arXiv subjects

Yuxin Yang

Publications and source records attributed to Yuxin Yang.

62 records · Page 4Linked to original sources

arXiv2023

FSD: An Initial Chinese Dataset for Fake Song Detection

Singing voice synthesis and singing voice conversion have significantly advanced, revolutionizing musical experiences. However, the rise of "Deepfake Songs" generated by these technologies raises concerns about authenticity. Unlike Audio DeepFake Detection (ADD), the field of song deepfake detection lacks specialized datasets or methods for song authenticity verification. In this paper, we initially construct a Chinese Fake Song Detection (FSD) dataset to investigate the field of song deepfake detection. The fake songs in the FSD dataset are generated by five state-of-the-art singing voice synthesis and singing voice conversion methods. Our initial experiments on FSD revealed the ineffectiveness of existing speech-trained ADD models for the task of song deepFake detection. Thus, we employ the FSD dataset for the training of ADD models. We subsequently evaluate these models under two scenarios: one with the original songs and another with separated vocal tracks. Experiment results show that song-trained ADD models exhibit a 38.58% reduction in average equal error rate compared to speech-trained ADD models on the FSD test set.

cs.SD↗

arXiv2023

Accelerating Magnetic Resonance T1\r{ho} Mapping Using Simultaneously Spatial Patch-based and Parametric Group-based Low-rank Tensors (SMART)

Quantitative magnetic resonance (MR) T1\r{ho} mapping is a promising approach for characterizing intrinsic tissue-dependent information. However, long scan time significantly hinders its widespread applications. Recently, low-rank tensor has been employed and demonstrated good performance in accelerating MR T1\r{ho} mapping. In this study, we propose a novel method that uses spatial patch-based and parametric group-based low rank tensors simultaneously (SMART) to reconstruct images from highly undersampled k-space data. The spatial patch-based low-rank tensor exploits the high local and nonlocal redundancies and similarities between the contrast images in T1\r{ho} mapping. The parametric group based low-rank tensor, which integrates similar exponential behavior of the image signals, is jointly used to enforce the multidimensional low-rankness in the reconstruction process. In vivo brain datasets were used to demonstrate the validity of the proposed method. Experimental results have demonstrated that the proposed method achieves 11.7-fold and 13.21-fold accelerations in two-dimensional and three-dimensional acquisitions, respectively, with more accurate reconstructed images and maps than several state-of-the-art methods. Prospective reconstruction results further demonstrate the capability of the SMART method in accelerating MR T1\r{ho} imaging.

eess.IV↗

arXiv2022

Decreased serum vitamin D level as a prognostic marker in patients with COVID-19

Background: The corona virus disease 2019 (COVID-19) pandemic, which is caused by severe acute respiratory syndrome coronavirus 2, is still localized outbreak and has resulted in a high rate of infection and severe disease in older patients with comorbidities. The vitamin D status of the population has been found to be an important factor that could influence outcome of COVID-19. However, whether vitamin D can lessen the symptoms or severity of COVID-19 still remains controversial. Methods: A total of 719 patients with confirmed COVID-19 were enrolled retrospectively in this study from April 13 to June 6, 2022 at Shanghai Forth People's Hospital. The circulating levels of 25(OH)D3, inflammatory factors, and clinical parameters were assayed. Time to viral RNA clearance (TVRC), classification and prognosis of COVID-19 were used to evaluate the severity of COVID-19 infection. Results: The median age was 76 years (interquartile range, IQR, 64.5-84.6), 44.1% of patients were male, and the TVRC was 11 days (IQR, 7-16) in this population. The median level of 25(OH)D3 was 27.15 (IQR, 19.31-38.89) nmol/L. Patients with lower serum 25(OH)D3 had prolonged time to viral clearance, more obvious inflammatory response, more severe respiratory symptoms and higher risks of impaired hepatic and renal function. Multiple regression analyses revealed that serum 25(OH)D3 level was negatively associated with TVRC independently. ROC curve showed the serum vitamin D level could predict the severity classification and prognosis of COVID-19 significantly.Conclusions: Serum 25(OH)D3 level is independently associated with the severity of COVID-19 in elderly, and it could be used as a predictor of the severity of COVID-19. In addition, supplementation with vitamin D might provide beneficial effects in old patients with COVID-19.

q-bio.TO↗

arXiv2022

Delicate Superconductivity in NaAlGe Single Crystal

Nodal-line superconductor NaAlSi with a transition temperature ($T_c$) of 7 K has attracted considerable attention in recent years, whereas its Ge counterpart, NaAlGe, does not superconduct down to the lowest temperature regardless of their similar atomic and electrical structures. To tackle this enigma, we resort to the growth of NaAlGe single crystal and characterize its semimetallic ground state. Interestingly, when hole doped by oxidation, single-crystalline NaAlGe transforms from a semimetal to a superconductor ($T_c = 2.3 \sim$ 3.5 K) with zero resistivity and a diamagnetic shielding fraction over 100$\%$, but without a thermodynamic response in heat capacity. Continuous x-ray diffraction reveals a transient new structure with a larger $c$ axis, which is suggested to have arisen from the minor loss of Na and to be responsible for the emergence of the delicate superconductivity. Our findings resolve the controversies in NaAlSi and NaAlGe, while their similarities and differences provide an ideal opportunity to investigate a variety of exciting topological quantum states.

cond-mat.supr-con↗

arXiv2022

Making Invisible Visible: Data-Driven Seismic Inversion with Spatio-temporally Constrained Data Augmentation

Deep learning and data-driven approaches have shown great potential in scientific domains. The promise of data-driven techniques relies on the availability of a large volume of high-quality training datasets. Due to the high cost of obtaining data through expensive physical experiments, instruments, and simulations, data augmentation techniques for scientific applications have emerged as a new direction for obtaining scientific data recently. However, existing data augmentation techniques originating from computer vision, yield physically unacceptable data samples that are not helpful for the domain problems that we are interested in. In this paper, we develop new data augmentation techniques based on convolutional neural networks. Specifically, our generative models leverage different physics knowledge (such as governing equations, observable perception, and physics phenomena) to improve the quality of the synthetic data. To validate the effectiveness of our data augmentation techniques, we apply them to solve a subsurface seismic full-waveform inversion using simulated CO$_2$ leakage data. Our interest is to invert for subsurface velocity models associated with very small CO$_2$ leakage. We validate the performance of our methods using comprehensive numerical tests. Via comparison and analysis, we show that data-driven seismic imaging can be significantly enhanced by using our data augmentation techniques. Particularly, the imaging quality has been improved by 15% in test scenarios of general-sized leakage and 17% in small-sized leakage when using an augmented training set obtained with our techniques.

cs.LG↗

arXiv2021

Discovery of two families of VSb-based compounds with V-kagome lattice

We report the structure and physical properties of two newly-discovered compounds AV8Sb12 and AV6Sb6 (A = Cs, Rb), which have C2 (space group: Cmmm) and C3 (space group: R-3m) symmetry, respectively. The basic V-kagome unit is present in both compounds, but stacking differently. A V2Sb2 layer is sandwiched between two V3Sb5 layers in AV8Sb12, altering the V-kagome lattice and lowering the symmetry of kagome layer from hexagonal to orthorhombic. In AV6Sb6, the building block is a more complex slab made up of two half-V3Sb5 layers that are intercalated by Cs cations along the c-axis. Transport property measurements demonstrate that both compounds are nonmagnetic metals, with carrier concentrations at around 1021cm-3. No superconductivity has been observed in CsV8Sb12 above 0.3 K under in-situ pressure up to 46 GPa. In contrast to CsV3Sb5, theoretical calculations and angle-resolved photoemission spectroscopy (ARPES) reveal a quasi-two-dimensional electronic structure in CsV8Sb12 with C2 symmetry and no van Hove singularities near the Fermi level. Our findings will stimulate more research into V-based kagome quantum materials.

cond-mat.supr-con↗

arXiv2012

Generalised Clark-Ocone formulae for differential forms

We generalise the Clark-Ocone formula for functions to give analogous representations for differential forms on the classical Wiener space. Such formulae provide explicit expressions for closed and co-closed differential forms and, as a by-product, a new proof of the triviality of the L^2 de Rham cohomology groups on the Wiener space, alternative to Shigekawa's approach [16] and the chaos-theoretic version [18]. This new approach has the potential of carrying over to curved path spaces, as indicated by the vanishing result for harmonic one-forms in [6]. For the flat path group, the generalised Clark-Ocone formulae can be proved directly using the Itô map.

math.PR↗

arXiv2011

Ito-Wiener chaos and the Hodge decomposition on an abstract Wiener space

Using the structure of the Boson-Fermion Fock space and an argument taken from [2], we give a new proof of the triviality of the $L^2$ cohomology groups on an abstract Wiener space, alternative to that given by Shigekawa [9]. We apply some representation theory of the symmetric group to characterise the spaces of exact and co-exact forms in their Boson-Fermion Fock space representation.

math.PR↗