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Applications of artificial intelligence in life sciences
No full textArtificial intelligence (AI) encompasses the science and engineering behind creating intelligent machines capable of tasks that typically rely on human intelligence, such as learning, reasoning, decision-making, and problem-solving. By analyzing vast amounts of data, identifying patterns, and making predictions that were once impossible, AI has rapidly advanced in recent years. This progress owes much to the availability of extensive data, powerful computing devices, and innovative algorithms. Life sciences explore the study of living organisms and their interactions with the environment. These disciplines seek to unravel the mechanisms of life, enhance human health, and address global challenges such as food security. In this review we investigate the contributions of AI to various domains within life sciences, including drug discovery, genomics, marine biology, and education. Additionally, we address the challenges related to integrating AI into life sciences applications. Furthermore, we reflect on the ethical and social implications of AI deployment, emphasizing the need for responsible and transparent utilization of this powerful technology
Reimagining the Future of Teaching & Learning in the Age of AI (23 May 2025)
No full textH.E. Dr May Laith Al Taee delivers her opening remarks
Teaching high school students about the role of epigenetics in diseases
No full textEpigenetics shows how environmental factors and life experiences alter gene activity without changing the gene sequences. This review examines key epigenetic mechanisms such as DNA methylation, histone modifications, microRNAs, and long non-coding RNAs, and their roles in gene regulation. It also highlights the impact of maternal diet, stress, and toxin exposure on epigenetic marks. The paper discusses the role of epigenetics in diseases such as cancer and diabetes, presenting new avenues for diagnosis and treatment. Ethical, social, and legal challenges, including informed consent, discrimination, distributive justice, and transgenerational equity, are also explored. Additionally, the review suggests innovative teaching strategies for epigenetics, including interactive videos, simulations, storytelling, and case studies, to enhance student engagement. Ultimately, understanding epigenetics empowers informed health choices and promotes a healthier world by integrating these insights responsibly for the benefit of current and future generations
Reimagining the Future of Teaching & Learning in the Age of AI (23 May 2025)
No full textAn attendee poses his question to the panel
Intelligent technology for educational applications: Second international conference
No full textThis book constitutes the refereed proceedings of the 2nd International Conference on Intelligent Technology for Educational Applications, ITEA 2025, held in Bangkok, Thailand, during May19–21, 2025.
The 32 full papers included in this book were carefully reviewed and selected from 88 submissions. The papers were organized in topical sections as follows: AI-Driven Personalized Learning & Adaptive Systems; Intelligent Tools for Language Learning & Translation; Data Analytics & Automation in Educational Management; Immersive Technologies in Education; Innovative Pedagogical Approaches & Multimedia Integration
Reimagining the Future of Teaching & Learning in the Age of AI (23 May 2025)
No full textAttendees gather before the symposium
EEG-based functional connectivity patterns during boredom in an educational context
No full textThe open access publication is available at https://doi.org/10.1038/s41598-025-19245-7Boredom is a common yet understudied emotional state that can adversely impact cognitive performance, motivation, and mental well-being. Gaining insight into its neural basis is crucial for developing strategies to manage or reduce its impact across various settings, including education contexts. The present study investigated brain functional connectivity during boredom in an educational context using electroencephalography (EEG). It was hypothesized that the brain exhibits distinct connections during the experience of boredom. Eighty-four healthy adults (mean age = 26.90 ± 5.29 years) were asked to watch two educational videos designed to induce boredom or neutral states while their EEG signals were captured. Functional connectivity matrices were constructed using coherence in traditional EEG frequency bands. Clustering coefficient, characteristic path length, global efficiency, local efficiency, and node strength were calculated to compare scalp-level network characteristics between boredom and neutral states. The results showed significant differences in functional connectivity in the alpha, beta, and gamma bands. Boredom was characterized as having significantly higher and lower in the alpha, beta, and gamma bands, relative to the neutral condition. Gamma band and were also found to be higher during boredom. The study findings suggest that boredom is associated with distinct patterns of brain functional connectivity, potentially reflecting increased internal processing. The study findings contribute to the broader field of affective neuroscience by highlighting how boredom can influence functional brain network activity in educational contexts.OER 14/22 Y