A multimodal functional structure-based graph neural network for fatigue detection.

Fatigue detection remains a critical research focus in the field. Recent studies have attempted to enhance detection performance through multimodal information fusion, yet they largely overlook the impact of functional connectivity among multimodal signals. To address this limitation, we propose a novel multimodal fatigue classification framework integrating electroencephalogram (EEG) and electrocardiogram (ECG) signals.

IncorporationNet: a novel bimodal EEG-EOG vigilance estimation method via time-frequency-space feature fusion network.

The assessment of driver vigilance is critical for promoting road safety, as it evaluates a driver's ability to sustain appropriate levels of attention and reaction capabilities. Electroencephalogram (EEG) and electrooculogram (EOG) signals have proven effective in this context. We propose a bimodal time-frequency-space feature fusion framework aimed at enhancing the integration of EEG and EOG features to improve the predictive accuracy of vigilance estimation.

A continuous multi-night sleep database for exploring sleep structure similarity.

The sleep structure of healthy adults varies across continuous nights but exhibits periodicity and regularity. To explore the similarities and differences in sleep electroencephalogram structures on an intra- and inter-individual basis across nights, we present an open-access, continuous, multi-night sleep database. This database contains multi-modal sleep monitoring data from 20 healthy participants over three consecutive nights.

A multi-domain constraint learning system inspired by adaptive cognitive graphs for emotion recognition.

Neuroscience shows that the brain stimulated by external information can induce functional responses to emotions, which can be measured and analyzed by electroencephalogram (EEG). Most existing works focus on extracting specific spatial topological information and temporal dependency representations, with a few works begin to mine the value of spatiotemporal cross-domain information. However, these approaches overdependence on cognitive prior information, limiting their ability to grasp complex domain-structured information.

Symmetry Restoration and Quantum Mpemba Effect in Symmetric Random Circuits.

Entanglement asymmetry, which serves as a diagnostic tool for symmetry breaking and a proxy for thermalization, has recently been proposed and studied in the context of symmetry restoration for quantum many-body systems undergoing a quench. In this Letter, we investigate symmetry restoration in various symmetric random quantum circuits, particularly focusing on the U(1) symmetry case. In contrast to nonsymmetric random circuits where the U(1) symmetry of a small subsystem can always be restored at late times, we reveal that symmetry restoration can fail in U(1)-symmetric circuits for certain weak symmetry-broken initial states in finite-size systems.

Strong Pairing Originated from an Emergent Z_{2} Berry Phase in La_{3}Ni_{2}O_{7}.

The recent discovery of high-temperature superconductivity in La_{3}Ni_{2}O_{7} offers a fresh platform for exploring unconventional pairing mechanisms. Starting with the basic argument that the electrons in d_{z^{2}} orbitals nearly form local moments, we examine the effect of the Hubbard interaction U on the binding strength of Cooper pairs based on a single-orbital bilayer model with intralayer hopping t_{∥} and interlayer superexchange J_{⊥}. By extensive density matrix renormalization group calculations, we observe a remarkable enhancement in binding energy as much as 10-20 times larger with U/t_{∥} increasing from 0 to 12 at J_{⊥}/t_{∥}∼1.

Absence of Barren Plateaus in Finite Local-Depth Circuits with Long-Range Entanglement.

Ground state preparation is classically intractable for general Hamiltonians. On quantum devices, shallow parametrized circuits can be effectively trained to obtain short-range entangled states under the paradigm of variational quantum eigensolver, while deep circuits are generally untrainable due to the barren plateau phenomenon. In this Letter, we give a general lower bound on the variance of circuit gradients for arbitrary quantum circuits composed of local 2-designs.

Identification of magnetic interactions and high-field quantum spin liquid in α-RuCl.

The frustrated magnet α-RuCl constitutes a fascinating quantum material platform that harbors the intriguing Kitaev physics. However, a consensus on its intricate spin interactions and field-induced quantum phases has not been reached yet. Here we exploit multiple state-of-the-art many-body methods and determine the microscopic spin model that quantitatively explains major observations in α-RuCl, including the zigzag order, double-peak specific heat, magnetic anisotropy, and the characteristic M-star dynamical spin structure, etc.

The complete chloroplast genome sequence of .

In this study, the chloroplast genome sequence of was obtained from the whole genome sequencing data of . Its length is 158,248 bp, which consists of 86,331 bp large single-copy region (LSC), 26,408 bp two reverse repeat regions (IR) and 19,101 bp small single-copy region (SSC). GC content of the whole chloroplast genome is 36.