Cognitive Diagnosis (CD) plays a crucial role in personalized learning by evaluating students' mastery of various concepts. However, current CD models face a significant challenge—the "student-concept sparsity barrier." This occurs when students have limited interactions with certain concepts.

The privacy protection issue of multi-domain traffic engineering has always been a hot topic. Consider that domains from different service providers may not be willing to expose the topology information within their own domains for security and privacy reasons.

Researchers from Tianjin University have introduced the Emergency Medical Procedures 3D Dataset (EMP3D), a pioneering resource that captures the intricate movements of medical professionals during life-saving interventions with unprecedented precision. Published on 15 November 2025 in Frontiers of Computer Science co-published by Higher Education Press and Springer Nature, this dataset leverages synchronized multi-camera systems, advanced AI algorithms, and rigorous human validation to create the first 3D digital blueprint of emergency medical workflows. The innovation holds the potential to fundamentally transform emergency medical training and enhance robotic support in healthcare settings.

Multimorbidity is defined as the concurrent presence of two or more age-associated diseases within an individual, which often results in detrimental health outcomes. Immunosenescence, the gradual deterioration of the immune system associated with aging, constitutes a significant risk factor for the development of these conditions. Moreover, certain diseases may exacerbate immunosenescence, thereby establishing a self-perpetuating pathological cycle. This bidirectional interaction forms a complex pathological network that presents considerable challenges for both the investigation and prevention of multimorbidity. In light of these challenges, it is pertinent to consider whether a paradigm shift in research and intervention strategies—centered on protective factors or anti-aging mechanisms—could facilitate substantial advancements in this field. On October 13, 2025, a research team led by Associate Researcher Xiaolin Ni and Researcher Erping Long from the Institute of Basic Medical Sciences at the Chinese Academy of Medical Sciences published an article entitled "Centenarians: a model of immune resilience against multimorbidity" in the journal Life Medicine. By examining the mechanistic interplay between immunosenescence and multimorbidity and referencing the unique immune profiles of centenarians, the authors proposed a novel systemic therapeutic paradigm termed IMET. This approach focuses on the modulation and restoration of the immune microenvironment, thereby offering innovative research directions and intervention strategies aimed at mitigating the burden of aging-related multimorbidity.

Researchers from The University of Osaka have developed a unique approach to delivering laser light through photonic circuitry for controlling the states of trapped ions, representing a potential novel method for overcoming challenges in quantum computing technology.

Researchers from Kumamoto University have developed a new peptide-based technology that enables insulin—normally injected—to be taken orally while still powerfully lowering blood sugar. Their breakthrough, demonstrated in diabetic mice, could pave the way for needle-free insulin treatments that are safer, simpler, and more comfortable for patients.

Adversarial examples—images subtly altered to mislead AI systems—are used to test the reliability of deep neural networks. However, existing methods often produce images with unnatural noise that is easy to detect. In a recent study, researchers from Japan developed “IFAP,” a new framework that aligns adversarial noise with the spectral characteristics of the original image. Extensive tests show that IFAP generates more natural-looking perturbations while remaining highly effective and resistant to common defenses.