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In the context of China's ongoing industrial revolution and technological transformation, there is a growing demand for advanced energy management solutions and the increasing role of artificial intelligence in various industries. This paper aims to explore how artificial intelligence (AI) and Energy Storage Technology (EST) interact and co-evolve. Utilizing a full-sample Granger causality test, we identified significant interactions between AI and EST.

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Limited research has examined the possible synergistic interrelationships between serious bacterial infections (SBIs) of the heart (i.e., endocarditis), bone, spine, brain, or joints (e.

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EEG microstate analysis and machine learning classification in patients with obsessive-compulsive disorder.

J Psychiatr Res

January 2025

Department of Psychiatry, National Clinical Research Center for Mental Disorders, and National Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, 410011, Hunan, China. Electronic address:

Background: Microstate characterization of electroencephalogram (EEG) is a data-driven approach to explore the functional changes and interrelationships of multiple brain networks on a millisecond scale. This study aimed to explore the pathological changes of whole-brain functional networks in patients with obsessive-compulsive disorders (OCD) through microstate analysis and further to explore its potential value as an auxiliary diagnostic index.

Methods: Forty-eight OCD patients (33 with more than moderate anxiety symptoms, 15 with mild anxiety symptoms) and 52 healthy controls (HCs) were recruited.

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Aims: Adolescence is a critical developmental phase during which young people are vulnerable to the experiences of mental ill-health and social exclusion (consisting of various domains including education and employment, housing, finances and social supports and relationships). The aims of this study were to (i) obtain an understanding of the relationships between social exclusion, mental health and wellbeing of young people; and (ii) identify potentially modifiable targets, or population groups that require greater or targeted supports.

Methods: Data were obtained from the Mission Australia 2022 , Australia's largest annual population-wide survey of young people aged 15-19 years ( = 18,800).

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Background: Adverse childhood experiences (ACEs) are a major risk factor for mental disorders in children. Parenting interventions can mitigate the impact of family-level ACEs and subsequently improve young people's mental health. However, a substantial research-to-practice gap hinders access to, and uptake of, available interventions.

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