Results 111 to 120 of about 72,058 (269)

Aggregation‐Enhanced Asymmetric Heptamethine Cyanine Nanoplatform for Imaging‐Guided Synergistic Phototherapy and Ferroptosis

Aggregate, EarlyView.
An asymmetric heptamethine cyanine photosensitizer, Cyp‐TPE, is designed to break molecular symmetry and form ordered nanoaggregates, resulting in ultrahigh ROS generation and synergistic photothermal/photodynamic activity. It further triggers ferroptosis and lysosomal dysfunction, providing a potent aggregate‐based theranostic platform for imaging ...
Mengyuan Cui, Wenqing Li, Yanli Chen, Huijia Liu, Li Liu, Min Ji, Peng Wang   +6 more
wiley   +1 more source

Carbon Dots: Small Materials With Big Impacts on Optoelectronic Devices

Aggregate, EarlyView.
This review systematically summarizes the roles of carbon dots in optoelectronic devices, emphasizing their electro‐induced effects, and structural optimization strategies. It further analyzes performance limitations and prospects for the preparation and application of high‐quality carbon dots.
Boyang Wang, Junwei Wang, Siyu Lu
wiley   +1 more source

CrossMatAgent: AI‐Assisted Design of Manufacturable Metamaterial Patterns via Multi‐Agent Generative Framework

Advanced Intelligent Discovery, EarlyView.
CrossMatAgent is a multi‐agent framework that combines large language models and diffusion‐based generative AI to automate metamaterial design. By coordinating task‐specific agents—such as describer, architect, and builder—it transforms user‐provided image prompts into high‐fidelity, printable lattice patterns.
Jie Tian, Martin Taylor Sobczak, Dhanush Patil, Jixin Hou, Lin Pang, Arunachalam Ramanathan, Libin Yang, Xianyan Chen, Yuval Golan, Xiaoming Zhai, Hongyue Sun, Kenan Song, Xianqiao Wang   +12 more
wiley   +1 more source

Sampling Strategy: An Overlooked Factor Affecting Artificial Intelligence Prediction Accuracy of Peptides’ Physicochemical Properties

Advanced Intelligent Discovery, EarlyView.
This study reveals that sampling strategy (i.e., sampling size and approach) is a foundational prerequisite for building accurate and generalizable AI models in peptide discovery. Reaching a threshold of 7.5% of the total tetrapeptide sequence space was essential to ensure reliable predictions.
Meiru Yan, Ankeer Abuduhebaier, Haojin Zhou, Jiaqi Wang   +3 more
wiley   +1 more source

A Review on Recent Trends of Bioinspired Soft Robotics: Actuators, Control Methods, Materials Selection, Sensors, Challenges, and Future Prospects

Advanced Intelligent Systems, Volume 7, Issue 3, March 2025.
This article reviews the current state of bioinspired soft robotics. The article discusses soft actuators, soft sensors, materials selection, and control methods used in bioinspired soft robotics. It also highlights the challenges and future prospects of this field.
Abhirup Sarker, Tamzid Ul Islam, Md. Robiul Islam   +2 more
wiley   +1 more source

Forecasting Research Trends Using Knowledge Graphs and Large Language Models

Advanced Intelligent Systems, EarlyView.
When research trends can be anticipated, academia and industry are able to allocate limited resources more effectively and accelerate innovation. By constructing knowledge graphs using large language models, this study analyzes the time evolution of nuclear materials research concepts and suggests a data‐driven approach of forecasting research trends ...
Maciej Tomczak, Yang Jeong Park, Chia‐Wei Hsu, Payden Brown, Dario Massa, Piotr Sankowski, Ju Li, Stefanos Papanikolaou   +7 more
wiley   +1 more source

Evolution for our time: a theory of legal memetics [PDF]

The purpose of this paper is to explore the significance for legal thought of recent developments in evolutionary theory which are associated with the notion of 'memetics'.
Simon Deakin
core  

BiT‐HyMLPKANClassifier: A Hybrid Deep Learning Framework for Human Peripheral Blood Cell Classification Using Big Transfer Models and Kolmogorov–Arnold Networks

Advanced Intelligent Systems, EarlyView.
This study presents BiT‐HyMLPKANClassifier, a novel hybrid deep learning framework for automated human peripheral blood cell classification. Model combines Big Transfer models with multilayer perceptron and efficient Kolmogorov–Arnold Network architectures, achieving over 97% accuracy.
Ömer Miraç KÖKÇAM, Ferhat UÇAR
wiley   +1 more source

Explicable prioritization of genetic variants by integration of rule-based and machine learning algorithms for diagnosis of rare Mendelian disorders

Human Genomics
Background In the process of finding the causative variant of rare diseases, accurate assessment and prioritization of genetic variants is essential. Previous variant prioritization tools mainly depend on the in-silico prediction of the pathogenicity of ...
Ho Heon Kim, Dong-Wook Kim, Junwoo Woo, Kyoungyeul Lee   +3 more
doaj   +1 more source

Elastic Fast Marching Learning from Demonstration

Advanced Intelligent Systems, EarlyView.
This article presents Elastic Fast Marching Learning (EFML), a novel approach for learning from demonstration that combines velocity‐based planning with elastic optimization. EFML enables smooth, precise, and adaptable robot trajectories in both position and orientation spaces.
Adrian Prados, Brendan Hertel, Ramon Barber, Reza Azadeh   +3 more
wiley   +1 more source