Adaptive Robust Method for Multi-trait Genome-wide Association Studies Abstract: Genome-wide association studies (GWAS) over the past decade have identified thousands of genetic variants associated with human traits or diseases. However, the heritability of many traits remains largely unexplained. Traditional single-trait analysis methods are overl...
Image Classification Based on Bayesian Tensor Modeling for Alzheimer’s Disease Introduction Neuroimaging research is a crucial component of contemporary neuroscience, significantly enhancing our understanding of brain structure and function. Through these non-invasive visualization techniques, researchers can more accurately predict the risk of cer...
The Relationship Between Mask Effectiveness and Population Coverage Rates Background and Research Motivation During the COVID-19 pandemic, non-pharmaceutical interventions (NPIs) such as social distancing, mask-wearing, and test-trace-isolate strategies were widely applied to control the spread of the virus. Despite a large body of empirical resear...
Study of Mathematical Models for Tumor Growth – Exploring Glioma Extension Using Longitudinal Magnetic Resonance Imaging A recent article published in the IEEE Transactions on Biomedical Engineering presents a systematic study on the mathematical modeling and growth patterns of gliomas (glioma). This research was conducted by Birkan Tunç, David A. ...
Long-baseline Quantum Sensor Network as a Dark Matter Haloscope Academic Background Ultralight dark photons, as one of the significant candidates for dark matter, have attracted extensive theoretical and experimental attention. According to the kinetic mixing mechanism, when dark photons couple with standard model photons, coherent electromagnetic ...
Academic News Report In Volume 285 of “Neuroimage” (2024), there is a published article entitled “Bridging Stories and Science: An fNIRS-Based Hyperscanning Investigation into Child Learning in STEM”. This article was co-authored by Juan Zhang and others, with the research team hailing from the Faculty of Education, Faculty of Health Sciences, and ...
Academic Report: Advanced Optimal Tracking Integrating Neural Critic Technique for Asymmetric Constrained Zero-Sum Games Background and Research Problem In the field of modern control, game theory is the mathematical model that studies the competition and cooperation between intelligent decision-makers, involving an interaction decision problem wit...
Background and Research Objectives Reinforcement Learning (RL) has recently become a dynamic and transformative field within artificial intelligence, aiming to maximize cumulative rewards through the interaction between agents and the environment. However, the application of RL faces challenges in optimizing the Bellman Error. This error is particu...
With the continuous advancement of data acquisition technology, obtaining large amounts of high-dimensional data containing multiple features has become very easy, such as images and vision data. However, traditional machine learning methods, especially those based on vectors and matrices, face challenges such as the curse of dimensionality, increa...
Fast Synchronization Control and Application for Encryption-Decryption of Coupled Neural Networks With Intermittent Random Disturbance I. Background and Research Motivation In recent years, neural networks have been widely applied in various fields such as data classification, image recognition, and combinatorial optimization problems. Regarding th...