Ferroelectric memristors possess advantages such as low operating voltage, high storage density and sub-micron-scale multi-state storage, making them widely used in fields such as information storage and mimicking biological synaptic functions. Here, the ferroelectric resistive switching (RS) devices with an Ag/(1-x)Bi0.5Na0.5TiO3-xSrTiO3/FTO (x = 0.1-0.3) structure are fabricated by the sol-gel method. The structure, memory resistance characteristics, RS mechanism and neural state application simulation of the memristors have been thoroughly studied. The optimal memristor characteristics with 103 storage window, 300 resistive switching cycles and 2 × 103 s retention time is obtained in the Ag/0.8Bi0.5Na0.5TiO3-0.2SrTiO3/FTO (BNT-ST) sample. The RS mechanism of the BNT-ST sample is mainly attributed to the combined effect of ferroelectric polarization and conductive filaments. Moreover, the BNT-ST memristor possesses outstanding synaptic functions, including excitatory/inhibitory postsynaptic current (EPSC/IPSC), paired-pulse facilitation/depression (PPF/PPD), spike-timing-dependent plasticity (STDP) and long-term potentiation/depression (LTP/LTD), as well as the characteristics of nociceptors and pain sensitization behavior. It also simulated image memory related to human brain learning-forgetting and the variations in body water levels across distinct operational states. Furthermore, through an artificial neural network model, the BNT-ST memristor achieved a recognition rate of 93.45% on the MNIST handwritten digit dataset, demonstrating excellent accuracy.
Graph-based electroencephalogram (EEG) emotion recognition methods model inter-channel relationships by constructing connectivity graphs over EEG electrodes. Fixed structural priors may be insufficient to characterize subject- and trial-specific variations, whereas highly adaptive graphs may be sensitive to noise. In addition, temporal and spectral EEG representations are often fused mainly at the feature level, leaving the graph-level relationship between representation domains relatively underexplored. To address these issues, we propose PSAGAN, a Prior-Guided Sample-Adaptive Graph Attention Network with diffusion-based cross-domain graph topology regularization for EEG-based emotion recognition. PSAGAN constructs spatial-spectral and spatial-temporal pathways and introduces a prior-guided sample-adaptive graph attention mechanism within each pathway. This mechanism incorporates distance-based anatomical priors into feature-dependent attention computation, enabling the model to use structural guidance while learning sample-dependent edge weights within anatomically guided neighborhoods. To coordinate the two pathway-specific graphs, PSAGAN introduces a diffusion-based topology regularization strategy that compares multi-scale diffusion signatures and uses category-level contrastive learning to encourage coarse-grained topological coherence while retaining domain-specific learned connectivity patterns. An adaptive integration module then combines the two pathway representations for classification. Experiments on SEED and SEED-IV under both subject-dependent and subject-independent settings, and on DEAP under trial-grouped 10-fold cross-validation, show that PSAGAN achieves competitive performance under the adopted evaluation protocols. On SEED, PSAGAN obtains 98.39% subject-dependent accuracy and 90.18% subject-independent accuracy. On SEED-IV, it achieves 90.57% and 79.36% under the two settings, respectively. On DEAP, it reaches 97.83% and 98.21% for valence and arousal classification, respectively. Ablation studies indicate that prior-guided graph learning, diffusion-based topology regularization, and adaptive integration provide complementary benefits. Additional evaluations on motor imagery, sleep staging, and depression detection suggest potential applicability to broader multi-channel EEG tasks.
As emerging contaminants, sulfonamide antibiotics (SAs) widely exist in aqueous systems and photo-degrade significantly in surface waters, requiring new insights into their aqueous apparent photolytic mechanisms and photo-modified toxicity. In this study, reaction kinetics, self-sensitized photo-oxidation, transformation pathways, antibacterial activity and photo-induced toxicity were investigated during the apparent photolysis of nine SAs including sulfamethoxazole (SMX), sulfisoxazole, sulfathiazole, sulfamethizole, sulfadimethoxine (SDM), sulfadiazine, sulfachloropyridazine, sulfamerazine and sulfamethazine. Under simulated sunlight irradiation (λ > 290 nm), most five-membered heterocyclic SAs underwent photodegradation at a faster rate than all six-membered heterocyclic SAs, which was ascribed to their chemical structures including different heterocyclic groups and associated substituents (− CH3). The scavenging experiments indicated that SMX underwent self-sensitized photo-degradation via O2•−, 1O2 and •OH, and direct photo-degradation via 3P*. The contribution of O2•− (40.71
Myocarditis is a clinical condition characterized by inflammation of the myocardium. It commonly occurs in various heart disorders and, in extreme circumstances, can be fatal. However, the effective and safe dietary strategies for alleviating myocardial inflammatory injury are currently lacking. Here we investigated the potential of daidzein (DD), a natural isoflavone found in leguminous plants, in alleviating myocardial inflammatory injury. The lipopolysaccharides (LPS)-treated C57BL/6J mice and H9c2 cardiomyocytes were employed to investigate the protective effects and mechanisms of DD against myocardial inflammation. In animal studies, DD supplementation at 50 and 100 mg/kg/d significantly alleviated the myocardial injury induced by LPS. In cell experiments, 2.5 µM DD effectively decreased LPS-induced oxidative stress, cell death, and inflammatory responses. In addition, DD mitigated the LPS-induced calcium imbalance in cardiomyocytes. Mechanistically, DD inhibited the LPS-induced myocardial inflammatory injury by targeting estrogen receptor beta (ERβ), subsequently leading to a reduction in ER stress. Furthermore, the molecular docking and experimental validation revealed that the binding pocket of DD in ERβ was highly conserved, and that the H475 and R376 residues were essential for binding DD. In summary, our results suggest that dietary DD supplementation is a promising strategy for alleviating myocardial inflammatory injury.
As electromagnetic environmental issues become increasingly prominent, particularly in scenarios where multiple frequency bands coexist—such as 5G/satellite communications, radar, and Wi-Fi—there is a growing need for efficient, thin, and lightweight electromagnetic wave absorption materials across wide bandwidths (e.g., 2–18 GHz) to mitigate electromagnetic interference and leakage risks. Polyurethane (PU) and graphene (GR) have emerged as focal points in broadband absorber research due to their lightweight properties, processability, and tunable dielectric characteristics. This paper systematically reviews the limitations of traditional absorption materials, focusing on recent advances in PU/GR composite absorption materials regarding composition, fabrication techniques, and absorption mechanisms. It analyzes key mechanisms affecting broadband absorption—including dielectric loss, impedance matching, and multiple scattering—through specific case studies. The paper identifies key shortcomings in current research—such as impedance mismatch caused by GR agglomeration, the trade-off between thin-film thickness and broadband performance, environmental stability, and standardization of fabrication processes—while proposing feasible optimization strategies and future research directions. This aims to provide researchers in the field with clear, actionable design and fabrication recommendations.
