Social anxiety prediction based on ERP features: A deep learning approach.

Background: Social Anxiety Disorder is traditionally diagnosed using subjective scales that may lack accuracy. Recently, EEG technology has gained importance for anxiety detection due to its ability to capture stable and objective neurophysiological activities. However, existing methods mainly focus on extracting EEG features during resting states, with limited use of psychologically features like Event-Related Potential (ERP) in task-related states for anxiety detection in deep learning frameworks.

Pseudomorphic amorphization of three-dimensional superlattices through morphological transformation of nanocrystal building blocks.

Nanocrystal (NC) superlattices (SLs) have been widely studied as a new class of functional mesoscopic materials with collective physical properties. The arrangement of NCs in SLs governs the collective properties of SLs, and thus investigations of phenomena that can change the assembly of NC constituents are important. In this study, we investigated the dynamic evolution of NC arrangements in three-dimensional (3D) SLs, specifically the morphological transformation of NC constituents during the direct liquid-phase synthesis of 3D NC SLs.

Event-related alpha power in early stage of facial expression processing in social anxiety: Influence of language context.

Accurate interpretation of the emotional information conveyed by others' facial expressions is crucial for social interactions. Event-related alpha power, measured by time-frequency analysis, is a frequently used EEG index of emotional information processing. However, it is still unclear how event-related alpha power varies in emotional information processing in social anxiety groups.

The effective removal of Pb by activated carbon fibers modified by l-cysteine: exploration of kinetics, thermodynamics and mechanism.

Herein, we developed a low-cost fabrication route to prepare chemically grafted activated carbon fibers, which effectively removed Pb from solution. Multiple characteristic results indicated that l-cyst-ACF had abundant nitrogen-containing and sulfur-containing functional groups. Based on the XPS and EDS analyses, the capture of Pb was attributed to the abundant adsorption sites on the fiber surface.

Simulation study on comprehensive thermal treatment of oil sludge based on Aspen plus.

This article proposed an original comprehensive thermal treatment coupled with gasification and combustion (CGC) of oil sludge (OS), which was designed to produce hydrogen-rich syngas. Based on the experimental results of OS gasification with steam, the combustion characteristics of char from OS gasification were analyzed by thermogravimetric experiments under different heating rates of 10, 20 and 30 °C/min. The combustion process of OS gasification char can be divided into three stages, including water evaporation, volatile combustion and heavy component combustion.

A review of application and development of combustion technology for oil sludge.

Oil sludge is a typical hazardous waste in the petrochemical and electric power industry. It has complex components and special properties, and has serious hazards to humans, plants, water, and soil. Therefore, how to realize the effective disposal of oil sludge has become an urgent issue to be solved worldwide.