent differences in how males and females experience changes in the firing rates of active motor units during sustained maximal contractions.
A comprehensive review of quantum machine learning: from NISQ to fault tolerance
Authors: Wang Yunfei , Liu Junyu 
Published: September 2024

Abstract
Quantum machine learning, which involves running machine learning algorithms on quantum devices, has garnered significant attention in both academic and business circles. In this paper, we offer a comprehensive and unbiased review of the various concepts that have emerged in the field of quantum machine learning. This includes techniques used in Noisy Intermediate-Scale Quantum (NISQ) technologies and approaches for algorithms compatible with fault-tolerant quantum computing hardware. Our review covers fundamental concepts, algorithms, and the statistical learning theory pertinent to quantum machine learning.
REBCO tapes for applications in ultra-high fields: critical current surface and scaling relations
Authors: Senatore Carmine , Bonura Marco , Bagni Tommaso 
Published: September 2024

Abstract
REBa2Cu3O7−x
(REBCO) tapes produced by leading manufacturers were tested at UNIGE to characterize the dependence of the critical current on temperature, field intensity and orientation. This measurement campaign was carried out in the frame of international collaborations having the common goal of developing technology for ultra-high field magnets in the 30–50 T range. The examined samples differ in many respects, e.g. processing methods, thickness of the superconducting layer, Rare Earth element in REBCO, and type of artificial pinning centers (3D nanoparticles vs extended 1D nanorods). We measured the transport critical current of full-width tapes at 4.2 K and 20 K in magnetic fields up to 19 T and at various orientations of the field with respect to the tape surface. Additionally, magnetic characterization was conducted over a wider temperature range (4.2–77 K). The highly engineered vortex pinning results in outstanding critical current performance for all examined tapes: the non-copper critical current density, i.e. the critical current divided by the wire cross-section area minus the Cu area, ranges between 1500 and 2000 A mm−2 at 4.2 K, 19 T and close to 1000 A mm−2 at 20 K, 19 T in the perpendicular field orientation. We obtained scaling expressions for the critical current surface based on the analysis of the pinning-force curves but the pinning-force shape parameters were found to vary from one manufacturer to another. The results presented in this work may offer valuable information not only to magnet designers but also to manufacturers looking to optimize their tapes and achieve better performance.
On the learning of high order polynomial reconstructions for essentially non-oscillatory schemes
Authors: Kumar Jayswal Vikas , Kumar Dubey Ritesh 
Published: September 2024

Abstract
Approximation accuracy and convergence behavior are essential required properties for the computed numerical solution of differential equations. These requirements restrict the application of deep learning networks in the domain of scientific computing. Moreover, the recipe to create suitable synthetic data which can be used to train a good model is also not very clear. This study focuses on learning of third order essentially non-oscillatory (ENO) and weighted essentially non-oscillatory (WENO) reconstructions using classification neural networks with small data sets. In particular, this work (i) proposes a novel way to obtain a third order WENO reconstruction which can be posed as classification problem, (ii) gives simple and novel approach to sample data sets which are small but rich enough to inherit the latent feature of inter-spatial regularity information in the constructed data, (iii) it is established that sampling of train data sets impacts quantitatively as well as qualitatively the required accuracy and non-oscillatory properties of resulting ENO3 and WENO3 schemes, (iv) proposes to use a limiter based multi model to retain desired accuracy as well as non-oscillatory properties of the resulting numerical schemes. Computational results are given which established that learned networks perform well and retain the features of the reconstruction methods.