Emotion Recognition Model of EEG Signals Based on Double Attention Mechanism.

Background: Emotions play a crucial role in people's lives, profoundly affecting their cognition, decision-making, and interpersonal communication. Emotion recognition based on brain signals has become a significant challenge in the fields of affective computing and human-computer interaction.

Methods: Addressing the issue of inaccurate feature extraction and low accuracy of existing deep learning models in emotion recognition, this paper proposes a multi-channel automatic classification model for emotion EEG signals named DACB, which is based on dual attention mechanisms, convolutional neural networks, and bidirectional long short-term memory networks.

Development of a rapid, sensitive detection method for SARS-CoV-2 and influenza virus based on recombinase polymerase amplification combined with CRISPR-Cas12a assay.

Respiratory tract infections are associated with the most common diseases transmitted among people and remain a huge threat to global public health. Rapid and sensitive diagnosis of causative agents is critical for timely treatment and disease control. Here, we developed a novel method based on recombinase polymerase amplification (RPA) combined with CRISPR-Cas12a to detect three viral pathogens, including SARS-CoV-2, influenza A, and influenza B, which cause similar symptom complexes of flu cold in the respiratory tract.

Direct observation of topological magnon polarons in a multiferroic material.

Magnon polarons are novel elementary excitations possessing hybrid magnonic and phononic signatures, and are responsible for many exotic spintronic and magnonic phenomena. Despite long-term sustained experimental efforts in chasing for magnon polarons, direct spectroscopic evidence of their existence is hardly observed. Here, we report the direct observation of magnon polarons using neutron spectroscopy on a multiferroic FeMoO possessing strong magnon-phonon coupling.

CDBA: a novel multi-branch feature fusion model for EEG-based emotion recognition.

EEG-based emotion recognition through artificial intelligence is one of the major areas of biomedical and machine learning, which plays a key role in understanding brain activity and developing decision-making systems. However, the traditional EEG-based emotion recognition is a single feature input mode, which cannot obtain multiple feature information, and cannot meet the requirements of intelligent and high real-time brain computer interface. And because the EEG signal is nonlinear, the traditional methods of time domain or frequency domain are not suitable.

A fast vanishing point detection method based on row space features suitable for real driving scenarios.

The vanishing point (VP) is particularly important road information, which provides an important judgment criterion for the autonomous driving system. Existing vanishing point detection methods lack speed and accuracy when dealing with real road environments. This paper proposes a fast vanishing point detection method based on row space features.

DSCNN-LSTMs: A Lightweight and Efficient Model for Epilepsy Recognition.

Epilepsy is the second most common disease of the nervous system. Because of its high disability rate and the long course of the disease, it is a worldwide medical problem and social public health problem. Therefore, the timely detection and treatment of epilepsy are very important.

Modulating the catalytic activity of gold nanoparticles using amine-terminated ligands.

Nanozymes have broad applications in theranostics and point-of-care tests. To enhance the catalytic activity of nanozymes, the conventional strategy is doping metals to form highly active nanoalloys. However, high-quality and stable nanoalloys are hard to synthesize.

Gag Protein Oriented Supramolecular Nets as Potential HIV Traps.

For HIV/AIDS treatment, the cocktail therapy which uses a combination of anti-retroviral drugs remains the most widely accepted practice. However, the potential drug toxicity, patient tolerability, and emerging drug resistance have limited its long-term efficiency. Here, we design a HIV Gag protein-targeting redox supramolecular assembly (ROSA) system for potential HIV inhibition.

Evidence of the Berezinskii-Kosterlitz-Thouless phase in a frustrated magnet.

The Berezinskii-Kosterlitz-Thouless (BKT) mechanism, building upon proliferation of topological defects in 2D systems, is the first example of phase transition beyond the Landau-Ginzburg paradigm of symmetry breaking. Such a topological phase transition has long been sought yet undiscovered directly in magnetic materials. Here, we pin down two transitions that bound a BKT phase in an ideal 2D frustrated magnet TmMgGaO, via nuclear magnetic resonance under in-plane magnetic fields, which do not disturb the low-energy electronic states and allow BKT fluctuations to be detected sensitively.

Spatiotemporal variations in the incidence of bacillary dysentery and long-term effects associated with meteorological and socioeconomic factors in China from 2013 to 2017.

Bacillary dysentery is a global public health problem that exhibits manifest spatiotemporal heterogeneity. However, long-term variations and regional determinant factors remain unclear. In this study, the Bayesian space-time hierarchy model was used to identify the long-term spatiotemporal heterogeneity of the incidence of bacillary dysentery and quantify the associations of meteorological factors with the incidence of bacillary dysentery in northern and southern China from 2013 to 2017.

Supramolecular assemblies mimicking neutrophil extracellular traps for MRSE infection control.

Neutrophil extracellular traps (NETs) stick to bacteria and prevent infections in vivo, whose activation is upon inflammatory stimuli along with the sudden increase of reactive oxygen species (ROS). Nevertheless, the risky over activation in NETosis may result in deleterious outcome. A big challenge in using NETs for therapeutics is to synthesize an artificial system that can function as NETs in vivo.

Enzyme-Instructed Supramolecular Self-Assembly with Anticancer Activity.

Cancer remains one of the leading causes of death, which has continuously stimulated the development of numerous functional biomaterials with anticancer activities. Herein is reviewed one recent trend of biomaterials focusing on the advances in enzyme-instructed supramolecular self-assembly (EISA) with anticancer activity. EISA relies on enzymatic transformations to convert designed small-molecular precursors into corresponding amphiphilic residues that can form assemblies in living systems.

Hydrogen sulfide induced supramolecular self-assembly in living cells.

Here we developed a critical gasotransmitter (HS) mediated reduction to induce supramolecular self-assembly in multiple living cell lines. Specifically, the reduction converted an azido group to an amine which allowed the formation of intramolecular hydrogen bonds. The hydrogen bonds planarized the assembling molecules and promoted the supramolecular self-assembly.

Redox supramolecular self-assemblies nonlinearly enhance fluorescence to identify cancer cells.

Based on the nonlinear fluorescence enhancement, our H2O2 induced supramolecular self-assembly reveals a H2O2 threshold among multiple cancer and normal cells. Oxidative elimination restores an intramolecular hydrogen bond which can planarize the molecule to generate a fluorophore. The planarization enhances the intermolecular π-π stacking to promote self-assembly.

Enzyme-Instructed Self-assembly in Biological Milieu for Theranostics Purpose.

Precision medicine is in an urgent need for public healthcare. Among the past several decades, the flourishing development in nanotechnology significantly advances the realization of precision nanomedicine. Comparing to well-documented nanoparticlebased strategy, in this review, we focus on the strategy using enzyme instructed selfassembly (EISA) in biological milieu for theranostics purpose.

A dual-mode turn-on fluorescent BODIPY-based probe for visualization of mercury ions in living cells.

A novel turn-on fluorescent 8-amino BODIPY-based probe carrying a thiourea unit as the mercury ion recognition unit has been developed. Due to the cascade reaction processes, consecutive color changes reflecting the electronic absorption and emission responses were observed upon addition of increased concentrations of mercury(ii) ions. The likely sensing mechanism was proposed as mercury ion-promoted cyclization and subsequent hydrolysis.

Dual emission channels for sensitive discrimination of Cys/Hcy and GSH in plasma and cells.

A new selective fluorescent and colorimetric chemosensor for the detection of GSH was developed. The discrimination of GSH from Cys and Hcy is achieved through two emission channel detection. The detection limit of probe 1 for GSH reached 10 nM (3 ppb).

Highly selective and sensitive 1-amino BODIPY-based red fluorescent probe for thiophenols with high off-to-on contrast ratio.

A highly selective and sensitive turn-on red fluorescent 1-amino BODIPY-based probe (where BODIPY denotes indole-based boron-dipyrromethene) with high off-to-on contrast ratio has been developed. The probe displayed selective response to thiophenols over aliphatic thiols. Probe 1 is promising for the quantitative detection of thiophenol with a linear response from 6 × 10(-6) M to 1 × 10(-4) M, and the detection limit for thiophenol (PhSH) reaches 4 × 10(-6) M measured in acetonitrile/PBS buffer.