Results 191 to 200 of about 165,816 (266)

Automated generative process synthesis via transformer‐based dual‐loop simulation and optimization

AIChE Journal, EarlyView.
Abstract This study presents a novel framework for automated generative process synthesis, addressing the complexity of simultaneously optimizing discrete topologies and continuous operating variables. To overcome conventional superstructure limitations, we propose a dual‐loop architecture integrating generative transformers with rigorous process ...
Yeong Woo Son, Chan Kim, Ji Hun Pak, Hain Lee, Jong Min Lee   +4 more
wiley   +1 more source

A logic-based knowledge-driven bidirectional multi-attention GRU framework for fear level classification in humans. [PDF]

Sci Rep
Joshva AA, Balasubramanian VK, Murugappan M.   +2 more
europepmc   +1 more source

GraphRAG for engineering diagrams: ChatP&ID enables LLM interaction with P&IDs

AIChE Journal, EarlyView.
Abstract Piping and Instrumentation Diagrams (P&IDs) are central to process engineering workflows, yet extracting information from them remains a tedious and time‐consuming task. This work introduces ChatP&ID, a framework enabling natural‐language interaction with smart P&IDs through Graph Retrieval‐Augmented Generation (GraphRAG), to our knowledge ...
Achmad Anggawirya Alimin, Artur M. Schweidtmann   +1 more
wiley   +1 more source

Towards a neuro-symbolic approach for precision anti-reflux surgery. [PDF]

Updates Surg
Wang Q, Dai Y, Aiolfi A, Manna M, Ricioppo A, Liu X, Pezzi V, Leone N, Bonavina L.   +8 more
europepmc   +1 more source

LLM‐Based Scientific Assistants for Knowledge Extraction: Which Design Choices Matter?

Advanced Intelligent Discovery, EarlyView.
A comprehensive framework for optimizing Large Language Models in domain‐specific applications is introduced. The LLM Playground integrates Prompt Engineering, knowledge augmentation, and advanced reasoning strategies to enable systematic comparison of architectures and base models.
David Exler, Manuel Raimann, Marc Münker, Maxim Rosin, Joaquin E. Urrutia Gómez, Christof M. Niemeyer, Markus Reischl, Luca Rettenberger   +7 more
wiley   +1 more source

Iontronics of nanofluidic conical pores: learning phenomena using voltage pulses.

Nanoscale
Portillo S, Cervera J, Manzanares JA, Bisquert J, Mafe S, Ramirez P.   +5 more
europepmc   +1 more source

Explaining the Origin of Negative Poisson's Ratio in Amorphous Networks With Machine Learning

Advanced Intelligent Discovery, EarlyView.
This review summarizes how machine learning (ML) breaks the “vicious cycle” in designing auxetic amorphous networks. By transitioning from traditional “black‐box” optimization to an interpretable “AI‐Physics” closed‐loop paradigm, ML is shown to not only discover highly optimized structures—such as all‐convex polygon networks—but also unveil hidden ...
Shengyu Lu, Xiangying Shen
wiley   +1 more source

Evaluating reasoning large language models with human-like thinking in ophthalmic question answering. [PDF]

BMJ Open Ophthalmol
Wang Z, Xu C, Wang L, Qiang W, Li Y, Li D, Xu F, Zhang Y, Jiang J, Li Z.   +9 more
europepmc   +1 more source

Autonomous X‐Ray Fluorescence Mapping for Nanoscale Chemical Speciation of Fine Particulate Matter

Advanced Intelligent Discovery, EarlyView.
We present X‐AutoMap, an autonomous X‐ray fluorescence mapping framework that integrates real‐time analysis with rule‐based computer vision to selectively target chemically relevant regions. By avoiding background‐dominated areas, the method reduces acquisition time by fourfold while enabling accurate particle‐level speciation.
Carlos Deleon, Dmitri Gavrilov, Peggy O’Day, Ajith Pattammattel   +3 more
wiley   +1 more source

Reply to Hinpetch Daungsupawong et al. [PDF]

Interdiscip Cardiovasc Thorac Surg
Matsushima S, Matsuhisa H, Okada K, Kawanami O.   +3 more
europepmc   +1 more source