Exploring Biomarkers and Biosensors for Motion Sickness: Innovative Approaches to Diagnostic Challenges Motion sickness (MS) is a common syndrome experienced by humans, triggered by unnatural motions such as those encountered during transportation or virtual reality (VR). It manifests through symptoms like headaches, nausea, vomiting, cold sweats, ...
Choline Phosphate-Based Antigen Capture Strategy Boosts In Situ Tumor Vaccine Research: A Novel Immunotherapy Approach In the field of cancer immunotherapy, in situ tumor vaccines have garnered significant attention for their ability to harness a patient’s immune system to target tumors. However, challenges remain in their clinical application. To ...
Academic Report on “Bioprinting Perfusable and Vascularized Skeletal Muscle Flaps for the Treatment of Volumetric Muscle Loss” Background Muscle tissues constitute a significant portion of human cellular mass and are a complex, highly vascularized, and dynamic tissue. However, traumatic or surgical Volumetric Muscle Loss (VML)—defined as the loss o...
Mitochondria-Targeting Bimetallic Cluster Nanozymes Alleviate Neuropathic Pain by Scavenging ROS and Reducing Inflammation Background Introduction Neuropathic pain is a complex and multifaceted public health issue, with its high incidence and significant negative impact on patients’ quality of life making it a critical area of medical research. Cur...
Can Large Language Models Tackle Misinformation? — In-Depth Research on LLMs In today’s digital era of rapid information dissemination, the spread of misinformation and fake news has become a significant societal challenge. The widespread use of the internet and social media has dramatically lowered the barriers to information sharing, enabling any...
In-Depth Exploration of Sector-Based Pairs Trading Strategies and Innovative Pair Selection Techniques Background and Research Objectives Pairs Trading Strategy (PTS) is a widely used financial arbitrage strategy that leverages the relative performance of two highly correlated stocks to profit from temporary price deviations. The core concept of tr...
A Research Report on a New Framework for Solving Migrant Resettlement Using Multiobjective Evolutionary Optimization Against the backdrop of accelerated globalization and evolving socio-economic conditions, migration has become an undeniable global trend. From the perspective of humanitarian relief or the sustainable development of a globalized eco...
Multi-agent Cooperative Navigation in Hybrid Environments: A New Reinforcement Learning Approach Based on Relational Graph Learning Mobile robotics is witnessing a surge in applications, fueled by advancements in artificial intelligence, with navigation capabilities being one of the core focus areas of research. Traditional navigation methods often...
Intrusion Detection Approach for Industrial Internet of Things Traffic Using Deep Recurrent Reinforcement Learning and Federated Learning Academic Background The rapid development of the Industrial Internet of Things (IIoT) has profoundly transformed intelligent industrial systems, enabling data exchange, remote control, and smart decision-making b...
Nonlinear Fixed-Time Reinforcement Learning Optimized Control for Intelligent Ship Autopilots In recent years, intelligent autopilot technology has gradually become a research hotspot in the field of automation control. For complex nonlinear systems, the design of optimized control strategies, especially the achievement of system stability and perf...