Husformer: A Multi-Modal Transformer for Multi-Modal Human State Recognition

Human state recognition is a critical topic with pervasive and important applications in human-machine systems.Multi-modal fusion, the combination of metrics from multiple data sources, has been shown as a sound method for improving the recognition performance. However, while promising results have been reported by recent multi-modal-based models, they generally fail to leverage the sophisticated fusion strategies that would model sufficient cross-modal interactions when producing the fusion representation; instead, current methods rely on lengthy and inconsistent data preprocessing and feature crafting. To address this limitation, we propose an end-to-end multi-modal transformer framework for multi-modal human state recognition called Husformer.Specifically, we propose to use cross-modal transformers, which inspire one modality to reinforce itself through directly attending to latent relevance revealed in other modalities, to fuse different modalities while ensuring sufficient awareness of the cross-modal interactions introduced. Subsequently, we utilize a self-attention transformer to further prioritize contextual information in the fusion representation. Using two such attention mechanisms enables effective and adaptive adjustments to noise and interruptions in multi-modal signals during the fusion process and in relation to high-level features. Extensive experiments on two human emotion corpora (DEAP and WESAD) and two cognitive workload datasets (MOCAS and CogLoad) demonstrate that in the recognition of human state, our Husformer outperforms both state-of-the-art multi-modal baselines and the use of a single modality by a large margin, especially when dealing with raw multi-modal signals. We also conducted an ablation study to show the benefits of each component in Husformer

Fault diagnosis of motorized spindle via modified empirical wavelet transform-kernel PCA and optimized support vector machine

The fault diagnosis of motorized spindle contributes to the improvement of the reliability of computer numerical control machine tools. Presently, numerous mechanical fault diagnosis technologies suffer from the drawbacks of mode mixing, non-adaptive analysis, and low efficiency. Therefore, adopting an effective signal processing method for fault diagnosis of motorized spindle is essential. A method based on modified empirical wavelet transform (EWT) and kernel principal component analysis (Kernel PCA) is proposed. A new method, which determines the proper number of the Fourier spectrum segments, is applied when using EWT. To improve computational efficiency, Kernel PCA is adopted to reduce dimension. The support vector machine optimized by genetic algorithm is introduced to accomplish fault identification. The performance of the proposed method is validated through single and compound fault experiments. Results show that the recognition rate using the proposed method reached 98.8095 % and 98.4375 % in terms of single and compound fault diagnoses, respectively. Moreover, compared with empirical mode decomposition (EMD), ensemble empirical mode decomposition (EEMD), local mean decomposition (LMD) and EWT, the proposed method can save much computing time. The proposed method can be generalized to other mechanical fault diagnoses as well

Two-way in-/congruence in three components of paternalistic leadership and subordinate justice: The mediating role of perceptions of renqing

This paper examines the effects of two-way congruences and incongruences between three components of paternalistic leadership, namely, benevolence, morality, and authoritarianism, on overall subordinate justice perceptions. We hypothesize that these dyad in-/congruences would differentially predict subordinate overall justice perceptions, with perceptions of renqing as a mediator. With data collected from two-wave surveys in the People’s Republic of China, the results indicate that dyad congruences and incongruences between benevolence, morality, and authoritarianism have significant impacts on subordinate perceptions of renqing and, ultimately, their overall justice perception. Our findings underscore that to fully understand the influencing processes of paternalistic leadership on subordinate outcomes, it is important to take into account the context and the different combinations of its three dimensions

Robust anomalous Hall effect in ferromagnetic metal under high pressure

Recently, the giant intrinsic anomalous Hall effect (AHE) has been observed in the materials with kagome lattice. In this study, we systematically investigate the influence of high pressure on the AHE in the ferromagnet LiMn6Sn6 with clean Mn kagome lattice. Our in-situ high-pressure Raman spectroscopy indicates that the crystal structure of LiMn6Sn6 maintains a hexagonal phase under high pressures up to 8.51 GPa. The anomalous Hall conductivity (AHC) {\sigma}xyA remains around 150 {\Omega}-1 cm-1, dominated by the intrinsic mechanism. Combined with theoretical calculations, our results indicate that the stable AHE under pressure in LiMn6Sn6 originates from the robust electronic and magnetic structure.Comment: 11 pages 5 figure

Pressure-tunable magnetic topological phases in magnetic topological insulator MnSb4Te7

Magnetic topological insulators, possessing both magnetic order and topological electronic structure, provides an excellent platform to research unusual physical properties. Here, we report a high-pressure study on the anomalous Hall effect of magnetic TI MnSb4Te7 through transports measurements combined with first-principle theoretical calculations. We discover that the ground state of MnSb4Te7 experiences a magnetic phase transition from the A-type antiferromagnetic state to ferromagnetic dominating state at 3.78 GPa, although its crystal sustains a rhombohedral phase under high pressures up to 8 GPa. The anomalous Hall conductance {\sigma}xyA keeps around 10 {\Omega}-1 cm-1, dominated by the intrinsic mechanism even after the magnetic phase transition. The results shed light on the intriguing magnetism in MnSb4Te7 and pave the way for further studies of the relationship between topology and magnetism in topological materials.Comment: 10 pages, 4 figure

Pressure-induced Superconductivity and Structure Phase Transition in SnAs-based Zintl Compound SrSn2As2

Layered SnAs-based Zintl compounds exhibit a distinctive electronic structure, igniting extensive research efforts in areas of superconductivity, topological insulators and quantum magnetism. In this paper, we systematically investigate the crystal structures and electronic properties of the Zintl compound SrSn2As2 under high-pressure. At approximately 20.8 GPa, pressure-induced superconductivity is observed in SrSn2As2 with a characteristic dome-like evolution of Tc. Theoretical calculations together with high pressure synchrotron X-ray diffraction and Raman spectroscopy have identified that SrSn2As2 undergoes a structural transformation from a trigonal to a monoclinic structure. Beyond 28.3 GPa, the superconducting transition temperature is suppressed due to a reduction of the density of state at the Fermi level. The discovery of pressure-induced superconductivity, accompanied by structural transitions in SrSn2As2, greatly expands the physical properties of layered SnAs-based compounds and provides a new ground states upon compression.Comment: 15 pages, 6 figures. arXiv admin note: text overlap with arXiv:2307.1562

Pressure-induced Superconductivity in Zintl Topological Insulator SrIn2As2

The Zintl compound AIn2X2 (A = Ca, Sr, and X = P, As), as a theoretically predicted new non-magnetic topological insulator, requires experiments to understand their electronic structure and topological characteristics. In this paper, we systematically investigate the crystal structures and electronic properties of the Zintl compound SrIn2As2 under both ambient and high-pressure conditions. Based on systematic angle-resolved photoemission spectroscopy (ARPES) measurements, we observed the topological surface states on its (001) surface as predicted by calculations, indicating that SrIn2As2 is a strong topological insulator. Interestingly, application of pressure effectively tuned the crystal structure and electronic properties of SrIn2As2. Superconductivity is observed in SrIn2As2 for pressure where the temperature dependence of the resistivity changes from a semiconducting-like behavior to that of a metal. The observation of nontrivial topological states and pressure-induced superconductivity in SrIn2As2 provides crucial insights into the relationship between topology and superconductivity, as well as stimulates further studies of superconductivity in topological materials.Comment: 15 pages,5 figure