Results 101 to 110 of about 3,046 (217)
DNA methylation status of the cell proliferation genes in atherosclerosis
The purpose of this study was to identify the features of methylation status of genes whose products are involved in the cell proliferation in vascular tissues of patients with atherosclerosis.
M. S. Nazarenko +7 more
doaj
ABSTRACT Using survey and discrete choice experiment data, we examined US specialty crop growers' preferences for marketing contract attributes in the context of emerging blockchain‐based technologies and expanding traceability initiatives. Results show that farmers preferred traditional written contracts but might be willing to accept digital ...
Elizabeth Canales +3 more
wiley +1 more source
Automated generative process synthesis via transformer‐based dual‐loop simulation and optimization
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 +4 more
wiley +1 more source
GraphRAG for engineering diagrams: ChatP&ID enables LLM interaction with P&IDs
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 +1 more
wiley +1 more source
Factorization machine with iterative quantum reverse annealing (FMIRA) leverages quantum reverse annealing to perform batch black‐box optimization. Factorization machine with quantum annealing (FMQA) is a widely used python package for solving black‐box optimization problems using D‐Wave quantum annealers.
Andrejs Tučs, Ryo Tamura, Koji Tsuda
wiley +1 more source
Autonomous AI‐Driven Design for Skin Product Formulations
This review presents a comprehensive closed‐loop framework for autonomous skin product formulation design. By integrating artificial intelligence‐driven experiment selection with automated multi‐tiered assays, the approach shifts development from trial‐and‐error to intelligent optimisation.
Yu Zhang +5 more
wiley +1 more source
Overcoming the Nyquist Limit in Molecular Hyperspectral Imaging by Reinforcement Learning
Explorative spectral acquisition guide automatically selects informative spectral bands to optimize downstream tasks, outperforming full‐spectrum acquisition. The selected hyperspectral data are used for tasks such as unmixing and segmentation. BandOptiNet encodes selection states and outputs optimal bands to guide spectral acquisition. Recent advances
Xiaobin Tang +4 more
wiley +1 more source
Materials informatics and autonomous experimentation are transforming the discovery of organic molecular crystals. This review presents an integrated molecule–crystal–function–optimization workflow combining machine learning, crystal structure prediction, and Bayesian optimization with robotic platforms.
Takuya Taniguchi +2 more
wiley +1 more source
Human‐in‐the‐Loop Swarms: A Bionic Swarm Approach to Real‐World Soil Mapping
This article introduces the “Bionic Swarm,” a novel system that lowers the barriers to real‐world swarm validation by abstracting difficult hardware tasks to app‐guided human agents. We demonstrate the system's utility through the experimental validation of a geotechnical soil‐mapping swarm algorithm and show superior performance to baseline approaches
Petras Swissler +5 more
wiley +1 more source

