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Review Open access Oct 2026

Human Factors in Brain–Computer Interfaces: Boundaries, Key Issues, and Methodological Approaches

Centered on the collaborative adaptation across neural, cognitive, and system levels, Human Factors Engineering for BCIs represents a deepening of the human-centered design philosophy and extends the research boundaries of human factors engineering.

Liu Yan, Tian-Wen Li, Lei Zhao et al. · 0 citations
Open access Aug 2026

Effects of virtual nature scenes and imagery dialogue intervention on academic anxiety in college students

Background Academic anxiety is increasingly prevalent among college students and can negatively affect both academic performance and mental well-being. Virtual reality-based nature exposure has emerged as a promising approach for emotional regulation. This study examined whether integrating imagery dialogue with virtua...

Hao Fang, Ying Ran, Yi-Fan Xu et al. · 0 citations
Open access Oct 2026

Aesthetic preference and gaze-based visual attention in atlas-cover design: Evidence from an eye-tracking study

Atlas covers communicate thematic identity and shape first impressions, yet their design remains largely guided by heuristic experience rather than empirical evidence. Although eye-tracking research has examined map use, packaging design, and visual interfaces, little is known about whether atlas-cover variables that e...

Pi-Zhao Hu, Hao Fang, Yu-Hui Gui et al. · 0 citations
Open access Aug 2026

Harnessing large language models in virtual CBT for university students’ academic anxiety: a preliminary randomized trial

Academic anxiety is a common mental health problem among university students. It is often associated with reduced learning efficiency and an increased risk of depression. Cognitive behavioral therapy (CBT) is supported by an established evidence base, but its use in university settings is still limited by factors such...

Hao Fang, Zi-Xi Huang, Ling-Xin Zhu et al. · 0 citations
Open access Sep 2026

Explainable image aesthetic assessment via semantic segmentation-guided cross-attention fusion

Most existing image aesthetic assessment methods rely on global representations or simple aggregation of local features. This makes it difficult to model semantic region information and provide region-level explanations. To address this issue, we propose a Semantic Segmentation-Guided Cross-Attention Fusion (SSG-CAF) m...

Hao Fang, Cheng-Cai Cao, Zi-Xi Huang et al. · 0 citations
#reinforcement learning Open access Sep 2026

Off-Policy Inverse Q-Learning Algorithm with Unobservable States

This paper investigates the output-feedback inverse reinforcement learning (IRL) problem and proposes a data-driven output-feedback off-policy inverse Q-learning algorithm that relies solely on input–output trajectory data from an expert system to address the problem of an unknown performance index in discrete-time lin...

Zheng-Lin Li, Li-Qi Zhang, Xi-Sheng Dai et al. · 0 citations

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