Using Generative Cellular Automata to Study the Chiral Morphogenesis of Gold Background and Objectives Chirality is ubiquitous in nature and can be transferred and amplified between systems through specific molecular interactions and multi-scale couplings. However, the mechanisms of chiral formation and the critical steps during the growth process ...

Accelerating the Discovery of Ionizable Lipids for mRNA Delivery using Machine Learning and Combinatorial Chemistry Research Background To fully realize the potential of mRNA therapies, it is essential to expand the toolkit of lipid nanoparticles (LNPs). However, a key bottleneck in LNP development is identifying new ionizable lipids. Previous stud...

Study on Enhanced Electromechanical Response of Antiferroelectric Thin Films Based on Clamping Effect Background Antiferroelectric thin film materials have garnered significant attention for their potential applications in micro/nano electromechanical systems. These systems require materials with high electromechanical responses, capable of generat...

Optimal Working Point of Heavy Hole Spin Qubit in Germanium and Its High Anisotropic Noise Sensitivity Background and Motivation The development of quantum computers holds great promise for solving complex problems. However, building a fault-tolerant quantum computer requires the integration of a large number of highly coherent qubits. Spin qubits,...

Research Progress on Programmable Topological Photonic Chips Research Background In recent years, topological insulators (TI) have garnered significant attention in the physics community due to their rich physical mechanisms and the potential applications of topological boundary modes, leading to rapid development in this field. Since the discovery...

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...

Invisible and Robust Protection Method for Content Generated by Deep Neural Networks Academic Background In recent years, with the revolutionary development and widespread application of deep learning models in engineering applications, phenomenon-level applications such as ChatGPT and DALL⋅E 2 have emerged, profoundly impacting people’s daily live...

Academic Report Background A Knowledge Graph (KG) is structured data that records information about entities and relationships, widely used in question-answering systems, information retrieval, machine reading, and other fields. Knowledge Graph Embedding (KGE) technology maps entities and relationships in the graph into a low-dimensional dense vect...

In recent years, applications such as privacy protection and large-scale data transmission have posed significant challenges to the inaccessibility of data. Researchers have proposed Data-Free Knowledge Distillation (DFKD) methods to address these issues. Knowledge Distillation (KD) is a method for training a lightweight model (student model) to le...

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...