Liouville integrability of the finite dimensional Hamiltonian systems derived from principal chiral field

For finite dimensional Hamiltonian systems derived from 1+1 dimensional integrable systems, if they have Lax representations, then the Lax operator creates a set of conserved integrals. When these conserved integrals are in involution, it is believed quite popularly that there will be enough functionally independent ones among them to guarantee the Liouville integrability of the Hamiltonian systems, at least for those derived from physical problems. In this paper, we give a counterexample based on the U(2) principal chiral field. It is proved that the finite dimensional Hamiltonian systems derived from the U(2) principal chiral field are Liouville integrable. Moreover, their Lax operator gives a set of involutive conserved integrals, but they are not enough to guarantee the integrability of the Hamiltonian systems.Comment: LaTeX, 11page

MDSC: Towards Evaluating the Style Consistency Between Music and

We propose MDSC(Music-Dance-Style Consistency), the first evaluation metric which assesses to what degree the dance moves and music match. Existing metrics can only evaluate the fidelity and diversity of motion and the degree of rhythmic matching between music and motion. MDSC measures how stylistically correlated the generated dance motion sequences and the conditioning music sequences are. We found that directly measuring the embedding distance between motion and music is not an optimal solution. We instead tackle this through modelling it as a clustering problem. Specifically, 1) we pre-train a music encoder and a motion encoder, then 2) we learn to map and align the motion and music embedding in joint space by jointly minimizing the intra-cluster distance and maximizing the inter-cluster distance, and 3) for evaluation purpose, we encode the dance moves into embedding and measure the intra-cluster and inter-cluster distances, as well as the ratio between them. We evaluate our metric on the results of several music-conditioned motion generation methods, combined with user study, we found that our proposed metric is a robust evaluation metric in measuring the music-dance style correlation. The code is available at: https://github.com/zixiangzhou916/MDSC.Comment: 17 pages, 17 figur

Solutions of the Yang-Mills-Higgs equations in 2+1 dimensional anti-de Sitter space-time

The solutions of the Bogomolny equation in anti-de Sitter space-time are obtained by using Darboux transformations with both constant spectral parameters and variable "spectral parameters". These solutions give the Yang-Mills-Higgs fields in anti-de Sitter space-time. Some examples in SU(2) case are considered and qualitative asymptotic behaviors of the solutions as t tends to infinity are discussed in detail.Comment: LaTeX, 18 pages, 11 PS figure

A Unified Framework for Multimodal, Multi-Part Human Motion Synthesis

The field has made significant progress in synthesizing realistic human motion driven by various modalities. Yet, the need for different methods to animate various body parts according to different control signals limits the scalability of these techniques in practical scenarios. In this paper, we introduce a cohesive and scalable approach that consolidates multimodal (text, music, speech) and multi-part (hand, torso) human motion generation. Our methodology unfolds in several steps: We begin by quantizing the motions of diverse body parts into separate codebooks tailored to their respective domains. Next, we harness the robust capabilities of pre-trained models to transcode multimodal signals into a shared latent space. We then translate these signals into discrete motion tokens by iteratively predicting subsequent tokens to form a complete sequence. Finally, we reconstruct the continuous actual motion from this tokenized sequence. Our method frames the multimodal motion generation challenge as a token prediction task, drawing from specialized codebooks based on the modality of the control signal. This approach is inherently scalable, allowing for the easy integration of new modalities. Extensive experiments demonstrated the effectiveness of our design, emphasizing its potential for broad application.Comment: 19 pages, 18 figure

AvatarGPT: All-in-One Framework for Motion Understanding, Planning, Generation and Beyond

Large Language Models(LLMs) have shown remarkable emergent abilities in unifying almost all (if not every) NLP tasks. In the human motion-related realm, however, researchers still develop siloed models for each task. Inspired by InstuctGPT, and the generalist concept behind Gato, we introduce AvatarGPT, an All-in-One framework for motion understanding, planning, generations as well as other tasks such as motion in-between synthesis. AvatarGPT treats each task as one type of instruction fine-tuned on the shared LLM. All the tasks are seamlessly interconnected with language as the universal interface, constituting a closed-loop within the framework. To achieve this, human motion sequences are first encoded as discrete tokens, which serve as the extended vocabulary of LLM. Then, an unsupervised pipeline to generate natural language descriptions of human action sequences from in-the-wild videos is developed. Finally, all tasks are jointly trained. Extensive experiments show that AvatarGPT achieves SOTA on low-level tasks, and promising results on high-level tasks, demonstrating the effectiveness of our proposed All-in-One framework. Moreover, for the first time, AvatarGPT enables a principled approach by iterative traversal of the tasks within the closed-loop for unlimited long-motion synthesis.Comment: 22 pages, 21 figure

INTERVENTION EFFECT OF RESEARCH-BASED PSYCHOLOGICAL COUNSELING ON ADOLESCENTS’ MENTAL HEALTH DURING THE COVID-19 EPIDEMIC

Background: This study aims to explore the intervention effect of research-based psychological counseling on adolescents’ mental health during the COVID-19 epidemic. Subjects and methods: From May to July 2020, 160 young students were selected from 5 middle schools in Shandong Province of China as the participants of this study and were randomly divided into the experiment and control groups with 80 members in each group. The routine in-campus education of health knowledge related to the epidemic was conducted in the control group, while the experiment group received both the routine education and the intervention of psychological counseling in combination with outdoor exercise. Results: No significant difference exists between the experiment and control groups (P>0.05) before the intervention, but the scores of the experiment group in anxiety and depression are lower than those of the control group (P<0.05) after the intervention; the PSQI score of the experiment group is significantly lower after the intervention, suggesting that the effect on the experiment group is better than the control group (P<0.05); the scores of the experiment group in psychological resilience and its 5 dimensions are higher than those of the control group (P<0.05). Conclusions: This intervention model has a good intervention effect on adolescents’ mental health and psychological resilience. At the same time, this study enlightens the introduction of the research-based psychological counseling model when helping adolescents solve mental health problems and highlights the important role of exercise in improving adolescents’ mental health and psychological resilience

Pathway Bridge Based Multiobjective Optimization Approach for Lurking Pathway Prediction

Ovarian carcinoma immunoreactive antigen-like protein 2 (OCIAD2) is a protein with unknown function. Frequently methylated or downregulated, OCIAD2 has been observed in kinds of tumors, and TGFβ signaling has been proved to induce the expression of OCIAD2. However, current pathway analysis tools do not cover the genes without reported interactions like OCIAD2 and also miss some significant genes with relatively lower expression. To investigate potential biological milieu of OCIAD2, especially in cancer microenvironment, a nova approach pbMOO was created to find the potential pathways from TGFβ to OCIAD2 by searching on the pathway bridge, which consisted of cancer enriched looping patterns from the complicated entire protein interactions network. The pbMOO approach was further applied to study the modulator of ligand TGFβ1, receptor TGFβR1, intermediate transfer proteins, transcription factor, and signature OCIAD2. Verified by literature and public database, the pathway TGFβ1- TGFβR1- SMAD2/3- SMAD4/AR-OCIAD2 was detected, which concealed the androgen receptor (AR) which was the possible transcription factor of OCIAD2 in TGFβ signal, and it well explained the mechanism of TGFβ induced OCIAD2 expression in cancer microenvironment, therefore providing an important clue for the future functional analysis of OCIAD2 in tumor pathogenesis