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Motion-to-music and music-to-motion have been studied separately, each attracting substantial research interest within their respective domains. The interaction between human motion and music is a reflection of advanced human intelligence, and establishing a unified relationship between them is particularly important. However, to date, there has been no work that considers them jointly to explore the modality alignment within. To bridge this gap, we propose a novel framework, termed MoMu-Diffusion, for long-term and synchronous motion-music generation. Firstly, to mitigate the huge computational costs raised by long sequences, we propose a novel Bidirectional Contrastive Rhythmic Variational Auto-Encoder (BiCoR-VAE) that extracts the modality-aligned latent representations for both motion and music inputs. Subsequently, leveraging the aligned latent spaces, we introduce a multi-modal Transformer-based diffusion model and a cross-guidance sampling strategy to enable various generation tasks, including cross-modal, multi-modal, and variable-length generation. Extensive experiments demonstrate that MoMu-Diffusion surpasses recent state-of-the-art methods both qualitatively and quantitatively, and can synthesize realistic, diverse, long-term, and beat-matched music or motion sequences. The generated samples and codes are available at https://momu-diffusion.github.io/, Comment: NeurIPS 2024

The cosmic distance duality relation (DDR), which links the angular diameter distance and the luminosity distance, is a cornerstone in modern cosmology. Any deviation from DDR may indicate new physics beyond the standard cosmological model. In this paper, we use four high-precision time-delayed strong gravitational lensing (SGL) systems provided by the H0LiCOW to test the validity of DDR. To this end, we directly compare the angular diameter distances from these SGL systems and the luminosity distances from the latest Pantheon+ compilation of SNe Ia. In order to reduce the statistical errors arising from redshift matching, the Gaussian process method is applied to reconstruct the distance-redshift relation from the Pantheon+ dataset. We parameterize the possible violation of DDR in three different models. It is found that all results confirm the validity of DDR at 1$\sigma$ confidence level. Additionally, Monte Carlo simulations based on the future LSST survey indicate that the precision of DDR could reach $10^{-2}$ level with 100 SGL systems., Comment: 11 pages, 6 figures

The significant discrepancy in the difference of squared nuclear charge radii $\Delta R^2$ of $^{3,4}$He obtained from electronic-atom or muonic-atom energy levels is a puzzle. In this paper, we show that the tension is resolved by including off-diagonal mixing effects due to the hyperfine interaction. Our findings indicate that the hyperfine mixing effect from the $n\,^3\!S$ and $n\,^1\!S$ states ($n>2$) of $^3$He leads to a $-1.37$ kHz adjustment in the isotope shift of the $2\,^1\!S-2\,^3\!S$ transition, surpassing the current uncertainty by a factor of $7$. This results in a change of $-0.0064~\rm{fm}^2$ in $\Delta R^2$, shifting from $1.0757(15)~\mathrm{fm}^2$ to $1.0693(15)~\mathrm{fm}^2$ as determined by Werf {\it et al.}, significantly reducing the discrepancy with the value of $1.0636(31)~\mathrm{fm}^2$ determined by $\mu\rm{He}^+$, and aligning with the result of $1.069(3)$ $\mathrm{fm}^2$ obtained from the $2\,^3\!S-2\,^3\!P$ transition. This adjustment will result in a noticeable change in the absolute nuclear charge radius of $^{3}$He by $-0.0017~\rm{fm}$, aligning the revised value of $1.9715(11)~\mathrm{fm}$ with the value of $1.97007(94)~\mathrm{fm}$ determined by $\mu^3\rm{He}^+$ within $1\sigma$. Our results offer crucial insights into resolving discrepancy in $\Delta R^2$ for $^{3,4}$He and determining the charge radius of $^3$He.

In this article we propose a simple approach for the precision calculation of Bethe logarithm. The leading contributions are obtained using specific operators, while the remaining terms are eliminated by adjusting the parameter $\lambda$. Through the use of dimensional regularization, singular divergences are algebraically canceled. Compared to the standard form of Bethe logarithm, our approach significantly reduces the complexity of constructing pseudostates in numerical evaluations. Using this approach we obtain a very highly precise result of Bethe logarithm for the ground state of the hydrogen, achieving 49 significant digits. And for multi-electron systems this approach appears simplicity and efficiency as well., Comment: 8 pages, 5 tables

The spin characteristics of black holes offer valuable insights into the evolutionary pathways of their progenitor stars, crucial for understanding the broader population properties of black holes. Traditional Hierarchical Bayesian inference techniques employed to discern these properties often entail substantial time investments, and consensus regarding the spin distribution of Binary Black Hole (BBH) systems remains elusive. In this study, leveraging observations from GWTC-3, we adopt a machine learning approach to infer the spin distribution of black holes within BBH systems. Specifically, we develop a Deep Neural Network (DNN) and train it using data generated from a Beta distribution. Our training strategy, involving the segregation of data into 10 bins, not only expedites model training but also enhances the DNN's versatility and adaptability to accommodate the burgeoning volume of gravitational wave observations. Utilizing Monte Carlo-bootstrap (MC-bootstrap) to generate observation-simulated samples, we derive spin distribution parameters: $\alpha=1.3^{+0.25}_{-0.18},\beta=1.70^{+0.24}_{-0.29}$ for the larger BH sample and $\alpha=1.37^{+0.31}_{-0.20},\beta=1.63^{+0.30}_{-0.20}$ for the smaller BH sample. Within our constraints, the distributions of component spin magnitudes suggest the likelihood of both black holes in the BBH merger possessing non-zero spin., Comment: 10 pages, 8 figures, 1 table

In this paper we obtain optimal multipolar Rellich inequality for biharmonic Schrodinger operator with positive multi-singular potentials. Moreover, we prove the attainability of the best constant and the criticality of the biharmonic Schrodinger operator.

Purpose The aim of this study was to explore whether electroacupuncture regulates phenotypic transformation of smooth muscle cells by inhibiting ferroptosis and inhibiting fibrosis, thereby improving bladder urination function after suprasacral spinal cord injury (SSCI). Methods The experiment was divided into sham, model, and electroacupuncture group. After 10 days of electroacupuncture intervention, urodynamic examination was performed, and bladder neck was taken for HE staining, tandem mass tag (TMT)-based quantitative proteomics analysis, Western blot(WB) detection, ferrous ion concentration detection and Masson staining. Conclusion Electroacupuncture may prevent the phenotype of bladder neck smooth muscle cells from transforming from contraction type to synthesis type by inhibiting ferroptosis, inhibit bladder neck fibrosis, improve bladder neck compliance, and thus improve bladder urination function after SSCI.

Encoding is the carrier of information. Artificial intelligence models possess basic capabilities in syntax, semantics, and reasoning, but these capabilities are sensitive to specific inputs. This study introduces TSIS (Simplified TSID) to the t-SMILES family, with the intention of conducting a more comprehensive and in-depth evaluation of t-SMILES. TSID has been demonstrated significantly outperforms classical SMILES, DeepSMILES, and SELFIES in previous research. Further analysis of this study reveals that the tree structure utilized by the t-SMILES framework is more effectively comprehensible than initially anticipated. Additionally, TSIS, along with their variants, demonstrate comparable performance to TSID and markedly surpass that of SMILES, SAFE, and SELFIES. Moreover, its format is more straightforward to read. Overall, the contrast analysis indicates that the hierarchical structure of t-SMILES enhances its generalizability. Concurrently, the evaluation of the generative models reveals that the GPT model exhibits the highest novelty-similarity scores. The VAE and diffusion models demonstrate robust capabilities in terms of interpolation, whereas the LSTM model encounters some challenges in parsing complex structures.

The hyperpolarizability of an atom is a property that describes the nonlinear interaction between an atom and an external electric field leading to a higher-order Stark shift. Accurate evaluations of these coefficients for various systems are crucial to improve experimental precision in advanced atom-based clocks. However, there is a dearth of reports on atomic hyperpolarizabilities, particularly regarding relativistic hyperpolarizabilities. Thus, in this paper, we use fourth-order perturbation theory to establish a universal formula for the hyperpolarizability and calculate the relativistic hyperpolarizabilities of low-lying states for the monovalent electronic atomic systems H, Li, and Be$^+$. The highly accurate results given here for the H atom could serve as benchmarks for other theoretical methods., Comment: 12 pages; 1 figure

In recent years, the deployment of large-scale pre-trained models in audio-visual downstream tasks has yielded remarkable outcomes. However, these models, primarily trained on single-modality unconstrained datasets, still encounter challenges in feature extraction for multi-modal tasks, leading to suboptimal performance. This limitation arises due to the introduction of irrelevant modality-specific information during encoding, which adversely affects the performance of downstream tasks. To address this challenge, this paper proposes a novel Dual-Guided Spatial-Channel-Temporal (DG-SCT) attention mechanism. This mechanism leverages audio and visual modalities as soft prompts to dynamically adjust the parameters of pre-trained models based on the current multi-modal input features. Specifically, the DG-SCT module incorporates trainable cross-modal interaction layers into pre-trained audio-visual encoders, allowing adaptive extraction of crucial information from the current modality across spatial, channel, and temporal dimensions, while preserving the frozen parameters of large-scale pre-trained models. Experimental evaluations demonstrate that our proposed model achieves state-of-the-art results across multiple downstream tasks, including AVE, AVVP, AVS, and AVQA. Furthermore, our model exhibits promising performance in challenging few-shot and zero-shot scenarios. The source code and pre-trained models are available at https://github.com/haoyi-duan/DG-SCT., Comment: Accepted to NeurIPS 2023

We use the distance sum rule (DSR) method to constrain the spatial curvature of the Universe with a large sample of 161 strong gravitational lensing (SGL) systems, whose distances are calibrated from the Pantheon compilation of type Ia supernovae (SNe Ia) using deep learning. To investigate the possible influence of mass model of the lens galaxy on constraining the curvature parameter $\Omega_k$, we consider three different lens models. Results show that a flat Universe is supported in the singular isothermal sphere (SIS) model with the parameter $\Omega_k=0.049^{+0.147}_{-0.125}$. While in the power-law (PL) model, a closed Universe is preferred at $\sim 3\sigma$ confidence level, with the parameter $\Omega_k=-0.245^{+0.075}_{-0.071}$. In extended power-law (EPL) model, the 95$\%$ confidence level upper limit of $\Omega_k$ is $<0.011$. As for the parameters of the lens models, constrains on the three models indicate that the mass profile of the lens galaxy could not be simply described by the standard SIS model., Comment: 17 pages, 7 figures

We investigate the possible anisotropy of the universe using the most up-to-date type Ia supernovae, i.e. the Pantheon+ compilation. We fit the full Pantheon+ data with the dipole-modulated $\Lambda$CDM model, and find that it is well consistent with a null dipole. We further divide the full sample into several subsamples with different high-redshift cutoff $z_c$. It is shown that the dipole appears at $2\sigma$ confidence level only if $z_c\leq 0.1$, and in this redshift region the dipole is very stable, almost independent of the specific value of $z_c$. For $z_c=0.1$, the dipole amplitude is $D=1.0_{-0.4}^{+0.4}\times 10^{-3}$, pointing towards $(l,b)=(334.5_{\ -21.6^{\circ}}^{\circ +25.7^{\circ}},16.0_{\ -16.8^{\circ}}^{\circ +27.1^{\circ}})$, which is about $65^{\circ}$ away from the CMB dipole. This implies that the full Pantheon+ is consistent with a large-scale isotropic universe, but the low-redshift anisotropy couldn't be purely explained by the peculiar motion of the local universe., Comment: 11 pages, 6 figures

Most sign language translation (SLT) methods to date require the use of gloss annotations to provide additional supervision information, however, the acquisition of gloss is not easy. To solve this problem, we first perform an analysis of existing models to confirm how gloss annotations make SLT easier. We find that it can provide two aspects of information for the model, 1) it can help the model implicitly learn the location of semantic boundaries in continuous sign language videos, 2) it can help the model understand the sign language video globally. We then propose \emph{gloss attention}, which enables the model to keep its attention within video segments that have the same semantics locally, just as gloss helps existing models do. Furthermore, we transfer the knowledge of sentence-to-sentence similarity from the natural language model to our gloss attention SLT network (GASLT) to help it understand sign language videos at the sentence level. Experimental results on multiple large-scale sign language datasets show that our proposed GASLT model significantly outperforms existing methods. Our code is provided in \url{https://github.com/YinAoXiong/GASLT}.

The theoretical calculations of the dynamic E2-M1 polarizability at the magic wavelength of the Sr optical clock are inconsistent with experimental results. We investigate role of negative-energy states in the E2 and M1 polarizabilities. Our result for E2-M1 polarizability difference $-$7.74(3.92)$\times$10$^{-5}$ a.u. is dominated by the contribution from negative-energy states to M1 polarizability and has the same sign as and consistent with all the experimental values. In addition, we apply the present calculations to various other optical clocks, further confirming the importance of negative-energy states to the M1 polarizability., Comment: 7 pages, 3 figures, arXiv admin note: this is an extended version of arXiv:2301.06740