Processing of Affective Pictures: A Study Based on Functional Connectivity Network in the Cerebral Cortex.

Emotion plays an important role in people's life. However, the existing researches do not give a unified conclusion on the brain function network under different emotional states. In this study, pictures from the international affective picture system (IAPS) of different valences were presented to subjects with a fixed frequency blinking frequency to induce stable state visual evoked potential (SSVEP).

Neural Mechanism of Affective Perception: Evidence from Phase and Causality Analysis in the Cerebral Cortex.

Emotion plays an important role in people's lives. However, the neural mechanism of affective perception is still unclear. In this study, steady-state visual evoked potentials (SSVEPs) were used to explore information processing speed and interactions among cortical structures involved in affective perception.

Two-Level Domain Adaptation Neural Network for EEG-Based Emotion Recognition.

Emotion recognition plays an important part in human-computer interaction (HCI). Currently, the main challenge in electroencephalogram (EEG)-based emotion recognition is the non-stationarity of EEG signals, which causes performance of the trained model decreasing over time. In this paper, we propose a two-level domain adaptation neural network (TDANN) to construct a transfer model for EEG-based emotion recognition.

Experimental study on bone defect repair by BMSCs combined with a light-sensitive material: g-CN/rGO.

Bone marrow mesenchymal stem cells (BMSCs), as seed cells, have played an important role in bone defect repair. However, efficiently amplifying and inducing BMSCs or vivo remains an urgent problem to be solved. Electrical stimulation has been beneficial to the proliferation and differentiation of BMSCs, but current electrical stimulation methods have a critical disadvantage in that they usually burn the skin.

High Gamma Band EEG Closely Related to Emotion: Evidence From Functional Network.

High-frequency electroencephalography (EEG) signals play an important role in research on human emotions. However, the different network patterns under different emotional states in the high gamma band (50-80 Hz) remain unclear. In this paper, we investigate different emotional states using functional network analysis on various frequency bands.

The Optimization Design Of Lactoferrin Loaded HupA Nanoemulsion For Targeted Drug Transport Via Intranasal Route.

Background: Huperzine A (HupA) is a selective acetylcholinesterase inhibitor used to treat Alzheimer's disease. The existing dosage of HupA lacks brain selectivity and can cause serious side effects in the gastrointestinal and peripheral cholinergic systems.

Purpose: The aim of this study was to develop and characterize a HupA nanoemulsion (NE) and a targeted HupA-NE modified with lactoferrin (Lf) for intranasal administration.

Fine-Grained Video Captioning via Graph-based Multi-Granularity Interaction Learning.

Learning to generate continuous linguistic descriptions for multi-subject interactive videos in great details has particular applications in team sports auto-narrative. In contrast to traditional video caption, this task is more challenging as it requires simultaneous modeling of fine-grained individual actions, uncovering of spatio-temporal dependency structures of frequent group interactions, and then accurate mapping of these complex interaction details into long and detailed commentary. To explicitly address these challenges, we propose a novel framework Graph-based Learning for Multi-Granularity Interaction Representation (GLMGIR) for fine-grained team sports auto-narrative task.

Carboxymethyl Cellulose Binder Greatly Stabilizes Porous Hollow Carbon Submicrospheres in Capacitive K-Ion Storage.

On account of the large radius of K-ions, the electrodes can suffer huge deformation during K-ion insertion and extraction processes. In our work, we unveil the impact of using carboxymethyl cellulose (CMC) instead of poly(vinylidene fluoride) (PVDF) as binders for K-ion storage. Our porous hollow carbon submicrosphere anodes using the CMC binder exhibit a reversible capacity of 208 mA h g after 50 cycles at 50 mA g, and even at a high current density of 1 A g, they achieve a reversible capacity of 111 mA h g over 3000 cycles with almost no decay, demonstrating remarkably improved reversibility and cycling stability than those using PVDF (18 mA h g after 3000 cycles at 1 A g).

Rational design of metal organic framework-derived FeS hollow nanocages@reduced graphene oxide for K-ion storage.

K-ion batteries (KIBs) have become one of the promising alternatives to lithium ion batteries. In this work, we are the first to utilize reduced graphene oxide (RGO) wrapped metal organic framework-derived FeS2 hollow nanocages (FeS2@RGO) as an anode for KIBs. Owing to the synergistic effect from FeS2 nanocages and RGO shells, our FeS2@RGO sample exhibited superior electrochemical performance.

Investigating Patterns for Self-Induced Emotion Recognition from EEG Signals.

Most current approaches to emotion recognition are based on neural signals elicited by affective materials such as images, sounds and videos. However, the application of neural patterns in the recognition of self-induced emotions remains uninvestigated. In this study we inferred the patterns and neural signatures of self-induced emotions from electroencephalogram (EEG) signals.

Emotion Recognition from EEG Signals Using Multidimensional Information in EMD Domain.

This paper introduces a method for feature extraction and emotion recognition based on empirical mode decomposition (EMD). By using EMD, EEG signals are decomposed into Intrinsic Mode Functions (IMFs) automatically. Multidimensional information of IMF is utilized as features, the first difference of time series, the first difference of phase, and the normalized energy.

The impact of urban health insurance reform on hospital charges: a case study from two cities in China.

During the transition from a centrally planned to a market economy, China's urban health insurance system is being reformed. The control of the rapidly increasing hospital expenses will be a major determinant of the success of the reform. This study aims to examine the impact of the reform on hospital charges by comparing changes between two cities with different insurance systems and identifying determinants for those changes.