Synthesis of CC/BiPO4/Bi2WO6 Composite Material and Its Photocatalytic Performance

Along with the popularity of environmental protection concepts, the environmental treatment of water pollution attracts widespread attention, among which, the research on Bi-based semiconductor photocatalytic degradation technology has made great progress. However, the development of such bismuth-based composites still remains a challenging task due to difficult recovery and low catalytic efficiency. Herein, a novel CC/BiPO4/Bi2WO6 composite was successfully synthesized through two-step hydrothermal method using activated flexible carbon cloth as a substrate. The results of the photocatalytic degradation experiments showed that the obtained CC/BiPO4/Bi2WO6 composites can degrade 92.1% RhB in 60 min under UV-visible light irradiation, which was much higher than that of unloaded BiPO4 (24.4%) and BiPO4/Bi2WO6 (52.9%), exhibiting a better adsorption-photocatalytic degradation performance than BiPO4 and BiPO4/Bi2WO6. Photoluminescence spectra indicated that the improved photocatalytic activity was due to the more effective inhibition of photogenerated carrier complexation. Furthermore, the radical capture experiments confirmed that h+, ·OH and O2- were the main active substances in the photocatalytic degradation process of RhB by the CC/BiPO4/Bi2WO6 composites. More importantly, the prepared CC/BiPO4/Bi2WO6 composite had a simple separation process and good recycling stability, and its photocatalytic degradation efficiency can still reach 53.3% after six cycles of RhB degradation. .

Formulation of Locational Marginal Electricity-carbon Price in Power Systems

Decarbonisation of power systems is essential for realising carbon neutrality,in which the economic cost caused by carbon needs to be qualified.Based on the formulation of locational marginal price(LMP),this paper proposes a locational marginal electricity-carbon price(EC-LMP)model to reveal carbon-related costs caused by power consumers.A carbon-priceintegrated optimal power flow(C-OPF)is then developed to maximise economic efficiency of the power system considering the costs of electricity and carbon.Case studies are presented to demonstrate the new formulation and results demonstrate the efficacy of the EC-LMP-based C-OPF on decarbonisation and economy.

A personality-guided affective brain-computer interface for implementation of emotional intelligence in machines

Affective brain-computer interfaces have become an increasingly important topic to achieve emotional intelligence in human–machine collaboration.However,due to the complexity of electroencephalogram(EEG)signals and the individual differences in emotional response,it is still a great challenge to design a reliable and effective model.Considering the influence of personality traits on emotional response,it would be helpful to integrate personality information and EEG signals for emotion recognition.This study proposes a personalityguided attention neural network that can use personality information to learn effective EEG representations for emotion recognition.Specifically,we first use a convolutional neural network to extract rich temporal and regional representations of EEG signals,and a special convolution kernel is designed to learn inter-and intra-regional correlations simultaneously.Second,inspired by the fact that electrodes within distinct brain scalp regions play different roles in emotion recognition,a personality-guided regional-attention mechanism is proposed to further explore the contributions of electrodes within a region and between regions.Finally,attention-based long short-term memory is designed to explore the temporal dynamics of EEG signals.Experiments on the AMIGOS dataset,which is a dataset for multimodal research for affect,personality traits,and mood on individuals and groups,show that the proposed method can significantly improve the performance of subject-independent emotion recognition and outperform state-of-the-art methods.