Ethical Considerations in Emotion Recognition Research by Darlene Barker, Mukesh Kumar Reddy Tippireddy, Ali Farhan, Bilal Ahmed

“…The paper provides practical ethical recommendations for developing affective computing systems that advance the field while maintaining responsible deployment and governance in academic research and industry settings. …”
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EmoTrans attention based emotion recognition using EEG signals and facial analysis with expert validation by Ch Anwar Ul Hassan, Muhammad Ehatisham-ul-Haq, Fiza Murtaza, Aman Ullah Yasin, Syed Sajid Ullah

“…Abstract Emotion recognition via EEG signals and facial analysis becomes one of the key aspects of human–computer interaction and affective computing, enabling scientists to gain insight into the behavior of humans. …”
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MB-MSTFNet: A Multi-Band Spatio-Temporal Attention Network for EEG Sensor-Based Emotion Recognition by Cheng Fang, Sitong Liu, Bing Gao

“…This sensor-driven framework advances affective computing by integrating spatio-temporal dynamics and multi-band interactions of EEG sensor signals, enabling efficient real-time emotion recognition.…”
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ArabSis: Arabic Corpus Sentiment Analysis by Ziad Doughan, Sari Itani, Samir Itani

“…Despite rapid progress in natural language processing (NLP), the development of specialized resources for niche domains—critical for specialized applications like affective computing and emotionally intelligent AI—remains a persistent challenge. …”
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A Resource-Efficient Multi-Entropy Fusion Method and Its Application for EEG-Based Emotion Recognition by Jiawen Li, Guanyuan Feng, Chen Ling, Ximing Ren, Xin Liu, Shuang Zhang, Leijun Wang, Yanmei Chen, Xianxian Zeng, Rongjun Chen

“…Emotion recognition is an advanced technology for understanding human behavior and psychological states, with extensive applications for mental health monitoring, human–computer interaction, and affective computing. Based on electroencephalography (EEG), the biomedical signals naturally generated by the brain, this work proposes a resource-efficient multi-entropy fusion method for classifying emotional states. …”
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Emotional content and semantic structure of dialogues are associated with Interpersonal Neural Synchrony in the Prefrontal Cortex by Alessandro Carollo, Massimo Stella, Mengyu Lim, Andrea Bizzego, Gianluca Esposito

“…This study addresses this research gap by bridging recent advances in cognitive neuroscience data, affective computing, and cognitive data science frameworks. …”
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SynAdult: Multimodal Synthetic Adult Dataset Generation via Diffusion Models and Neuromorphic Event Simulation for Critical Biometric Applications by Muhammad Ali Farooq, Paul Kielty, Wang Yao, Peter Corcoran

“…This modality enhances geometric understanding and supports applications in AR/VR and affective computing. To validate the robustness and utility of the generated dataset, we perform a comprehensive evaluation using Kernel Inception Distance (KID), BRISQUE, CLIP score, and identity similarity metrics. …”
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Attention-Driven Emotion Recognition in EEG: A Transformer-Based Approach With Cross-Dataset Fine-Tuning by Ghulam Ghous, Shaheryar Najam, Mohammed Alshehri, Abdulmonem Alshahrani, Yahya AlQahtani, Ahmad Jalal, Hui Liu

“…This work advances emotion recognition systems by addressing challenges in EEG signal processing, feature extraction, and model generalization, positioning it as a promising tool for applications in healthcare, affective computing, and emotional state analysis.…”
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Predicting emotional responses in interactive art using Random Forests: a model grounded in enactive aesthetics by Xiaowei Chen, Xiaowei Chen, Zainuddin Ibrahim, Azlan Abdul Aziz

“…This study contributes to the evolving convergence of affective computing, human-computer interaction (HCI), and empirical aesthetics. …”
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Disruption-induced changes in syntrophic propionate and acetate oxidation: flocculation, cell proximity, and microbial activity by Nils Weng, Hossein Nadali Najafabadi, Maria Westerholm

“…Results Stirring significantly delayed the initiation of propionate degradation in one culture and completely inhibited it in the other two parallel cultures, whereas acetate degradation was less affected. Computational fluid dynamics modelling revealed that stirring generated higher shear rates (~ 20 s−1) and uniform cell distribution, while shaking led to lower shear rates and cell accumulation at the bottom of the culture bottle. …”
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APPLICATION OF ANTHROPOMORPHIC DESIGN IN CHATBOT DIGITAL AVATARS: A COMPARATIVE ANALYSIS OF ABSTRACT AND FIGURATIVE REPRESENTATIONS by Ma Ning, Ruslana Viktorivna Khynevych

“…The findings suggest potential avenues for future research in affective computing and human-computer interaction. Methodology. …”
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