Interactive Spatiotemporal Token Attention Network for Skeleton-based General Interactive Action Recognition

Recognizing interactive action plays an important role in human-robot interaction and collaboration. Previous methods use late fusion and co-attention mechanism to capture interactive relations, which have limited learning capability or inefficiency to adapt to more interacting entities. With assumption that priors of each entity are already known, they also lack evaluations on a more general setting addressing the diversity of subjects. To address these problems, we propose an Interactive Spatiotemporal Token Attention Network (ISTA-Net), which simultaneously model spatial, temporal, and interactive relations. Specifically, our network contains a tokenizer to partition Interactive Spatiotemporal Tokens (ISTs), which is a unified way to represent motions of multiple diverse entities. By extending the entity dimension, ISTs provide better interactive representations. To jointly learn along three dimensions in ISTs, multi-head self-attention blocks integrated with 3D convolutions are designed to capture inter-token correlations. When modeling correlations, a strict entity ordering is usually irrelevant for recognizing interactive actions. To this end, Entity Rearrangement is proposed to eliminate the orderliness in ISTs for interchangeable entities. Extensive experiments on four datasets verify the effectiveness of ISTA-Net by outperforming state-of-the-art methods. Our code is publicly available at https://github.com/Necolizer/ISTA-NetComment: IROS 2023 Camera-ready version. Project website: https://necolizer.github.io/ISTA-Net

Genetic alteration of histone lysine methyltransferases and their significance in renal cell carcinoma

Background Histone lysine methyltransferases (HMTs), a category of enzymes, play essential roles in regulating transcription, cellular differentiation, and chromatin construction. The genomic landscape and clinical significance of HMTs in renal cell carcinoma (RCC) remain uncovered. Methods We conducted an integrative analysis of 50 HMTs in RCC and discovered the internal relations among copy number alterations (CNAs), expressive abundance, mutations, and clinical outcome. Results We confirmed 12 HMTs with the highest frequency of genetic alterations, including seven HMTs with high-level amplification, two HMTs with somatic mutation, and three HMTs with putative homozygous deletion. Patterns of copy number and expression varied among different subtypes of RCC, including clear cell renal cell carcinoma, papillary cell carcinoma, and chromophobe renal carcinoma. Kaplan–Meier survival analysis and multivariate analysis identified that CNA or mRNA expression in some HMTs were significantly associated with shorter overall patient survival. Systematic analysis identified six HMTs (ASH1L, PRDM6, NSD1, EZH2, WHSC1L1, SETD2) which were dysregulated by genetic alterations as candidate therapeutic targets. Discussion In summary, our findings strongly evidenced that genetic alteration of HMTs may play an important role in generation and development of RCC, which lays a solid foundation for the mechanism for further research in the future

A Multi-Factorial Evolutionary Algorithm With Asynchronous Optimization Processes for Solving the Robust Influence Maximization Problem

Wang S, Ding B, Jin Y. A Multi-Factorial Evolutionary Algorithm With Asynchronous Optimization Processes for Solving the Robust Influence Maximization Problem. IEEE Computational Intelligence Magazine. 2023;18(3):41-53.The complex network has attracted increasing attention and shown effectiveness in modeling multifarious systems. Focusing on selecting members with good spreading ability, the influence maximization problem is of great significance in network-based information diffusion tasks. Plenty of attention has been paid to simulating the diffusion process and choosing influential seeds. However, errors and attacks typically threaten the normal function of networked systems, and few studies have considered the influence maximization problem under structural failures. Therefore, a quantitative measure with a changeable parameter is first developed in this paper to tackle the unpredictable destruction percentage on networks. Further, limitations on the existing methods are shown experimentally. To address these limitations, the evolutionary multitasking paradigm is employed, and several problem-specific operators are developed. On top of these developments, a multi-factorial evolutionary algorithm is devised to find seeds with robust influence ability, termed MFEARIM, where the genetic information for both myopia and holistic areas is considered to improve the search ability. Additionally, an asynchronous strategy is designed to efficiently tackle tasks with distinct costs, and the convergence of the search process can thus be accelerated. Experiments on several synthetic and real-world networks validate the competitive performance of MFEARIM over the existing methods

Robust H-Infinity Tracking Control for a Valve-Controlled Hydraulic Motor System with Uncertain Parameters in the Complex Load Environment

A valve-controlled hydraulic motor system operating in a complex environment is subject to complex load changes. In extreme cases, the load can be regarded as a disturbance signal with complex frequency and strong amplitude fluctuations, which greatly affects the speed stability of the hydraulic motor and reduces the operating efficiency. In this paper, the structure of valve-controlled hydraulic motor systems is analyzed, and a valve-controlled hydraulic motor system model with uncertain parameters is established after considering the actual target parameter error and model linearization error. Different from the common H-infinity control, which regards the load disturbance as external disturbance, this paper presents a robust H-infinity tracking control strategy, which considers uncertain parameters and the load torque of the valve-controlled hydraulic motor system as internal disturbances. The simulation results show that the proposed control scheme has better control characteristics and robustness than the traditional PID control

The complete mitochondrial genome of Holothuria fuscocinerea (Jaeger,1833)

In this study, the complete mitochondrial genome of Holothuria fuscocinerea was sequenced on an Illumina platform and assembled using NovoPlasty v. 2.7.1. It was submitted to NCBI GenBank and is available with accession number MN542416. The genome was 15,827 bp in size and contains 22 tRNA genes, 12 protein-coding genes, and 2 rRNA genes. The composition of A + T in Holothura spinifera mtDNA was 60.30%. Except ND6 and 5 tRNAs, the others are not on the H-strand. The phylogenetic relationship of 13 species of sea cucumber were analyzed using the neighbor-joining method by software MEGA5.0. Holothuria fuscocinerea was most closely related to Holothuria polii

A novel collaborative control algorithm for maximum power point tracking of wind energy hydraulic conversion system

Abstract Wind has been admitted as one of the most promising renewable energy resources in multinational regionalization policies. However, the energy conversion and utilization are challenging due to the technique reliability and cost issues. Hydraulic wind turbine (HWT) may solve the above problems. HWT is taken as a research object, and the maximum power point tracking (MPPT) control strategy is proposed collaborating with active disturbance rejection control (ADRC) and linear quadratic regulator (LQR) control methods, to solve multiplicative nonlinearity problems in the plant models and the influence of external disturbance on control performance in the MPPT control process. A nonlinear simulation model is built to explain the main findings from the experiments and obtain a better understanding of the effect of time‐varying system parameters and random fluctuation in wind speed. The collaborative control algorithm is experimentally verified on a 24‐kW HWT semi‐physical test platform that results in a promising energy conversion rate, plus the hydraulic parameters can satisfy the demand, accordingly. Ultimately, the potential challenges of implementing this technique in a smart wind energy conversion system are discussed to give a further design guidance, either theoretically or practically

The complete mitochondrial genome of Holothuria spinifera (Théel, 1866)

In this research, on an Illumina platform, the full mitochondrial genome of Holothuria spinifera was listed in a sequence and also gathered by using the NovoPlasty v. 2.7.1. It was submitted to NCBI GenBank, and is available with accession number MN816440. The size of genome was 15,812 bp and contained 12 protein-coding genes, two rRNA genes, and 22 tRNA genes. The configuration of A + T in Holothuria spinifera mtDNA was 60.44%. Except five tRNAs and ND6, others are placed on the H-strand. By using the Neighbor-Joining method by software MEGA5.0, the phylogenetic relationship of 13 species of sea cucumber was analyzed. Holothuria spinifera was most closely associated to Parastichopus parvimensis