Event-Triggered Fuzzy Adaptive Stabilization of Parabolic PDE–ODE Systems

Scientific Report: On “Event-Triggered Fuzzy Adaptive Stabilization of Parabolic PDE–ODE Systems” Research Background and Significance In modern engineering systems, such as flexible manipulators, heat transfer devices, and reactor controllers, many complex systems must be modeled using partial differential equations (PDEs). Due to their unique rea...

Optimal Control of Stochastic Markovian Jump Systems with Wiener and Poisson Noises: Two Reinforcement Learning Approaches

Optimal Control of Stochastic Markovian Jump Systems with Wiener and Poisson Noises: Two Reinforcement Learning Approaches Academic Context In modern control theory, optimal control is a crucial research field, aiming to design an optimal control strategy under various constraints for dynamic systems to minimize a given cost function. For stochasti...

Toward Optimal Disease Surveillance with Graph-Based Active Learning

Toward Optimal Disease Surveillance with Graph-Based Active Learning Academic Background With the acceleration of globalization, the speed and scope of infectious disease transmission have significantly increased. How to effectively monitor and control the spread of infectious diseases has become a critical issue in public health. Traditional disea...

Basis Restricted Elastic Shape Analysis Framework for Surfaces

# Basis Restricted Elastic Shape Analysis on the Space of Unregistered Surfaces ## Introduction Analyzing three-dimensional (3D) surfaces has become increasingly important in computer vision, driven by the emergence of high-accuracy 3D scanning devices. These devices have significantly increased the availability of 3D data, enabling applications in...

An Adaptive and Robust Method for Multi-Trait Analysis of Genome-Wide Association Studies Using Summary Statistics

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...

Bayesian Tensor Modeling for Image-Based Classification of Alzheimer's Disease

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...

Simulation Study Suggests Masks Can Become More Effective When Fewer People Wear Them

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...

Modeling of Glioma Growth with Mass Effect by Longitudinal Magnetic Resonance Imaging

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 Dark Matter Haloscope

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 ...

Bridging Stories and Science: An fNIRS-based Hyperscanning Investigation into Child Learning in STEM

Bridging Stories and Science: An fNIRS-based Hyperscanning Investigation into Child Learning in STEM

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 ...